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Cao X, You X, Wang D, Qiu W, Guo Y, Zhou M, Chen W, Zhang X. Short-term effects of ambient ozone exposure on daily hospitalizations for circulatory diseases in Ganzhou, China: A time-series study. CHEMOSPHERE 2023; 327:138513. [PMID: 36990357 DOI: 10.1016/j.chemosphere.2023.138513] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 03/01/2023] [Accepted: 03/24/2023] [Indexed: 06/19/2023]
Abstract
Adverse health effects of ambient ozone are getting widespread attention, but the evidence on the relationship between ozone levels and circulatory system diseases are limited and inconsistent. Daily data for ambient ozone levels and hospitalizations for total circulatory diseases and five subtypes in Ganzhou, China from January 1, 2016 to December 31, 2020 were collected. We constructed a generalized additive model with quasi-Poisson regression accounting for lag effects to estimate the associations between ambient ozone levels and the number of hospitalized cases of total circulatory diseases and five subtypes. The differences among gender, age, and season subgroups were furtherly assessed through stratified analysis. A total of 201,799 hospitalized cases of total circulatory diseases were included in the present study, including 94,844 hypertension (HBP), 28,597 coronary heart disease (CHD), 42,120 cerebrovascular disease (CEVD), 21,636 heart failure (HF), and 14,602 arrhythmia. Significantly positive associations were observed between ambient ozone levels and daily hospitalizations for total circulatory diseases and all subtypes except arrhythmia. Each 10 μg/m3 increase in ozone concentration, the risk of hospitalizations for total circulatory diseases, HBP, CHD, CEVD, and HF increased by 0.718% (95% confidence interval, 0.156%-1.284%), 0.956% (0.346%-1.570%), 0.499% (0.057%-0.943%), 0.386% (0.025%-0.748%), and 0.907% (0.118%-1.702%), respectively. The above associations remained significant after adjusting for other air pollutants. The risk of hospitalization for circulatory diseases was higher in warm season (May to October) and varied in gender and age subgroups. This study suggested that short-term exposure to ambient ozone may increase the risk of hospitalizations for circulatory diseases. Our findings reinforce the importance of reducing ambient ozone pollution levels for protecting public health.
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Affiliation(s)
- Xiuyu Cao
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Xiaojie You
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Dongming Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Weihong Qiu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - You Guo
- First Affiliated Hospital, Gannan Medical University, Ganzhou, China; Key Laboratory of Prevention and Treatment of Cardiovascular and Cerebrovascular Diseases, Ministry of Education, Gannan Medical University, Ganzhou, China; School of Public Health and Health Management, Gannan Medical University, Ganzhou, China
| | - Min Zhou
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Weihong Chen
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
| | - Xiaokang Zhang
- First Affiliated Hospital, Gannan Medical University, Ganzhou, China; Key Laboratory of Prevention and Treatment of Cardiovascular and Cerebrovascular Diseases, Ministry of Education, Gannan Medical University, Ganzhou, China; School of Public Health and Health Management, Gannan Medical University, Ganzhou, China
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Wang K, Xie F, Sulaymon ID, Gong K, Li N, Li J, Hu J. Understanding the nocturnal ozone increase in Nanjing, China: Insights from observations and numerical simulations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 859:160211. [PMID: 36410475 DOI: 10.1016/j.scitotenv.2022.160211] [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: 10/01/2022] [Revised: 11/11/2022] [Accepted: 11/12/2022] [Indexed: 06/16/2023]
Abstract
Surface ozone (O3) is mainly photochemically formed by nitrogen oxides (NOX) and volatile organic compounds (VOCs), and therefore O3 usually has a distinct diurnal variation with high concentrations in the afternoon and low values at night. However, eight nocturnal O3 increase (NOI) events were identified in Nanjing in June 2021. To understand the mechanism of NOI events, we selected two events (June 6-7, and 24-25) for observational data analysis. The Community Multiscale Air Quality (CMAQ) model was employed for the process analysis (PA) and regional transport of O3. By analyzing the O3 observation data and meteorological factors, we found that there were clear southeastward O3 transport paths. The O3 peak clearly moved from the upwind to the downwind cities in both events. Model simulations showed that when nocturnal O3 enhancement occurred, horizontal transport resulted in a negative to positive net O3 production rate. O3 continued to get accumulated in Nanjing. Nocturnal O3 in the first event was dominated by long-range transport, with the top two contributing cities being Huzhou (5.6 %) and Jiaxing (4.7 %). NOI during the second event was from the nearby upwind cities. The top three contributing cities were Shanghai (18.3 %), Wuxi (9.1 %), and Suzhou (8.8 %). We conclude that the June NOI events in Nanjing were mainly driven by the horizontal transport of southeasterly winds. This study provides scientific support for O3 prevention and control in Nanjing in the summer.
