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Zhang W, Liu D, Tian H, Pan N, Yang R, Tang W, Yang J, Lu F, Dayananda B, Mei H, Wang S, Shi H. Parsimonious estimation of hourly surface ozone concentration across China during 2015-2020. Sci Data 2024; 11:492. [PMID: 38744849 PMCID: PMC11094007 DOI: 10.1038/s41597-024-03302-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 04/24/2024] [Indexed: 05/16/2024] Open
Abstract
Surface ozone is an important air pollutant detrimental to human health and vegetation productivity, particularly in China. However, high resolution surface ozone concentration data is still lacking, largely hindering accurate assessment of associated environmental impacts. Here, we collected hourly ground ozone observations (over 6 million records), remote sensing products, meteorological data, and social-economic information, and applied recurrent neural networks to map hourly surface ozone data (HrSOD) at a 0.1° × 0.1° resolution across China during 2015-2020. The coefficient of determination (R2) values in sample-based, site-based, and by-year cross-validations were 0.72, 0.65 and 0.71, respectively, with the root mean square error (RMSE) values being 11.71 ppb (mean = 30.89 ppb), 12.81 ppb (mean = 30.96 ppb) and 11.14 ppb (mean = 31.26 ppb). Moreover, it exhibits high spatiotemporal consistency with ground-level observations at different time scales (diurnal, seasonal, annual), and at various spatial levels (individual sites and regional scales). Meanwhile, the HrSOD provides critical information for fine-resolution assessment of surface ozone impacts on environmental and human benefits.
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Affiliation(s)
- Wenxiu Zhang
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Di Liu
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hanqin Tian
- Schiller Institute of Integrated Science and Society, Boston College, Chestnut Hill, MA, 02467, USA
| | - Naiqin Pan
- Schiller Institute of Integrated Science and Society, Boston College, Chestnut Hill, MA, 02467, USA
- College of Forestry, Wildlife and Environment, Auburn University, Auburn, AL, 36849, USA
| | - Ruqi Yang
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Wenhan Tang
- Department of Atmospheric Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Jia Yang
- Natural Resource Ecology & Management, Oklahoma State University, Stillwater, OK, 74078, USA
| | - Fei Lu
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Buddhi Dayananda
- School of Agriculture and Food Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Han Mei
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong, 999077, China
| | - Siyuan Wang
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hao Shi
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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Zeydan Ö, Ülker U. Assessment of ground-level ozone pollution in Türkiye according to new WHO limits. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:549. [PMID: 38743179 DOI: 10.1007/s10661-024-12718-8] [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: 02/01/2024] [Accepted: 05/10/2024] [Indexed: 05/16/2024]
Abstract
Ground-level ozone is a secondary pollutant and is attributable to respiratory diseases and mortality. For this reason, the World Health Organization (WHO) implemented a new long-term (peak season) limit value for ozone. The previous studies related to ozone in Türkiye were spatially limited to certain locations. In this study, annual mean and peak season ozone concentrations, and limit exceedances were investigated for Türkiye for the year 2021. Moreover, ozone peak seasons were determined for the first time for 126 air quality monitoring stations. The annual mean ozone concentration was determined as 44.3 ± 19.3 µg/m3 whereas the peak season average ozone level was 68.4 ± 27.2 µg/m3. April-September period was the most frequently observed ozone peak season. Among all stations, Erzurum Palandöken was by far the most polluted station in terms of annual mean and limit exceedances of ozone. Ankara Siteler stations have the highest rank in peak season mean. 87 and 83 stations exceeded the short-term and long-term recommendations of WHO, respectively. Four hotspot regions were revealed in terms of peak season exceedance: Adana and surrounding provinces, the surroundings of Burdur and Isparta provinces, and the northeastern and northwestern parts of Türkiye. To protect public health, WHO recommendations for 8-h and peak season limits should be immediately implemented in Turkish regulations.
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Affiliation(s)
- Özgür Zeydan
- Department of Environmental Engineering, Zonguldak Bülent Ecevit University, 67100, Zonguldak, Türkiye.
