User:ThomasYehYeh/沙盒:修订间差异
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[[File:20210626 Variwide chart of greenhouse gas emissions per capita by country.svg|thumb|upright=1.5 |於2021年發表的全球前15大溫室氣體排放國資料,縱軸表示排放量,橫軸表示人均排放量。<ref name=GlobalCarbonAtlas_Territorial_Mt{{CO2}}>● {{cite web |title=Territorial (Mt{{CO2}}) |url=http://www.globalcarbonatlas.org/en/CO2-emissions |website=GlobalCarbonAtlas.org |access-date= 2021-12-30 }} (choose "Chart view"; use download link) <br />● Data for 2020 is also presented in {{cite news |last1=Popovich |first1=Nadja |last2=Plumer |first2=Brad |title=Who Has The Most Historical Responsibility for Climate Change? |url=https://www.nytimes.com/interactive/2021/11/12/climate/cop26-emissions-compensation.html |work=The New York Times |date=2021-11-12 |archive-url=https://web.archive.org/web/20211229053102/https://www.nytimes.com/interactive/2021/11/12/climate/cop26-emissions-compensation.html |archive-date= 2021-12-29 |url-status=live }}<br />● Source for country populations: {{cite web |title=List of the populations of the world's countries, dependencies, and territories |url=https://www.britannica.com/print/article/2156538 |website=britannica.com |publisher=Encyclopedia Britannica}}</ref>]] |
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人類活動產生的'''溫室氣體排放'''({{lang-en|Greenhouse gas emissions }})導致[[溫室效應]]加劇,造成{{le|氣候變化|Climate change}}。燃燒[[煤]]炭、[[石油]]和[[天然氣]]等[[化石燃料]]產生的[[二氧化碳]] (CO2) 是造成氣候變化最重要的因素之一。全球最大的排放國是[[中國]],接著是[[美國]]。而就人均排放量,美國則排名第一。大型石油和天然氣公司的的產品助長人類的排放。人類活動的排放讓{{le|大氣中的二氧化碳|Carbon dioxide in Earth's atmosphere}}比[[第一次工業革命]]之前的平均水準增加約50%。不同溫室氣體的排放均呈現成長趨勢,但水準各不相同。 2010年代的平均排放量為每年560億噸,高於以前的任何十年期間。<ref name=ipccar6wg3ch2>{{cite journal |title=Chapter 2: Emissions trends and drivers |journal=Ipcc_Ar6_Wgiii |url=https://report.ipcc.ch/ar6wg3/pdf/IPCC_AR6_WGIII_FinalDraft_Chapter02.pdf |year=2022 |access-date=2022-04-04 |archive-date=2022-04-12 |archive-url=https://web.archive.org/web/20220412163517/https://report.ipcc.ch/ar6wg3/pdf/IPCC_AR6_WGIII_FinalDraft_Chapter02.pdf |url-status=dead }}</ref>在1870年至2017年期間,化石燃料和工業的累積排放總量為425±20吉噸碳(GtC,一吉噸為十億噸) (相當於1,539吉噸二氧化碳(GtCO2)),[[土地利用、土地利用改變與林業]](LULUCF)產生的累積排放量為180±60吉噸碳 (相當於660吉噸二氧化碳)。同一期間的累計排放量,來自土地利用變化(例如[[森林砍伐]])約佔31%,煤炭佔32%,石油佔25%,天然氣佔10%。<ref>{{Cite web |title=Global Carbon Project (GCP) |url=https://www.globalcarbonproject.org/carbonbudget/18/highlights.htm |url-status=dead |archive-url=https://web.archive.org/web/20190404014758/https://www.globalcarbonproject.org/carbonbudget/18/highlights.htm |archive-date=2019-04-04 |access-date=2019-05-19 |website=www.globalcarbonproject.org |language=en}}</ref> |
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[[File:Greenhouse-effect-t2.svg|thumb|upright=1.35|溫室氣體會留住來自太陽的熱量,其中三種最重要的是[[二氧化碳]]、[[水蒸氣]]與[[甲烷]]。]] |
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[[File:Physical Drivers of climate change.svg|thumb|upright=1.35|各種溫室氣體與其他會影響{{le|氣候變化|Climate change}}的因素(如[[氣膠]]),及影響程度。 ]] |
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二氧化碳是人類活動產生溫室氣體中最主要者,佔導致全球變暖因素的一半以上。[[甲烷]] (CH4) 排放幾乎具有相同的短期影響。<ref name="ch4-vs-co2" />相較之下,[[一氧化二氮]] (N2O) 和{{le|氟化氣體|Fluorinated gases}} (F-氣體) 的作用較小。 |
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'''溫室氣體'''({{lang-en|Greenhouse gas}})是在如[[地球]]般的[[行星]][[大氣層]]中的[[氣體]],有提高行星表面溫度的作用。這類氣體與其他氣體不同之處在於其會[[吸收 (光學)|吸收]]行星本身發出的[[電磁波譜]],而產生[[溫室效應]]。<ref name="NASACO2" />地球被陽光加熱,導致表面產生[[輻射能]],然後大部分被溫室氣體吸收。如果大氣中沒溫室氣體,地表的平均溫度將會成為約-18°C (0°F),<ref name="NASACO2" />而非目前的平均15°C (59°F)。<ref name="Trenberth2003" /><ref name=":0">Le Treut, H., R. Somerville, U. Cubasch, Y. Ding, C. Mauritzen, A. Mokssit, T. Peterson and M. Prather, 2007: [https://www.ipcc.ch/site/assets/uploads/2018/03/ar4-wg1-chapter1.pdf Chapter 1: Historical Overview of Climate Change]. In: [https://www.ipcc.ch/report/ar4/wg1/ Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change] [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA</ref> |
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[[發電]]、供熱和交通[[運輸]]是主要排放源,約佔排放量的73%。<ref>{{Cite journal |last1=Ritchie |first1=Hannah |author1-link=Hannah Ritchie |last2=Roser |first2=Max |author2-link=Max Roser |last3=Rosado |first3=Pablo |date=2020-05-11 |title={{CO2}} and Greenhouse Gas Emissions |url=https://ourworldindata.org/emissions-by-sector |journal=Our World in Data}}</ref>森林砍伐和土地利用變化也會排放二氧化碳和甲烷。人為甲烷排放的最大來源是[[農業]],緊隨其後的是化石燃料開採時的有意{{le|宣洩排放|gas venting}}和石化產業的{{le|逸散排放|Fugitive emission}}。最大的農業甲烷來源是畜養的[[家畜|牲畜]]。化學肥料是農田土壤排放一氧化二氮的部分原因。同樣的,冷媒中的氟化氣體在人類總排放量中也具有重大的作用。 |
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地球大氣中最豐富的溫室氣體(以平均[[莫耳分率]],由大到小排序)分別為:<ref>{{cite web |date=2016-08-01 |title=Atmospheric Concentration of Greenhouse Gases |url=https://www.epa.gov/sites/default/files/2016-08/documents/print_ghg-concentrations-2016.pdf |url-status=live |archive-url=https://web.archive.org/web/20211019134514/https://www.epa.gov/sites/default/files/2016-08/documents/print_ghg-concentrations-2016.pdf |archive-date= 2021-10-19 |access-date= 2021-09-06 |publisher=[[U.S. Environmental Protection Agency]]}}</ref><ref>{{cite web |author=<!--Not stated--> |date=<!--Not stated--> |title=Inside the Earth's invisible blanket. |url=http://sequestration.org/science/greenhousegases.html |url-status=dead |archive-url=https://web.archive.org/web/20200728231450/http://sequestration.org/science/greenhousegases.html |archive-date= 2020-07-28 |access-date=2021-03-05 |website=sequestration.org |publisher=<!--Not stated--> |quote=}}</ref>[[水蒸氣]]({{chem|H|2|O}})、二氧化碳({{chem|CO|2}})、甲烷({{chem|CH|4|}})、[[一氧化二氮]]({{chem|N|2|O}})、[[臭氧]] ({{chem|O|3|}})、[[氯氟烴|氯氟碳化合物]](CFC和HCFC)、[[氫氟烴|氫氟碳化合物]](HFC)、[[碳氟化合物]]({{chem|CF|4}}、{{chem|C|2|F|6}}等)、 [[六氟化硫]]({{chem|SF|6}})和[[三氟化氮]]({{chem|NF|3}})。水蒸氣是一種強效溫室氣體,但其濃度並非由人類直接造成,<ref name=":3">{{cite web |author=Gavin Schmidt |date=2010-10-01 |title=Taking the Measure of the Greenhouse Effect |url=https://www.giss.nasa.gov/research/briefs/2010_schmidt_05/ |publisher=NASA Goddard Institute for Space Studies - Science Briefs}}</ref>它不是導致{{le|氣候變化|Climate change}}的主要驅動因素,反而是一種[[氣候變化反饋]]。<ref name="h2o">{{cite web |title=NASA Science Mission Directorate article on the water cycle |url=http://nasascience.nasa.gov/earth-science/oceanography/ocean-earth-system/ocean-water-cycle |url-status=dead |archive-url=https://web.archive.org/web/20090117143544/http://nasascience.nasa.gov/earth-science/oceanography/ocean-earth-system/ocean-water-cycle |archive-date=2009-01-17 |access-date=2010-10-16 |publisher=Nasascience.nasa.gov}}</ref>而全球暖化約有四分之三是由二氧化碳所造成,且其可能需要數千年的時間才能被[[碳循環]]完全吸收。<ref>{{cite web |title=Global Greenhouse Gas Emissions Data |date= 2016-01-12 |publisher=United States Environmental Protection Agency |url=https://www.epa.gov/ghgemissions/global-greenhouse-gas-emissions-data}}</ref><ref>{{cite web |title=Climate Change Indicators: Greenhouse Gases |date= 2015-12-16 |publisher=United States Environmental Protection Agency |url=https://www.epa.gov/climate-indicators/greenhouse-gases |quote=Carbon dioxide's lifetime cannot be represented with a single value because the gas is not destroyed over time, but instead moves among different parts of the ocean–atmosphere–land system. Some of the excess carbon dioxide is absorbed quickly (for example, by the ocean surface), but some will remain in the atmosphere for thousands of years, due in part to the very slow process by which carbon is transferred to ocean sediments.}}</ref>剩餘的暖化作用大部分是由甲烷造成,這種氣體在大氣中的平均存在時間為12年。<ref>{{cite web |title=Understanding methane emissions |publisher=International Energy Agency |url=https://www.iea.org/reports/global-methane-tracker-2023/understanding-methane-emissions}}</ref> |
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目前全球的二氧化碳當量排放率為每年人均6.6噸,<ref name=":5">{{Cite web |last=widworld_admin |date=2021-10-20 |title=The World #InequalityReport 2022 presents the most up-to-date & complete data on inequality worldwide |url=https://wir2022.wid.world/chapter-6/ |access-date=2023-07-14 |website=World Inequality Report 2022 |language=fr-FR}}</ref>遠超過根據《[[巴黎協定]]》要在2030年將全球升溫控制在1.5°C(2.7°F)之內(相對於工業化前的水準),人均排放必須控制在2.3噸的目標。<ref name=":7">{{Cite web |title=Carbon inequality in 2030: Per capita consumption emissions and the 1.5C goal – IEEP AISBL |url=https://ieep.eu/publications/carbon-inequality-in-2030-per-capita-consumption-emissions-and-the-1-5c-goal/ |access-date=2023-07-14 |language=en-GB}}</ref><ref name=":8">{{Cite book |last=Gore |first=Tim |date=2021-11-05 |title=Carbon Inequality in 2030: Per capita consumption emissions and the 1.5 °C goal |publisher=Institute for European Environmental Policy |url=http://hdl.handle.net/10546/621305 |doi=10.21201/2021.8274|hdl=10546/621305 |isbn=9781787488274 |s2cid=242037589 }}</ref><ref name=":9">{{Cite web |title=AR6 Climate Change 2022: Mitigation of Climate Change — IPCC |url=https://www.ipcc.ch/report/sixth-assessment-report-working-group-3/ |access-date=2023-07-14}}</ref>[[已開發國家]]的人均排放量通常是[[開發中國家]]平均量的十倍。<ref name="grubb kyoto protocol" /> |
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自[[第一次工業革命]]起(大約於1750年)以來的人類活動已導致[[大氣甲烷|大氣中的甲烷]]濃度增加150%以上,[[二氧化碳]]濃度增加50%以上,<ref>{{cite web |title=Understanding methane emissions |publisher=International Energy Agency |url=https://www.iea.org/reports/global-methane-tracker-2023/understanding-methane-emissions |quote=The concentration of methane in the atmosphere is currently over two-and-a-half times greater than its pre-industrial levels}}</ref><ref name="NOAA2022">{{cite web |title=Carbon dioxide now more than 50% higher than pre-industrial levels |url=https://www.noaa.gov/news-release/carbon-dioxide-now-more-than-50-higher-than-pre-industrial-levels |publisher=National Oceanic and Atmospheric Administration |access-date=2022-08-30 |language=en |date=2022-06-03}}</ref>是過去300多萬年以來前所未見的水平。<ref>{{Cite web|url=https://www.climate.gov/news-features/understanding-climate/climate-change-atmospheric-carbon-dioxide|title=Climate Change: Atmospheric Carbon Dioxide |website=www.climate.gov |access-date=2020-03-02 |archive-date=2013-06-24 |archive-url=https://web.archive.org/web/20130624204311/https://www.climate.gov/news-features/understanding-climate/climate-change-atmospheric-carbon-dioxide |url-status=live}}</ref>人類排放的二氧化碳絕大多數來自燃燒[[化石燃料]](主要是[[煤]]炭、[[石油]]和[[天然氣]]),其他的來源有[[水泥]]製造、[[肥料]]生產以及如[[森林砍伐]]等[[土地利用]]變化。<ref>Canadell, J.G., P.M.S. Monteiro, M.H. Costa, L. Cotrim da Cunha, P.M. Cox, A.V. Eliseev, S. Henson, M. Ishii, S. Jaccard, C. Koven, A. Lohila, P.K. Patra, S. Piao, J. Rogelj, S. Syampungani, S. Zaehle, and K. Zickfeld, 2021: [https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_Chapter05.pdf Chapter 5: Global Carbon and other Biogeochemical Cycles and Feedbacks]. In [https://www.ipcc.ch/report/ar6/wg1/ Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change] [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 673–816, doi:10.1017/9781009157896.007.</ref>{{rp|687}}<ref name="EPA_GHGdata">{{cite web |date= 2016-01-12 |title=Global Greenhouse Gas Emissions Data |url=https://www.epa.gov/ghgemissions/global-greenhouse-gas-emissions-data |url-status=live |archive-url=https://web.archive.org/web/20191205123907/https://www.epa.gov/ghgemissions/global-greenhouse-gas-emissions-data |archive-date= 2019-12-05 |access-date= 2019-12-30 |publisher=[[United States Environmental Protection Agency|U.S. Environmental Protection Agency]] |quote=The burning of coal, natural gas, and oil for electricity and heat is the largest single source of global greenhouse gas emissions.}}</ref><ref>{{cite web |title=AR4 SYR Synthesis Report Summary for Policymakers – 2 Causes of change |url=https://www.ipcc.ch/publications_and_data/ar4/syr/en/spms2.html |url-status=dead |archive-url=https://web.archive.org/web/20180228235005/http://www.ipcc.ch/publications_and_data/ar4/syr/en/spms2.html |archive-date= 2018-02-28 |access-date=2015-10-09 |work=ipcc.ch}}</ref>甲烷的排放源有[[農業]]、化石燃料生產、廢棄物及其他來源。<ref>{{cite web |title=Global Methane Tracker 2023 |url=https://www.iea.org/reports/global-methane-tracker-2023 |publisher=International Energy Agency}}</ref> |
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[[碳足跡]](或稱溫室氣體足跡)是種指標,用來比較不同商品或服務的整個[[生命週期]]中溫室氣體排放量。<ref>{{Cite web |title=What is a carbon footprint |url=https://www.conservation.org/stories/what-is-a-carbon-footprint |access-date=2023-05-28 |website=www.conservation.org}}</ref><ref name=":6">IPCC, 2022: [https://www.ipcc.ch/report/ar6/wg3/downloads/report/IPCC_AR6_WGIII_Annex-I.pdf Annex I: Glossary] {{Webarchive|url=https://web.archive.org/web/20230313100106/https://www.ipcc.ch/report/ar6/wg3/downloads/report/IPCC_AR6_WGIII_Annex-I.pdf|date=2023-03-13}} [van Diemen, R., J.B.R. Matthews, V. Möller, J.S. Fuglestvedt, V. Masson-Delmotte, C. Méndez, A. Reisinger, S. Semenov (eds)]. In IPCC, 2022: [https://www.ipcc.ch/report/ar6/wg3/ Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change] {{Webarchive|url=https://web.archive.org/web/20220802125242/https://www.ipcc.ch/report/ar6/wg3/|date= 2022-08-02}} [P.R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA. doi: 10.1017/9781009157926.020</ref>[[碳核算]](或稱溫室氣體核算)是種方法架構,用來衡量和追蹤不同個體排放溫室氣體的數量。<ref name=":3">{{Cite web |title=Carbon Accounting |url=https://corporatefinanceinstitute.com/resources/esg/carbon-accounting/ |access-date=2023-01-06 |website=Corporate Finance Institute |language=en-US}}</ref> |
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根據非營利組織{{le|Berkeley Earth|Berkeley Earth}}提供的數據,由於溫室氣體排放,自前工業化時期(1850至1899年)開始迄今,全球平均地表氣溫已上升超過1.2°C (2.2°F)。如果目前的排放率持續,到2040年至2070年之間的某個時候,地表氣溫上升將會超過2.0°C (3.6°F),這是IPCC所提及的"危險"水準。<ref>{{Cite web|date=2020-12-04|title=Analysis: When might the world exceed 1.5C and 2C of global warming?|url=https://www.carbonbrief.org/analysis-when-might-the-world-exceed-1-5c-and-2c-of-global-warming|access-date=2021-06-17|website=Carbon Brief|language=en|archive-date=2021-06-06|archive-url=https://web.archive.org/web/20210606135004/https://www.carbonbrief.org/analysis-when-might-the-world-exceed-1-5c-and-2c-of-global-warming|url-status=live}}</ref> |
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==溫室效應和全球暖化的相關性== |
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==特性== |
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{{Excerpt|溫室效應|paragraph=1-5|File=No}} |
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[[File:Atmospheric Transmission.svg|right|thumb|upright=1.35|alt=refer to caption and adjacent text|大氣層對不同[[波長]]的[[電磁輻射]]會產生吸收和散射的作用。二氧化碳最大的吸收帶正好位於地面紅外線波段的高峰附近,且會部分阻擋住水的溫度透明窗口,這就是二氧化碳被稱為温室氣體的主因。]] |
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==各種來源概述== |
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溫室氣體具有紅外線活性,表示其可吸收和發射與地球表面、雲層和大氣所發射相同長波段範圍內的紅外線輻射。<ref name="AR6_WGI_AnnexVII">IPCC, 2021: [https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_AnnexVII.pdf Annex VII: Glossary] [Matthews, J.B.R., V. Möller, R. van Diemen, J.S. Fuglestvedt, V. Masson-Delmotte, C. Méndez, S. Semenov, A. Reisinger (eds.)]. In [https://www.ipcc.ch/report/ar6/wg1/ Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change] [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 2215–2256, [[doi:10.1017/9781009157896.022]].</ref>{{rp|2233}} |
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[[File:Global GHG Emissions by gas.png|thumb|2016年全球溫室氣體排放組成。<ref name=":4" />二氧化碳佔絕大部分 (74%) , 次為甲烷 (17%)。]] |
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===相關氣體=== |
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地球上99%的乾燥大氣(但包含水蒸氣)是由[[氮]]({{chem|N|2}}) (78%)和[[氧]]({{chem|O|2}}) (21%)組成。由於這兩種氣體的[[分子]]是[[雙原子分子]],其中電荷分佈不存在不對稱性,<ref name="Archer2011Ch4" />因此幾乎完全不受紅外線[[熱輻射]]的影響,<ref>{{cite journal |last1=Wei |first1=Peng-Sheng |last2=Hsieh |first2=Yin-Chih |last3=Chiu |first3=Hsuan-Han |last4=Yen |first4=Da-Lun |last5=Lee |first5=Chieh |last6=Tsai |first6=Yi-Cheng |last7=Ting |first7=Te-Chuan |date=6 October 2018 |title=Absorption coefficient of carbon dioxide across atmospheric troposphere layer |journal=[[Heliyon]] |volume=4 |issue=10 |pages=e00785 |doi=10.1016/j.heliyon.2018.e00785 |pmid=30302408 |pmc=6174548 |bibcode=2018Heliy...400785W }}</ref>{{le|碰撞誘導吸收和發射|collision-induced absorption and emission|}}中的吸收效果非常小。<ref>{{Cite journal |last1=Höpfner |first1=M. |last2=Milz |first2=M. |last3=Buehler |first3=S. |last4=Orphall |first4=J. |last5=Stiller |first5=G. |date=2012-05-24 |title=The natural greenhouse effect of atmospheric oxygen (O<sub>2</sub>) and nitrogen (N<sub>2</sub>) |journal=Geophysical Research Letters |language=en |volume=39 |issue=L10706 |doi=10.1029/2012GL051409 |bibcode=2012GeoRL..3910706H |s2cid=128823108 |issn=1944-8007}}</ref><ref>{{cite web |title=Which Gases Are Greenhouse Gases? |url=https://www.acs.org/content/acs/en/climatescience/greenhousegases/whichgases.html |access-date=2021-05-31 |publisher=American Chemical Society}}</ref><ref>{{Cite journal |last1=Höpfner |first1=M. |last2=Milz |first2=M. |last3=Buehler |first3=S. |last4=Orphall |first4=J. |last5=Stiller |first5=G. |date= 2012-05-24|title=The natural greenhouse effect of atmospheric oxygen (O<sub>2</sub>) and nitrogen (N<sub>2</sub>) |journal=Geophysical Research Letters |language=en |volume=39 |issue=L10706 |doi=10.1029/2012GL051409 |bibcode=2012GeoRL..3910706H |issn=1944-8007 |s2cid=128823108}}</ref>另外0.9%的大氣成分為[[氬]] (Ar) ,它是[[單原子氣體]],完全不會吸收熱輻射。另一方面,二氧化碳(大氣中佔比0.04%)、甲烷、一氧化二氮,甚至含量較少的{{le|微量氣體|Trace gas}}佔地球大氣的比例不到0.1%,但由於它們的分子含有不同元素的原子,因此電荷分佈呈不對稱性,會有分子振動與電磁輻射相互作用,讓它們具有紅外線活性,因而有導致溫室效應的作用。<ref name="Archer2011Ch4">{{cite book |last1=Archer |first1=David |url=http://forecast.uchicago.edu/chapter4.pdf |title=Global Warming: Understanding the Forecast, Chapter 4: Greenhouse Gases |date=2011 |publisher=Wiley |isbn=978-0470943410 |edition=2 |access-date=2023-06-14}}</ref> |
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{{see also|{{le|大氣中的二氧化碳|Carbon dioxide in Earth's atmosphere}}|大氣甲烷}} |
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主要人為溫室氣體的來源是二氧化碳 、一氧化二氮 、甲烷、三組氟化氣體([[六氟化硫]](SF6)、[[氫氟烴|氫氟碳化合物]](HFC)和[[碳氟化合物]](PFC)。<ref>Dhakal, S., J.C. Minx, F.L. Toth, A. Abdel-Aziz, M.J. Figueroa Meza, K. Hubacek, I.G.C. Jonckheere, Yong-Gun Kim, G.F. Nemet, S. Pachauri, X.C. Tan, T. Wiedmann, 2022: [https://www.ipcc.ch/report/ar6/wg3/downloads/report/IPCC_AR6_WGIII_Chapter02.pdf Chapter 2: Emissions Trends and Drivers]. In IPCC, 2022: [https://www.ipcc.ch/report/ar6/wg3/ Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change] [P.R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA. doi: 10.1017/9781009157926.004</ref>雖然溫室效應在很大程度上是由水蒸氣所驅動,<ref>{{Cite web |date=2023-06-30 |title=Water Vapor |url=https://earthobservatory.nasa.gov/global-maps/MYDAL2_M_SKY_WV |access-date=2023-08-16 |website=earthobservatory.nasa.gov |language=en}}</ref>但人類排放的水蒸氣並不是導致暖化的重要因素。 |
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===輻射強迫=== |
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{{main|輻射強迫}} |
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[[File:Greenhouse gas absorption coefficients.svg|thumb|upright=1.35|主要溫室氣體的[[地球長波輻射]]長波紅外吸收係數。水蒸氣在寬廣的波長範圍内吸收輻射。地球在二氧化碳15微米吸收帶附近會特别强烈釋放熱輻射。水蒸氣的相對重要性隨著[[海拔]]上升而降低。]] |
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雖然氯氟碳化合物(CFC)是溫室氣體,但受到《[[蒙特婁議定書]]》的監管,簽訂議定書的動機是因CFC會導致{{le|臭氧層消耗|Ozone depletion}},而非導致全球暖化。臭氧層消耗對暖化的影響很小,但有時媒體會將此兩種過程混為一談。 來自170多個國家的代表於2016年在[[聯合國環境署]]高峰會上達成一項具有法律約束力的協議 - 在《蒙特婁議定書》的{{le|基加利修正案|Kigali Amendment}}中議定要逐步淘汰HFC。 <ref>{{Cite web |last1=Johnston |first1=Chris |last2=Milman |first2=Oliver |last3=Vidal |first3=John |date=2016-10-15 |title=Climate change: global deal reached to limit use of hydrofluorocarbons |url=https://www.theguardian.com/environment/2016/oct/15/climate-change-environmentalists-hail-deal-to-limit-use-of-hydrofluorocarbons |access-date=2018-08-21 |website=[[The Guardian]] |language=en}}</ref><ref>{{cite news |date= 2016-10-15 |title=Climate change: 'Monumental' deal to cut HFCs, fastest growing greenhouse gases |work=BBC News |url=https://www.bbc.co.uk/news/science-environment-37665529 |access-date=2016-10-15}}</ref><ref>{{cite web |date= 2016-10-15 |title=Nations, Fighting Powerful Refrigerant That Warms Planet, Reach Landmark Deal |url=https://www.nytimes.com/2016/10/15/world/africa/kigali-deal-hfc-air-conditioners.html |access-date=2016-10-15 |work=[[The New York Times]]}}</ref>由於CFC-12有消耗臭氧層的特性,已被淘汰(除某些必要用途外)。<ref>{{citation |last1=Vaara |first1=Miska |title=Use of ozone depleting substances in laboratories |url=http://www.norden.org/en/publications/publications/2003-516/ |page=170 |year=2003 |archive-url=https://web.archive.org/web/20110806001547/http://www.norden.org/en/publications/publications/2003-516/ |url-status=dead |publisher=TemaNord |isbn=978-9289308847 |archive-date= 2011-08-06}}</ref>活性較低的[[鹵烷]]也將於2030年完成淘汰。<ref>[[Montreal Protocol]]</ref> |
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地球吸收一些從太陽而來的輻射能,將其中一些以光的形式反射,並將其餘的以熱輻射的形式反射或輻射回太空。行星的表面溫度取決於輸入和輸出能量之間的平衡。當[[地球能量收支]]發生變化時,表面會變暖或是變冷,導致地球氣候發生各種變化。<ref name="epa ggas">{{cite web |year=2016 |title=Climate Change Indicators in the United States - Greenhouse Gases |url=https://www.epa.gov/climate-indicators/greenhouse-gases |url-status=live |archive-url=https://web.archive.org/web/20160827230238/https://www.epa.gov/climate-indicators/greenhouse-gases |archive-date=2016-08-27 |access-date= 2020-09-05 |publisher=U.S. Environmental Protection Agency (EPA)}}.</ref>輻射強迫是一種以[[瓦特|瓦]]/平方米為單位計算的指標,表徵影響氣候因素外部變化的影響。它的計算方式是由這種外部變化立即引起的大氣層頂部 (top-of-atmosphere,TOA) 能量平衡的差異。所謂正向強迫(例如溫室氣體濃度增加)表示到達大氣層頂部的能量多於離開的,而會累積額外的熱量,而負向強迫(例如[[二氧化硫]]在大氣中形成的硫酸鹽[[氣膠]])會導致冷卻效應。<ref name="AR6_WGI_AnnexVII" />{{rp|2245}}<ref name="epa cforce">{{cite web |year=2016 |title=Climate Change Indicators in the United States - Climate Forcing |url=https://www.epa.gov/climate-indicators/climate-change-indicators-climate-forcing |url-status=live |archive-url=https://web.archive.org/web/20160827223551/https://www.epa.gov/climate-indicators/climate-change-indicators-climate-forcing |archive-date= 2016-08-27 |access-date=2020-09-05 |publisher=U.S. Environmental Protection Agency (EPA)}}[https://www.epa.gov/sites/production/files/2016-08/documents/print_climate-forcing-2016.pdf] {{Webarchive|url=https://web.archive.org/web/20200921073951/https://www.epa.gov/sites/production/files/2016-08/documents/print_climate-forcing-2016.pdf|date= 2020-09-21}}</ref> |
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===人類活動=== |
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[[File:Global climate forcing of the industrial era.png|thumb|300px|從1750年起,人類工業化過程中大氣中溫室氣體(以二氧化碳當量表示)的增長路徑,其中Annual Greenhouse Gas Index (AGGI)為一種指数,用於量化地球大氣中長壽命和充分混合温室氣體產生的直接氣候强迫增長。指數以1990年為基準,1表示當前强迫與1990年的相當,高於1表示强迫增加,低於1表示强迫减少。<ref name="noaa2023">{{cite web |year= 2020 |title= NOAA's Annual Greenhouse Gas Index (An Introduction) |publisher= NOAA |url= http://www.esrl.noaa.gov/gmd/aggi/ |access-date= 2023-11-02}}</ref>]] |
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由化石燃料驅動的工業活動大約從1750年開始顯著增加二氧化碳及其他溫室氣體的排放。[[第二次世界大戰]]結束後,全球人口和經濟活動自1950年左右開始持續擴張,排放量迅速增長。截至2021年,測得的大氣中二氧化碳濃度已比工業化前水準高出近50%。<ref name="noaa2023" /><ref>{{Cite web |last=Fox |first=Alex |title=Atmospheric Carbon Dioxide Reaches New High Despite Pandemic Emissions Reduction |url=https://www.smithsonianmag.com/smart-news/atmospheric-carbon-dioxide-reaches-new-high-despite-pandemic-emissions-reduction-180977945/ |access-date= 2021-06-22 |website=Smithsonian Magazine |language=en}}</ref> |
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人類活動產生的溫室氣體主要來源是: |
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*燃燒化石燃料和砍伐森林:估計於2015年排放的人為溫室氣體中,燃燒化石燃料佔62%。<ref>{{Cite web |title=Climate Change: Causation Archives |url=http://earthcharts.org/category/climate-change/climate-change-causation/ |access-date= 2021 -06-22|website=EarthCharts |language=en-US}}</ref>最大單一來源是[[燃煤發電廠]],截至2021年,其排放佔比為20%。<ref>{{Cite web |title=It's critical to tackle coal emissions – Analysis |url=https://www.iea.org/commentaries/it-s-critical-to-tackle-coal-emissions |access-date=2021-10-09 |website=IEA |language=en-GB}}</ref> |
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*土地利用變化(主要是源自[[熱帶]]地區的森林砍伐) 約佔人為溫室氣體排放總量的四分之一。<ref>{{Cite web |last=US EPA |first=OAR |date= 2016 -01-12|title=Global Greenhouse Gas Emissions Data |url=https://www.epa.gov/ghgemissions/global-greenhouse-gas-emissions-data |access-date= 2021-09-13 |website=www.epa.gov |language=en}}</ref> |
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*牲畜{{le|腸道發酵|enteric fermentation}}和[[牲畜糞肥管理]]、<ref name="livestock">{{Cite report |url=http://www.fao.org/docrep/010/a0701e/a0701e00.htm |title=Livestock's long shadow |last1=Steinfeld |first1=H. |last2=Gerber |first2=P. |publisher=FAO Livestock, Environment and Development (LEAD) Initiative |last3=Wassenaar |first3=T. |last4=Castel |first4=V. |last5=Rosales |first5=M. |last6=de Haan |first6=C. |year=2006}}</ref>[[水稻]]種植、土地利用和[[濕地]]改變、人造湖泊、<ref name="IPCC 5th Assessment, Chp. 6">{{cite book |author1=Ciais, Phillipe |title=Climate Change 2013: The Physical Science Basis |author2=Sabine, Christopher |publisher=IPCC |editor=Stocker Thomas F. |page=473 |chapter=Carbon and Other Biogeochemical Cycles |display-authors=etal |display-editors=etal |chapter-url=http://www.climatechange2013.org/images/report/WG1AR5_ALL_FINAL.pdf}}</ref>輸送管道洩漏以及[[堆填|垃圾掩埋場]]排放,導致甲烷進入大氣。許多新型全通風[[化糞池]]系統可增強發酵過程,也是大氣中甲烷的來源。 |
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*在[[製冷]]系統中使用CFC,在滅火系統和其製造過程中使用PFC和[[鹵代甲烷]]。 |
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*因在農業用地使用化學肥料而排放一氧化二氮。<ref name="Chrobak">{{cite journal |last1=Chrobak |first1=Ula |date= 2021-05-14 |title=Fighting climate change means taking laughing gas seriously |url=https://knowablemagazine.org/article/food-environment/2021/nitrous-oxide-greenhouse-gas-agriculture |journal=Knowable Magazine |doi=10.1146/knowable-051321-2 |s2cid=236555111 |access-date=2022-03-08|doi-access=free }}</ref> |
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*人為甲烷排放的最大來源是農業,緊隨其後的是化石燃料開採中的宣洩排放和逸散排放。<ref name="Initiative">{{cite web |year=2020 |title=Global Methane Emissions and Mitigation Opportunities |url=https://www.globalmethane.org/documents/gmi-mitigation-factsheet.pdf |website=Global Methane Initiative}}</ref><ref name="ieasources">{{cite web |date= 2020-08-20 |title=Sources of methane emissions |url=https://www.iea.org/data-and-statistics/charts/sources-of-methane-emissions-2 |website=International Energy Agency}}</ref>最大的農業甲烷來源是牲畜。牛是排放量最大的物種,約佔畜牧業排放量的65%。<ref>{{cite web |last= |first= |date=n.d. |title=Key facts and findings |url=https://www.fao.org/news/story/en/item/197623/icode/ |access-date=2022-10-25 |website=Fao.org |publisher=Food and Agricultural Organization |quote=}}</ref> |
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===全球估計=== |
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{{see also|北極甲烷釋出|{{le|濕地溫室氣體排放|Greenhouse gas emissions from wetlands}}}} |
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全球每年溫室氣體排放量約為50吉噸,<ref name=":4">{{Cite journal |last1=Ritchie |first1=Hannah |last2=Roser |first2=Max |date= 2020-05-11 |title=Greenhouse gas emissions |url=https://ourworldindata.org/greenhouse-gas-emissions |journal=Our World in Data |access-date=2021-06-22}}</ref>2019年排放的二氧化碳當量估計為57吉噸,其中包括源自土地利用變化而排放的5吉噸。<ref>{{Cite web |last=PBL |date= 2020-12-21 |title=Trends in Global {{CO2}} and Total Greenhouse Gas Emissions; 2020 Report |url=https://www.pbl.nl/en/publications/trends-in-global-co2-and-total-greenhouse-gas-emissions-2020-report |access-date= 2021-09-08 |website=PBL Netherlands Environmental Assessment Agency |language=en}}</ref>於2019年,人為溫室氣體淨排放總量中約34%(20吉噸二氧化碳當量)來自能源供應部門、24%(14吉噸)來自工業、22%(13吉噸)來自LULUCF、15%(8.7吉噸)來自交通運輸,有6%(3.3吉噸)來自建築物。<ref>{{Cite journal |last=IPCC |date=2019 |title=Summary for Policy Makers |url=https://report.ipcc.ch/ar6wg3/pdf/IPCC_AR6_WGIII_SummaryForPolicymakers.pdf |journal=IPCC |pages=99 |access-date=2022-04-04 |archive-date=2022-08-07 |archive-url=https://web.archive.org/web/20220807023536/https://report.ipcc.ch/ar6wg3/pdf/IPCC_AR6_WGIII_SummaryForPolicymakers.pdf |url-status=dead }}</ref> |
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目前人均排放率為每人每年6.6噸,<ref name=":5" />遠高於為維持《巴黎協定》限制全球升溫的排放目標。<ref name=":9" /> |
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雖然有時城市被認為是人均甚高的排放源,但城市的人均排放量往往低於其所處國家的平均值。<ref>{{Cite journal |last=Dodman |first=David |date=April 2009 |title=Blaming cities for climate change? An analysis of urban greenhouse gas emissions inventories |journal=Environment and Urbanization |volume=21 |issue=1 |pages=185–201 |doi=10.1177/0956247809103016 |issn=0956-2478 |s2cid=154669383|doi-access=free |bibcode=2009EnUrb..21..185D }}</ref> |
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2017年對排放企業進行的一項調查,發現排名在前100家公司的排放量佔全球直接和間接排放量的71%(參見{{le|導致氣候變化名列前茅的公司排名|Top contributors to climate change }}),其中[[國有企業]]的排放量佔比達到59%。<ref>{{Cite web |date= 2017-07-10 |title=Just 100 companies responsible for 71% of global emissions, study says |url=http://www.theguardian.com/sustainable-business/2017/jul/10/100-fossil-fuel-companies-investors-responsible-71-global-emissions-cdp-study-climate-change |access-date=2021-04-09 |website=The Guardian |language=en}}</ref><ref>{{Cite news |last=Gustin |first=Georgina |date=2017-07-09 |title=25 Fossil Fuel Producers Responsible for Half Global Emissions in Past 3 Decades |url=https://insideclimatenews.org/news/09072017/fossil-fuel-companies-responsible-global-emissions-cdp-report/ |access-date=2021-05-04 |website=[[Inside Climate News]]}}</ref> |
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中國是[[亞洲]],乃至全球最大的排放國:每年排放近100億噸,佔全球排放量的四分之一以上。<ref name="auto" />其他快速成長的排放國包括[[大韓民國|韓國]]、[[伊朗]]和[[澳大利亞]]。另一方面,[[歐盟]]中15國和美國的人均排放量隨著時間的演進而逐漸減少。<ref name="pbl annual emissions in 2008" />[[俄羅斯]]和[[烏克蘭]]自1990年以來因經濟結構調整,排放量下降最快。<ref>{{cite web |date=March 2009 |title=Global Carbon Mechanisms: Emerging lessons and implications (CTC748) |url=http://www.carbontrust.com/resources/reports/advice/global-carbon-mechanisms |access-date= 2010-03-31 |publisher=Carbon Trust |page=24}}</ref> |