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Affiliation(s)
- Kang Wang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, China
| | - Fangjian Xie
- Nanjing Municipal Academy of Ecological and Environment Protection Science, Nanjing 210093, China
| | - Ishaq Dimeji Sulaymon
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, China
| | - Kangjia Gong
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, China
| | - Nan Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, China
| | - Jingyi Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, China
| | - Jianlin Hu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, China.
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Kuttippurath J, Patel VK, Pathak M, Singh A. Improvements in SO 2 pollution in India: role of technology and environmental regulations. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:78637-78649. [PMID: 35696063 PMCID: PMC9189448 DOI: 10.1007/s11356-022-21319-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Accepted: 06/02/2022] [Indexed: 05/06/2023]
Abstract
India relies heavily on coal-based thermal power plants to meet its energy demands. Sulphur dioxide (SO2) emitted from these plants and industries is a major air pollutant. Analysis of spatial and temporal changes in SO2 using accurate and continuous observations is required to formulate mitigation strategies to curb the increasing air pollution in India. Here, we present the temporal changes in SO2 concentrations over India in the past four decades (1980-2020). Our analysis shows that the Central and East India, and Indo-Gangetic Plain (IGP) are the hotspots of SO2, as these regions house a cluster of thermal power plants, petroleum refineries, steel manufacturing units, and cement Industries. Thermal power plants (51%), and manufacturing and construction industries (29%) are the main sources of anthropogenic SO2 in India. Its concentration over India is higher in winter (December-February) and lower in pre-monsoon (March-May) seasons. The temporal analyses reveal that SO2 concentrations in India increased between 1980 and 2010 due to high coal burning and lack of novel technology to contain the emissions during the period. However, SO2 shows a decreasing trend in recent decade (2010-2020) because of the environmental regulations and implementation of effective control technologies such as the flue gas desulphurisation (FGD) and scrubber. Since 2010, India's renewable energy production has also been increased substantially when India adopted a sustainable development policy. Therefore, the shift in energy production from conventional coal to renewable sources, solid environmental regulation, better inventory, and effective technology would help to curb SO2 pollution in India. Both economic growth and air pollution control can be performed hand-in-hand by adopting new technology to reduce SO2 and GHG emissions.
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Affiliation(s)
| | - Vikas Kumar Patel
- CORAL, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
| | - Mansi Pathak
- CORAL, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
| | - Ajay Singh
- CORAL, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
- AgFE Department, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
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Qiu C, Feng W, An X, Liu F, Liang F, Tang X, Zhang P, Liang X. The effect of fine particulate matter exposure on allergic rhinitis of adolescents aged 10-13 years: A cross-sectional study from Chongqing, China. Front Public Health 2022; 10:921089. [PMID: 36388289 PMCID: PMC9642846 DOI: 10.3389/fpubh.2022.921089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 09/26/2022] [Indexed: 01/22/2023] Open
Abstract
Background Allergic rhinitis (AR) has become a tremendous disease burden worldwide. Only a few studies have explored the effects of environmental exposure on the prevalence of AR in children in China. Methods In the present study, we investigated the associations of environmental exposure (including fine particulate matter (PM2.5), air humidity, temperature, and passive smoking) with AR in adolescents aged 10-13 years in Chongqing. Data from 4,146 participants in urban and rural areas between March 2019 and May 2019 were collected. Results The overall prevalence of AR was 17.50% in adolescents. After adjusting for other covariates, AR was positively correlated with the annual mean PM2.5 concentration, monthly mean PM2.5 concentration and air temperature, and negatively related to air humidity. Furthermore, the annual mean PM2.5 was positively associated with the risk of AR after adjusting for air temperature and humidity. Passive smoking (PS) was marginally associated with a high risk of AR. Conclusion High PM2.5 exposure, high air temperature, and low air humidity were associated with a high risk of AR in adolescents. Our findings have potential implications for public health strategies and interventions aimed at reducing the burden of AR in adolescents.
