COVID-19背景下上海大气CO<sub>2</sub>浓度特征及潜在源分析

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (2502 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Based on the atmospheric CO₂ records in the Shanghai Tower station (SH station) from April 2021 to December 2022, this study focused on the characteristics of atmospheric CO₂ concentration and emission sources in Shanghai, and analyzed the differences in CO₂ concentration during the landfall of Typhoon "In-Fa", the Chinese New Year, and the lockdown during COVID-19 pandemic. The results showed: the diurnal variation of CO in the atmosphere at the SH station had a distinct bimodal pattern (11:00 LT and 17:00 LT), corresponded to the peak times of local human activities. The CO₂ concentration on weekdays was higher than that on weekends, and the concentration difference mainly appeared at 03:00~05:00LT and traffic rush hours. The CO₂ concentration remained low from April to September, with the lowest value in July ((423.42±0.05)×10^-6) and the highest value in December((445.94±0.27)×10^-6). During the landing of Typhoon "In-Fa", the atmospheric CO₂ concentration was diluted by the combined action of precipitation leaching and strong local wind. During the Chinese Spring Festival and the COVID-19 lockdown, anthropogenic activities plummeted and traffic was restricted during the lockdown, that significantly reduced the atmospheric CO₂ concentration. Backward trajectory clustering and weighted potential source contribution function (WPSCF) analysis indicated that the air masses from the ocean diluted the CO₂ concentration at the SH station, and the anthropogenic emissions from urban traffic and industry in Anhui, Jiangsu, Hubei and Zhejiang regions to the west of the SH station were the primary potential sources for the atmospheric CO₂ at the SH station.

Key words： Shanghai the Yangtze River Delta tall tower atmospheric CO₂ observation megacity

Received: 19 February 2024

PACS:

X511

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	GUO Peng
	QING Xue-mei
	LIN Yi
	ZANG Kun-peng
	CHEN Yuan-yuan
	LIU Shuo
	CHEN Bing-jiang
	LAN Wen-gang
	GAO Wei
	FANG Shuang-xi

Cite this article:

GUO Peng,QING Xue-mei,LIN Yi等. Analyze of characteristics and potential source of atmospheric CO₂ concentration in the context of COVID-19 at the Shanghai station[J]. CHINA ENVIRONMENTAL SCIENCECE, 2024, 44(9): 4864-4873.

URL:

http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2024/V44/I9/4864

[1] Artuso F, Chamard P, Piacentino S, et al. Influence of transport and trends in atmospheric CO₂ at Lampedusa [J]. Atmospheric Environment, 2009,43(19):3044-3051.
[2] Friedlingstein P, Jones M W, O’Sullivan M, et al. Global Carbon Budget 2019[J]. Earth System Science Data, 2019,11(4):1783-1838.
[3] IPCC, 2023: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds.)]. [R] IPCC, Geneva, Switzerland, 184pp., doi: 10.59327/IPCC/AR6-9789291691647.
[4] Fang S X, Tans P P, Dong F, et al. Characteristics of atmospheric CO₂ and CH₄ at the Shangdianzi regional background station in China [J]. Atmospheric Environment, 2016,131:1-8.
[5] Crisp D, Dolman H, Tanhua T, et al. How well do we understand the land-ocean-atmosphere carbon cycle [J]. Reviews of Geophysics, 2022,60(2):e2021RG000736.
[6] Friedlingstein P, O’Sullivan M, Jones M W, et al. Global Carbon Budget 2020[J]. Earth System Science Data, 2020,12(4):3269-3340.
[7] Gregg J S, Andres R J, Marland G. China: Emissions pattern of the world leader in CO₂ emissions from fossil fuel consumption and cement production [J]. Geophysical Research Letters, 2008,35(8):2007GL032887.
[8] Guan D B, Hubacek K, Weber C L, et al. The drivers of Chinese CO₂emissions from 1980 to 2030[J]. Global Environmental Change, 2008,18(4):626-634.
[9] Köne A Ç, Büke T. Forecasting of CO₂ emissions from fuel combustion using trend analysis [J]. Renewable and Sustainable Energy Reviews, 2010,14(9):2906-2915.
[10] Shan Y L, Liu J H, Liu Z, et al. An emissions-socioeconomic inventory of Chinese cities [J]. Scientific Data, 2019,6(1):190027.
[11] 胡汉舟.中国能源统计年鉴2021[M]. 北京:中国统计出版社, 2022:176-199. Hu H Z. China Energy Statistical Yearbook 2021[M]. Beijing: China Statistics Press, 2022:176-199.
[12] Cheng S Y, Zhou L X, Tans P P, et al. Comparison of atmospheric CO₂mole fractions and source–sink characteristics at four WMO/GAW stations in China [J]. Atmospheric Environment, 2018,180:216-225.
[13] 方双喜,李邹,周凌晞,等.云南香格里拉本底站大气CH₄体积分数及变化特征[J]. 环境科学学报, 2012,32(10):2568-2574. Fang S X, li Z, Zhou L X, et al. Variation of CH₄ concentrations at Yunnan Xianggelila background station in China [J]. Acta Scientiae Circumstantiae, 2012,32(10):2568-2574.
[14] Fang S X, Tans P P, Yao B, et al. Study of atmospheric CO₂and CH₄at Longfengshan WMO/GAW regional station: The variations, trends, influence of local sources/sinks, and transport [J]. Science China Earth Sciences, 2017,60(10):1886-1895.
[15] Liu S, Feng Z Z, Lin H W, et al. Changes of Atmospheric CO₂ in the Tibetan Plateau From 1994 to 2019[J]. Journal of Geophysical Research: Atmospheres, 2021,126(20):e2021JD035299.
[16] Fang S X, Du R G, Qi B, et al. Variation of carbon dioxide mole fraction at a typical urban area in the Yangtze River Delta, China [J]. Atmospheric Research, 2022,265:105884.
[17] Mai B R, Deng X J, Liu X, et al. The climatology of ambient CO₂concentrations from long-term observation in the Pearl River Delta region of China: Roles of anthropogenic and biogenic processes [J]. Atmospheric Environment, 2021,251:118266.
[18] 李晶,王跃思,刘强,等.北京市两种主要温室气体浓度的日变化[J]. 气候与环境研究, 2006,11(1):49-56. LI J, Wang Y S, Liu Q, et al. Diurnal variation of two greenhouse gases in Beijing [J]. Climatic and Environmental Research, 2006,11(1): 49-56.
