Bayesian inversion of HFC-134a emissions in southern China from a new AGAGE site: Results from an observing system simulation experiment

Li, Juan1,2; Sheng, Jianxiong3; Zhu, Lei2,4,5; Yao, Bo6; Wu, Jing7; Pu, Dongchuan1,2; Shu, Lei2,8; Liu, Song2; Li, Xicheng2; Chen, Yuyang2; Zuo, Xiaoxing2; Li, Yali2; Fu, Weitao2; Zhang, Peng2; Yan, Zhuoxian2; Shen, Huizhong2,4,5; Ye, Jianhuai2,4,5; Wang, Chen2,4,5; Yang, Xin2,4,5; Fu, Tzung-May2,4,5

2024-10-01

10.1016/j.atmosenv.2024.120715

ATMOSPHERIC ENVIRONMENT   影响因子和分区

1352-2310

1873-2844

The abundance of hydrofluorocarbons (HFCs) in the atmosphere is increasing and is of significant importance to the Earth's system. It is thus crucial to investigate the spatial distribution of HFC emissions. However, inversion modeling, a commonly used approach, is susceptible to errors from a-priori emissions, inversion grids, observations, and other parameters. In this study, we conduct Observing System Simulation Experiment (OSSE) to evaluate the impact of inversion parameters on HFC emission estimates, focusing on HFC-134a at the newly established Xichong (XCG) AGAGE site in Shenzhen, China. We regard the EDGAR (v7) dataset as a reference for "true" emissions and simulate the "true" atmosphere using the GEOS-Chem model. Our OSSE indicates that conducting inversions in the medium- sensitivity region with source-receptor sensitivity larger than 6.0 (nmol mol-1)/(mol-1 )/(mol m- 2 s- 1 ) minimizes the bias between a-posteriori and "true" total emissions to 0.58 %-1.88 %. In the high-sensitivity region, enhancing the spatial resolution of inversion grids lowers this error from-27.07 % to +0.36 %. The accuracy of apriori spatial distribution crucially influences that of the a-posteriori: the higher correlation coefficient between a-priori and "true" emissions, the better a-posteriori agree with the "true" emissions, as evidenced by a reduced root mean square error (RMSE) of the a-posteriori vs. "true" emissions from 1.44 x 10-9-9 g m- 2 s- 1 (GDP- based) to 8.78 x 10-10 g m- 2 s-1 (VIIRS-based). Furthermore, selecting regularization parameters and balancing instrumental and a-priori errors are also important. Our OSSE setups allow for parameter testing during the inversion, offering a framework to assess the regional representativeness of future HFC measurement sites.

SCI ; EI

英语

通讯

Ministry of Science and Technology of the People's Republic of China[2023YFE0112900] ; Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks[ZDSYS20220606100604008] ; Guangdong Basic and Applied Basic Research Foundation[2021A1515110713] ; Guangdong University Research Project Science Team[2021KCXTD004] ; Major Talent Project of Guangdong Province[2021QN020924] ; Shenzhen Science and Technology Program["KQTD2021081109004802","JCYJ20210324104604012","JCYJ20220530115404009"] ; High level of special funds[G030290001]

Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences

Environmental Sciences ; Meteorology & Atmospheric Sciences

WOS:001282494000001

PERGAMON-ELSEVIER SCIENCE LTD

20243116777971

Earth atmosphere ; Mean square error ; Spatial distribution

Surveying:405.3 ; Atmospheric Properties:443.1 ; Engineering Graphics:902.1 ; Mathematics:921 ; Mathematical Statistics:922.2

GEOSCIENCES

Web of Science

1.Harbin Inst Technol, Sch Environm, Harbin, Peoples R China
2.Southern Univ Sci & Technol, Sch Environm Sci & Engn, Shenzhen, Guangdong, Peoples R China
3.MIT, Ctr Global Change Sci, Cambridge, MA 02139 USA
4.Guangdong Prov Observat & Res Stn Coastal Atmosphe, Shenzhen, Guangdong, Peoples R China
5.Southern Univ Sci & Technol, Sch Environm Sci & Engn, Shenzhen Key Lab Precis Measurement & Early Warnin, Shenzhen, Guangdong, Peoples R China
6.Fudan Univ, Inst Atmospher Sci, Dept Atmospher & Ocean Sci, Shanghai, Peoples R China
7.Beijing Jiaotong Univ, Engn Res Ctr Clean & Low Carbon Technol Intelligen, Sch Environm, Minist Educ, Beijing, Peoples R China
8.Fujian Normal Univ, Sch Geog Sci, Fuzhou, Fujian, Peoples R China

Li, Juan,Sheng, Jianxiong,Zhu, Lei,et al. Bayesian inversion of HFC-134a emissions in southern China from a new AGAGE site: Results from an observing system simulation experiment[J]. ATMOSPHERIC ENVIRONMENT,2024,334.

Li, Juan.,Sheng, Jianxiong.,Zhu, Lei.,Yao, Bo.,Wu, Jing.,...&Fu, Tzung-May.(2024).Bayesian inversion of HFC-134a emissions in southern China from a new AGAGE site: Results from an observing system simulation experiment.ATMOSPHERIC ENVIRONMENT,334.

Li, Juan,et al."Bayesian inversion of HFC-134a emissions in southern China from a new AGAGE site: Results from an observing system simulation experiment".ATMOSPHERIC ENVIRONMENT 334(2024).