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2015年是全球首見經濟總體有成長,而碳排放卻減少的一年。<ref>{{Cite news |last=Vaughan |first=Adam |date=2015-12-07 |title=Global emissions to fall for first time during a period of economic growth |newspaper=The Guardian |url=https://www.theguardian.com/environment/2015/dec/07/global-emissions-to-fall-for-first-time-during-a-period-of-economic-growth |access-date=2016-12-23 |issn=0261-3077}}</ref> |
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===高收入國家與低收入國家間比較=== |
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[[File:CO2 emissions vs GDP.svg|thumb|upright=1.5|人均二氧化碳排放與GDP的關聯圖(2018年),通則是人均所得越高,排放量就越高。<ref>{{Cite web |title={{CO2}} emissions per capita vs GDP per capita |url=https://ourworldindata.org/grapher/co2-emissions-vs-gdp |access-date=2023-06-21 |website=Our World in Data}}</ref>]] |
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工業化國家的年人均排放量通常是開發中國家的十倍。<ref name="grubb kyoto protocol" />{{Rp|144}}由於中國經濟快速發展,其人均年排放量正在迅速接近《京都議定書》附件一國家的水平(即不含美國的已開發國家)。<ref name="pbl annual emissions in 2008">{{cite web |date=2009-06-25 |title=Global {{CO2}} emissions: annual increase halves in 2008 |url=http://www.pbl.nl/en/publications/2009/Global-CO2-emissions-annual-increase-halves-in-2008.html |url-status=dead |archive-url=https://web.archive.org/web/20101219064127/http://www.pbl.nl/en/publications/2009/Global-CO2-emissions-annual-increase-halves-in-2008.html |archive-date=19 December 2010 |access-date=2010-05-05 |publisher=Netherlands Environmental Assessment Agency (PBL) website}}</ref> |
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[[非洲]]和[[南美洲]]都是相當小的排放區域:各佔全球排放量的3-4%。兩者的排放量幾乎與國際航空業或是航運業所產生的相當。<ref name="auto" /> |
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==核算與報告== |
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{{Further|碳核算|碳足跡|溫室氣體盤查}} |
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[[File:1800- Global carbon dioxide emissions, per person.svg |thumb|全球人均二氧化碳排放於20世紀中葉大增,但增加速率開始減緩。<ref name=ESSD_CarbonBudget_2022/>]] |
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===變數=== |
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目前有幾種衡量溫室氣體排放的方法,包括有:<ref name="sapiens.revues.org">{{cite journal|author=Bader, N.|author2=Bleichwitz, R.|year=2009|title=Measuring urban greenhouse gas emissions: The challenge of comparability |journal=S.A.P.I.EN.S.|volume=2|issue=3|url=http://sapiens.revues.org/index854.html|access-date=2011-09-11}}</ref> |
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*涵蓋的地理區域:排放量依地理位置予以歸屬(領土原則),或是依活動原則而將排放歸屬。例如測量從一國到另一國的電力輸入或於國際機場的排放量時,使用兩個原則會導致不同的結果。 |
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*不同氣體的存在時間長度:給定溫室氣體數量以二氧化碳當量報告。在做計算時會將該氣體在大氣中存在的時間列入考慮。但由於這些氣體在大氣中的複雜交互作用以及產生來源變動,必須定期更新以反映新資訊。 |
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*測量方式:排放可透過直接測量或是估計來達成。四種主要方法是基於排放因子法、質量平衡法、預測式{{le|排放監測|Greenhouse gas monitoring}}系統和{{le|連續排放監測系統|continuous emissions monitoring system}}系統。這些方法在準確性、成本和可用性方面有所不同。由非營利組織及幾家公司組成的機構{{le|Climate Trace| Climate Trace}}在[[2021年聯合國氣候變化大會]](第26屆聯合國氣候變遷大會)之前把各個大型工廠的排放以公開資訊方式予以揭露。<ref>{{Cite news|title=Transcript: The Path Forward: Al Gore on Climate and the Economy|newspaper=[[Washington Post]]|url=https://www.washingtonpost.com/washington-post-live/2021/04/22/transcript-path-forward-al-gore-climate-economy/|access-date=2021-05-06|issn=0190-8286}}</ref> |
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各國有時會使用這些測量數據來主張有關氣候變化的政策/道德立場。<ref name="banuri">{{cite book|author=Banuri, T.|url=https://archive.org/details/climatechange1990000unse_h1m9|title=Equity and social considerations. In: Climate change 1995: Economic and social dimensions of climate change. Contribution of Working Group III to the Second Assessment Report of the Intergovernmental Panel on Climate Change (J.P. Bruce et al. Eds.)|publisher=This version: Printed by Cambridge University Press, Cambridge, and New York. PDF version: IPCC website|year=1996|isbn=978-0521568548|url-access=registration}}</ref>{{rp|94}}使用不同的措施會導致其中間缺乏可比性,而會在監測目標進度時出現問題。對於採用通用測量工具方面,或在開發不同工具之間的溝通方面仍存在爭議。<ref name="sapiens.revues.org" /> |
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===報告=== |
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排放可經長期追蹤(稱為歷史或是累積排放測量)。這種測量方式提供一些導致大氣中溫室氣體濃度增加的指標。<ref name="iea"> |
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{{cite book|url=http://www.iea.org/publications/free_new_Desc.asp?PUBS_ID=1927|title=World energy outlook 2007 edition – China and India insights|publisher=International Energy Agency (IEA), Head of Communication and Information Office, 9 rue de la Fédération, 75739 Paris Cedex 15, France|year=2007|isbn=978-9264027305|page=600|access-date=2010-05-04|archive-url=https://web.archive.org/web/20100615062421/http://iea.org/publications/free_new_Desc.asp?PUBS_ID=1927|archive-date=2010-06-15|url-status=dead}}</ref>{{rp|199}} |
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===國民帳戶餘額=== |
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{{see also|碳洩漏}} |
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國民經濟綜合帳戶餘額法是根據一個國家的出口和進口之間的差額來追蹤排放量。對許多富裕國家來說,因為進口商品多於出口商品,導致差額為負數。有此結果主要是由於在此類國家之外生產商品的成本會更低,導致已開發國家的經濟活動越來越依賴提供服務而非商品。有正帳戶餘額表示一個國家有更多生產活動,而有更多營運的工廠會增加碳排放水準。<ref name="holtz-eakin">{{cite journal|last=Holtz-Eakin|first=D.|year=1995|title=Stoking the fires? {{CO2}} emissions and economic growth|url=http://www.nber.org/papers/w4248.pdf|journal=[[Journal of Public Economics]]|volume=57|issue=1|pages=85–101|doi=10.1016/0047-2727(94)01449-X|s2cid=152513329}}</ref> |
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也可在更短的時間內測量排放量。例如可根據以1990年作為基準年來衡量。《[[聯合國氣候變化綱要公約]]》(UNFCCC) 使用1990年作為測量排放量的基準年,《京都議定書》也使用1990年作為基準年(但某有些氣體是從1995年開始測量)。<ref name="grubb kyoto protocol"> |
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{{cite journal |author=Grubb, M. |date=July–September 2003 |title=The economics of the Kyoto protocol |url=http://www.econ.cam.ac.uk/rstaff/grubb/publications/J36.pdf |url-status=dead |journal=World Economics |volume=4 |issue=3 |archive-url=https://web.archive.org/web/20110717152152/http://www.econ.cam.ac.uk/rstaff/grubb/publications/J36.pdf |archive-date= 2011-07-17}}</ref>{{Rp|146, 149}}一個國家的排放量也可用在特定年份全球排放量中的佔比來報告。 |
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另一種衡量法是人均排放量。將一個國家的年度總排放量除以該國於年中的人口數目。<ref name="world bank emissions data"> |
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{{cite book|url=https://archive.org/details/developmentclima0000unse|title=World Development Report 2010: Development and Climate Change|publisher=The International Bank for Reconstruction and Development / The World Bank|year=2010|isbn=978-0821379875|location=Washington, DC|at=Tables A1 and A2|chapter=Selected Development Indicators|format=PDF|doi=10.1596/978-0-8213-7987-5|chapter-url=http://siteresources.worldbank.org/INTWDRS/Resources/477365-1327504426766/8389626-1327510418796/Statistical-Annex.pdf}}</ref>{{Rp|370}}人均排放量可能以歷史上或是年度的排放量來表達。<ref name="banuri" />{{rp|106–107}} |
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===隱含排放=== |
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{{see also|{{le|隱含排放|Embedded emissions}}}} |
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表達溫室氣體排放歸因的一種方式是測量在消費的商品中隱含的排放。通常衡量排放量是以產量而非以消耗量為之。<ref>{{cite book |author=Helm, D. |url=http://www.dieterhelm.co.uk/sites/default/files/Carbon_record_2007_0.pdf |title=Too Good To Be True? The UK's Climate Change Record |date= 2007-12-10 |page=3 |display-authors=etal |archive-url=https://web.archive.org/web/20110715110205/http://www.dieterhelm.co.uk/sites/default/files/Carbon_record_2007_0.pdf |archive-date= 2011-07-15 |url-status=dead |df=dmy-all}}</ref>例如在UNFCCC中,各國報告的是其境內產生的排放(如燃燒化石燃料產生的排放)。<ref name="world energy outlook 2009"> |
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{{citation |title=World Energy Outlook 2009 |url=http://www.iea.org/textbase/nppdf/free/2009/weo2009.pdf |pages=179–80 |df=dmy-all |year=2009 |access-date=2011-12-27 |archive-url=https://web.archive.org/web/20150924045811/http://www.iea.org/textbase/nppdf/free/2009/weo2009.pdf |url-status=dead |location=Paris |publisher=International Energy Agency (IEA) |isbn=978-9264061309 |archive-date=2015-09-24}} |
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</ref>{{Rp|179}}<ref name="davis consumption emissions"> |
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{{cite journal |author1=Davis, S.J. |author2=K. Caldeira |date=2010-03-08 |title=Consumption-based Accounting of {{CO2}} Emissions |url=http://www.pnas.org/content/early/2010/02/23/0906974107.full.pdf+html |format=PDF |journal=Proceedings of the National Academy of Sciences of the United States of America |volume=107 |issue=12 |pages=5687–5692 |bibcode=2010PNAS..107.5687D |doi=10.1073/pnas.0906974107 |pmc=2851800 |pmid=20212122 |access-date=2011-04-18 |doi-access=free}}</ref>{{Rp|1}}在基於生產的排放核算中,進口貨物的隱含排放歸因於出口國,而非進口國。根據基於消費的排放核算,進口商品的隱含排放歸因於進口國,而非出口國。 |
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二氧化碳排放量的很大部分經由國際貿易而易手。貿易的淨效果是將中國和其他新興市場的排放量出口到美國、[[日本]]和[[西歐]]的消費者。<ref name="davis consumption emissions" />{{Rp|4}} |
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===碳足跡=== |
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{{Excerpt|碳足跡|paragraph=1-6|File=No}} |
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===排放強度=== |
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{{Further|{{le|排放強度|Emission intensity}}}} |
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排放強度是溫室氣體排放與其他指標(例如[[國內生產毛額]](GDP)或能源使用量)之間的比率。有時也稱為"碳強度"和"排放強度"。<ref>{{cite book |author=Herzog, T. |url=http://pdf.wri.org/target_intensity.pdf |title=Target: intensity – an analysis of greenhouse gas intensity targets |date=November 2006 |publisher=World Resources Institute |isbn=978-1569736388 |editor=Yamashita, M.B. |access-date=2011-04-11}}</ref>排放強度可使用現行市場[[匯率]](MER)或[[購買力平價]](PPP)來計算。<ref name="banuri" />{{Rp|96}}基於MER的計算顯示已開發國家和開發中國家之間的排放強度差異較大,而基於PPP的計算所顯示的差異會較小。 |
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===範例工具和網站=== |
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碳核算(也稱溫室氣體核算)是衡量和追蹤一組織排放溫室氣體數量的方法架構。<ref name=":3" /> |
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====Climate TRACE==== |
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本節摘自{{le|Climate TRACE|Climate TRACE}}。 |
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Climate TRACE(即時追蹤大氣碳排放(Tracking Real-Time Atmospheric Carbon Emissions)的簡稱)<ref>{{Cite news|last=Gore|first=Al|date= 2020-12-12|title=Opinion {{!}} Al Gore: Where I Find Hope|work=[[The New York Times]]|url=https://www.nytimes.com/2020/12/12/opinion/sunday/biden-climate-change-al-gore.html|access-date=2021-07-10|issn=0362-4331|archive-date=2021-08-18|archive-url=https://web.archive.org/web/20210818162825/https://www.nytimes.com/2020/12/12/opinion/sunday/biden-climate-change-al-gore.html|url-status=live}}</ref>是個獨立組織,可監測和發佈在數週內發生的溫室氣體排放量。<ref>{{Cite web |date=2020-08-17 |title=Climate TRACE to track real-time global carbon emissions |url=http://yaleclimateconnections.org/2020/08/climate-trace-to-track-real-time-global-carbon-emissions/ |access-date= 2021-07-10 |publisher=[[Yale Climate Connections]] |archive-date=2021-07-12 |archive-url=https://web.archive.org/web/20210712052433/https://yaleclimateconnections.org/2020/08/climate-trace-to-track-real-time-global-carbon-emissions/ |url-status=live }}</ref>此組織於2021年COP26(第26屆聯合國氣候變遷大會)之前啟動,<ref>{{Cite web|last=Freedman|first=Andrew|title=Al Gore's Climate TRACE tracking group finds vast undercounts of emissions|url=https://www.axios.com/global-carbon-emissions-inventory-surprises-cb7f220a-6dfd-4f88-9349-5c9ffa0817e9.html|access-date=2021-09-27|website=Axios|language=en|archive-date=2021-09-27|archive-url=https://web.archive.org/web/20210927135601/https://www.axios.com/global-carbon-emissions-inventory-surprises-cb7f220a-6dfd-4f88-9349-5c9ffa0817e9.html|url-status=live}}</ref>它將二氧化碳和甲烷的監測、報告和驗證技術改進,<ref name=":0y">{{Cite web|last=Roberts|first=David|date=2020-07-16|title=The entire world's carbon emissions will finally be trackable in real time|url=https://www.vox.com/energy-and-environment/2020/7/16/21324662/climate-change-air-pollution-tracking-greenhouse-gas-emissions-trace-coalition|access-date= 2021-7-10|website=[[Vox (website)|Vox]]|archive-date=2021-07-10|archive-url=https://web.archive.org/web/20210710132950/https://www.vox.com/energy-and-environment/2020/7/16/21324662/climate-change-air-pollution-tracking-greenhouse-gas-emissions-trace-coalition|url-status=live}}</ref><ref>{{Cite web|date=2021-07-07|title=Methane: A Threat to People and Planet|url=https://rmi.org/methane-a-threat-to-people-and-planet/|access-date=2021-07-10|publisher=[[Rocky Mountain Institute]]|archive-date=2021-07-10|archive-url=https://web.archive.org/web/20210710130155/https://rmi.org/methane-a-threat-to-people-and-planet/|url-status=live}}</ref>利用衛星資料和[[人工智慧]]來監測世界各地的[[煤炭開採]]地點和發電站煙囪等排放來源。<ref>{{Cite news|last=Puko|first=Timothy|date=2021-04-13|title=John Kerry Says U.S. Will Hold China to Account on Climate Pledges|work=[[The Wall Street Journal]]|url=https://www.wsj.com/articles/kerry-says-u-s-will-hold-beijing-to-account-on-climate-pledges-11618338675|access-date=2021-07-10|issn=0099-9660|archive-date= 2021-07-10|archive-url=https://web.archive.org/web/20210710131308/https://www.wsj.com/articles/kerry-says-u-s-will-hold-beijing-to-account-on-climate-pledges-11618338675|url-status=live}}</ref><ref>{{Cite web|last=Peters|first=Adele|date=2020-07-15|title=This Al Gore-supported project uses AI to track the world's emissions in near real time|url=https://www.fastcompany.com/90527328/this-al-gore-supported-project-uses-ai-to-track-the-worlds-emissions-in-near-real-time|access-date=2021-07-15|website=[[Fast Company]]|archive-date=2021-05-12|archive-url=https://web.archive.org/web/20210512185220/https://www.fastcompany.com/90527328/this-al-gore-supported-project-uses-ai-to-track-the-worlds-emissions-in-near-real-time|url-status=live}}</ref> |
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==歷史趨勢== |
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===累積及歷史排放量=== |
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{{multiple image |total_width=500 |header=累積與年度二氧化碳排放 |
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| image1=1850- Cumulative emissions of carbon dioxide, by country.svg |caption1= 美國迄今的累積排放量仍居世界第一,而中國的排放則呈陡峭式增長。<ref name=ESSD_CarbonBudget_2022/> |
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| image2=1850- Annual emissions of carbon dioxide, by country.svg |caption2= 美國迄21世紀初的年度排放量仍居世界第一,然後被中國超越。<ref name=ESSD_CarbonBudget_2022>{{cite journal |last1=Friedlingstein |first1=Pierre |last2=O'Sullivan |first2=Michael |last3=Jones |first3=Matthew W. |last4=Anddrew |first4=Robbie M. |last5=Gregor |first5=Luke |display-authors=4 |title=Global Carbon Budget 2022 (Data description paper) |journal=Earth System Science Data |date=2022-11-11 |volume=14 |pages=4811–4900 |doi=10.5194/essd-14-4811-2022 |url=https://essd.copernicus.org/articles/14/4811/2022/ |doi-access=free |bibcode=2022ESSD...14.4811F |hdl=20.500.11850/594889 |hdl-access=free }} Data available for download at Our World in Data ([https://ourworldindata.org/grapher/cumulative-co-emissions cumulative] and [https://ourworldindata.org/grapher/annual-co2-emissions-per-country annual] and [https://ourworldindata.org/grapher/co-emissions-per-capita?tab=chart ''per capita'']).</ref> |
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}} |
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{{multiple image |total_width=500 |
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| image1= Cumulative CO2 emission by world region.png |caption1=全球各地區二氧化碳累積排放量示意圖 |
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| image2= Cumulative per person emissions by world region in 3 time periods.png |caption2= 全球各地區二氧化碳累積人均排放量示意圖(於三段時期內的表現) |
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[[File:CO2 Emissions by Source Since 1880.svg |thumb|從1880年起的不同二氧化碳來源排放成長趨勢。]] |
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人類使用化石燃料所產生的二氧化碳累積排放是全球暖化的主要原因,<ref>{{cite journal |author=Botzen, W.J.W. |display-authors=etal |year=2008 |title=Cumulative {{CO2}} emissions: shifting international responsibilities for climate debt |journal=Climate Policy |volume=8 |issue=6 |page=570 |doi=10.3763/cpol.2008.0539 |bibcode=2008CliPo...8..569B |s2cid=153972794}}</ref>並顯示出哪些國家對人為造成的氣候變化影響最大。二氧化碳在大氣中可存在至少150年至長達1,000年,<ref>{{Cite web |last=Buis |first=Alan |date=2019-10-19 |title=The Atmosphere: Getting a Handle on Carbon Dioxide |url=https://climate.nasa.gov/news/2915/the-atmosphere-getting-a-handle-on-carbon-dioxide |access-date=2023-07-14 |website=Climate Change: Vital Signs of the Planet}}</ref>甲烷會在十年左右的時間內消失,<ref>{{Cite web |title=Methane and climate change – Global Methane Tracker 2022 – Analysis |url=https://www.iea.org/reports/global-methane-tracker-2022/methane-and-climate-change |access-date=2023-07-14 |website=IEA |language=en-GB}}</ref>而一氧化二氮可持續約100年。<ref>{{Cite journal |last1=Prather |first1=Michael J. |last2=Hsu |first2=Juno |last3=DeLuca |first3=Nicole M. |last4=Jackman |first4=Charles H. |last5=Oman |first5=Luke D. |last6=Douglass |first6=Anne R. |last7=Fleming |first7=Eric L. |last8=Strahan |first8=Susan E. |last9=Steenrod |first9=Stephen D. |last10=Søvde |first10=O. Amund |last11=Isaksen |first11=Ivar S. A. |last12=Froidevaux |first12=Lucien |last13=Funke |first13=Bernd |date=2015-06-16 |title=Measuring and modeling the lifetime of nitrous oxide including its variability |journal=Journal of Geophysical Research: Atmospheres |language=en |volume=120 |issue=11 |pages=5693–5705 |doi=10.1002/2015JD023267 |issn=2169-897X |pmc=4744722 |pmid=26900537|bibcode=2015JGRD..120.5693P }}</ref>此類數字顯示哪些地區對人類造成的氣候變化影響最大。<ref>{{cite web |title=Climate Watch - Historical Emissions Data |url=https://www.wri.org/data/climate-watch-historical-emissions-data-countries-us-states-unfccc |access-date= 2021-10-23 |publisher=World Resources Institute}}</ref><ref name="hohne 2010 regional contribution to global warming"> |
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{{cite journal |author=Höhne, N. |display-authors=etal |date=2010-09-24 |title=Contributions of individual countries' emissions to climate change and their uncertainty |url=http://www.gcca.eu/usr/documents/Contributions_Individual_countries_201011229410.pdf |url-status=dead |journal=Climatic Change |volume=106 |issue=3 |pages=359–91 |doi=10.1007/s10584-010-9930-6 |s2cid=59149563 |archive-url=https://web.archive.org/web/20120426072941/http://www.gcca.eu/usr/documents/Contributions_Individual_countries_201011229410.pdf |archive-date=2012-04-26 |df=dmy-all}}</ref>{{Rp|15}} |
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於1890年至2007年期間,非[[經濟合作暨發展組織|經合組織]]國家佔與能源相關的累計二氧化碳排放量的42%。<ref name="world energy outlook 2009" />{{Rp|179–80}} <ref>{{cite web| url =https://www.oecd.org/berlin/44044848.pdf|title = Why is our current energy pathway unsustainable? | publisher =IEA | date =2009-11-10 | accessdate = 2024-0124}}</ref>在此期間,美國佔排放量的28%、歐盟佔23%、日本佔4%、其他經合組織國家佔5%、俄羅斯佔11%、中國佔9%、印度佔3%,世界其他地區佔18%。<ref name="world energy outlook 2009" />{{Rp|179–80}} |
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整體而言,已開發國家於此段期間的工業二氧化碳排放量佔全球此類排放的83.8%,佔二氧化碳總排放量的67.8%。在此期間,開發中國家的工業二氧化碳排放量佔此類排放的16.2%,佔二氧化碳排放總量的32.2%。 |
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然而當我們審視當今世界各地的排放量時,就會清楚地發現歷史上排放量最高的國家並非一定是當今最大的排放國。例如[[英國]]於2017年的排放量僅佔全球的1%。<ref name="auto" /> |
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相較之下,人類迄今排放的溫室氣體比導致恐龍滅絕([[白堊紀—古近紀滅絕事件]])的[[希克蘇魯伯隕石坑]]撞擊事件所產生的還要多。<ref name="Specktor 2019">{{cite web |last=Specktor |first=Brandon |date= 2019-10-01 |title=Humans Are Disturbing Earth's Carbon Cycle More Than the Dinosaur-Killing Asteroid Did |url=https://www.livescience.com/anthropogenic-warming-like-dinosaur-killing-asteroid.html |access-date= 2021-07-08 |website=livescience.com}}</ref> |
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交通運輸和發電是導致歐盟溫室氣體排放的主要來源。單獨交通運輸業與發電加上幾乎所有其他行業相比,所產生的溫室氣體排放量持續上升。交通運輸排放量自1990年起已增加30%。交通運輸部門約佔排放量的70%,其中大部分排放是由乘用車和貨車所造成。公路旅行是交通運輸溫室氣體排放中的排名第一來源,其次是航空業和海運業。<ref>{{Cite web |title=Transport emissions |url=https://ec.europa.eu/clima/eu-action/transport-emissions_en |access-date= 2021-10-18 |website=ec.europa.eu |language=en}}</ref><ref name=":2">{{Cite web |last=US EPA |first=OAR |date= 2015-09-10 |title=Carbon Pollution from Transportation |url=https://www.epa.gov/transportation-air-pollution-and-climate-change/carbon-pollution-transportation |access-date= 2021-10-18 |website=www.epa.gov |language=en}}</ref>水路運輸仍是平均碳強度最低的運輸方式,是永續[[供應鏈]]中的重要一環。<ref>{{Cite web |title=Rail and waterborne — best for low-carbon motorised transport — European Environment Agency |url=https://www.eea.europa.eu/publications/rail-and-waterborne-transport |access-date= 2021-10-18 |website=www.eea.europa.eu |language=en}}</ref> |
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建築物與工業一樣,導致直接排放的溫室氣體約佔總量的五分之一,主要由於供暖和熱水消耗。但加上建築物內的電力消耗,佔比會攀升至三分之一以上。<ref>{{Cite web |title=Luxembourg 2020 – Analysis |url=https://www.iea.org/reports/luxembourg-2020 |access-date= 2021-10-18 |website=IEA |language=en-GB}}</ref><ref>{{Cite journal |last1=Ritchie |first1=Hannah |last2=Roser |first2=Max |date=2020-05-11 |title={{CO2}} and Greenhouse Gas Emissions |url=https://ourworldindata.org/emissions-by-sector |journal=Our World in Data}}</ref><ref>{{Cite web |title=Why The Building Sector? – Architecture 2030 |url=https://architecture2030.org/why-the-building-sector/ |access-date=2021-10-18 |language=en-US}}</ref> |
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歐盟內部的農業部門目前約佔溫室氣體排放總量的10%,其中牲畜排放的甲烷約佔這10%中的一半以上。<ref>{{Cite web |date=2021-05-06 |title=Global Assessment: Urgent steps must be taken to reduce methane emissions this decade |url=https://www.unep.org/news-and-stories/press-release/global-assessment-urgent-steps-must-be-taken-reduce-methane |website=United Nations}}</ref> |
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在低層大氣中,溫室氣體與地表進行熱輻射交換,並限制輻射熱流離開地表,而將向上輻射傳熱的總體速率降低。<ref name="Wallace2006">{{cite book |last1=Wallace |first1=J. M. |last2=Hobbs |first2=P. V. |title=Atmospheric Science |date=2006 |publisher=Academic Press |isbn=978-0-12-732951-2 |edition=2}}</ref>{{rp|139}}<ref name="Manabe1964">{{cite journal |last1=Manabe |first1=S. |last2=Strickler |first2=R. F. |title=Thermal Equilibrium of the Atmosphere with a Convective Adjustment |journal=J. Atmos. Sci. |date=1964 |volume=21 |issue=4 |pages=361–385 |doi=10.1175/1520-0469(1964)021<0361:TEOTAW>2.0.CO;2|bibcode=1964JAtS...21..361M |doi-access=free }}</ref>溫室氣體濃度增加後也會將上層大氣溫度降低,因為上層大氣中的溫室氣體比下層為薄,溫室氣體重新散發的任何熱量更有可能傳播到更遠的太空,而不會與上層中較少的溫室氣體分子相互作用。結果是高層大氣層的範圍正在縮小。<ref>{{Cite web |last=Hatfield |first=Miles |date=2021-06-30 |title=NASA Satellites See Upper Atmosphere Cooling and Contracting Due to Climate Change |url=https://www.nasa.gov/general/nasa-satellites-see-upper-atmosphere-cooling-and-contracting-due-to-climate-change/ |publisher=[[NASA]] }}</ref> |
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二氧化碳排放總量的估計包括[[生物炭]]排放,主要是因為森林砍伐的結果。<ref name="banuri" />{{Rp|94}}將生物排放列入會帶來前面提到的有關碳匯和土地利用變化的相同爭議。<ref name="banuri" />{{Rp|93–94}}實際計算淨排放量會非常複雜,並受到區域間碳匯分配方式和[[氣候系統]]動態的影響。 |
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===全球暖化潛勢與二氧化碳當量=== |
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[[File:Co2 growth log piecewise.png |thumb|由化石燃料排放二氧化碳的成長對數趨勢,於1913、1945與1973這三年可看出明顯的成長。]] |
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[[File:Perfluorotributylamine-global-warming-potential.jpg|thumb|三種溫室氣體([[全氟三丁胺]]、二氧化碳、甲烷)與二氧化碳的GWP比較(期間100年),二氧化碳作為基準,GWP值為1。]] |
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此圖顯示於1850年至2019年化石燃料二氧化碳排放量的[[對數]]。<ref name="Global Carbon Budget 2020">{{Cite journal |last1=Friedlingstein |first1=Pierre |last2=O'Sullivan |first2=Michael |last3=Jones |first3=Matthew W. |last4=Andrew |first4=Robbie M. |last5=Hauck |first5=Judith |last6=Olsen |first6=Are |last7=Peters |first7=Glen P. |last8=Peters |first8=Wouter |last9=Pongratz |first9=Julia |last10=Sitch |first10=Stephen |last11=Le Quéré |first11=Corinne |last12=Canadell |first12=Josep G. |last13=Ciais |first13=Philippe |last14=Jackson |first14=Robert B. |last15=Alin |first15=Simone |date=2020 |title=Global Carbon Budget 2020 |url=https://boris.unibe.ch/153200/1/essd-12-3269-2020.pdf |journal=Earth System Science Data |language=en |volume=12 |issue=4 |pages=3269–3340 |bibcode=2020ESSD...12.3269F |doi=10.5194/essd-12-3269-2020 |issn=1866-3516 |doi-access=free|url-access= }}</ref>左側為自然對數,右側為每年1吉噸的實際值。排放量在170年期間每年整體增加約3%,但可檢測到明顯不同的成長率間隔(在1913年、1945年和1973年時發生幅度甚大的轉折)。根據回歸線,排放量可迅速從一種增長方式轉變為另一種增長方式,然後持續很長一段時間。最近一次排放量成長下降(幾乎下降3個百分點)是在20世紀[[1970年代能源危機]]期間。所用數據取自{{le|綜合碳觀測系統|Integrated Carbon Observation System}}。<ref>{{Cite web |title=Global Carbon Budget 2019 |url=https://www.icos-cp.eu/science-and-impact/global-carbon-budget/2019}}</ref> |
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本節摘自[[全球暖化潛勢]]。 |
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===自特定基準年以來的變化=== |
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全球暖化潛勢(GWP)是衡量溫室氣體進入大氣層後在給定時間範圍內吸收多少紅外線熱輻射的指數。 GWP讓不同的溫室氣體在"造成輻射強迫的有效性"方面具有可比性。<ref name=":2">IPCC, 2021: Annex VII: [https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_AnnexVII.pdf Glossary] [Matthews, J.B.R., V. Möller, R. van Diemen, J.S. Fuglestvedt, V. Masson-Delmotte, C. Méndez, S. Semenov, A. Reisinger (eds.)]. In [https://www.ipcc.ch/report/ar6/wg1/ Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change] [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 2215–2256, doi:10.1017/9781009157896.022.</ref>{{Rp|page=2232}}它以相同質量的二氧化碳(作為參考氣體)能吸收輻射的倍數表示。因此GWP是以二氧化碳作為基準。而對於其他溫室氣體,則取決於其吸收紅外線熱輻射的強度、氣體離開大氣的速度以及所需的時間。 |
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{{see also|溫室氣體盤查}} |
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全球二氧化碳排放量從1990年代的每年增加1.1%,到2000起每年急劇增加為3%以上(大氣中二氧化碳濃度每年增加超過2[[百萬分比]](ppm)),這是由於開發中國家和已開發國家雙方之前的碳強度下降的趨勢已經消失。在此期間,中國對全球排放量成長的影響最大。<ref name="Raupach">{{cite journal |author=Raupach, M.R. |last2=Marland |first2=G. |last3=Ciais |first3=P. |last4=Le Quere |first4=C. |last5=Canadell |first5=J. G. |last6=Klepper |first6=G. |last7=Field |first7=C.B. |display-authors=1 |year=2007 |title=Global and regional drivers of accelerating {{CO2}} emissions |url=http://www.pnas.org/cgi/reprint/0700609104v1.pdf |journal=Proc. Natl. Acad. Sci. USA |volume=104 |issue=24 |pages=10288–93 |bibcode=2007PNAS..10410288R |doi=10.1073/pnas.0700609104 |pmc=1876160 |pmid=17519334 |doi-access=free}}</ref>相較之下,甲烷並沒有明顯增加,而二氧化氮年增加率為0.25%。 |
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例如甲烷於20年內的GWP (GWP-20) 為81.2,<ref name=":0x">{{Citation |title=7.SM.6 Tables of greenhouse gas lifetimes, radiative efficiencies and metrics |date=2021 |url=https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_Chapter_07_Supplementary_Material.pdf |page=7SM-24 |publisher=[[IPCC]]}}.</ref>表示洩漏一噸甲烷相當於在20年內排放81.2噸二氧化碳。由於甲烷在大氣中的壽命比二氧化碳短得多,因此在較長時間內其GWP會低得多,GWP-100(100年)為27.9,GWP-500(500年)為7.95。<ref name=":0x" />{{Rp|page=7SM-24}} |
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測量排放量時,採用不同的基準年,對於估計國家對全球暖化貢獻度的估計會有不同的結果。<ref name="hohne 2010 regional contribution to global warming" />{{Rp|17–18}}<ref>The cited paper uses the term "start date" instead of "base year".</ref>解決此問題,可將一個國家從一特定基準年開始對全球暖化的最高貢獻度除以從同一特定基準年開始對全球暖化的最低貢獻度,然後在各國間作比較。在1750年、1900年、1950年和1990年之間進行基準年選擇對大多數國家都有顯著影響。<ref name="hohne 2010 regional contribution to global warming" />{{Rp|17–18}}在[[八大工業國組織]](G8)國家中,對英國、[[法國]]和[[德國]]的影響最為顯著。這些國家有著悠久的二氧化碳排放歷史。 |
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二氧化碳當量(以CO2e、CO2eq或CO2-e表達)可根據GWP計算。二氧化碳當量成為測量不同氣體對氣候影響的通用尺度。它的計算方式為用GWP乘以其他氣體的質量而得。 |
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===來自全球碳計畫的數據=== |
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==特定氣體在溫室效應的作用== |
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[[File:Potential_CO2_emissions_from_large_fossil_fuel_projects_'carbon_bombs'_per_country.jpg|thumb|全球各大化石燃料開發地點(稱為"碳炸彈")圖,這些計畫經充分開發後均有排放1吉噸二氧化碳的潛力。<ref>{{Cite journal |last1=Kühne |first1=Kjell |last2=Bartsch |first2=Nils |last3=Tate |first3=Ryan Driskell |last4=Higson |first4=Julia |last5=Habet |first5=André |date=2022 |title="Carbon Bombs" - Mapping key fossil fuel projects |url=https://eprints.whiterose.ac.uk/189177/1/1-s2.0-S0301421522001756-main.pdf |journal=Energy Policy |language=en |volume=166 |pages=112950 |doi=10.1016/j.enpol.2022.112950|s2cid=248756651 |url-access= }}</ref>]] |
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{{main|溫室效應}} |
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[[File:CO2_H2O_absorption_atmospheric_gases_unique_pattern_energy_wavelengths_of_energy_transparent_to_others.png|thumb|upright=1.4|大氣中溫室氣體只會吸收某種波長的能量,圖中水蒸氣的吸收(藍色部分)和二氧化碳的吸收(粉紅部分),兩者有部分重疊。<ref name="NASA climate forcings">{{cite web |date=2009-01-14 |title=NASA: Climate Forcings and Global Warming |url=http://earthobservatory.nasa.gov/Features/EnergyBalance/page7.php |url-status=live |archive-url=https://web.archive.org/web/20210418152758/https://earthobservatory.nasa.gov/features/EnergyBalance/page7.php |archive-date= 2021-04-18 |access-date= 2014-04-20}}</ref>]] |
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成立於2001年的組織[[全球碳計畫]]持續發佈有關二氧化碳排放、{{le|碳預算|Carbon budget}}和濃度的數據。 |
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===整體溫室效應=== |
