1
|
Wang Z, Tian X, Xie P, Xu J, Zheng J, Pan Y, Zhang T, Fan G. A convolutional neural networks method for tropospheric ozone vertical distribution retrieval from Multi-AXis Differential Optical Absorption Spectroscopy measurements. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 951:175049. [PMID: 39067587 DOI: 10.1016/j.scitotenv.2024.175049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 07/20/2024] [Accepted: 07/24/2024] [Indexed: 07/30/2024]
Abstract
The vertical distribution of tropospheric ozone (O3) is crucial for understanding atmospheric physicochemical processes. A Convolutional Neural Networks (CNN) method for the retrieval of tropospheric O3 vertical distribution from ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements to tackle the issue of stratospheric O3 absorption interference faced by MAX-DOAS in obtaining tropospheric O3 profiles. Firstly, a hybrid model, named PCA-F_Regression-SVR, is developed to screen features sensitive to O3 inversion based on the MAX-DOAS spectra and EAC4 reanalysis O3 profiles, which incorporates Principal Component Analysis (PCA), F_Regression function, and Support Vector Regression (SVR) algorithm. Thus, these screened features for ancillary inversion include the profiles of temperature, specific humidity, fraction of cloud coverage, eastward and northward wind, the profiles of SO2, NO2, and HCHO, as well as season and time features to serve as sensitive factors. Secondly, the preprocessed MAX-DOAS spectra dataset and the sensitive factor dataset are utilized as input, while the O3 profiles of the EAC4 reanalysis dataset incorporating the surface O3 concentrations are employed as output for constructing the CNN model. The Mean Absolute Percentage Error (MAPE) decreases from 26 % to approximately 19 %. Finally, the CNN model is applied for inversion and comparison of tropospheric O3 profiles using independent input data. The CNN model effectively reproduces the O3 profiles of the EAC4 dataset, showing a Gaussian-like spatial distribution with peaks primarily around 950 hPa (550 m). Since the reanalysis data used for model training has been smoothed, the CNN model is insensitive to extreme values. This behavior can be attributed to the MAPE loss function, which evaluates Absolute Percentage Errors (APEs) of O₃ concentration at all altitudes, resulting in varying retrieval accuracy across different altitudes while maintaining overall MAPE control. Temporally, the CNN model tends to overestimate surface O3 in summer by around 20 μg/m3, primarily due to the influence of the temperature feature in the sensitivity factor dataset. In conclusion, leveraging MAX-DOAS spectra enables the retrieval of tropospheric O3 vertical distribution through the established CNN model.
Collapse
Affiliation(s)
- Zijie Wang
- Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Xin Tian
- Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China.
| | - Pinhua Xie
- Key Laboratory of Environmental Optical and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China.
| | - Jin Xu
- Key Laboratory of Environmental Optical and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Jiangyi Zheng
- Key Laboratory of Environmental Optical and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Yifeng Pan
- Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Tianshu Zhang
- Key Laboratory of Environmental Optical and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Guangqiang Fan
- Key Laboratory of Environmental Optical and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| |
Collapse
|
2
|
Jiang Y, Zhang A, Zou Q, Zhang L, Zuo H, Ding J, Wang Z, Li Z, Jin L, Xu D, Sun X, Zhao W, Xu B, Li X. Long-Term Halocarbon Observations in an Urban Area of the YRD Region, China: Characteristic, Sources Apportionment and Health Risk Assessment. TOXICS 2024; 12:738. [PMID: 39453158 PMCID: PMC11511214 DOI: 10.3390/toxics12100738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2024] [Revised: 10/07/2024] [Accepted: 10/10/2024] [Indexed: 10/26/2024]
Abstract
To observe the long-term variations in halocarbons in the Yangtze River Delta (YRD) region, this study analyzes halocarbon concentrations and composition characteristics in Shanxi from 2018 to 2020, exploring their origins and the health effects. The total concentration of halocarbons has shown an overall increasing trend, which is driven by both regulated substances (CFC-11 and CFC-113) and unregulated substances, such as dichloromethane, chloromethane and chloroform. The results of the study also reveal that dichloromethane (1.194 ± 1.003 to 1.424 ± 1.004 ppbv) and chloromethane (0.205 ± 0.185 to 0.666 ± 0.323 ppbv) are the predominant halocarbons in Shanxi, influenced by local and northwestern emissions. Next, this study identifies that neighboring cities in Zhejiang Province and other YRD areas are potentially affected by backward trajectory models. Notably, chloroform and 1,2-dichloroethane have consistently surpassed acceptable thresholds, indicating a significant carcinogenic risk associated with solvent usage. This research sheds light on the evolution of halocarbons in the YRD region, offering valuable data for the control and reduction in halocarbon emissions.
Collapse
Affiliation(s)
- Yuchun Jiang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
| | - Anqi Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Qiaoli Zou
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
- Zhejiang Key Laboratory of Ecological and Environmental Monitoring, Forewarning and Quality Control, Hangzhou 310012, China
| | - Lu Zhang
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
- Zhejiang Key Laboratory of Ecological and Environmental Monitoring, Forewarning and Quality Control, Hangzhou 310012, China
| | - Hanfei Zuo
- College of Environmental and Resource Sciences, Zhejiang Provincial Key Laboratory of Organic Pollution Process and Control, Zhejiang University, Hangzhou 310058, China
| | - Jinmei Ding
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
- Zhejiang Key Laboratory of Ecological and Environmental Monitoring, Forewarning and Quality Control, Hangzhou 310012, China
| | - Zhanshan Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Zhigang Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Lingling Jin
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
- Zhejiang Key Laboratory of Ecological and Environmental Monitoring, Forewarning and Quality Control, Hangzhou 310012, China
| | - Da Xu
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
- Zhejiang Key Laboratory of Ecological and Environmental Monitoring, Forewarning and Quality Control, Hangzhou 310012, China
| | - Xin Sun
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
- Zhejiang Key Laboratory of Ecological and Environmental Monitoring, Forewarning and Quality Control, Hangzhou 310012, China
| | - Wenlong Zhao
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
- Zhejiang Key Laboratory of Ecological and Environmental Monitoring, Forewarning and Quality Control, Hangzhou 310012, China
| | - Bingye Xu
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
- Zhejiang Key Laboratory of Ecological and Environmental Monitoring, Forewarning and Quality Control, Hangzhou 310012, China
| | - Xiaoqian Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| |
Collapse
|
3
|
Hong Q, Xing J, Xing C, Yang B, Su W, Chen Y, Zhang C, Zhu Y, Liu C. Investigating vertical distributions and photochemical indications of formaldehyde, glyoxal, and NO 2 from MAX-DOAS observations in four typical cities of China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 954:176447. [PMID: 39307370 DOI: 10.1016/j.scitotenv.2024.176447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Revised: 09/05/2024] [Accepted: 09/19/2024] [Indexed: 09/26/2024]
Abstract
Formaldehyde (HCHO), glyoxal (CHOCHO), and nitrogen dioxide (NO2) are crucial in atmospheric photochemical processes at both surface and elevated altitudes. This study presents synchronous multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of the vertical distributions of summertime HCHO, CHOCHO and NO2 in four representative megacities within the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), Sichuan Basin (SB), and Pearl River Delta (PRD) regions of China. The vertical distributions of HCHO and CHOCHO tended to occur at higher altitudes compared to NO2, influenced by both primary emissions near the ground and photochemical oxidation processes at elevated altitudes. Source separation regression analysis using the CO-CHOCHO trace pair identified secondary formation as the predominant source of ambient HCHO. In urban areas, the ratio of CHOCHO to secondary HCHO (RGFsec) serves as a more reliable metric at ground level for diagnosing VOC precursor sources, excluding the interference of primary and background HCHO. The increase in RGF values at higher altitudes highlights the relative contribution of VOCs favoring CHOCHO production. Moreover, four indicators (e.g. FNR, FNRsec, GNR, and MNR) were utilized to characterize O3 formation sensitivity at different altitudes. The range of FNR, FNRsec, GNR, and MNR marking the O3 formation sensitivity regime varies regionally, highlighting the need for localized assessments. The VOC-limited regime dominated at the ground level, whereas the contribution of the NOx-limited regime increased with altitude. Therefore, a comprehensive control strategy addressing both VOC and NOx emissions across different altitudes is essential for effectively mitigating photochemical pollution in urban areas of China.
Collapse
Affiliation(s)
- Qianqian Hong
- Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), Wuxi University, Wuxi 214105, China
| | - Jingchen Xing
- School of Environmental and Ecology, Jiangnan University, Wuxi 214122, China
| | - Chengzhi Xing
- Key Lab of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China.
| | - Baixue Yang
- School of Environmental and Ecology, Jiangnan University, Wuxi 214122, China
| | - Wenjing Su
- School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China
| | - Yujia Chen
- Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China; Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
| | - Chengxin Zhang
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
| | - Yizhi Zhu
- School of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou 215009, China
| | - Cheng Liu
- Key Lab of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
| |
Collapse
|
4
|
Chen TL, Hsiao TC, Chen AY, Chang KE, Lin TC, Griffith SM, Chou CCK. A traffic-induced shift of ultrafine particle sources under COVID-19 soft lockdown in a subtropical urban area. ENVIRONMENT INTERNATIONAL 2024; 187:108658. [PMID: 38640612 DOI: 10.1016/j.envint.2024.108658] [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: 02/04/2024] [Revised: 04/10/2024] [Accepted: 04/11/2024] [Indexed: 04/21/2024]
Abstract
During the unprecedented COVID-19 city lockdown, a unique opportunity arose to dissect the intricate dynamics of urban air quality, focusing on ultrafine particles (UFPs) and volatile organic compounds (VOCs). This study delves into the nuanced interplay between traffic patterns and UFP emissions in a subtropical urban setting during the spring-summer transition of 2021. Leveraging meticulous roadside measurements near a traffic nexus, our investigation unravels the intricate relationship between particle number size distribution (PNSD), VOCs mixing ratios, and detailed vehicle activity metrics. The soft lockdown era, marked by a 20-27% dip in overall traffic yet a surprising surge in early morning motorcycle activity, presented a natural experiment. We observed a consequential shift in the urban aerosol regime: the decrease in primary emissions from traffic substantially amplified the role of aged particles and secondary aerosols. This shift was particularly pronounced under stagnant atmospheric conditions, where reduced dilution exacerbated the influence of alternative emission sources, notably solvent evaporation, and was further accentuated with the resumption of normal traffic flows. A distinct seasonal trend emerged as warmer months approached, with aromatic VOCs such as toluene, ethylbenzene, and xylene not only increasing but also significantly contributing to more frequent particle growth events. These findings spotlight the criticality of targeted strategies at traffic hotspots, especially during periods susceptible to weak atmospheric dilution, to curb UFP and precursor emissions effectively. As we stand at the cusp of widespread vehicle electrification, this study underscores the imperative of a holistic approach to urban air quality management, embracing the complexities of primary emission reductions and the resultant shifts in atmospheric chemistry.