| | - Uğur Ülker
- Department of Environmental Engineering, Zonguldak Bülent Ecevit University, 67100, Zonguldak, Türkiye
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Ye X, Zhang L, Wang X, Lu X, Jiang Z, Lu N, Li D, Xu J. Spatial and temporal variations of surface background ozone in China analyzed with the grid-stretching capability of GEOS-Chem High Performance. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 914:169909. [PMID: 38185162 DOI: 10.1016/j.scitotenv.2024.169909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 12/11/2023] [Accepted: 01/02/2024] [Indexed: 01/09/2024]
Abstract
Surface background ozone, defined as the ozone in the absence of domestic anthropogenic emissions, is important for developing emission reduction strategies. Here we apply the recently developed GEOS-Chem High Performance (GCHP) global atmospheric chemistry model with ∼0.5° stretched resolution over China to understand the sources of Chinese background ozone (CNB) in the metric of daily maximum 8 h average (MDA8) and to identify the drivers of its interannual variability (IAV) from 2015 to 2019. The GCHP ozone simulations over China are evaluated with an ensemble of surface and aircraft measurements. The five-year national-mean CNB ozone is estimated as 37.9 ppbv, with a spatially west-to-southeast downward gradient (55 to 25 ppbv) and a summer peak (42.5 ppbv). High background levels in western China are due to abundant transport from the free troposphere and adjacent foreign regions, while in eastern China, domestic formation from surface natural precursors is also important. We find greater importance of soil nitric oxides (NOx) than biogenic volatile organic compound emissions to CNB ozone in summer (6.4 vs. 3.9 ppbv), as ozone formation becomes increasingly NOx-sensitive when suppressing anthropogenic emissions. The percentage of daily CNB ozone to total surface ozone generally decreases with increasing daily total ozone, indicating an increased contribution of domestic anthropogenic emissions on polluted days. CNB ozone shows the largest IAV in summer, with standard deviations (seasonal means) of ∼5 ppbv over Qinghai-Tibet Plateau (QTP) and >3.5 ppbv in eastern China. CNB values in QTP are strongly correlated with horizontal circulation anomalies in the middle troposphere, while soil NOx emissions largely drive the IAV in the east. El Nino can inhibit CNB ozone formation in Southeast China by increased precipitation and lower temperature locally in spring, but enhance CNB in Southwest China through increased biomass burning emissions in Southeast Asia.
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Affiliation(s)
- Xingpei Ye
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Lin Zhang
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China.
| | - Xiaolin Wang
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Xiao Lu
- School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, Guangdong, China
| | - Zhongjing Jiang
- Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY 11973-5000, United States of America
| | - Ni Lu
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Danyang Li
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Jiayu Xu
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
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Guan Y, Shen Y, Wu T, Su W, Li D, Ni S, Zhang T, Han J, Duan E. Urban canopy height ozone distribution in a Chinese inland city: Effects of anthropogenic NO emissions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 905:167448. [PMID: 37777121 DOI: 10.1016/j.scitotenv.2023.167448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 09/17/2023] [Accepted: 09/27/2023] [Indexed: 10/02/2023]
Abstract
With the increase of urban building height, people pay more and more attention to the characteristics of pollutants in urban canopy height. This study combined the generalized additive model (GAM) and the observation-based model (OBM) to explore the vertical characteristics and drivers of ozone (O3) based on meteorology tower (200 m) data to quantify the effects of factors and photochemical reactions on O3 formation at different heights. The F values of GAM reflect the importance of each factor, indicating that NO (F is 33.99 in the peak season, 36.72 in the non-peak season) was the dominant driver of O3 and was more important in the lower layer (20-116 m). Temperature (F is 35.42) was the main contributor to O3 pollution in the peak season, especially for O3 in the upper layer (116-200 m). The net O3 production rate in the peak season was 1.47 times that in the non-peak season due to strong photochemical reactions and meteorological conditions. And the net O3 production rate decreased sharply with increasing height in the two seasons. Less net O3 production in the upper layer was accompanied by a higher O3 mixing ratio, which indicated that there was more background O3 in the upper layer. OBM model results showed that the reaction between hydroperoxyl radical (HO2) and NO was the primary contribution pathway, accounting for 54.00 % and 57.50 % in the peak and non-peak seasons, respectively. O3 formation was highly sensitive to VOCs, while NOx reduction could have positive or negative effects on O3 depending on the levels of hydroxyl radical (OH). The understanding of the formation mechanism of O3 and the influence of NO on O3 provides insights into the importance of anthropogenic activities at urban canopy heights in shaping the vertical structure of O3.
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Affiliation(s)
- Yanan Guan
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; National Joint Local Engineering Research Center for Volatile Organic Compounds and Odorous Pollution Control, Shijiazhuang 050018, China
| | - Ying Shen
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
| | - Tianyuan Wu
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
| | - Wenkang Su
- HeBei Provincial Academy of Ecological Environmental Science, Shijiazhuang 050018, China
| | - Dong Li
- Shijiazhuang City Environmental Prediction and Forecast Center, Shijiazhuang 050018, China
| | - Shuangying Ni
- HeBei Provincial Academy of Ecological Environmental Science, Shijiazhuang 050018, China
| | - Tao Zhang
- Shijiazhuang Environmental Monitoring Center, Shijiazhuang 050021, China
| | - Jing Han
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; National Joint Local Engineering Research Center for Volatile Organic Compounds and Odorous Pollution Control, Shijiazhuang 050018, China
| | - Erhong Duan
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; National Joint Local Engineering Research Center for Volatile Organic Compounds and Odorous Pollution Control, Shijiazhuang 050018, China.