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下表顯示發揮最大作用的溫室氣體。如果沒這些氣體,地球表面的平均溫度將會成為約-18°C (0°F),<ref name="NASACO2">{{Cite web |title=NASA GISS: Science Briefs: Greenhouse Gases: Refining the Role of Carbon Dioxide |url=http://www.giss.nasa.gov/research/briefs/ma_01/ |url-status=dead |archive-url=https://web.archive.org/web/20050112211604/http://www.giss.nasa.gov/research/briefs/ma_01/ |archive-date=2005-01-12 |access-date=2016-04-26 |website=www.giss.nasa.gov}}</ref>而非當前的15°C (59°F) 左右。<ref name="Trenberth2003">{{cite journal |vauthors=Karl TR, Trenberth KE |year=2003 |title=Modern global climate change |url=https://zenodo.org/record/1230878 |url-status=live |journal=Science |volume=302 |issue=5651 |pages=1719–23 |bibcode=2003Sci...302.1719K |doi=10.1126/science.1090228 |pmid=14657489 |s2cid=45484084 |archive-url=https://web.archive.org/web/20210422194919/https://zenodo.org/record/1230878 |archive-date= 2021-04-22 |access-date= 2019-07-26}}</ref>並指出[[對流層臭氧]] - 在[[平流層]]中的臭氧具有冷卻作用,但在[[對流層]]的臭氧,卻與一氧化二氮和氯氟碳化合物具有相同的暖化作用。<ref>{{cite web |date=2016-08-01 |title=Atmospheric Concentration of Greenhouse Gases |url=https://www.epa.gov/sites/default/files/2016-08/documents/print_ghg-concentrations-2016.pdf |publisher=[[U.S. Environmental Protection Agency]]}}</ref> |
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{| class="wikitable" style="text-align:center" |
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|+二氧化碳排放<ref>{{cite web |title=Global Carbon Budget - Latest Data |url=https://www.globalcarbonbudgetdata.org/latest-data.html |access-date=2023-06-18 |publisher=Global Carbon Project}}</ref> |
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|+ 產生溫室效應影響的佔比 |
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!年 |
|||
! !! colspan="2" | K&T研究報告 (1997年)<ref name="kiehl197">{{cite journal |last=Kiehl |first=J.T. |author2=Kevin E. Trenberth |year=1997 |title=Earth's annual global mean energy budget |journal=Bulletin of the American Meteorological Society |volume=78 |issue=2 |pages=197–208 |bibcode=1997BAMS...78..197K |doi=10.1175/1520-0477(1997)078<0197:EAGMEB>2.0.CO;2 |doi-access=free|url=http://www.geo.utexas.edu/courses/387h/PAPERS/kiehl.pdf }}</ref> !! colspan="2" |Schmidt研究報告(2010年)<ref name="Schmidt2010paper">{{citation |author1=Schmidt, G.A. |title=The attribution of the present-day total greenhouse effect |url=http://pubs.giss.nasa.gov/docs/2010/2010_Schmidt_etal_1.pdf |work=J. Geophys. Res. |volume=115 |issue=D20 |pages=D20106 |df=dmy-all |year=2010 |archive-url=https://web.archive.org/web/20111022111918/http://pubs.giss.nasa.gov/docs/2010/2010_Schmidt_etal_1.pdf |url-status=dead |bibcode=2010JGRD..11520106S |doi=10.1029/2010JD014287 |archive-date= 2011-10-22 |author2=R. Ruedy |author3=R.L. Miller |author4=A.A. Lacis |author-link1=Gavin Schmidt |doi-access=free}}, D20106. [http://pubs.giss.nasa.gov/abs/sc05400j.html Web page ] {{Webarchive|url=https://web.archive.org/web/20120604034848/http://pubs.giss.nasa.gov/abs/sc05400j.html|date=2012-06-04}}</ref> |
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!石化燃料及工業排放(吉噸碳) |
|||
(未計入水泥碳化,吸收二氧化碳) |
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!土地利用改變 |
|||
(吉噸碳) |
|||
!總計 |
|||
(吉噸碳) |
|||
!總計 |
|||
吉噸二氧化碳 |
|||
|- |
|- |
||
|2010年 |
|||
! 溫室氣體 !! 晴空 !! 有雲 !! 晴空 !! 有雲 |
|||
|9.106 |
|||
|1.32 |
|||
|10.43 |
|||
|38.0 |
|||
|- |
|- |
||
|2011年 |
|||
| 水蒸氣 || 60 || 41 || 67 || 50 |
|||
|9.412 |
|||
|1.35 |
|||
|10.76 |
|||
|39.2 |
|||
|- |
|- |
||
|2012年 |
|||
| 雲 || || 31 || || 25 |
|||
|9.554 |
|||
|1.32 |
|||
|10.87 |
|||
|39.6 |
|||
|- |
|- |
||
|2013年 |
|||
| 二氧化碳 || 26 || 18 || 24 || 19 |
|||
|9.640 |
|||
|1.26 |
|||
|10.9 |
|||
|39.7 |
|||
|- |
|- |
||
|2014年 |
|||
|對流層臭氧 || 8 || || || |
|||
|9.710 |
|||
|1.34 |
|||
|11.05 |
|||
|40.2 |
|||
|- |
|- |
||
|2015年 |
|||
| 二氧化氮+甲烷 || 6 || || || |
|||
|9.704 |
|||
|1.47 |
|||
|11.17 |
|||
|40.7 |
|||
|- |
|- |
||
|2016年 |
|||
| 其他 || || 9 || 9 || 7 |
|||
|9.695 |
|||
|1.24 |
|||
|10.93 |
|||
|39.8 |
|||
|- |
|- |
||
|2017年 |
|||
! colspan="5" style="font-size: 0.85em; padding: 5px 2px 5px 10px; text-align: left; font-weight: normal;" | |
|||
|9.852 |
|||
'''K&T研究報告 (1997年)''' 採二氧化碳濃度353ppm,並計算出125瓦/平方米的總晴空溫室效應。<br/>'''Schmidt研究報告 (2010年)'''採1980年氣候模型,二氧化碳濃度339ppm,及總溫室效應155瓦/平方米,並將吸收體的時空分佈列入考慮。<br /> |
|||
|1.18 |
|||
|11.03 |
|||
|40.2 |
|||
|- |
|||
|2018年 |
|||
|10.051 |
|||
|1.14 |
|||
|11.19 |
|||
|40.7 |
|||
|- |
|||
|2019年 |
|||
|10.120 |
|||
|1.24 |
|||
|11.36 |
|||
|41.3 |
|||
|- |
|||
|2020年 |
|||
|9.624 |
|||
|1.11 |
|||
|10.73 |
|||
|39.1 |
|||
|- |
|||
|2021年 |
|||
|10.132 |
|||
|1.08 |
|||
|11.21 |
|||
|40.8 |
|||
|- |
|||
|2022年 |
|||
(預測) |
|||
|10.2 |
|||
|1.08 |
|||
|11.28 |
|||
|41.3 |
|||
|} |
|} |
||
== |
==不同溫室氣體排放量== |
||
{{see also|溫室氣體}} |
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[[File:1979- Radiative forcing - climate change - global warming - EPA NOAA.svg|thumb|right|upright=1.5|會產生變暖效應的溫室氣體在40年之內的排放速率幾乎增加一倍。<ref name="NOAA_AGGI_2022">{{cite web |date=Spring 2023 |title=The NOAA Annual Greenhouse Gas Index (AGGI) |url=https://gml.noaa.gov/aggi/aggi.html |url-status=live |archive-url=https://web.archive.org/web/20230524133553/https://gml.noaa.gov/aggi/aggi.html |archive-date=2023-05-24 |website=NOAA.gov |publisher=National Oceanic and Atmospheric Administration (NOAA)}}</ref><ref>{{Cite web |title=Annual Greenhouse Gas Index |url=https://www.globalchange.gov/browse/indicators/annual-greenhouse-gas-index |url-status=live |archive-url=https://web.archive.org/web/20210421143115/https://www.globalchange.gov/browse/indicators/annual-greenhouse-gas-index |archive-date= 2021-04-21 |access-date=2020-09-05 |publisher=U.S. Global Change Research Program}}</ref><ref name="butmon">{{Cite web |author=Butler J. and Montzka S. |year=2020 |title=The NOAA Annual Greenhouse Gas Index (AGGI) |url=https://www.esrl.noaa.gov/gmd/aggi/aggi.html |url-status=live |archive-url=https://web.archive.org/web/20130922035917/https://www.esrl.noaa.gov/gmd/aggi/aggi.html |archive-date=2013-09-22 |access-date= 2020-09-05 |publisher=[[NOAA]] Global Monitoring Laboratory/Earth System Research Laboratories}}</ref>]] |
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{{Pie chart|thumb=right|caption=不同的溫室氣體排放組成(2020年)<br />土地利用變化未列入計算<br />總計:49.8吉噸二氧化碳當量。<ref name="Olivier 2022">Olivier J.G.J. (2022), [https://www.pbl.nl/sites/default/files/downloads/pbl-2022-trends-in-global-co2-and_total-greenhouse-gas-emissions-2021-summary-report_4758.pdf Trends in global {{CO2}} and total greenhouse gas emissions: 2021 summary report] {{Webarchive|url=https://web.archive.org/web/20230308142245/https://www.pbl.nl/sites/default/files/downloads/pbl-2022-trends-in-global-co2-and_total-greenhouse-gas-emissions-2021-summary-report_4758.pdf |date=2023-03-08 }}. PBL Netherlands, Environmental Assessment Agency, The Hague.</ref>{{rp|5}}|label1=二氧化碳當量,絕大部分來自化石燃料使用|value1=72|color1=black|label2=CH<sub>4</sub> methane|color2=brown|value2=19|label3=一氧化二氮|value3=6|color3=grey|label4=F-氣體|value4=3|color4=blue}} |
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{{Pie chart|thumb=right|caption=不同的燃料所排放的二氧化碳組成。<ref name="Global Carbon Budget 2020"/>|label1=煤炭|value1=39|color1=#602200|label2=石油|value2=34|color2=#333333|label3=天然氣|value3=21|color3=#888800|label4=水泥|value4=4|color4=#888888|label5=其他|value5=1.5|color5=#000050}} |
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二氧化碳佔溫室氣體排放的很大部分,而甲烷排放的短期影響幾乎與二氧化碳相同。<ref name="ch4-vs-co2">{{cite web |date=2014-09-30 |title=Methane vs. Carbon Dioxide: A Greenhouse Gas Showdown |url=http://www.onegreenplanet.org/animalsandnature/methane-vs-carbon-dioxide-a-greenhouse-gas-showdown/ |access-date=13 February 2020 |website=One Green Planet}}</ref>相較之下,一氧化二氮和氟化氣體的作用較小。 |
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人類行為導致自然溫室效應發生變化,此現象有時被稱為"增強式溫室效應"。<ref name="AR6_WGI_AnnexVII" />{{rp|2223}}每種氣體的增強溫室效應程度取決於此氣體的特性、豐度以及它能產生的間接影響。例如某種質量的甲烷在20年的時間範圍內所產生的直接輻射效應比相同質量的二氧化碳強約84倍。<ref name="TableOfWarmingPotentials5">{{cite book |title=Intergovernmental Panel on Climate Change Fifth Assessment Report |page=731 |chapter=Appendix 8.A |access-date=2017-11-06 |chapter-url=http://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_Chapter08_FINAL.pdf |archive-url=https://web.archive.org/web/20171013100414/http://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_Chapter08_FINAL.pdf |archive-date=2017-10-13 |url-status=live}}</ref>自1980年代起,溫室氣體強迫產生的影響(相對於1750年)也因使用IPCC推薦的{{le|大氣輻射傳輸模型|atmospheric radiative transfer codes}}而獲得高精度的估計。<ref name="butmon2">{{Cite web |author=Butler J. and Montzka S. |year=2020 |title=The NOAA Annual Greenhouse Gas Index (AGGI) |url=https://www.esrl.noaa.gov/gmd/aggi/aggi.html |publisher=[[NOAA]] Global Monitoring Laboratory/Earth System Research Laboratories}}</ref> |
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溫室氣體排放量以二氧化碳當量衡量,而二氧化碳當量則由這些氣體的[[全球暖化潛勢]] (GWP) 決定,而全球暖化潛勢則由氣體在大氣中的壽命決定。估計時很大程度上由海洋和陸地吸收這些氣體的能力決定。短期氣候污染物(SLCP)(包括甲烷、氫氟碳化物、[[對流層臭氧]]和[[黑碳]])在大氣中持續存在的時間從數天到15年不等,而二氧化碳可在大氣中保留數千年。<ref name=":1">{{Cite web |last=IGSD |date=2013 |title=Short-Lived Climate Pollutants (SLCPs) |url=http://www.igsd.org/initiatives/slcps/ |access-date= 2019-11-29 |website=Institute of Governance and Sustainable Development (IGSD)}}</ref>減少SLCP排放量可將全球暖化的持續速率降低近一半,並將預期的[[全球暖化在北極的影響|北極暖化]]速率降低三分之二。<ref>{{cite web |last1=Zaelke |first1=Durwood |last2=Borgford-Parnell |first2=Nathan |last3=Andersen |first3=Stephen |last4=Picolotti |first4=Romina |last5=Clare |first5=Dennis |last6=Sun |first6=Xiaopu |last7=Gabrielle |first7=Danielle |year=2013 |title=Primer on Short-Lived Climate Pollutants |url=http://www.igsd.org/documents/PrimeronShort-LivedClimatePollutantsNovemberElectronicversion.pdf |publisher=Institute for Governance and Sustainable Development |pages=3}}</ref> |
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溫室氣體的濃度通常以體積百萬分之一 (ppm) 或十億分之一 (ppb) 為單位測量。 二氧化碳濃度為420ppm表示每百萬個空氣分子中有420個是二氧化碳分子。從第一次工業革命開始到1958年約200年期間,二氧化碳濃度首次增加30ppm。然而接下來所增加的90ppm是在56年內完成(從1958年到2014年)。<ref name="NOAA2022" /><ref name="Kibert2016">{{cite book |author=Charles J. Kibert |title=Sustainable Construction: Green Building Design and Delivery |publisher=Wiley |year=2016 |isbn=978-1119055327 |chapter=Background |chapter-url={{google books |plainurl=y |id=qv3iCwAAQBAJ|page=698}}}}</ref><ref>{{cite web |year=2005 |title=Full Mauna Loa CO<sub>2</sub> record |url=https://www.esrl.noaa.gov/gmd/ccgg/trends/full.html |url-status=live |archive-url=https://web.archive.org/web/20170428033710/https://www.esrl.noaa.gov/gmd/ccgg/trends/full.html |archive-date=2017-04-28 |access-date=2017-05-06 |publisher=Earth System Research Laboratory}}</ref>而在2000年代的增長率僅及2000年至2007年間的37%,速度之快為前所未見。<ref>{{cite web |last=Tans |first=Pieter |date=3 May 2008 |title=Annual CO<sub>2</sub> mole fraction increase (ppm) for 1959–2007 |url=ftp://ftp.cmdl.noaa.gov/ccg/co2/trends/co2_gr_mlo.txt |publisher=National Oceanic and Atmospheric Administration Earth System Research Laboratory, Global Monitoring Division}} {{cite web |title=additional details |url=http://www.esrl.noaa.gov/gmd/ccgg/trends/ |url-status=live |archive-url=https://web.archive.org/web/20181225142754/https://www.esrl.noaa.gov/gmd/ccgg/trends/ |archive-date= 2018-12-25 |access-date=2008-05-15}}; see also {{cite journal |last1=Masarie |first1=K.A. |last2=Tans |first2=P.P. |year=1995 |title=Extension and integration of atmospheric carbon dioxide data into a globally consistent measurement record |url=https://zenodo.org/record/1231364 |url-status=live |journal=J. Geophys. Res. |volume=100 |issue=D6 |pages=11593–610 |bibcode=1995JGR...10011593M |doi=10.1029/95JD00859 |archive-url=https://web.archive.org/web/20210308193900/https://zenodo.org/record/1231364 |archive-date=2021-03-08 |access-date= 2019-07-26}}</ref> |
|||
全球於2019年的溫室氣體排放量估計為57.4吉噸二氧化碳當量,而僅二氧化碳排放量就達42.5吉噸(包括土地利用變化 (LUC) 在內)。<ref name="Trends2">using 100 year [[global warming potential]] from IPCC-AR4</ref> |
|||
許多觀測結果可在各種{{le|大氣化學觀測資料庫|Atmospheric chemistry observational databases}}在線上取得。以下是IPCC確定的最具影響力的長壽命、充分混合的溫室氣體,及其於對流層中濃度和直接[[輻射強迫]]能力。<ref name="ar5">{{cite book |url=https://www.ipcc.ch/report/ar5/wg1/ |title=AR5 Climate Change 2013: The Physical Science Basis |contribution=Chapter 8}}</ref>大氣科學家定期從世界各地收集的樣本中測量這些微量氣體的豐度。<ref>{{cite web |title=Global Monitoring Laboratory |url=https://www.esrl.noaa.gov/gmd/ |access-date=2020-12-11 |publisher=NOAA Earth System Research Laboratories}}</ref><ref>{{cite web |title=World Data Centre for Greenhouse Gases |url=https://gaw.kishou.go.jp/ |access-date=2020-12-11 |publisher=World Meteorological Organization Global Atmosphere Watch Programme and Japan Meteorological Agency}}</ref><ref>{{cite web |title=Advanced Global Atmospheric Gas Experiment |url=https://agage.mit.edu/ |access-date=2020-12-11 |publisher=Massachusetts Institute of Technology}}</ref>但不包括 1.水蒸氣,因為其濃度變化被推算為由其他溫室氣體以及臭氧的變化,而間接引起的氣候變化反饋、2. 臭氧的濃度僅由導致{{le|臭氧消耗|ozone depletion}}的各種製冷劑間接改變、3. 一些短壽命氣體(例如一氧化碳、氮氧化物)和氣膠(例如{{le|礦物粉塵|Mineral dust}}或[[黑碳]])因為作用有限,且變化較大,4.還有小批量生產的製冷劑和其他[[鹵化]]氣體,<ref name="ar5" />{{rp|731-738}} 以及列於2021年IPCC第一工作組報告附件三的氣體。<ref name="ar6">{{citation |title=Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change |date=2021-08-09 |editor=Dentener F. J. |url=https://www.ipcc.ch/report/ar6/wg1/#FullReport |section=Annex III: Tables of historical and projected well-mixed greenhouse gas mixing ratios and effective radiative forcing of all climate forcers |section-url=https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_AnnexIII.pdf |publisher=Cambridge University Press |editor2=B. Hall |editor3=C. Smith}}</ref>{{rp|4-9}} |
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脫碳是甚為重要的長期措施,但處理對氣候影響更快的短期污染物也同樣重要,將針對此兩因素的措施結合,對實現氣候目標非常重要。<ref>{{cite journal |last1=Dreyfus |first1=Gabrielle B. |last2=Xu |first2=Yangyang |last3=Shindell |first3=Drew T. |last4=Zaelke |first4=Durwood |last5=Ramanathan |first5=Veerabhadran |date= 2022-05-31 |title=Mitigating climate disruption in time: A self-consistent approach for avoiding both near-term and long-term global warming |journal=Proceedings of the National Academy of Sciences |language=en |volume=119 |issue=22 |pages=e2123536119 |bibcode=2022PNAS..11923536D |doi=10.1073/pnas.2123536119 |doi-access=free |issn=0027-8424 |pmc=9295773 |pmid=35605122 |s2cid=249014617}}</ref> |
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{| class="wikitable sortable" style="text-align:center" |
|||
|+IPCC所列的溫室氣體(經由其發表的第三、第四、第五及第六次評估報告匯集而得) |
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===二氧化碳=== |
|||
! rowspan="2" |氣體種類 |
|||
*化石燃料:石油、天然氣和煤炭是人為全球暖化的主要驅動因素,於2019年年排放量為35.6吉噸二氧化碳(佔比89%))。<ref name="Olivier 2020">Olivier J.G.J. and Peters J.A.H.W. (2020), [https://www.pbl.nl/sites/default/files/downloads/pbl-2020-trends-in-global-co2-and_total-greenhouse-gas-emissions-2020-report_4331.pdf Trends in global {{CO2}} and total greenhouse gas emissions: 2020 report] {{Webarchive|url=https://web.archive.org/web/20220402191139/https://www.pbl.nl/sites/default/files/downloads/pbl-2020-trends-in-global-co2-and_total-greenhouse-gas-emissions-2020-report_4331.pdf |date=2022-04-02 }}. [https://www.pbl.nl/en PBL Netherlands] {{Webarchive|url=https://web.archive.org/web/20210909141756/https://www.pbl.nl/en/ |date=2021-09-09 }} Environmental Assessment Agency, The Hague.</ref>{{rp|20}} |
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! rowspan="2" |於大氣中壽命(年) |
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*水泥生產估計排放量為1.42吉噸二氧化碳(佔比4%)。 |
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<ref name="ar5" />{{rp|731}} |
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*土地利用變化(LUC)是森林砍伐遠高於[[林地復育]]的結果,粗略估計為4.5吉噸二氧化碳排放量。光是[[野火]]每年就造成約7吉噸二氧化碳排放量。<ref>{{cite news |last1=Lombrana |first1=Laura Millan |last2=Warren |first2=Hayley |last3=Rathi |first3=Akshat |year=2020 |title=Measuring the Carbon-Dioxide Cost of Last Year's Worldwide Wildfires |publisher=Bloomberg L.P. |url=https://www.bloomberg.com/graphics/2020-fire-emissions/}}</ref><ref>{{cite report |url=http://www.globalfiredata.org/_plots/annual_emissions.pdf |title=Global fire annual emissions |publisher=Global Fire Emissions Database}}</ref> |
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! rowspan="2" |100年 |
|||
*化石燃料作非能源使用、生產[[焦炭]]過程中的碳損失以及原油/天然氣生產中的{{le|燃除|Gas flare}}也會產生二氧化碳。<ref name="Olivier 2020" /> |
|||
GWP |
|||
<ref name="ar5" />{{rp|731}} |
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===甲烷=== |
|||
! colspan="5" |莫耳分率 [百萬分比,除非另有說明)]<sup>a</sup> + 輻射強迫 [瓦特/平方米] {{ref label|ERF|B|B}} |
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{{see also|{{le|甲烷排放|Methane emissions}}|北極甲烷釋出}} |
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! rowspan="2" |Data<ref name="hats">{{cite web |title=Long-term global trends of atmospheric trace gases |url=https://www.esrl.noaa.gov/gmd/hats/data.html |access-date=2021-02-11 |publisher=NOAA Earth System Research Laboratories}}</ref><ref name="agage">{{cite web |title=AGAGE Data and Figures |url=https://agage.mit.edu/data/agage-data |access-date=2021-02-11 |publisher=Massachusetts Institute of Technology}}</ref> |
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[[File:Historical_and_future_temperature_projections_showing_importance_of_mitigating_short-lived_climate_pollutants.jpg|thumb|根據歷史資料與全球升溫情景預測迄2050年的升溫趨勢,但採取緩解措施,消除短壽命溫室氣體(如甲烷)預計可產生抑制的效果。]] |
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2020 |
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甲烷能產生很高的直接影響,它在在5年吸收熱量的能力是二氧化碳的100倍。<ref name="ch4-vs-co2" />因此目前3.89噸的甲烷排放量<ref name="Olivier 2020" />{{rp|6}}與總體二氧化碳排放量具有大致相同的短期全球暖化效應,並有引發氣候和[[生態系|生態系統]]不可逆轉的風險。將目前的甲烷排放量減少約30%將導致其於大氣中的濃度維持穩定。 |
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*化石燃料相關活動佔甲烷排放的大部分(32%),包括煤炭開採(12%)、天然氣輸送和洩漏(11%)以及石油開採中的宣洩排放(9%)。<ref name="Olivier 2020" />{{rp|6}}<ref name="Olivier 2020" />{{rp|12}} |
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*牲畜(28%),其中牛(21%)為主要來源,其次是水牛(3%)、綿羊(2%)和山羊(1.5%)。<ref name="Olivier 2020" />{{rp|6, 23}} |
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*人類廢棄物和[[廢水|污水]](21%):當垃圾掩埋場的[[生物質]]廢棄物以及生活和工業污水中的[[有機物質]]在厭氧條件下被[[細菌]]分解時,會產生大量甲烷。<ref name="Olivier 2020" />{{rp|12}} |
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*水稻種植是另一個農業來源(10%),被水淹沒的田地中有機物質受厭氧分解而產生甲烷。<ref name="Olivier 2020" />{{rp|12}} |
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===一氧化二氮=== |
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一氧化二氮具有高GWP和顯著的臭氧消耗潛力。估計一氧化二氮在100年內的暖化潛力是二氧化碳的265倍。<ref>{{Cite journal |last=World Meteorological Organization |date=January 2019 |title=Scientific Assessment of ozone Depletion: 2018 |url=https://ozone.unep.org/sites/default/files/2019-05/SAP-2018-Assessment-report.pdf |journal=Global Ozone Research and Monitoring Project |volume=58 |pages=A3 (see Table A1)}}</ref>對於此種氣體,需要減少50%以上排放才能維持其在大氣中的穩定。 |
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一氧化二氮的大部分排放量來自農業(56%) ,尤其是畜養牲畜:牛(牧場中的糞便)、化肥、牲畜糞肥管理。<ref name="Olivier 2020" />{{rp|12}}另外的來源是化石燃料(18%) 和燃燒生物燃料,<ref>{{Cite journal |last1=Thompson |first1=R.L |last2=Lassaletta |first2=L. |last3=Patra |first3=P.K |year=2019 |others=et al. |title=Acceleration of global N2O emissions seen from two decades of atmospheric inversion |url=http://pure.iiasa.ac.at/id/eprint/16173/1/N2O_trends_revision2_v1_clean.pdf |journal=Nature Climate Change |volume=9 |issue=12 |pages=993–998 |bibcode=2019NatCC...9..993T |doi=10.1038/s41558-019-0613-7 |s2cid=208302708|url-access= }}</ref>以及[[己二酸]](用於生產[[尼龍]])和[[硝酸]]的工業生產。 |
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===F-氣體=== |
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氟化氣體包括HFC、PFC、SF6和[[三氟化氮]] (NF3)。它們用於電力行業的開關設備、[[半導體]]製造、[[鋁]]生產,另有尚不知來源的SF6排放。<ref name="Olivier 2020" />{{rp|38}}根據《蒙特婁議定書》基加利修正案,繼續逐步減少HFC的製造和使用將有助於於減少其排放,同時又能提高空調、冰櫃和其他製冷設備等設備的能源效率。 |
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===氫氣=== |
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氫氣洩漏會間接導致全球暖化。<ref>{{cite web|url=https://www.rechargenews.com/energy-transition/hydrogen-twice-as-powerful-a-greenhouse-gas-as-previously-thought-uk-government-study/2-1-1200115 |title=Hydrogen 'twice as powerful a greenhouse gas as previously thought': UK government study |date=2022-04-08 |access-date=2023-03-03 }}</ref>當氫氣在大氣中被氧化時,結果是[[對流層]]和[[平流層]]中溫室氣體的濃度會增加。<ref>{{cite journal |last1=Ocko |first1=Illisa |last2=Hamburg |first2=Steven |date= 2022-07-20 |title=Climate consequences of hydrogen emissions |url=https://acp.copernicus.org/preprints/acp-2022-91/acp-2022-91.pdf |journal=Atmospheric Chemistry and Physics |volume=22 |issue=14 |pages=9349–9368 |doi=10.5194/acp-22-9349-2022 |bibcode=2022ACP....22.9349O |s2cid=250930654 |access-date=2023-04-25 |doi-access=free |url-access= }}</ref>氫氣可能從{{le|氫氣生產|Hytrogen production}}設施以及任何運輸、儲存或消耗氫氣的基礎設施中洩漏。<ref>{{Cite journal |last1=Cooper |first1=Jasmin |last2=Dubey |first2=Luke |last3=Bakkaloglu |first3=Semra |last4=Hawkes |first4=Adam |date=2022-07-15 |title=Hydrogen emissions from the hydrogen value chain-emissions profile and impact to global warming |journal=Science of the Total Environment |volume=830 |pages=154624 |doi=10.1016/j.scitotenv.2022.154624 |pmid=35307429 |bibcode=2022ScTEn.830o4624C |s2cid=247535630 |issn=0048-9697|doi-access=free |hdl=10044/1/96970 |hdl-access=free }}</ref> |
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===黑碳=== |
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黑碳是經由化石燃料、生物燃料和生物質的不完全燃燒而形成。它並非溫室氣體,而是[[輻射強迫]]物質。黑碳沉積在雪和冰上時可吸收陽光並降低[[反照率]]。其與雲的相互作用可能會引起間接加熱作用。<ref>{{Cite journal |last=Bond |display-authors=etal |date=2013 |title=Bounding the role of black carbon in the climate system: A scientific assessment |journal=J. Geophys. Res. Atmos. |volume=118 |issue=11 |pages=5380–5552 |bibcode=2013JGRD..118.5380B |doi=10.1002/jgrd.50171 |doi-access=free|hdl=2027.42/99106 |hdl-access=free }}</ref>黑碳在大氣中僅停留幾天到幾週。<ref name="Ramanathan & Carmichael 2008">{{cite journal |last1=Ramanathan |first1=V. |last2=Carmichael |first2=G. |date=April 2008 |title=Global and regional climate changes due to black carbon |journal=Nature Geoscience |volume=1 |issue=4 |pages=221–227 |bibcode=2008NatGe...1..221R |doi=10.1038/ngeo156}}</ref>可透過將煉焦碳爐升級、在柴油引擎上安裝顆粒物過濾器、減少常規燃除作業,以及最大限度減少露天燃燒生物質來降低排放。 |
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==各經濟部門排放量== |
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{{see also|氣候變化緩解#各區塊的緩解措施}} |
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[[File:Greenhouse Gas Emissions by Economic Sector.svg|thumb|upright=1.35|不同經濟部門所造成的溫室氣體排放,含直接及間接效果(2019年)。]] |
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[[File:Global GHG Emissions by Sector 2016.png|thumb|upright=1.35|全球不同經濟部門的溫室氣體(列於京都議定書中的)排放比例(2016年)。<ref>{{Cite web |date= 2020-03-06 |title=Global Greenhouse Gas Emissions by Sector |url=http://earthcharts.org/emissions-sources/ |access-date=2020-03-15 |website=EarthCharts}}</ref>數字均以二氧化碳當量表示。]] |
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全球溫室氣體排放可歸因於不同的[[經濟部門]]。了解其對氣候變化造成的不同影響程度,有助於了解[[氣候變化緩解]]所需的行動。 |
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溫室氣體排放可分為因燃燒燃料取得能量而產生的溫室氣體排放,和其他過程所產生的。大約三分之二的溫室氣體排放來自燃燒過程。<ref name=":0">{{Cite web |title=Life Cycle Assessment of Electricity Generation Options {{!}} UNECE |url=https://unece.org/sed/documents/2021/10/reports/life-cycle-assessment-electricity-generation-options |access-date=2021-11-26 |website=unece.org}}</ref> |
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能量可在消耗點產生,或生產電力以供他處消耗。因此生產能源而產生的排放可根據生產地點,或是能源消耗地點進行分類。如果排放量歸因於生產地點,那麼發電機的排放量約佔全球溫室氣體排放量的5%。<ref>IEA, {{CO2}} Emissions from Fuel Combustion 2018: Highlights (Paris: International Energy Agency, 2018) p.98</ref>如果這些排放歸因於最終消費者,那麼總排放量的24%來自製造業和建築業,17%來自運輸業,11%來自家庭消費者,7%來自商業消費者。<ref>IEA, {{CO2}} Emissions from Fuel Combustion 2018: Highlights (Paris: International Energy Agency, 2018) p.101</ref>大約有4%的排放量來自能源和燃料產業本身消耗的能源。 |
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其餘三分之一的排放來自能源生產以外的製程。總排放量的12%來自農業、7%來自土地利用變化和林業、6%來自工業流程,及3%來自廢棄物。<ref name=":0" /> |
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===發電=== |
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{{see also|{{le|能源生命週期溫室氣體排放|Life-cycle greenhouse gas emissions of energy sources}}}} |
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[[File:Global_emissions_gas_2015.png|thumb|全球溫室氣體排放組成(2015年)。]] |
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燃煤發電廠是最大的單一排放源,於2018年佔全球溫室氣體排放量的20%以上。<ref>{{Cite web |title=Emissions |url=https://www.iea.org/geco/emissions/ |url-status=dead |archive-url=https://web.archive.org/web/20190812215445/https://www.iea.org/geco/emissions/ |archive-date= 2019-08-12 |access-date= 2019-09-21 |website=www.iea.org}}</ref>天然氣發電廠的污染比燃煤電廠少得多,但它也是個主要排放源,<ref>{{Cite web |date= 2019-07-01 |title=We have too many fossil-fuel power plants to meet climate goals |url=https://www.nationalgeographic.com/environment/2019/07/we-have-too-many-fossil-fuel-power-plants-to-meet-climate-goals/ |archive-url=https://web.archive.org/web/20190702105444/https://www.nationalgeographic.com/environment/2019/07/we-have-too-many-fossil-fuel-power-plants-to-meet-climate-goals/ |url-status=dead |archive-date=2019-07-02 |access-date=2019-09-21 |website=Environment |language=en}}</ref>2018年火力發電量廠的排放佔全球總排放量的25%以上。<ref>{{Cite web |title=March: Tracking the decoupling of electricity demand and associated {{CO2}} emissions |url=https://www.iea.org/newsroom/news/2019/march/tracking-the-decoupling-of-electricity-demand-and-associated-co2-emissions.html |access-date= 2019-09-21 |website=www.iea.org}}</ref>值得注意的是根據對221個國家中29,000多個化石燃料發電廠的盤查,發現其中僅5%發電廠就佔發電碳排放量的近四分之三。<ref>{{Cite journal |last1=Grant |first1=Don |last2=Zelinka |first2=David |last3=Mitova |first3=Stefania |date=2021-07-13 |title=Reducing {{CO2}} emissions by targeting the world's hyper-polluting power plants |journal=Environmental Research Letters |volume=16 |issue=9 |page=094022 |bibcode=2021ERL....16i4022G |doi=10.1088/1748-9326/ac13f1 |issn=1748-9326 |doi-access=free|url=https://scholar.colorado.edu/downloads/9z903115h }}</ref>[[聯合國]][[政府間氣候變化專門委員會]](IPCC)於2022年發表的報告指出,如果能源服務能透過現代化的方式,溫室氣體排放最多只會增加幾個百分點,這種小幅增長表示為所有人提升生活水平,所採用的能源將會遠低於當前的平均水平。<ref>Emission Trends and Drivers, Ch 2 in "Climate Change 2022: Mitigation of Climate Change" https://www.ipcc.ch/report/ar6/wg3/ {{Webarchive|url=https://web.archive.org/web/20220802125242/https://www.ipcc.ch/report/ar6/wg3/ |date=2022-08-02 }}</ref> |
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===農業、林業和土地利用=== |
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====農業==== |
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{{see also|{{le|甲烷排放|Methane emissions}}}} |
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{{Excerpt|農業產生的溫室氣體排放|paragraphs=1-3|File=no}} |
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====森林砍伐==== |
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[[File:Spatial pattern of forest carbon loss across the tropics.webp|thumb|全球因森林砍伐而釋出的二氧化碳(平均數),上圖為2001年-2005年期間,下圖為2015年-2019年期間。<ref name="10.1038/s41893-022-00854-3">{{cite journal |last1=Feng |first1=Yu |last2=Zeng |first2=Zhenzhong |last3=Searchinger |first3=Timothy D. |last4=Ziegler |first4=Alan D. |last5=Wu |first5=Jie |last6=Wang |first6=Dashan |last7=He |first7=Xinyue |last8=Elsen |first8=Paul R. |last9=Ciais |first9=Philippe |last10=Xu |first10=Rongrong |last11=Guo |first11=Zhilin |last12=Peng |first12=Liqing |last13=Tao |first13=Yiheng |last14=Spracklen |first14=Dominick V. |last15=Holden |first15=Joseph |date=2022-02-28|title=Doubling of annual forest carbon loss over the tropics during the early twenty-first century |journal=Nature Sustainability |language=en |volume=5 |issue=5 |pages=444–451 |doi=10.1038/s41893-022-00854-3 |issn=2398-9629 |first22=Venkataraman |first24=Chunmiao |last24=Zheng |first23=Eric F. |last23=Wood |last22=Lakshmi |last16=Liu |first21=Xiao-Peng |last21=Song |first20=Xin |last20=Jiang |first19=Ji |last19=Chen |first18=Peng |last18=Xu |first17=Yi |last17=Zheng |first16=Xiaoping |s2cid=247160560|doi-access=free |bibcode=2022NatSu...5..444F |url=https://eprints.whiterose.ac.uk/185396/18/s41893-022-00854-3.pdf }}</ref>]] |
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{{Further|森林砍伐}} |
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森林砍伐也是溫室氣體排放的主要來源。一項研究顯示熱帶森林砍伐造成的年度碳排放量(或碳損失)在過去二十年中翻了一倍,且還繼續增加中。(2001年至2005年期間每年有0.97 ±0.16吉噸碳,而在2015年至2019年期間每年有1.99 ±0.13吉噸碳 )<ref>{{cite news |date= 2022-02-28 |title=Deforestation emissions far higher than previously thought, study finds |language=en |work=The Guardian |url=https://www.theguardian.com/environment/2022/feb/28/deforestation-emissions-far-higher-than-previously-thought-study-finds-aoe |access-date=2022-03-16}}</ref><ref name="10.1038/s41893-022-00854-3" /> |
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====土地利用變化==== |
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{{main|農業產生的溫室氣體排放}} |
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[[File:2019 Greenhouse gas emissions per capita by region - variwide bar chart - IPCC AR6 WG3 - Fig SPM.2c.svg|thumb|upright=1.5 |於[[拉丁美洲]]、[[東南亞]]、[[非洲]]及太平洋島嶼,因土地利用改變而導致當地有大量的溫室氣體排放。<ref name=IPCCwg3Fig2c>Fig. SPM.2c from {{cite book |author1=Working Group III |date=2022-04-04 |title=Climate Change 2022 / Mitigation of Climate Change / Summary for Policymakers |url=https://www.ipcc.ch/report/ar6/wg3/downloads/report/IPCC_AR6_WGIII_SummaryForPolicymakers.pdf |url-status=live |archive-url=https://web.archive.org/web/20230722045040/https://www.ipcc.ch/report/ar6/wg3/downloads/report/IPCC_AR6_WGIII_SummaryForPolicymakers.pdf |archive-date=2023-07-22 |website=IPCC.ch |publisher=Intergovernmental Panel on Climate Change |page=10 |isbn=978-92-9169-160-9 }} GDP data is for 2019.</ref>]] |
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土地利用變化,例如砍伐森林改作農業用途,會將儲存於碳匯的碳量釋放進入大氣,增加其中溫室氣體的濃度。<ref>{{citation |title=Annex I: Glossary J–P |url=http://www.ipcc.ch/publications_and_data/ar4/wg3/en/annex1sglossary-j-p.html |editor1=B. Metz |archive-url=https://web.archive.org/web/20100503041746/http://www.ipcc.ch/publications_and_data/ar4/wg3/en/annex1sglossary-j-p.html |archive-date=2010-05-03 |editor2=O.R. Davidson |editor3=P.R. Bosch |editor4=R. Dave |editor5=L.A. Meyer |url-status=dead}}</ref>土地利用變化的核算可理解為衡量"淨"排放的概念,即所有來源的總排放扣除例如森林的碳匯從大氣中清除的溫室氣體。<ref name="banuri" />{{Rp|92–93}} |