Collapse
Affiliation(s)
- Tse-Lun Chen
- Institute of Environmental Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan; Graduate Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan
| | - Ta-Chih Hsiao
- Graduate Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan; Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan.
| | - Albert Y Chen
- Department of Civil Engineering, National Taiwan University, Taipei, Taiwan
| | - Kuo-En Chang
- Graduate Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan
| | - Tzu-Chi Lin
- Graduate Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan
| | - Stephen M Griffith
- Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan
| | - Charles C-K Chou
- Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan
| |
Collapse
|
5
|
Ni W, Xing Y, Li G, Du Z, Yang P, Wang Q, Yang X, Lyu B, Fa H, Shi Q, Xing Q. Windows of sensitivity for risk of adverse birth outcomes related to gestational PM 2.5 exposure: Evidence from a natural experiment. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 347:123759. [PMID: 38462193 DOI: 10.1016/j.envpol.2024.123759] [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: 10/23/2023] [Revised: 03/02/2024] [Accepted: 03/07/2024] [Indexed: 03/12/2024]
Abstract
While numerous studies have associated maternal exposure to PM2.5 with adverse birth outcomes, findings remain inconsistent and difficult to generalize. We aimed to investigate the causal relationship and window of sensitivity between gestational exposure to PM2.5 and birth outcomes. We leveraged high-resolution satellite data to quantify gestational PM2.5 exposure at the individual level, along with a combined model to determine daily relative risks (RRs) of birth outcomes in COVID-19 prelockdown and lockdown groups. RRs between the two groups were further compared using a longitudinal pre-post non-experimental design to identify sensitivity windows of adverse birth outcomes. A total of 73,781 pregnant women from the COVID-19 prelockdown group and 6267 pregnant women from the lockdown group were included for analysis. The daily mean PM2.5 concentrations in the lockdown group decreased by 21.7% compared to the prelockdown group. During the first trimester, every 10 μg/m3 increase in PM2.5 significantly increased the risk of congenital abnormalities of major organs such as the cardiovascular system, gastrointestinal tract, nervous system, urinary system, and respiratory system. Moreover, gestational exposure to PM2.5 during the first trimester was associated with higher risks of premature delivery and term low birth weight. While PM2.5 exposure during the second trimester was positively correlated with macrosomia. Gestational exposure to PM2.5 is associated with increased risks of various adverse birth outcomes with specific sensitive windows. We demonstrated that gestational exposure to PM2.5 increased risks of various adverse birth outcomes with specific window of sensitivity through the natural experiment design. Our findings underscore the urgent need for policies and initiatives targeting PM2.5 reduction, especially during critical periods of pregnancy.
Collapse
Affiliation(s)
- Wei Ni
- Qingdao Women and Children's Hospital, Qingdao University, Qingdao City, Shandong Province, China; State Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, Chongqing, China
| | - Yuhan Xing
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China; School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 518107, China
| | - Guoju Li
- Qingdao Women and Children's Hospital, Qingdao University, Qingdao City, Shandong Province, China
| | - Zhanhui Du
- Qingdao Women and Children's Hospital, Qingdao University, Qingdao City, Shandong Province, China
| | - Ping Yang
- Qingdao Women and Children's Hospital, Qingdao University, Qingdao City, Shandong Province, China
| | - Qinzheng Wang
- Qingdao Women and Children's Hospital, Qingdao University, Qingdao City, Shandong Province, China
| | - Xinmeng Yang
- Qingdao Women and Children's Hospital, Qingdao University, Qingdao City, Shandong Province, China
| | - Bei Lyu
- Qingdao Women and Children's Hospital, Qingdao University, Qingdao City, Shandong Province, China
| | - Hongge Fa
- Qingdao Women and Children's Hospital, Qingdao University, Qingdao City, Shandong Province, China
| | - Qiuling Shi
- State Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, Chongqing, China
| | - Quansheng Xing
- Qingdao Women and Children's Hospital, Qingdao University, Qingdao City, Shandong Province, China.
| |
Collapse
|
6
|
Zheng X, Javed Z, Liu C, Tanvir A, Sandhu O, Liu H, Ji X, Xing C, Lin H, Du D. MAX-DOAS and in-situ measurements of aerosols and trace gases over Dongying, China: Insight into ozone formation sensitivity based on secondary HCHO. J Environ Sci (China) 2024; 135:656-668. [PMID: 37778836 DOI: 10.1016/j.jes.2022.09.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 08/31/2022] [Accepted: 09/12/2022] [Indexed: 10/03/2023]
Abstract
This study presents a comprehensive overview of the atmospheric pollutants including Sulfur dioxide (SO2), Nitrogen dioxide (NO2), Formaldehyde (HCHO), Particulate Matter PM; PM10: diameter ≤ 10 µm, and PM2.5: diameter ≤ 2.5 µm), and Ozone (O3), over Dongying (Shandong Province) from March-April 2018 and September-October 2019 by employing ground-based Multiple Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations along with the in-situ measurements attained by the national air quality monitoring platform. The concentrations of SO2 and NO2 were under the acceptable level, while both PM2.5, and PM10 were higher than the safe levels as prescribed by national and international air quality standards. The results depict that 21% of the total observation days were found to be complex polluted days (PM2.5 > 35 µg/m3 and O3 > 160 µg/m3). The secondary HCHO was used for accurate analysis of O3 sensitivity. A difference of 11.40% and 10% during March-April 2018 and September-October 2019 respectively in O3 sensitivity was found between HCHOtotal/NO2 and HCHOsec/NO2. The results indicate that primary HCHO have significant contribution in HCHO. O3 formation predominantly remained to be in VOC-limited and transitional regime during March-April 2018 and September-October 2019 in Dongying. These results imply that concurrent control of both NOx and VOCs would benefit in ozone reductions. Additionally, the criteria pollutants (PM, SO2, and NO2) depicted strong correlations with each other except for O3 for which weak correlation coefficient was obtained with all the species. This study will prove to be baseline for designing of air pollution control strategies.
Collapse
Affiliation(s)
- Xiaojun Zheng
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Zeeshan Javed
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Cheng Liu
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China; Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei 230026, China.
| | - Aimon Tanvir
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Osama Sandhu
- National Agromet Center, Pakistan Meteorological Department, Islamabad 44000, Pakistan
| | - Haoran Liu
- Institute of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Xiangguang Ji
- Institute of Physical Science and Information Technology, Anhui University, Hefei 230601, China; Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China
| | - Chengzhi Xing
- Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Hua Lin
- School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China
| | - Daolin Du
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013, China.
| |
Collapse
|
7
|
Wang L, Yang X, Dong J, Yang Y, Ma P, Zhao W. Evolution of surface ozone pollution pattern in eastern China and its relationship with different intensity heatwaves. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 338:122725. [PMID: 37827354 DOI: 10.1016/j.envpol.2023.122725] [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: 08/15/2023] [Revised: 09/23/2023] [Accepted: 10/09/2023] [Indexed: 10/14/2023]
Abstract
With climate warming, eastern China has experienced a significant increase in temperature accompanied by intensified ozone pollution. We aimed to investigate the spatiotemporal patterns and relationships between ozone levels and temperature in eastern China using observation-based ozone data from 418 air quality monitoring stations and temperature data from ERA5. The summer maximum temperature and annual ozone concentration in eastern China increased significantly between 2015 and 2022, with increases rate of 10% and 2.84 μg/m3 yr-1, respectively. The baseline ozone concentration was increasing over time. The average difference in MDA8 O3 concentration in spring, summer, and autumn decreased, with more ozone pollution spreading into spring and autumn, indicating a trend of prolonging the ozone season. During the June-July-August (JJA) period of 2015-2022, heatwaves increased significantly in eastern China. The frequency of heatwave events >10 days played a vital role in exacerbating ozone pollution. During the JJA period, the increase rate in MDA8 O3 concentration was 9.31 μg/m3 yr-1 during heatwave periods, significantly higher than that during non-heatwave periods (4.01 μg/m3 yr-1). The correlation between MDA8 O3 concentration and temperature was as high as 0.99, indicating that temperature was vital in ozone formation during the JJA period in eastern China. This study suggests that more stringent actions are needed to control ozone-precursor compounds during frequent summertime heatwaves in eastern China.
