1
|
Cheng B, Ma Y, Qin P, Wang W, Zhao Y, Liu Z, Zhang Y, Wei L. Characterization of air pollution and associated health risks in Gansu Province, China from 2015 to 2022. Sci Rep 2024; 14:14751. [PMID: 38926518 PMCID: PMC11208435 DOI: 10.1038/s41598-024-65584-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Accepted: 06/21/2024] [Indexed: 06/28/2024] Open
Abstract
Air pollution poses a major threat to both the environment and public health. The air quality index (AQI), aggregate AQI, new health risk-based air quality index (NHAQI), and NHAQI-WHO were employed to quantitatively evaluate the characterization of air pollution and the associated health risk in Gansu Province before (P-I) and after (P-II) COVID-19 pandemic. The results indicated that AQI system undervalued the comprehensive health risk impact of the six criteria pollutants compared with the other three indices. The stringent lockdown measures contributed to a considerable reduction in SO2, CO, PM2.5, NO2 and PM10; these concentrations were 43.4%, 34.6%, 21.4%, 17.4%, and 14.2% lower in P-II than P-I, respectively. But the concentration of O3 had no obvious improvement. The higher sandstorm frequency in P-II led to no significant decrease in the ERtotal and even resulted in an increase in the average ERtotal in cities located in northwestern Gansu from 0.78% in P-I to 1.0% in P-II. The cumulative distribution of NHAQI-based population-weighted exposure revealed that 24% of the total population was still exposed to light pollution in spring during P-II, while the air quality in other three seasons had significant improvements and all people were under healthy air quality level.
Collapse
Affiliation(s)
- Bowen Cheng
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Yuxia Ma
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China.
| | - Pengpeng Qin
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Wanci Wang
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Yuhan Zhao
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Zongrui Liu
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Yifan Zhang
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Linbo Wei
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China.
| |
Collapse
|
2
|
Zhao H, Wang Y, Zhang Z. Increased ground-level O 3 during the COVID-19 pandemic in China aggravates human health risks but has little effect on winter wheat yield. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 338:122713. [PMID: 37813142 DOI: 10.1016/j.envpol.2023.122713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 10/01/2023] [Accepted: 10/07/2023] [Indexed: 10/11/2023]
Abstract
In January 2020, the novel coronavirus (COVID-19) outbreak emerged in China, prompting the enforcement of stringent lockdown measures nationwide to contain its spread. Multiple studies have demonstrated that these measures successfully reduced the levels of air pollutants except for ozone (O3). However, the potential risks of nationwide O3 changes during this period remain uncertain. To address this gap, we evaluated the ecological and health effects of O3 using hourly O3 data from 1 January to 17 June in both 2020 and 2019. Our results indicated that all health and ecological indicators, except SUM06 (sum of all hourly O3 over 60 ppb), during the COVID-19 pandemic in 2020 increased most obviously in Stages 2 and 3 with the strictest control measures, compared to the same period in 2019. The national premature deaths due to short-term O3 exposure during Stages 2-3 in 2020 totaled 146,558 (95% CI: 79,386-213,730) for all non-accidental causes and 82,408 (95% CI: 30,522-134,295) for cardiovascular diseases, increasing by 18.78% and 18.76% in 2019, respectively. The most significant increase in health risks occurred in Hubei, followed by Jiangxi, Zhejiang, Hunan, and Shaanxi. In addition, the estimated national winter wheat production losses (WWPL) attributable to O3 amounted to 50.6 and 51.1 million metric tons for 2019 and 2020, respectively. Among the major winter wheat-producing provinces, Anhui and Jiangsu experienced a larger increase in WWPL, while Shandong and Hebei suffered a greater decrease in 2020 compared to 2019, resulting in little overall change in WWPL between the two years. These findings provided direct evidence of the harmful effects of O3 during the COVID-19 pandemic and serve as a valuable reference for future air pollution control.