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Affiliation(s)
- Chunlan Qiu
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China
| | - Wei Feng
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China
| | - Xizhou An
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China
| | - Fangchao Liu
- Department of Epidemiology, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fengchao Liang
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
| | - Xian Tang
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China
| | - Ping Zhang
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China
| | - Xiaohua Liang
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China,*Correspondence: Xiaohua Liang
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Xu C, Wang X. Air Pollution and Migration Intention: Evidence from the Unified National Graduate Entrance Examination. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19148813. [PMID: 35886664 PMCID: PMC9323777 DOI: 10.3390/ijerph19148813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 07/15/2022] [Accepted: 07/18/2022] [Indexed: 02/04/2023]
Abstract
Using a unique dataset of applicants for the Unified National Graduate Entrance Examination (UNGEE) of 76 double first-class universities in China, this paper evaluates the causal impact of air pollution on the migration intentions of highly educated talents by exploiting an instrumental variable approach based on annually average wind speed. We find that a 1 ug/m3 increase in the annually average PM2.5 concentration in destination cities decreases the number of applicants for the UNGEE of elite universities by about 250, but better university quality and more abundant educational resources can weaken the effect partially. A heterogeneity analysis indicates that the university-city choices of applicants are shifting from north to south. Our findings suggest that air pollution may lead to the loss of high human capital.
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Affiliation(s)
- Chao Xu
- School of Public Finance & Taxation, Shandong University of Finance and Economics, Jinan 250002, China;
| | - Xiulei Wang
- School of Economics & Trade, Hunan University, Changsha 410006, China
- Correspondence:
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Holder AJ, Hayes F. Substantial yield reduction in sweet potato due to tropospheric ozone, the dose-response function. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 304:119209. [PMID: 35341818 DOI: 10.1016/j.envpol.2022.119209] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 03/03/2022] [Accepted: 03/22/2022] [Indexed: 06/14/2023]
Abstract
Impacts of tropospheric ozone on sweet potato (Ipomoea batatas) are poorly understood despite being a staple food grown in locations deemed at risk from ozone pollution. Three varieties of sweet potato were exposed to ozone treatments (peaks of: 30 (Low), 80 (Medium), and 110 (High) ppb) using heated solardomes. Weekly measurements of stomatal conductance (gs) and chlorophyll content (CI) were used to determine physiological responses, along with final yield. gs and CI were reduced with increasing ozone exposure, but effects were partially masked due to elevated leaf senescence and turnover. Yield for the Erato orange and Murasaki varieties was reduced by ∼40% and ∼50% (Medium and High ozone treatments, respectively, vs Low) whereas Beauregard yield was reduced by 58% in both. The DO3SE (Deposition of Ozone for Stomatal Exchange) model was parameterized for gs in response to light, temperature, vapour pressure deficit and soil water potential. Clear responses of gs to the environmental parameters were found. Yield reductions were correlated with both concentration based AOT40 (accumulated ozone above a threshold of 40 ppb) and flux based POD6 (accumulated stomatal flux of ozone above a threshold of 6 nmol m- 2 s- 1) metrics (R2 0.66 p = 0.01; and R2 0.44 p = 0.05, respectively). A critical level estimate of a POD6 of 3 (mmol m-2 Projected Leaf Area-1) was obtained using the relationship. This study showed that sweet potato yield was reduced by ozone pollution, and that stomatal conductance and chlorophyll content were also affected. Results from this study can improve model predictions of ozone impacts on sweet potato together with associated ozone risk assessments for tropical countries.
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Affiliation(s)
- Amanda J Holder
- UK Centre for Ecology & Hydrology, Environment Centre Wales, Deiniol Road, Bangor, LL57 2UW, UK
| | - Felicity Hayes
- UK Centre for Ecology & Hydrology, Environment Centre Wales, Deiniol Road, Bangor, LL57 2UW, UK.