Collapse
Affiliation(s)
- Lili Wang
- College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China
| | - Xingchuan Yang
- College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China.
| | - Junwu Dong
- College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China
| | - Yang Yang
- College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China
| | - Pengfei Ma
- Ministry of Ecology and Environment Center for Satellite Application on Ecology and Environment/ State Environmental Protection Key Laboratory of Satellite Remote Sensing, Beijing, 100094, China
| | - Wenji Zhao
- College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China
| |
Collapse
|
8
|
Chang JH, Lee YL, Chang LT, Chang TY, Hsiao TC, Chung KF, Ho KF, Kuo HP, Lee KY, Chuang KJ, Chuang HC. Climate change, air quality, and respiratory health: a focus on particle deposition in the lungs. Ann Med 2023; 55:2264881. [PMID: 37801626 PMCID: PMC10561567 DOI: 10.1080/07853890.2023.2264881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 09/19/2023] [Indexed: 10/08/2023] Open
Abstract
This review article delves into the multifaceted relationship between climate change, air quality, and respiratory health, placing a special focus on the process of particle deposition in the lungs. We discuss the capability of climate change to intensify air pollution and alter particulate matter physicochemical properties such as size, dispersion, and chemical composition. These alterations play a significant role in influencing the deposition of particles in the lungs, leading to consequential respiratory health effects. The review paper provides a broad exploration of climate change's direct and indirect role in modifying particulate air pollution features and its interaction with other air pollutants, which may change the ability of particle deposition in the lungs. In conclusion, climate change may play an important role in regulating particle deposition in the lungs by changing physicochemistry of particulate air pollution, therefore, increasing the risk of respiratory disease development.
Collapse
Affiliation(s)
- Jer-Hwa Chang
- School of Respiratory Therapy, College of Medicine, Taipei Medical University, Taipei, Taiwan
- Division of Pulmonary Medicine, Department of Internal Medicine, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
| | - Yueh-Lun Lee
- Department of Microbiology and Immunology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Li-Te Chang
- Department of Environmental Engineering and Science, Feng Chia University, Taichung, Taiwan
| | - Ta-Yuan Chang
- Department of Occupational Safety and Health, College of Public Health, China Medical University, Taichung, Taiwan
| | - Ta-Chih Hsiao
- Graduate Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan
| | - Kian Fan Chung
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Kin Fai Ho
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Han-Pin Kuo
- Division of Pulmonary Medicine, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Kang-Yun Lee
- Division of Pulmonary Medicine, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
- Division of Pulmonary Medicine, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
| | - Kai-Jen Chuang
- School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan
- Department of Public Health, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Hsiao-Chi Chuang
- School of Respiratory Therapy, College of Medicine, Taipei Medical University, Taipei, Taiwan
- National Heart and Lung Institute, Imperial College London, London, UK
- Division of Pulmonary Medicine, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
- Cell Physiology and Molecular Image Research Center, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
| |
Collapse
|
9
|
Liu X, Yi G, Zhou X, Zhang T, Bie X, Li J, Tan H. Spatio-temporal variations of PM 2.5 and O 3 in China during 2013-2021: Impact factor analysis. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 334:122189. [PMID: 37451585 DOI: 10.1016/j.envpol.2023.122189] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 06/13/2023] [Accepted: 07/11/2023] [Indexed: 07/18/2023]
Abstract
Fine particulate matter (PM2.5) and ozone (O3) pollution are regarded as significant secondary air pollutants. The PM2.5 in most regions in China declined, and the decreasing rate in January was lower than the annual average. However, O3 concentration showed a steady increasing trend in most regions, and the increasing rate in July was slightly higher than the annual average. In particular, the annual average PM2.5 concentration and excess rate showed an increasing trend on the northern slope of the Tianshan Mountains. Conversely, O3 concentrations had shown a consistent increasing trend, exceeding the annual average limit of 100 μg/m3. Surface pressure exhibited positive correlations with PM2.5 in winter and O3 in summer across urban agglomerations. Moreover, soil temperature at different depths explained over 30% of the variations in PM2.5 and O3 in the Chengdu-Chongqing, Beijing-Tianjin-Hebei, and Lanzhou-Xining urban agglomerations. In winter, relative humidity demonstrated a positive correlation with urban agglomerations in northeast and northwest China, regions characterized by dry climates. During the COVID-19 period, the impacts of meteorological factors and soil temperature on PM2.5 and O3 differed significantly compared to preceding and subsequent periods. Notably, during the winter of 2020, the Harbin-Changchuan urban agglomeration exhibited a notable transition, as O3 and PM2.5 concentrations shifted from a strong negative correlation to a robust positive correlation. This remarkable shift, with deviations explained up to 60%, represents a unique phenomenon worth emphasizing in the study's findings.
Collapse
Affiliation(s)
- Xian Liu
- College of Earth Science, Chengdu University of Technology, Chengdu, 610059, China
| | - Guihua Yi
- College of Tourism and Urban-Rural Planning, Chengdu University of Technology, Chengdu, 610059, China.
| | - Xiaobing Zhou
- Geological Engineering Department, Montana Technological University, Butte, MT, 59701, USA
| | - Tingbin Zhang
- College of Earth Science, Chengdu University of Technology, Chengdu, 610059, China; State Environmental Protection Key Laboratory of Synergetic Control and Joint Remediation for Soil & Water Pollution, Chengdu University of Technology, Chengdu, 610059, China
| | - Xiaojuan Bie
- College of Tourism and Urban-Rural Planning, Chengdu University of Technology, Chengdu, 610059, China
| | - Jingji Li
- State Environmental Protection Key Laboratory of Synergetic Control and Joint Remediation for Soil & Water Pollution, Chengdu University of Technology, Chengdu, 610059, China; College of Ecological Environment, Chengdu University of Technology, Chengdu, 610059, China
| | - Huizhi Tan
- College of Earth Science, Chengdu University of Technology, Chengdu, 610059, China
| |
Collapse
|
10
|
Jeong JI, Park RJ. Can climate indices forecast daily variations of wintertime PM 2.5 concentrations in East Asia? THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 881:163505. [PMID: 37062311 DOI: 10.1016/j.scitotenv.2023.163505] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 04/04/2023] [Accepted: 04/10/2023] [Indexed: 06/01/2023]
Abstract
Synoptic meteorological variability plays an important role in determining air quality. In East Asia, the expansion and contraction of the Siberian high-pressure system is an essential mechanism for determining surface particulate matter concentrations (PM2.5) during the winter season. Here, we selected four climate indices that reflected the variability of the Siberian high-pressure system and analyzed their correlation with the daily variability of the observed winter PM2.5 concentrations in China and South Korea over the past six years (2014/15-2019/20). Siberian High Intensity (SHI) and East Asian Winter Monsoon (EAWM) indices were good indicators of daily PM2.5 concentration changes. Two to four days after the daily SHI and EAWM indices exceed the threshold (±1), the daily PM2.5 concentrations in East Asia significantly increased or decreased, up to 40 % compared to the mean winter PM2.5 concentrations. The climate indices associated with the Siberian high-pressure system thus potentially effectively forecast the daily PM2.5 concentrations in East Asia within a period of one week.
Collapse
Affiliation(s)
- Jaein I Jeong
- School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea
| | - Rokjin J Park
- School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea.
| |
Collapse
|
11
|
Zhang Y, Shi M, Chen J, Fu S, Wang H. Spatiotemporal variations of NO 2 and its driving factors in the coastal ports of China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 871:162041. [PMID: 36754320 DOI: 10.1016/j.scitotenv.2023.162041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 02/01/2023] [Accepted: 02/01/2023] [Indexed: 06/18/2023]
Abstract
Nitrogen Dioxide (NO2) is one of the major air pollutants in coastal ports of China. Understanding the spatiotemporal varying effects of driving factors of NO2 is vital for the implementation of differentiated air pollution control measures for different port areas. Based on the Ozone Monitoring Instrument (OMI) satellite data, we adopted a Geographically and Temporally Weighted Regression (GTWR) model to explore the influences of meteorological and socioeconomic factors on the NO2 Vertical Column Concentrations (VCDs) in coastal ports of China from 2015 to 2021. The results indicate that NO2 VCD in most ports has decreased since 2016 and the ports with serious NO2 pollution are mainly distributed in northern China. The associations between NO2 VCD levels and their drivers exhibit obvious spatiotemporal heterogeneity. Higher wind speed and relative humidity are more helpful to alleviate NO2 pollution in ports of the Bohai Rim and the Pearl River Delta. Cargo throughput has more closely associated with NO2 pollution in Beibu Gulf in recent years, yet there is no significant association found for Shanghai ports. The positive relationship between transportation emissions and NO2 VCD is more significant in southern ports. This work provides some implications for the formulation of targeted emission reduction policies for different ports along the Chinese coast.
Collapse
Affiliation(s)
- Yang Zhang
- College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China
| | - Meiyu Shi
- College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China
| | - Jihong Chen
- College of Management, Shenzhen University, Shenzhen 518073, China; Shenzhen International Maritime Institute, Shenzhen 518081, China; Business School, Xi'an International University, Xi'an 710077, China.