[19] 郭毅.西安市大气CO₀₂时空分布研究[D]. 西安:陕西师范大学, 2011. Guo Y. Spatial and temporal distribution of atmospheric CO₂ in Xian [D]. Xian: Shanxi Normal University, 2011.
[20] 上海市统计局.2022年上海市国民经济和社会发展统计公报[J]. 统计科学与实践, 2023,42(3):40-50. Shanghai Municipal Statistics Bureau. Statistical Bulletin of Shanghai National Economic and Social Development in 2022[J]. Statistical Theory and Practice, 2023,42(3):40-50.
[21] 方双喜,周凌晞,臧昆鹏,等.光腔衰荡光谱CRDS法观测我国4个本底站大气CO₂ [J]. 环境科学学报, 2011,31(3):624-629. Fang S X, Zhou L X, Zang K P, et al. Measurement of atmospheric CO₂ mixing ratio by cavity ring-down spectroscopy (CRDS) at the 4background stations in China [J]. Acta Scientiae Circumstantiae, 2011,31(3):624-629.
[22] 臧昆鹏,周凌晞,方双喜,等.新型CO₂和CH₄混合标气标校流程及方法[J]. 环境化学, 2011,30(2):511-516. Zang K P, Zhou L X, Fang S X, et al. A new system for calibration and propagation of mixed CO₂ and CH₄ standards [J]. Environmental Chemistry, 2011,30(2):511-516.
[23] Hsu Y K, Holsen T M, Hopke P K. Comparison of hybrid receptor models to locate PCB sources in Chicago [J]. Atmospheric Environment, 2003,37(4):545-562.
[24] Rousseau D, Duzer D, Etienne J, et al. Pollen record of rapidly changing air trajectories to the North Pole [J]. Journal of Geophysical Research: Atmospheres, 2004,109(D6):D06116.
[25] 栾天.黑龙江龙凤山区域大气本底站温室气体浓度特征及源汇研究[D]. 南京:南京信息工程大学, 2015. Luan T. Study on concentration characteristics and emission/sink of greenhouse gases at Longfengshan regional background station in Heilongjiang province of China [D]. Nanjing: Nanjing University of Information Science and Technology, 2018.
[26] Polissar A V, Hopke P K, Paatero P, et al. The aerosol at Barrow, Alaska: long-term trends and source locations [J]. Atmospheric Environment, 1999,33(16):2441-2458.
[27] Zeng Y, Hopke P K. A study of the sources of acid precipitation in Ontario, Canada [J]. Atmospheric Environment, 1989,23(7):1499-1509.
[28] 庞宇婷,徐宏辉,单萌,等.长江三角洲地区CO₂浓度本底特征及来源分析[J]. 环境科学学报, 2023,43(2):340-353. Pang Y T, Xu H H, Shan M, et al. Background characteristics and source analysis of CO₂ concentration in the Yangtze River Delta [J]. Acta Scientiae Circumstantiae, 2023,43(2):340-353.
[29] Jiang K, Ma Q, Zang K, et al. Evolution of Atmospheric Carbon Dioxide and Methane Mole Fractions in the Yangtze River Delta, China [J]. Atmosphere, 2023,14(8):1295.
[30] 中国气象局.中国温室气体公报-2021[R]. [2022-01-09].https://www.cma.gov.cn/zfxxgk/gknr/qxbg/202301/t20230119_5274988.html. China Meteorological Administration. China Greenhouse Gas Bulletin-2021[R]. [2022-01-09]. https://www.cma.gov.cn/zfxxgk/gknr/qxbg/202301/t20230119_5274988.html.
[31] 顾一琼,陆益峰,何易,等.上海迎战“烟花”48小时[N]. 文汇报, 2021-7-27(2). Gu Y M, Lu Y F, He Y. 2021. Shanghai takes on "In-Fa" for 48hours [N]. Wen Hui Bao, 2021-7-27(2).
[32] 朱民,朱章海.上海统计年鉴2022[M]. 北京:中国统计出版社, 2023. Zhu M, Zhu Z H. Shanghai Statistical Yearbook 2022[M]. Beijing: China Statistics Press, 2023.
[33] 严远,轩召强.去年上海机动车保有量达537万辆驾驶人944万人[EB/OL].http://sh.people.com.cn/n2/2023/0130/c176737-40282646.html. Yan Y, Xuan Z Q. Last year, Shanghai had 5.37million vehicles and 9.44million drivers [EB/OL]. http://sh.people.com.cn/n2/2023/0130/c176737-40282646.html.
[34] 魏文栋,梅玥如,钟晨.上海实现碳达峰的前景、难点和实现路径[J]. 科学发展, 2023,16(5):78-86. Wei W D, Mei Y R, Zhong C.2023. Prospects, difficulties and pathways to achieve carbon peak in Shanghai [J]. Scientific Development, 2023,16(5):78-86.