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淨碳排放量的計量存在很大的不確定性。<ref>{{cite book |author=Markandya, A. |title=Costing Methodologies |publisher=Print version: Cambridge University Press, Cambridge, and New York. This version: GRID-Arendal website |year=2001 |isbn=978-0521015028 |editor=B. Metz |series=Climate Change 2001: Mitigation. Contribution of Working Group III to the Third Assessment Report of the Intergovernmental Panel on Climate Change |chapter=7.3.5 Cost Implications of Alternative GHG Emission Reduction Options and Carbon Sinks |access-date=2011-04-11 |display-editors=etal |chapter-url=http://www.grida.no/climate/ipcc_tar/wg3/293.htm |archive-url=https://web.archive.org/web/20110805022315/http://www.grida.no/climate/ipcc_tar/wg3/293.htm |archive-date=2011-08-05 |url-status=dead |df=dmy-all}}</ref>此外,關於碳匯應如何在不同地區和在不同的時代間分配也存在爭議。<ref name="banuri" />{{Rp|93}}例如關注現代的碳匯變化可能對那些較早之前經歷過砍伐森林的地區(例如[[歐洲]])有利。 |
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於1997年,人為造成的[[1997年東南亞霾害|印尼泥炭沼澤森林火災]],估計產生的碳排放是全球燃燒化石燃料平均排放量的13%至40%。<ref>{{Cite journal |last1=Page |first1=S. |last2=Siegert |first2=F. |last3=Rieley |first3=J. |last4=Boehm |first4=H. |last5=Jaya |first5=A. |last6=Limin |first6=S. |year=2002 |title=The amount of carbon released from peat and forest fires in Indonesia during 1997 |journal=[[Nature (journal)|Nature]] |volume=420 |issue=6911 |pages=61–65 |bibcode=2002Natur.420...61P |doi=10.1038/nature01131 |pmid=12422213 |s2cid=4379529}}</ref><ref>{{cite web |last=Lazaroff |first=Cat |date=2002-11-08 |title=Indonesian Wildfires Accelerated Global Warming |url=http://www.ens-newswire.com/ens/nov2002/2002-11-08-06.asp |url-status=dead |archive-url=https://web.archive.org/web/20190908133919/http://www.ens-newswire.com/ens/nov2002/2002-11-08-06.asp |archive-date= 2019-09-08 |access-date=2011-11-07 |work=Environment New Service}}</ref><ref>{{cite news |author=Pearce, Fred |date= 2004-11-06 |title=Massive peat burn is speeding climate change |publisher=New Scientist |url=https://www.newscientist.com/article.ns?id=dn6613}}</ref> |
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===人員和貨物運輸=== |
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[[File:World_fossil_carbon_dioxide_emissions_six_top_countries_and_confederations.png|thumb|航空業與海運業共同產生可觀的二氧化碳排放(虛線部分)。]] |
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{{Further|氣候變化緩解#交通運輸|航運對環境的影響#溫室氣體排放|{{le|電池驅動電動車的環境足跡|Environmental footprint of battery electric cars}}|{{le|鐵路運輸的環境設計|Environmental design in rail transportation}}}} |
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交通運輸產生的排放量佔全球的15%。<ref>{{Cite journal |last1=Ge |first1=Mengpin |last2=Friedrich |first2=Johannes |last3=Vigna |first3=Leandro |date=6 February 2020 |title=4 Charts Explain Greenhouse Gas Emissions by Countries and Sectors |url=https://www.wri.org/blog/2020/02/greenhouse-gas-emissions-by-country-sector |language=en |access-date= 2020-12-30 |website=World Resources Institute}}</ref>全球交通運輸二氧化碳排放量的四分之一以上來自公路貨運,<ref>{{Cite web |title=Cars, planes, trains: where do {{CO2}} emissions from transport come from? |url=https://ourworldindata.org/co2-emissions-from-transport |access-date=2021-06-19 |website=Our World in Data}}</ref>因此許多國家正在進一步限制卡車二氧化碳排放,以助於限制氣候變化。<ref>{{cite news |date=2018-12-20 |title=EU countries agree to 30 percent cut in truck {{CO2}} emissions |work=Reuters |url=https://www.reuters.com/article/us-eu-autos-emissions/eu-countries-agree-to-30-percent-cut-in-truck-co2-emissions-idUSKCN1OJ1ZC}}</ref> |
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海上運輸產生的排放量佔所有排放量的3.5%至4%,主要是二氧化碳。<ref name="Walker et al 2019 Environmental Effects of Marine Transportation">{{Cite book |last1=Walker |first1=Tony R. |title=World Seas: An Environmental Evaluation |last2=Adebambo |first2=Olubukola |last3=Del Aguila Feijoo |first3=Monica C. |last4=Elhaimer |first4=Elias |last5=Hossain |first5=Tahazzud |last6=Edwards |first6=Stuart Johnston |last7=Morrison |first7=Courtney E. |last8=Romo |first8=Jessica |last9=Sharma |first9=Nameeta |year=2019 |isbn=978-0-12-805052-1 |pages=505–530 |chapter=Environmental Effects of Marine Transportation |doi=10.1016/B978-0-12-805052-1.00030-9 |name-list-style=vanc |last10=Taylor |first10=Stephanie |last11=Zomorodi |first11=Sanam |s2cid=135422637}}</ref><ref name="vidal2009">{{Cite news |last=Vidal |first=John |date=2009-04-09 |title=Health risks of shipping pollution have been 'underestimated' |work=The Guardian |url=https://www.theguardian.com/environment/2009/apr/09/shipping-pollution |access-date=2009-07-03}}</ref>航運業於2022年產生的排放量佔全球的3%,使其成為"全球第六大溫室氣體排放個體,排名介於日本和德國之間。"<ref>{{Cite web |date=2022-03-16 |title=Infrastructure Podcast; Decarbonized Shipping |url=https://www.worldbank.org/en/news/podcast/2022/03/16/decarbonized-shipping-reducing-the-dependence-on-fossil-fuels |access-date=2022-08-18 |publisher=World Bank}}</ref><ref>{{Cite web |last1=Kersing |first1=Arjen |last2=Stone |first2=Matt |date=2022-01-25 |title=Charting global shipping's path to zero carbon |url=https://www.mckinsey.com/industries/travel-logistics-and-infrastructure/our-insights/charting-global-shippings-path-to-zero-carbon |access-date=2022-08-18 |publisher=McKinsey}}</ref><ref>{{Cite web |last=Raucci |first=Carlo |date=2019-06-06 |title=Three pathways to shipping's decarbonization |url=https://www.globalmaritimeforum.org/news/three-pathways-to-shippings-decarbonization |access-date=2022-08-18 |publisher=Global Maritime Forum}}</ref> |
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====航空==== |
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{{Further|航空業對環境的影響#氣候變化}} |
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噴射客機排放二氧化碳、[[氮氧化物]]、[[凝結尾跡]]和顆粒物,均有導致氣候變化的作用。全球於2018年的航空營運產生的二氧化碳排放量佔所有碳排放量的2.4%。<ref name="ICCTsep2019">{{cite web |author=Brandon Graver |author2=Kevin Zhang |author3=Dan Rutherford |date=September 2019 |title={{CO2}} emissions from commercial aviation, 2018 |url=https://theicct.org/sites/default/files/publications/ICCT_CO2-commercl-aviation-2018_20190918.pdf |publisher=[[International Council on Clean Transportation]]}}</ref> |
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人類於2020年的活動對氣候的整體影響中約有3.5%來自航空業。該部門於近20年來的排放量翻了一倍,但於全球的排放佔比中並沒有改變,因為其他部門的排放也在增長。<ref>{{cite news |last1=Davidson |first1=Jordan |date=2020-09-04 |title=Aviation Accounts for 3.5% of Global Warming Caused by Humans, New Research Says |agency=Ecowatch |url=https://www.ecowatch.com/aviation-emissions-global-warming-2647461303.html |access-date=2020-09-06}}</ref> |
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客機二氧化碳平均直接排放量(不考慮高空輻射效應)的一些代表性數據,以二氧化碳和每乘客公里二氧化碳當量表示:<ref>{{cite web |title=Average passenger aircraft emissions and energy consumption per passenger kilometre in Finland 2008 |url=http://lipasto.vtt.fi/yksikkopaastot/henkiloliikennee/ilmaliikennee/ilmae.htm |url-status=live |archive-url=https://web.archive.org/web/20110719224215/http://lipasto.vtt.fi/yksikkopaastot/henkiloliikennee/ilmaliikennee/ilmae.htm |archive-date=2011-07-19 |access-date=2009-07-03 |website=lipasto.vtt.fi}}</ref> |
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*國內短途,小於463公里(288英里):257克/公里二氧化碳,或259克/公里(14.7盎司/英里)二氧化碳當量 |
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*長途飛行:113克/公里二氧化碳,或114克/公里(6.5盎司/英里)二氧化碳當量 |
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===建築物與營建=== |
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於2018年製造建築材料和維護建築物的二氧化碳排放量佔能源和製程相關排放量的39%。玻璃、水泥和鋼鐵的製造佔能源和製程相關排放量的11%。<ref name="Urge">{{cite journal |last1=Ürge-Vorsatz |first1=Diana |last2=Khosla |first2=Radhika |last3=Bernhardt |first3=Rob |last4=Chan |first4=Yi Chieh |last5=Vérez |first5=David |last6=Hu |first6=Shan |last7=Cabeza |first7=Luisa F. |year=2020 |title=Advances Toward a Net-Zero Global Building Sector |journal=Annual Review of Environment and Resources |volume=45 |pages=227–269 |doi=10.1146/annurev-environ-012420-045843 |doi-access=free|hdl=10459.1/69710 |hdl-access=free }}</ref>由於建築施工是項重大投資,因此到2050年,三分之二以上的現有建築仍將存在。為實現《巴黎協定》的目標,有必要對現有建築進行{{le|改裝|Retrofitting}}以提高效率,僅要求新建建築適用低排放標準無法符合整體需求。<ref>{{cite web |title=Why the building sector? |url=https://architecture2030.org/buildings_problem_why/ |access-date= 2021-04-01 |website=Architecture 2020}}</ref>產生能源與消耗能源一樣多的建築物稱為[[零碳建築]],而產生能源多於消耗的建築無稱為{{le|正能量建築|Energy-plus building}}。{{le|低能耗建築|Low-energy building}}的設計是高效的低能耗和低碳排放 - 其中一種流行的類型是[[被動式節能屋]]。<ref name="Urge" /> |
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建築業在建築性能和能源效率方面在近幾十年來已取得顯著進步。<ref>{{Cite journal |last1=Fowlie |first1=Meredith |last2=Greenstone |first2=Michael |last3=Wolfram |first3=Catherine |date=2018-08-01 |title=Do Energy Efficiency Investments Deliver? Evidence from the Weatherization Assistance Program |url=https://academic.oup.com/qje/article/133/3/1597/4828342 |url-status=live |journal=The Quarterly Journal of Economics |language=en |volume=133 |issue=3 |pages=1597–1644 |doi=10.1093/qje/qjy005 |issn=0033-5533 |archive-url=https://web.archive.org/web/20200607184218/https://academic.oup.com/qje/article/133/3/1597/4828342 |archive-date=2020-06-07 |access-date=2020-11-21}}</ref>[[綠色建築]]可避免排放或是可捕集環境中已存在的碳,而降低建築行業的足跡,例如於建築和景觀美化中使用{{le|麻凝土|hempcrete}}、{{le|纖維素絕緣材料|cellulose fiber insulation}}。<ref>{{Cite web |date=2017-06-23 |title=Sequestering Carbon in Buildings |url=http://www.greenenergytimes.org/2017/06/23/sequestering-carbon-in-buildings/ |access-date=2021-01-22 |website=Green Energy Times |language=en-US}}</ref> |
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全球建築業於2019年排放12吉噸二氧化碳當量。其中95%以上是碳,其餘5%是甲烷、一氧化二氮和[[有機鹵化物]]。<ref>{{Cite web |title=IPCC — Intergovernmental Panel on Climate Change |url=https://www.ipcc.ch/ |access-date=4 April 2022}}</ref> |
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建築部門中最大的排放來源(佔總量的49%)是產生其所需的電力。<ref name=":04">{{Cite book |last=International Energy Agency |url=https://www.iea.org/reports/global-status-report-for-buildings-and-construction-2019 |title=Global Status Report for Buildings and Construction 2019 |publisher=IEA |year=2019 |isbn=978-92-807-3768-4 |location=Paris |author-link=International Energy Agency |access-date=2020-11-20 |archive-url=https://web.archive.org/web/20201126024632/https://www.iea.org/reports/global-status-report-for-buildings-and-construction-2019 |archive-date=2020-11-26 |url-status=live}}</ref> |
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在全球建築業產生的溫室氣體排放中,28%來自鋼鐵、水泥<ref>{{Cite web |title=CoatingsTech - Coatings and Low-carbon Cement Technology |url=https://www.coatingstech-digital.org/coatingstech/library/item/july_2022/4025830/ |access-date=2022-07-07 |website=www.coatingstech-digital.org |language=en}}</ref>和玻璃<ref name=":04" />等建築材料的製造過程中所產生的。鋼鐵和水泥生產會排放大量二氧化碳。例如於2018年,鋼鐵生產佔全球二氧化碳排放量的7%至9%。<ref>{{Cite journal |last1=De Ras |first1=Kevin |last2=Van De Vijver |first2=Ruben |last3=Galvita |first3=Vladimir V. |last4=Marin |first4=Guy B. |last5=Van Geem |first5=Kevin M. |date=2019-12-01 |title=Carbon capture and utilization in the steel industry: challenges and opportunities for chemical engineering |url=https://www.sciencedirect.com/science/article/abs/pii/S221133981930036X |url-status=live |journal=Current Opinion in Chemical Engineering |language=en |volume=26 |pages=81–87 |doi=10.1016/j.coche.2019.09.001 |issn=2211-3398 |s2cid=210619173 |archive-url=https://web.archive.org/web/20210520201639/https://www.sciencedirect.com/science/article/abs/pii/S221133981930036X |archive-date=2021-05-20 |access-date=2021-07-02 |hdl=1854/LU-8635595}}</ref> |
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全球建築業的溫室氣體排放所剩餘的23%是直接在建築現場產生。<ref name=":04" /> |
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====建築業的隱含碳排放==== |
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隱含碳排放(或稱前期碳排放 (upfront carbon emissions(UCE)) 是創建和維護建築材料的結果。<ref name=":03">{{Cite web |last=Alter |first=Lloyd |date= 2019-04-01 |title=Let's rename "Embodied Carbon" to "Upfront Carbon Emissions" |url=https://www.treehugger.com/green-architecture/lets-rename-embodied-carbon-upfront-carbon-emissions.html |url-status=live |archive-url=https://web.archive.org/web/20190401151555/https://www.treehugger.com/green-architecture/lets-rename-embodied-carbon-upfront-carbon-emissions.html |archive-date=2019-04-01 |access-date=2019-08-10 |website=TreeHugger |language=en}}</ref>截至2018年,"隱含碳排放佔全球溫室氣體排放量的11%,佔全球建築業排放量的28%……從現在到2050年,隱含碳排放將佔新建建築排放總量的近一半。" <ref>{{Cite web |title=New Buildings: Embodied Carbon |url=https://architecture2030.org/new-buildings-embodied/ |url-status=live |archive-url=https://web.archive.org/web/20181212173439/https://architecture2030.org/new-buildings-embodied/ |archive-date=2018-12-12 |access-date= 2019-08-10 |website=Architecture 2030 |language=en-US}}</ref> |
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建築材料的開採、加工、製造、運輸和安裝過程中產生的溫室氣體排放被稱為材料的隱含碳排放。<ref>{{Cite journal |last1=Pomponi |first1=Francesco |last2=Moncaster |first2=Alice |date=2016 |title=Embodied carbon mitigation and reduction in the built environment - What does the evidence say? |url=https://www.repository.cam.ac.uk/handle/1810/260832 |url-status=live |journal=Journal of Environmental Management |volume=181 |pages=687–700 |doi=10.1016/j.jenvman.2016.08.036 |pmid=27558830 |archive-url=https://web.archive.org/web/20211120193019/https://www.repository.cam.ac.uk/handle/1810/260832 |archive-date=2021-11-20 |access-date=2021-07-27}}</ref>透過使用低碳材料進行建築結構和飾面、減少拆除以及盡可能重複利用建築物和建築材料,可減少建築項目的隱含碳排放。<ref name=":04" /> |
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===工業流程=== |
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{{see also|混凝土對環境的影響#二氧化碳排放與氣候變化}} |
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截至2020年,位於[[南非]]的[[合成燃料]]工廠{{le|Secunda CTL|Secunda CTL}}是世界上最大的單一排放個體,每年排放5,650萬噸二氧化碳。<ref>{{Cite news |date=2020-03-17 |title=The World's Biggest Emitter of Greenhouse Gases |language=en |work=Bloomberg.com |url=https://www.bloomberg.com/news/features/2020-03-17/south-africa-living-near-the-world-s-biggest-emitting-plant |access-date= 2020-12-29}}</ref> |
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====採礦==== |
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將油井中湧出的天然氣以燃除處理,還有宣洩排放是溫室氣體排放的重要來源。自1970年代約1.1億噸/年的峰值以來,這種排放已下降四分之三,在2004年的排放約佔所有人為排放量的0.5%。<ref>[http://cdiac.esd.ornl.gov/trends/emis/tre_glob.htm Global, Regional, and National CO<sub>2</sub> Emissions] {{webarchive|url=https://web.archive.org/web/20070711043835/http://cdiac.esd.ornl.gov/trends/emis/tre_glob.htm|date=2007-07-11}}. In ''Trends: A Compendium of Data on Global Change'', Marland, G., T.A. Boden, and R. J. Andres, 2005, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee.</ref> |
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[[世界銀行]]估計每年燃除或是洩漏的天然氣量為1,340億立方公尺(2010年數據),相當於德國和法國每年消耗天然氣的總和,這種數量足以供全世界使用16天。燃除的做法高度集中:前10個國家加總佔排放量的70%,前20個國家加總佔85%。<ref>{{cite web |author=<!--Staff writer(s); no by-line.--> |title=Global Gas Flaring Reduction Partnership (GGFR) |url=http://www.worldbank.org/en/programs/gasflaringreduction |url-status=live |archive-url=https://web.archive.org/web/20160826152139/http://www.worldbank.org/en/programs/gasflaringreduction |archive-date= 2016-08-26 |access-date=2016-08-24 |website=worldbank.org |publisher=The [[World Bank]] |quote=previous redirect from web.worldbank.org}}</ref> |
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====鋼和鋁==== |
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鋼鐵和鋁生產這兩個經濟部門是執行[[碳捕集與封存]]的關鍵所在。根據一項在2013年所做的研究,"鋼鐵業於2004年排放的二氧化碳約5.9億噸,佔全球人為溫室氣體排放量的5.2%。鋼鐵生產排放的二氧化碳主要來自燃燒化石燃料,以及使用[[石灰石]]以純化氧化鐵。"<ref>{{cite journal |last1=Tsaia |first1=I-Tsung |last2=Al Alia |first2=Meshayel |last3=El Waddi |first3=Sanaâ |last4=Adnan Zarzourb |first4=aOthman |year=2013 |title=Carbon Capture Regulation for The Steel and Aluminum Industries in the UAE: An Empirical Analysis |journal=Energy Procedia |volume=37 |issue= |pages=7732–7740 |doi=10.1016/j.egypro.2013.06.719 |issn=1876-6102 |oclc=5570078737 |doi-access=free}}</ref> |
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====塑膠==== |
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塑膠主要由化石燃料產出。估計全球溫室氣體排放量的3%至4%,與塑膠的生命週期有關聯。<ref>{{Cite journal |last1=Zheng |first1=Jiajia |last2=Suh |first2=Sangwon |date=May 2019 |title=Strategies to reduce the global carbon footprint of plastics |url=https://escholarship.org/content/qt8pp2t7v8/qt8pp2t7v8.pdf?t=qxd7cq |journal=Nature Climate Change |language=en |volume=9 |issue=5 |pages=374–378 |bibcode=2019NatCC...9..374Z |doi=10.1038/s41558-019-0459-z |issn=1758-6798 |s2cid=145873387|url-access= }}</ref>[[美國國家環境保護局]](EPA)估計<ref>{{cite web |last= |first= |date=2009 |title=The Link Between Plastic Use and Climate Change: Nitty-gritty |url=https://stanfordmag.org/contents/the-link-between-plastic-use-and-climate-change-nitty-gritty |access-date=2021-03-05 |website=stanfordmag.org |publisher= |quote=... According to the EPA, approximately one ounce of carbon dioxide is emitted for each ounce of polyethylene (PET) produced. PET is the type of plastic most commonly used for beverage bottles. ...'}}</ref>每生產一個質量單位的[[聚對苯二甲酸乙二酯]](PET)(最常用於製造飲料瓶的塑膠類),就會排放多達5個質量單位的二氧化碳,<ref name="Plastic Pollution and Climate Change">{{cite web |last1=Glazner |first1=Elizabeth |title=Plastic Pollution and Climate Change |url=http://www.plasticpollutioncoalition.org/pft/2015/11/17/plastic-pollution-and-climate-change |access-date= 2018-08-06 |website=Plastic Pollution Coalition |date= 2017-11-21 }}</ref>與之相關的運輸也會產生溫室氣體。<ref name="What Is the Carbon Footprint of a Plastic Bottle?">{{cite web |last1=Blue |first1=Marie-Luise |title=What Is the Carbon Footprint of a Plastic Bottle? |url=https://sciencing.com/carbon-footprint-plastic-bottle-12307187.html |access-date=2018-08-06 |website=Sciencing |publisher=Leaf Group Ltd}}</ref>塑膠廢棄物降解時會排放二氧化碳。一項於2018年所做的研究聲稱,環境中一些最常見的塑膠在暴露於陽光下時會釋放溫室氣體 - 甲烷和乙烯,其數量之大可能會影響到氣候。<ref name="Production of methane and ethylene from plastic in the environment">{{cite journal |last1=Royer |first1=Sarah-Jeanne |last2=Ferrón |first2=Sara |last3=Wilson |first3=Samuel T. |last4=Karl |first4=David M. |date=1 August 2018 |title=Production of methane and ethylene from plastics in the environment |journal=PLOS ONE |volume=13 |issue=Plastic, Climate Change |pages=e0200574 |bibcode=2018PLoSO..1300574R |doi=10.1371/journal.pone.0200574 |pmc=6070199 |pmid=30067755 |doi-access=free}}</ref><ref name="Study Finds New Reason to Ban Plastic: It Emits Methane in the Sun">{{cite news |last1=Rosane |first1=Olivia |date=2018-08-02 |title=Study Finds New Reason to Ban Plastic: It Emits Methane in the Sun |agency=Ecowatch |issue=Plastic, Climate Change |url=https://www.ecowatch.com/plastic-waste-could-contribute-to-climate-change-2592101036.html |access-date= 2018-08-06}}</ref> |
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由於塑膠比玻璃或金屬更輕,因此運輸塑膠可減少能源消耗。當玻璃或金屬包裝是一次性用途時,改用PET預計可節省52%的運輸能源。 |
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有份《塑膠與氣候》的報告於2019年發佈,稱當年塑膠的生產和焚燒將向大氣排放相當於8.5億噸二氧化碳。按照目前的趨勢,預計到2030年,塑膠的年生命週期溫室氣體排放量將增長至13.4億噸,而到2050年,塑膠的生命週期排放量可能達到560億噸,相當於地球剩餘碳預算的14%。<ref>{{cite web |title=Sweeping New Report on Global Environmental Impact of Plastics Reveals Severe Damage to Climate |url=https://www.ciel.org/news/plasticandclimate/ |access-date=2019-05-16 |website=Center for International Environmental Law (CIEL)}}</ref>報告稱唯有減少消耗才能解決問題,而其他諸如生物可降解塑料、海洋清理、在塑料工業中使用再生能源等措施的收效甚微,在某些情況下甚至可能會讓問題變得更嚴重。<ref>{{cite book |url=https://www.ciel.org/wp-content/uploads/2019/05/Plastic-and-Climate-FINAL-2019.pdf |title=Plastic & Climate The Hidden Costs of a Plastic Planet |date=May 2019 |publisher=Center for International Environmental Law, Environmental Integrity Project, FracTracker Alliance, Global Alliance for Incinerator Alternatives, 5 Gyres, and Break Free From Plastic. |pages=82–85 |access-date=2019-05-20}}</ref> |
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====紙漿和紙張==== |
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{{Further|造紙對環境的影響}} |
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全球印刷和造紙產業約佔二氧化碳排放量的1%。<ref>{{cite web |date=2010 |title=World GHG Emissions Flow Chart |url=http://www.ecofys.com/files/files/asn-ecofys-2013-world-ghg-emissions-flow-chart-2010.pdf |access-date=2018-08-16 |website=Ecofys.com}}</ref>紙漿與造紙工業的溫室氣體排放來自原料生產和運輸、[[污水處理]]設施、外購電力、相關產品運輸、處置和回收,各種流程所消耗的化石燃料。 |
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===各種服務=== |
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====數位服務==== |
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{{see also|串流媒體|資料中心|加密貨幣}} |
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資料中心(不包括加密貨幣挖礦)和資料傳輸於2020年分別消耗全球約1%的電力。<ref name=":02">{{Cite web |title=Data Centres and Data Transmission Networks – Analysis |url=https://www.iea.org/reports/data-centres-and-data-transmission-networks |access-date=2022-03-06 |website=IEA |language=en-GB}}</ref>[[數位經濟]]產生的溫室氣體排放量佔全球排放量的2%至4%,<ref>{{Cite arXiv |eprint=2102.02622 |class=physics.soc-ph |first1=Charlotte |last1=Freitag |first2=Mike |last2=Berners-Lee |title=The climate impact of ICT: A review of estimates, trends and regulations |date=December 2020}}</ref>其中很大部分來自[[半導體元件|晶片]]製造。<ref>{{Cite web |date=2021-09-18 |title=The computer chip industry has a dirty climate secret |url=https://www.theguardian.com/environment/2021/sep/18/semiconductor-silicon-chips-carbon-footprint-climate |access-date= 2021-09-19 |website=the Guardian |language=en}}</ref>然而此部門有減少全球份額較大的其他部門的排放,例如人員移動,<ref>{{Cite web |date=2020-05-19 |title=Working from home is erasing carbon emissions -- but for how long? |url=https://grist.org/climate/working-from-home-is-erasing-carbon-emissions-but-for-how-long/ |access-date= 2021-04-04 |website=Grist |language=en-us}}</ref>可能也包括建築和工業部門。<ref>{{Cite web |last=Cunliff |first=Colin |date= 2020-07-06 |title=Beyond the Energy Techlash: The Real Climate Impacts of Information Technology |url=https://itif.org/publications/2020/07/06/beyond-energy-techlash-real-climate-impacts-information-technology |language=en}}</ref> |
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加密貨幣的挖礦工作需要用到大量電力,會產生大量碳足跡。<ref>{{Cite journal |last=Foteinis |first=Spyros |date=7 February 2018 |title=Bitcoin's alarming carbon footprint |journal=Nature |language=en |volume=554 |issue=7691 |page=169 |bibcode=2018Natur.554..169F |doi=10.1038/d41586-018-01625-x |doi-access=free}}</ref>估計於2016年1月1日至2017年6月30日期間,[[比特幣]]、[[以太坊]]、[[萊特幣]]和[[門羅幣]]等[[區塊鏈]][[工作量證明]](俗稱挖礦)已向大氣排放300萬噸至1,500萬噸二氧化碳。<ref>{{cite journal |last1=Krause |first1=Max J. |last2=Tolaymat |first2=Thabet |date=November 2018 |title=Quantification of energy and carbon costs for mining cryptocurrencies |journal=Nature Sustainability |volume=1 |issue=11 |pages=711–718 |doi=10.1038/s41893-018-0152-7 |bibcode=2018NatSu...1..711K |s2cid=169170289}}</ref>預計到2021年底,比特幣的挖礦將產生6,540萬噸二氧化碳,與[[希臘]]一國所產生的一樣多,<ref>{{cite web |last=Davies |first=Pascale |date=2022-02-26 |title=Bitcoin mining is worse for the environment now since China banned it |url=https://www.euronews.com/next/2022/02/26/bitcoin-mining-was-actually-worse-for-the-environment-since-china-banned-it-a-new-study-sa |access-date=2022-03-01 |website=euronews |language=en}}</ref>每年消耗91至177太瓦時(tWh=10<sup>12</sup>watt-hour)。比特幣是能源效率最低的加密貨幣,每筆交易會耗用707.6千瓦時(kWh=10<sup>3</sup>watt-hour)的電力。<ref>{{cite web |last=Ponciano |first=Jonathan |title=Bill Gates Sounds Alarm On Bitcoin's Energy Consumption–Here's Why Crypto Is Bad For Climate Change |url=https://www.forbes.com/sites/jonathanponciano/2021/03/09/bill-gates-bitcoin-crypto-climate-change/ |access-date=2021-07-30 |website=Forbes |language=en}}</ref><ref>{{Cite news |last1=Huang |first1=Jon |last2=O'Neill |first2=Claire |last3=Tabuchi |first3=Hiroko |author-link=Hiroko Tabuchi |date=2021-09-03 |title=Bitcoin Uses More Electricity Than Many Countries. How Is That Possible? |language=en-US |work=The New York Times |url=https://www.nytimes.com/interactive/2021/09/03/climate/bitcoin-carbon-footprint-electricity.html |access-date=2022-03-01 |issn=0362-4331}}</ref><ref>{{cite web |title=Bitcoin energy consumption worldwide 2017-2021 |url=https://www.statista.com/statistics/881472/worldwide-bitcoin-energy-consumption/ |access-date=2022-03-01 |website=Statista |language=en}}</ref> |
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有項在2015年所做的研究,調查2010年至2030年間全球[[信息及通信技术|資訊及通訊技術]](CT) 的用電量。CT用電量分為四個主要類別:(i) 消費設備,包括[[個人電腦]]、[[行動電話]]、[[電視]]和{{le|家庭娛樂|Home entertainment}}系統、 (ii) 網路基礎設施、 (iii) 資料中心計算與儲存裝置,以及 (iv) 前述類別相關生產。估計在最壞的情況下,2030年的CT電力使用量可能佔全球溫室氣體排放量的23%。<ref>{{Cite journal |last1=Andrae |first1=Anders |last2=Edler |first2=Tomas |date=2015 |title=On Global Electricity Usage of Communication Technology: Trends to 2030 |journal=Challenges |language=en |volume=6 |issue=1 |pages=117–157 |doi=10.3390/challe6010117 |issn=2078-1547|doi-access=free}} [[File:CC-BY icon.svg|50px]] Text was copied from this source, which is available under a [https://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International License]</ref> |
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====醫療保健==== |
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[[醫療保健]]產業產生的溫室氣體排放量佔全球溫室氣體排放量的4.4–4.6%。<ref>{{cite journal |last1=J. Eckelman |first1=Matthew |last2=Huang |first2=Kaixin |last3=Dubrow |first3=Robert |last4=D. Sherman |first4=Jodi |date=December 2020 |title=Health Care Pollution And Public Health Damage In The United States: An Update |journal=Health Affairs |volume=39 |issue=12 |pages=2071–2079 |doi=10.1377/hlthaff.2020.01247 |pmid=33284703 |doi-access=free}}</ref> |
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根據一項於2013年所做的醫療保健產業的生命週期排放量研究,估計與美國與此活動相關的溫室氣體排放每年可能導致額外123,000至381,000個[[失能調整生命年]](DALY)。<ref>{{cite journal |last1=Eckelman |first1=Matthew J. |last2=Sherman |first2=Jodi D. |title=Estimated Global Disease Burden From US Health Care Sector Greenhouse Gas Emissions |journal=American Journal of Public Health |date=April 2018 |volume=108 |issue=S2 |pages=S120–S122 |doi=10.2105/AJPH.2017.303846 |pmid=29072942 |pmc=5922190 |language=en |issn=0090-0036}}</ref> |
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====供水和衛生==== |
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本節摘自{{le|WASH|WASH}}#Reducing greenhouse gas emissions。 |
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現在已有減少由供水和衛生服務產生溫室氣體排放的解決方案。<ref name=":110">{{Cite journal |last1=Howard |first1=Guy |last2=Calow |first2=Roger |last3=Macdonald |first3=Alan |last4=Bartram |first4=Jamie |date=2016 |title=Climate Change and Water and Sanitation: Likely Impacts and Emerging Trends for Action |journal=Annual Review of Environment and Resources |language=en |volume=41 |issue=1 |pages=253–276 |doi=10.1146/annurev-environ-110615-085856 |issn=1543-5938 |doi-access=free |s2cid=155259589}}</ref>這類解決方案分為三類,且有部分重疊:首先是"透過精益和高效的方法減少水和能源消耗"、其次是"擁抱[[循環經濟]]以生產能源和有價值的產品",及第三"透過策略決策規劃減少溫室氣體排放"。<ref name="IWAbook2022">{{Cite book |url=https://iwaponline.com/ebooks/book/850/Reducing-the-Greenhouse-Gas-Emissions-of-Water-and |title=Reducing the Greenhouse Gas Emissions of Water and Sanitation Services: Overview of emissions and their potential reduction illustrated by utility know-how |date=2022 |publisher=IWA Publishing |isbn=978-1-78906-317-2 |editor-last=Alix |editor-first=Alexandre |language=en |doi=10.2166/9781789063172 |s2cid=250128707 |editor-last2=Bellet |editor-first2=Laurent |editor-last3=Trommsdorff |editor-first3=Corinne |editor-last4=Audureau |editor-first4=Iris}}</ref>{{rp|28}}所謂精益和高效的方法包括減少水管網路漏水損失和減少雨水或地下水滲入[[下水道]]的方法等。<ref name="IWAbook2022" />{{rp|29}}此外,透過激勵措施以鼓勵家庭和工業減少用水量和為水加熱的能源需求。<ref name="IWAbook2022" />{{rp|31}}還有另一方法可減少處理原水的能源需求:更好地保護水源的水質。 <ref name="IWAbook2022" />{{rp|32}} |
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====旅遊==== |
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據聯合國環境署稱,全球[[旅遊]]業是大氣中溫室氣體濃度不斷增加的重要因素。<ref>{{cite web |title=Environmental Impacts of Tourism – Global Level |url=http://www.unep.org/resourceefficiency/Business/SectoralActivities/Tourism/TheTourismandEnvironmentProgramme/FactsandFiguresaboutTourism/ImpactsofTourism/EnvironmentalImpacts/EnvironmentalImpactsofTourism-GlobalLevel/tabid/78777/Default.aspx |publisher=UNEP}}</ref> |
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==其他排放特徵== |
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人為氣候變遷的責任因人而異(例如不同的群體之間)。 |
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===依能源類型=== |
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[[File:CO2 Emissions from Electricity Production IPCC.png|thumb|IPCC提供的資料(2014年):不同發電技術生命週期中產生溫室氣體[[中位數]]。<ref name="IPCC 2014 Annex III">{{cite web|title=IPCC Working Group III – Mitigation of Climate Change, Annex III: Technology - specific cost and performance parameters - Table A.III.2 (Emissions of selected electricity supply technologies (gCO 2eq/kWh))|url=https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7|publisher=IPCC|access-date= 2018-12-14|page=1335|year=2014|archive-date=2018-12-14|archive-url=https://web.archive.org/web/20181214164438/https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7|url-status=live}}</ref>]] |
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[[File:UNECE 2020 Lifecycle Emissions.png|thumb|[[聯合國歐洲經濟委員會]]提供歐洲於2020年每生產1千瓦時電力所產生的生命週期溫室氣體排放(克)。<ref name=":0" />]] |
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本節摘自{{le|能源生命週期溫室氣體排放|Life-cycle greenhouse gas emissions of energy sources}}}。 |