| | - Shanshan Fu
- College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China
| | - Huizhen Wang
- Business School, Xi'an International University, Xi'an 710077, China
| |
Collapse
|
12
|
Chen Y, Wang D, ElAmraoui A, Guo H, Ke X. The effectiveness of traffic and production restrictions on urban air quality: A rare opportunity for investigation. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2023; 73:225-239. [PMID: 35993663 DOI: 10.1080/10962247.2022.2115161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 07/13/2022] [Accepted: 08/11/2022] [Indexed: 06/15/2023]
Abstract
Traffic and production restrictions are two important emergency measures for controlling urban air pollution. The lockdown policies implemented during the COVID-19 pandemic period are nearly equivalent to the policies of traffic and production restriction, which provides a rare opportunity to quantitatively evaluate the effectiveness of these emergency measures. Taking Wuhan, China as the study area, this paper firstly verified the changes in six air pollutants and analyzed their change rules in different lockdown periods using statistical methods. Then the structural breakpoints in air pollutants were detected via regression discontinuity design model. To comprehensively understand the effects of restrictions on air pollution, the influences of meteorological conditions on air pollution were also investigated. The results illustrated that the concentrations of PM2.5, PM10 and NO2 decreased significantly during lockdown period. By comparing with the RDD coefficients of PM2.5 (-34.46), PM10 (-37.11) and NO2 (-19.15), the lockdown had little effect on CO (-0.32). The traffic and production restrictions had no apparent effects on SO2. Although O3 showed an increasing trend, the increase was not limited to the lockdown period, meaning that the traffic and production restrictions had less effect on the increasing trend of O3 concentration. Moreover, the structural breakpoints were verified in four air pollutants (PM2.5, PM10, NO2, and CO), and the structural breakpoints were caused by lockdown instead of the Spring Festival. The results also indicated that the meteorological conditions were not the main reasons for the changes in air pollutants during the lockdown period. This paper reveals how the traffic and production restrictions affect urban air pollution and provides a strong implementation basis for the air pollution control policy.Implications: The traffic and production restrictions are two important emergency measures for controlling heavy urban air pollution. However, these two measures have never been implemented in a large area like a city for a long enough period, so the effectiveness of these two measures has never been estimated quantitatively at a city level. The lockdown policies implemented during the COVID-19 pandemic are nearly equivalent to the policies of traffic and production restriction, which provides a rare opportunity to quantitatively evaluate the effectiveness of these emergency measures. Thus, this study measured the effectiveness of production and traffic restrictions on different air pollutants. This study provides the following implications: (1) the dominant factors for air pollution changes during the lockdown are traffic and production restriction instead of meteorological conditions; (2) the production and traffic restriction policies are effective for reducing concentrations of PM2.5, PM10 and NO2, while having less effect on O3 and CO concentrations; (3) the sharp changes in air pollutants in 2020 are unlikely to be caused by the Spring Festival. These findings are crucial for making more comprehensive policies for protecting urban air quality.
Collapse
Affiliation(s)
- Yiqing Chen
- School of Economics and Management, China University of Geosciences, Wuhan, People's Republic of China
| | - Deyun Wang
- School of Economics and Management, China University of Geosciences, Wuhan, People's Republic of China
| | - Adnen ElAmraoui
- Univ. Artois, Laboratoire de Génie Informatique et d'Automatique de l'Artois (LGI2A), Béthune, France
| | - Haixiang Guo
- School of Economics and Management, China University of Geosciences, Wuhan, People's Republic of China
| | - Xiaoling Ke
- School of Economics and Management, China University of Geosciences, Wuhan, People's Republic of China
| |
Collapse
|
13
|
Wang Y, Ge Q. The positive impact of the Omicron pandemic lockdown on air quality and human health in cities around Shanghai. ENVIRONMENT, DEVELOPMENT AND SUSTAINABILITY 2023:1-26. [PMID: 37362999 PMCID: PMC9975847 DOI: 10.1007/s10668-023-03071-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 02/21/2023] [Indexed: 06/28/2023]
Abstract
The Omicron pandemic broke out in Shanghai in March 2022, and some infected people spread to some cities in the Yangtze River Delta (YRD) region. To achieve the dynamic zero-COVID target as soon as possible, Shanghai and nine cities that were heavily affected by Shanghai implemented the lockdown measures. This paper aims to quantify the impact of the lockdown on air quality and human health. A difference-in-difference (DID) model was first used to measure the impact of the lockdown on air quality in these ten cities. Based on the results of the DID model, we estimated the PM2.5-related health and economic benefits using the concentration-response function and the value of statistical life method. Results showed that the lockdown has reduced the concentrations of PM2.5, PM10, SO2, NO2, and CO by 9.87 μg/m3, 17.31 μg/m3, 0.75 μg/m3, 9.03 μg/m3, and 0.07 mg/m3, respectively. The number of avoided premature deaths due to PM2.5 reduction was estimated to be 35,342. The resulting economic benefits totaled 18.86 billion US dollars. We investigated the reasons for the air quality improvement in these ten cities and found the "3 + 11" policy has had a great impact on air quality. Compared with the first COVID-19 lockdown in early 2020, the effect of the lockdown in 2022 was smaller. These findings demonstrated that reductions in anthropogenic emissions would achieve substantial air quality improvement and health benefits. This paper re-emphasized continuous efforts to improve air quality are essential to protect public health.
Collapse
Affiliation(s)
- Yu Wang
- Business School, University of Shanghai for Science and Technology, 334 Jungong Rd, Shanghai, 200093 People’s Republic of China
| | - Qingqing Ge
- College of Business, Yancheng Teachers University, 2 South Hope Avenue, Yancheng, 224051 People’s Republic of China
| |
Collapse
|
14
|
Hwang Y, Kim YM, Lee JE, Rhee GH, Show PL, Andrew Lin KY, Park YK. Catalytic removal of 2-butanone with ozone over porous spent fluid catalytic cracking catalyst. ENVIRONMENTAL RESEARCH 2023; 219:115071. [PMID: 36528046 DOI: 10.1016/j.envres.2022.115071] [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: 09/24/2022] [Revised: 11/29/2022] [Accepted: 12/13/2022] [Indexed: 06/17/2023]
Abstract
To remove harmful volatile organic compounds (VOCs) including 2-butanone (methyl ethyl ketone, MEK) emitted from various industrial plants is very important for the clean air. Also, it is worthwhile to recycle porous spent fluid catalytic cracking (SFCC) catalysts from various petroleum refineries in terms of reducing industrial waste and the reuse of discharged resources. Therefore, Mn and Mn-Cu added SFCC (Mn/SFCC and Mn-Cu/SFCC) catalysts were prepared to compare their catalytic efficiencies together with the SFCC catalyst in the ozonation of 2-butanone. Since the SFCC-based catalysts have a structure similar to that of zeolite Y (Y), the Mn-loaded zeolite Y catalyst (Mn/Y) was also prepared to compare its activity for the removal of 2-butanone and ozone to that of the SFCC-based ones at room temperature. Among the five catalysts of this study (Y, Mn/Y, SFCC, Mn/SFCC, and Mn-Cu/SFCC), the Mn-Cu/SFCC and Mn/SFCC catalysts showed the better catalytic decomposition activity than the others. The increased distributions of the Mn3+ species and the Ovacancy sites in Mn/SFCC and Mn-Cu/SFCC catalysts which could supply more available active sites for the 2-butanone and ozone removal would enhance the catalytic activity of them.
Collapse
Affiliation(s)
- Yujin Hwang
- School of Environmental Engineering, University of Seoul 02504, Republic of Korea
| | - Young-Min Kim
- Department of Environmental Engineering, Daegu University, Gyeongsan 38453, Republic of Korea
| | - Jung Eun Lee
- Department of Environmental Engineering, Kwangwoon University 01897, Republic of Korea
| | - Gwang Hoon Rhee
- Department of Mechanical and Information Engineering, University of Seoul, Seoul 02504, Republic of Korea
| | - Pau-Loke Show
- Zhejiang Provincial Key Laboratory for Subtropical Water Environment and Marine Biological Resources Protection, Wenzhou University, Wenzhou, 325035, China; Department of Sustainable Engineering, Saveetha School of Engineering, SIMATS, Chennai, 602105, India; Department of Chemical and Environmental Engineering, Faculty of Science and Engineering, University of Nottingham Malaysia, Jalan Broga, 43500, Semenyih, Selangor Darul Ehsan, Malaysia
| | - Kun-Yi Andrew Lin
- Department of Environmental Engineering & Innovation and Development Center of Sustainable Agriculture, National Chung Hsing University, Taichung, 402, Taiwan
| | - Young-Kwon Park
- School of Environmental Engineering, University of Seoul 02504, Republic of Korea.
| |
Collapse
|
15
|
Wang NN, Zhu CY, Li W, Qiu MY, Wang BL, Li XY, Jiang BD, Qu XY, Li ZS, Cheng HC. Air quality improvement assessment and exposure risk of Shandong Province in China during 2014 to 2020. INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY : IJEST 2022; 20:1-10. [PMID: 36567804 PMCID: PMC9761030 DOI: 10.1007/s13762-022-04651-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 05/11/2022] [Accepted: 11/07/2022] [Indexed: 06/17/2023]
Abstract
As one of the most polluted provinces in China, air pollution events occur frequently in Shandong. Based on the hourly (or daily) concentrations of six air pollutants (PM2.5, PM10, O3, NO2, SO2 and CO), the situations of air quality improvement in three kinds of cities (key cities, coastal cities and general cities) are assessed comprehensively during 2014-2020. Contrary to the daily maximum 8-h average ozone (MDA8 O3), the annual average concentrations of other pollutants show the downward trends during 2014-2020. Therein, the improvement rates of annual average concentrations of air pollutants in key cities are highest. By 2020, the day proportions of O3 as the primary pollutant are up to 38% in three kinds of cities. Besides, due to the impact of COVID-19, the monthly average concentrations of PM2.5, PM10, NO2, SO2 and CO in February 2020 decrease by 32.1-49.5% year-on-year. There are still about 50% of population exposed to high-risk regions (R i > 2), which are mainly concentrated in main urban areas and industrial areas. Thus, the adjustment of industrial structure and energy composition in the context of carbon peak and carbon neutrality should be implemented in the future. Supplementary Information The online version contains supplementary material available at 10.1007/s13762-022-04651-5.
