key: cord-0772983-h32c0edg
authors: Zhao, Na; Wang, Gang; Li, Guohao; Lang, Jianlei; Zhang, Hanyu
title: Air pollution episodes during the COVID-19 outbreak in the Beijing–Tianjin–Hebei region of China: An insight into the transport pathways and source distribution()
date: 2020-09-08
journal: Environ Pollut
DOI: 10.1016/j.envpol.2020.115617
sha: e9d4191c471b2117e2c9ab39137811723a2478c4
doc_id: 772983
cord_uid: h32c0edg

Although anthropogenic emissions decreased, polluted days still occurred in the Beijing–Tianjin–Hebei (BTH) region during the initial outbreak of the coronavirus disease (COVID-19). Analysis of the characteristics and source distribution of large-scale air pollution episodes during the COVID-19 outbreak (from 23 January to 8 April 2020) in the BTH region is helpful for exploring the efficacy of control measures and policy making. The results indicated that the BTH region suffered two large-scale air pollution episodes (23–28 January and 8–13 February), which were characterized by elevated PM(2.5), SO(2), NO(2), and CO concentrations, while the O(3) concentration decreased by 1.5%–33.9% (except in Shijiazhuang, where it increased by 16.6% during the second episode). These large-scale air pollution episodes were dominated by unfavorable meteorological conditions comprising a low wind speed and increased relative humidity. The transport pathways and source distribution were explored using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT), potential source contribution function (PSCF), and concentration weighted trajectory (CWT) models. The air pollution in the BTH region was mainly affected by local emission sources during the first episode, which contributed 51.6%–60.6% of the total trajectories in the BTH region with a PM(2.5) concentration ranging from 146.2 μg/m(3) to 196.7 μg/m(3). The short-distance air masses from the southern and southwestern areas of the BTH region were the main transport pathways of airflow arriving in the BTH region during the second episode. These contributed 51.9%–57.9% of the total trajectories and originated in Hebei, Henan, central Shanxi, and Shaanxi provinces, which were the areas contributing the most to the PM(2.5) level and exhibited the highest PSCF and CWT values. Therefore, on the basis of local emission reduction, enhancing regional environmental cooperation and implementing a united prevention and control of air pollution are effective mitigation measures for the BTH region.

episodes during the COVID-19 outbreak (from 23 January to 8 April 2020) in the BTH region is 23 helpful for exploring the efficacy of control measures and policy making. The results indicated 24 that the BTH region suffered two large-scale air pollution episodes (23-28 January and 8-13 25 February), which were characterized by elevated PM 2.5 , SO 2 , NO 2 , and CO concentrations, while 26 the O 3 concentration decreased by 1.5%-33.9% (except in Shijiazhuang, where it increased by 27 16.6% during the second episode). These large-scale air pollution episodes were dominated by 28 unfavorable meteorological conditions comprising a low wind speed and increased relative 29 humidity. The transport pathways and source distribution were explored using the Hybrid Single 30 Particle Lagrangian Integrated Trajectory (HYSPLIT), potential source contribution function 31 (PSCF), and concentration weighted trajectory (CWT) models. The air pollution in the BTH 32 region was mainly affected by local emission sources during the first episode, which contributed 33 51.6%-60.6% of the total trajectories in the BTH region with a PM 2.5 concentration ranging from 34 146.2 μg/m 3 to 196.7 μg/m 3 . The short-distance air masses from the southern and southwestern 35 areas of the BTH region were the main transport pathways of airflow arriving in the BTH region 36 during the second episode. These contributed 51.9%-57.9% of the total trajectories and 37 originated in Hebei, Henan, central Shanxi, and Shaanxi provinces, which were the areas 38 contributing the most to the PM 2.5 level and exhibited the highest PSCF and CWT values. 39 Therefore, on the basis of local emission reduction, enhancing regional environmental 40 cooperation and implementing a united prevention and control of air pollution are effective 41 mitigation measures for the BTH region.