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Ren B, Xie P, Xu J, Li A, Qin M, Hu R, Zhang T, Fan G, Tian X, Zhu W, Hu Z, Huang Y, Li X, Meng F, Zhang G, Tong J, Ren H, Zheng J, Zhang Z, Lv Y. Vertical characteristics of NO 2 and HCHO, and the ozone formation regimes in Hefei, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 823:153425. [PMID: 35090930 DOI: 10.1016/j.scitotenv.2022.153425] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 01/10/2022] [Accepted: 01/22/2022] [Indexed: 06/14/2023]
Abstract
The research on the mechanism of combined air pollution in the Yangtze-Huaihe region, which is characterized by unique meteorological and geographical conditions and pollution emission characteristics, is still insufficient. We performed an experiment on key pollutants and an ozone formation study in Hefei, which is a pivotal city in the Yangtze-Huaihe region, from September 1 to 20, 2020. The aerosols retrieved via two-dimensional Multi-axis Differential Optical Absorption Spectroscopy (2D-MAX-DOAS) with a Boltzmann-shaped a priori profile had the best agreement with the results of Light Detection and Ranging (LIDAR) and sun-photometer measurements among the three typical a priori profiles (Gaussian, Boltzmann, and exponential shapes). The correlation coefficients of the near-surface gas concentrations retrieved using both 2D-MAX-DOAS and in situ measurements were 0.86 (NO2) and 0.61 (HCHO). The high NO2 and HCHO concentrations were observed at azimuths of 180° and 315° at heights of 0.8-1.5 km, and they may have been emitted by aircrafts. Importantly, the ratio of HCHO to NO2 during a typical pollution episode revealed that the factors controlling the O3 formation changed with altitude: VOCs (surface) to NOx (0.4 km) to transition (1.0 km) to VOCs (1.6 km). Moreover, the effect of VOCs on the O3 generation was stronger than that of NOx, especially in the downtown area of Hefei. When the ratio of HCHO to NO2 was 3.55-7.46, the ozone concentration in Hefei could be controlled well, especially at the optimal value of 5.50.
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Affiliation(s)
- Bo Ren
- School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China; Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Pinhua Xie
- School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China; Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China; CAS Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China; Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China.
| | - Jin Xu
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China.
| | - Ang Li
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Min Qin
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Renzhi Hu
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Tianshu Zhang
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Guangqiang Fan
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Xin Tian
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China; Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Wei Zhu
- Beijing SDL Environment Technology Ltd., Beijing SDL Technology Co., Ltd., Beijing 102206, China
| | - Zhaokun Hu
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Yeyuan Huang
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Xiaomei Li
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Fanhao Meng
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Guoxian Zhang
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Jinzhao Tong
- School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China; Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Hongmei Ren
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Jiangyi Zheng
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Zhidong Zhang
- School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China; Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
| | - Yinsheng Lv
- School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China; Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
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Conibear L, Reddington CL, Silver BJ, Chen Y, Arnold SR, Spracklen DV. Emission Sector Impacts on Air Quality and Public Health in China From 2010 to 2020. GEOHEALTH 2022; 6:e2021GH000567. [PMID: 35765413 PMCID: PMC9207900 DOI: 10.1029/2021gh000567] [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: 12/01/2021] [Revised: 03/22/2022] [Accepted: 03/31/2022] [Indexed: 06/15/2023]
Abstract
Anthropogenic emissions and ambient fine particulate matter (PM2.5) concentrations have declined in recent years across China. However, PM2.5 exposure remains high, ozone (O3) exposure is increasing, and the public health impacts are substantial. We used emulators to explore how emission changes (averaged per sector over all species) have contributed to changes in air quality and public health in China over 2010-2020. We show that PM2.5 exposure peaked in 2012 at 52.8 μg m-3, with contributions of 31% from industry and 22% from residential emissions. In 2020, PM2.5 exposure declined by 36% to 33.5 μg m-3, where the contributions from industry and residential sources reduced to 15% and 17%, respectively. The PM2.5 disease burden decreased by only 9% over 2012 where the contributions from industry and residential sources reduced to 15% and 17%, respectively 2020, partly due to an aging population with greater susceptibility to air pollution. Most of the reduction in PM2.5 exposure and associated public health benefits occurred due to reductions in industrial (58%) and residential (29%) emissions. Reducing national PM2.5 exposure below the World Health Organization Interim Target 2 (25 μg m-3) would require a further 80% reduction in residential and industrial emissions, highlighting the challenges that remain to improve air quality in China.
