1
|
Shi B, Liu G, Fu J, Zhai S, He L, Li R, Chen W. Traceability and policy suggestions for ozone pollution in heavy industrial city in Northeast China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:47630-47643. [PMID: 39002081 DOI: 10.1007/s11356-024-33992-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Accepted: 06/10/2024] [Indexed: 07/15/2024]
Abstract
In the heavy industrial city of Northeast China, there has been a significant decrease in particulate matter pollution while experiencing a sharp increase in ozone (O3) pollution. However, the main influencing factors and source contributions to O3 remain unclear. Taking the case of Siping as an example, this study analyzed the spatiotemporal characteristics, assessed local source contributions to O3, and revealed regional transmission effects using numeric simulation and statistical methods. Temporally, higher O3 concentrations were observed in summer and the afternoon, with hourly peaks up to 254 µg/m3. Spatially, O3 pollution was mainly contributed by background concentrations (34.52%), external transport (34.50%), and local emissions (30.98%) during the case study period (June 11-18, 2021). Among the local emission sources, biological emissions, the industrial sector, and the traffic sector accounted for 35.30%, 32.09%, and 23.58% of the O3 concentration, respectively. For regional atmospheric transmission, high O3 pollution was accompanied by wind from the southwest directions, and the trajectory of air mass transport suggests that eastern Mongolia, the Korean Peninsula, and its neighboring regions contribute to O3 pollution. Furthermore, sensitivity analysis showed that O3 pollution in Siping is a co-controlled region by anthropogenic volatile organic compounds (AVOCs) and NOX, which implies control in an optimal ratio of VOCs and NOX emissions. Thus, our results highlight the importance of joint prevention and control of O3 pollution in the region, optimization of biogenic landscape ecology, and control of VOCs and NOx in both the industrial and transport sectors.
Collapse
Affiliation(s)
- Bowen Shi
- Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Gang Liu
- Jilin Province Shi Ze Environmental Protection Technology Co., Ltd., Changchun, 130000, China
| | - Jing Fu
- Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
| | - Shuai Zhai
- Changchun Normal University, Changchun, 130032, China
| | - Luyan He
- Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
| | - Ruiqi Li
- Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Weiwei Chen
- Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China.
| |
Collapse
|
2
|
Lu CW, Fu J, Liu XF, Cui ZH, Chen WW, Guo L, Li XL, Ren Y, Shao F, Chen LN, Hao JL. Impacts of air pollution and meteorological conditions on dry eye disease among residents in a northeastern Chinese metropolis: a six-year crossover study in a cold region. LIGHT, SCIENCE & APPLICATIONS 2023; 12:186. [PMID: 37495595 PMCID: PMC10372063 DOI: 10.1038/s41377-023-01207-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 06/07/2023] [Accepted: 06/10/2023] [Indexed: 07/28/2023]
Abstract
The purpose of this study is to explore the associations among dry eye disease (DED), air pollution, and meteorological conditions in the cold region of a northeastern Chinese metropolis (i.e., Changchun). Data on ambient air pollutants and meteorological parameters as well as diagnosed DED outpatients during 2015-2021 were collected. The associations between DED and environmental factors were analysed at multiple time scales using various statistical methods (i.e., correlation, regression and machine learning). Among the 10,809 DED patients (21,617 eyes) studied, 64.60% were female and 35.40% were male. A higher frequency of DED was observed in March and April, followed by January, August and October. Individual and multiple factor models showed the positive importance of particles with aerodynamic diameters <10 μm (PM10), carbon monoxide (CO), and ozone (O3) among normal air pollutants and air pressure (AP), air temperature (AT) and wind speed (WS) among normal meteorological parameters. Air pollutants (PM10, nitrogen dioxide: NO2) and meteorological parameters (AT, AP) have combined impacts on DED occurrence. For the first time, we further explored the associations of detailed components of atmospheric particles and DED, suggesting potential emission sources, including spring dust from bare soil and roads and precursor pollutants of summer O3 formation from vehicles and industry in Northeast China. Our results revealed the quantitative associations among air pollutants, meteorological conditions and DED outpatients in cold regions, highlighting the importance of coordinated policies in air pollution control and climate change mitigation.
Collapse
Affiliation(s)
- Cheng-Wei Lu
- Opthalmology Department, The First Hospital of Jilin University, Changchun, 130021, China.
| | - Jing Fu
- Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
| | - Xiu-Fen Liu
- Opthalmology Department, The First Hospital of Jilin University, Changchun, 130021, China
| | - Zhi-Hua Cui
- Opthalmology Department, The First Hospital of Jilin University, Changchun, 130021, China
| | - Wei-Wei Chen
- Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China.