Collapse
Affiliation(s)
- Hui Zhao
- School of Resources and Environmental Engineering, Jiangsu University of Technology, Changzhou, 213001, China; Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing, 210044, China.
| | - Yiyi Wang
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing, 210044, China; State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China
| | - Zhen Zhang
- Shaanxi Meteorological Service Center of Agricultural Remote Sensing and Economic Crops, Xi'an, 710014, China
| |
Collapse
|
3
|
Ma Y, Cheng B, Li H, Feng F, Zhang Y, Wang W, Qin P. Air pollution and its associated health risks before and after COVID-19 in Shaanxi Province, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 320:121090. [PMID: 36649879 PMCID: PMC9840128 DOI: 10.1016/j.envpol.2023.121090] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 01/11/2023] [Accepted: 01/13/2023] [Indexed: 05/05/2023]
Abstract
Air pollution is a serious environmental problem that damages public health. In the present study, we used the segmentation function to improve the health risk-based air quality index (HAQI) and named it new HAQI (NHAQI). To investigate the spatiotemporal distribution characteristics of air pollutants and the associated health risks in Shaanxi Province before (Period I, 2015-2019) and after (Period II, 2020-2021) COVID-19. The six criteria pollutants were analyzed between January 1, 2015, and December 31, 2021, using the air quality index (AQI), aggregate AQI (AAQI), and NHAQI. The results showed that compared with AAQI and NHAQI, AQI underestimated the combined effects of multiple pollutants. The average concentrations of the six criteria pollutants were lower in Period II than in Period I due to reductions in anthropogenic emissions, with the concentrations of PM2.5 (particulate matter ≤2.5 μm diameter), PM10 (PM ≤ 10 μm diameter) SO2, NO2, O3, and CO decreased by 23.5%, 22.5%, 45.7%, 17.6%, 2.9%, and 41.6%, respectively. In Period II, the excess risk and the number of air pollution-related deaths decreased considerably by 46.5% and 49%, respectively. The cumulative population distribution estimated using the NHAQI revealed that 61% of the total number of individuals in Shaanxi Province were exposed to unhealthy air during Period I, whereas this proportion decreased to 16% during Period II. Although overall air quality exhibited substantial improvements, the associated health risks in winter remained high.
Collapse
Affiliation(s)
- Yuxia Ma
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China.
| | - Bowen Cheng
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Heping Li
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Fengliu Feng
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Yifan Zhang
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Wanci Wang
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Pengpeng Qin
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| |
Collapse
|
4
|
Dong X, Zheng X, Wang C, Zeng J, Zhang L. Air pollution rebound and different recovery modes during the period of easing COVID-19 restrictions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 843:156942. [PMID: 35753487 PMCID: PMC9222490 DOI: 10.1016/j.scitotenv.2022.156942] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 06/20/2022] [Accepted: 06/20/2022] [Indexed: 05/16/2023]
Abstract
Although COVID-19 lockdown policies have improved air quality in numerous countries, there is a lack of empirical evidence on the extent to which recovery has resulted in air pollution rebound, and the differences and similarities among regions' recovery modes during the period of easing COVID-19 restrictions. Here, we used daily air quality data and the recovery index constructed by a city-pair inflow index for 119 cities in China to quantify the impact of recovery on air pollution from March 2 to October 30, 2020. Findings show that recovery has significantly increased air pollution. When the recovery level increased by 10 %, the concentration of PM2.5, SO2, and NO2 respectively deteriorated by 1.10, 0.33, 1.25 μg/m3, and the average growth rates of three air pollutants were about 3 %-6 %. Moreover, we used the counterfactual framework and time series clustering with wavelet transform to cluster the rebound trajectory of air pollution for 17 provinces into five recovery modes. Results show that COVID-19 has further intensified regional differentiations in economic development ability and green recovery trend. Three northwestern provinces dependent on their resource endowments belong to energy-intensive recovery mode, which have experienced a sharp rebound of air pollution for two months, thereby making green recovery more challenging to achieve. Three regions with a diversified industrial structure are in industrial-restructuring recovery mode, which has effectively returned to a normal level through adjusting industrial structure and technological innovation. Owing to local policies and the outbreak of COVID-19 in other countries, six provinces in policy-oriented and international trade-oriented recovery modes have not fully recovered to the level without COVID-19 until October 2020. The result highlights the importance of diversifying industrial structure, technological innovation, policy flexibility and industrial upgrading for different recovery modes to achieve long-term green recovery in the future.
