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Hao T, Liu B, Cai Z, Lu M, Han S. Cause of nocturnal surface ozone enhancement in the North China Plain. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 954:176583. [PMID: 39357766 DOI: 10.1016/j.scitotenv.2024.176583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 09/22/2024] [Accepted: 09/26/2024] [Indexed: 10/04/2024]
Abstract
The North China Plain (NCP), known for its dense population, extensive urbanization, and developed industry and agriculture, faces one of the foremost ozone (O3) pollution issues nationwide and even globally. Currently, most studies focus on daytime peak O3 levels, with insufficient understanding of the increase in nighttime O3 concentrations. Based on data from 204 national atmospheric composition monitoring sites in the NCP from 2015 to 2023, we investigated the characteristics of nocturnal surface O3 enhancement (NSOE) events and explored potential formation mechanisms. The mean annual frequencies of single-site and regional NSOE event in the NCP between 2015 and 2023 are 42 % and 21 %, respectively. The daytime peak O3 concentrations before and after NSOE events exceeded those during the corresponding periods of non-NSOE events by 84 ± 19 and 32 ± 15 μg/m3, respectively. The overall effect of the NSOE events was to decelerate the rate of decline in nighttime O3 concentrations and resulted in a reduction of NO2 and CO concentrations from 22:00 onwards. Low level jet (LLJ) and vertical mixing were the main factors affecting NSOE events in the NCP. The proportion of NSOE events affected by LLJ in four representative cities ranged from 57.6 % to 79.5 %. Furthermore, the high concentration of O3 in the residual layer before the NSOE event and the reduction of atmospheric stability during the NSOE event favored downward mixing of upper layer O3. The primary weather systems influencing the four most severe regional NSOE events were LLJ, typhoon, and cold fronts. The first two events were dominated by vertical mixing of O3, while the latter two events were mainly affected by horizontal transport. Our findings provide the first overview of NSOE events in the NCP from characteristics to mechanisms, emphasizing the necessity for future detailed studies based on nocturnal vertical O3 observations.
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Affiliation(s)
- Tianyi Hao
- Tianjin Environmental Meteorological Center, Tianjin 300074, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300074, China; Tianjin Interdisciplinary Innovation Centre for Health and Meteorology, Tianjin 300074, China
| | - Bo Liu
- Tianjin Meteorological Observatory, Tianjin 300074, China
| | - Ziying Cai
- Tianjin Environmental Meteorological Center, Tianjin 300074, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300074, China; Tianjin Interdisciplinary Innovation Centre for Health and Meteorology, Tianjin 300074, China
| | - Miaomiao Lu
- Tianjin Environmental Meteorological Center, Tianjin 300074, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300074, China; Tianjin Interdisciplinary Innovation Centre for Health and Meteorology, Tianjin 300074, China
| | - Suqin Han
- Tianjin Environmental Meteorological Center, Tianjin 300074, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300074, China; Tianjin Interdisciplinary Innovation Centre for Health and Meteorology, Tianjin 300074, China.
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Yang X, Li Y, Ma X, Tan Z, Lu K, Zhang Y. Unclassical Radical Generation Mechanisms in the Troposphere: A Review. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:15888-15909. [PMID: 39206567 DOI: 10.1021/acs.est.4c00742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Hydroxyl (OH) and hydroperoxyl (HO2) radicals, collectively known as HOx radicals, are crucial in removing primary pollutants, controlling atmospheric oxidation capacity, and regulating global air quality and climate. An imbalance between radical observations and simulations has been identified based on radical closure experiments, a valuable tool for accessing the state-of-the-art chemical mechanisms, demonstrating a deviation between the existing and actual tropospheric mechanisms. In the past decades, researchers have attempted to explain this deviation and proposed numerous radical generation mechanisms. However, these newly proposed unclassical radical generation mechanisms have not been systematically reviewed, and previous radical-related reviews dominantly focus on radical measurement instruments and radical observations in extensive field campaigns. Herein, we overview the unclassical generation mechanisms of radicals, mainly focusing on outlining the methodology and results of radical closure experiments worldwide and systematically introducing the mainstream mechanisms of unclassical radical generation, involving the bimolecular reaction of HO2 and organic peroxy radicals (RO2), RO2 isomerization, halogen chemistry, the reaction of H2O with O2 over soot, epoxide formation mechanism, mechanism of electronically excited NO2 and water, and prompt HO2 formation in aromatic oxidation. Finally, we highlight the existing gaps in the current studies and suggest possible directions for future research. This review of unclassical radical generation mechanisms will help promote a comprehensive understanding of the latest radical mechanisms and the development of additional new mechanisms to further explain deviations between the existing and actual mechanisms.