- College of New Energy and Environment, Jilin University, Changchun, 130021, China.
| | - Li Guo
- China College of Biological and Agricultural Engineering, Jilin University, Changchun, 130022, China
| | - Xiao-Lan Li
- Shenyang Institute of Atmospheric Environment, China Meteorological Administration, Shenyang, 110166, China
| | - Yu Ren
- Opthalmology Department, The First Hospital of Jilin University, Changchun, 130021, China
| | - Fei Shao
- Opthalmology Department, The First Hospital of Jilin University, Changchun, 130021, China
| | - Li-Na Chen
- Opthalmology Department, The First Hospital of Jilin University, Changchun, 130021, China
| | - Ji-Long Hao
- Opthalmology Department, The First Hospital of Jilin University, Changchun, 130021, China
| |
Collapse
|
3
|
Chen Z, Xie Y, Liu J, Shen L, Cheng X, Han H, Yang M, Shen Y, Zhao T, Hu J. Distinct seasonality in vertical variations of tropospheric ozone over coastal regions of southern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 874:162423. [PMID: 36858237 DOI: 10.1016/j.scitotenv.2023.162423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/18/2023] [Accepted: 02/19/2023] [Indexed: 06/18/2023]
Abstract
The surface ozone pollution is strongly coupled with ozone variations above the ground. Using sufficient airborne ozone profiles during 2012-2018, this study reveals the tropospheric ozone distributions over four cities located in coastal regions of southern China. The 7-year mean tropospheric ozone profiles in the four cities consistently show a double-maxima profile, with a local maximum at 1 km altitude and the other in the middle-to-upper troposphere. Seasonally, springtime ozone is larger than the annual mean throughout the troposphere, while ozone in summer is high in the middle-to-upper troposphere, leading to largest vertical variations among seasons. Ozone in the middle-to-upper troposphere is lower in autumn than in spring and summer. The winter ozone is characterized with a minimum in the lower troposphere, and low values in the middle-to-upper troposphere, leading to least vertical variations among seasons. We untangle the causes for these complicated vertical ozone variations using the GEOS-Chem model. The tropospheric ozone over southern China is partitioned into locally produced ozone, regionally transported native ozone, imported ozone from outside of China (foreign ozone) and natural stratospheric ozone. The results suggest that the springtime ozone abundance is due to the enhanced import of foreign and stratospheric ozone and the intensified regional transport processes of native ozone. In summer, local ozone production is enhanced and regional transport of ozone in the middle-to-upper troposphere is strengthened due to upward air motions, while such transport becomes weaker in autumn leaving low ozone in the middle-to-upper troposphere. In winter, the intensive westerly jets promote foreign and stratospheric ozone again in the middle-to-upper troposphere, but the local ozone production and regional transport are sharply reduced, resulting in low ozone near the surface. This study provides new insights into regional ozone profiles and reveals the significance of vertical ozone variations on surface ozone prevention strategy.
Collapse
Affiliation(s)
- Zhixiong Chen
- Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, China
| | - Yangcheng Xie
- Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, China
| | - Jane Liu
- Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, China; Department of Geography and Planning, University of Toronto, Toronto, Ontario, Canada.
| | - Lijuan Shen
- Key Laboratory for Aerosol-Cloud-Precipitation of the China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, China
| | - Xugeng Cheng
- Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, China
| | - Han Han
- Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, China
| | - Mengmiao Yang
- Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, China
| | - Yukun Shen
- Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, China
| | - Tianliang Zhao
- Key Laboratory for Aerosol-Cloud-Precipitation of the China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, China
| | - Jun Hu
- Fujian Provincial Key Laboratory of Environmental Engineering, Fujian Academy of Environmental Sciences, Fuzhou, China
| |
Collapse
|
4
|
Bhatti UA, Zeeshan Z, Nizamani MM, Bazai S, Yu Z, Yuan L. Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19. CHEMOSPHERE 2022; 288:132569. [PMID: 34655644 PMCID: PMC8514250 DOI: 10.1016/j.chemosphere.2021.132569] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 10/01/2021] [Accepted: 10/12/2021] [Indexed: 05/21/2023]
Abstract
Following the outbreak of the novel coronavirus in early 2020, to effectively prevent the spread of the disease, major cities across China suspended work and production. While the rest of the world struggles to control COVID-19, China has managed to control the pandemic rapidly and effectively with strong lockdown policies. This study investigates the change in air pollution (focusing on the air quality index (AQI), six ambient air pollutants nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), carbon monoxide (CO), particulate matter with aerodynamic diameters ≤10 μm (PM10) and ≤2.5 μm (PM2.5)) patterns for three periods: pre-COVID (from 1 January to May 30, 2019), active COVID (from 1 January to May 30, 2020) and post-COVID (from 1 January to May 30, 2021) in the Jiangsu province of China. Our findings reveal that the change in air pollution from pre-COVID to active COVID was greater than in previous years due to the government's lockdown policies. Post-COVID, air pollutant concentration is increasing. Mean change PM2.5 from pre-COVID to active COVID decreased by 18%; post-COVID it has only decreased by 2%. PM10 decreased by 19% from pre-COVID to active COVID, but post-COVID pollutant concentration has seen a 23% increase. Air pollutants show a positive correlation with COVID-19 cases among which PM2.5, PM10 and NO2 show a strong correlation during active COVID-19 cases. Metrological factors such as minimum temperature, average temperature and humidity show a positive correlation with COVID-19 cases while maximum temperature, wind speed and air pressure show no strong positive correlation. Although the COVID-19 pandemic had numerous negative effects on human health and the global economy, the reduction in air pollution and significant improvement in ambient air quality likely had substantial short-term health benefits; the government must implement policies to control post-COVID environmental issues.