Collapse
Affiliation(s)
- Xinyang Dong
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China
| | - Xinzhu Zheng
- School of Economics and Management, China University of Petroleum-Beijing, Beijing 102249, China
| | - Can Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China.
| | - Jinghai Zeng
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China
| | - Lixiao Zhang
- School of Environment, Beijing Normal University, Beijing 100875, China
| |
Collapse
|
5
|
Lei R, Nie D, Zhang S, Yu W, Ge X, Song N. Spatial and temporal characteristics of air pollutants and their health effects in China during 2019-2020. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 317:115460. [PMID: 35660829 DOI: 10.1016/j.jenvman.2022.115460] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 04/19/2022] [Accepted: 05/29/2022] [Indexed: 05/17/2023]
Abstract
This work presents the temporal and spatial characteristics of the major air pollutants and their associated health risks in China from 2019 to 2020, by using the monitoring data from 367 cities. The annual average PM2.5, PM10, NO2, SO2, CO, and O3 concentrations decreased by 10.9%, 13.2%, 9.3%, 10.1%, 9.4%, and 5.5% from 2019 to 2020. National average PM2.5 concentration in 2020 met the standard of 35 μg/m3, and that of O3 decreased from 2019. COVID-19 lockdown affected NO2 level dramatically, yet influences on PM2.5 and O3 were less clear-cut. Positive correlations between PM2.5 and O3 were found, even in winter in all five key regions, e.g., Jing-Jin-Ji (JJJ), FenWei Plain (FWP), Yangtze River Delta (YRD), Pearl River Delta (PRD) and Chengdu-Chongqing Region (CCR), indicating importance of secondary production for both PM2.5 and O3. Large seasonal variability of PM2.5-SO2 correlation indicates a varying role of SO2 to PM2.5 pollution in different seasons; and generally weak correlations in winter between PM2.5 and NO2 or SO2 reveal the complexity of secondary formation processes to PM2.5 pollution in winter. Multilinear regression analysis between PM2.5 and SO2, NO2 and CO demonstrates that PM2.5 is more sensitive to the change of NO2 than SO2 in JJJ, FWP, PRD and CCR, suggesting a priority of NOx emission control for future PM2.5 reduction. Furthermore, the new World Health Organization Air Quality Guidelines (WHO AQG2021) were adopted to calculate the excess health risks (ER) as well as the health-risk based air quality index (HAQIWHO) of the pollutants. Such assessment points out the severity of air pollution associated health risks under strict standards: 40.0% of days had HAQIWHO>100, while only 14.4% days had AQI>100. PM2.5 ER was generally larger than O3 ER, but O3 ER in low PM2.5 region (PRD) and during summer became more serious. Notably, NO2 ER became even more important than PM2.5 due to its strict limit of WHO AQG2021. Overall, our results highlight the increasing importance of O3 in both air quality evaluation and health risk assessment, and the importance of coordinated mitigation of multiple pollutants (mainly PM2.5, O3 and NO2) in protecting the public health.
Collapse
Affiliation(s)
- Ruoyuan Lei
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CIC-AEET), School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Dongyang Nie
- School of Environmental Science and Engineering, South University of Science and Technology of China, Shenzhen, 518055, China
| | - Shumeng Zhang
- Reading Academy, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Wanning Yu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CIC-AEET), School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Xinlei Ge
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CIC-AEET), School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
| | - Ninghui Song
- Nanjing Institute of Environmental Science, Ministry of Ecology and Environment, 210042, China.
