TY - JOUR
T1 - Quantifying Contributions of Local Emissions and Regional Transport to NOX in Beijing Using TROPOMI Constrained WRF-Chem Simulation
AU - Zhu, Yizhi
AU - Hu, Qihou
AU - Gao, Meng
AU - Zhao, Chun
AU - Zhang, Chengxin
AU - Liu, Ting
AU - Tian, Yuan
AU - Yan, Liu
AU - Su, Wenjing
AU - Hong, Xinhua
AU - Liu, Cheng
N1 - Funding Information:
This research was supported by grants from the National Key Research and Development Program of China (No. 2017YFC0210002, 2018YFC0213104, 2016YFC0203302 and 2017YFC0212800), the National Natural Science Foundation of China (No. 41722501, 51778596, 41977184 and 41941011), Anhui Science and Technology Major Project (No. 18030801111), the Strategic Priority Research Program of the Chinese Academy of Sciences (No. XDA23020301), the National Key Project for Causes and Control of Heavy Air Pollution (No. DQGG0102 and DQGG0205), the Natural Science Foundation of Anhui Province (1908085QD170), Key Research and Development Project of Anhui Province (202004i07020002); the Youth Innovation Promotion Association of CAS (2021443); the Young Talent Project of the Center for Excellence in Regional Atmospheric Environment, CAS (CERAE202004).
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/5/1
Y1 - 2021/5/1
N2 - Air quality is strongly influenced by both local emissions and regional transport. Atmospheric chemical transport models can distinguish between emissions and regional transport sources in air pollutant concentrations. However, quantifying model inventories is challenging due to emission changes caused by the recent strict control measures taken by the Chinese government. In this study, we use NO2 column observations from the Tropospheric Monitoring Instrument to retrieve top-down nitrogen oxide (NOX) emissions and quantify the contributions of local emissions and regional transport to NOx in Beijing (BJ), from 1 November 2018 to 28 February 2019 (W_2018) and 1 November 2019 to 29 February 2020 (W_2019). In W_2018 and W_2019, the BJ bottom-up NOX emissions from the multi-resolution emission inventory for China in 2017 were overestimated by 11.8% and 40.5%, respectively, and the input of NOX from other cities to BJ was overestimated by 10.9% and 51.6%, respectively. The simulation using our adjusted inventory exhibited a much higher spatial agreement (slope = 1.0, R2 = 0.79) and reduced a mean relative error by 45% compared to those of bottom-up NOX emissions. The top-down inventory indicated that (1) city boundary transport contributes approximately 40% of the NOX concentration in BJ; (2) in W_2019, NOX emissions and transport in BJ decreased by 20.4% and 17.2%, respectively, compared to those of W_2018; (3) in W_2019, NOX influx substantially decreased (−699 g/s) in BJ compared to that of W_2018 despite negative meteorological conditions that should have increased NOx influx by +503 g/s. Overall, the contribution of intercity input to NOx in BJ has declined with decreasing emissions in the surrounding cities due to regional cooperative control measures, and the role of local emissions in BJ NOx levels was more prominent. Our findings indicate that local emissions may play vital roles in regional center city air quality.
AB - Air quality is strongly influenced by both local emissions and regional transport. Atmospheric chemical transport models can distinguish between emissions and regional transport sources in air pollutant concentrations. However, quantifying model inventories is challenging due to emission changes caused by the recent strict control measures taken by the Chinese government. In this study, we use NO2 column observations from the Tropospheric Monitoring Instrument to retrieve top-down nitrogen oxide (NOX) emissions and quantify the contributions of local emissions and regional transport to NOx in Beijing (BJ), from 1 November 2018 to 28 February 2019 (W_2018) and 1 November 2019 to 29 February 2020 (W_2019). In W_2018 and W_2019, the BJ bottom-up NOX emissions from the multi-resolution emission inventory for China in 2017 were overestimated by 11.8% and 40.5%, respectively, and the input of NOX from other cities to BJ was overestimated by 10.9% and 51.6%, respectively. The simulation using our adjusted inventory exhibited a much higher spatial agreement (slope = 1.0, R2 = 0.79) and reduced a mean relative error by 45% compared to those of bottom-up NOX emissions. The top-down inventory indicated that (1) city boundary transport contributes approximately 40% of the NOX concentration in BJ; (2) in W_2019, NOX emissions and transport in BJ decreased by 20.4% and 17.2%, respectively, compared to those of W_2018; (3) in W_2019, NOX influx substantially decreased (−699 g/s) in BJ compared to that of W_2018 despite negative meteorological conditions that should have increased NOx influx by +503 g/s. Overall, the contribution of intercity input to NOx in BJ has declined with decreasing emissions in the surrounding cities due to regional cooperative control measures, and the role of local emissions in BJ NOx levels was more prominent. Our findings indicate that local emissions may play vital roles in regional center city air quality.
KW - Meteorology
KW - Top-down nitrogen oxide emissions
KW - Transport
KW - Tropospheric monitoring instrument
KW - Weather research and forecasting with coupled chemistry
UR - http://www.scopus.com/inward/record.url?scp=85105944681&partnerID=8YFLogxK
U2 - 10.3390/rs13091798
DO - 10.3390/rs13091798
M3 - Journal article
AN - SCOPUS:85105944681
SN - 2072-4292
VL - 13
JO - Remote Sensing
JF - Remote Sensing
IS - 9
M1 - 1798
ER -