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Gao X, Li J, Zhang X, Jiang W, Liao J, Yang L. Short-term ambient ozone exposure increases the risk of hospitalization with depression: a multi-city time-stratified case-crossover study. J Ment Health 2023:1-8. [PMID: 37950397 DOI: 10.1080/09638237.2023.2278102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 09/06/2023] [Indexed: 11/12/2023]
Abstract
BACKGROUND Depression, the most common mental illness worldwide, has been studied and air pollution has been found to increase the risk of depression hospitalization, but research results on ozone (O3) remain limited. In this context, we investigated the relationship between short-term O3 exposure and depression-related hospital admissions (HAs). METHODS The 10,459 records of HAs for depression from medical institutions across in 9 cities, China, were collected between 1 January 2017, and 31 December 2018. Air pollutants and meteorological data was obtained from provincial ecological environment monitoring stations in the study area. Conditional Poisson regression was employed to estimate the association between O3 and hospitalizations for depression, with data stratification by sex, age, weather, and economic level. RESULTS Short-term O3 exposure was positively associated with the number of depression-related hospitalizations (Relative risk: 1.04 [95% CI: 1.02, 1.05]). O3 had a significant effect on the risk of depression-related hospitalizations on warm days (P = 0.021, Relative risk: 1.05 [1.03, 1.08]). The high gross domestic product group was more likely to be affected by O3 exposure-associated depression-related hospitalizations (P = 0.005, Relative risk: 1.03 [1.01, 1.05]). CONCLUSIONS Short-term changes to O3 exposure may increase the risk of depression related hospitalizations, especially on warm days.
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Affiliation(s)
- Xi Gao
- HEOA Group, School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan Province, China
- Department of Operations Management, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jia Li
- HEOA Group, School of Management, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan Province, China
| | - Xueli Zhang
- HEOA Group, Sichuan Province Health Commission, Chengdu, Sichuan Province, China
| | - Wanyanhan Jiang
- HEOA Group, School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan Province, China
| | - Jiaqiang Liao
- HEOA Group, West China School of Public Health, Sichuan University, Chengdu, Sichuan Province, China
| | - Lian Yang
- HEOA Group, School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan Province, China
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Mu X, Wang S, Jiang P, Wu Y. Estimation of surface ozone concentration over Jiangsu province using a high-performance deep learning model. J Environ Sci (China) 2023; 132:122-133. [PMID: 37336603 DOI: 10.1016/j.jes.2022.09.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2021] [Revised: 09/22/2022] [Accepted: 09/26/2022] [Indexed: 06/21/2023]
Abstract
Recently, the global background concentration of ozone (O3) has demonstrated a rising trend. Among various methods, groun-based monitoring of O3 concentrations is highly reliable for research analysis. To obtain information on the spatial characteristics of O3 concentrations, it is necessary that the ground monitoring sites be constructed in sufficient density. In recent years, many researchers have used machine learning models to estimate surface O3 concentrations, which cannot fully provide the spatial and temporal information contained in a sample dataset. To solve this problem, the current study utilized a deep learning model called the Residual connection Convolutional Long Short-Term Memory network (R-ConvLSTM) to estimate daily maximum 8-hr average (MDA8) O3 over Jiangsu province, China during 2020. In this research, the R-ConvLSTM model not only provides the spatiotemporal information of MDA8 O3, but also involves residual connection to avoid the problem of gradient explosion and gradient disappearance with the deepening of network layers. We utilized the TROPOMI total O3 column retrieved from Sentinel-5 Precursor, ERA5 reanalysis meteorological data, and other supplementary data to build a pre-trained dataset. The R-ConvLSTM model achieved an overall sample-base cross-validation (CV) R2 of 0.955 with root mean square error (RMSE) of 9.372 µg/m3. Model estimation also showed a city-based CV R2 of 0.896 with RMSE of 14.029 µg/m3, the highest MDA8 O3 in spring being 122.60 ± 31.60 µg/m3 and the lowest in winter being 69.93 ± 18.48 µg/m3.
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Affiliation(s)
- Xi Mu
- School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China
| | - Sichen Wang
- School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China
| | - Peng Jiang
- School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China; Information Materials and Intelligent Sensing Laboratory of Anhui Province, Hefei 230601, China; Anhui Province Engineering Laboratory for Mine Ecological Remediation, Anhui University, Hefei 230601, China.