Collapse
Affiliation(s)
- N. N. Wang
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353 People’s Republic of China
| | - C. Y. Zhu
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353 People’s Republic of China
| | - Wei Li
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353 People’s Republic of China
| | - M. Y. Qiu
- State Grid of China Technology College, State Grid, Jinan, 250002 People’s Republic of China
| | - B. L. Wang
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353 People’s Republic of China
| | - X. Y. Li
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353 People’s Republic of China
| | - B. D. Jiang
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353 People’s Republic of China
| | - X. Y. Qu
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353 People’s Republic of China
| | - Z. S. Li
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353 People’s Republic of China
| | - H. C. Cheng
- Weifang Municipal Ecology and Environment Bureau Shouguang Branch, Weifang, 262700 People’s Republic of China
| |
Collapse
|
16
|
Yin H, Sun Y, You Y, Notholt J, Palm M, Wang W, Shan C, Liu C. Using machine learning approach to reproduce the measured feature and understand the model-to-measurement discrepancy of atmospheric formaldehyde. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 851:158271. [PMID: 36028030 DOI: 10.1016/j.scitotenv.2022.158271] [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: 06/21/2022] [Revised: 08/10/2022] [Accepted: 08/21/2022] [Indexed: 06/15/2023]
Abstract
The solar absorption spectrometry in the infrared spectral region, using high-resolution Fourier transform infrared (FTIR) spectrometer, has been established as a powerful tool in atmospheric science. These observations cannot be performed continuously, for example, clouds prevent observations. On the other hand, chemical transport models give continuously data. Their results depend on the knowledge of emission inventories, the chemistry involved, and the meteorological fields, yielding to potential biases between measurements and simulations. In our study we concentrated on Formaldehyde (HCHO) and used machine learning approach to fill the gap between the observations, performed on an irregular time scale and having their measurement lacks, and model data, giving continuous data, but having potential variable biases. The proposed machine learning approach is based on the Light Gradient Boosting Machine (LightGBM) algorithm and created by using GEOS-Chem simulations, meteorological fields, emission inventory, and is referred to as the GEOS-Chem-LightGBM model. The results of established GEOS-Chem-LightGBM model have generated consistent HCHO predictions with the ground-based FTIR and satellite (OMI and TROPOMI) observations. In order to understand the GEOS-Chem model to measurement discrepancy, we have investigated the contribution of each input variable to GEOS-Chem-LightGBM model HCHO predictions through the SHapely Additive exPlanations (SHAP) approach. We found that the GEOS-Chem model underestimates the sensitivities of HCHO total column to most photochemical variables, contributing to lower amplitudes of diurnal cycle and seasonal cycle by the GEOS-Chem model. By correcting the model-to-measurement discrepancy, the sensitivities of HCHO total column to all variables by the GEOS-Chem-LightGBM became to be in good agreement with the FTIR observations. As a result, GEOS-Chem-LightGBM model has significantly improved the performance of HCHO predictions compared to the GEOS-Chem alone. The proposed GEOS-Chem-LightGBM model can be extendible to other atmospheric constituents obtained by various measurement techniques and platforms, and is expected to have wide applications.
Collapse
Affiliation(s)
- Hao Yin
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China; Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
| | - Youwen Sun
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China; Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
| | - Yan You
- National Observation and Research Station of Coastal Ecological Environments in Macao, Macao Environmental Research Institute, Macau University of Science and Technology, 999078, Macau.
| | - Justus Notholt
- University of Bremen, Institute of Environmental Physics, P. O. Box 330440, 28334 Bremen, Germany
| | - Mathias Palm
- University of Bremen, Institute of Environmental Physics, P. O. Box 330440, 28334 Bremen, Germany
| | - Wei Wang
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Changgong Shan
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Cheng Liu
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China; Anhui Province Key Laboratory of Polar Environment and Global Change, University of Science and Technology of China, Hefei 230026, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei 230026, China
| |
Collapse
|
17
|
Zhang Z, Jiang J, Lu B, Meng X, Herrmann H, Chen J, Li X. Attributing Increases in Ozone to Accelerated Oxidation of Volatile Organic Compounds at Reduced Nitrogen Oxides Concentrations. PNAS NEXUS 2022; 1:pgac266. [PMID: 36712335 PMCID: PMC9802302 DOI: 10.1093/pnasnexus/pgac266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 08/26/2022] [Accepted: 11/15/2022] [Indexed: 11/19/2022]
Abstract
Surface ozone (O3) is an important secondary pollutant affecting climate change and air quality in the atmosphere. Observations during the COVID-19 lockdown in urban China show that the co-abatement of nitrogen oxides (NOx) and volatile organic compounds (VOCs) caused winter ground-level O3 increases, but the chemical mechanisms involved are unclear. Here we report field observations in the Shanghai lockdown that reveals increasing photochemical formation of O3 from VOC oxidation with decreasing NOx. Analyses of the VOC profiles and NO/NO2 indicate that the O3 increases by the NOx reduction counteracted the O3 decreases through the VOC emission reduction in the VOC-limited region, and this may have been the main mechanism for this net O3 increase. The mechanism may have involved accelerated OH-HO2-RO2 radical cycling. The NOx reductions for increasing O3 production could explain why O3 increased from 2014 to 2020 in response to NOx emission reduction even as VOC emissions have essentially remained unchanged. Model simulations suggest that aggressive VOC abatement, particularly for alkenes and aromatics, should help reverse the long-term O3 increase under current NOx abatement conditions.
Collapse
Affiliation(s)
- Zekun Zhang
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200032, China
| | - Jiakui Jiang
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200032, China
| | - Bingqing Lu
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200032, China
| | - Xue Meng
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200032, China
| | - Hartmut Herrmann
- Leibniz-Institut für Troposphärenforschung (IfT), Permoserstr. 15, 04318 Leipzig, Germany
| | - Jianmin Chen
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200032, China
| | - Xiang Li
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200032, China
- Institute of Eco-Chongming (IEC), Shanghai, China
| |
Collapse
|
18
|
Tong L, Liu Y, Meng Y, Dai X, Huang L, Luo W, Yang M, Pan Y, Zheng J, Xiao H. Surface ozone changes during the COVID-19 outbreak in China: An insight into the pollution characteristics and formation regimes of ozone in the cold season. JOURNAL OF ATMOSPHERIC CHEMISTRY 2022; 80:103-120. [PMID: 36248311 PMCID: PMC9540070 DOI: 10.1007/s10874-022-09443-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Accepted: 09/20/2022] [Indexed: 06/16/2023]
Abstract
The countrywide lockdown in China during the COVID-19 pandemic provided a natural experiment to study the characteristics of surface ozone (O3). Based on statistical analysis of air quality across China before and during the lockdown, the tempo-spatial variations and site-specific formation regimes of wintertime O3 were analyzed. The results showed that the O3 pollution with concentrations higher than air quality standards could occur widely in winter, which had been aggravated by the emission reduction during the lockdown. On the national scale of China, with the significant decrease (54.03%) in NO2 level from pre-lockdown to COVID-19 lockdown, the maximum daily 8-h average concentration of O3 (MDA8h O3) increased by 39.43% from 49.05 to 64.22 μg/m3. This increase was comprehensively contributed by attenuated NOx suppression and favorable meteorological changes on O3 formation during the lockdown. As to the pollution states of different monitoring stations, surface O3 responded oppositely to the consistent decreased NO2 across China. The O3 levels were found to increase in the northern and central regions, but decrease in the southern region, where the changes in both meteorology (e.g. temperature drops) and precursors (reduced emissions) during the lockdown had diminished local O3 production. The spatial differences in NOx levels generally dictate the site-specific O3 formation regimes in winter, with NOx-titration/VOCs-sensitive regimes being dominant in northern and central China, while VOCs-sensitive/transition regimes being dominant in southern China. These findings highlight the influence of NOx saturation levels on winter O3 formation and the necessity of VOCs emission reductions on O3 pollution controls.
Collapse
Affiliation(s)
- Lei Tong
- Center for Excellence in Regional Atmospheric Environment & Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021 China
- Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, Ningbo (Beilun) Zhongke Haixi Industrial Technology Innovation Center, Ningbo, 315800 China
| | - Yu Liu
- Center for Excellence in Regional Atmospheric Environment & Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021 China
- Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, Ningbo (Beilun) Zhongke Haixi Industrial Technology Innovation Center, Ningbo, 315800 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Yang Meng
- Center for Excellence in Regional Atmospheric Environment & Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021 China
- Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, Ningbo (Beilun) Zhongke Haixi Industrial Technology Innovation Center, Ningbo, 315800 China
| | - Xiaorong Dai
- Center for Excellence in Regional Atmospheric Environment & Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021 China
- College of Biological and Environmental Sciences, Zhejiang Wanli University, Ningbo, 315100 China
| | - Leijun Huang
- College of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou, 311300 China
| | - Wenxian Luo
- College of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou, 311300 China
| | - Mengrong Yang
- Center for Excellence in Regional Atmospheric Environment & Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021 China
- Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, Ningbo (Beilun) Zhongke Haixi Industrial Technology Innovation Center, Ningbo, 315800 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Yong Pan
- Center for Excellence in Regional Atmospheric Environment & Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021 China
- Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, Ningbo (Beilun) Zhongke Haixi Industrial Technology Innovation Center, Ningbo, 315800 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Jie Zheng
- Center for Excellence in Regional Atmospheric Environment & Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021 China
- Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, Ningbo (Beilun) Zhongke Haixi Industrial Technology Innovation Center, Ningbo, 315800 China
| | - Hang Xiao
- Center for Excellence in Regional Atmospheric Environment & Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021 China
- Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, Ningbo (Beilun) Zhongke Haixi Industrial Technology Innovation Center, Ningbo, 315800 China
| |
Collapse
|
19
|
Ziemke JR, Kramarova NA, Frith SM, Huang L, Haffner DP, Wargan K, Lamsal LN, Labow GJ, McPeters RD, Bhartia PK. NASA Satellite Measurements Show Global-Scale Reductions in Free Tropospheric Ozone in 2020 and Again in 2021 During COVID-19. GEOPHYSICAL RESEARCH LETTERS 2022; 49:e2022GL098712. [PMID: 36247521 PMCID: PMC9538536 DOI: 10.1029/2022gl098712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 07/01/2022] [Accepted: 07/24/2022] [Indexed: 06/16/2023]
Abstract
NASA satellite measurements show that ozone reductions throughout the Northern Hemisphere (NH) free troposphere reported for spring-summer 2020 during the COronaVIrus Disease 2019 pandemic have occurred again in spring-summer 2021. The satellite measurements show that tropospheric column ozone (TCO) (mostly representative of the free troposphere) for 20°N-60°N during spring-summer for both 2020 and 2021 averaged ∼3 Dobson Units (DU) (or ∼7%-8%) below normal. These ozone reductions in 2020 and 2021 were the lowest in the 2005-2021 record. We also include satellite measurements of tropospheric NO2 that exhibit reductions of ∼10%-20% in the NH in early spring-to-summer 2020 and 2021, suggesting that reduced pollution was the main cause for the low anomalies in NH TCO in 2020 and 2021. Reductions of TCO ∼2 DU (7%) are also measured in the Southern Hemisphere in austral summer but are not associated with reduced NO2.