The coronavirus disease (COVID-19) broke out worldwide in the first half of 2020 and became 51 a global public health threat. Unconventional and stringent prevention and control measures were 52 implemented by many countries and cities to prevent the further spread of the virus. In China, 53 preventive lockdown was first implemented on 23 January 2020 in Wuhan, Hubei Province, and 54 was subsequently followed by other provinces and cities (Le et al., 2020) . Through a joint 55 national effort, the lockdown was gradually lifted, with Wuhan being the last city in China to be 56 removed from lockdown on 8 April 2020. 57 Overall, the air quality in China "Olympic blue", "APEC blue", and "Parade blue". The emission reduction rates for SO 2 , NO x , volatile organic compounds (VOCs), and PM 2.5 in Beijing during these events were 35%-41%, 78 44%-51%, 30%-57%, and 37%-42%, respectively (no value for PM 2.5 during the 2008 Olympics) 79 (Wang et al., 2010 and 2017). However, the meteorological conditions and pollutant emissions 80 during the COVID-19 outbreak were different from these three earlier events or other studied 81 periods. Firstly, the previous three events were held during the summer and autumn in Beijing 82 when no air pollution episodes occurred. The regional transport pathways of air masses may be 83 influenced by the local climate in different seasons (Wang et al., 2015b). Secondly, the potential 84 source regions may be influenced by the emission distribution. In the case of the COVID-19 85 lockdown period, there was a larger impact scope and a longer impact time with a significant 86 emission reduction compared with previous three earlier events. Chen et al (2020b) reported that 87 nationwide contingency plans were implemented to shut down traffic and public activities in 88 China, and that almost everyone was isolated at home during the COVID-19. 89 The Beijing-Tianjin-Hebei (BTH) region is the largest economic core area in northern China; 90 it has highest level of development and generated 8.5% of the total national gross domestic The COVID-19 lockdown in China provided an excellent opportunity to investigate the 99 corresponding air pollution characteristics and source distribution in the BTH region. To provide 100 a sound basis for the effective control of urban agglomerated air pollution, it is of great Backward trajectory, PSCF, and CWT analyses were conducted to explore the transport pathways 105 and potential source regions of air pollutants during pollution episodes. The results can help to 106 guide future control strategies and policy making in the BTH region. In this study, Beijing, Tianjin, and Shijiazhuang were selected to analysis the air quality and 112 pollution episodes in the BTH region. Beijing, as the capital of China, is the center of politics, 113 economics, and culture. Tianjin is one of the four directly governed municipalities of China. 114 Shijiazhuang, as the capital of Hebei Province, is an important industrial city in the BTH region. 115 The hourly concentrations of PM 2.5 , SO 2 , NO 2 , O 3 , and CO from 35 monitoring stations in 116 Beijing, Tianjin, and Shijiazhuang were obtained from China's National Environmental 117 Monitoring Centre for the period from 23 January to 8 April 2020. The standard procedure (e.g., 118 monitoring system, analysis method, quality assurance, and quality control) for monitoring of 119 pollutants are illustrated in the Text S1. Additionally, hourly meteorological data including wind 120 speed, relative humidity, and visibility for Beijing, Tianjin, and Shijiazhuang were collected from The PSCF is a conditional probability function that can be applied to identify potential source Despite this, polluted days accounted for 20.8%, 29.9%, and 40.3% of the total number of 181 outbreak days in Beijing, Tianjin, and Shijiazhuang, respectively. In particular, 11.7% of the days 182 during the COVID-19 outbreak were heavily polluted in Shijiazhuang (Fig. 2) , thus indicating an 183 urgent need to control air pollution. Therefore, the government faces a considerable challenge to 184 effectively tackle the serious regional air pollution in the BTH region. The potential source regions with higher WCWT values generally agreed with the results of the 349 WPSCF during the first pollution episode (Fig. 8a-c) . However, the results of WCWT differed to 350 the WPSCF results in some aspects in Beijing, whereby high WCWT values were also found in 351 Tangshan. In addition, the regions with lower WCWT values indicate that PM 2.5 pollution in the 352 BTH region was unaffected by long-distance transport from eastern Inner Mongolia and eastern 353 China during this episode. 25.5 ± 11.9, 33.2 ± 6.4, 43.7 ± 8.4

4.4 ± 2.6, 9.3 ± 2.7, 4.7 ± 1.7 0.7 ± 0.5, 1.3 ± 0.5, 1. 15.8 ± 9.7, 5.2 ± 4.6, 2.9 ± 3.1 46.7% ± 19.4%, 58.2% ± 7.3%, 71.2% ± 9.9%

1.8 ± 0.9, 0.8 ± 0.5, 0.8 ± 0.3 0 60 120 Humidity (%) 1.6 ± 1.0, 0.4 ± 0.3, 0.5 ± 0.3 53.6% ± 22.8%, 72.0% ± 7.4%, 82.6% ± 13.2%

18.2 ± 10.3, 5.4 ± 4.6, 4.5 ± 5.9 2.0 ± 0.9, 1.2 ± 0.3, 1.7 ± 0.4 51.4% ± 19.2%, 66.3% ± 3.4%, 56.0% ± 17.9% 11.5 ± 8.4, 2.3 ± 0.5, 4.8 ± 3.7 

Puzzling haze events in China during the coronavirus (COVID-19) shutdown

Impact of quarantine measures on 456 chemical compositions of PM 2.5 during the COVID-19 epidemic in

Influence of COVID-19 event on air quality and 459 their association in mainland China

Unexpected air pollution with 494 marked emission reductions during the COVID-19 outbreak in China

Identification 497 of long-range transport pathways and potential sources of PM 2.5 and PM 10 in Beijing from 498

Characteristics and source distribution of air 500 pollution in winter in Qingdao, eastern China

A severe fog-haze episode in 503

Hebei region: Characteristics, sources and impacts of boundary layer 504 structure

A paradox for air pollution 506 controlling in China revealed by "APEC Blue" and

Pollution characteristics and regional migration 509 impact of PM 2.5 in Beijing in winter season (in Chinese)

Chemical characteristics and source apportionment of water-soluble ions in PM 2

Master's thesis

Ministry of ecology and environment of the people's republic of China (MEE)

China's ecological environment in 2019

Weighted concentration weighted trajectory (WCWT) maps for PM 2.5 arriving in the 669

and (c) refer to the 670 WCWT during the first pollution episode from 23 to 28

J o u r n a l P r e -p r o o f

☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:J o u r n a l P r e -p r o o f