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溫室氣體排放是{{le|發電對環境的影響|environmental impacts of electricity generation}}中的一種。衡量能源生命週期溫室氣體排放涉及透過生命週期評估,計算能源的全球暖化潛力,通常只對電能來源做研究,但有時也會評估熱源方面的。<ref>{{Cite web|title=Full lifecycle emissions intensity of global coal and gas supply for heat generation, 2018 – Charts – Data & Statistics|url=https://www.iea.org/data-and-statistics/charts/full-lifecycle-emissions-intensity-of-global-coal-and-gas-supply-for-heat-generation-2018|access-date=2020-07-30|website=IEA|language=en-GB|archive-date=24 June 2020|archive-url=https://web.archive.org/web/20200624021455/https://www.iea.org/data-and-statistics/charts/full-lifecycle-emissions-intensity-of-global-coal-and-gas-supply-for-heat-generation-2018|url-status=live}}</ref>研究結果以該能源產生的每單位電能的全球暖化潛勢為單位,量表使用二氧化碳當量與電能千瓦時 (kWh)表達。此類評估的目標是覆蓋能源的整個生命週期,從材料和燃料開採到施工、營運和廢棄物管理。 |
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IPCC於2014年將全球主要發電來源的二氧化碳當量調查結果作統一處理(透過分析數百篇評估每種能源的獨立科學論文的結果來達成)。<ref name="NREL-LCA1">[http://www.nrel.gov/analysis/sustain_lca_nuclear.html Nuclear Power Results – Life Cycle Assessment Harmonization] {{webarchive|url=https://web.archive.org/web/20130702205635/http://www.nrel.gov/analysis/sustain_lca_nuclear.html |date=2013-07-02 }}, NREL Laboratory, Alliance For Sustainable Energy LLC website, U.S. Department Of Energy, last updated: 2013-01-24.</ref> |
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煤炭是迄今為止排放最高的,其次是天然氣,而[[太陽能]]、[[風能]]和[[核子動力|核能]]均為低碳能源。[[水力發電]]、[[生質燃料|生質能]]、[[地熱能]]和[[海洋能]]通常是低碳的,但設計不當或其他因素可能會導致個別發電廠的排放量更高。 |
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===世代間差異=== |
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研究人員指出老年人在溫室氣體排放上升中扮演"主導角色",並有望成為未來導致溫室氣體排放的最大群體。人口老化、對氣候變化的低知情程度和擔憂,以及高碳產品消費(如在取暖和私人交通<ref>{{cite news |last1=Mel |first1=Svein Inge |title=People over 60 are greenhouse gas emission 'bad guys' |language=en |work=Norwegian University of Science |url=https://phys.org/news/2022-03-people-greenhouse-gas-emission-bad.html |access-date=18 April 2022}}</ref><ref>{{cite journal |last1=Zheng |first1=Heran |last2=Long |first2=Yin |last3=Wood |first3=Richard |last4=Moran |first4=Daniel |last5=Zhang |first5=Zengkai |last6=Meng |first6=Jing |last7=Feng |first7=Kuishuang |last8=Hertwich |first8=Edgar |last9=Guan |first9=Dabo |date=March 2022 |title=Ageing society in developed countries challenges carbon mitigation |url=https://www.researchgate.net/publication/359121007 |journal=Nature Climate Change |language=en |volume=12 |issue=3 |pages=241–248 |bibcode=2022NatCC..12..241Z |doi=10.1038/s41558-022-01302-y |hdl=11250/3027882 |issn=1758-6798 |url-access=subscription |s2cid=247322718|hdl-access=free }}</ref>)等因素均推動此一現象。當今老年人曾歷經氣候變化影響會較日後年輕人預計將遇到的為小,<ref>{{cite journal |last1=Thiery |first1=Wim |last2=Lange |first2=Stefan |last3=Rogelj |first3=Joeri |author3-link=Joeri Rogelj |last4=Schleussner |first4=Carl-Friedrich |last5=Gudmundsson |first5=Lukas |last6=Seneviratne |first6=Sonia I. |last7=Andrijevic |first7=Marina |last8=Frieler |first8=Katja |last9=Emanuel |first9=Kerry |last10=Geiger |first10=Tobias |last11=Bresch |first11=David N. |last12=Zhao |first12=Fang |last13=Willner |first13=Sven N. |last14=Büchner |first14=Matthias |last15=Volkholz |first15=Jan |date=2021-10-08 |title=Intergenerational inequities in exposure to climate extremes |url=https://biblio.vub.ac.be/vubirfiles/75475997/Thiery_etal_2021_Science_postprint.pdf |journal=Science |volume=374 |issue=6564 |pages=158–160 |bibcode=2021Sci...374..158T |doi=10.1126/science.abi7339 |pmid=34565177 |access-date=2021-10-28 |last16=Bauer |first16=Nico |last17=Chang |first17=Jinfeng |last18=Ciais |first18=Philippe |last19=Dury |first19=Marie |last20=François |first20=Louis |last21=Grillakis |first21=Manolis |last22=Gosling |first22=Simon N. |last23=Hanasaki |first23=Naota |last24=Hickler |first24=Thomas |last25=Huber |first25=Veronika |last26=Ito |first26=Akihiko |last27=Jägermeyr |first27=Jonas |last28=Khabarov |first28=Nikolay |last29=Koutroulis |first29=Aristeidis |last30=Liu |first30=Wenfeng |last31=Lutz |first31=Wolfgang |last32=Mengel |first32=Matthias |last33=Müller |first33=Christoph |last34=Ostberg |first34=Sebastian |last35=Reyer |first35=Christopher P. O. |last36=Stacke |first36=Tobias |last37=Wada |first37=Yoshihide |s2cid=237942847|url-access= }}</ref>但他們在選舉决策中仍擁有有和其他人一樣的權利(例如每人一票),這一现象值得深思,因為他們的選擇可能會對下一代應對氣候變化產生深遠的影響。 |
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===依社會經濟階層=== |
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{{multiple image |total_width=450 |
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| image1= 2019 Carbon dioxide emissions by income group - Oxfam data.svg |caption1= 此圖顯示不同收入群體的排放,及其中人均排放。最高收入群體中前10%的排放佔全球所有排放的50%,這群體中人均排放是全球低收入底層50%人均排放的五倍以上。<ref name=OxfamClimateEquality_202311>{{cite book |title=Climate Equality: a Climate for the 99% |date=November 2023 |publisher=Oxfam International |url=https://webassets.oxfamamerica.org/media/documents/cr-climate-equality-201123-en.pdf |archive-url=https://web.archive.org/web/20231123191311/https://webassets.oxfamamerica.org/media/documents/cr-climate-equality-201123-en.pdf |archive-date= 2023-11-23 |url-status=live }} Fig. ES.2, Fig. ES.3, Box 1.2.</ref> |
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|image2=2021 CO2 emissions by income decile - International Energy Agency IEA.svg |caption2=雖然各地高排放區的排放量各不相同,但其組成中的高收入群體排放高於低收入群體的,表現一致。<ref name=IEA_20230222/>全球高收入頂層1%人口的排放量超過低收入底層1%人口1千倍。<ref name=IEA_20230222>{{cite web |last1=Cozzi |first1=Laura |last2=Chen |first2=Olivia |last3=Kim |first3=Hyeji |title=The world's top 1% of emitters produce over 1000 times more {{CO2}} than the bottom 1% |url=https://www.iea.org/commentaries/the-world-s-top-1-of-emitters-produce-over-1000-times-more-co2-than-the-bottom-1 |website=iea.org |publisher=International Energy Agency (IEA) |archive-url=https://web.archive.org/web/20230303032020/https://www.iea.org/commentaries/the-world-s-top-1-of-emitters-produce-over-1000-times-more-co2-than-the-bottom-1 |archive-date=3 March 2023 |date= 2023-02-22 |url-status=live }} "Methodological note: ... The analysis accounts for energy-related CO2, and not other greenhouse gases, nor those related to land use and agriculture."</ref> |
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}} |
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[[File:2021 Carbon dioxide (CO2) emissions per person versus GDP per person - scatter plot.svg |thumb|upright=1.15 |圖示,已開發國家的人均二氧化碳排放遠高於開發中國家的。<ref name=WashPost_20230301>{{cite news |last1=Stevens |first1=Harry |title=The United States has caused the most global warming. When will China pass it? |url=https://www.washingtonpost.com/climate-environment/interactive/2023/global-warming-carbon-emissions-china-us/ |newspaper=The Washington Post |date= 2023-03-01 |archive-url=https://web.archive.org/web/20230301130719/https://www.washingtonpost.com/climate-environment/interactive/2023/global-warming-carbon-emissions-china-us/ |archive-date=2023-03-01 |url-status=live }}</ref>排放數字上升速率大約與GDP等比,但在人均GDP抵達1萬美元後,上升速率開始變緩。 。]] |
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在所得高者[[過度消耗|過度消費]]生活方式推動下,全球最富有的5%人口對全球溫室氣體絕對排放的貢獻率達到37%。可見收入與人均二氧化碳排放量之間存在很強的關聯性。<ref name="auto">{{Cite journal |last1=Ritchie |first1=Hannah |last2=Roser |first2=Max |last3=Rosado |first3=Pablo |date=2020-05-11 |title={{CO2}} and Greenhouse Gas Emissions |url=https://ourworldindata.org/co2-emissions |journal=Our World in Data}}</ref>全球絕對排放量成長的近一半是由最富有的10%人口所造成。<ref>Rapid Transition Alliance, 13 April 2021 [https://www.rapidtransition.org/wp-content/uploads/2021/04/Cambridge-Sustainability-Commission-on-Scaling-behaviour-change-report.pdf "Cambridge Sustainability Commission Report on Scaling Behaviour Change"] {{Webarchive|url=https://web.archive.org/web/20220205165843/https://www.rapidtransition.org/wp-content/uploads/2021/04/Cambridge-Sustainability-Commission-on-Scaling-behaviour-change-report.pdf |date=2022-02-05 }} p. 20</ref>IPCC於2022年發表的報告指出,新興經濟體的窮人和中產階級的生活方式產生的消費量比已開發的高收入國家中高收入階層的,要低約5-50倍。<ref>Emission trends and drivers, Ch 2 in "Climate Change 2022: Mitigation of Climate Change". ''http://www.ipcc.ch''. Retrieved 2022-04-05.</ref><ref name="report.ipcc.ch">[https://report.ipcc.ch/ar6wg3/pdf/IPCC_AR6_WGIII_SummaryForPolicymakers.pdf Climate Change 2022] ipcc.ch{{Webarchive|url=https://web.archive.org/web/20220404160950/https://report.ipcc.ch/ar6wg3/pdf/IPCC_AR6_WGIII_SummaryForPolicymakers.pdf |date= 2022-04-04}}</ref>地區和國家人均排放量的差異部分反映出各自不同的發展階段,但在相似的收入水平下也存在很大差異。人均排放量最高的10%家庭在全球家庭溫室氣體排放量中所佔的比例是超比例的巨大。<ref name="report.ipcc.ch" /> |
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研究發現世界上最富裕的公民對大部分環境影響負有責任,他們必須採取強而有力的行動,才能實現更安全的環境條件。<ref name="10.1038/s41467-020-16941-y">{{cite journal |last1=Wiedmann |first1=Thomas |last2=Lenzen |first2=Manfred |last3=Keyßer |first3=Lorenz T. |last4=Steinberger |first4=Julia K. |date=2020-06-19 |title=Scientists' warning on affluence |journal=Nature Communications |language=en |volume=11 |issue=1 |pages=3107 |bibcode=2020NatCo..11.3107W |doi=10.1038/s41467-020-16941-y |issn=2041-1723 |pmc=7305220 |pmid=32561753}}</ref><ref name="The role of high-socioeconomic-stat">{{cite journal |last1=Nielsen |first1=Kristian S. |last2=Nicholas |first2=Kimberly A. |last3=Creutzig |first3=Felix |last4=Dietz |first4=Thomas |last5=Stern |first5=Paul C. |author3-link=Felix Creutzig |date=2021-09-30 |title=The role of high-socioeconomic-status people in locking in or rapidly reducing energy-driven greenhouse gas emissions |journal=Nature Energy |language=en |volume=6 |issue=11 |pages=1011–1016 |bibcode=2021NatEn...6.1011N |doi=10.1038/s41560-021-00900-y |issn=2058-7546 |s2cid=244191460|doi-access=free }}</ref> |
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根據英國的[[樂施會]]和{{le|斯德哥爾摩環境研究所|Stockholm Environment Institute}}於2020年共同發表的的報告,<ref>{{Cite web |last=Gore |first=Tim |date=2020-09-23 |title=Confronting carbon inequality |url=https://www.oxfam.org/en/research/confronting-carbon-inequality |url-status=live |archive-url=https://web.archive.org/web/20220324062107/https://www.oxfam.org/en/research/confronting-carbon-inequality |archive-date=2022-03-24 |access-date=2022-03-20 |website=Oxfam International |language=en}}</ref><ref>{{cite web |last1=Kartha |first1=Sivan |last2=Kemp-Benedict |first2=Eric |last3=Ghosh |first3=Emily |last4=Nazareth |first4=Anisha |last5=Gore |first5=Tim |date=September 2020 |title=The Carbon Inequality Era: An assessment of the global distribution of consumption emissions among individuals from 1990 to 2015 and beyond |url=https://www.sei.org/wp-content/uploads/2020/09/research-report-carbon-inequality-era.pdf |url-status=live |archive-url=https://web.archive.org/web/20220122094405/http://www.sei.org/wp-content/uploads/2020/09/research-report-carbon-inequality-era.pdf |archive-date= 2022-01-22 |access-date= 2022-05-11 |work=Stockholm Environment Institute}}</ref>從1990年到2015年的25年期間,全球最富有的1%人口造成的碳排放量是最貧窮的50%人口的兩倍。<ref>{{cite news |last1=Clifford |first1=Catherine |date=26 January 2021 |title=The '1%' are the main drivers of climate change, but it hits the poor the hardest: Oxfam report |language=en |work=CNBC |url=https://www.cnbc.com/2021/01/26/oxfam-report-the-global-wealthy-are-main-drivers-of-climate-change.html |url-status=live |access-date=2021-10-28 |archive-url=https://web.archive.org/web/20211028161800/https://www.cnbc.com/2021/01/26/oxfam-report-the-global-wealthy-are-main-drivers-of-climate-change.html |archive-date= 2021-10-28}}</ref><ref>{{cite web |last1=Berkhout |first1=Esmé |last2=Galasso |first2=Nick |last3=Lawson |first3=Max |last4=Rivero Morales |first4=Pablo Andrés |last5=Taneja |first5=Anjela |last6=Vázquez Pimentel |first6=Diego Alejo |date= 2021-01-25 |title=The Inequality Virus |url=https://www.oxfam.org/en/research/inequality-virus |url-status=live |archive-url=https://web.archive.org/web/20211028161802/https://www.oxfam.org/en/research/inequality-virus |archive-date= 2021-10-28 |access-date=2021-10-28 |website=Oxfam International |language=en}}</ref><ref name="UNEmissionsGap">{{cite web |date=2021 |title=Emissions Gap Report 2020 / Executive Summary |url=https://wedocs.unep.org/bitstream/handle/20.500.11822/34438/EGR20ESE.pdf |url-status=live |archive-url=https://web.archive.org/web/20210731143517/https://wedocs.unep.org/bitstream/handle/20.500.11822/34438/EGR20ESE.pdf |archive-date=2021-07-31 |website=United Nations Environment Programme |at=p. XV Fig. ES.8}}</ref>在此期間,兩者分別佔累計排放量的15%和7%。<ref>{{cite web |last1=Paddison |first1=Laura |date= 2021-10-28 |title=How the rich are driving climate change |url=https://www.bbc.com/future/article/20211025-climate-how-to-make-the-rich-pay-for-their-carbon-emissions |url-status=live |archive-url=https://web.archive.org/web/20211105220537/https://www.bbc.com/future/article/20211025-climate-how-to-make-the-rich-pay-for-their-carbon-emissions |archive-date= 2021-11-05 |access-date=2021-11-07 |work=BBC |language=en}}</ref>處於底層的一半人口直接造成不到20%的能源足跡,且按貿易修正後的能源消耗量也低於頂層5%的人口。最大的不成比例性被認為是發生在交通領域,例如前10%的人消耗56%的車輛燃料,且進行70%的車輛購買活動。<ref>{{cite journal |last1=Oswald |first1=Yannick |last2=Owen |first2=Anne |last3=Steinberger |first3=Julia K. |date=March 2020 |title=Large inequality in international and intranational energy footprints between income groups and across consumption categories |url=http://eprints.whiterose.ac.uk/156055/3/Submission%2520manuscript%25202.05%2520Y.O.%2520A.O.%2520J.K.S%5B1%5D.pdf |url-status=live |journal=Nature Energy |language=en |volume=5 |issue=3 |pages=231–239 |bibcode=2020NatEn...5..231O |doi=10.1038/s41560-020-0579-8 |issn=2058-7546 |archive-url=https://web.archive.org/web/20211028093113/https://eprints.whiterose.ac.uk/156055/3/Submission%20manuscript%202.05%20Y.O.%20A.O.%20J.K.S%5b1%5d.pdf |archive-date= 2021-10-28 |access-date=2021-11-16 |s2cid=216245301}}</ref>然而,富有的個人通常也是機構股東,通常具有更大的影響力,<ref name="bbc-20200618">{{cite news |last1=Timperley |first1=Jocelyn |title=Who is really to blame for climate change? |language=en |work=www.bbc.com |url=https://www.bbc.com/future/article/20200618-climate-change-who-is-to-blame-and-why-does-it-matter |access-date=2022-06-08}}</ref>有更甚者,億萬富翁也可直接進行遊說、直接財務決策和/或控制公司。 |
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==減少溫室氣體排放的方法== |
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{{see also|{{le|甲烷排放|Methane emissions}}}} |
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各國政府已採取行動以減少溫室氣體排放,緩解氣候變化。 UNFCCC附件一所列國家和地區(即經合組織和前蘇聯計畫經濟體)必須定期向UNFCCC提交其應對氣候變化行動的評估<ref name="2011 UNFCC synthesis of annex I communications"> |
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{{cite book |url=http://unfccc.int/resource/docs/2011/sbi/eng/inf01.pdf |title=Compilation and synthesis of fifth national communications. Executive summary. Note by the secretariat. |publisher=[[United Nations Framework Convention on Climate Change]] (UNFCCC) |year=2011 |location=Geneva (Switzerland) |pages=9–10}} |
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</ref>{{Rp|3}}政府實施的政策包括國家和地區減排目標、提高能源效率、支持能源轉型等。 |
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{{Excerpt|氣候變化緩解|paragraph=1,2|File=no}} |
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==未來排放預測== |
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[[File:Figure 3 from US Energy Information Administration IEO2023 report.png|thumb|圖 3,EIA於2023年10月根據目前可確定的政策干預措施,發佈迄2050年的一系列預測,在低GDP成長情景下,二氧化碳的排放也維持低成長,否則成長越高,排放會大幅升高。<ref name="eia-2023-narrative"/>]] |
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{{see also|{{le|碳預算|Carbon budget}}|氣候變化情景}} |
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{{Excerpt|氣候變化緩解#降低需求|paragraph=1-3|File=No}} |
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2023年10月,[[美國能源資訊管理局]](EIA)於2023年10月根據目前可確定的政策干預措施,發佈迄2050年的一系列預測。<ref name="eia-2023-narrative"> |
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{{cite book |
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| author = EIA |
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| title = International Energy Outlook 2023 |
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| date = October 2023 |
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| publisher = US Energy Information Administration (EIA) |
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| location = Washington DC, USA |
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| url = https://www.eia.gov/outlooks/ieo/pdf/IEO2023_Narrative.pdf |
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| access-date = 2023-10-11 |
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}} Informally describes as a "narrative" and tagged IEO2023. |
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</ref><ref name="eia-2023-landing-page"> |
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{{cite web |
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| author = EIA |
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| title = International Energy Outlook 2023 — Landing page |
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| date = 11 October 2023 |
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| work = US Energy Information Administration (EIA) |
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| location = Washington DC, USA |
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| url = https://www.eia.gov/outlooks/ieo/index.php |
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| access-date = 2023-10-13 |
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}} Landing page. |
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</ref><ref name="csis-2023"> |
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{{cite AV media |
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| author = CSIS |
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| title = US EIA's International Energy Outlook 2023 |
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| date = 11 October 2023 |
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| publisher = Center for Strategic and International Studies (SCIS) |
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| location = Washington DC, USA |
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| url = https://www.youtube.com/watch?v=o0ARuBDrE_o |
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| access-date = 2023-10-13 |
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}} YouTube. Duration: 00:57:12. Includes interview with [[Joseph DeCarolis]]. |
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</ref>預測將排放量浮動,而非將2050年限制僅有[[淨零排放]]。於敏感性分析中將關鍵參數改變,主要是未來GDP的成長(每年2.6%作為參考,分別為1.8%和3.4%),其次是技術學習率、未來原油價格和類似的外源投入。模型結果遠非令人鼓舞。在任何情況下,與能源相關的碳排放總量都沒有低於2022年的水準(見圖3)。 這項探索提供一個基準,顯示需要採取更強有力的氣候行動。 |
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==國家案例== |
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[[File:Ghg-co2-2012.svg|thumb|upright=1.5|2012年全球40大溫室氣體排放國,圖左顯示所有來源,以及排除土地利用及林業相關因素的,圖右顯示人均排放量。{{cite web|url=http://www.wri.org/resources/data-sets/cait-historical-emissions-data-countries-us-states-unfccc |title=World Resources Institute data}}. [[印度尼西亞|印尼]]與[[巴西]]兩國顯示使用化石燃料的巨大效果。]] |
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===國家列表=== |
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{{See also|各國二氧化碳排放量列表|各國人均二氧化碳排放量列表|各國溫室氣體排放量列表|{{le|各國人均溫室氣體排放量列表|List of countries by greenhouse gas emissions per capita}}}} |
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2019年全球最大的五個二氧化碳排放國與地區 - 中國、美國、印度、歐盟27國+英國、俄羅斯和日本,合計佔人口的51%、全球[[國內生產毛額]](GDP)的62.5%、全球化石能源消耗總量中的62%和二氧化碳量總量中的67%。於2019年這五個國家和歐盟27國+英國的排放量和2018年相比,呈現不同的變化:相對增幅最大的是中國(+3.4%),其次是印度(+1.6%)。反而是其餘的發生下降:歐盟27國+英國(-3.8%)、美國(-2.6%)、日本(-2.1%)和俄羅斯(-0.8%)。<ref name=EDGAR/> |
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<div style="float:left; width:50em; height:50em; overflow:auto; border:none"> |
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{|class="wikitable sortable" style="text-align:right;" |
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|+2019年各國使用化石燃料的二氧化碳排放<ref name=EDGAR>{{cite web |title=Fossil {{CO2}} emissions of all world countries - 2020 report |publisher=EDGAR - Emissions Database for Global Atmospheric Research |url=https://edgar.jrc.ec.europa.eu/report_2020}} {{CC-notice|cc=by4|url=https://edgar.jrc.ec.europa.eu/report_2020}}</ref> |
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!國家 !! 總排放量<br />(百萬噸) !! 佔比<br />(%) !! 人均量<br />(噸) !! 每GDP<br />(噸/千元美金) |
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|- |
|- |
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|style="text-align:left;"|Global Total || 38,016.57 || 100.00 || 4.93 || 0.29 |
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!基準年 |
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1750年 |
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![[IPCC第三次評估報告|TAR]]<ref name="tar">{{cite book |url=https://www.ipcc.ch/report/ar3/wg1/ |title=TAR Climate Change 2001: The Scientific Basis |page=358 |contribution=Chapter 6}}</ref> |
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1998年 |
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![[IPCC第四次評估報告|AR4]]<ref name="ar4">{{cite book |url=http://www.ipcc.ch/ipccreports/ar4-wg1.htm |title=AR4 Climate Change 2007: The Physical Science Basis |page=141 |contribution=Chapter 2}}</ref> |
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2005年 |
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![[IPCC第五次評估報告|AR5]]<ref name="ar5" />{{rp|678}} |
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2011年 |
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![[IPCC第六次評估報告|AR6]]<ref name="ar6" />{{rp|4-9}} |
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2019年 |
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|- |
|- |
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|style="text-align:left;"|{{flag|China}} || 11,535.20 || 30.34 || 8.12 || 0.51 |
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|二氧化碳 [ppm] |
|||
|{{ref label|COL|A|A}} |
|||
|1 |
|||
|278 |
|||
|365 '''(1.46)''' |
|||
|379 '''(1.66)''' |
|||
|391 '''(1.82)''' |
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|410 '''(2.16)''' |
|||
|[[File:Mauna_Loa_CO2_monthly_mean_concentration.svg|upright=0.5|frameless]] |
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|- |
|- |
||
|style="text-align:left;"|{{flag|United States}} || 5,107.26 || 13.43 || 15.52 || 0.25 |
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|甲烷 [十億分比,ppb] |
|||
|12.4 |
|||
|28 |
|||
|700 |
|||
|1,745 '''(0.48)''' |
|||
|1,774 '''(0.48)''' |
|||
|1,801 '''(0.48)''' |
|||
|1866 '''(0.54)''' |
|||
|[[File:Mlo_ch4_ts_obs_03437.png|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|[[European Union|EU27]]+UK || 3,303.97 || 8.69 || 6.47 || 0.14 |
|||
|一氧化二氮 [ppb] |
|||
|121 |
|||
|265 |
|||
|270 |
|||
|314 '''(0.15)''' |
|||
|319 '''(0.16)''' |
|||
|324 '''(0.17)''' |
|||
|332 '''(0.21)''' |
|||
|[[File:HATS_Nitrous_Oxide_concentration.png|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|India}} || 2,597.36 || 6.83 || 1.90 || 0.28 |
|||
|[[一氟三氯甲烷]](氟利昂-11) |
|||
|45 |
|||
|4,660 |
|||
|0 |
|||
|268 '''(0.07)''' |
|||
|251 '''(0.063)''' |
|||
|238 '''(0.062)''' |
|||
|226 '''(0.066)''' |
|||
|[[File:Hats_f11_global.png|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Russia}} || 1,792.02 || 4.71 || 12.45 || 0.45 |
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|[[二氟二氯甲烷]](氟利昂-12) |
|||
|100 |
|||
|10,200 |
|||
|0 |
|||
|533 '''(0.17)''' |
|||
|538 '''(0.17)''' |
|||
|528 '''(0.17)''' |
|||
|503 '''(0.18)''' |
|||
|[[File:Hats_f12_global.png|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Japan}} || 1,153.72 || 3.03 || 9.09 || 0.22 |
|||
|[[三氟氯甲烷]](氟利昂-13) |
|||
|640 |
|||
|13,900 |
|||
|0 |
|||
|4 '''(0.001)''' |
|||
| - |
|||
|2.7 '''(0.0007)''' |
|||
|3.28 '''(0.0009)''' |
|||
|[https://agage2.eas.gatech.edu/data_archive/data_figures/monthly/pdf/CFC-13_mm.pdf cfc13] |
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|- |
|- |
||
|style="text-align:left;"|International Shipping || 730.26 || 1.92 || - || - |
|||
|[[1,2,2-三氟-1,1,2-三氯乙烷]](氟利昂-113) |
|||
|85 |
|||
|6,490 |
|||
|0 |
|||
|84 '''(0.03)''' |
|||
|79 '''(0.024)''' |
|||
|74 '''(0.022)''' |
|||
|70 '''(0.021)''' |
|||
|[[File:Hats_f113_global.png|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Germany}} || 702.60 || 1.85 || 8.52 || 0.16 |
|||
|[[1,1,2,2-四氟-1,2-二氯乙烷]](氟利昂-114) |
|||
|190 |
|||
|7,710 |
|||
|0 |
|||
|15 '''(0.005)''' |
|||
| - |
|||
| - |
|||
|16 '''(0.005)''' |
|||
|[https://agage2.eas.gatech.edu/data_archive/data_figures/monthly/pdf/CFC-114_mm.pdf cfc114] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Iran}} || 701.99 || 1.85 || 8.48 || 0.68 |
|||
|[[一氯五氟乙烷]](氟利昂-115) |
|||
|1,020 |
|||
|5,860 |
|||
|0 |
|||
|7 '''(0.001)''' |
|||
| - |
|||
|8.37 '''(0.0017)''' |
|||
|8.67 '''(0.0021)''' |
|||
|[https://agage2.eas.gatech.edu/data_archive/data_figures/monthly/pdf/CFC-115_mm.pdf cfc115] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|South Korea}} || 651.87 || 1.71 || 12.70 || 0.30 |
|||
|[[二氟一氯甲烷]](氟利昂-22) |
|||
|11.9 |
|||
|5,280 |
|||
|0 |
|||
|132 '''(0.03)''' |
|||
|169 '''(0.033)''' |
|||
|213 '''(0.0447)''' |
|||
|247 '''(0.0528)''' |
|||
|[[File:HCFC22_concentration.jpg|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|International Aviation || 627.48 || 1.65 || - || - |
|||
|[[1,1-二氯-1-氟乙烷]](HCFC-141b) |
|||
|9.2 |
|||
|2,550 |
|||
|0 |
|||
|10 '''(0.001)''' |
|||
|18 '''(0.0025)''' |
|||
|21.4 '''(0.0034)''' |
|||
|24.4 '''(0.0039)''' |
|||
|[[File:HCFC141b_concentration.jpg|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Indonesia}} || 625.66 || 1.65 || 2.32 || 0.20 |
|||
|[[1-氯-1,1-二氟乙烷]](HCFC-142b) |
|||
|17.2 |
|||
|5,020 |
|||
|0 |
|||
|11 '''(0.002)''' |
|||
|15 '''(0.0031)''' |
|||
|21.2 '''(0.0040)''' |
|||
|22.3 '''(0.0043)''' |
|||
|[[File:HCFC142b_concentration.jpg|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Saudi Arabia}} || 614.61 || 1.62 || 18.00 || 0.38 |
|||
|[[1,1,1-三氯乙烷]](1,1,1-Trichloroethane) |
|||
|5 |
|||
|160 |
|||
|0 |
|||
|69 '''(0.004)''' |
|||
|19 '''(0.0011)''' |
|||
|6.32 '''(0.0004)''' |
|||
|1.6 '''(0.0001)''' |
|||
|[[File:BK_MC.jpg|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Canada}} || 584.85 || 1.54 || 15.69 || 0.32 |
|||
|[[四氯化碳]](Carbon tetrachloride) |
|||
|26 |
|||
|1,730 |
|||
|0 |
|||
|102 '''(0.01)''' |
|||
|93 '''(0.012)''' |
|||
|85.8 '''(0.0146)''' |
|||
|78 '''(0.0129)''' |
|||
|[[File:Hats_ccl4_global.png|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|South Africa}} || 494.86 || 1.30 || 8.52 || 0.68 |
|||
|[[氟仿]](HFC-23) |
|||
|222 |
|||
|12,400 |
|||
|0 |
|||
|14 '''(0.002)''' |
|||
|18 '''(0.0033)''' |
|||
|24 '''(0.0043)''' |
|||
|32.4 '''(0.0062)''' |
|||
|[[File:HFC-23_mm.png|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Mexico}} || 485.00 || 1.28 || 3.67 || 0.19 |
|||
|[[二氟甲烷]](HFC-32) |
|||
|5.2 |
|||
|677 |
|||
|0 |
|||
| - |
|||
| - |
|||
|4.92 '''(0.0005)''' |
|||
|20 '''(0.0022)''' |
|||
|[[File:BK_HFC32.jpg|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Brazil}} || 478.15 || 1.26 || 2.25 || 0.15 |
|||
|[[五氟乙烷]](HFC-125) |
|||
|28.2 |
|||
|3,170 |
|||
|0 |
|||
| - |
|||
|3.7 '''(0.0009)''' |
|||
|9.58 '''(0.0022)''' |
|||
|29.4 '''(0.0069)''' |
|||
|[[File:HFC125_concentration.jpg|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Australia}} || 433.38 || 1.14 || 17.27 || 0.34 |
|||
|[[1,1,1,2-四氟乙烷]](R-134a) |
|||
|13.4 |
|||
|1,300 |
|||
|0 |
|||
|7.5 '''(0.001)''' |
|||
|35 '''(0.0055)''' |
|||
|62.7 '''(0.0100)''' |
|||
|107.6 '''(0.018)''' |
|||
|[[File:Mauna_Loa_HFC-134a_(CH2FCF3)_concentration.png|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Turkey}} || 415.78 || 1.09 || 5.01 || 0.18 |
|||
|[[1,1,1-三氟乙烷]](R-143a) |
|||
|47.1 |
|||
|4,800 |
|||
|0 |
|||
| - |
|||
| - |
|||
|12.0 '''(0.0019)''' |
|||
|24 '''(0.0040)''' |
|||
|[[File:HFC143a_concentration.jpg|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|United Kingdom}} || 364.91 || 0.96 || 5.45 || 0.12 |
|||
|[[1,1-二氟乙烷]](R-152a ) |
|||
|1.5 |
|||
|138 |
|||
|0 |
|||
|0.5 '''(0.0000)''' |
|||
|3.9 '''(0.0004)''' |
|||
|6.4 '''(0.0006)''' |
|||
|7.1 '''(0.0007)''' |
|||
|[[File:HFC152a_concentration.jpg|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Italy}}, {{flag|San Marino}} and the Holy See || 331.56 || 0.87 || 5.60 || 0.13 |
|||
|[[四氟化碳]] (Freon-14,R 14) |
|||
|50,000 |
|||
|6,630 |
|||
|40 |
|||
|80 '''(0.003)''' |
|||
|74 '''(0.0034)''' |
|||
|79 '''(0.0040)''' |
|||
|85.5 '''(0.0051)''' |
|||
|[[File:Mauna_Loa_Tetrafluoromethane.jpg|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Poland}} || 317.65 || 0.84 || 8.35 || 0.25 |
|||
|[[六氟乙烷]] (PFC-116) |
|||
|10,000 |
|||
|11,100 |
|||
|0 |
|||
|3 '''(0.001)''' |
|||
|2.9 '''(0.0008)''' |
|||
|4.16 '''(0.0010)''' |
|||
|4.85 '''(0.0013)''' |
|||
|[[File:Hexafluoroethane_concentration.jpg|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|France}} and {{flag|Monaco}} || 314.74 || 0.83 || 4.81 || 0.10 |
|||
|[[六氟化硫]](SF<sub>6</sub>) |
|||
|3,200 |
|||
|23,500 |
|||
|0 |
|||
|4.2 '''(0.002)''' |
|||
|5.6 '''(0.0029)''' |
|||
|7.28 '''(0.0041)''' |
|||
|9.95 '''(0.0056)''' |
|||
|[[File:Mauna_Loa_Sulfur_Hexafluoride_concentration.jpg|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Vietnam}} || 305.25 || 0.80 || 3.13 || 0.39 |
|||
|[[硫醯氟]](SO<sub>2</sub>F<sub>2</sub>) |
|||
|36 |
|||
|4,090 |
|||
|0 |
|||
| - |
|||
| - |
|||
|1.71 '''(0.0003)''' |
|||
|2.5 '''(0.0005)''' |
|||
|[[File:SO2F2_mm.png|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Kazakhstan}} || 277.36 || 0.73 || 14.92 || 0.57 |
|||
|[[三氟化氮]](NF<sub>3</sub>) |
|||
|500 |
|||
|16,100 |
|||
|0 |
|||
| - |
|||
| - |
|||
|0.9 '''(0.0002)''' |
|||
|2.05 '''(0.0004)''' |
|||
|[[File:Nitrogen_Trifluoride_concentration.jpg|upright=0.5|frameless]] |
|||
|- |
|- |
||
|style="text-align:left;"|{{flag|Taiwan}} || 276.78 || 0.73 || 11.65 || 0.23 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Thailand}} || 275.06 || 0.72 || 3.97 || 0.21 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Spain}} and Andorra || 259.31 || 0.68 || 5.58 || 0.13 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Egypt}} || 255.37 || 0.67 || 2.52 || 0.22 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Malaysia}} || 248.83 || 0.65 || 7.67 || 0.27 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Pakistan}} || 223.63 || 0.59 || 1.09 || 0.22 |