| |
Collapse
|
6
|
Yang L, Hong S, He C, Huang J, Ye Z, Cai B, Yu S, Wang Y, Wang Z. Spatio-Temporal Heterogeneity of the Relationships Between PM 2.5 and Its Determinants: A Case Study of Chinese Cities in Winter of 2020. Front Public Health 2022; 10:810098. [PMID: 35480572 PMCID: PMC9035510 DOI: 10.3389/fpubh.2022.810098] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 03/21/2022] [Indexed: 11/17/2022] Open
Abstract
Fine particulate matter (PM2.5) poses threat to human health in China, particularly in winter. The pandemic of coronavirus disease 2019 (COVID-19) led to a series of strict control measures in Chinese cities, resulting in a short-term significant improvement in air quality. This is a perfect case to explore driving factors affecting the PM2.5 distributions in Chinese cities, thus helping form better policies for future PM2.5 mitigation. Based on panel data of 332 cities, we analyzed the function of natural and anthropogenic factors to PM2.5 pollution by applying the geographically and temporally weighted regression (GTWR) model. We found that the PM2.5 concentration of 84.3% of cities decreased after lockdown. Spatially, in the winter of 2020, cities with high PM2.5 concentrations were mainly distributed in Northeast China, the North China Plain and the Tarim Basin. Higher temperature, wind speed and relative humidity were easier to promote haze pollution in northwest of the country, where enhanced surface pressure decreased PM2.5 concentrations. Furthermore, the intensity of trip activities (ITAs) had a significant positive effect on PM2.5 pollution in Northwest and Central China. The number of daily pollutant operating vents of key polluting enterprises in the industrial sector (VOI) in northern cities was positively correlated with the PM2.5 concentration; inversely, the number of daily pollutant operating vents of key polluting enterprises in the power sector (VOP) imposed a negative effect on the PM2.5 concentration in these regions. This work provides some implications for regional air quality improvement policies of Chinese cities in wintertime.
Collapse
Affiliation(s)
- Lu Yang
- School of Resource and Environment Science, Wuhan University, Wuhan, China
| | - Song Hong
- School of Resource and Environment Science, Wuhan University, Wuhan, China
| | - Chao He
- College of Resources and Environment, Yangtze University, Wuhan, China
| | - Jiayi Huang
- Business School, The University of Sydney, Sydney, NSW, Australia
| | - Zhixiang Ye
- School of Resource and Environment Science, Wuhan University, Wuhan, China
| | - Bofeng Cai
- Center for Climate Change and Environmental Policy, Chinese Academy of Environmental Planning, Beijing, China
| | - Shuxia Yu
- College of Resource and Environment, Huazhong Agricultural University, Wuhan, China
| | - Yanwen Wang
- Economics and Management College, China University of Geosciences, Wuhan, China
| | - Zhen Wang
- College of Resource and Environment, Huazhong Agricultural University, Wuhan, China
| |
Collapse
|
7
|
Haghnazar H, Cunningham JA, Kumar V, Aghayani E, Mehraein M. COVID-19 and urban rivers: Effects of lockdown period on surface water pollution and quality- A case study of the Zarjoub River, north of Iran. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:27382-27398. [PMID: 34981401 PMCID: PMC8723709 DOI: 10.1007/s11356-021-18286-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 12/19/2021] [Indexed: 05/15/2023]
Abstract
Due to the spreading of the coronavirus (COVID-19) in Iran, restrictions and lockdown were announced to control the infection. In order to determine the effects of the lockdown period on the status of the water quality and pollution, the concentrations of Al, As, Ba, Cr, Cu, Mo, Ni, Pb, Se, and Zn, together with Na+, Mg2+, Ca2+ and electrical conductivity (EC), were measured in the Zarjoub River, north of Iran, in both pre-lockdown and post-lockdown periods. The results indicated that water pollution and associated human health risk reduced by an average of 30% and 39%, respectively, during the lockdown period. In addition, the multi-purpose water quality index also improved by an average of 34%. However, the water salinity and alkalinity increased during the lockdown period due to the increase of municipal wastewater and the use of disinfectants. The major sources of pollution were identified as weathering, municipal wastewater, industrial and agricultural effluents, solid waste, and vehicular pollution. PCA-MLR receptor model showed that the contribution of mixed sources of weathering and municipal wastewater in water pollution increased from 23 to 50% during the lockdown period. However, the contribution of mixed sources of industrial effluents and solid wastes reduced from 64 to 45%. Likewise, the contribution of traffic-related sources exhibited a reduction from 13% in the pre-lockdown period to 5% together with agricultural effluent in the post-lockdown period. Overall, although the lockdown period resulted in positive impacts on diminishing the level of water pollution caused by industrial and vehicular contaminants, the increase of municipal waste and wastewater is a negative consequence of the lockdown period.