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Affiliation(s)
- Xinping Yang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Vehicle Emission Control and Simulation, Vehicle Emission Control Center, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yang Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100084, China
| | - Xuefei Ma
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100084, China
| | - Zhaofeng Tan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100084, China
| | - Keding Lu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100084, China
| | - Yuanhang Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100084, China
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Cao J, Liu J, Cheng Y, Ai S, Li F, Xue T, Zhang Q, Zhu T. Impacts of different vehicle emissions on ozone levels in Beijing: Insights into source contributions and formation processes. ENVIRONMENT INTERNATIONAL 2024; 191:109002. [PMID: 39265323 DOI: 10.1016/j.envint.2024.109002] [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: 06/20/2024] [Revised: 08/21/2024] [Accepted: 09/06/2024] [Indexed: 09/14/2024]
Abstract
Beijing, with the highest number of motor vehicles in China, significantly contributes to O3 pollution through substantial NOx and VOC emissions in the on-road transportation sector. Understanding the unique impact of emissions from different vehicle types on O3 levels is crucial for developing targeted strategies for O3 pollution. This study applied the Community Multiscale Air Quality Modeling System (CMAQ) to comprehensively investigate the impacts of emissions from different vehicle types on O3 levels in various regions of Beijing and to provide valuable insights into source contributions and formation processes. The results revealed that various vehicle types exhibited different spatial-temporal emission patterns, with medium-heavy duty trucks (HDT) and mini-light passenger vehicles (LDPV) identified as the primary contributors to NOx (36.1 %) and VOC (57.6 %) emissions. Using the Integrated Source Apportionment Method (ISAM) coupled in CMAQ, we found the total vehicle emissions contributed to over 20 % of daily maximum 8-h average O3 (MDA8 O3) concentration, ranked as the second largest contributor after regional transport. Contributions to O3 formation from LDPV and medium-large passenger vehicles (MDPV) were 2.6-4.0 and 4.2-6.8 ppb and mainly concentrated in urban areas, while the contributions from mini-light duty trucks (LDT) and HDT were 3.5-4.8 and 3.7-6.2 ppb and mainly concentrated in suburban areas. Through scenario analysis that removed emissions from specific types of vehicles, we found removing LDPV emissions led to decreases in daytime O3 concentration by 0.3-3.8 ppb. In contrast, removing MDPV emissions led to notable O3 increases by 4.0-11.8 ppb at rush hours. Removing LDT and HDT emissions resulted in 0.6-8.0 ppb increases in nocturnal O3 concentrations while 0.8-2.0 ppb decreases during the afternoon. This research highlights the necessity of tailoring control strategies for different vehicle types to effectively reduce O3 levels in Beijing and provides useful information for decision-makers to formulate effective measures of vehicle management in the future.
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Affiliation(s)
- Jingyuan Cao
- SKL-ESPC & SEPKL-AERM, College of Environmental Sciences and Engineering, and Center for Environment and Health, Peking University, Beijing, China
| | - Jun Liu
- Department of Environmental Engineering, School of Energy and Environmental Engineering, University of Science and Technology Beijing, China.
| | - Ying Cheng
- Beijing Transport Institute, Beijing, China.
| | - Siqi Ai
- SKL-ESPC & SEPKL-AERM, College of Environmental Sciences and Engineering, and Center for Environment and Health, Peking University, Beijing, China
| | - Fangzhou Li
- SKL-ESPC & SEPKL-AERM, College of Environmental Sciences and Engineering, and Center for Environment and Health, Peking University, Beijing, China
| | - Tao Xue
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health / Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases, School of Public Health, Peking University Health Science Centre, Beijing, China; State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China
| | - Tong Zhu
- SKL-ESPC & SEPKL-AERM, College of Environmental Sciences and Engineering, and Center for Environment and Health, Peking University, Beijing, China; State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing, China.