[35] Wang S, Wang Q Q, Zhu S H, et al. Hourly organic tracers-based source apportionment of PM_2.5 before and during the Covid-19lockdown in suburban Shanghai, China: Insights into regional transport influences and response to urban emission reductions [J]. Atmospheric Environment, 2022,289:119308.
[36] Yin C Q, Xu J M, Gao W, et al. Characteristics of fine particle matter at the top of Shanghai Tower [J]. Atmospheric Chemistry and Physics, 2023,23(2):1329-1343.
[37] Qing X M, Qi B, Lin Y, et al. Characteristics of the methane (CH₄) mole fraction in a typical city and suburban site in the Yangtze River Delta, China [J]. Atmospheric Pollution Research, 2022,13(8):101498.
[38] Leng C P, Duan J Y, Xu C, et al. Insights into a historic severe haze event in Shanghai: synoptic situation, boundary layer and pollutants [J]. Atmospheric Chemistry and Physics, 2016,16(14):9221-9234.
[39] Wei C, Wang M H, Fu Q Y, et al. Temporal characteristics of greenhouse gases (CO₂ and CH₄) in the megacity Shanghai, China: Association with air pollutants and meteorological conditions [J]. Atmospheric Research, 2020,235:104759.
[40] 李邹,方双喜,和春荣,等.香格里拉本底站大气CO₂浓度变化特征初步研究[J]. 环境化学, 2012,31(12):1996-2001. Li Z, Fang S X, He C R, et al. Preliminary study of the atmospheric CO₂ concentration and its variation at Xianggelila background station [J]. Environmental Chemistry, 2012,31(12):1996-2001.
[41] Thoning K W, Tans P P, Komhyr W D. Atmospheric carbon dioxide at Mauna Loa Observatory: 2. Analysis of the NOAA GMCC data, 1974~1985[J]. Journal of Geophysical Research: Atmospheres, 1989, 94(D6):8549-8565.
[42] Nevison C D, Mahowald N M, Doney S C, et al. Contribution of ocean, fossil fuel, land biosphere, and biomass burning carbon fluxes to seasonal and interannual variability in atmospheric CO₂ [J]. Journal of Geophysical Research-Biogeosciences, 2008,113(G1):G01010.
[43] Guo M R, Fang S X, Liu S, et al. Comparison of Atmospheric CO₂, CH₄, and CO at Two Stations in the Tibetan Plateau of China [J]. Earth and Space Science, 2020,7(5):e2019EA001051.
[44] Wang Y, Munger J W, Xu S, et al. CO₂ and its correlation with CO at a rural site near Beijing: implications for combustion efficiency in China [J]. Atmospheric Chemistry and Physics, 2010,10(18):8881-8897.
[45] 郑柯.京津冀区域近地面CO₂时空变化的观测和模拟研究[D]. 南京:南京信息工程大学, 2020. Zheng K. Observation and simulation study of spatio-temporal changes of near-surface CO₂ in Beijing-Tianjin-Hebei region [D]. Nanjing: Nanjing University of Information Science and Technology, 2017.
[46] 刘少振.中国CO₂时空分布及影响因素分析[D]. 徐州:中国矿业大学, 2017. Liu S Z. Study on Spatial and temporal distribution of CO₂ and analysis of influencing factors in China [D]. Xuzhou: China University of Mining and Technology, 2017.
[47] 张玉秀.山东省能源消费和二氧化碳排放总量控制模型与对策研究[D]. 济南:山东师范大学, 2018. Zhang Y X. Research on total energy consumption and CO₂ emission control models and countermeasures in Shandong Province [D]. Jinan: Shandong Normal University, 2018.
[48] Zhang F S, Zhu L Y, Yan S M, et al. Analysis of the carbon dioxide mole fraction variation and its transmission characteristics in Taiyuan [J]. Atmospheric and Oceanic Science Letters, 2020,13(4):363-370.
[49] 王松伟,汤克勤,张皓然,等.江苏省二氧化碳减排政策对空气质量改善增益[J]. 环境科学, 2023,44(10):5443-5455. Wang S W, Tang K Q, Zhang H R, et al. 2023. Effect of carbon dioxide emission reduction policy on air quality improvement in Jiangsu province [J]. Environmental Science, 2023,44(10):5443-5455.