Collapse
Affiliation(s)
- Jerry R. Ziemke
- NASA Goddard Space Flight CenterGreenbeltMDUSA
- Goddard Earth Sciences Technology and Research (GESTAR)/Morgan State UniversityBaltimoreMDUSA
| | | | - Stacey M. Frith
- NASA Goddard Space Flight CenterGreenbeltMDUSA
- Science Systems and Applications Inc. (SSAI)LanhamMDUSA
| | - Liang‐Kang Huang
- NASA Goddard Space Flight CenterGreenbeltMDUSA
- Science Systems and Applications Inc. (SSAI)LanhamMDUSA
| | - David P. Haffner
- NASA Goddard Space Flight CenterGreenbeltMDUSA
- Science Systems and Applications Inc. (SSAI)LanhamMDUSA
| | - Krzysztof Wargan
- NASA Goddard Space Flight CenterGreenbeltMDUSA
- Science Systems and Applications Inc. (SSAI)LanhamMDUSA
| | - Lok N. Lamsal
- NASA Goddard Space Flight CenterGreenbeltMDUSA
- University of Maryland Baltimore CountyBaltimoreMDUSA
| | - Gordon J. Labow
- NASA Goddard Space Flight CenterGreenbeltMDUSA
- Science Systems and Applications Inc. (SSAI)LanhamMDUSA
| | | | - Pawan K. Bhartia
- NASA Goddard Space Flight CenterGreenbeltMDUSA
- Emeritus, NASA Goddard Space Flight CenterGreenbeltMDUSA
| |
Collapse
|
20
|
Ye F, Rupakheti D, Huang L, T N, Kumar Mk S, Li L, Kt V, Hu J. Integrated process analysis retrieval of changes in ground-level ozone and fine particulate matter during the COVID-19 outbreak in the coastal city of Kannur, India. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 307:119468. [PMID: 35588959 PMCID: PMC9109815 DOI: 10.1016/j.envpol.2022.119468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 04/25/2022] [Accepted: 05/09/2022] [Indexed: 06/15/2023]
Abstract
The Community Multi-Scale Air Quality (CMAQ) model was applied to evaluate the air quality in the coastal city of Kannur, India, during the 2020 COVID-19 lockdown. From the Pre1 (March 1-24, 2020) period to the Lock (March 25-April 19, 2020) and Tri (April 20-May 9, 2020) periods, the Kerala state government gradually imposed a strict lockdown policy. Both the simulations and observations showed a decline in the PM2.5 concentrations and an enhancement in the O3 concentrations during the Lock and Tri periods compared with that in the Pre1 period. Integrated process rate (IPR) analysis was employed to isolate the contributions of the individual atmospheric processes. The results revealed that the vertical transport from the upper layers dominated the surface O3 formation, comprising 89.4%, 83.1%, and 88.9% of the O3 sources during the Pre1, Lock, and Tri periods, respectively. Photochemistry contributed negatively to the O3 concentrations at the surface layer. Compared with the Pre1 period, the O3 enhancement during the Lock period was primarily attributable to the lower negative contribution of photochemistry and the lower O3 removal rate by horizontal transport. During the Tri period, a slower consumption of O3 by gas-phase chemistry and a stronger vertical import from the upper layers to the surface accounted for the increase in O3. Emission and aerosol processes constituted the major positive contributions to the net surface PM2.5, accounting for a total of 48.7%, 38.4%, and 42.5% of PM2.5 sources during the Pre1, Lock, and Tri periods, respectively. The decreases in the PM2.5 concentrations during the Lock and Tri periods were primarily explained by the weaker PM2.5 production from emission and aerosol processes. The increased vertical transport rate of PM2.5 from the surface layer to the upper layers was also a reason for the decrease in the PM2.5 during the Lock periods.
Collapse
Affiliation(s)
- Fei Ye
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Dipesh Rupakheti
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Lin Huang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Nishanth T
- Department of Physics, Sree Krishna College Guruvayur, Kerala, 680102, India
| | - Satheesh Kumar Mk
- Department of Atomic and Molecular Physics, Manipal Academy of Higher Education, Karnataka, 576104, India
| | - Lin Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Valsaraj Kt
- Cain Department of Chemical Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA
| | - Jianlin Hu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
| |
Collapse
|
21
|
Li M, Yang Q, Yuan Q, Zhu L. Estimation of high spatial resolution ground-level ozone concentrations based on Landsat 8 TIR bands with deep forest model. CHEMOSPHERE 2022; 301:134817. [PMID: 35523298 DOI: 10.1016/j.chemosphere.2022.134817] [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: 12/26/2021] [Revised: 04/04/2022] [Accepted: 04/29/2022] [Indexed: 06/14/2023]
Abstract
In recent years, China has been facing severe ozone (O3) pollution, which poses a remarkable threat to human health. Most estimation methods only provide ozone products at a relatively coarse resolution, such as 5 km, but high-resolution ozone data are essential for ozone pollution prevention and control. To this end, we proposed a new framework for estimating ozone concentrations at 300 m resolution in China based on Landsat 8 infrared (IR) bands and meteorological data using a deep forest (DF) model. DF combines the excellent performance of tree integration with the expressive power of hierarchical distributed representations of neural networks. The accuracy and mapping results of DF are considerably better than some widely used machine learning methods (generalized regression neural regression network and random forest). The sample-based cross-validation (CV), station-based CV, time-based CV, and extrapolation validation show that the estimations of DF are in high agreement with the station observations with determination coefficient values of 0.938, 0.926, 0.687, and 0.660, respectively. The proposed method was used to analyze the spatial and temporal ozone variations at fine scales in three typical Chinese cities (Beijing, Wuhan and Guangzhou), where the mean ozone concentrations during the polluted season are consistent with the land use and urban heat island distribution. The rationality of ozone estimates was verified, and the advantages of high-resolution mapping was demonstrated by comparing the monitoring data from municipal controlling stations in Beijing, 10 km ozone products, and satellite images. Our product can represent spatial details and locate local pollution sources, such as temples. The proposed method has important implications for the fine-scale monitoring of ozone pollution.
Collapse
Affiliation(s)
- Muyu Li
- School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, 430079, China.
| | - Qianqian Yang
- School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, 430079, China.
| | - Qiangqiang Yuan
- School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, 430079, China; The Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University, Wuhan, Hubei, 430079, China.
| | - Liye Zhu
- School of Atmospheric Sciences and Key Laboratory of Tropical Atmosphere-Ocean System, Sun Yat-sen University, Ministry of Education and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong, 519082, China.
| |
Collapse
|
22
|
Liu M, Wei D, Chen H. Consistency of the relationship between air pollution and the urban form: Evidence from the COVID-19 natural experiment. SUSTAINABLE CITIES AND SOCIETY 2022; 83:103972. [PMID: 35719128 PMCID: PMC9194566 DOI: 10.1016/j.scs.2022.103972] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 05/29/2022] [Accepted: 05/29/2022] [Indexed: 05/16/2023]
Abstract
The lockdown measures enacted to control the COVID-19 pandemic in Wuhan, China, resulted in a suspension of nearly all non-essential human activities on January 23, 2020. Nevertheless, the lockdown provided a natural experiment to understand the consistency of the relationship between the urban form and air pollution with different compositions of locally or regionally transported sources. This study investigated the variations in six air pollutants (PM2.5, PM10, NO2, CO, O3, and SO2) in Wuhan before and during the lockdown and in the two same time spans in 2021. Moreover, a hierarchical agglomerative cluster analysis was conducted to differentiate the relative levels of pollutants and to detect the relationships between the air pollutants and the urban form during these four periods. Several features depicting the urban physical structures delivered consistent impacts. A lower building density and plot ratio, and a higher porosity always mitigated the concentrations of NO2 and PM2.5. However, they had inverse effects on O3 during the non-lockdown periods. PM10, CO, and SO2 concentrations have little correlation with the urban form. This study improves the comprehensive understanding of the effect of the urban form on ambient air pollution and suggests practical strategies for mitigating air pollution in Wuhan.