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Affiliation(s)
- Luke Conibear
- Institute for Climate and Atmospheric ScienceSchool of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - Carly L. Reddington
- Institute for Climate and Atmospheric ScienceSchool of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - Ben J. Silver
- Institute for Climate and Atmospheric ScienceSchool of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - Ying Chen
- College of Engineering, Mathematics and Physical SciencesUniversity of ExeterExeterUK
| | - Stephen R. Arnold
- Institute for Climate and Atmospheric ScienceSchool of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - Dominick V. Spracklen
- Institute for Climate and Atmospheric ScienceSchool of Earth and EnvironmentUniversity of LeedsLeedsUK
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Zhang X, Cheng C, Zhao H. A Health Impact and Economic Loss Assessment of O 3 and PM 2.5 Exposure in China From 2015 to 2020. GEOHEALTH 2022; 6:e2021GH000531. [PMID: 35355832 PMCID: PMC8950782 DOI: 10.1029/2021gh000531] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 02/21/2022] [Accepted: 02/27/2022] [Indexed: 05/29/2023]
Abstract
China is in a critical air quality management stage. Rapid industrial development and urbanization has resulted in non-ignorable air pollution, which seriously endangers human health. Assessment of the health impacts and economic losses of air pollution is essential for the prevention and control policy formulation. Based on ozone (O3) and fine particulate matter concentration (PM2.5) monitoring data in 331 Chinese cities from 2015 to 2020, this study evaluated the health effects and the corresponding economic losses of O3 and PM2.5 pollution on three health endpoints. The ratio of population exposed to O3 levels that exceeded the Chinese Ambient Air Quality Standards (CAAQS) increased from 13.35% in 2015 to 14.15% in 2020, which resulted in 133,415 (2015) - 156,173 (2020) all-cause deaths, 88,941 (2015) - 104,051 (2020) cardiovascular deaths, and 28,614 (2015) - 33,456 (2020) respiratory deaths. The ratio of population exposed to PM2.5 levels that exceeded the CAAQS decreased, but in many regions, especially in North China and the Yangtze River Delta, the PM2.5 concentration remained high. By 2020, nearly half of the population in China was still exposed to PM2.5 levels that exceeded the CAAQS, and the corresponding economic losses reached CNY 3.46 and 3.05 billion, respectively. These results improved the understanding of the spatial-temporal variation trends of major air pollutants at city scale in China, and emphasize the continued coordination urgently needed for controlling O3 and PM2.5 following the implementation of the 2013 policy to mitigate air pollution to protect human health.
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Affiliation(s)
- Xiangxue Zhang
- State Key Laboratory of Earth Surface Processes and Resource EcologyBeijing Normal UniversityBeijingChina
- Key Laboratory of Environmental Change and Natural DisasterMinistry of EducationBeijing Normal UniversityBeijingChina
| | - Changxiu Cheng
- State Key Laboratory of Earth Surface Processes and Resource EcologyBeijing Normal UniversityBeijingChina
- Key Laboratory of Environmental Change and Natural DisasterMinistry of EducationBeijing Normal UniversityBeijingChina
- National Tibetan Plateau Data CenterBeijingChina
| | - Hui Zhao
- Department of Environmental Science and EngineeringFudan UniversityShanghaiChina
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10
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Chi Y, Fan M, Zhao C, Yang Y, Fan H, Yang X, Yang J, Tao J. Machine learning-based estimation of ground-level NO 2 concentrations over China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 807:150721. [PMID: 34619217 DOI: 10.1016/j.scitotenv.2021.150721] [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: 09/02/2021] [Revised: 09/27/2021] [Accepted: 09/27/2021] [Indexed: 05/16/2023]
Abstract
Most current scientific research on NO2 remote sensing focuses on tropospheric NO2 column concentrations rather than ground-level NO2 concentrations; however, ground-level NO2 concentrations are more related to anthropogenic emissions and human health. This study proposes a machine learning estimation method for retrieving the ground-level NO2 concentrations throughout China based on the tropospheric NO2 column concentrations from the TROPOspheric Monitoring Instrument (TROPOMI) and multisource geographic data from 2018 to 2020. This method adopts the XGBoost machine learning model characterized by a strong fitting ability and complex model structure, which can explain the complex nonlinear and high-order relationships between ground-measured NO2 and its influencing factors. The R2 values between the retrievals and the validation and test datasets are 0.67 and 0.73, respectively, which suggests that the proposed method can reliably retrieve the ground-level NO2 concentrations across China. The distribution characteristics, seasonal variations and interannual differences in ground-level NO2 concentrations are further analyzed based on the retrieval results, demonstrating that the ground-level NO2 concentrations exhibit significant geographical and seasonal variations, with high concentrations in winter and low concentrations in summer, and the highly polluted regions are concentrated mainly in Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), Cheng-Yu District (CY) and other urban agglomerations. Finally, the interannual variation in the ground-level NO2 concentrations indicates that pollution decreased continuously from 2018 to 2020.