Collapse
Affiliation(s)
- Hamed Haghnazar
- Department of Watershed Sciences, Utah State University, Logan, UT , USA
| | - Jeffrey A Cunningham
- Department of Civil and Environmental Engineering, University of South Florida, Tampa, FL, USA
| | - Vinod Kumar
- Department of Botany, Government Degree College, Ramban, 182,144, India
| | - Ehsan Aghayani
- Department of Environmental Health Engineering, Abadan University of Medical Sciences, Abadan, Iran
| | - Mojtaba Mehraein
- Faculty of Engineering, Kharazmi University, 15,719-14,911, No.43 South Mofatteh Ave, Tehran, Iran.
| |
Collapse
|
8
|
Zhou M, Hu T, Zhang W, Wang Q, Kong L, Zhou M, Rao P, Peng W, Chen X, Song X. COVID-19 pandemic: impacts on air quality and economy before, during and after lockdown in China in 2020. ENVIRONMENTAL TECHNOLOGY 2022:1-11. [PMID: 35244530 DOI: 10.1080/09593330.2022.2049894] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
ABSTRACTThis paper comprehensively evaluates the dynamic effects on China's environment and economy during the COVID-19 pandemic. Results show that the COVID-19 lockdown resulted in a temporary improvement in air quality. Furthermore, nitrogen dioxide (NO2) levels in the atmosphere in China were 36% lower than in the week after last year's Lunar New Year holiday, but this also led to an economic downturn. Moreover, the aerosol optical depth (AOD) decreased significantly. During the back-to-work period, the economy recovered and there was an increase in energy consumption, and CO2, NO2 emissions sharply increased to pre-lockdown levels. In the post-lockdown period, the AOD was lower than that of the same period last year. This study can provide reference for environmental policy making, as it demonstrates to what extent the control of pollution sources can improve air quality. Precise emission reduction and regional joint prevention and control are important and effective means for the prevention and control of O3 pollution. The health and economic benefits of COVID-19 pandemic control measures are incalculable. And this can provide an effective scientific basis and theoretical support for the prevention and control of air pollution.
Collapse
Affiliation(s)
- Mengge Zhou
- College of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai, People's Republic of China
| | - Tingting Hu
- College of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai, People's Republic of China
| | - Wenqi Zhang
- College of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai, People's Republic of China
| | - Qi Wang
- College of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai, People's Republic of China
| | - Lin Kong
- National University of Singapore, Singapore, Singapore
| | - Menglong Zhou
- Huanghe S & T University, Zhengzhou, People's Republic of China
| | - Pinhua Rao
- College of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai, People's Republic of China
| | - Wangminzi Peng
- Jiangxi Meteorological Station, Nanchang, People's Republic of China
| | - Xiangxiang Chen
- Jiangxi Meteorological Station, Nanchang, People's Republic of China
| | - Xiaojuan Song
- Hubei University of Medicine, Shiyan, People's Republic of China
| |
Collapse
|
9
|
Feng Z, Zheng F, Liu Y, Fan X, Yan C, Zhang Y, Daellenbach KR, Bianchi F, Petäjä T, Kulmala M, Bao X. Evolution of organic carbon during COVID-19 lockdown period: Possible contribution of nocturnal chemistry. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 808:152191. [PMID: 34875334 PMCID: PMC8651497 DOI: 10.1016/j.scitotenv.2021.152191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 11/15/2021] [Accepted: 12/01/2021] [Indexed: 05/03/2023]
Abstract
Carbonaceous aerosol is one of the main components of atmospheric particulate matter, which is of great significance due to its role in climate change, earth's radiation balance, visibility, and human health. In this work, carbonaceous aerosols were measured in Shijiazhuang and Beijing using the OC/EC analyzer from December 1, 2019 to March 15, 2020, which covered the Coronavirus Disease 2019 (COVID-19) pandemic. The observed results show that the gas-phase pollutants, such as NO, NO2, and aerosol-phase pollutants (Primary Organic Compounds, POC) from anthropogenic emissions, were significantly reduced during the lockdown period due to limited human activities in North China Plain (NCP). However, the atmospheric oxidation capacity (Ox/CO) shows a significantly increase during the lockdown period. Meanwhile, additional sources of nighttime Secondary Organic Carbon (SOC), Secondary Organic Aerosol (SOA), and babs, BrC(370 nm) are observed and ascribed to the nocturnal chemistry related to NO3 radical. The Potential Source Contribution Function (PSCF) analysis indicates that the southeast areas of the NCP region contributed more to the SOC during the lockdown period than the normal period. Our results highlight the importance of regional nocturnal chemistry in SOA formation.