Collapse
Affiliation(s)
- Mengyang Liu
- School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan, Hubei 430000, China
| | - Di Wei
- School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan, Hubei 430000, China
| | - Hong Chen
- School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan, Hubei 430000, China
| |
Collapse
|
23
|
Hong Q, Zhu L, Xing C, Hu Q, Lin H, Zhang C, Zhao C, Liu T, Su W, Liu C. Inferring vertical variability and diurnal evolution of O 3 formation sensitivity based on the vertical distribution of summertime HCHO and NO 2 in Guangzhou, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 827:154045. [PMID: 35217050 DOI: 10.1016/j.scitotenv.2022.154045] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Revised: 02/16/2022] [Accepted: 02/17/2022] [Indexed: 06/14/2023]
Abstract
The vertical distributions of formaldehyde (HCHO) and nitrogen dioxide (NO2) and their indicative roles in ozone (O3) sensitivity are important for designing O3 mitigation strategies. Using hyperspectral remote sensing observations, tropospheric vertical profiles of HCHO, NO2, and aerosol extinction were investigated in Guangzhou, China from July to September 2019. On both O3 non-exceedance and polluted days, the HCHO and aerosol vertical profiles exhibited similar Gaussian shapes, but the NO2 profile exhibited an exponential decreasing shape. HCHO and aerosol were especially sensitive to O3 pollution, with higher values generally occurring at approximately noon and late afternoon at higher altitudes. We attempted to study the diurnal evolution of O3 sensitivity at different altitudes based on the HCHO to NO2 ratio (FNR) vertical profile. The FNR thresholds marking the transition regime (2.5 < FNR < 4.0) were derived from the relationship between the increase in O3 (∆O3) and FNR. Our results showed that O3 sensitivity tends to be VOC-limited both at lower (below approximately 0.4 km) and higher (above approximately 1.8 km) altitudes throughout the daytime. In the middle altitudes, the photochemical formation of O3 was mainly in the transition/NOx-limited regime in the morning and afternoon but in the VOC-limited regime at noontime. The relationship between TROPOMI column FNR and near-surface O3 sensitivity was further investigated. Compared with the MAX-DOAS near-surface FNR, slightly higher values of column FNR would increase the number of days classified as transition regimes, which was mainly caused by the inhomogeneous vertical distribution of HCHO and NO2 in the lower troposphere. This study provides an improved understanding of vertical variability and diurnal evolution of O3 formation sensitivity.
Collapse
Affiliation(s)
- Qianqian Hong
- School of Environment and Civil Engineering, Jiangnan University, Wuxi 214122, China
| | - Linbin Zhu
- School of Environment and Civil Engineering, Jiangnan University, Wuxi 214122, China
| | - Chengzhi Xing
- Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China.
| | - Qihou Hu
- Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Hua Lin
- School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China
| | - Chengxin Zhang
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
| | - Chunhui Zhao
- Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Ting Liu
- School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China
| | - Wenjing Su
- School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China
| | - Cheng Liu
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China; Anhui Province Key Laboratory of Polar Environment and Global Change, University of Science and Technology of China, Hefei 230026, China.
| |
Collapse
|
24
|
Cheng CY, Tseng YL, Huang KC, Chiu IM, Pan HY, Cheng FJ. Association between Ambient Air Pollution and Emergency Room Visits for Pediatric Respiratory Diseases: The Impact of COVID-19 Pandemic. TOXICS 2022; 10:toxics10050247. [PMID: 35622660 PMCID: PMC9146083 DOI: 10.3390/toxics10050247] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 05/06/2022] [Accepted: 05/11/2022] [Indexed: 02/05/2023]
Abstract
The level and composition of air pollution have changed during the coronavirus disease 2019 (COVID-19) pandemic. However, the association between air pollution and pediatric respiratory disease emergency department (ED) visits during the COVID-19 pandemic remains unclear. The study was retrospectively conducted between 2017 and 2020 in Kaohsiung, Taiwan, from 1 January 2020 to 1 May 2020, defined as the period of the COVID-19 pandemic, and 1 January 2017 to 31 May 2019, defined as the pre-COVID-19 pandemic period. We enrolled patients under 17 years old who visited the ED in a medical center and were diagnosed with respiratory diseases such as pneumonia, asthma, bronchitis, and acute pharyngitis. Measurements of particulate matter (PM) with aerodynamic diameters of <10 μm (PM10) and < 2.5 μm (PM2.5), nitrogen dioxide (NO2), and Ozone (O3) were collected. During the COVID-19 pandemic, an increase in the interquartile range of PM2.5, PM10, and NO2 levels was associated with increases of 72.5% (95% confidence interval [CI], 50.5−97.7%), 98.0% (95% CI, 70.7−129.6%), and 54.7% (95% CI, 38.7−72.6%), respectively, in the risk of pediatric respiratory disease ED visits on lag 1, which were greater than those in the pre-COVID-19 pandemic period. After adjusting for temperature and humidity, the risk of pediatric respiratory diseases after exposure to PM2.5 (inter p = 0.001) and PM10 (inter p < 0.001) was higher during the COVID-19 pandemic. PM2.5, PM10, and NO2 may play important roles in pediatric respiratory events in Kaohsiung, Taiwan. Compared with the pre-COVID-19 pandemic period, the levels of PM2.5 and PM10 were lower; however, the levels were related to a greater increase in ED during the COVID-19 pandemic.
Collapse
Affiliation(s)
- Chi-Yung Cheng
- Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung 833, Taiwan; (C.-Y.C.); (K.-C.H.); (I.-M.C.); (H.-Y.P.)
- College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
- Department of Computer Science and Engineering, National Sun Yat-sen University, 70, Lian-Hai Road, Kaohsiung 804, Taiwan
| | - Yu-Lun Tseng
- Institute of Environmental Engineering, National Sun Yat-sen University, 70, Lian-Hai Road, Kaohsiung 804, Taiwan;
| | - Kuo-Chen Huang
- Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung 833, Taiwan; (C.-Y.C.); (K.-C.H.); (I.-M.C.); (H.-Y.P.)
- College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
| | - I-Min Chiu
- Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung 833, Taiwan; (C.-Y.C.); (K.-C.H.); (I.-M.C.); (H.-Y.P.)
- College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
- Department of Computer Science and Engineering, National Sun Yat-sen University, 70, Lian-Hai Road, Kaohsiung 804, Taiwan
| | - Hsiu-Yung Pan
- Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung 833, Taiwan; (C.-Y.C.); (K.-C.H.); (I.-M.C.); (H.-Y.P.)
- College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
| | - Fu-Jen Cheng
- Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung 833, Taiwan; (C.-Y.C.); (K.-C.H.); (I.-M.C.); (H.-Y.P.)
- College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
- Correspondence: ; Tel.: +886-975056646; Fax: +886-7-7317123
| |
Collapse
|
25
|
Deng C, Tian S, Li Z, Li K. Spatiotemporal characteristics of PM 2.5 and ozone concentrations in Chinese urban clusters. CHEMOSPHERE 2022; 295:133813. [PMID: 35114261 DOI: 10.1016/j.chemosphere.2022.133813] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 01/25/2022] [Accepted: 01/28/2022] [Indexed: 06/14/2023]
Abstract
Despite China's public commitment to emphasise air pollution investigation and control, trends in PM2.5 and ozone concentrations in Chinese urban clusters remain unclear. This study quantifies the spatiotemporal variations in PM2.5 and surface ozone at the scale of Chinese urban clusters by using a long-term integrated dataset from 2015 to 2020. Nonlinear Granger causality testing was used to explore the spatial association patterns of PM2.5 and ozone pollution in five megacity cluster regions. The results show a significant downward trend in annual mean PM2.5 concentrations from 2015 to 2020, with a decline rate of 2.8 μg m-3 yr-1. By contrast, surface ozone concentrations increased at a rate of 2.1 μg m-3 yr-1 over the 6 years. The annual mean PM2.5 concentrations in urban clusters show significant spatial clustering characteristics, mainly in Beijing-Tianjin-Hebei (BTH), Fenwei Plain (FWP), Northern slope of Tianshan Mountains urban cluster (NSTM), Sichuan Basin urban cluster (SCB), and Yangtze River Delta (YRD). Surface ozone shows severe summertime pollution and distributional variability, with increased ozone pollution in major urban clusters. The highest increases were observed in BTH, Yangtze River midstream urban cluster (YRMR), YRD, and Pearl River Delta (PRD). Nonlinear Granger causality tests showed that PM2.5 was a nonlinear Granger cause of ozone, further supporting the literature's findings that PM2.5 reduction promoted photochemical reaction rates and stimulated ozone production. The nonlinear test statistic passed the significance test in magnitude and statistical significance. FWP was an exception, with no significant long-term nonlinear causal link between PM2.5 and ozone. This study highlights the challenges of compounded air pollution caused primarily by ozone and secondary PM2.5. These results have implications for the design of synergistic pollution abatement policies for coupled urban clusters.
Collapse
Affiliation(s)
- Chuxiong Deng
- School of Geographic Sciences, Hunan Normal University, Changsha, Hunan, 410081, PR China.
| | - Si Tian
- School of Geographic Sciences, Hunan Normal University, Changsha, Hunan, 410081, PR China.
| | - Zhongwu Li
- School of Geographic Sciences, Hunan Normal University, Changsha, Hunan, 410081, PR China.
| | - Ke Li
- Key Laboratory of Computing and Stochastic Mathematics (Ministry of Education of China), Key Laboratory of Applied Statistics and Data Science, School of Mathematics and Statistics, Hunan Normal University, Changsha, Hunan, 410081, PR China.
| |
Collapse
|
26
|
Analysis of the Effect of Economic Development on Air Quality in Jiangsu Province Using Satellite Remote Sensing and Statistical Modeling. ATMOSPHERE 2022. [DOI: 10.3390/atmos13050697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
In recent decades, the economy of China has developed rapidly, but this has brought widespread damage to the environment, which forces us to explore a sustainable, green, economic development model. Therefore, it is particularly necessary to clarify the relationship between economic development and environmental pollution. In this paper, we used satellite remote sensing tropospheric NO2 vertical column density (VCD) as an air quality indicator; the total exports, total imports, and industrial electricity consumption as the economic indicators; and the wind speed, temperature, and planetary boundary layer height as the meteorological factors to perform a Generalized Additive Modeling (GAM) analysis. By deducing the influence of meteorological factors, the relationship between economic indicators and the air quality indicator can be determined. When total exports increased by one billion USD (United States Dollar), the tropospheric NO2 VCDs of Nanjing and Suzhou increased by about 15% and 6%, respectively. The tropospheric NO2 VCDs of Suzhou increased by about 5% when the total imports increased by one billion USD. In addition, when the industrial electricity consumption increased by one billion kWh, the tropospheric NO2 VCDs of Nanjing, Suzhou and Xuzhou increased by about 25%, 12%, and 59%, respectively. This study provides a method to quantify the contribution of economic growth to air pollution, which is helpful for better understanding of the relationship between economic development and air quality.