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Affiliation(s)
- Yulei Chi
- State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
| | - Meng Fan
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
| | - Chuanfeng Zhao
- State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China.
| | - Yikun Yang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
| | - Hao Fan
- State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
| | - Xingchuan Yang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
| | - Jie Yang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
| | - Jinhua Tao
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
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11
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Zhu L, Zhang Y, Wu Z, Zhang C. Spatio-Temporal Characteristics of SO 2 across Weifang from 2008 to 2020. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182212206. [PMID: 34831963 PMCID: PMC8624775 DOI: 10.3390/ijerph182212206] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 11/14/2021] [Accepted: 11/16/2021] [Indexed: 11/30/2022]
Abstract
China has achieved good results in SO2 pollution control, but SO2 pollution still exists in some areas. Analyzing the spatio-temporal distribution of SO2 is critical for regional SO2 pollution prevention and control. Compared with existing air pollution studies that paid more attention to PM2.5, NO2 and O3, and focused on the macro scale, this study took the small-scale Weifang city as the research area, analyzed the temporal and spatial changes in SO2, discussed the migration trajectory of SO2 pollution and explored the impact of wind on SO2 pollution. The results show that the average annual concentration of SO2 in Weifang has exhibited a downward trend in the past 13 years, showing the basic characteristics of “highest in winter, lowest in summer and slightly higher in spring and autumn”, “highest on Sunday, lowest on Thursday and gradually decreasing from Monday to Thursday” and “highest at 9 a.m., lowest at 4 p.m. and gradually increasing from midnight to 9 a.m.”. SO2 concentration showed obvious spatial heterogeneity: higher in the north and lower in the south. In addition, Shouguang, Changyi and Gaomi were seriously polluted. The SO2 pollution shifted from south to northeast. The clean wind direction (southeast wind and northeast wind) of Weifang city accounted for about 41%, and the pollution wind direction (northwest wind and west wind) accounted for about 7%. Drawing from the multi-scale analysis, vegetation, precipitation, temperature, transport situation and human activity were the most relevant factors. Limited to data collection, more quantitative research is needed to gain insight into the influence mechanism in the future.
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12
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Research on the Temporal and Spatial Characteristics of Air Pollutants in Sichuan Basin. ATMOSPHERE 2021. [DOI: 10.3390/atmos12111504] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Sichuan Basin is one of the most densely populated areas in China and the world. Human activities have great impact on the air quality. In order to understand the characteristics of overall air pollutants in Sichuan Basin in recent years, we analyzed the concentrations of six air pollutants monitored in 22 cities during the period from January 2015 to December 2020. During the study period, the annual average concentrations of CO, NO2, SO2, PM2.5 and PM10 all showed a clear downward trend, while the ozone concentration was slowly increasing. The spatial patterns of CO and SO2 were similar. High-concentration areas were mainly located in the western plateau of Sichuan Basin, while the concentrations of NO2 and particulate matter were more prominent in the urban agglomerations inside the basin. During the study period, changes of the monthly average concentrations for pollutants (except for O3) conformed to the U-shaped pattern, with the highest in winter and the lowest in summer. In the southern cities of the basin, secondary sources had a higher contribution to the generation of fine particulate matter, while in large cities inside the basin, such as Chengdu and Chongqing, air pollution had a strong correlation with automobile exhaust emissions. The heavy pollution incidents observed in the winter of 2017 were mainly caused by the surrounding plateau terrain with typical stagnant weather conditions. This finding was also supported by the backward trajectory analysis, which showed that the air masses arrived in Chengdu were mainly from the western plateau area of the basin. The results of this study will provide a basis for the government to take measures to improve the air quality in Sichuan Basin.