| | - Yanlan Wu
- School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China; Information Materials and Intelligent Sensing Laboratory of Anhui Province, Hefei 230601, China
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Song X, Hao Y. An assessment of O 3-related health risks and economic losses in typical regions of China. Front Public Health 2023; 11:1194340. [PMID: 37732098 PMCID: PMC10508848 DOI: 10.3389/fpubh.2023.1194340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 08/23/2023] [Indexed: 09/22/2023] Open
Abstract
Introduction As one of the key areas for air pollution prevention and control in China, the Fenwei Plain is experiencing serious near-surface O3 pollution, which is a key issue that needs to be solved urgently. Methods Based on pollutant concentration monitoring data and meteorological and health data over the same period, this study analyzed the temporal and spatial characteristics, the relationships with meteorological factors of O3 pollution, and the health effects and economic losses caused by exposure to O3 pollution using environmental health risk and environmental value assessment methods in 11 cities on the Fenwei Plain in China from 2014 to 2020. Results The results showed that O3 pollution has become increasingly serious on the Fenwei Plain in recent years. The annual average concentration of O3_8h_max showed an overall upwards trend, with an increase of 32.39% in 2020 compared to 2014. The mean concentrations observed in summer were the highest, followed by spring and autumn, and the lowest was in winter. The O3 concentration had a significant positive correlation with air temperature and sunshine hours. The evaluation results of the impact of air pollution on population health showed that the number of premature deaths caused by O3 pollution fluctuated and increased during 2014-2020. In 2020, the numbers of total, cardiovascular and respiratory deaths attributable to O3 pollution on the Fenwei Plain were 6,867 (95% CI: 3,739-9,965), 3,652 (95% CI: 1,363-5,905), and 1,257 (95% CI: 747-2,365), respectively, and the total number of premature deaths related to O3 exposure increased by 48.05% compared with 2014. The health and economic losses attributed to O3 pollution on the Fenwei Plain during the study period were 44.22 (95% CI: 22.17-69.18), 47.16 (95% CI: 23.64-73.77), 68.28 (95% CI: 34.27-106.31), 114.44 (95% CI: 57.42-177.76), 110.85 (95% CI: 55.45-172.52), 116.41 (95% CI: 58.24-180.74), and 116.81 (95% CI: 58.00-180.88) billion yuan, respectively. In Linfen City, the increasing rate of the number of premature deaths reached 283.39% because the O3 concentration increased greatly. Discussion Due to high O3 concentrations and obvious population growth in Xi'an, the problems of premature death and health and economic losses attributed to O3 concentrations exceeding the standard value are prominent.
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Affiliation(s)
- Xiaowei Song
- College of Resources and Environment, Shanxi University of Finance and Economics, Taiyuan, China
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Jiang Y, Ding D, Dong Z, Liu S, Chang X, Zheng H, Xing J, Wang S. Extreme Emission Reduction Requirements for China to Achieve World Health Organization Global Air Quality Guidelines. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:4424-4433. [PMID: 36898019 DOI: 10.1021/acs.est.2c09164] [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] [Indexed: 06/18/2023]
Abstract
A big gap exists between current air quality in China and the World Health Organization (WHO) global air quality guidelines (AQG) released in 2021. Previous studies on air pollution control have focused on emission reduction demand in China but ignored the influence of transboundary pollution, which has been proven to have a significant impact on air quality in China. Here, we develop an emission-concentration response surface model coupled with transboundary pollution to quantify the emission reduction demand for China to achieve WHO AQG. China cannot achieve WHO AQG by its own emission reduction for high transboundary pollution of both PM2.5 and O3. Reducing transboundary pollution will loosen the reduction demand for NH3 and VOCs emissions in China. However, to meet 10 μg·m-3 for PM2.5 and 60 μg·m-3 for peak season O3, China still needs to reduce its emissions of SO2, NOx, NH3, VOCs, and primary PM2.5 by more than 95, 95, 76, 62, and 96% respectively, on the basis of 2015. We highlight that both extreme emission reduction in China and great efforts in addressing transboundary air pollution are crucial to reach WHO AQG.
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Affiliation(s)
- Yueqi Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Dian Ding
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Zhaoxin Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shuchang Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- Institute for Atmospheric and Climate Science, ETH Zurich, CH-8092 Zurich, Switzerland
| | - Xing Chang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- Transport Planning and Research Institute, Ministry of Transport, Laboratory of Transport Pollution Control and Monitoring Technology, Beijing 100028, China
| | - Haotian Zheng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jia Xing
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
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Yao Y, Wang W, Ma K, Tan H, Zhang Y, Fang F, He C. Transmission paths and source areas of near-surface ozone pollution in the Yangtze River delta region, China from 2015 to 2021. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 330:117105. [PMID: 36610191 DOI: 10.1016/j.jenvman.2022.117105] [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: 10/19/2022] [Revised: 11/29/2022] [Accepted: 12/19/2022] [Indexed: 06/17/2023]
Abstract
Near-ground ozone in the Yangtze River Delta (YRD) region has become one of the main air pollutants that threaten the health of residents. However, to date, the transport behavior and source areas of ozone in the YRD region have not been systematically analyzed. In this study, by combining the ozone observational record with a HYSPLIT (hybrid single-particle Lagrangian integrated trajectory) model, we tried to reveal the spatiotemporal regularity of the airflow transport trajectory of ozone. Spatially, high ozone concentrations mainly clustered in industrial cities and resource-based cities. Temporally, the center of the ozone pollution shifted westward of Nanjing from 2015 to 2021. With the passage of time, the influence of meteorological elements on the ozone concentration in the YRD region gradually weakened. Marine atmosphere had the most significant impact on the transmission path of ozone in Shanghai, of which the trajectory frequency in 2021 accounted for 64.21% of the total frequency. The transmission trajectory of ozone in summer was different from that in other seasons, and its transmission trajectory was mainly composed of four medium-distance transmission paths: North China-Bohai Sea, East China Sea-West Pacific Ocean, Philippine Sea, and South China Sea-South China. The contribution source areas mainly shifted to the southeast, and the emission of pollutants from the Shandong Peninsula, the Korean Peninsula-Japan, and the Philippine Sea-Taiwan area increased the impact of ozone pollution in the Shanghai area from 2019 to 2021. This study identified the regional transport path of ozone in the YRD region and provided a scientific reference for the joint prevention and control of ozone pollution in this area.