Collapse
Affiliation(s)
- Zemin Feng
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Feixue Zheng
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Yongchun Liu
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China; College of Chemistry and Chemical Engineering, China West Normal University, Nanchong 637002, China.
| | - Xiaolong Fan
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Chao Yan
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
| | - Yusheng Zhang
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Kaspar R Daellenbach
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
| | - Federico Bianchi
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
| | - Tuukka Petäjä
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
| | - Markku Kulmala
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China; Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
| | - Xiaolei Bao
- Hebei Provincial Academy of Environmental Sciences, Shijiazhuang 050037, China; Hebei Chemical & Pharmaceutical College, Shijiazhuang 050026, China.
| |
Collapse
|
10
|
Shen F, Hegglin MI, Luo Y, Yuan Y, Wang B, Flemming J, Wang J, Zhang Y, Chen M, Yang Q, Ge X. Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China. NPJ CLIMATE AND ATMOSPHERIC SCIENCE 2022; 5:54. [PMID: 35789740 PMCID: PMC9244310 DOI: 10.1038/s41612-022-00276-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 06/06/2022] [Indexed: 05/07/2023]
Abstract
The COVID-19 restrictions in 2020 have led to distinct variations in NO2 and O3 concentrations in China. Here, the different drivers of anthropogenic emission changes, including the effects of the Chinese New Year (CNY), China's 2018-2020 Clean Air Plan (CAP), and the COVID-19 lockdown and their impact on NO2 and O3 are isolated by using a combined model-measurement approach. In addition, the contribution of prevailing meteorological conditions to the concentration changes was evaluated by applying a machine-learning method. The resulting impact on the multi-pollutant Health-based Air Quality Index (HAQI) is quantified. The results show that the CNY reduces NO2 concentrations on average by 26.7% each year, while the COVID-lockdown measures have led to an additional 11.6% reduction in 2020, and the CAP over 2018-2020 to a reduction in NO2 by 15.7%. On the other hand, meteorological conditions from 23 January to March 7, 2020 led to increase in NO2 of 7.8%. Neglecting the CAP and meteorological drivers thus leads to an overestimate and underestimate of the effect of the COVID-lockdown on NO2 reductions, respectively. For O3 the opposite behavior is found, with changes of +23.3%, +21.0%, +4.9%, and -0.9% for CNY, COVID-lockdown, CAP, and meteorology effects, respectively. The total effects of these drivers show a drastic reduction in multi-air pollutant-related health risk across China, with meteorology affecting particularly the Northeast of China adversely. Importantly, the CAP's contribution highlights the effectiveness of the Chinese government's air-quality regulations on NO2 reduction.