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Wang J, Lei Y, Chen Y, Wu Y, Ge X, Shen F, Zhang J, Ye J, Nie D, Zhao X, Chen M. Comparison of air pollutants and their health effects in two developed regions in China during the COVID-19 pandemic. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2021; 287:112296. [PMID: 33711659 PMCID: PMC7927583 DOI: 10.1016/j.jenvman.2021.112296] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 02/22/2021] [Accepted: 02/24/2021] [Indexed: 05/09/2023]
Abstract
Air pollution attributed to substantial anthropogenic emissions and significant secondary formation processes have been reported frequently in China, especially in Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD). In order to investigate the aerosol evolution processes before, in, and after the novel coronavirus (COVID-19) lockdown period of 2020, ambient monitoring data of six air pollutants were analyzed from Jan 1 to Apr 11 in both 2020 and 2019. Our results showed that the six ambient pollutants concentrations were much lower during the COVID-19 lockdown due to a great reduction of anthropogenic emissions. BTH suffered from air pollution more seriously in comparison of YRD, suggesting the differences in the industrial structures of these two regions. The significant difference between the normalized ratios of CO and NO2 during COVID-19 lockdown, along with the increasing PM2.5, indicated the oxidation of NO2 to form nitrate and the dominant contribution of secondary processes on PM2.5. In addition, the most health risk factor was PM2.5 and health-risked based air quality index (HAQI) values during the COVID-19 pandemic in YRD in 2020 were all lower than those in 2019. Our findings suggest that the reduction of anthropogenic emissions is essential to mitigate PM2.5 pollution, while O3 control may be more complicated.
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Affiliation(s)
- Junfeng Wang
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Yali Lei
- Key Lab of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Yi Chen
- Yangzhou Environmental Monitoring Center, Yangzhou 225007, China.
| | - Yangzhou Wu
- Department of Atmospheric Sciences, School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
| | - Xinlei Ge
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
| | - Fuzhen Shen
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Jie Zhang
- Atmospheric Sciences Research Center, University at Albany, State University of New York, Albany, NY 12203, USA
| | - Jianhuai Ye
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Dongyang Nie
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
| | - Xiuyong Zhao
- State Environmental Protection Key Laboratory of Atmospheric Physical Modeling and Pollution Control, State Power Environmental Protection Research Institute, Nanjing 210000, China
| | - Mindong Chen
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
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14
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Zhao H, Chen K, Liu Z, Zhang Y, Shao T, Zhang H. Coordinated control of PM 2.5 and O 3 is urgently needed in China after implementation of the "Air pollution prevention and control action plan". CHEMOSPHERE 2021; 270:129441. [PMID: 33388503 DOI: 10.1016/j.chemosphere.2020.129441] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 12/08/2020] [Accepted: 12/22/2020] [Indexed: 05/13/2023]
Abstract
To improve air quality, China formulated the Air Pollution Prevention and Control Action Plan (APPCAP) in 2013. In the present study, the changes in the concentration of air pollutants after the implementation of APPCAP were investigated based on nationwide monitoring data. From the results, it is evident that the annual mean concentrations of PM2.5, PM10, SO2, and CO show a significant downward trend over 2015-2018, with decreasing rates of 3.4, 4.1, 3.8, and 70 μg m-3/year, respectively. However, no significant change was found in NO2 while maximum daily 8 h average O3 concentration (MDA8 O3) was increased by 3.4 μg m-3/year during the four years. Spatially, the highest decrease in PM2.5 was found in Beijing-Tianjin-Hebei (BTH), followed by central China and northeast China, while the Pearl River Delta (PRD), Yungui Plateau, and northwest China showed less decreases. MDA8 O3 had a higher increase in BTH, central China, Yangtze River Delta (YRD), and PRD. With the decrease in PM2.5 in recent years, cumulative population exposure to PM2.5 gradually decreased, whereas there was still more than 65% of the population exposing to annual PM2.5 higher than the standard of 35 μg m-3 in 2018. In contrast, the health effects of O3 gradually increased with 13.1%, 14.3%, 20.4%, and 21.7% of the population exposed to unhealthy O3 levels in summer from 2015 to 2018. O3 pollution is causing severe health risks with estimated nationwide mortality of 70,024 (95% CI: 55,510-84,501), 79,159 (95% CI: 62,750-95,525), 105,150 (95% CI: 83,378-126,852), and 104,404 (95% CI: 82,784-125,956) in the four years, respectively. This clearly shows that the target of air pollution control in China shifts and coordinated control of PM2.5 and O3 is urgently needed after the successful implementation of APPCAP.