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Affiliation(s)
- Youru Yao
- Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, Anhui Province, School of Geography and Tourism, Anhui Normal University, Wuhu, 241002, China.
| | - Wei Wang
- Nanjing Institute of Environmental Sciences, Ministry of Ecological Environment, Nanjing, 210042, China.
| | - Kang Ma
- Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, Anhui Province, School of Geography and Tourism, Anhui Normal University, Wuhu, 241002, China.
| | - Huarong Tan
- Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, Anhui Province, School of Geography and Tourism, Anhui Normal University, Wuhu, 241002, China.
| | - Yong Zhang
- Department of Geological Sciences, University of Alabama, Tuscaloosa, AL, 35487, USA.
| | - Fengman Fang
- Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, Anhui Province, School of Geography and Tourism, Anhui Normal University, Wuhu, 241002, China.
| | - Cheng He
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, 85764, Germany.
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Yang L, Hong S, Mu H, Zhou J, He C, Wu Q, Gong X. Ozone exposure and health risks of different age structures in major urban agglomerations in People's Republic of China from 2013 to 2018. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:42152-42164. [PMID: 36645592 DOI: 10.1007/s11356-022-24809-5] [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: 06/09/2022] [Accepted: 12/13/2022] [Indexed: 06/17/2023]
Abstract
High concentration of surface ozone (O3) will cause health risks to people. In order to analyze the spatiotemporal characteristics of O3 and assess O3 exposure and health risks for different age groups in China, we applied multiple methods including standard deviation ellipse, spatial autocorrelation, and exposure-response functions. Results show that O3 concentrations increased in 64.5% of areas in China from 2013 to 2018. The central plain urban agglomeration (CPU), Beijing-Tianjin-Hebei (BTH), and Yangtze River Delta (YRD) witnessed the greatest incremental rates of O3 by 16.7%, 14.3%, and 13.1%. Spatially, the trend of O3 shows a significant positive autocorrelation, and high trend values primarily in central and east China. The proportion of the total population exposed to high O3 (above 160 μg/m3) increased annually. Compared to 2013, the proportion of the young, adult, and old populations exposed to high O3 increased to different extents in 2018 by 26.8%, 29.6%, and 27.2%, respectively. The extent of population exposure risk areas in China expanded in size, particularly in north and east China. The total premature respiratory mortalities attributable to long-term O3 exposure in six urban agglomerations were about 177,000 in 2018 which has increased by 16.4% compared to that in 2013. Among different age groups, old people are more vulnerable to O3 pollution, so we need to strengthen their relevant health protection of them.
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Affiliation(s)
- Lu Yang
- School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, Hubei, China
| | - Song Hong
- School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, Hubei, China.
| | - Hang Mu
- School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, Hubei, China
| | - Jingwei Zhou
- Wageningen Institute for Environment and Climate Research, Wageningen University & Research, 6700 HB, Wageningen, Gelderland, Netherlands
| | - Chao He
- College of Resources and Environment, Yangtze University, Wuhan, 430100, China
| | - Qian Wu
- School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, Hubei, China
| | - Xi Gong
- School of Low Carbon Economics, Hubei University of Economics, Wuhan, 430205, China
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11
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Wang T, Wang F, Song H, Zhou S, Ru X, Zhang H. Maize yield reduction and economic losses caused by ground-level ozone pollution with exposure- and flux-response relationships in the North China Plain. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 324:116379. [PMID: 36202037 DOI: 10.1016/j.jenvman.2022.116379] [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: 07/14/2022] [Revised: 09/05/2022] [Accepted: 09/25/2022] [Indexed: 06/16/2023]
Abstract
Ground-level ozone (O3) has negative effects on agricultural crops. Maize is an important grain crop in China. The North China Plain (NCP) serves as the major crops' production area of China and experiences severe ozone pollution. Using the ground-level ozone simulated by an atmospheric chemistry transport model (WRF-Chem), we quantified the yield reduction and economic losses of maize during 2015-2018 over NCP based on exposure-response AOT40 (accumulation of hourly O3 concentration exceed 40 ppb) and flux-response POD6 (phytotoxic dose of ozone over 6 nmol m-2 s-1). Results showed that the ozone concentration, AOT40, and POD6 clearly increased from 2015 to 2018 in growing season of maize over NCP. The four-year annual mean ozone concentration, AOT40, and POD6 were 0.055 ppm, 18.02 ppm h, and 5.02 mmol m-2, respectively. At county level, the relative loss of maize yield (MRYL) based on AOT40 and POD6 had clearly spatio-temporal differences in NCP. The average MRYLs of AOT40 and of POD6 from 2015 to 2018 were 10.4% and 21.4%, respectively, and these reductions were associated with 2399 million and 5637 million US dollars, respectively. This study suggests that surface ozone increased the yield losses of maize, and indicates that further reductions in ozone concentrations can enhance the food security in China.
