Huili Liu , Cheng Hu , Qitao Xiao , Junqing Zhang , Fan Sun , Xuejing Shi , Xin Chen , Yanrong Yang , Wei Xiao
{"title":"长江三角洲地区城市尺度人为二氧化碳排放不确定性及影响因素分析:全球最大的排放热点之一","authors":"Huili Liu , Cheng Hu , Qitao Xiao , Junqing Zhang , Fan Sun , Xuejing Shi , Xin Chen , Yanrong Yang , Wei Xiao","doi":"10.1016/j.apr.2024.102281","DOIUrl":null,"url":null,"abstract":"<div><p>Cities occupy only 3% of the earth's land area, yet they contribute over 70% of anthropogenic CO<sub>2</sub> emissions. Accurately quantifying the corresponding uncertainty of CO<sub>2</sub> emissions at the city scale is the first step in simulating global/regional greenhouse gas concentration and implementing effective emission reduction policies. As the world's largest emitter, China has committed to reaching its CO<sub>2</sub> emissions peak by 2030, and cities are facing substantial pressure to reduce CO<sub>2</sub> emissions. The Yangtze River Delta (YRD) region is treated as the largest urban agglomeration in China and globally. Despite the availability of multiple emission inventories, comprehensive assessments of city-level CO<sub>2</sub> emissions uncertainty within this region are still lacking. This study focused on the YRD region, compared six inventories and used nighttime light intensity, GDP, population, and satellite-based xCO<sub>2</sub> concentrations as proxy data to identify potential sources of emission bias. The findings are as follows: (1) The city-level CO<sub>2</sub> emissions in the YRD region ranged from tens of Mt to approximately 600 Mt. From 2010 to 2019, emissions in the region increased slowly. However, emission intensity (calculated by dividing the CO<sub>2</sub> emissions by the Gross Domestic Product) showed a declining trend. The relatively low proportion of point source emissions in EDGAR inventory is attributed to its reliance on the point source CARMA, which overlooks smaller point sources. (2) The average uncertainties for low emission (0–50 Mt), medium emission (50–100 Mt) and high emission (>100 Mt) cities were 51.1%, 34.0%, and 45.0%, respectively. The absolute errors of emissions showed strong positive correlations with proxy data. There exists a logarithmic relationship between them and uncertainty, which can assist in estimating emission uncertainty in other cities in the future. (3) The ratios of biological CO<sub>2</sub> flux to the ten-year average of CO<sub>2</sub> emissions varied between-6.79% and −0.02%, which are much smaller than the uncertainty of anthropogenic emissions, the comparisons indicate that recent large biases in estimating anthropogenic CO<sub>2</sub> emissions hinder the evaluation of carbon neutrality ability.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 11","pages":"Article 102281"},"PeriodicalIF":3.9000,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of anthropogenic CO2 emission uncertainty and influencing factors at city scale in Yangtze River Delta region: One of the world's largest emission hotspots\",\"authors\":\"Huili Liu , Cheng Hu , Qitao Xiao , Junqing Zhang , Fan Sun , Xuejing Shi , Xin Chen , Yanrong Yang , Wei Xiao\",\"doi\":\"10.1016/j.apr.2024.102281\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Cities occupy only 3% of the earth's land area, yet they contribute over 70% of anthropogenic CO<sub>2</sub> emissions. Accurately quantifying the corresponding uncertainty of CO<sub>2</sub> emissions at the city scale is the first step in simulating global/regional greenhouse gas concentration and implementing effective emission reduction policies. As the world's largest emitter, China has committed to reaching its CO<sub>2</sub> emissions peak by 2030, and cities are facing substantial pressure to reduce CO<sub>2</sub> emissions. The Yangtze River Delta (YRD) region is treated as the largest urban agglomeration in China and globally. Despite the availability of multiple emission inventories, comprehensive assessments of city-level CO<sub>2</sub> emissions uncertainty within this region are still lacking. This study focused on the YRD region, compared six inventories and used nighttime light intensity, GDP, population, and satellite-based xCO<sub>2</sub> concentrations as proxy data to identify potential sources of emission bias. The findings are as follows: (1) The city-level CO<sub>2</sub> emissions in the YRD region ranged from tens of Mt to approximately 600 Mt. From 2010 to 2019, emissions in the region increased slowly. However, emission intensity (calculated by dividing the