|||
|- |
|||
|style="text-align:left;"|{{flag|United Arab Emirates}} || 222.61 || 0.59 || 22.99 || 0.34 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Argentina}} || 199.41 || 0.52 || 4.42 || 0.20 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Iraq}} || 197.61 || 0.52 || 4.89 || 0.46 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Ukraine}} || 196.40 || 0.52 || 4.48 || 0.36 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Algeria}} || 180.57 || 0.47 || 4.23 || 0.37 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Netherlands}} || 156.41 || 0.41 || 9.13 || 0.16 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Philippines}} || 150.64 || 0.40 || 1.39 || 0.16 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Bangladesh}} || 110.16 || 0.29 || 0.66 || 0.14 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Venezuela}} || 110.06 || 0.29 || 3.36 || 0.39 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Qatar}} || 106.53 || 0.28 || 38.82 || 0.41 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Czechia}} || 105.69 || 0.28 || 9.94 || 0.25 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Belgium}} || 104.41 || 0.27 || 9.03 || 0.18 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Nigeria}} || 100.22 || 0.26 || 0.50 || 0.10 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Kuwait}} || 98.95 || 0.26 || 23.29 || 0.47 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Uzbekistan}} || 94.99 || 0.25 || 2.90 || 0.40 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Oman}} || 92.78 || 0.24 || 18.55 || 0.67 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Turkmenistan}} || 90.52 || 0.24 || 15.23 || 0.98 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Chile}} || 89.89 || 0.24 || 4.90 || 0.20 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Colombia}} || 86.55 || 0.23 || 1.74 || 0.12 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Romania}} || 78.63 || 0.21 || 4.04 || 0.14 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Morocco}} || 73.91 || 0.19 || 2.02 || 0.27 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Austria}} || 72.36 || 0.19 || 8.25 || 0.14 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Serbia and Montenegro}} || 70.69 || 0.19 || 7.55 || 0.44 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Israel}} and {{flag|Palestine}} || 68.33 || 0.18 || 7.96 || 0.18 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Belarus}} || 66.34 || 0.17 || 7.03 || 0.37 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Greece}} || 65.57 || 0.17 || 5.89 || 0.20 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Peru}} || 56.29 || 0.15 || 1.71 || 0.13 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Singapore}} || 53.37 || 0.14 || 9.09 || 0.10 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Hungary}} || 53.18 || 0.14 || 5.51 || 0.17 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Libya}} || 52.05 || 0.14 || 7.92 || 0.51 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Portugal}} || 48.47 || 0.13 || 4.73 || 0.14 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Myanmar}} || 48.31 || 0.13 || 0.89 || 0.17 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Norway}} || 47.99 || 0.13 || 8.89 || 0.14 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Sweden}} || 44.75 || 0.12 || 4.45 || 0.08 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Hong Kong}} || 44.02 || 0.12 || 5.88 || 0.10 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Finland}} || 43.41 || 0.11 || 7.81 || 0.16 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Bulgaria}} || 43.31 || 0.11 || 6.20 || 0.27 |
|||
|- |
|||
|style="text-align:left;"|{{flag|North Korea}} || 42.17 || 0.11 || 1.64 || 0.36 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Ecuador}} || 40.70 || 0.11 || 2.38 || 0.21 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Switzerland}} and {{flag|Liechtenstein}} || 39.37 || 0.10 || 4.57 || 0.07 |
|||
|- |
|||
|style="text-align:left;"|{{flag|New Zealand}} || 38.67 || 0.10 || 8.07 || 0.18 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Ireland}} || 36.55 || 0.10 || 7.54 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Slovakia}} || 35.99 || 0.09 || 6.60 || 0.20 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Azerbaijan}} || 35.98 || 0.09 || 3.59 || 0.25 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Mongolia}} || 35.93 || 0.09 || 11.35 || 0.91 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Bahrain}} || 35.44 || 0.09 || 21.64 || 0.48 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Bosnia and Herzegovina}} || 33.50 || 0.09 || 9.57 || 0.68 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Trinidad and Tobago}} || 32.74 || 0.09 || 23.81 || 0.90 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Tunisia}} || 32.07 || 0.08 || 2.72 || 0.25 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Denmark}} || 31.12 || 0.08 || 5.39 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Cuba}} || 31.04 || 0.08 || 2.70 || 0.11 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Syria}} || 29.16 || 0.08 || 1.58 || 1.20 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Jordan}} || 28.34 || 0.07 || 2.81 || 0.28 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Sri Lanka}} || 27.57 || 0.07 || 1.31 || 0.10 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Lebanon}} || 27.44 || 0.07 || 4.52 || 0.27 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Dominican Republic}} || 27.28 || 0.07 || 2.48 || 0.14 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Angola}} || 25.82 || 0.07 || 0.81 || 0.12 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Bolivia}} || 24.51 || 0.06 || 2.15 || 0.24 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Sudan}} and {{flag|South Sudan}} || 22.57 || 0.06 || 0.40 || 0.13 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Guatemala}} || 21.20 || 0.06 || 1.21 || 0.15 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Kenya}} || 19.81 || 0.05 || 0.38 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Croatia}} || 19.12 || 0.05 || 4.62 || 0.16 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Estonia}} || 18.50 || 0.05 || 14.19 || 0.38 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Ethiopia}} || 18.25 || 0.05 || 0.17 || 0.07 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Ghana}} || 16.84 || 0.04 || 0.56 || 0.10 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Cambodia}} || 16.49 || 0.04 || 1.00 || 0.23 |
|||
|- |
|||
|style="text-align:left;"|{{flag|New Caledonia}} || 15.66 || 0.04 || 55.25 || 1.67 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Slovenia}} || 15.37 || 0.04 || 7.38 || 0.19 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Nepal}} || 15.02 || 0.04 || 0.50 || 0.15 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Lithuania}} || 13.77 || 0.04 || 4.81 || 0.13 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Côte d'Ivoire}} || 13.56 || 0.04 || 0.53 || 0.10 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Georgia}} || 13.47 || 0.04 || 3.45 || 0.24 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Tanzania}} || 13.34 || 0.04 || 0.22 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Kyrgyzstan}} || 11.92 || 0.03 || 1.92 || 0.35 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Panama}} || 11.63 || 0.03 || 2.75 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Afghanistan}} || 11.00 || 0.03 || 0.30 || 0.13 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Yemen}} || 10.89 || 0.03 || 0.37 || 0.17 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Zimbabwe}} || 10.86 || 0.03 || 0.63 || 0.26 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Honduras}} || 10.36 || 0.03 || 1.08 || 0.19 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Cameroon}} || 10.10 || 0.03 || 0.40 || 0.11 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Senegal}} || 9.81 || 0.03 || 0.59 || 0.18 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Luxembourg}} || 9.74 || 0.03 || 16.31 || 0.14 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Mozambique}} || 9.26 || 0.02 || 0.29 || 0.24 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Moldova}} || 9.23 || 0.02 || 2.29 || 0.27 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Costa Rica}} || 8.98 || 0.02 || 1.80 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|North Macedonia}} || 8.92 || 0.02 || 4.28 || 0.26 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Tajikistan}} || 8.92 || 0.02 || 0.96 || 0.28 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Paraguay}} || 8.47 || 0.02 || 1.21 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Latvia}} || 8.38 || 0.02 || 4.38 || 0.14 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Benin}} || 8.15 || 0.02 || 0.69 || 0.21 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Mauritania}} || 7.66 || 0.02 || 1.64 || 0.33 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Zambia}} || 7.50 || 0.02 || 0.41 || 0.12 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Jamaica}} || 7.44 || 0.02 || 2.56 || 0.26 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Cyprus}} || 7.41 || 0.02 || 6.19 || 0.21 |
|||
|- |
|||
|style="text-align:left;"|{{flag|El Salvador}} || 7.15 || 0.02 || 1.11 || 0.13 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Botswana}} || 7.04 || 0.02 || 2.96 || 0.17 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Brunei}} || 7.02 || 0.02 || 15.98 || 0.26 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Laos}} || 6.78 || 0.02 || 0.96 || 0.12 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Uruguay}} || 6.56 || 0.02 || 1.89 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Armenia}} || 5.92 || 0.02 || 2.02 || 0.15 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Curaçao}} || 5.91 || 0.02 || 36.38 || 1.51 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Nicaragua}} || 5.86 || 0.02 || 0.92 || 0.17 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Congo}} || 5.80 || 0.02 || 1.05 || 0.33 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Albania}} || 5.66 || 0.01 || 1.93 || 0.14 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Uganda}} || 5.34 || 0.01 || 0.12 || 0.06 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Namibia}} || 4.40 || 0.01 || 1.67 || 0.18 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Mauritius}} || 4.33 || 0.01 || 3.41 || 0.15 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Madagascar}} || 4.20 || 0.01 || 0.16 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Papua New Guinea}} || 4.07 || 0.01 || 0.47 || 0.11 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Iceland}} || 3.93 || 0.01 || 11.53 || 0.19 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Puerto Rico}} || 3.91 || 0.01 || 1.07 || 0.04 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Barbados}} || 3.83 || 0.01 || 13.34 || 0.85 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Burkina Faso}} || 3.64 || 0.01 || 0.18 || 0.08 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Haiti}} || 3.58 || 0.01 || 0.32 || 0.18 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Gabon}} || 3.48 || 0.01 || 1.65 || 0.11 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Equatorial Guinea}} || 3.47 || 0.01 || 2.55 || 0.14 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Réunion}} || 3.02 || 0.01 || 3.40 || - |
|||
|- |
|||
|style="text-align:left;"|{{flag|Democratic Republic of the Congo}} || 2.98 || 0.01 || 0.03 || 0.03 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Guinea}} || 2.92 || 0.01 || 0.22 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Togo}} || 2.85 || 0.01 || 0.35 || 0.22 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Bahamas}} || 2.45 || 0.01 || 6.08 || 0.18 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Niger}} || 2.36 || 0.01 || 0.10 || 0.08 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Bhutan}} || 2.12 || 0.01 || 2.57 || 0.24 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Suriname}} || 2.06 || 0.01 || 3.59 || 0.22 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Martinique}} || 1.95 || 0.01 || 5.07 || - |
|||
|- |
|||
|style="text-align:left;"|{{flag|Guadeloupe}} || 1.87 || 0.00 || 4.17 || - |
|||
|- |
|||
|style="text-align:left;"|{{flag|Malawi}} || 1.62 || 0.00 || 0.08 || 0.08 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Guyana}} || 1.52 || 0.00 || 1.94 || 0.20 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Sierra Leone}} || 1.40 || 0.00 || 0.18 || 0.10 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Fiji}} || 1.36 || 0.00 || 1.48 || 0.11 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Palau}} || 1.33 || 0.00 || 59.88 || 4.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Macao}} || 1.27 || 0.00 || 1.98 || 0.02 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Liberia}} || 1.21 || 0.00 || 0.24 || 0.17 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Rwanda}} || 1.15 || 0.00 || 0.09 || 0.04 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Eswatini}} || 1.14 || 0.00 || 0.81 || 0.11 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Djibouti}} || 1.05 || 0.00 || 1.06 || 0.20 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Seychelles}} || 1.05 || 0.00 || 10.98 || 0.37 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Malta}} || 1.04 || 0.00 || 2.41 || 0.05 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Mali}} || 1.03 || 0.00 || 0.05 || 0.02 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Cabo Verde}} || 1.02 || 0.00 || 1.83 || 0.26 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Somalia}} || 0.97 || 0.00 || 0.06 || 0.57 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Maldives}} || 0.91 || 0.00 || 2.02 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Chad}} || 0.89 || 0.00 || 0.06 || 0.04 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Aruba}} || 0.78 || 0.00 || 7.39 || 0.19 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Eritrea}} || 0.75 || 0.00 || 0.14 || 0.08 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Lesotho}} || 0.75 || 0.00 || 0.33 || 0.13 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Gibraltar}} || 0.69 || 0.00 || 19.88 || 0.45 |
|||
|- |
|||
|style="text-align:left;"|{{flag|French Guiana}} || 0.61 || 0.00 || 2.06 || - |
|||
|- |
|||
|style="text-align:left;"|{{flag|French Polynesia}} || 0.60 || 0.00 || 2.08 || 0.10 |
|||
|- |
|||
|style="text-align:left;"|{{flag|The Gambia}} || 0.59 || 0.00 || 0.27 || 0.11 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Greenland}} || 0.54 || 0.00 || 9.47 || 0.19 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Antigua and Barbuda}} || 0.51 || 0.00 || 4.90 || 0.24 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Central African Republic}} || 0.49 || 0.00 || 0.10 || 0.11 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Guinea-Bissau}} || 0.44 || 0.00 || 0.22 || 0.11 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Cayman Islands}} || 0.40 || 0.00 || 6.38 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Timor-Leste}} || 0.38 || 0.00 || 0.28 || 0.10 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Belize}} || 0.37 || 0.00 || 0.95 || 0.14 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Bermuda}} || 0.35 || 0.00 || 5.75 || 0.14 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Burundi}} || 0.34 || 0.00 || 0.03 || 0.04 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Saint Lucia}} || 0.30 || 0.00 || 1.65 || 0.11 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Western Sahara}} || 0.30 || 0.00 || 0.51 || - |
|||
|- |
|||
|style="text-align:left;"|{{flag|Grenada}} || 0.23 || 0.00 || 2.10 || 0.12 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Comoros}} || 0.21 || 0.00 || 0.25 || 0.08 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Saint Kitts and Nevis}} || 0.19 || 0.00 || 3.44 || 0.14 |
|||
|- |
|||
|style="text-align:left;"|{{flag|São Tomé and Príncipe}} || 0.16 || 0.00 || 0.75 || 0.19 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Saint Vincent and the Grenadines}} || 0.15 || 0.00 || 1.32 || 0.11 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Samoa}} || 0.14 || 0.00 || 0.70 || 0.11 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Solomon Islands}} || 0.14 || 0.00 || 0.22 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Tonga}} || 0.13 || 0.00 || 1.16 || 0.20 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Turks and Caicos Islands}} || 0.13 || 0.00 || 3.70 || 0.13 |
|||
|- |
|||
|style="text-align:left;"|{{flag|British Virgin Islands}} || 0.12 || 0.00 || 3.77 || 0.17 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Dominica}} || 0.10 || 0.00 || 1.38 || 0.12 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Vanuatu}} || 0.09 || 0.00 || 0.30 || 0.09 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Saint Pierre and Miquelon}} || 0.06 || 0.00 || 9.72 || - |
|||
|- |
|||
|style="text-align:left;"|{{flag|Cook Islands}} || 0.04 || 0.00 || 2.51 || - |
|||
|- |
|||
|style="text-align:left;"|{{flag|Falkland Islands}} || 0.03 || 0.00 || 10.87 || - |
|||
|- |
|||
|style="text-align:left;"|{{flag|Kiribati}} || 0.03 || 0.00 || 0.28 || 0.13 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Anguilla}} || 0.02 || 0.00 || 1.54 || 0.12 |
|||
|- |
|||
|style="text-align:left;"|{{flag|Saint Helena}}, {{flag|Ascension}} and {{flag|Tristan da Cunha}} || 0.02 || 0.00 || 3.87 || - |
|||
|- |
|||
|style="text-align:left;"|{{flag|Faroe Islands}} || 0.00 || 0.00 || 0.04 || 0.00 |
|||
|} |
|} |
||
</div> |
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<sup>a</sup>莫耳分率:μmol/mol = ppm = 百萬分之一 (106)、nmol/mol = ppb = 十億分之一 (109)、pmol/mol = ppt = 兆分之一 (1012)。 |
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{{note label|COL|A|A}}IPCC表示對二氧化碳而言,"無法給予單一的大氣壽命數字"。<ref name="ar5" />{{rp|731}}主要是由於人類在化石碳的開採和燃燒對地球碳循環造成極快速增長以及累積的擾動。<ref>Friedlingstein, P., Jones, M., O'Sullivan, M., Andrew, R., Hauck, J., Peters, G., Peters, W., Pongratz, J., Sitch, S., Le Quéré, C. and 66 others (2019) "Global carbon budget 2019". ''Earth System Science Data'', '''11'''(4): 1783–1838. {{doi|10.5194/essd-11-1783-2019}}</ref>根據AR5評估中引用{le|耦合氣候模式比對專案|Coupled model intercomparison project}}(CMIP)的模擬,截至2014年,化石二氧化碳排放量在現有大氣濃度之上,理論上有10至100吉噸碳的增量,預計有50%將在不到一個世紀的時間內會被陸地[[植被]]和海洋的碳庫清除。<ref>{{cite book |title=Intergovernmental Panel on Climate Change Fifth Assessment Report - Supplemental Material |page=8SM-16 |chapter=Figure 8.SM.4 |chapter-url=https://www.ipcc.ch/site/assets/uploads/2018/07/WGI_AR5.Chap_.8_SM.pdf}}</ref>預計很大部分(20-35%)將在大氣中保留幾個世紀到幾千年,其持久性分率會隨著增率而增加。<ref>{{cite journal |last=Archer |first=David |year=2009 |title=Atmospheric lifetime of fossil fuel carbon dioxide |url=https://orbi.uliege.be/handle/2268/12933 |journal=Annual Review of Earth and Planetary Sciences |volume=37 |issue=1 |pages=117–34 |bibcode=2009AREPS..37..117A |doi=10.1146/annurev.earth.031208.100206 |hdl=2268/12933}}</ref><ref>{{Cite journal |author=Joos, F. |author2=Roth, R. |author3=Fuglestvedt, J.D. |display-authors=etal |year=2013 |title=Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: A multi-model analysis |url=https://www.atmos-chem-phys.net/13/2793/2013/ |journal=Atmospheric Chemistry and Physics |volume=13 |issue=5 |pages=2793–2825 |doi=10.5194/acpd-12-19799-2012 |doi-access=free |hdl-access=free |hdl=20.500.11850/58316}}</ref> |
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{{note label|ERF|B|B}}表中數值是相對於1750年的。AR6報告中的有效輻射強迫,包括大氣和地表快速調整的影響。<ref>{{Cite journal |author=Hansen, J. |author2=Sato, M. |author3=Ruedy, R. |display-authors=etal |year=2005 |title=Efficacy of Climate Forcings |journal=Journal of Geophysical Research: Atmospheres |volume=119 |issue=D18104 |doi=10.1029/2005JD005776 |doi-access=free|bibcode=2005JGRD..11018104H }}</ref> |
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{{clear}} |
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===影響濃度的因素=== |
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此類氣體於大氣中的濃度由"源"(人類活動和自然系統的氣體排放)和"匯"(通過轉化為不同的化合物或被[[水體]]吸收)之間的平衡決定。<ref>Denman, K.L., G. Brasseur, A. Chidthaisong, P. Ciais, P.M. Cox, R.E. Dickinson, D. Hauglustaine, C. Heinze, E. Holland, D. Jacob, U. Lohmann, S Ramachandran, P.L. da Silva Dias, S.C. Wofsy and X. Zhang, 2007: [https://www.ipcc.ch/site/assets/uploads/2018/02/ar4-wg1-chapter7-1.pdf Chapter 7: Couplings Between Changes in the Climate System and Biogeochemistry]. In: [https://www.ipcc.ch/report/ar4/wg1/ Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change] [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.</ref>{{rp|512}} |
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=== |
===美國=== |
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[[File:1990- Annual greenhouse gas emissions - U.S. - line chart.svg |thumb|upright=1.35 |雖然美國的人均和平均GDP排放有大幅下降,但將其他經濟因素列入考慮,其降幅並不算顯著。<ref name=EPA_GHGemissions_1990_>{{cite web |title=Climate Change Indicators: U.S. Greenhouse Gas Emissions / Figure 3. U.S. Greenhouse Gas Emissions per Capita and per Dollar of GDP, 1990–2020 |url=https://www.epa.gov/climate-indicators/climate-change-indicators-us-greenhouse-gas-emissions |website=EPA.gov |date=2016-06-27 |publisher=U.S. Environmental Protection Agency |archive-url=https://web.archive.org/web/20230405092424/https://www.epa.gov/climate-indicators/climate-change-indicators-us-greenhouse-gas-emissions |archive-date=2023-04-05 |url-status=live}}</ref>]] |
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在指定時間後殘留在大氣中的排放物的比例是"{{le|大氣中分率|Airborne fraction}}(AF)"。年度大氣中分率是某一年大氣增加量與當年總排放量的比率。 |
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截至2006年,二氧化碳的年大氣中分率約為0.45。於1959年至2006年期間,每年的分率增加速度為0.25 ± 0.21%。<ref name="Canadell2007">{{cite journal |author=Canadell, J.G. |author2=Le Quere, C. |author3=Raupach, M.R. |author4=Field, C.B. |author5=Buitenhuis, E.T. |author6=Ciais, P. |author7=Conway, T.J. |author8=Gillett, N.P. |author9=Houghton, R.A. |author10=Marland, G. |year=2007 |title=Contributions to accelerating atmospheric CO<sub>2</sub> growth from economic activity, carbon intensity, and efficiency of natural sinks |journal=Proc. Natl. Acad. Sci. USA |volume=104 |issue=47 |pages=18866–70 |bibcode=2007PNAS..10418866C |doi=10.1073/pnas.0702737104 |pmc=2141868 |pmid=17962418 |doi-access=free}}</ref> |
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本節摘自{{le|美國溫室氣體排放|Greenhouse gas emissions by the United States}}。 |
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====大氣壽命==== |
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[[File:Carbon Dioxide Partitioning.svg|thumb|upright=1.35|根據[[全球碳計劃]]2020年的資料,全球二氧化碳排放中的大部分均被如植物、土壤與海洋的碳匯所吸收。]] |
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美國於2020年產生52億噸二氧化碳當量溫室氣體排放,[<ref>{{Cite web |last=US EPA |first=OAR |date=2017-02-08 |title=Inventory of U.S. Greenhouse Gas Emissions and Sinks |url=https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks |access-date=2022-08-04 |website=www.epa.gov |language=en}}</ref>僅次於中國,位居世界第二,美國是人均溫室氣體排放量最高的國家之一。 估計中國於2019年排放的溫室氣體是全球的27%,其次是美國(佔11%),然後是印度(佔6.6%)。<ref>{{Cite news|date=2021-05-07|title=Report: China emissions exceed all developed nations combined|work=BBC News|url=https://www.bbc.com/news/world-asia-57018837}}</ref>總計美國已排放世界溫室氣體的四分之一,比任何一個國家均多。<ref>{{Cite web|title=Cumulative {{CO2}} emissions globally by country 2018|url=https://www.statista.com/statistics/1007454/cumulative-co2-emissions-worldwide-by-country/|access-date=2021-02-19|website=Statista|language=en}}</ref><ref>{{Cite web|date=2021-10-26|title=The world is still falling short of meeting its climate goals|url=https://www.nationalgeographic.com/environment/article/the-world-is-still-falling-short-of-meeting-its-climate-goals|archive-url=https://web.archive.org/web/20211026221942/https://www.nationalgeographic.com/environment/article/the-world-is-still-falling-short-of-meeting-its-climate-goals|url-status=dead|archive-date=October 26, 2021|access-date=2021-10-28|website=Environment|language=en}}</ref><ref>{{Cite web|title=Who has contributed most to global {{CO2}} emissions?|url=https://ourworldindata.org/contributed-most-global-co2|access-date=2021-12-29|website=Our World in Data}}</ref>人均年排放量超過15噸。<ref>{{Cite journal|date=2020-02-06|title=4 Charts Explain Greenhouse Gas Emissions by Countries and Sectors|url=https://www.wri.org/blog/2020/02/greenhouse-gas-emissions-by-country-sector|access-date=2020-04-29|website=World Resources Institute|language=en|last1=Ge |first1=Mengpin |last2=Friedrich |first2=Johannes |last3=Vigna |first3=Leandro }}</ref>然而[[國際能源署]]估計,美國最富有的十分之一人群每年人均排放超過55噸。<ref>IEA (2023), The world’s top 1% of emitters produce over 1000 times more {{CO2}} than the bottom 1%, IEA, Paris https://www.iea.org/commentaries/the-world-s-top-1-of-emitters-produce-over-1000-times-more-co2-than-the-bottom-1, License: CC BY 4.0</ref>由於燃煤發電廠逐漸關閉,該國於2010年代的發電廠排放量下降,次於交通運輸,交通運輸目前是最大的單一排放源。<ref name="EPA, OA">{{cite web|last=EPA, OA|first=US|date=2015-12-29|title=Sources of Greenhouse Gas Emissions - US EPA|url=https://www.epa.gov/ghgemissions/sources-greenhouse-gas-emissions|access-date=2018-04-19|website=US EPA}}</ref>美國溫室氣體排放量於2020年中有27%來自交通運輸、25%來自電力生產、24%來自工業、13%來自商業和住宅建築,及11%來自農業。<ref name="EPA, OA"/>於2021年,電力業仍是美國第二大溫室氣體排放源,占美國總量的25%。<ref>{{cite web |title=Sources of Greenhouse Gas Emissions |url=https://www.epa.gov/ghgemissions/sources-greenhouse-gas-emissions |website=EPA |access-date=2023-04-28}}</ref>這些溫室氣體排放會加劇美國乃至全世界的氣候變化。 |
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除水蒸氣的大氣壽命約為九天之外,<ref>{{cite web |date= 1995-04-27|title=AGU Water Vapor in the Climate System |url=http://www.eso.org/gen-fac/pubs/astclim/espas/pwv/mockler.html |url-status=live |archive-url=https://web.archive.org/web/20121020163357/http://www.eso.org/gen-fac/pubs/astclim/espas/pwv/mockler.html |archive-date=2012-10-20 |access-date=2011-09-11 |publisher=Eso.org}}</ref>其他主要溫室氣體均混合良好,需要很多年才能離開大氣。<ref name="betts">{{cite book |author=Betts |url=http://www.grida.no/publications/other/ipcc%5Ftar/?src=/climate/ipcc_tar/wg1/218.htm |title=Chapter 6 Radiative Forcing of Climate Change |publisher=UNEP/GRID-Arendal – Publications |year=2001 |series=Working Group I: The Scientific Basis IPCC Third Assessment Report – Climate Change 2001 |contribution=6.3 Well-mixed Greenhouse Gases |access-date=2010-10-16 |archive-url=https://web.archive.org/web/20110629043240/http://www.grida.no/publications/other/ipcc_tar/?src=%2Fclimate%2Fipcc_tar%2Fwg1%2F218.htm |archive-date=2011-06-29 |url-status=dead}}</ref>雖然要準確了解溫室氣體離開大氣層的時間並不容易,但科學界對主要溫室氣體的大氣壽命有做一些估計。 研究人員Jacob (1999年)報告中<ref name="JacobDJ1999">{{cite book |last=Jacob |first=Daniel |url=http://www-as.harvard.edu/people/faculty/djj/book/ |title=Introduction to atmospheric chemistry |publisher=[[Princeton University Press]] |year=1999 |isbn=978-0691001852 |pages=25–26 |archive-url=https://web.archive.org/web/20110902182732/http://www-as.harvard.edu/people/faculty/djj/book/ |archive-date=2011-09-02 |url-status=dead |df=dmy-all}}</ref>提出的定義:大氣化學物質X在單箱[[氣候模型]]中的壽命<math>\tau</math>,即X分子在箱中停留的平均時間。從數學上講,<math>\tau</math>可定義為箱中X的質量<math>m</math>(以公斤為單位)與其去除率之比,去除率是流出箱的X流量(<math>F_\text{out}</math>)、X的化學損失(<math>L</math>)以及X的{{le|析出|Deposition (chemistry)}}(<math>D</math>)(均以公斤/秒(kg/s)為單位)的總和: |
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{{Pie chart| caption=美國不同經濟部門溫室氣體排放組成。<ref>{{cite web |title=Greenhouse Gas Inventory Data Explorer {{!}} US EPA |url=https://cfpub.epa.gov/ghgdata/inventoryexplorer/index.html |website=cfpub.epa.gov |access-date= 2021-04-17 |language=en}}</ref>|other = |value1 = 28.6 |label1 = 交通運輸 |color1=black|value2 = 25.1|label2 = 發電|color2=red|value3 = 22.9|label3 = 工業|color3=blue|value4 = 10.2|label4 = 農業|color4=green|value5 = 6.9|label5 = 商業|value6 = 5.8|label6 = 住宅|value7=0.4|label7=美國區域}} |
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===中國=== |
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<math>\tau = \frac{m}{F_\text{out}+L+D}</math>.<ref name="JacobDJ1999" /> |
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{{multiple image | align = right | direction = horizontal | total_width =500 |
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| image1=20210703 Variwide chart of greenhouse gas emissions per capita by country (includes OTHER).svg | caption1=中國有最高的排放量與相當高的人均排放量。<ref name=ClimateWatch_GHGemissions>{{cite web |title=Historical GHG Emissions / Global Historical Emissions |url=https://www.climatewatchdata.org/ghg-emissions?end_year=2018&start_year=1990 |website=ClimateWatchData.org |publisher=Climate Watch |archive-url=https://web.archive.org/web/20210521225317/https://www.climatewatchdata.org/ghg-emissions?end_year=2018&start_year=1990 |archive-date=21 May 2021 |url-status=live}} ● Population data from {{cite web |title=List of the populations of the world's countries, dependencies, and territories |url=https://www.britannica.com/print/article/2156538 |website=britannica.com |publisher=Encyclopedia Britannica |archive-url=https://web.archive.org/web/20210626134803/https://www.britannica.com/print/article/2156538 |archive-date= 2021-06-26 |url-status=live}}</ref> |
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| image2=20220712 Global economic damage due to greenhouse gas emissions - by country.svg |caption2= 排放累積的結果,美國對於經濟上造成的損害排名第一,中國的排放緊隨其後。<ref name=Guardian_20220712>Chart based on: {{cite news |last1=Milman |first1=Oliver |title=Nearly $2tn of damage inflicted on other countries by US emissions |url=https://www.theguardian.com/environment/2022/jul/12/us-carbon-emissions-greenhouse-gases-climate-crisis |newspaper=The Guardian |date=2022-07-12 |archive-url=https://web.archive.org/web/20220712091602/https://www.theguardian.com/environment/2022/jul/12/us-carbon-emissions-greenhouse-gases-climate-crisis |archive-date=2022-07-12 |url-status=live }} ''Guardian'' cites {{cite journal |last1=Callahan |first1=Christopher W. |last2=Mankin |first2=Justin S. |title=National attribution of historical climate damages |journal=Climatic Change |date=2022-07-12 |volume=172 |issue=40 |page=40 |doi=10.1007/s10584-022-03387-y |bibcode=2022ClCh..172...40C |s2cid=250430339 |doi-access=free }}</ref> |