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Affiliation(s)
- Tuanhui Wang
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, Henan, 475004, China; Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, 210023, China
| | - Feng Wang
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, Henan, 475004, China; Institute of Urban Big Data, College of Geography and Environmental Science, Henan University, Kaifeng, Henan, 475004, China
| | - Hongquan Song
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, Henan, 475004, China; Henan Key Laboratory of Integrated Air Pollution Control and Ecological Security, Henan University, Kaifeng, Henan, 475004, China.
| | - Shenghui Zhou
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, Henan, 475004, China
| | - Xutong Ru
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, Henan, 475004, China; Institute of Urban Big Data, College of Geography and Environmental Science, Henan University, Kaifeng, Henan, 475004, China
| | - Haopeng Zhang
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, Henan, 475004, China; Institute of Urban Big Data, College of Geography and Environmental Science, Henan University, Kaifeng, Henan, 475004, China
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12
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Study on Transpiration Water Consumption and Photosynthetic Characteristics of Landscape Tree Species under Ozone Stress. ATMOSPHERE 2022. [DOI: 10.3390/atmos13071139] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Using Pinus bungeana, Platycladus orientalis, Koelreuteria paniculata and Ginkgo biloba as research objects, three open-top chambers with different ozone-concentration gradients were set up (NF, NF40 and NF80) based on trunk sap-flow technology to study the difference in ozone absorption by trees under different ozone concentrations. The results showed that the monthly and diurnal variations of sap-flow density of different tree species decreased with the increase in ozone concentration, and the increase in ozone concentration reduced the water consumption, ozone uptake rate (FO3), net photosynthetic rate (Pn) and water-use efficiency (WUE) of different tree species. The sap-flow density, water consumption, FO3 and WUE of Koelreuteria paniculata and Ginkgo biloba were higher than those of Pinus bungeana and Platycladus orientalis under different ozone concentrations. The sap-flow density, water consumption, FO3 and WUE of Koelreuteria paniculata and Ginkgo biloba decreased significantly at the ozone concentrations of NF40 and NF80; compared with the ozone concentration of NF, the sap flow density of Koelreuteria paniculata and Ginkgo biloba decreased by 1.04 and 1.03 times as much as that of Pinus bungeana and Platycladus orientalis, respectively; the water consumption of Koelreuteria paniculata and Ginkgo biloba decreased by 1.82 and 1.56 times that of Pinus bungeana and Platycladus orientalis, respectively; the decline rate of FO3 in Koelreuteria paniculata and Ginkgo biloba was 1.30 and 1.04 times that of Pinus bungeana and Platycladus orientalis, respectively; and the decline rate of WUE of Koelreuteria paniculata and Ginkgo biloba was 1.52 and 1.64 times that of Pinus bungeana and Platycladus orientalis, respectively. Pinus bungeana and Platycladus orientalis have stronger tolerance to ozone, while Koelreuteria paniculata and Ginkgo biloba were weak. A variety of conifers can be planted in areas with serious ozone pollution.
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Lidar- and UAV-Based Vertical Observation of Spring Ozone and Particulate Matter in Nanjing, China. REMOTE SENSING 2022. [DOI: 10.3390/rs14133051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The rapid urbanization in China is accompanied by increasingly serious air pollution. Particulate matter and ozone are the main air pollutants, and the study of their vertical distribution and correlation plays an important role in the synergistic air pollution control. In this study, we performed Lidar- and UAV-based observations in spring in Nanjing, China. The average concentrations of surface ozone and PM2.5 during the observation period are 87.78 µg m−3 and 43.48 µg m−3, respectively. Vertically, ozone reaches a maximum in the upper boundary layer, while the aerosol extinction coefficient decreases with height. Generally, ozone and aerosol are negatively correlated below 650 m. The correlation coefficient increases with altitude and reaches a maximum of 0.379 at 1875 m. Within the boundary layer, ozone and aerosols are negatively correlated on days with particulate pollution (PM2.5 > 35 μg m−3), while on clean days they are positively correlated. Above the boundary layer, the correlation coefficient is usually positive, regardless of the presence of particulate pollution. The UAV study compensates for Lidar detections below 500 m. We found that ozone concentration is higher in the upper layers than in the near-surface layers, and that ozone depletion is faster in the near-surface layers after sunset.