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Affiliation(s)
- Hui Zhao
- Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China
| | - Kaiyu Chen
- Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, 70803, Louisiana, USA
| | - Zhen Liu
- Qinhuangdao Meteorological Bureau, Qinhuangdao, 066000, China
| | - Yuxin Zhang
- School of Science, Hong Kong University of Science and Technology, 999077, Hong Kong
| | - Tian Shao
- Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China
| | - Hongliang Zhang
- Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China.
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15
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Varbanov PS, Jia X, Lim JS. Process assessment, integration and optimisation: The path towards cleaner production. JOURNAL OF CLEANER PRODUCTION 2021; 281:124602. [PMID: 33071477 PMCID: PMC7550104 DOI: 10.1016/j.jclepro.2020.124602] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Revised: 10/05/2020] [Accepted: 10/07/2020] [Indexed: 05/07/2023]
Abstract
This contribution starts from the broad perspective of the global material cycles, analysing the main resource and pollution issues world-wide from the viewpoint of the disturbances to these cycles caused by human activities. The issues are analysed in the light of the currently developing COVID-19 pandemic with the resulting behavioural and business pattern changes. It has been revealed in the analysis of previous reviews that there is a need for a more comprehensive analysis of the resource and environmental impact contributions by industrial and urban processes, as well as product supply chains. The review discusses the recent key developments in the areas of Process Integration and Optimisation, the assessment and reduction of process environmental impacts, waste management and integration, green technologies. That is accompanied by a review of the papers in the current Virtual Special Issue of the Journal of Cleaner Production which is dedicated to the extended articles developed on the basis of the papers presented at the 22nd Conference on Process Integration for Energy Saving and Pollution Reduction. The follow-up analysis reveals significant advances in the efficiency and emission cleaning effects of key processes, as well as water/wastewater management and energy storage. The further analysis of the developments identifies several key areas for further research and development - including increases of the safety and robustness of supply networks for products and services, increase of the resources use efficiency of core production and resource conversion processes, as well as the emphasis on improved product and process design for minimising product wastage.
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Affiliation(s)
- Petar Sabev Varbanov
- Sustainable Process Integration Laboratory - SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology - VUT Brno, Technická 2896/2, 616 69, Brno, Czech Republic
| | - Xuexiu Jia
- Sustainable Process Integration Laboratory - SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology - VUT Brno, Technická 2896/2, 616 69, Brno, Czech Republic
| | - Jeng Shiun Lim
- Process Systems Engineering Centre (PROSPECT), Research Institute of Sustainable Environment, Universiti Teknologi Malaysia, 81310, UTM Johor Bahru, Johor, Malaysia
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Analysis of Spatio-Temporal Variation Characteristics of Main Air Pollutants in Shijiazhuang City. SUSTAINABILITY 2021. [DOI: 10.3390/su13020941] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Air pollution has become one of the important concerns of environmental pollution in the Beijing–Tianjin–Hebei region. As an important city in Beijing–Tianjin–Hebei, Shijiazhuang has long been ranked in the bottom ten in terms of air quality in the country. In order to effectively grasp the influencing factors and current distribution of air pollution in Shijiazhuang City, this paper collects data on the top air pollutants in Shijiazhuang from 2017 to 2019, analyzes the characteristics of time changes in the region, and uses the Kriging interpolation method to affect the air pollutants in this area. The spatial distribution characteristics are studied. The results show (1) From 2017 to 2019, the environmental quality of Shijiazhuang City showed a decreasing trend except for O3. (2) Seasonal changes show that NO2, PM2.5, and CO show as winter > autumn > spring > summer, PM10, SO2 show as winter > spring > autumn > summer, and O3 concentration changes as summer > spring > autumn > winter. (3) The daily change trends of NO2, SO2, PM10 and PM2.5 are similar, while the change trends of O3 and NO2 are opposite. (4) The correlations between air quality index (AQI) and concentrations suggest that PM10, PM2.5, and CO contribute the most to undesirable pollution levels in this area, while NO2, SO2, and O3 contribute less to undesirable pollution. We have concluded that the particulate pollution in Shijiazhuang City has been effectively controlled, thanks to the relevant measures introduced by the government, but the O3-based compound pollution is gradually increasing, so particulate pollution and O3 pollution need to be treated together. The research results of this article have important practical significance for urban or regional air environment monitoring and prevention.
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