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如果氣體停止輸入箱中,經過<math>\tau</math>的時間後,箱中的濃度會降低約63%。 |
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}} |
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本節摘自{{le|中國溫室氣體排放量|Greenhouse gas emissions by China}}。 |
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中國的溫室氣體排放量無論在生產或消費方面都是世界上最大的國家,主要來自煤炭燃燒,包括燃煤發電、煤炭開採<ref name=":0x">{{Cite news|url=https://www.theguardian.com/environment/2019/nov/15/methane-emissions-from-coal-mines-could-stoke-climate-crisis-study|title=Methane emissions from coalmines could stoke climate crisis – study|last=Ambrose|first=Jillian|date=2019-11-15|work=The Guardian|access-date=2019-11-15|language=en-GB|issn=0261-3077|archive-url=https://web.archive.org/web/20191115072824/https://www.theguardian.com/environment/2019/nov/15/methane-emissions-from-coal-mines-could-stoke-climate-crisis-study|archive-date=2019-11-15|url-status=live}}</ref>以及使用[[高爐]]生產鋼鐵。<ref>{{Cite web|date=2021-05-20|title=Analysis: China's carbon emissions grow at fastest rate for more than a decade|url=https://www.carbonbrief.org/analysis-chinas-carbon-emissions-grow-at-fastest-rate-for-more-than-a-decade|access-date=2021-07-07|website=Carbon Brief|language=en}}</ref>在衡量生產排放方面,中國於2019年排放超過14億噸二氧化碳當量,<ref>{{Cite web|title=Preliminary 2020 Greenhouse Gas Emissions Estimates for China|url=https://rhg.com/research/preliminary-2020-greenhouse-gas-emissions-estimates-for-china/|access-date=2021-04-25|website=[[Rhodium Group]]|language=en-US}}</ref>佔世界總量的27%。<ref name="bloomberg_2021">{{cite web|url=https://www.bloomberg.com/news/articles/2021-05-06/china-s-emissions-now-exceed-all-the-developed-world-s-combined |title=China's Emissions Now Exceed All the Developed World's Combined |website=Bloomberg |date=6 May 2021 |author=Bloomberg News }}</ref><ref name=":4x">{{Cite web|title={{CO2}} Emissions: China - 2020 - Climate TRACE|url=https://climatetrace.org/inventory|access-date=2021-09-27|website=climatetrace.org|language=en}}</ref>當以基於消費的方式衡量方面,將進口商品相關的排放量計入,並將出口商品相關的排放量剔除,中國的排放量為13吉噸,佔全球排放量的25%。<ref name="rh_2019">{{cite web|url=https://rhg.com/research/chinas-emissions-surpass-developed-countries/ |title=China's Greenhouse Gas Emissions Exceeded the Developed World for the First Time in 2019 |website=Rhodium Group |date= 2021-05-06 |first1=Kate |last1=Larsen |first2=Hannah |last2=Pitt}}</ref> |
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因此估計氣體於大氣中的壽命,是衡量其在大氣中的濃度突然增加或減少後恢復平衡所需的時間。單一原子或分子可能會流失或是沉降到土壤、海洋和其他水域,或是植被和其他生物系統之中,而將過量的濃度降低到與背景濃度相同。實現這一目標所需的平均時間就是平均壽命。 |
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===印度=== |
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二氧化碳的大氣壽命具有變動性,無法精確計算。<ref>{{cite web |date=2005-05-15 |title=How long will global warming last? |url=http://www.realclimate.org/index.php/archives/2005/03/how-long-will-global-warming-last |url-status=live |archive-url=https://web.archive.org/web/20210304213944/http://www.realclimate.org/index.php/archives/2005/03/how-long-will-global-warming-last/ |archive-date= 2021-03-04 |access-date=2012-06-12 |publisher=RealClimate}}</ref><ref name="TableOfWarmingPotentials5" /><ref name="AR6_WGI_AnnexVII" />{{rp|2237}}類似的問題也適用於其他溫室氣體,其中許多氣體的平均壽命比二氧化碳更長,例如二氧化氮的平均大氣壽命為121年。<ref name="TableOfWarmingPotentials5" /> |
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本節摘自{{le|印度氣候變化|Climate change in India }}#§Greenhouse gas emissions。 |
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印度的溫室氣體排放量位居世界第三,主要來源是煤炭。<ref name="CarbonBrief">{{cite web|date=2019-03-14|title=The Carbon Brief Profile: India|url=https://www.carbonbrief.org/the-carbon-brief-profile-india|access-date=2019-09-25|website=Carbon Brief|language=en}}</ref>印度於2016年排放2.8吉噸二氧化碳當量(2.5吉噸,加上[[土地利用、土地利用改變與林業]](LULUCF))。<ref>Government of India (2018) [https://unfccc.int/sites/default/files/resource/INDIA%20SECOND%20BUR%20High%20Res.pdf India Second Biennial Update Report to the United Nations Framework Convention on Climate Change]</ref><ref name=":9x">{{cite web|title=India: Third Biennial Update Report to The United Nations Framework Convention on Climate Change|url=https://unfccc.int/sites/default/files/resource/INDIA_%20BUR-3_20.02.2021_High.pdf|url-status=live|archive-url=https://web.archive.org/web/20210227192140/https://unfccc.int/sites/default/files/resource/INDIA_%20BUR-3_20.02.2021_High.pdf |archive-date=2021-02-27 }}</ref>79%是二氧化碳、4%是甲烷及5%是一氧化二氮。<ref name=":9x" />印度每年排放約3吉噸二氧化碳當量的溫室氣體,人均排放約兩噸,<ref>{{cite web|title=By 2030, Cut Per Capita Emission to Global Average: India to G20|url=https://www.eqmagpro.com/by-2030-cut-per-capita-emission-to-global-average-india-to-g20/|access-date=2021-09-17|website=The Leading Solar Magazine In India|date=2021 -07-26|language=en-US}}</ref>是世界平均的一半。<ref name=":3" />該國的排放量佔全球排放量的7%。<ref name=":1" /> |
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====水蒸氣==== |
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水蒸氣濃度因地區而波動,但人類活動不會直接影響其濃度,但有局部範圍(例如受灌溉田地的附近)會有例外。當全球氣溫因人類活動升高,會增加水蒸氣濃度,根據[[克勞修斯-克拉佩龍方程]],每單位體積會因溫度升高而將有更多的水蒸氣。此過程稱為水蒸氣反饋。<ref name="Held&Soden2000">{{Cite journal |last1=Held |first1=Isaac M. |last2=Soden |first2=Brian J. |date=November 2000 |title=Water vapor feedback and global warming |journal=[[Annual Review of Energy and the Environment]] |language=en |volume=25 |issue=1 |pages=441–475 |citeseerx=10.1.1.22.9397 |doi=10.1146/annurev.energy.25.1.441 |issn=1056-3466 |doi-access=free}}</ref>大氣中的蒸氣濃度變化很大,很大程度上取決於氣溫,從極冷地區的不到0.01%到氣溫在32°C左右地區飽和空氣中的3%(按質量計)。<ref>{{cite book |author=Evans, Kimberly Masters |url=https://archive.org/details/environment00kimm_0 |title=The environment: a revolution in attitudes |publisher=Thomson Gale |year=2005 |isbn=978-0787690823 |location=Detroit |chapter=The greenhouse effect and climate change |chapter-url={{google books |plainurl=y |id=DdtzAAAACAAJ}} |url-access=registration}}</ref> |
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== |
==社會與文化== |
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===COVID-19大流行的影響=== |
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===自然來源=== |
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{{main|2019冠狀病毒病疫情對環境的影響}} |
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大多數溫室氣體都有自然來源及人為來源。有個例外是純由人類造出的合成鹵化碳,此物質無天然來源。在前工業化[[全新世]]期間,當時大氣中不同氣體的濃度大致恆定(大型自然的源和匯之間約略維持平衡)。在工業化時代開始後,人類透過燃燒化石燃料和砍伐森林的活動將溫室氣體大量排放進入大氣。<ref>{{cite web |year=2000 |title=Chapter 3, IPCC Special Report on Emissions Scenarios, 2000 |url=https://ipcc.ch/pdf/special-reports/spm/sres-en.pdf |url-status=live |archive-url=https://web.archive.org/web/20180820085208/http://www.ipcc.ch/pdf/special-reports/spm/sres-en.pdf |archive-date= 2018-08-20 |access-date=2010-10-16 |publisher=Intergovernmental Panel on Climate Change}}</ref><ref name=":0" />{{rp|115}} |
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全球二氧化碳排放量於2020年下降6.4%,即23億噸。<ref name=":21">{{cite journal |vauthors=Tollefson J |date=January 2021 |title=COVID curbed carbon emissions in 2020 - but not by much |journal=Nature |volume=589 |issue=7842 |pages=343 |bibcode=2021Natur.589..343T |doi=10.1038/d41586-021-00090-3 |pmid=33452515 |s2cid=231622354}}</ref>氮氧化物排放量於2020年4月下降高達30%。<ref name=":18">{{cite journal |display-authors=6 |vauthors=Forster PM, Forster HI, Evans MJ, Gidden MJ, Jones CD, Keller CA, Lamboll RD, Quéré CL, Rogelj J, Rosen D, Schleussner CF, Richardson TB, Smith CJ, Turnock ST |date=August 2020 |title=Erratum: Publisher Correction: Current and future global climate impacts resulting from COVID-19 |journal=Nature Climate Change |volume=10 |issue=10 |page=971 |doi=10.1038/s41558-020-0904-z |pmc=7427494 |pmid=32845944}}</ref>在中國,封鎖和其他措施讓煤炭消耗量減少26%,氮氧化物排放量減少50%。.<ref name=":92">{{cite journal |vauthors=Rume T, Islam SM |date=September 2020 |title=Environmental effects of COVID-19 pandemic and potential strategies of sustainability |journal=Heliyon |volume=6 |issue=9 |pages=e04965 |doi=10.1016/j.heliyon.2020.e04965 |pmc=7498239 |pmid=32964165|bibcode=2020Heliy...604965R }}</ref>溫室氣體排放量在疫情後期因許多國家開始取消限制而出現反彈,疫情政策對氣候變化的長期直接影響似可忽略不計。<ref name=":21" /><ref name="effectspaper">{{cite journal |display-authors=6 |vauthors=Forster PM, Forster HI, Evans MJ, Gidden MJ, Jones CD, Keller CA, Lamboll RD, Le Quéré C, Rogelj J, Rosen D, Schleussner CF |date=7 August 2020 |title=Current and future global climate impacts resulting from COVID-19 |journal=Nature Climate Change |language=en |volume=10 |issue=10 |pages=913–919 |bibcode=2020NatCC..10..913F |doi=10.1038/s41558-020-0883-0 |issn=1758-6798 |doi-access=free|url=https://eprints.whiterose.ac.uk/164227/7/Covid_emissions_paperV3_clean_supplementary.pdf }}</ref> |
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===人類活動產生的溫室氣體排放=== |
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[[File:Greenhouse Gas Emissions by Economic Sector.svg|thumb|upright=1.35|根據IPCC於2019年發佈的資料,將所有二氧化碳的直接與間接排放列入考慮,其中工業是最大的排放部門。]] |
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本節摘自{{le|溫室氣體排放#各種氣體來源概述|Greenhouse gas emissions|Overview of main sources}} |
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主要的人為溫室氣體是二氧化碳 、一氧化二氮 、甲烷、三組氟化氣體([[六氟化硫]](SF6)、[[氫氟烴|氫氟碳化合物]](HFC)和[[碳氟化合物]](PFC)。<ref>Dhakal, S., J.C. Minx, F.L. Toth, A. Abdel-Aziz, M.J. Figueroa Meza, K. Hubacek, I.G.C. Jonckheere, Yong-Gun Kim, G.F. Nemet, S. Pachauri, X.C. Tan, T. Wiedmann, 2022: [https://www.ipcc.ch/report/ar6/wg3/downloads/report/IPCC_AR6_WGIII_Chapter02.pdf Chapter 2: Emissions Trends and Drivers]. In IPCC, 2022: [https://www.ipcc.ch/report/ar6/wg3/ Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change] [P.R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA. doi: 10.1017/9781009157926.004</ref>雖然溫室效應在很大程度上是由水蒸氣所驅動,<ref>{{Cite web |date=2023-06-30 |title=Water Vapor |url=https://earthobservatory.nasa.gov/global-maps/MYDAL2_M_SKY_WV |access-date=2023-08-16 |website=earthobservatory.nasa.gov |language=en}}</ref>但人類排放的水蒸氣並不是導致暖化的重要因素。 |
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雖然氯氟碳化合物(CFC)是溫室氣體,但受到《[[蒙特婁議定書]]》的監管,簽訂議定書的動機是因CFC會導致{{le|臭氧層消耗|Ozone depletion}},而非導致全球暖化。臭氧層消耗對暖化的影響很小,但有時媒體會將此兩種過程混為一談。 來自170多個國家的代表於2016年在[[聯合國環境署]]高峰會上達成一項具有法律約束力的協議 - 在《蒙特婁議定書》的{{le|基加利修正案|Kigali Amendment}}中議定要逐步淘汰HFC。 <ref>{{Cite web |last1=Johnston |first1=Chris |last2=Milman |first2=Oliver |last3=Vidal |first3=John |date=2016-10-15 |title=Climate change: global deal reached to limit use of hydrofluorocarbons |url=https://www.theguardian.com/environment/2016/oct/15/climate-change-environmentalists-hail-deal-to-limit-use-of-hydrofluorocarbons |access-date=2018-08-21 |website=[[The Guardian]] |language=en}}</ref><ref>{{cite news |date= 2016-10-15 |title=Climate change: 'Monumental' deal to cut HFCs, fastest growing greenhouse gases |work=BBC News |url=https://www.bbc.co.uk/news/science-environment-37665529 |access-date=2016-10-15}}</ref><ref>{{cite web |date= 2016-10-15 |title=Nations, Fighting Powerful Refrigerant That Warms Planet, Reach Landmark Deal |url=https://www.nytimes.com/2016/10/15/world/africa/kigali-deal-hfc-air-conditioners.html |access-date=2016-10-15 |work=[[The New York Times]]}}</ref>由於CFC-12有消耗臭氧層的特性,已被淘汰(除某些必要用途外)。<ref>{{citation |last1=Vaara |first1=Miska |title=Use of ozone depleting substances in laboratories |url=http://www.norden.org/en/publications/publications/2003-516/ |page=170 |year=2003 |archive-url=https://web.archive.org/web/20110806001547/http://www.norden.org/en/publications/publications/2003-516/ |url-status=dead |publisher=TemaNord |isbn=978-9289308847 |archive-date= 2011-08-06}}</ref>活性較低的[[鹵烷]]也將於2030年完成淘汰。<ref>[[Montreal Protocol]]</ref> |
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==監測== |
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{{Further|{{le|溫室氣體監測|Greenhouse gas monitoring}}|溫室氣體盤查|溫室氣體排放}} |
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溫室氣體監測涉及直接測量溫室氣體排放及數量。有幾種不同方法可用來測量大氣中二氧化碳濃度,包括{{le|紅外線分析法|infrared gas analyzer}}和{{le|測壓法|Pressure measurement}}。甲烷和一氧化二氮則用其他儀器測量。{{le|從太空測量二氧化碳|Space-based measurements of carbon dioxide}}的方法,例如透過[[美國國家航空暨太空總署|NASA}}的{{le|軌道碳觀測站|Orbiting Carbon Observatory}},以及[[衛星地面站]]網絡(例如歐洲的{{le|綜合碳觀測系統|Integrated Carbon Observation System}})。 |
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年度溫室氣體指數 (Annual Greenhouse Gas Index,AGGI) 由[[美國國家海洋暨大氣總署]](NOAA) 的大氣科學家定義為"在有足夠的全球測量數據的任何年份,由於長期存在且充分混合的溫室氣體而產生的總直接輻射強迫與1990年基期的比率"。<ref name="butmon" /><ref>{{cite web |author=LuAnn Dahlman |date= 2020-08-14 |title=Climate change: annual greenhouse gas index |url=https://www.climate.gov/news-features/understanding-climate/climate-change-annual-greenhouse-gas-index |url-status=live |archive-url=https://web.archive.org/web/20130816013542/https://www.climate.gov/news-features/understanding-climate/climate-change-annual-greenhouse-gas-index |archive-date=2013-08-16 |access-date=2020-09-05 |publisher=NOAA Climate.gov science news & Information for a climate smart nation}}</ref>這些輻射強迫水平是相對於1750年的水平(即第一次工業革命開始之前)而言。選擇1990年是因為它是《[[京都議定書]]》的基準年,也是第一個IPCC氣候變化評估報告發佈的年度。 |
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NOAA就此表示,AGGI"衡量出(全球)社會為應對氣候變化所實現的既有承諾。它基於來自世界各地最高品質的大氣觀測數據,具具甚低的誤差。"<ref>{{Cite web |title=The NOAA Annual Greenhouse Gas Index (AGGI) - An Introduction |url=https://www.esrl.noaa.gov/gmd/aggi/ |url-status=live |archive-url=https://web.archive.org/web/20201127013113/https://www.esrl.noaa.gov/gmd/aggi/ |archive-date=2020-11-27 |access-date=2020-09-05 |publisher=[[NOAA]] Global Monitoring Laboratory/Earth System Research Laboratories}}</ref> |
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===資料網絡=== |
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本節摘自{{le|地球大氣中的二氧化碳#資料網絡| Carbon dioxide in Earth's atmosphere#Data networks}}。 |
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== 參見 == |
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有多個地表測量(包括使用容器和連續的[[in situ|原位]]測量點)的網絡,包括NOAA/[[地球系統研究實驗室]](NOAA/ESRL)、<ref>{{Cite web |url=http://www.esrl.noaa.gov/gmd/ccgg/index.html |title=NOAA CCGG page Retrieved 2016-03-02 |access-date=14 March 2023 |archive-date=2011-08-11 |archive-url=https://web.archive.org/web/20110811160744/http://www.esrl.noaa.gov/gmd/ccgg/index.html |url-status=live }}</ref>世界溫室氣體資料中心(WDCGG)、<ref>[http://ds.data.jma.go.jp/gmd/wdcgg/ WDCGG webpage] {{Webarchive|url=https://web.archive.org/web/20160406090043/http://ds.data.jma.go.jp/gmd/wdcgg/|date=2016-04-06}} Retrieved 2016-03-02</ref>和法國的RAMCES。<ref>[http://www.lsce.ispl.fr/ RAMCES webpage] {{dead link|date=November 2016|bot=InternetArchiveBot|fix-attempted=yes}} Retrieved 2016-03-02</ref>NOAA/ESRL的基線觀測站網絡和[[加利福尼亞大學聖地牙哥分校]]的[[斯克里普斯海洋研究所]]網絡<ref>{{Cite web |url=http://cdiac.ornl.gov/trends/co2/ |title=CDIAC CO2 page Retrieved 2016-02-09 |access-date= 2023-03-14 |archive-date=2011-08-13 |archive-url=https://web.archive.org/web/20110813142008/http://cdiac.ornl.gov/trends/co2/ |url-status=live }}</ref>資料由[[橡樹嶺國家實驗室]](ORNL)的{{le|二氧化碳資料分析中心|Carbon Dioxide Information Analysis Center}}(CDIAC)管理。世界溫室氣體資料中心隸屬於{{le|全球大氣觀察|Global Atmosohere Watch}}(GAW,由[[世界氣象組織]]設立),資料由[[氣象廳 (日本)]](JMA)管理。 法國大氣溫室氣體觀測網 (Réseau Atmospherique de Mesure des Composes à Effet de Serre,RAMCES, RAMCES) 隸屬於研究氣候科學的{{le|皮耶爾·西蒙·拉普拉斯研究所 |Institut Pierre Simon Laplace}} (IPSL)。 |
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{{Div col|colwidth=18em}} |
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* [[北極甲烷釋出]] |
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==從大氣中移除溫室氣體== |
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* [[近期氣候變化的歸因]] |
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{{Further|碳匯|碳截存}} |
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* {{le|碳抵銷與碳信用|Carbon offsets and credits}} |
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===自然過程=== |
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* [[碳稅]] |
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{{Further|碳循環}} |
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* {{le|濕地的溫室氣體排放|Greenhouse gas emissions from wetlands}} |
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* [[低碳經濟]] |
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二氧化碳主要經[[光合作用]]由大氣中移除後,進入陸地和海洋的[[生物圈]]。二氧化碳也會直接從大氣溶解進入水體(海洋、湖泊等)中,以及當[[降水]]時被穿過大氣的水滴所吸附。當二氧化碳溶解在水中時,會與水分子反應並形成[[碳酸]],導致[[海洋酸化]]。然後它可經[[風化]]被岩石吸收。它也可經酸化,將接觸到物體表面腐蝕,並被攜帶進入海洋。<ref name="Planet">{{Cite journal |title=Many Planets, One Earth // Section 4: Carbon Cycling and Earth's Climate |url=http://www.learner.org/courses/envsci/unit/text.php?unit=1&secNum=4 |url-status=live |journal=Many Planets, One Earth |volume=4 |archive-url=https://web.archive.org/web/20120417175417/http://www.learner.org/courses/envsci/unit/text.php?unit=1&secNum=4 |archive-date= 2012-04-17 |access-date=2012-06-24 |df=dmy-all}}</ref> |
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* [[淨零排放]] |
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*{{le|世界溫室氣體排放前矛地點及機構列表|list of locations and entities by greenhouse gas emissions}} |
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本節摘自{{le|大氣碳循環|Atmospheric carbon cycle}}。 |
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* {{le|世界能源供應及消耗|World energy supply and consumption}} |
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大氣碳循環涉及地球大氣、海洋和陸地生物圈之間氣態[[碳化合物]](主要是二氧化碳)的交換。它是地球整體碳循環中速度最快的部分之一,每年有超過2,000億噸碳進出大氣層。<ref name=GlobalCarbonCycle>{{Cite journal | last1 = Falkowski | first1 = P. | last2 = Scholes | first2 = R. J. | last3 = Boyle | first3 = E. | last4 = Canadell | first4 = J. | last5 = Canfield | first5 = D. | last6 = Elser | first6 = J. | last7 = Gruber | first7 = N. | last8 = Hibbard | first8 = K. | last9 = Högberg | first9 = P. | last10 = Linder | first10 = S. | last11 = MacKenzie | first11 = F. T. | last12 = Moore III | first12 = B. | last13 = Pedersen | first13 = T. | last14 = Rosenthal | first14 = Y. | last15 = Seitzinger | first15 = S. | last16 = Smetacek | first16 = V. | last17 = Steffen | first17 = W. | title = The Global Carbon Cycle: A Test of Our Knowledge of Earth as a System | doi = 10.1126/science.290.5490.291 | journal = Science | volume = 290 | issue = 5490 | pages = 291–296 | year = 2000 | pmid = 11030643| bibcode = 2000Sci...290..291F }}</ref>只有當這交換之間存在平衡時,大氣中二氧化碳的濃度才能在較長的時間內保持穩定。大氣中甲烷、一氧化碳和其他人造化合物的濃度較小,也是大氣碳循環的一部分。<ref>{{cite web|last1=Riebeek|first1=Holli|title=The Carbon Cycle|url=http://earthobservatory.nasa.gov/Features/CarbonCycle/?src=eoa-features|website=Earth Observatory|publisher=NASA|access-date= 2018-04-05|date= 2011-06-16|archive-url=https://web.archive.org/web/20160305010126/http://earthobservatory.nasa.gov/Features/CarbonCycle/?src=eoa-features|archive-date=2016-03-05|url-status=live|df=dmy-all}}</ref> |
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===負排放=== |
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{{main|二氧化碳移除}} |
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有幾種技術可將大氣中的溫室氣體移除。受到最廣泛研究的是那些去除二氧化碳的方法,或是將其注入地質構造(例如通過[[生物能源與碳捕獲和儲存]]以及[[直接空氣捕獲]]法),<ref name="RoyalSociety">{{cite web |year=2009 |title=Geoengineering the climate: science, governance and uncertainty |url=http://royalsociety.org/displaypagedoc.asp?id=35151 |url-status=dead |archive-url=https://web.archive.org/web/20090907031520/http://royalsociety.org/displaypagedoc.asp?id=35151 |archive-date=2009-09-07 |access-date=2009-09-12 |work=The Royal Society}}</ref>或是於土壤中儲存(如以[[生物炭]]形式)。<ref name="RoyalSociety" />許多長期[[氣候情景]]模型模擬的結果是人類需做大規模的人為負排放措施以避免嚴重的氣候變化。<ref>Fisher, B.S., N. Nakicenovic, K. Alfsen, J. Corfee Morlot, F. de la Chesnaye, J.-Ch. Hourcade, K. Jiang, M. Kainuma, E. La Rovere, A. Matysek, A. Rana, K. Riahi, R. Richels, S. Rose, D. van Vuuren, R. Warren, 2007: [https://www.ipcc.ch/site/assets/uploads/2018/02/ar4-wg3-chapter3-1.pdf Chapter 3: Issues related to mitigation in the long term context], In [https://www.ipcc.ch/report/ar4/wg3/ Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Inter-governmental Panel on Climate Change] [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)], Cambridge University Press, Cambridge,</ref>大氣甲烷的負排放方法也正受到研究,稱為{{le|大氣甲烷移除|atmospheric methane removal}}。<ref>{{Cite journal |last1=Jackson |first1=Robert B. |last2=Abernethy |first2=Sam |last3=Canadell |first3=Josep G. |last4=Cargnello |first4=Matteo |last5=Davis |first5=Steven J. |last6=Féron |first6=Sarah |last7=Fuss |first7=Sabine |last8=Heyer |first8=Alexander J. |last9=Hong |first9=Chaopeng |last10=Jones |first10=Chris D. |last11=Damon Matthews |first11=H. |last12=O'Connor |first12=Fiona M. |last13=Pisciotta |first13=Maxwell |last14=Rhoda |first14=Hannah M. |last15=de Richter |first15=Renaud |date=2021-11-15 |title=Atmospheric methane removal: a research agenda |journal=Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences |language=en |volume=379 |issue=2210 |pages=20200454 |bibcode=2021RSPTA.37900454J |doi=10.1098/rsta.2020.0454 |issn=1364-503X |pmc=8473948 |pmid=34565221}}</ref> |
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==於地質時間尺度== |
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[[File:Phanerozoic Carbon Dioxide.png|thumb|地球於過去5億年的大氣中二氧化碳濃度。|315x315px]] |
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[[File:CO2 40k.png|thumb|自[[末次盛冰期]](約4萬年前){{le|冰河退縮|Deglaciation}}起迄今的大氣中二氧化碳濃度,目前的濃度為此段期間中最高的。]] |
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本節摘自{{le|地球大氣中的二氧化碳#過往地質時期的濃度|Carbon dioxide in Earth's atmosphere#Concentrations in the geologic past}}。 |
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據信二氧化碳於地球47億年歷史中曾在調節地球溫度方面發揮過重要作用。科學家發現在地球誕生的早期有液態水的證據,顯示當時存在一個溫暖的世界,而當時太陽輸出的能量被認為只有今天的70%。早期地球大氣中較高的二氧化碳濃度可能有助於解釋這種[[年輕太陽黯淡佯謬|年輕太陽黯淡悖論]]。當地球最初形成時,大氣層中可能含有更多的溫室氣體,二氧化碳濃度可能更高,估計[[分壓]]高達1,000千帕(1,000[[帕斯卡]],即10[[bar]]),因為那時並無細菌進行光合作用將氣體還原為碳化合物和氧氣。甲烷是一種非常活躍的溫室氣體,當時也可能更為普遍。<ref name="Walker">{{cite journal |last=Walker |first=James C.G. |date=June 1985 |title=Carbon dioxide on the early earth |url=http://deepblue.lib.umich.edu/bitstream/2027.42/43349/1/11084_2005_Article_BF01809466.pdf |journal=Origins of Life and Evolution of the Biosphere |volume=16 |issue=2 |pages=117–27 |bibcode=1985OrLi...16..117W |doi=10.1007/BF01809466 |pmid=11542014 |access-date=2010-01-30 |hdl-access=free |hdl=2027.42/43349 |s2cid=206804461 |archive-date=2012-09-14 |archive-url=https://web.archive.org/web/20120914033408/http://deepblue.lib.umich.edu/bitstream/2027.42/43349/1/11084_2005_Article_BF01809466.pdf |url-status=live }}</ref><ref name="Pavlov">{{cite journal |author1=Pavlov, Alexander A. |author2=Kasting, James F. |author3=Brown, Lisa L. |author4=Rages, Kathy A. |author5=Freedman, Richard |date=May 2000 |title=Greenhouse warming by CH<sub>4</sub> in the atmosphere of early Earth |journal=Journal of Geophysical Research |volume=105 |issue=E5 |pages=11981–90 |bibcode=2000JGR...10511981P |doi=10.1029/1999JE001134 |pmid=11543544 |doi-access=free}}</ref> |
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{{Div col end}} |
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地球的二氧化碳濃度呈現數個變化週期,從全新世和[[更新世]]深度冰期的約180ppm到[[間冰期]]的280ppm。在地球45.4億年的歷史中,二氧化碳濃度有很大的變化。據信二氧化碳在地球形成後不久就存在於地球的第一個大氣層中。第二個大氣層主要由氮氣和二氧化碳組成,是火山爆發的結果,並在巨大[[小行星]]對地球的[[後期重轟炸期]]間產生更多的氣體。<ref name="Zahnle">{{cite journal |last1=Zahnle |first1=K. |last2=Schaefer |first2=L. |author2-link=Laura K. Schaefer |last3=Fegley |first3=B. |year=2010 |title=Earth's Earliest Atmospheres |journal=Cold Spring Harbor Perspectives in Biology |volume=2 |issue=10 |pages=a004895 |doi=10.1101/cshperspect.a004895 |pmc=2944365 |pmid=20573713}}</ref>這類二氧化碳排放中的大部分很快就溶解在水中,之後融入碳酸鹽沉積物中。 |
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==歷史== |
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{{Further|氣候變化科學史|溫室效應#歷史}} |
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[[File:19120814 Coal Consumption Affecting Climate - Rodney and Otamatea Times.jpg | thumb|此發表於1912年的報導清楚描述燃燒煤炭會導致氣候變化。<ref name="Otamatea_Times">{{cite news |date= 1912-08-14 |title=Coal Consumption Affecting Climate |url=https://paperspast.natlib.govt.nz/newspapers/ROTWKG19120814.2.56.5 |work=Rodney and Otamatea Times, Waitemata and Kaipara Gazette |location=Warkworth, New Zealand |page=7}} Text was earlier [[:File:191203 Furnaces of the world - Popular Mechanics - Global warming.jpg|published in ''Popular Mechanics'']], March 1912, p. 341.</ref>]] |
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科學家於19世紀末透過實驗發現<chem>N2</chem>及<chem>O2</chem>不吸收紅外線輻射(當時稱為"暗輻射"),而水(無論是真正的蒸汽或是懸浮在雲中的凝結微小液滴)、二氧化碳及其他的多原子氣態分子都會吸收紅外線輻射。<ref name="CarbonicAcid">{{cite journal |last1=Arrhenius |first1=Svante |date=1896 |title=On the influence of carbonic acid in the air upon the temperature of the ground |url=http://www.rsc.org/images/Arrhenius1896_tcm18-173546.pdf |url-status=live |journal=The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science |volume=41 |issue=251 |pages=237–276 |doi=10.1080/14786449608620846 |archive-url=https://web.archive.org/web/20201118065555/https://www.rsc.org/images/Arrhenius1896_tcm18-173546.pdf |archive-date=2020-11-18 |access-date=2020-12-01}}</ref><ref>{{cite journal |last1=Arrhenius |first1=Svante |year=1897 |title=On the Influence of Carbonic Acid in the Air Upon the Temperature of the Ground |journal=Publications of the Astronomical Society of the Pacific |volume=9 |issue=54 |pages=14 |bibcode=1897PASP....9...14A |doi=10.1086/121158 |doi-access=free}}</ref>研究人員於20世紀初意識到大氣中的溫室氣體會導致地球的整體溫度比無這些氣體時更高。[[瑞典]]氣象學家{{le|尼爾斯·古斯塔夫·埃克霍爾姆 |Nils Gustaf Ekholm}}於1901年首次將"溫室"這個名詞用於描述此現象。<ref>{{cite web |last1=Easterbrook |first1=Steve |date=2015-08-18 |title=Who first coined the term "Greenhouse Effect"? |url=http://www.easterbrook.ca/steve/2015/08/who-first-coined-the-term-greenhouse-effect/ |url-status=live |archive-url=https://web.archive.org/web/20151113131713/http://www.easterbrook.ca/steve/2015/08/who-first-coined-the-term-greenhouse-effect/ |archive-date=2015-11-13 |access-date= 2015-11-11 |website=Serendipity}}</ref><ref>{{cite journal |author=Ekholm N |year=1901 |title=On The Variations Of The Climate Of The Geological And Historical Past And Their Causes |journal=Quarterly Journal of the Royal Meteorological Society |volume=27 |pages=1–62 |bibcode=1901QJRMS..27....1E |doi=10.1002/qj.49702711702 |number=117}}</ref> |
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科學界於20世紀末達成共識:大氣中溫室氣體濃度不斷增加,導致全球氣溫大幅上升,而將氣候系統中其他部分改變,<ref>{{Cite journal |last1=Cook |first1=J. |last2=Nuccitelli |first2=D. |last3=Green |first3=S.A. |last4=Richardson |first4=M. |last5=Winkler |first5=B.R. |last6=Painting |first6=R. |last7=Way |first7=R. |last8=Jacobs |first8=P. |last9=Skuce |first9=A. |year=2013 |title=Quantifying the consensus on anthropogenic global warming in the scientific literature |journal=Environmental Research Letters |volume=8 |issue=2 |page=024024 |bibcode=2013ERL.....8b4024C |doi=10.1088/1748-9326/8/2/024024 |doi-access=free}}</ref>開始對環境和人類健康造成影響。 |
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==其他行星== |
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{{Further|{{le|溫室效應#太陽系地球以外的星體|Greenhouse effect#Bodies other than Earth}}}} |
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溫室氣體也存在於許多星體的大氣中,對[[火星]]、[[土衛六大氣層|土衛六]],特別是擁有深厚大氣層[[金星]]也會產生溫室效應。<ref>{{cite web |author=Eddie Schwieterman |title=Comparing the Greenhouse Effect on Earth, Mars, Venus, and Titan: Present Day and through Time |url=http://www.astro.washington.edu/users/eschwiet/essays/greenhouse_ASTR555.pdf |url-status=dead |archive-url=https://web.archive.org/web/20150130202450/http://www.astro.washington.edu/users/eschwiet/essays/greenhouse_ASTR555.pdf |archive-date=2015-01-30}}</ref>雖然金星上的情況被描述為一種[[失控溫室效應]]造成的終極形式,但由於地球離開太陽的距離比金星為遠,曝露於太陽的亮度不及金星的,由人類造成的溫室氣體濃度增加幾乎無可能引發類似的過程。<ref name="IPCC2009">{{cite report |url=https://www.ipcc.ch/site/assets/uploads/2018/03/inf3-6.pdf |title=Scoping of the IPCC 5th Assessment Report Cross Cutting Issues |work=Thirty-first Session of the IPCC Bali, 26–29 October 2009 |url-status=live |archive-url=https://web.archive.org/web/20091109215503/http://www.ipcc.ch/meetings/session31/inf3.pdf |archive-date=2009 -11-09|access-date=24 March 2019}}</ref>縱然太陽亮度可能增加幾十個百分點,也需要數十億年的時間才能將地球燒烤到如金星般的程度。<ref name="Hansen et al 2013">{{cite journal |last1=Hansen |first1=James |first2=Makiko |last2=Sato |first3=Gary |last3=Russell |first4=Pushker |last4=Kharecha |date=2013 |title=Climate sensitivity, sea level and atmospheric carbon dioxide |journal= Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences |volume=371 |issue=2001 |at=20120294 |bibcode=2013RSPTA.37120294H |doi=10.1098/rsta.2012.0294 |pmid=24043864 |pmc=3785813|arxiv=1211.4846 }}</ref> |
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==參見== |
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{{Portal|Climate change|Environment|Renewable Energy}} |
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{{clear}} |
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{{Columns-list|colwidth=22em| |
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* [[近期氣候變化的歸因]] |
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* [[碳核算]] |
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* {{le|碳預算|Carbon budget}} |
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* [[碳中和]] |
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*[[氣候變化反饋]] |
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* {{le|溫室氣體監測|Greenhouse gas monitoring}} |
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*[[製冷劑列表]] |
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* [[低碳經濟]] |
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}} |
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==參考文獻== |
== 參考文獻 == |
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{{Reflist|2}} |
{{Reflist|2}} |