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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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15
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Wu H, Lu K, Fu J. A Time-Series Study for Effects of Ozone on Respiratory Mortality and Cardiovascular Mortality in Nanchang, Jiangxi Province, China. Front Public Health 2022; 10:864537. [PMID: 35558528 PMCID: PMC9087186 DOI: 10.3389/fpubh.2022.864537] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 03/31/2022] [Indexed: 12/02/2022] Open
Abstract
Objective Most evidence comes from studies show that ambient ozone(O3) pollution has become a big issue in China. Few studies have investigated the impact of ozone spatiotemporal patterns on respiratory mortality and cardiovascular mortality in Nanchang city. Thus, this study aimed to explore the health effect of ozone exposure on respiratory mortality and cardiovascular mortality in Nanchang, Jiangxi Province. Methods Using the daily mortality data, atmospheric routine monitoring data and meteorological data in Nanchang from 2014 to 2020, we performed a generalized additive model (GAM) based on the poisson distribution in which time-series analysis to calculate the risk correlation between respiratory mortality and cardiovascular mortality and ozone exposure level (8h average ozone concentration, O3-8h). Besides, analyses were also stratified by season, age and sex. Results In the single-pollutant model, for every 10 μg/m3 increase in ozone, respiratory mortality increased 1.04% with 95% confidence interval (CI) between 0.04 and 1.68%, and cardiovascular mortality increased 1.26% (95%CI: 0.68 ~ 1.83%). In the multi-day moving average lag model, the mortality of respiratory diseases and cardiovascular diseases reached a relative risk peak on the cumulative lag5 (1.77%,95%CI: 0.99 ~ 2.57%) and the cumulative lag3 (1.68%,95%CI: 0.93 ~ 2.45%), respectively. The differences were statistically significant (P < 0.05). Results of the stratified analyses showed the effect value of respiratory mortality in people aged ≥65 years was higher than aged <65 years, whereas the greatest effect of cardiovascular mortality in people aged <65 years than aged ≥65 years. Ozone had a more profound impact on females than males in respiratory diseases and cardiovascular diseases. In winter and spring, ozone had a obvious impact on respiratory mortality, and effects of ozone pollution on cardiovascular mortality were stronger in summer and winter. There was a statistically significant difference of respiratory mortality in winter and spring and of cardiovascular mortality in summer and winter (P < 0.05). Conclusions In the long run, the more extreme the pollution of ozone exposure, the higher the health risk of residents' respiratory mortality and cardiovascular mortality. Therefore, the government should play an important role in the prevention and control ways of decreasing and eliminating the ozone pollution to protect the resident's health. The findings provide valuable data for further scientific research and improving environmental policies in Nanchang city.
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Affiliation(s)
- Hao Wu
- Jiangxi Provincial Center for Disease Control and Prevention, Jiangxi, China.,School of Public Health, Nanchang University, Jiangxi, China
| | - Keke Lu
- Jiangxi Provincial Center for Disease Control and Prevention, Jiangxi, China.,School of Public Health, Nanchang University, Jiangxi, China
| | - Junjie Fu
- Jiangxi Provincial Center for Disease Control and Prevention, Jiangxi, China
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Xu D, Yuan Z, Wang M, Zhao K, Liu X, Duan Y, Fu Q, Wang Q, Jing S, Wang H, Zhao X. Multi-factor reconciliation of discrepancies in ozone-precursor sensitivity retrieved from observation- and emission-based models. ENVIRONMENT INTERNATIONAL 2022; 158:106952. [PMID: 34717174 DOI: 10.1016/j.envint.2021.106952] [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: 07/30/2021] [Revised: 10/12/2021] [Accepted: 10/21/2021] [Indexed: 05/22/2023]
Abstract
Ground-level O3 pollution has been continuously worsening in China despite gradual improvement in other major pollutant levels. Understanding the sensitivity of O3 production to its precursors (OPS) is a prerequisite for formulating effective O3 control measures, but this has been hampered by significant discrepancies in OPS produced by traditional identification approaches using observation-based models (OBM) and emission-based models (EBM). In this study, by applying OBM and EBM in parallel within a month having significant O3 pollution in Shanghai, China, we demonstrated that a lack of carbonyl input, overestimation in NO2 monitoring data, and differences in simulation period and emission reduction area were the core factors leading to OPS discrepancies, and that a reliable OPS cannot be obtained unless these factors are reconciled. By collectively addressing these factors, the number of days with a consistent OPS from both models increased from 6-7 to 20-21 in a month, and the R value defined to quantify the discrepancy decreased by ∼55%. The contributions of these factors to OPS discrepancy differed greatly in urban and suburban settings, mainly caused by differences in pollutant emission and transport characteristics. Overall, OPS identified solely by OBM or EBM is associated with great uncertainty, while reliable OPS estimation can be achieved by a collective application of OBM and EBM with consensus on the above factors. The method demonstrated here could be applied to other photo-chemically active regions worldwide as part of efforts to address ozone pollution.
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Affiliation(s)
- Danni Xu
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Zibing Yuan
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China.
| | - Ming Wang
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.