Collapse
|
27
|
Sbai SE, Bentayeb F, Yin H. Atmospheric pollutants response to the emission reduction and meteorology during the COVID-19 lockdown in the north of Africa (Morocco). STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT : RESEARCH JOURNAL 2022; 36:3769-3784. [PMID: 35498271 PMCID: PMC9033931 DOI: 10.1007/s00477-022-02224-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 03/25/2022] [Indexed: 06/14/2023]
Abstract
Climate and air quality change due to COVID-19 lockdown (LCD) are extremely concerned subjects of several research recently. The contribution of meteorological factors and emission reduction to air pollution change over the north of Morocco has been investigated in this study using the framework generalized additive models, that have been proved to be a robust technique for the environmental data sets, focusing on main atmospheric pollutants in the region including ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter (PM2.5 and PM10), secondary inorganic aerosols (SIA), nom-methane volatile organic compounds and carbon monoxide (CO) from the regional air pollution dataset of the Copernicus Atmosphere Monitoring Service. Our results, indicate that secondary air pollutants (PM2.5, PM10 and O3) are more influenced by metrological factors and the other air pollutants reported by this study (NO2 and SO2). We show a negative effect for PBHL, total precipitation and NW10M on PM (PM2.5 and PM10 ), this meteorological parameters contribute to decrease in PM2.5 by 9, 2 and 9% respectively, before LCD and 8, 1 and 5% respectively during LCD. However, a positive marginal effect was found for SAT, Irradiance and RH that contribute to increase PM2.5 by 9, 12 and 18% respectively, before LCD and 17, 54 and 34% respectively during LCD. We found also that meteorological factors contribute to O3, PM2.5, PM10 and SIA average mass concentration by 22, 5, 3 and 34% before LCD and by 28, 19, 5 and 42% during LCD respectively. The increase in meteorological factors marginal effect during LCD shows the contribution of photochemical oxidation to air pollution due to increase in atmospheric oxidant (O3 and OH radical) during LCD, which can explain the response of PM to emission reduction. This study indicates that PM (PM2.5, PM10) has more controlled by SO2 due to the formation of sulfate particles especially under high oxidants level. The positive correlation between westward wind at 10 m (WW10M), Northward Wind at 10 m (NW10M) and PM indicates the implication of sea salt particles transported from Mediterranean Sea and Atlantic Ocean. The Ozone mass concentration shows a positive trend with Irradiance, Total and SAT during LCD; because temperature and irradiance enhance tropospheric ozone formation via photochemical reaction.This study shows the contribution of atmospheric oxidation capacity to air pollution change. Supplementary Information The online version contains supplementary material available at 10.1007/s00477-022-02224-z.
Collapse
Affiliation(s)
- Salah Eddine Sbai
- Department of Physics, Laboratoires de Physique des Hauts Energies Modélisation et Simulation, Mohammed V University in Rabat, Rabat, Morocco
| | - Farida Bentayeb
- Department of Physics, Laboratoires de Physique des Hauts Energies Modélisation et Simulation, Mohammed V University in Rabat, Rabat, Morocco
| | - Hao Yin
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031 China
- University of Science and Technology of China, Hefei, 230026 China
| |
Collapse
|
28
|
Multi-Year Variation of Ozone and Particulate Matter in Northeast China Based on the Tracking Air Pollution in China (TAP) Data. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19073830. [PMID: 35409512 PMCID: PMC8997942 DOI: 10.3390/ijerph19073830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 03/18/2022] [Accepted: 03/22/2022] [Indexed: 12/10/2022]
Abstract
With the rapid development of economy and urbanization acceleration, ozone (O3) pollution has become the main factor of urban air pollution in China after particulate matter. In this study, 90th percentile of maximum daily average (MDA) 8 h O3 (O3-8h-90per) and PM2.5 data from the Tracking Air Pollution in China (TAP) dataset were used to determine the mean annual, seasonal, monthly, and interannual distribution of O3-8h-90per and PM2.5 concentrations in Northeast China (NEC). The O3-8h-90per concentration was highest in Liaoning (>100 μg/m3), whereas the highest PM2.5 concentration was observed mainly in urban areas of central Liaoning and the Harbin−Changchun urban agglomeration (approximately 60 μg/m3). The O3-8h-90per concentrations were highest in spring and summer due to more intense solar radiation. On the contrary, the PM2.5 concentration increased considerably in winter influenced by anthropogenic activities. In May and June, the highest monthly mean O3-8h-90per concentrations were observed in central and western Liaoning, about 170−180 μg/m3, while the PM2.5 concentrations were the highest in January, February, and December, approximately 100 μg/m3. The annual mean O3-8h-90per concentration in NEC showed an increasing trend, while the PM2.5 concentration exhibited an annual decline. By 2020, the annual mean O3-8h-90per concentration in southern Liaoning had increased considerably, reaching 120−130 μg/m3. From the perspective of city levels, PM2.5 and O3-8h-90per also showed an opposite variation trend in the 35 cities of NEC. The reduced tropospheric NO2 column is consistent with the decreasing trend of the interannual PM2.5, while the increased surface temperature could be the main meteorological factor affecting the O3-8h-90per concentration in NEC. The results of this study enable a comprehensive understanding of the regional and climatological O3-8h-90per and PM2.5 distribution at distinct spatial and temporal scales in NEC.
Collapse
|
29
|
Ghahremanloo M, Lops Y, Choi Y, Jung J, Mousavinezhad S, Hammond D. A comprehensive study of the COVID-19 impact on PM 2.5 levels over the contiguous United States: A deep learning approach. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2022; 272:118944. [PMID: 35043042 PMCID: PMC8758197 DOI: 10.1016/j.atmosenv.2022.118944] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 12/26/2021] [Accepted: 01/05/2022] [Indexed: 05/21/2023]
Abstract
We investigate the impact of the COVID-19 outbreak on PM2.5 levels in eleven urban environments across the United States: Washington DC, New York, Boston, Chicago, Los Angeles, Houston, Dallas, Philadelphia, Detroit, Phoenix, and Seattle. We estimate daily PM2.5 levels over the contiguous U.S. in March-May 2019 and 2020, and leveraging a deep convolutional neural network, we find a correlation coefficient, an index of agreement, a mean absolute bias, and a root mean square error of 0.90 (0.90), 0.95 (0.95), 1.34 (1.24) μg/m3, and 2.04 (1.87) μg/m3, respectively. Results from Google Community Mobility Reports and estimated PM2.5 concentrations show a greater reduction of PM2.5 in regions with larger decreases in human mobility and those in which individuals remain in their residential areas longer. The relationship between vehicular PM2.5 (i.e., the ratio of vehicular PM2.5 to other sources of PM2.5) emissions and PM2.5 reductions (R = 0.77) in various regions indicates that regions with higher emissions of vehicular PM2.5 generally experience greater decreases in PM2.5. While most of the urban environments ⸺ Washington DC, New York, Boston, Chicago, Los Angeles, Houston, Dallas, Philadelphia, Detroit, and Seattle ⸺ show a decrease in PM2.5 levels by 21.1%, 20.7%, 18.5%, 8.05%, 3.29%, 3.63%, 6.71%, 4.82%, 13.5%, and 7.73%, respectively, between March-May of 2020 and 2019, Phoenix shows a 5.5% increase during the same period. Similar to their PM2.5 reductions, Washington DC, New York, and Boston, compared to other cities, exhibit the highest reductions in human mobility and the highest vehicular PM2.5 emissions, highlighting the great impact of human activity on PM2.5 changes in eleven regions. Moreover, compared to changes in meteorological factors, changes in pollutant concentrations, including those of black carbon, organic carbon, SO2, SO4, and especially NO2, appear to have had a significantly greater impact on PM2.5 changes during the study period.
Collapse
Affiliation(s)
- Masoud Ghahremanloo
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77004, USA
| | - Yannic Lops
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77004, USA
| | - Yunsoo Choi
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77004, USA
| | - Jia Jung
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77004, USA
| | - Seyedali Mousavinezhad
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77004, USA
| | - Davyda Hammond
- Oak Ridge Associated Universities, Oak Ridge, TN, 37830, USA
| |
Collapse
|
30
|
Variations of Urban NO2 Pollution during the COVID-19 Outbreak and Post-Epidemic Era in China: A Synthesis of Remote Sensing and In Situ Measurements. REMOTE SENSING 2022. [DOI: 10.3390/rs14020419] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Since the COVID-19 outbreak in 2020, China’s air pollution has been significantly affected by control measures on industrial production and human activities. In this study, we analyzed the temporal variations of NO2 concentrations during the COVID-19 lockdown and post-epidemic era in 11 Chinese megacities by using satellite and ground-based remote sensing as well as in situ measurements. The average satellite tropospheric vertical column density (TVCD) of NO2 by TROPOMI decreased by 39.2–71.93% during the 15 days after Chinese New Year when the lockdown was at its most rigorous compared to that of 2019, while the in situ NO2 concentration measured by China National Environmental Monitoring Centre (CNEMC) decreased by 42.53–69.81% for these cities. Such differences between both measurements were further investigated by using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) remote sensing of NO2 vertical profiles. For instance, in Beijing, MAX-DOAS NO2 showed a decrease of 14.19% (versus 18.63% by in situ) at the ground surface, and 36.24% (versus 36.25% by satellite) for the total tropospheric column. Thus, vertical discrepancies of atmospheric NO2 can largely explain the differences between satellite and in situ NO2 variations. In the post-epidemic era of 2021, satellite NO2 TVCD and in situ NO2 concentrations decreased by 10.42–64.96% and 1.05–34.99% compared to 2019, respectively, possibly related to the reduction of the transportation industry. This study reveals the changes of China’s urban NO2 pollution in the post-epidemic era and indicates that COVID-19 had a profound impact on human social activities and industrial production.
Collapse
|