CO<sub>2</sub> emissions by the Gross Domestic Product) showed a declining trend. The relatively low proportion of point source emissions in EDGAR inventory is attributed to its reliance on the point source CARMA, which overlooks smaller point sources. (2) The average uncertainties for low emission (0–50 Mt), medium emission (50–100 Mt) and high emission (>100 Mt) cities were 51.1%, 34.0%, and 45.0%, respectively. The absolute errors of emissions showed strong positive correlations with proxy data. There exists a logarithmic relationship between them and uncertainty, which can assist in estimating emission uncertainty in other cities in the future. (3) The ratios of biological CO<sub>2</sub> flux to the ten-year average of CO<sub>2</sub> emissions varied between-6.79% and −0.02%, which are much smaller than the uncertainty of anthropogenic emissions, the comparisons indicate that recent large biases in estimating anthropogenic CO<sub>2</sub> emissions hinder the evaluation of carbon neutrality ability.</p></div>\",\"PeriodicalId\":8604,\"journal\":{\"name\":\"Atmospheric Pollution Research\",\"volume\":\"15 11\",\"pages\":\"Article 102281\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Pollution Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1309104224002460\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Pollution Research","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1309104224002460","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Analysis of anthropogenic CO2 emission uncertainty and influencing factors at city scale in Yangtze River Delta region: One of the world's largest emission hotspots
Cities occupy only 3% of the earth's land area, yet they contribute over 70% of anthropogenic CO2 emissions. Accurately quantifying the corresponding uncertainty of CO2 emissions at the city scale is the first step in simulating global/regional greenhouse gas concentration and implementing effective emission reduction policies. As the world's largest emitter, China has committed to reaching its CO2 emissions peak by 2030, and cities are facing substantial pressure to reduce CO2 emissions. The Yangtze River Delta (YRD) region is treated as the largest urban agglomeration in China and globally. Despite the availability of multiple emission inventories, comprehensive assessments of city-level CO2 emissions uncertainty within this region are still lacking. This study focused on the YRD region, compared six inventories and used nighttime light intensity, GDP, population, and satellite-based xCO2 concentrations as proxy data to identify potential sources of emission bias. The findings are as follows: (1) The city-level CO2 emissions in the YRD region ranged from tens of Mt to approximately 600 Mt. From 2010 to 2019, emissions in the region increased slowly. However, emission intensity (calculated by dividing the CO2 emissions by the Gross Domestic Product) showed a declining trend. The relatively low proportion of point source emissions in EDGAR inventory is attributed to its reliance on the point source CARMA, which overlooks smaller point sources. (2) The average uncertainties for low emission (0–50 Mt), medium emission (50–100 Mt) and high emission (>100 Mt) cities were 51.1%, 34.0%, and 45.0%, respectively. The absolute errors of emissions showed strong positive correlations with proxy data. There exists a logarithmic relationship between them and uncertainty, which can assist in estimating emission uncertainty in other cities in the future. (3) The ratios of biological CO2 flux to the ten-year average of CO2 emissions varied between-6.79% and −0.02%, which are much smaller than the uncertainty of anthropogenic emissions, the comparisons indicate that recent large biases in estimating anthropogenic CO2 emissions hinder the evaluation of carbon neutrality ability.
期刊介绍:
Atmospheric Pollution Research (APR) is an international journal designed for the publication of articles on air pollution. Papers should present novel experimental results, theory and modeling of air pollution on local, regional, or global scales. Areas covered are research on inorganic, organic, and persistent organic air pollutants, air quality monitoring, air quality management, atmospheric dispersion and transport, air-surface (soil, water, and vegetation) exchange of pollutants, dry and wet deposition, indoor air quality, exposure assessment, health effects, satellite measurements, natural emissions, atmospheric chemistry, greenhouse gases, and effects on climate change.