| | - Kaihui Zhao
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Xuehui Liu
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Yusen Duan
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Qingyan Fu
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Qian Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Shengao Jing
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Hongli Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Xin Zhao
- Nanjing Intelligent Environmental Science and Technology Co., Ltd., Nanjing 211800, China
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Wang M, Li G, Feng Z, Liu Y, Xu Y, Uscola M. Uptake of nitrogen forms by diploid and triploid white poplar depends on seasonal carbon use strategy and elevated summer ozone. JOURNAL OF EXPERIMENTAL BOTANY 2021; 72:7180-7190. [PMID: 34228101 DOI: 10.1093/jxb/erab317] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 07/03/2021] [Indexed: 06/13/2023]
Abstract
The ability of plants to acquire soil nitrogen (N) sources is plastic in response to abiotic and biotic factors. However, information about how plant preferences among N forms changes in response to internal plant N demand through growth phases, or to environmental stress such as ozone (O3), is scarce. Diploid and triploid Chinese white poplar were used to investigate N form preferences at two key developmental periods (spring, summer) and in response to summer O3 (ambient, 60 ppb above ambient). We used stable isotopes to quantify NH4+, NO3- and glycine N-uptake rates. Carbon acquisition was recorded simultaneously. Both ploidy levels differed in growth, N form preferences, and N and C use strategies. Diploid white poplars grew faster in spring but slower in summer compared with triploids. Diploid white poplars also showed plasticity among N form preferences through the season, with no preferences in spring, and NO3- preferred in summer, while triploids showed an overall preference for NO3-. Carbon acquisition and NO3- uptake were inhibited in both ploidy levels of poplar at elevated O3, which also reduced diploid total N uptake. However, triploid white poplars alleviated N uptake reduction, switching to similar preferences among N forms. We conclude that N form preferences by white poplar are driven by internal C and N use in response to nutrient demands, and external factors such as O3.
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Affiliation(s)
- Miaomiao Wang
- Research Center of Deciduous Oaks, Beijing Forestry University, Beijing 100083, China
- National Innovation Alliance of Valuable Deciduous Tree Industry, Beijing Forestry University, Beijing 100083, China
- Key Laboratory for Silviculture and Conservation, Ministry of Education, Beijing Forestry University, Beijing 100083, China
- Beijing Laboratory of Urban and Rural Ecological Environment, Beijing Forestry University, Beijing 100083, China
| | - Guolei Li
- Research Center of Deciduous Oaks, Beijing Forestry University, Beijing 100083, China
- National Innovation Alliance of Valuable Deciduous Tree Industry, Beijing Forestry University, Beijing 100083, China
- Key Laboratory for Silviculture and Conservation, Ministry of Education, Beijing Forestry University, Beijing 100083, China
- Beijing Laboratory of Urban and Rural Ecological Environment, Beijing Forestry University, Beijing 100083, China
| | - Zhaozhong Feng
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
- Key Laboratory of Agrometeorology of Jiangsu Province, Institute of Ecology, School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Yong Liu
- Research Center of Deciduous Oaks, Beijing Forestry University, Beijing 100083, China
- National Innovation Alliance of Valuable Deciduous Tree Industry, Beijing Forestry University, Beijing 100083, China
- Key Laboratory for Silviculture and Conservation, Ministry of Education, Beijing Forestry University, Beijing 100083, China
- Beijing Laboratory of Urban and Rural Ecological Environment, Beijing Forestry University, Beijing 100083, China
| | - Yansen Xu
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Mercedes Uscola
- Forest Ecology and Restoration Group, Departamento de Ciencias de la Vida, U.D. Ecología, Universidad de Alcalá, Apdo. 20, E-28805, Alcalá de Henares, Madrid, Spain
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Relationships between Long-Term Ozone Exposure and Allergic Rhinitis and Bronchitic Symptoms in Chinese Children. TOXICS 2021; 9:toxics9090221. [PMID: 34564372 PMCID: PMC8472948 DOI: 10.3390/toxics9090221] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 09/07/2021] [Accepted: 09/08/2021] [Indexed: 12/24/2022]
Abstract
Numerous studies have demonstrated that exposure to ambient ozone (O3) could have adverse effects on children's respiratory health. However, previous studies mainly focused on asthma and wheezing. Evidence for allergic rhinitis and bronchitic symptoms (e.g., persistent cough and phlegm) associated with O3 is limited, and results from existing studies are inconsistent. This study included a total of 59,754 children from the seven northeastern cities study (SNEC), who were aged 2 to 17 years and from 94 kindergarten, elementary and middle schools. Information on doctor-diagnosed allergic rhinitis (AR), persistent cough, and persistent phlegm was collected during 2012-2013 using a standardized questionnaire developed by the American Thoracic Society (ATS). Information for potential confounders was also collected via questionnaire. Individuals' exposure to ambient ozone (O3) during the four years before the investigation was estimated using a satellite-based random forest model. A higher level of O3 was significantly associated with increased risk of AR and bronchitic symptoms. After controlling for potential confounders, the OR (95% CI) were 1.13 (1.07-1.18), 1.10 (1.06-1.16), and 1.12 (1.05-1.20) for AR, persistent cough, and persistent phlegm, respectively, associated with each interquartile range (IQR) rise in O3 concentration. Interaction analyses showed stronger adverse effects of O3 on AR in children aged 7-17 years than those aged 2-6 years, while the adverse association of O3 with cough was more prominent in females and children aged 7-12 years than in males and children aged 2-6 and 13-17 years. This study showed that long-term exposure to ambient O3 was significantly associated with higher risk of AR and bronchitic symptoms in children, and the association varies across age and gender. Our findings contribute additional evidence for the importance of controlling O3 pollution and protecting children from O3 exposure.
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