Collapse
Affiliation(s)
- Fuzhen Shen
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, 210044 Nanjing, China
- Department of Meteorology, University of Reading, Reading, RG6 6BX UK
- Institute of Energy and Climate Research, IEK-7: Stratosphere, Forschungszentrum Jülich, 52425 Jülich, Germany
| | - Michaela I. Hegglin
- Department of Meteorology, University of Reading, Reading, RG6 6BX UK
- Institute of Energy and Climate Research, IEK-7: Stratosphere, Forschungszentrum Jülich, 52425 Jülich, Germany
| | | | - Yue Yuan
- Jining Meteorological Bureau, 272000 Shandong, China
| | - Bing Wang
- Henley Business School, University of Reading, Reading, RG6 6UD UK
| | | | - Junfeng Wang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, 210044 Nanjing, China
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138 USA
| | - Yunjiang Zhang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, 210044 Nanjing, China
| | - Mindong Chen
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, 210044 Nanjing, China
| | - Qiang Yang
- Hongkong University of Science and Technology, 999007 Hong Kong, China
| | - Xinlei Ge
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, 210044 Nanjing, China
| |
Collapse
|
11
|
Chang HH, Meyerhoefer CD, Yang FA. COVID-19 prevention, air pollution and transportation patterns in the absence of a lockdown. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2021; 298:113522. [PMID: 34426221 PMCID: PMC8352669 DOI: 10.1016/j.jenvman.2021.113522] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 06/26/2021] [Accepted: 08/07/2021] [Indexed: 05/04/2023]
Abstract
Recent studies demonstrate that air quality improved during the coronavirus pandemic due to the imposition of social lockdowns. We investigate the impact of COVID-19 on air pollution in the two largest cities in Taiwan, which were not subject to economic or mobility restrictions. Using a difference-in-differences approach and real-time data on air quality and transportation, we estimate that anthropogenic air pollution from local sources increased during working days and decreased during non-working days during the COVID-19 pandemic. This led to a 3-7 percent increase in CO, O3, SO2, PM10 and PM2.5. We demonstrate that the increase in air pollution resulted from a shift in preferred mode of travel away from public transportation and towards personal motor vehicles during working days. In particular, metro and shared bicycle usage decreased between 8 and 18 percent, on average, while automobile and scooter use increased between 11 and 21 percent during working days. Similar COVID-19 prevention behaviors in regions or countries emerging from lockdowns could likewise result in an increase in air pollution. Taking action to reduce the transmissibility of COVID-19 on metro cars, trains and buses could help policymakers limit the substitution of personal motor vehicles for public transit, and mitigate increases in air pollution when lifting mobility restrictions.
Collapse
Affiliation(s)
- Hung-Hao Chang
- Department of Agricultural Economics, National Taiwan University, No 1, Roosevelt Rd, Sec 4, Taipei, 10617, Taiwan.
| | - Chad D Meyerhoefer
- College of Business, Lehigh University, Rauch Business Center, 621 Taylor St., Bethlehem, PA, 18015, USA.
| | - Feng-An Yang
- Department of Agricultural Economics, National Taiwan University, No 1, Roosevelt Rd, Sec 4, Taipei, 10617, Taiwan.
| |
Collapse
|
12
|
Quantifying Air Pollutant Variations during COVID-19 Lockdown in a Capital City in Northwest China. ATMOSPHERE 2021. [DOI: 10.3390/atmos12060788] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
In the context of the outbreak of coronavirus disease 2019 (COVID-19), strict lockdown policies were implemented to control nonessential human activities in Xi’an, northwest China, which greatly limited the spread of the pandemic and affected air quality. Compared with pre-lockdown, the air quality index and concentrations of PM2.5, PM10, SO2, and CO during the lockdown reduced, but the reductions were not very significant. NO2 levels exhibited the largest decrease (52%) during lockdown, owing to the remarkable decreased motor vehicle emissions. The highest K+ and lowest Ca2+ concentrations in PM2.5 samples could be attributed to the increase in household biomass fuel consumption in suburbs and rural areas around Xi’an and the decrease in human physical activities in Xi’an (e.g., human travel, vehicle emissions, construction activities), respectively, during the lockdown period. Secondary chemical reactions in the atmosphere increased in the lockdown period, as evidenced by the increased O3 level (increased by 160%) and OC/EC ratios in PM2.5 (increased by 26%), compared with pre-lockdown levels. The results, based on a natural experiment in this study, can be used as a reference for studying the formation and source of air pollution in Xi’an and provide evidence for establishing future long-term air pollution control policies.
Collapse
|