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

IF 3.9 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
Huili Liu , Cheng Hu , Qitao Xiao , Junqing Zhang , Fan Sun , Xuejing Shi , Xin Chen , Yanrong Yang , Wei Xiao
{"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 ,&nbsp;Cheng Hu ,&nbsp;Qitao Xiao ,&nbsp;Junqing Zhang ,&nbsp;Fan Sun ,&nbsp;Xuejing Shi ,&nbsp;Xin Chen ,&nbsp;Yanrong Yang ,&nbsp;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 (&gt;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}
引用次数: 0

Abstract

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.

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
城市仅占地球陆地面积的 3%,却排放了 70% 以上的人为二氧化碳。准确量化城市范围内二氧化碳排放的相应不确定性,是模拟全球/区域温室气体浓度和实施有效减排政策的第一步。作为世界上最大的排放国,中国已承诺在 2030 年达到二氧化碳排放峰值,各城市正面临着减少二氧化碳排放的巨大压力。长三角地区被视为中国乃至全球最大的城市群。尽管有多种排放清单,但该地区仍缺乏对城市二氧化碳排放不确定性的全面评估。本研究以长三角地区为重点,比较了六份清单,并使用夜间光照强度、GDP、人口和基于卫星的 xCO2 浓度作为替代数据,以确定潜在的排放偏差来源。研究结果如下(1) 长三角地区城市一级的二氧化碳排放量从数千万吨到约 6 亿吨不等。从 2010 年到 2019 年,该地区的排放量增长缓慢。然而,排放强度(用二氧化碳排放量除以国内生产总值计算)呈下降趋势。EDGAR 清单中点源排放的比例相对较低,这是因为它依赖于点源 CARMA,而忽略了较小的点源。(2) 低排放(0-5,000 万吨)、中排放(5,000-1,000 万吨)和高排放(1,000 万吨)城市的平均不确定性分别为 51.1%、34.0% 和 45.0%。排放量的绝对误差与代用数据呈很强的正相关。它们与不确定性之间存在对数关系,这有助于未来估计其他城市排放的不确定性。(3)生物二氧化碳通量与十年平均二氧化碳排放量之比介于-6.79%和-0.02%之间,远小于人为排放量的不确定性,比较表明近期人为二氧化碳排放量估算存在较大偏差,阻碍了碳中和能力的评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Atmospheric Pollution Research
Atmospheric Pollution Research ENVIRONMENTAL SCIENCES-
CiteScore
8.30
自引率
6.70%
发文量
256
审稿时长
36 days
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信