Collapse
Affiliation(s)
- Uzair Aslam Bhatti
- School of Geography, Nanjing Normal University, Nanjing, 210023, China; Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, No. 1 Wenyuan Road, Nanjing, China
| | | | - Mir Muhammad Nizamani
- Key Laboratory of Tropical Biological Resources of Ministry of Education, School of Life and Pharmaceutical Sciences, Hainan University, Haikou, 570228, China
| | - Sibghatullah Bazai
- School of Natural and Computational Sciences, Massey University, Auckland, 0632, New Zealand; Department of Computer Engineering, BUITEMS, Quetta 87300, Pakistan
| | - Zhaoyuan Yu
- School of Geography, Nanjing Normal University, Nanjing, 210023, China; Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, No. 1 Wenyuan Road, Nanjing, China
| | - Linwang Yuan
- School of Geography, Nanjing Normal University, Nanjing, 210023, China; Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, No. 1 Wenyuan Road, Nanjing, China.
| |
Collapse
|
5
|
Temporal and Spatial Analysis of PM2.5 and O3 Pollution Characteristics and Transmission in Central Liaoning Urban Agglomeration from 2015 to 2020. SUSTAINABILITY 2022. [DOI: 10.3390/su14010511] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The central Liaoning urban agglomeration is an important heavy industry development base in China, and also an important part of the economy in northeast China. The atmospheric environmental problems caused by the development of heavy industry are particularly prominent. Trajectory clustering, potential source contribution (PSCF), and concentration weighted trajectory (CWT) analysis are used to discuss the temporal and spatial pollution characteristics of PM2.5 and ozone concentrations and reveal the regional atmospheric transmission pattern in central Liaoning urban agglomeration from 2015 to 2020. The results show that: (1) PM2.5 in the central Liaoning urban agglomeration showed a decreasing trend from 2015 to 2020. The concentration of PM2.5 is the lowest in 2018. Except for Benxi (34.7 µg/m3), the concentrations of PM2.5 in other cities do not meet the standard in 2020. The ozone concentration in Anshan, Liaoyang, and Shenyang reached the peaks in 2017, which are 68.76 µg/m3, 66.27 µg/m3, and 63.46 µg/m3 respectively. PM2.5 pollution is the highest in winter and the lowest in summer. The daily variation distribution of PM2.5 concentration showed a bimodal pattern. Ozone pollution is the most serious in summer, with the concentration of ozone reaching 131.14 µg/m3 in Shenyang. Fushun is affected by Shenyang intercity pollution, and the ozone concentration is high. (2) In terms of spatial distribution, the high values of PM2.5 are concentrated in monitoring stations in urban areas. On the contrary, the concentration of ozone in suburban stations is higher. The high concentration of ozone in the northeast of Anshan, Liaoyang, Shenyang to Tieling, and Fushun extended in a band distribution. (3) Through cluster analysis, it is found that PM2.5 and ozone in Shenyang are mainly affected by short-distance transport airflow. In winter, the weighted PSCF high-value area of PM2.5 presents as a potential contribution source zone of the northeast trend with wide coverage, in which the contribution value of the weighted CWT in the middle of Heilongjiang is the highest. The main potential source areas of ozone mass concentration in spring and summer are coastal cities and the Bohai Sea and the Yellow Sea. We conclude that the regional transmission of pollutants is an important factor of pollution, so we should pay attention to the supply of industrial sources and marine sources of marine pollution in the surrounding areas of cities, and strengthen the joint prevention and control of air pollution among regions. The research results of this article provide a useful reference for the central Liaoning urban agglomeration to improve air quality.
Collapse
|