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==外部連結== |
== 外部連結 == |
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{{Commons category|Greenhouse gas emissions}} |
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* [https://di.unfccc.int/time_series The official greenhouse gas emissions data of developed countries] from the [[UNFCCC]] |
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* {{citation |title=Carbon Dioxide Information Analysis Center (CDIAC) |publisher=U.S. Department of Energy |url=https://cdiac.ess-dive.lbl.gov/ |access-date=2020-07-26}} |
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* [http://www.cmdl.noaa.gov/aggi/ Annual Greenhouse Gas Index (AGGI)] from NOAA |
* [http://www.cmdl.noaa.gov/aggi/ Annual Greenhouse Gas Index (AGGI)] from [[NOAA]] |
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* [http://www.cmdl.noaa.gov/ccgg/iadv/ NOAA CMDL CCGG – Interactive Atmospheric Data Visualization] NOAA {{CO2}} data |
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* [http://www.spectralcalc.com/ Atmospheric spectra of GHGs and other trace gases] {{Webarchive|url=https://web.archive.org/web/20130325100504/http://spectralcalc.com/ |date=25 March 2013 }} |
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* [http://ipcc.ch IPCC Website] |
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** [https://www.ipcc.ch/assessment-report/ar6/ Official IPCC Sixth Assessment Report website] |
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{{模板:全球暖 |
{{模板:全球變暖}} |
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{{Authority control}} |
{{Authority control}} |
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{{World topic|Greenhouse gas emissions by|title=Greenhouse gas emissions by country|noredlinks=yes|state=show}} |
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{{World topic|Climate change in|title=Climate change by country|noredlinks=yes|state=show}} |
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{{DEFAULTSORT:Greenhouse Gas}} |
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{{draft categories| |
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[[分類:溫室氣體| ]] |
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[[分類:包含視頻剪輯的條目]] |
[[分類:包含視頻剪輯的條目]] |
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[[分類:氣候因子]] |
[[分類:氣候因子]] |
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[[分類:氣候變化]] |
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[[Category:Greenhouse gas emissions| ]] |
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}} |
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2024年2月28日 (三) 08:10的版本
人類活動產生的溫室氣體排放(英語:Greenhouse gas emissions)導致溫室效應加劇,造成氣候變化。燃燒煤炭、石油和天然氣等化石燃料產生的二氧化碳 (CO2) 是造成氣候變化最重要的因素之一。全球最大的排放國是中國,接著是美國。而就人均排放量,美國則排名第一。大型石油和天然氣公司的的產品助長人類的排放。人類活動的排放讓大氣中的二氧化碳比第一次工業革命之前的平均水準增加約50%。不同溫室氣體的排放均呈現成長趨勢,但水準各不相同。 2010年代的平均排放量為每年560億噸,高於以前的任何十年期間。[2]在1870年至2017年期間,化石燃料和工業的累積排放總量為425±20吉噸碳(GtC,一吉噸為十億噸) (相當於1,539吉噸二氧化碳(GtCO2)),土地利用、土地利用改變與林業(LULUCF)產生的累積排放量為180±60吉噸碳 (相當於660吉噸二氧化碳)。同一期間的累計排放量,來自土地利用變化(例如森林砍伐)約佔31%,煤炭佔32%,石油佔25%,天然氣佔10%。[3]
二氧化碳是人類活動產生溫室氣體中最主要者,佔導致全球變暖因素的一半以上。甲烷 (CH4) 排放幾乎具有相同的短期影響。[4]相較之下,一氧化二氮 (N2O) 和氟化氣體 (F-氣體) 的作用較小。
發電、供熱和交通運輸是主要排放源,約佔排放量的73%。[5]森林砍伐和土地利用變化也會排放二氧化碳和甲烷。人為甲烷排放的最大來源是農業,緊隨其後的是化石燃料開採時的有意宣洩排放和石化產業的逸散排放。最大的農業甲烷來源是畜養的牲畜。化學肥料是農田土壤排放一氧化二氮的部分原因。同樣的,冷媒中的氟化氣體在人類總排放量中也具有重大的作用。
目前全球的二氧化碳當量排放率為每年人均6.6噸,[6]遠超過根據《巴黎協定》要在2030年將全球升溫控制在1.5°C(2.7°F)之內(相對於工業化前的水準),人均排放必須控制在2.3噸的目標。[7][8][9]已開發國家的人均排放量通常是開發中國家平均量的十倍。[10]
碳足跡(或稱溫室氣體足跡)是種指標,用來比較不同商品或服務的整個生命週期中溫室氣體排放量。[11][12]碳核算(或稱溫室氣體核算)是種方法架構,用來衡量和追蹤不同個體排放溫室氣體的數量。[13]
溫室效應和全球暖化的相關性
溫室效应(英語:Greenhouse effect)是指行星的大氣層因為吸收辐射能量,使得行星表面升溫的效应。由於溫室效应,行星表面溫度會比沒有大氣層時的溫度要高[14][15]。以往認為其機制類似溫室使其中氣溫上昇的機制,故名為「溫室效应」。不少研究指出,人為因素使地球上的温室效应異常加劇,而造成全球暖化的效应。
太阳辐射主要是因為短波辐射,然而地面辐射和大气辐射則是长波辐射。大气对长波辐射的吸收力较强,对短波辐射的吸收力较弱。当太阳光照射到地球上,部分能量被大气吸收,部分被反射回宇宙,大約100%的能量被地球表面吸收,同时地球表面无论昼夜都以红外线的方式向宇宙散发吸收的能量,其中也有部分被大气吸收。
大气层像覆盖玻璃的温室一样,保存了一定的热量,使得地球不至于像没有大气层的月球一样,被太阳照射时温度急剧升高,不受太阳照射时温度急剧下降。一些理論認為,由於溫室氣體的增加,使地球整體所保留的熱能增加,導致全球暖化。张兵
如果沒有溫室效應,地球就會適合人類居住。據估計,如果沒有大氣層,地球表面平均溫度會是−18℃[16]。正是有了温室效应,使地球平均温度维持在15℃,然而当下过多的温室气体导致地球平均温度高于15℃。
目前,人類活動使大氣中温室气体含量增加,由於燃燒化石燃料及水蒸氣、二氧化碳、甲烷等產生排放的氣體,經紅外線輻射吸收留住能量,導致全球表面溫度升高[17],加劇溫室效應,造成全球暖化。为了解決此問題,联合国制定了气候变化框架公约,控制温室气体的排放量,防止地球的溫度上升,影響生態和環境。
各種來源概述
相關氣體
主要人為溫室氣體的來源是二氧化碳 、一氧化二氮 、甲烷、三組氟化氣體(六氟化硫(SF6)、氫氟碳化合物(HFC)和碳氟化合物(PFC)。[19]雖然溫室效應在很大程度上是由水蒸氣所驅動,[20]但人類排放的水蒸氣並不是導致暖化的重要因素。
雖然氯氟碳化合物(CFC)是溫室氣體,但受到《蒙特婁議定書》的監管,簽訂議定書的動機是因CFC會導致臭氧層消耗,而非導致全球暖化。臭氧層消耗對暖化的影響很小,但有時媒體會將此兩種過程混為一談。 來自170多個國家的代表於2016年在聯合國環境署高峰會上達成一項具有法律約束力的協議 - 在《蒙特婁議定書》的基加利修正案中議定要逐步淘汰HFC。 [21][22][23]由於CFC-12有消耗臭氧層的特性,已被淘汰(除某些必要用途外)。[24]活性較低的鹵烷也將於2030年完成淘汰。[25]
人類活動
由化石燃料驅動的工業活動大約從1750年開始顯著增加二氧化碳及其他溫室氣體的排放。第二次世界大戰結束後,全球人口和經濟活動自1950年左右開始持續擴張,排放量迅速增長。截至2021年,測得的大氣中二氧化碳濃度已比工業化前水準高出近50%。[26][27]
人類活動產生的溫室氣體主要來源是:
- 燃燒化石燃料和砍伐森林:估計於2015年排放的人為溫室氣體中,燃燒化石燃料佔62%。[28]最大單一來源是燃煤發電廠,截至2021年,其排放佔比為20%。[29]
- 土地利用變化(主要是源自熱帶地區的森林砍伐) 約佔人為溫室氣體排放總量的四分之一。[30]
- 牲畜腸道發酵和牲畜糞肥管理、[31]水稻種植、土地利用和濕地改變、人造湖泊、[32]輸送管道洩漏以及垃圾掩埋場排放,導致甲烷進入大氣。許多新型全通風化糞池系統可增強發酵過程,也是大氣中甲烷的來源。
- 在製冷系統中使用CFC,在滅火系統和其製造過程中使用PFC和鹵代甲烷。
- 因在農業用地使用化學肥料而排放一氧化二氮。[33]
- 人為甲烷排放的最大來源是農業,緊隨其後的是化石燃料開採中的宣洩排放和逸散排放。[34][35]最大的農業甲烷來源是牲畜。牛是排放量最大的物種,約佔畜牧業排放量的65%。[36]
全球估計
全球每年溫室氣體排放量約為50吉噸,[18]2019年排放的二氧化碳當量估計為57吉噸,其中包括源自土地利用變化而排放的5吉噸。[37]於2019年,人為溫室氣體淨排放總量中約34%(20吉噸二氧化碳當量)來自能源供應部門、24%(14吉噸)來自工業、22%(13吉噸)來自LULUCF、15%(8.7吉噸)來自交通運輸,有6%(3.3吉噸)來自建築物。[38]
目前人均排放率為每人每年6.6噸,[6]遠高於為維持《巴黎協定》限制全球升溫的排放目標。[9]
雖然有時城市被認為是人均甚高的排放源,但城市的人均排放量往往低於其所處國家的平均值。[39]
2017年對排放企業進行的一項調查,發現排名在前100家公司的排放量佔全球直接和間接排放量的71%(參見導致氣候變化名列前茅的公司排名),其中國有企業的排放量佔比達到59%。[40][41]
中國是亞洲,乃至全球最大的排放國:每年排放近100億噸,佔全球排放量的四分之一以上。[42]其他快速成長的排放國包括韓國、伊朗和澳大利亞。另一方面,歐盟中15國和美國的人均排放量隨著時間的演進而逐漸減少。[43]俄羅斯和烏克蘭自1990年以來因經濟結構調整,排放量下降最快。[44]
2015年是全球首見經濟總體有成長,而碳排放卻減少的一年。[45]
高收入國家與低收入國家間比較
工業化國家的年人均排放量通常是開發中國家的十倍。[10]:144由於中國經濟快速發展,其人均年排放量正在迅速接近《京都議定書》附件一國家的水平(即不含美國的已開發國家)。[43]
非洲和南美洲都是相當小的排放區域:各佔全球排放量的3-4%。兩者的排放量幾乎與國際航空業或是航運業所產生的相當。[42]
核算與報告
變數
目前有幾種衡量溫室氣體排放的方法,包括有:[48]
- 涵蓋的地理區域:排放量依地理位置予以歸屬(領土原則),或是依活動原則而將排放歸屬。例如測量從一國到另一國的電力輸入或於國際機場的排放量時,使用兩個原則會導致不同的結果。
- 不同氣體的存在時間長度:給定溫室氣體數量以二氧化碳當量報告。在做計算時會將該氣體在大氣中存在的時間列入考慮。但由於這些氣體在大氣中的複雜交互作用以及產生來源變動,必須定期更新以反映新資訊。
- 測量方式:排放可透過直接測量或是估計來達成。四種主要方法是基於排放因子法、質量平衡法、預測式排放監測系統和連續排放監測系統系統。這些方法在準確性、成本和可用性方面有所不同。由非營利組織及幾家公司組成的機構Climate Trace在2021年聯合國氣候變化大會(第26屆聯合國氣候變遷大會)之前把各個大型工廠的排放以公開資訊方式予以揭露。[49]
各國有時會使用這些測量數據來主張有關氣候變化的政策/道德立場。[50]:94使用不同的措施會導致其中間缺乏可比性,而會在監測目標進度時出現問題。對於採用通用測量工具方面,或在開發不同工具之間的溝通方面仍存在爭議。[48]
報告
排放可經長期追蹤(稱為歷史或是累積排放測量)。這種測量方式提供一些導致大氣中溫室氣體濃度增加的指標。[51]:199
國民帳戶餘額
國民經濟綜合帳戶餘額法是根據一個國家的出口和進口之間的差額來追蹤排放量。對許多富裕國家來說,因為進口商品多於出口商品,導致差額為負數。有此結果主要是由於在此類國家之外生產商品的成本會更低,導致已開發國家的經濟活動越來越依賴提供服務而非商品。有正帳戶餘額表示一個國家有更多生產活動,而有更多營運的工廠會增加碳排放水準。[52]
也可在更短的時間內測量排放量。例如可根據以1990年作為基準年來衡量。《聯合國氣候變化綱要公約》(UNFCCC) 使用1990年作為測量排放量的基準年,《京都議定書》也使用1990年作為基準年(但某有些氣體是從1995年開始測量)。[10]:146, 149一個國家的排放量也可用在特定年份全球排放量中的佔比來報告。
另一種衡量法是人均排放量。將一個國家的年度總排放量除以該國於年中的人口數目。[53]:370人均排放量可能以歷史上或是年度的排放量來表達。[50]:106–107
隱含排放
表達溫室氣體排放歸因的一種方式是測量在消費的商品中隱含的排放。通常衡量排放量是以產量而非以消耗量為之。[54]例如在UNFCCC中,各國報告的是其境內產生的排放(如燃燒化石燃料產生的排放)。[55]:179[56]:1在基於生產的排放核算中,進口貨物的隱含排放歸因於出口國,而非進口國。根據基於消費的排放核算,進口商品的隱含排放歸因於進口國,而非出口國。
二氧化碳排放量的很大部分經由國際貿易而易手。貿易的淨效果是將中國和其他新興市場的排放量出口到美國、日本和西歐的消費者。[56]:4
碳足跡
碳足跡(英語:Carbon footprint,也稱為溫室氣體足跡(英語:Greenhouse gas footprint))指的是由個人、事件、機構、服務、地點或產品產生的溫室氣體 (GHG) 排放總量,以二氧化碳當量 (CO2) 表示。[57]溫室氣體包括含碳氣體如二氧化碳和甲烷,會經由燃燒化石燃料、土地清理以及生產及耗用食品、製成品、材料、木材、道路、建築物、運輸和其他服務而排放。[58]
在大多數情況下,由於對產生過程中複雜的相互作用(包括儲存或釋放二氧化碳的自然過程)了解不足,因此無法對總體碳足跡作準確估計。為此,研究人員Wright、Kemp和Williams提出碳足跡的定義為:
衡量特定人群、系統或活動的二氧化碳和甲烷排放總量(相關人群、系統或活動的空間和時間範圍內所有相關來源、彙整和儲存均列入考慮),採相關百年全球暖化潛勢 (GWP100) 計算所得的二氧化碳當量。[59]
溫室氣體盤查議定書(Greenhouse Gas Protocol)把溫室氣體的範圍予以擴大。
包含《京都議定書》所涵蓋的7種溫室氣體的核算和報告 - 二氧化碳 (CO2)、甲烷 (CH4)、一氧化二氮 (N2O)、氫氟烴 (HFCs)、碳氟化合物 (PCFs)、六氟化硫 (SF6) 和三氟化氮 (NF3)。[60]
全球2014年人均碳足跡約為5公噸二氧化碳當量。[61]計算碳足跡的方法有多種,環保組織大自然保護協會認為美國公民的平均碳足跡為16噸。[62]此數字名列世界最高者之一,[63]導致該國要實施新政策以將其降低。學者們估計紐約市到2050年可把當地建築物的碳足跡消除。根據紐約市的文件和國家統計數據,該市能直接控制的重要做法是把其集中供熱的碳排放消除,此排放佔紐約市報告碳排放量的30%,在能源相關的碳排放量中佔比則為58%。 [64]
家庭碳足跡計算表源自石油生產商BP,這家公司聘請奥美公司開展宣傳活動,把造成氣候變化的責任從企業和機構轉移到個人生活方式之上 - 即人類經自身選擇而導致碳排放,無可避免。 “碳足跡”這個名詞也因BP推廣而變得風行。[65][66]
排放強度
排放強度是溫室氣體排放與其他指標(例如國內生產毛額(GDP)或能源使用量)之間的比率。有時也稱為"碳強度"和"排放強度"。[67]排放強度可使用現行市場匯率(MER)或購買力平價(PPP)來計算。[50]:96基於MER的計算顯示已開發國家和開發中國家之間的排放強度差異較大,而基於PPP的計算所顯示的差異會較小。
範例工具和網站
碳核算(也稱溫室氣體核算)是衡量和追蹤一組織排放溫室氣體數量的方法架構。[13]
Climate TRACE
本節摘自Climate TRACE。
Climate TRACE(即時追蹤大氣碳排放(Tracking Real-Time Atmospheric Carbon Emissions)的簡稱)[68]是個獨立組織,可監測和發佈在數週內發生的溫室氣體排放量。[69]此組織於2021年COP26(第26屆聯合國氣候變遷大會)之前啟動,[70]它將二氧化碳和甲烷的監測、報告和驗證技術改進,[71][72]利用衛星資料和人工智慧來監測世界各地的煤炭開採地點和發電站煙囪等排放來源。[73][74]
歷史趨勢
累積及歷史排放量
人類使用化石燃料所產生的二氧化碳累積排放是全球暖化的主要原因,[75]並顯示出哪些國家對人為造成的氣候變化影響最大。二氧化碳在大氣中可存在至少150年至長達1,000年,[76]甲烷會在十年左右的時間內消失,[77]而一氧化二氮可持續約100年。[78]此類數字顯示哪些地區對人類造成的氣候變化影響最大。[79][80]:15
於1890年至2007年期間,非經合組織國家佔與能源相關的累計二氧化碳排放量的42%。[55]:179–80 [81]在此期間,美國佔排放量的28%、歐盟佔23%、日本佔4%、其他經合組織國家佔5%、俄羅斯佔11%、中國佔9%、印度佔3%,世界其他地區佔18%。[55]:179–80
整體而言,已開發國家於此段期間的工業二氧化碳排放量佔全球此類排放的83.8%,佔二氧化碳總排放量的67.8%。在此期間,開發中國家的工業二氧化碳排放量佔此類排放的16.2%,佔二氧化碳排放總量的32.2%。
然而當我們審視當今世界各地的排放量時,就會清楚地發現歷史上排放量最高的國家並非一定是當今最大的排放國。例如英國於2017年的排放量僅佔全球的1%。[42]
相較之下,人類迄今排放的溫室氣體比導致恐龍滅絕(白堊紀—古近紀滅絕事件)的希克蘇魯伯隕石坑撞擊事件所產生的還要多。[82]
交通運輸和發電是導致歐盟溫室氣體排放的主要來源。單獨交通運輸業與發電加上幾乎所有其他行業相比,所產生的溫室氣體排放量持續上升。交通運輸排放量自1990年起已增加30%。交通運輸部門約佔排放量的70%,其中大部分排放是由乘用車和貨車所造成。公路旅行是交通運輸溫室氣體排放中的排名第一來源,其次是航空業和海運業。[83][84]水路運輸仍是平均碳強度最低的運輸方式,是永續供應鏈中的重要一環。[85]
建築物與工業一樣,導致直接排放的溫室氣體約佔總量的五分之一,主要由於供暖和熱水消耗。但加上建築物內的電力消耗,佔比會攀升至三分之一以上。[86][87][88]
歐盟內部的農業部門目前約佔溫室氣體排放總量的10%,其中牲畜排放的甲烷約佔這10%中的一半以上。[89]
二氧化碳排放總量的估計包括生物炭排放,主要是因為森林砍伐的結果。[50]:94將生物排放列入會帶來前面提到的有關碳匯和土地利用變化的相同爭議。[50]:93–94實際計算淨排放量會非常複雜,並受到區域間碳匯分配方式和氣候系統動態的影響。
此圖顯示於1850年至2019年化石燃料二氧化碳排放量的對數。[90]左側為自然對數,右側為每年1吉噸的實際值。排放量在170年期間每年整體增加約3%,但可檢測到明顯不同的成長率間隔(在1913年、1945年和1973年時發生幅度甚大的轉折)。根據回歸線,排放量可迅速從一種增長方式轉變為另一種增長方式,然後持續很長一段時間。最近一次排放量成長下降(幾乎下降3個百分點)是在20世紀1970年代能源危機期間。所用數據取自綜合碳觀測系統。[91]
自特定基準年以來的變化
全球二氧化碳排放量從1990年代的每年增加1.1%,到2000起每年急劇增加為3%以上(大氣中二氧化碳濃度每年增加超過2百萬分比(ppm)),這是由於開發中國家和已開發國家雙方之前的碳強度下降的趨勢已經消失。在此期間,中國對全球排放量成長的影響最大。[92]相較之下,甲烷並沒有明顯增加,而二氧化氮年增加率為0.25%。
測量排放量時,採用不同的基準年,對於估計國家對全球暖化貢獻度的估計會有不同的結果。[80]:17–18[93]解決此問題,可將一個國家從一特定基準年開始對全球暖化的最高貢獻度除以從同一特定基準年開始對全球暖化的最低貢獻度,然後在各國間作比較。在1750年、1900年、1950年和1990年之間進行基準年選擇對大多數國家都有顯著影響。[80]:17–18在八大工業國組織(G8)國家中,對英國、法國和德國的影響最為顯著。這些國家有著悠久的二氧化碳排放歷史。
來自全球碳計畫的數據
成立於2001年的組織全球碳計畫持續發佈有關二氧化碳排放、碳預算和濃度的數據。
年 | 石化燃料及工業排放(吉噸碳)
(未計入水泥碳化,吸收二氧化碳) |
土地利用改變
(吉噸碳) |
總計
(吉噸碳) |
總計
吉噸二氧化碳 |
---|---|---|---|---|
2010年 | 9.106 | 1.32 | 10.43 | 38.0 |
2011年 | 9.412 | 1.35 | 10.76 | 39.2 |
2012年 | 9.554 | 1.32 | 10.87 | 39.6 |
2013年 | 9.640 | 1.26 | 10.9 | 39.7 |
2014年 | 9.710 | 1.34 | 11.05 | 40.2 |
2015年 | 9.704 | 1.47 | 11.17 | 40.7 |
2016年 | 9.695 | 1.24 | 10.93 | 39.8 |
2017年 | 9.852 | 1.18 | 11.03 | 40.2 |
2018年 | 10.051 | 1.14 | 11.19 | 40.7 |
2019年 | 10.120 | 1.24 | 11.36 | 41.3 |
2020年 | 9.624 | 1.11 | 10.73 | 39.1 |
2021年 | 10.132 | 1.08 | 11.21 | 40.8 |
2022年
(預測) |
10.2 | 1.08 | 11.28 | 41.3 |
不同溫室氣體排放量
二氧化碳佔溫室氣體排放的很大部分,而甲烷排放的短期影響幾乎與二氧化碳相同。[4]相較之下,一氧化二氮和氟化氣體的作用較小。
溫室氣體排放量以二氧化碳當量衡量,而二氧化碳當量則由這些氣體的全球暖化潛勢 (GWP) 決定,而全球暖化潛勢則由氣體在大氣中的壽命決定。估計時很大程度上由海洋和陸地吸收這些氣體的能力決定。短期氣候污染物(SLCP)(包括甲烷、氫氟碳化物、對流層臭氧和黑碳)在大氣中持續存在的時間從數天到15年不等,而二氧化碳可在大氣中保留數千年。[97]減少SLCP排放量可將全球暖化的持續速率降低近一半,並將預期的北極暖化速率降低三分之二。[98]
全球於2019年的溫室氣體排放量估計為57.4吉噸二氧化碳當量,而僅二氧化碳排放量就達42.5吉噸(包括土地利用變化 (LUC) 在內)。[99]
脫碳是甚為重要的長期措施,但處理對氣候影響更快的短期污染物也同樣重要,將針對此兩因素的措施結合,對實現氣候目標非常重要。[100]
二氧化碳
- 化石燃料:石油、天然氣和煤炭是人為全球暖化的主要驅動因素,於2019年年排放量為35.6吉噸二氧化碳(佔比89%))。[101]:20
- 水泥生產估計排放量為1.42吉噸二氧化碳(佔比4%)。
- 土地利用變化(LUC)是森林砍伐遠高於林地復育的結果,粗略估計為4.5吉噸二氧化碳排放量。光是野火每年就造成約7吉噸二氧化碳排放量。[102][103]
- 化石燃料作非能源使用、生產焦炭過程中的碳損失以及原油/天然氣生產中的燃除也會產生二氧化碳。[101]
甲烷
甲烷能產生很高的直接影響,它在在5年吸收熱量的能力是二氧化碳的100倍。[4]因此目前3.89噸的甲烷排放量[101]:6與總體二氧化碳排放量具有大致相同的短期全球暖化效應,並有引發氣候和生態系統不可逆轉的風險。將目前的甲烷排放量減少約30%將導致其於大氣中的濃度維持穩定。
- 化石燃料相關活動佔甲烷排放的大部分(32%),包括煤炭開採(12%)、天然氣輸送和洩漏(11%)以及石油開採中的宣洩排放(9%)。[101]:6[101]:12
- 牲畜(28%),其中牛(21%)為主要來源,其次是水牛(3%)、綿羊(2%)和山羊(1.5%)。[101]:6, 23
- 人類廢棄物和污水(21%):當垃圾掩埋場的生物質廢棄物以及生活和工業污水中的有機物質在厭氧條件下被細菌分解時,會產生大量甲烷。[101]:12
- 水稻種植是另一個農業來源(10%),被水淹沒的田地中有機物質受厭氧分解而產生甲烷。[101]:12
一氧化二氮
一氧化二氮具有高GWP和顯著的臭氧消耗潛力。估計一氧化二氮在100年內的暖化潛力是二氧化碳的265倍。[104]對於此種氣體,需要減少50%以上排放才能維持其在大氣中的穩定。
一氧化二氮的大部分排放量來自農業(56%) ,尤其是畜養牲畜:牛(牧場中的糞便)、化肥、牲畜糞肥管理。[101]:12另外的來源是化石燃料(18%) 和燃燒生物燃料,[105]以及己二酸(用於生產尼龍)和硝酸的工業生產。
F-氣體
氟化氣體包括HFC、PFC、SF6和三氟化氮 (NF3)。它們用於電力行業的開關設備、半導體製造、鋁生產,另有尚不知來源的SF6排放。[101]:38根據《蒙特婁議定書》基加利修正案,繼續逐步減少HFC的製造和使用將有助於於減少其排放,同時又能提高空調、冰櫃和其他製冷設備等設備的能源效率。
氫氣
氫氣洩漏會間接導致全球暖化。[106]當氫氣在大氣中被氧化時,結果是對流層和平流層中溫室氣體的濃度會增加。[107]氫氣可能從氫氣生產設施以及任何運輸、儲存或消耗氫氣的基礎設施中洩漏。[108]
黑碳
黑碳是經由化石燃料、生物燃料和生物質的不完全燃燒而形成。它並非溫室氣體,而是輻射強迫物質。黑碳沉積在雪和冰上時可吸收陽光並降低反照率。其與雲的相互作用可能會引起間接加熱作用。[109]黑碳在大氣中僅停留幾天到幾週。[110]可透過將煉焦碳爐升級、在柴油引擎上安裝顆粒物過濾器、減少常規燃除作業,以及最大限度減少露天燃燒生物質來降低排放。
各經濟部門排放量
全球溫室氣體排放可歸因於不同的經濟部門。了解其對氣候變化造成的不同影響程度,有助於了解氣候變化緩解所需的行動。
溫室氣體排放可分為因燃燒燃料取得能量而產生的溫室氣體排放,和其他過程所產生的。大約三分之二的溫室氣體排放來自燃燒過程。[112]
能量可在消耗點產生,或生產電力以供他處消耗。因此生產能源而產生的排放可根據生產地點,或是能源消耗地點進行分類。如果排放量歸因於生產地點,那麼發電機的排放量約佔全球溫室氣體排放量的5%。[113]如果這些排放歸因於最終消費者,那麼總排放量的24%來自製造業和建築業,17%來自運輸業,11%來自家庭消費者,7%來自商業消費者。[114]大約有4%的排放量來自能源和燃料產業本身消耗的能源。
其餘三分之一的排放來自能源生產以外的製程。總排放量的12%來自農業、7%來自土地利用變化和林業、6%來自工業流程,及3%來自廢棄物。[112]
發電
燃煤發電廠是最大的單一排放源,於2018年佔全球溫室氣體排放量的20%以上。[115]天然氣發電廠的污染比燃煤電廠少得多,但它也是個主要排放源,[116]2018年火力發電量廠的排放佔全球總排放量的25%以上。[117]值得注意的是根據對221個國家中29,000多個化石燃料發電廠的盤查,發現其中僅5%發電廠就佔發電碳排放量的近四分之三。[118]聯合國政府間氣候變化專門委員會(IPCC)於2022年發表的報告指出,如果能源服務能透過現代化的方式,溫室氣體排放最多只會增加幾個百分點,這種小幅增長表示為所有人提升生活水平,所採用的能源將會遠低於當前的平均水平。[119]
農業、林業和土地利用
農業
農業產生的溫室氣體排放(英語:Greenhouse gas emissions from agriculture)數量龐大:由農業、林業和土地利用三個部門的排放,佔全球排放量的13%至21%。[120]最終導致氣候變化。農業的排放有兩種:直接溫室氣體排放以及將森林等非農業用地轉變為農業使用,而間接導致的排放。[121][122]農業溫室氣體排放中一氧化二氮和甲烷的排放量佔總量的一半以上。[123] 畜牧業所產生的溫室氣體排放佔整體農業排放的大部分,並耗用約30%的農業淡水用量。[124]
農業中的食物系統也是造成大量溫室氣體排放的來源,[125][126]除在大量土地利用及化石燃料使用時產生溫室氣體之外,也經由種植水稻和飼養牲畜等做法直接導致溫室氣體排放。[127]在過去250年來觀測到的全球溫室氣體增加,三個主要原因是燃燒化石燃料、土地利用及農業活動。[128]飼養動物的消化系統有兩類:單胃動物和反芻動物。用於生產牛肉和乳製品的牛是反芻動物,其溫室氣體排放量名列前茅,單胃動物,如豬隻和家禽類的排放並不高。單胃動物具有更高的飼料轉換效率,也不會產生很多甲烷。[125]二氧化碳是在農作物生長後期透過植物和土壤呼吸作用,被重新排放到大氣中,導致更多的溫室氣體排放。[129]估計氮肥製造和使用過程中所產生的溫室氣體數量約佔人為溫室氣體排放量的5%。減少化學肥料排放最重要的手段是減少其使用,同時也須將使用效率提高。[130]
有許多策略可用來減輕農業排放的影響,並進一步減少排放 - 此種做法統稱為氣候智慧型農業,其中的策略包括有提高畜牧業效率(包括管理和技術)、更有效的牲畜糞肥管理、降低對化石燃料和不可再生資源的依賴、動物進食和飲水時點與期間的調整,以及減少人類動物性食物的生產與消費。[125][131][132][133]這類策略可減少農業部門的溫室氣體排放,以實現更為永續的糧食系統。[134]:816–817
森林砍伐
森林砍伐也是溫室氣體排放的主要來源。一項研究顯示熱帶森林砍伐造成的年度碳排放量(或碳損失)在過去二十年中翻了一倍,且還繼續增加中。(2001年至2005年期間每年有0.97 ±0.16吉噸碳,而在2015年至2019年期間每年有1.99 ±0.13吉噸碳 )[136][135]
土地利用變化
土地利用變化,例如砍伐森林改作農業用途,會將儲存於碳匯的碳量釋放進入大氣,增加其中溫室氣體的濃度。[138]土地利用變化的核算可理解為衡量"淨"排放的概念,即所有來源的總排放扣除例如森林的碳匯從大氣中清除的溫室氣體。[50]:92–93
淨碳排放量的計量存在很大的不確定性。[139]此外,關於碳匯應如何在不同地區和在不同的時代間分配也存在爭議。[50]:93例如關注現代的碳匯變化可能對那些較早之前經歷過砍伐森林的地區(例如歐洲)有利。
於1997年,人為造成的印尼泥炭沼澤森林火災,估計產生的碳排放是全球燃燒化石燃料平均排放量的13%至40%。[140][141][142]
人員和貨物運輸
交通運輸產生的排放量佔全球的15%。[143]全球交通運輸二氧化碳排放量的四分之一以上來自公路貨運,[144]因此許多國家正在進一步限制卡車二氧化碳排放,以助於限制氣候變化。[145]
海上運輸產生的排放量佔所有排放量的3.5%至4%,主要是二氧化碳。[146][147]航運業於2022年產生的排放量佔全球的3%,使其成為"全球第六大溫室氣體排放個體,排名介於日本和德國之間。"[148][149][150]
航空
噴射客機排放二氧化碳、氮氧化物、凝結尾跡和顆粒物,均有導致氣候變化的作用。全球於2018年的航空營運產生的二氧化碳排放量佔所有碳排放量的2.4%。[151]
人類於2020年的活動對氣候的整體影響中約有3.5%來自航空業。該部門於近20年來的排放量翻了一倍,但於全球的排放佔比中並沒有改變,因為其他部門的排放也在增長。[152]
客機二氧化碳平均直接排放量(不考慮高空輻射效應)的一些代表性數據,以二氧化碳和每乘客公里二氧化碳當量表示:[153]
- 國內短途,小於463公里(288英里):257克/公里二氧化碳,或259克/公里(14.7盎司/英里)二氧化碳當量
- 長途飛行:113克/公里二氧化碳,或114克/公里(6.5盎司/英里)二氧化碳當量
建築物與營建
於2018年製造建築材料和維護建築物的二氧化碳排放量佔能源和製程相關排放量的39%。玻璃、水泥和鋼鐵的製造佔能源和製程相關排放量的11%。[154]由於建築施工是項重大投資,因此到2050年,三分之二以上的現有建築仍將存在。為實現《巴黎協定》的目標,有必要對現有建築進行改裝以提高效率,僅要求新建建築適用低排放標準無法符合整體需求。[155]產生能源與消耗能源一樣多的建築物稱為零碳建築,而產生能源多於消耗的建築無稱為正能量建築。低能耗建築的設計是高效的低能耗和低碳排放 - 其中一種流行的類型是被動式節能屋。[154]
建築業在建築性能和能源效率方面在近幾十年來已取得顯著進步。[156]綠色建築可避免排放或是可捕集環境中已存在的碳,而降低建築行業的足跡,例如於建築和景觀美化中使用麻凝土、纖維素絕緣材料。[157]
全球建築業於2019年排放12吉噸二氧化碳當量。其中95%以上是碳,其餘5%是甲烷、一氧化二氮和有機鹵化物。[158]
建築部門中最大的排放來源(佔總量的49%)是產生其所需的電力。[159]
在全球建築業產生的溫室氣體排放中,28%來自鋼鐵、水泥[160]和玻璃[159]等建築材料的製造過程中所產生的。鋼鐵和水泥生產會排放大量二氧化碳。例如於2018年,鋼鐵生產佔全球二氧化碳排放量的7%至9%。[161]
全球建築業的溫室氣體排放所剩餘的23%是直接在建築現場產生。[159]
建築業的隱含碳排放
隱含碳排放(或稱前期碳排放 (upfront carbon emissions(UCE)) 是創建和維護建築材料的結果。[162]截至2018年,"隱含碳排放佔全球溫室氣體排放量的11%,佔全球建築業排放量的28%……從現在到2050年,隱含碳排放將佔新建建築排放總量的近一半。" [163]
建築材料的開採、加工、製造、運輸和安裝過程中產生的溫室氣體排放被稱為材料的隱含碳排放。[164]透過使用低碳材料進行建築結構和飾面、減少拆除以及盡可能重複利用建築物和建築材料,可減少建築項目的隱含碳排放。[159]
工業流程
截至2020年,位於南非的合成燃料工廠Secunda CTL是世界上最大的單一排放個體,每年排放5,650萬噸二氧化碳。[165]
採礦
將油井中湧出的天然氣以燃除處理,還有宣洩排放是溫室氣體排放的重要來源。自1970年代約1.1億噸/年的峰值以來,這種排放已下降四分之三,在2004年的排放約佔所有人為排放量的0.5%。[166]
世界銀行估計每年燃除或是洩漏的天然氣量為1,340億立方公尺(2010年數據),相當於德國和法國每年消耗天然氣的總和,這種數量足以供全世界使用16天。燃除的做法高度集中:前10個國家加總佔排放量的70%,前20個國家加總佔85%。[167]
鋼和鋁
鋼鐵和鋁生產這兩個經濟部門是執行碳捕集與封存的關鍵所在。根據一項在2013年所做的研究,"鋼鐵業於2004年排放的二氧化碳約5.9億噸,佔全球人為溫室氣體排放量的5.2%。鋼鐵生產排放的二氧化碳主要來自燃燒化石燃料,以及使用石灰石以純化氧化鐵。"[168]
塑膠
塑膠主要由化石燃料產出。估計全球溫室氣體排放量的3%至4%,與塑膠的生命週期有關聯。[169]美國國家環境保護局(EPA)估計[170]每生產一個質量單位的聚對苯二甲酸乙二酯(PET)(最常用於製造飲料瓶的塑膠類),就會排放多達5個質量單位的二氧化碳,[171]與之相關的運輸也會產生溫室氣體。[172]塑膠廢棄物降解時會排放二氧化碳。一項於2018年所做的研究聲稱,環境中一些最常見的塑膠在暴露於陽光下時會釋放溫室氣體 - 甲烷和乙烯,其數量之大可能會影響到氣候。[173][174]
由於塑膠比玻璃或金屬更輕,因此運輸塑膠可減少能源消耗。當玻璃或金屬包裝是一次性用途時,改用PET預計可節省52%的運輸能源。
有份《塑膠與氣候》的報告於2019年發佈,稱當年塑膠的生產和焚燒將向大氣排放相當於8.5億噸二氧化碳。按照目前的趨勢,預計到2030年,塑膠的年生命週期溫室氣體排放量將增長至13.4億噸,而到2050年,塑膠的生命週期排放量可能達到560億噸,相當於地球剩餘碳預算的14%。[175]報告稱唯有減少消耗才能解決問題,而其他諸如生物可降解塑料、海洋清理、在塑料工業中使用再生能源等措施的收效甚微,在某些情況下甚至可能會讓問題變得更嚴重。[176]
紙漿和紙張
全球印刷和造紙產業約佔二氧化碳排放量的1%。[177]紙漿與造紙工業的溫室氣體排放來自原料生產和運輸、污水處理設施、外購電力、相關產品運輸、處置和回收,各種流程所消耗的化石燃料。
各種服務
數位服務
資料中心(不包括加密貨幣挖礦)和資料傳輸於2020年分別消耗全球約1%的電力。[178]數位經濟產生的溫室氣體排放量佔全球排放量的2%至4%,[179]其中很大部分來自晶片製造。[180]然而此部門有減少全球份額較大的其他部門的排放,例如人員移動,[181]可能也包括建築和工業部門。[182]
加密貨幣的挖礦工作需要用到大量電力,會產生大量碳足跡。[183]估計於2016年1月1日至2017年6月30日期間,比特幣、以太坊、萊特幣和門羅幣等區塊鏈工作量證明(俗稱挖礦)已向大氣排放300萬噸至1,500萬噸二氧化碳。[184]預計到2021年底,比特幣的挖礦將產生6,540萬噸二氧化碳,與希臘一國所產生的一樣多,[185]每年消耗91至177太瓦時(tWh=1012watt-hour)。比特幣是能源效率最低的加密貨幣,每筆交易會耗用707.6千瓦時(kWh=103watt-hour)的電力。[186][187][188]
有項在2015年所做的研究,調查2010年至2030年間全球資訊及通訊技術(CT) 的用電量。CT用電量分為四個主要類別:(i) 消費設備,包括個人電腦、行動電話、電視和家庭娛樂系統、 (ii) 網路基礎設施、 (iii) 資料中心計算與儲存裝置,以及 (iv) 前述類別相關生產。估計在最壞的情況下,2030年的CT電力使用量可能佔全球溫室氣體排放量的23%。[189]
醫療保健
醫療保健產業產生的溫室氣體排放量佔全球溫室氣體排放量的4.4–4.6%。[190]
根據一項於2013年所做的醫療保健產業的生命週期排放量研究,估計與美國與此活動相關的溫室氣體排放每年可能導致額外123,000至381,000個失能調整生命年(DALY)。[191]
供水和衛生
本節摘自WASH#Reducing greenhouse gas emissions。
現在已有減少由供水和衛生服務產生溫室氣體排放的解決方案。[192]這類解決方案分為三類,且有部分重疊:首先是"透過精益和高效的方法減少水和能源消耗"、其次是"擁抱循環經濟以生產能源和有價值的產品",及第三"透過策略決策規劃減少溫室氣體排放"。[193]:28所謂精益和高效的方法包括減少水管網路漏水損失和減少雨水或地下水滲入下水道的方法等。[193]:29此外,透過激勵措施以鼓勵家庭和工業減少用水量和為水加熱的能源需求。[193]:31還有另一方法可減少處理原水的能源需求:更好地保護水源的水質。 [193]:32
旅遊
據聯合國環境署稱,全球旅遊業是大氣中溫室氣體濃度不斷增加的重要因素。[194]
其他排放特徵
人為氣候變遷的責任因人而異(例如不同的群體之間)。
依能源類型
本節摘自能源生命週期溫室氣體排放}。
溫室氣體排放是發電對環境的影響中的一種。衡量能源生命週期溫室氣體排放涉及透過生命週期評估,計算能源的全球暖化潛力,通常只對電能來源做研究,但有時也會評估熱源方面的。[196]研究結果以該能源產生的每單位電能的全球暖化潛勢為單位,量表使用二氧化碳當量與電能千瓦時 (kWh)表達。此類評估的目標是覆蓋能源的整個生命週期,從材料和燃料開採到施工、營運和廢棄物管理。
IPCC於2014年將全球主要發電來源的二氧化碳當量調查結果作統一處理(透過分析數百篇評估每種能源的獨立科學論文的結果來達成)。[197] 煤炭是迄今為止排放最高的,其次是天然氣,而太陽能、風能和核能均為低碳能源。水力發電、生質能、地熱能和海洋能通常是低碳的,但設計不當或其他因素可能會導致個別發電廠的排放量更高。
世代間差異
研究人員指出老年人在溫室氣體排放上升中扮演"主導角色",並有望成為未來導致溫室氣體排放的最大群體。人口老化、對氣候變化的低知情程度和擔憂,以及高碳產品消費(如在取暖和私人交通[198][199])等因素均推動此一現象。當今老年人曾歷經氣候變化影響會較日後年輕人預計將遇到的為小,[200]但他們在選舉决策中仍擁有有和其他人一樣的權利(例如每人一票),這一现象值得深思,因為他們的選擇可能會對下一代應對氣候變化產生深遠的影響。
依社會經濟階層
在所得高者過度消費生活方式推動下,全球最富有的5%人口對全球溫室氣體絕對排放的貢獻率達到37%。可見收入與人均二氧化碳排放量之間存在很強的關聯性。[42]全球絕對排放量成長的近一半是由最富有的10%人口所造成。[204]IPCC於2022年發表的報告指出,新興經濟體的窮人和中產階級的生活方式產生的消費量比已開發的高收入國家中高收入階層的,要低約5-50倍。[205][206]地區和國家人均排放量的差異部分反映出各自不同的發展階段,但在相似的收入水平下也存在很大差異。人均排放量最高的10%家庭在全球家庭溫室氣體排放量中所佔的比例是超比例的巨大。[206]
研究發現世界上最富裕的公民對大部分環境影響負有責任,他們必須採取強而有力的行動,才能實現更安全的環境條件。[207][208]
根據英國的樂施會和斯德哥爾摩環境研究所於2020年共同發表的的報告,[209][210]從1990年到2015年的25年期間,全球最富有的1%人口造成的碳排放量是最貧窮的50%人口的兩倍。[211][212][213]在此期間,兩者分別佔累計排放量的15%和7%。[214]處於底層的一半人口直接造成不到20%的能源足跡,且按貿易修正後的能源消耗量也低於頂層5%的人口。最大的不成比例性被認為是發生在交通領域,例如前10%的人消耗56%的車輛燃料,且進行70%的車輛購買活動。[215]然而,富有的個人通常也是機構股東,通常具有更大的影響力,[216]有更甚者,億萬富翁也可直接進行遊說、直接財務決策和/或控制公司。
減少溫室氣體排放的方法
各國政府已採取行動以減少溫室氣體排放,緩解氣候變化。 UNFCCC附件一所列國家和地區(即經合組織和前蘇聯計畫經濟體)必須定期向UNFCCC提交其應對氣候變化行動的評估[217]:3政府實施的政策包括國家和地區減排目標、提高能源效率、支持能源轉型等。
氣候變化緩解(英語:Climate change mitigation)是為限制氣候變化,而透過減少溫室氣體排放,或是從大氣層中去除這些氣體(參見碳匯)而採取的行動。[218]:2239近期全球平均溫度上升主要是由燃燒化石燃料(煤、石油和天然氣)所引起。減緩的做法透過轉換使用可持續能源、節約能源和提高能源效率來達到減排的目的。此外,還可透過擴大森林面積、復育濕地和利用其他自然及技術的途徑來去除大氣中的二氧化碳,這些過程統稱為碳截存。[219]:12[220]
在一系列的選項之中,太陽能和風能具有最高的氣候變化緩解潛力和最低的成本。[221]太陽能和風能的可用變率(間歇性)可透過儲能和改進的輸電網路(包括超級電網、需求管理和可再生能源多樣化)來解決。 [222]:1直接使用化石燃料的設備(例如車輛和取暖設備)的排放量可透過電氣化來達到降低的目的。改用熱泵和電動載具可提高能源效率。如果工業過程無法避免產生二氧化碳,可採碳捕集與封存(CCS)措施以降低淨排放量。[223]
未來排放預測
降低對會導致溫室氣體排放的產品和服務需求有三種不同的方法。首先是透過行為和文化的改變,例如改變飲食的內容,其次是改善基礎設施(例如建立良好的大眾交通網絡),最後是改變終端技術(例如有良好隔熱的房屋比隔熱較差的會導致較少的排放)。[225](p. 119)
那些能減少對產品或服務需求的緩解方案可幫助人們做出減少碳足跡的個人選擇,(例如在選擇交通工具或食物時)。[226]:5-3這表示此類緩解方案有許多社會面上可減少需求的功能(也稱為需求方緩解行動)。例如社會經濟地位高的人往往比社會經濟地位低的人會產生更多溫室氣體排放。通過減少這類人的排放和推行綠色政策,他們可成為“低碳生活方式的榜樣”。[226]:5-4但有許多因素會影響到消費者的心理變量,例如認識和風險感知。政府政策會產生支持或是阻礙需求緩解方案的作用。例如公共政策可促進循環經濟概念以支持緩解氣候變化。[226]:5–6減少溫室氣體排放與共享經濟有關聯。
2023年10月,美國能源資訊管理局(EIA)於2023年10月根據目前可確定的政策干預措施,發佈迄2050年的一系列預測。[224][229][230]預測將排放量浮動,而非將2050年限制僅有淨零排放。於敏感性分析中將關鍵參數改變,主要是未來GDP的成長(每年2.6%作為參考,分別為1.8%和3.4%),其次是技術學習率、未來原油價格和類似的外源投入。模型結果遠非令人鼓舞。在任何情況下,與能源相關的碳排放總量都沒有低於2022年的水準(見圖3)。 這項探索提供一個基準,顯示需要採取更強有力的氣候行動。
國家案例
國家列表
2019年全球最大的五個二氧化碳排放國與地區 - 中國、美國、印度、歐盟27國+英國、俄羅斯和日本,合計佔人口的51%、全球國內生產毛額(GDP)的62.5%、全球化石能源消耗總量中的62%和二氧化碳量總量中的67%。於2019年這五個國家和歐盟27國+英國的排放量和2018年相比,呈現不同的變化:相對增幅最大的是中國(+3.4%),其次是印度(+1.6%)。反而是其餘的發生下降:歐盟27國+英國(-3.8%)、美國(-2.6%)、日本(-2.1%)和俄羅斯(-0.8%)。[231]
國家 | 總排放量 (百萬噸) |
佔比 (%) |
人均量 (噸) |
每GDP (噸/千元美金) |
---|---|---|---|---|
Global Total | 38,016.57 | 100.00 | 4.93 | 0.29 |
中國 | 11,535.20 | 30.34 | 8.12 | 0.51 |
美国 | 5,107.26 | 13.43 | 15.52 | 0.25 |
EU27+UK | 3,303.97 | 8.69 | 6.47 | 0.14 |
印度 | 2,597.36 | 6.83 | 1.90 | 0.28 |
俄羅斯 | 1,792.02 | 4.71 | 12.45 | 0.45 |
日本 | 1,153.72 | 3.03 | 9.09 | 0.22 |
International Shipping | 730.26 | 1.92 | - | - |
德国 | 702.60 | 1.85 | 8.52 | 0.16 |
伊朗 | 701.99 | 1.85 | 8.48 | 0.68 |
韩国 | 651.87 | 1.71 | 12.70 | 0.30 |
International Aviation | 627.48 | 1.65 | - | - |
印度尼西亞 | 625.66 | 1.65 | 2.32 | 0.20 |
沙烏地阿拉伯 | 614.61 | 1.62 | 18.00 | 0.38 |
加拿大 | 584.85 | 1.54 | 15.69 | 0.32 |
南非 | 494.86 | 1.30 | 8.52 | 0.68 |
墨西哥 | 485.00 | 1.28 | 3.67 | 0.19 |
巴西 | 478.15 | 1.26 | 2.25 | 0.15 |
澳大利亞 | 433.38 | 1.14 | 17.27 | 0.34 |
土耳其 | 415.78 | 1.09 | 5.01 | 0.18 |
英国 | 364.91 | 0.96 | 5.45 | 0.12 |
義大利, 圣马力诺 and the Holy See | 331.56 | 0.87 | 5.60 | 0.13 |
波蘭 | 317.65 | 0.84 | 8.35 | 0.25 |
法國 and 摩納哥 | 314.74 | 0.83 | 4.81 | 0.10 |
越南 | 305.25 | 0.80 | 3.13 | 0.39 |
哈萨克斯坦 | 277.36 | 0.73 | 14.92 | 0.57 |
臺灣 | 276.78 | 0.73 | 11.65 | 0.23 |
泰國 | 275.06 | 0.72 | 3.97 | 0.21 |
西班牙 and Andorra | 259.31 | 0.68 | 5.58 | 0.13 |
埃及 | 255.37 | 0.67 | 2.52 | 0.22 |
马来西亚 | 248.83 | 0.65 | 7.67 | 0.27 |
巴基斯坦 | 223.63 | 0.59 | 1.09 | 0.22 |
阿联酋 | 222.61 | 0.59 | 22.99 | 0.34 |
阿根廷 | 199.41 | 0.52 | 4.42 | 0.20 |
伊拉克 | 197.61 | 0.52 | 4.89 | 0.46 |
烏克蘭 | 196.40 | 0.52 | 4.48 | 0.36 |
阿尔及利亚 | 180.57 | 0.47 | 4.23 | 0.37 |
荷蘭 | 156.41 | 0.41 | 9.13 | 0.16 |
菲律賓 | 150.64 | 0.40 | 1.39 | 0.16 |
孟加拉国 | 110.16 | 0.29 | 0.66 | 0.14 |
委內瑞拉 | 110.06 | 0.29 | 3.36 | 0.39 |
卡塔尔 | 106.53 | 0.28 | 38.82 | 0.41 |
捷克 | 105.69 | 0.28 | 9.94 | 0.25 |
比利时 | 104.41 | 0.27 | 9.03 | 0.18 |
奈及利亞 | 100.22 | 0.26 | 0.50 | 0.10 |
科威特 | 98.95 | 0.26 | 23.29 | 0.47 |
乌兹别克斯坦 | 94.99 | 0.25 | 2.90 | 0.40 |
阿曼 | 92.78 | 0.24 | 18.55 | 0.67 |
土库曼斯坦 | 90.52 | 0.24 | 15.23 | 0.98 |
智利 | 89.89 | 0.24 | 4.90 | 0.20 |
哥伦比亚 | 86.55 | 0.23 | 1.74 | 0.12 |
羅馬尼亞 | 78.63 | 0.21 | 4.04 | 0.14 |
摩洛哥 | 73.91 | 0.19 | 2.02 | 0.27 |
奥地利 | 72.36 | 0.19 | 8.25 | 0.14 |
塞爾維亞與蒙特內哥羅 | 70.69 | 0.19 | 7.55 | 0.44 |
以色列 and 巴勒斯坦 | 68.33 | 0.18 | 7.96 | 0.18 |
白俄羅斯 | 66.34 | 0.17 | 7.03 | 0.37 |
希腊 | 65.57 | 0.17 | 5.89 | 0.20 |
秘魯 | 56.29 | 0.15 | 1.71 | 0.13 |
新加坡 | 53.37 | 0.14 | 9.09 | 0.10 |
匈牙利 | 53.18 | 0.14 | 5.51 | 0.17 |
利比亞 | 52.05 | 0.14 | 7.92 | 0.51 |
葡萄牙 | 48.47 | 0.13 | 4.73 | 0.14 |
緬甸 | 48.31 | 0.13 | 0.89 | 0.17 |
挪威 | 47.99 | 0.13 | 8.89 | 0.14 |
瑞典 | 44.75 | 0.12 | 4.45 | 0.08 |
香港 | 44.02 | 0.12 | 5.88 | 0.10 |
芬兰 | 43.41 | 0.11 | 7.81 | 0.16 |
保加利亚 | 43.31 | 0.11 | 6.20 | 0.27 |
朝鲜 | 42.17 | 0.11 | 1.64 | 0.36 |
厄瓜多尔 | 40.70 | 0.11 | 2.38 | 0.21 |
瑞士 and 列支敦斯登 | 39.37 | 0.10 | 4.57 | 0.07 |
新西兰 | 38.67 | 0.10 | 8.07 | 0.18 |
愛爾蘭 | 36.55 | 0.10 | 7.54 | 0.09 |
斯洛伐克 | 35.99 | 0.09 | 6.60 | 0.20 |
阿塞拜疆 | 35.98 | 0.09 | 3.59 | 0.25 |
蒙古国 | 35.93 | 0.09 | 11.35 | 0.91 |
巴林 | 35.44 | 0.09 | 21.64 | 0.48 |
波黑 | 33.50 | 0.09 | 9.57 | 0.68 |
千里達及托巴哥 | 32.74 | 0.09 | 23.81 | 0.90 |
突尼西亞 | 32.07 | 0.08 | 2.72 | 0.25 |
丹麦 | 31.12 | 0.08 | 5.39 | 0.09 |
古巴 | 31.04 | 0.08 | 2.70 | 0.11 |
叙利亚 | 29.16 | 0.08 | 1.58 | 1.20 |
约旦 | 28.34 | 0.07 | 2.81 | 0.28 |
斯里蘭卡 | 27.57 | 0.07 | 1.31 | 0.10 |
黎巴嫩 | 27.44 | 0.07 | 4.52 | 0.27 |
多米尼加 | 27.28 | 0.07 | 2.48 | 0.14 |
安哥拉 | 25.82 | 0.07 | 0.81 | 0.12 |
玻利维亚 | 24.51 | 0.06 | 2.15 | 0.24 |
苏丹 and 南蘇丹 | 22.57 | 0.06 | 0.40 | 0.13 |
危地马拉 | 21.20 | 0.06 | 1.21 | 0.15 |
肯尼亚 | 19.81 | 0.05 | 0.38 | 0.09 |
克罗地亚 | 19.12 | 0.05 | 4.62 | 0.16 |
爱沙尼亚 | 18.50 | 0.05 | 14.19 | 0.38 |
衣索比亞 | 18.25 | 0.05 | 0.17 | 0.07 |
加纳 | 16.84 | 0.04 | 0.56 | 0.10 |
柬埔寨 | 16.49 | 0.04 | 1.00 | 0.23 |
新喀里多尼亞 | 15.66 | 0.04 | 55.25 | 1.67 |
斯洛維尼亞 | 15.37 | 0.04 | 7.38 | 0.19 |
尼泊尔 | 15.02 | 0.04 | 0.50 | 0.15 |
立陶宛 | 13.77 | 0.04 | 4.81 | 0.13 |
科特迪瓦 | 13.56 | 0.04 | 0.53 | 0.10 |
格鲁吉亚 | 13.47 | 0.04 | 3.45 | 0.24 |
坦桑尼亚 | 13.34 | 0.04 | 0.22 | 0.09 |
吉尔吉斯斯坦 | 11.92 | 0.03 | 1.92 | 0.35 |
巴拿马 | 11.63 | 0.03 | 2.75 | 0.09 |
阿富汗 | 11.00 | 0.03 | 0.30 | 0.13 |
葉門 | 10.89 | 0.03 | 0.37 | 0.17 |
辛巴威 | 10.86 | 0.03 | 0.63 | 0.26 |
洪都拉斯 | 10.36 | 0.03 | 1.08 | 0.19 |
喀麦隆 | 10.10 | 0.03 | 0.40 | 0.11 |
塞内加尔 | 9.81 | 0.03 | 0.59 | 0.18 |
盧森堡 | 9.74 | 0.03 | 16.31 | 0.14 |
莫桑比克 | 9.26 | 0.02 | 0.29 | 0.24 |
摩尔多瓦 | 9.23 | 0.02 | 2.29 | 0.27 |
哥斯达黎加 | 8.98 | 0.02 | 1.80 | 0.09 |
北馬其頓 | 8.92 | 0.02 | 4.28 | 0.26 |
塔吉克斯坦 | 8.92 | 0.02 | 0.96 | 0.28 |
巴拉圭 | 8.47 | 0.02 | 1.21 | 0.09 |
拉脫維亞 | 8.38 | 0.02 | 4.38 | 0.14 |
贝宁 | 8.15 | 0.02 | 0.69 | 0.21 |
毛里塔尼亚 | 7.66 | 0.02 | 1.64 | 0.33 |
尚比亞 | 7.50 | 0.02 | 0.41 | 0.12 |
牙买加 | 7.44 | 0.02 | 2.56 | 0.26 |
賽普勒斯 | 7.41 | 0.02 | 6.19 | 0.21 |
薩爾瓦多 | 7.15 | 0.02 | 1.11 | 0.13 |
博茨瓦纳 | 7.04 | 0.02 | 2.96 | 0.17 |
汶萊 | 7.02 | 0.02 | 15.98 | 0.26 |
老挝 | 6.78 | 0.02 | 0.96 | 0.12 |
乌拉圭 | 6.56 | 0.02 | 1.89 | 0.09 |
亞美尼亞 | 5.92 | 0.02 | 2.02 | 0.15 |
库拉索 | 5.91 | 0.02 | 36.38 | 1.51 |
尼加拉瓜 | 5.86 | 0.02 | 0.92 | 0.17 |
刚果共和国 | 5.80 | 0.02 | 1.05 | 0.33 |
阿尔巴尼亚 | 5.66 | 0.01 | 1.93 | 0.14 |
乌干达 | 5.34 | 0.01 | 0.12 | 0.06 |
纳米比亚 | 4.40 | 0.01 | 1.67 | 0.18 |
模里西斯 | 4.33 | 0.01 | 3.41 | 0.15 |
马达加斯加 | 4.20 | 0.01 | 0.16 | 0.09 |
巴布亚新几内亚 | 4.07 | 0.01 | 0.47 | 0.11 |
冰島 | 3.93 | 0.01 | 11.53 | 0.19 |
波多黎各 | 3.91 | 0.01 | 1.07 | 0.04 |
巴巴多斯 | 3.83 | 0.01 | 13.34 | 0.85 |
布吉納法索 | 3.64 | 0.01 | 0.18 | 0.08 |
海地 | 3.58 | 0.01 | 0.32 | 0.18 |
加彭 | 3.48 | 0.01 | 1.65 | 0.11 |
赤道几内亚 | 3.47 | 0.01 | 2.55 | 0.14 |
留尼汪 | 3.02 | 0.01 | 3.40 | - |
刚果民主共和国 | 2.98 | 0.01 | 0.03 | 0.03 |
几内亚 | 2.92 | 0.01 | 0.22 | 0.09 |
多哥 | 2.85 | 0.01 | 0.35 | 0.22 |
巴哈马 | 2.45 | 0.01 | 6.08 | 0.18 |
尼日尔 | 2.36 | 0.01 | 0.10 | 0.08 |
不丹 | 2.12 | 0.01 | 2.57 | 0.24 |
苏里南 | 2.06 | 0.01 | 3.59 | 0.22 |
马提尼克 | 1.95 | 0.01 | 5.07 | - |
瓜德罗普 | 1.87 | 0.00 | 4.17 | - |
马拉维 | 1.62 | 0.00 | 0.08 | 0.08 |
圭亚那 | 1.52 | 0.00 | 1.94 | 0.20 |
塞拉利昂 | 1.40 | 0.00 | 0.18 | 0.10 |
斐济 | 1.36 | 0.00 | 1.48 | 0.11 |
帛琉 | 1.33 | 0.00 | 59.88 | 4.09 |
澳門 | 1.27 | 0.00 | 1.98 | 0.02 |
利比里亚 | 1.21 | 0.00 | 0.24 | 0.17 |
卢旺达 | 1.15 | 0.00 | 0.09 | 0.04 |
斯威士兰 | 1.14 | 0.00 | 0.81 | 0.11 |
吉布提 | 1.05 | 0.00 | 1.06 | 0.20 |
塞舌尔 | 1.05 | 0.00 | 10.98 | 0.37 |
馬爾他 | 1.04 | 0.00 | 2.41 | 0.05 |
马里 | 1.03 | 0.00 | 0.05 | 0.02 |
佛得角 | 1.02 | 0.00 | 1.83 | 0.26 |
索马里 | 0.97 | 0.00 | 0.06 | 0.57 |
馬爾地夫 | 0.91 | 0.00 | 2.02 | 0.09 |
乍得 | 0.89 | 0.00 | 0.06 | 0.04 |
阿鲁巴 | 0.78 | 0.00 | 7.39 | 0.19 |
厄立特里亚 | 0.75 | 0.00 | 0.14 | 0.08 |
賴索托 | 0.75 | 0.00 | 0.33 | 0.13 |
直布罗陀 | 0.69 | 0.00 | 19.88 | 0.45 |
法属圭亚那 | 0.61 | 0.00 | 2.06 | - |
法屬玻里尼西亞 | 0.60 | 0.00 | 2.08 | 0.10 |
冈比亚 | 0.59 | 0.00 | 0.27 | 0.11 |
格陵兰 | 0.54 | 0.00 | 9.47 | 0.19 |
安地卡及巴布達 | 0.51 | 0.00 | 4.90 | 0.24 |
中非 | 0.49 | 0.00 | 0.10 | 0.11 |
几内亚比绍 | 0.44 | 0.00 | 0.22 | 0.11 |
开曼群岛 | 0.40 | 0.00 | 6.38 | 0.09 |
东帝汶 | 0.38 | 0.00 | 0.28 | 0.10 |
伯利兹 | 0.37 | 0.00 | 0.95 | 0.14 |
百慕大 | 0.35 | 0.00 | 5.75 | 0.14 |
布隆迪 | 0.34 | 0.00 | 0.03 | 0.04 |
圣卢西亚 | 0.30 | 0.00 | 1.65 | 0.11 |
西撒哈拉 | 0.30 | 0.00 | 0.51 | - |
格瑞那達 | 0.23 | 0.00 | 2.10 | 0.12 |
科摩罗 | 0.21 | 0.00 | 0.25 | 0.08 |
圣基茨和尼维斯 | 0.19 | 0.00 | 3.44 | 0.14 |
聖多美和普林西比 | 0.16 | 0.00 | 0.75 | 0.19 |
圣文森特和格林纳丁斯 | 0.15 | 0.00 | 1.32 | 0.11 |
萨摩亚 | 0.14 | 0.00 | 0.70 | 0.11 |
所罗门群岛 | 0.14 | 0.00 | 0.22 | 0.09 |
汤加 | 0.13 | 0.00 | 1.16 | 0.20 |
特克斯和凯科斯群岛 | 0.13 | 0.00 | 3.70 | 0.13 |
英屬維爾京群島 | 0.12 | 0.00 | 3.77 | 0.17 |
多米尼克 | 0.10 | 0.00 | 1.38 | 0.12 |
瓦努阿图 | 0.09 | 0.00 | 0.30 | 0.09 |
圣皮埃尔和密克隆 | 0.06 | 0.00 | 9.72 | - |
庫克群島 | 0.04 | 0.00 | 2.51 | - |
福克蘭群島 | 0.03 | 0.00 | 10.87 | - |
基里巴斯 | 0.03 | 0.00 | 0.28 | 0.13 |
安圭拉 | 0.02 | 0.00 | 1.54 | 0.12 |
聖赫勒拿, Template:Country data Ascension and 特里斯坦-达库尼亚 | 0.02 | 0.00 | 3.87 | - |
法罗群岛 | 0.00 | 0.00 | 0.04 | 0.00 |
美國
本節摘自美國溫室氣體排放。
美國於2020年產生52億噸二氧化碳當量溫室氣體排放,[[233]僅次於中國,位居世界第二,美國是人均溫室氣體排放量最高的國家之一。 估計中國於2019年排放的溫室氣體是全球的27%,其次是美國(佔11%),然後是印度(佔6.6%)。[234]總計美國已排放世界溫室氣體的四分之一,比任何一個國家均多。[235][236][237]人均年排放量超過15噸。[238]然而國際能源署估計,美國最富有的十分之一人群每年人均排放超過55噸。[239]由於燃煤發電廠逐漸關閉,該國於2010年代的發電廠排放量下降,次於交通運輸,交通運輸目前是最大的單一排放源。[240]美國溫室氣體排放量於2020年中有27%來自交通運輸、25%來自電力生產、24%來自工業、13%來自商業和住宅建築,及11%來自農業。[240]於2021年,電力業仍是美國第二大溫室氣體排放源,占美國總量的25%。[241]這些溫室氣體排放會加劇美國乃至全世界的氣候變化。
中國
本節摘自中國溫室氣體排放量。
中國的溫室氣體排放量無論在生產或消費方面都是世界上最大的國家,主要來自煤炭燃燒,包括燃煤發電、煤炭開採[245]以及使用高爐生產鋼鐵。[246]在衡量生產排放方面,中國於2019年排放超過14億噸二氧化碳當量,[247]佔世界總量的27%。[248][249]當以基於消費的方式衡量方面,將進口商品相關的排放量計入,並將出口商品相關的排放量剔除,中國的排放量為13吉噸,佔全球排放量的25%。[250]
印度
本節摘自印度氣候變化#§Greenhouse gas emissions。
印度的溫室氣體排放量位居世界第三,主要來源是煤炭。[251]印度於2016年排放2.8吉噸二氧化碳當量(2.5吉噸,加上土地利用、土地利用改變與林業(LULUCF))。[252][253]79%是二氧化碳、4%是甲烷及5%是一氧化二氮。[253]印度每年排放約3吉噸二氧化碳當量的溫室氣體,人均排放約兩噸,[254]是世界平均的一半。[13]該國的排放量佔全球排放量的7%。[97]
社會與文化
COVID-19大流行的影響
全球二氧化碳排放量於2020年下降6.4%,即23億噸。[255]氮氧化物排放量於2020年4月下降高達30%。[256]在中國,封鎖和其他措施讓煤炭消耗量減少26%,氮氧化物排放量減少50%。.[257]溫室氣體排放量在疫情後期因許多國家開始取消限制而出現反彈,疫情政策對氣候變化的長期直接影響似可忽略不計。[255][258]
參見
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外部連結
- The official greenhouse gas emissions data of developed countries from the UNFCCC
- Annual Greenhouse Gas Index (AGGI) from NOAA
- NOAA CMDL CCGG – Interactive Atmospheric Data Visualization NOAA CO2 data
- IPCC Website
Lua错误:too many expensive function calls。