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Wang Y, Chen Y, Chi S, Wang J, Zhang C, Lin W, Zhao W, Ye C. Optimizing a twin-chamber system for direct ozone production rate measurement. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 348:123837. [PMID: 38537793 DOI: 10.1016/j.envpol.2024.123837] [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: 01/30/2024] [Revised: 03/10/2024] [Accepted: 03/20/2024] [Indexed: 04/04/2024]
Abstract
High Ozone Production Rate (OPR) leads to O3 pollution episodes and adverse human health outcomes. OPR observation (Obs-OPR) and OPR modelling (Mod-OPR) have been obtained from observed and modelled peroxy radicals and nitrogen oxides. However, discrepancies between them remind of an imperfect understanding of O3 photochemistry. Direct measurement of OPR (Mea-OPR) by a twin-chamber system emerges. Herein, we optimized Mea-OPR design, i.e., minimizing the chamber surface area to volume ratio (S/V) to 9.8 m-1 from 18 m-1 and the dark uptake coefficient of O3 to 9.9 × 10-9 from 7.1 × 10-8 in the literature. In addition, control experiments further revealed and quantified a photo-enhanced O3 uptake, and therefore recommended an essential correction of Mea-OPR. We finally characterized a measurement uncertainty of ±38% and a detection limit of 3.2 ppbv h-1 (3SD), which suggested that Mea-OPR would be sensitive enough to measure OPR in urban or suburban environments. Further application of this system in urban Beijing during the Beijing 2022 Olympic Winter Games recorded a noontime OPR of 7.3 (±3.3, 1SD) ppbv h-1. These observational results added up to our confidence in future field application of Mea-OPR, to facilitate pollution control policy evaluation and to shed light on O3 photochemistry puzzle.
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Affiliation(s)
- Yaru Wang
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, Center for Environment and Health, and College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Yi Chen
- Key Laboratory of Ecology and Environment in Minority Areas (Minzu University of China), National Ethnic Affairs Commission, Beijing, 100081, China
| | - Suzhen Chi
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, Center for Environment and Health, and College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Jianshu Wang
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, Center for Environment and Health, and College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Chong Zhang
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, Center for Environment and Health, and College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Weili Lin
- Key Laboratory of Ecology and Environment in Minority Areas (Minzu University of China), National Ethnic Affairs Commission, Beijing, 100081, China
| | - Weixiong Zhao
- Laboratory of Atmospheric Physico-Chemistry, Chinese Academy of Sciences Hefei Institutes of Physical Science Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, Anhui, 230031, China
| | - Chunxiang Ye
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, Center for Environment and Health, and College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
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Xu T, Nie W, Xu Z, Yan C, Liu Y, Zha Q, Wang R, Li Y, Wang L, Ge D, Chen L, Qi X, Chi X, Ding A. Investigation on the budget of peroxyacetyl nitrate (PAN) in the Yangtze River Delta: Unravelling local photochemistry and regional impact. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170373. [PMID: 38286297 DOI: 10.1016/j.scitotenv.2024.170373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/12/2024] [Accepted: 01/21/2024] [Indexed: 01/31/2024]
Abstract
Peroxyacetyl nitrate (PAN) is a significant indicator of atmospheric photochemical pollution, which can influence the regional distribution of ozone (O3) and hydroxyl radical (OH) through long-range transport. However, investigations of PAN incorporating comprehensive measurement and explicit modeling analysis are limited, hindering complete understandings of its temporal behavior, sources, and impacts on photochemistry. Here we conducted a 1-year continuous observation of PAN and relative atmospheric species in Nanjing located in Yangtze River Delta (YRD). The annual mean concentration of PAN was 0.62 ± 0.49 ppbv and showed a bimodal monthly variation, peaking in April-June and November-January, respectively. This pattern is different from the typical pattern of photochemistry, suggesting important contributions of other non-photochemical processes. We further analyzed the PAN budget using an observation-based model, by which, PAN from local photochemical production and regional source could be decoupled. Our results revealed that local photochemical production of PAN is the sole contributor to PAN in summer, whereas about half of the total PAN concentration is attributed to regional source in winter. Although the formation of PAN can suppress the atmospheric oxidation capacity by consuming the peroxyacetyl radical and nitrogen dioxide (NO2), our analyses suggested this effect is minor at our station (-3.2 ± 1.1 % in summer and - 7.2 ± 2.8 % in winter for O3 formation). However, it has the potential to enhance O3 and OH formation by 14.16 % and 5.93 %, if transported to cleaner environments with air pollutants halved. Overall, our study highlights the importance of both local photochemistry and regional process in PAN budget and provides a useful evaluation on the impact of PAN on atmospheric oxidation capacity.
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Affiliation(s)
- Tao Xu
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, China
| | - Wei Nie
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, China.
| | - Zheng Xu
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, China; Jiangsu Provincial Environmental Monitoring Center, Nanjing, Jiangsu 210036, China.
| | - Chao Yan
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, China
| | - Yuliang Liu
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, China
| | - Qiaozhi Zha
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, China
| | - Ruoxian Wang
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, China
| | - Yuanyuan Li
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, China
| | - Lei Wang
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, China
| | - Dafeng Ge
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, China
| | - Liangduo Chen
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, China
| | - Ximeng Qi
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, China
| | - Xuguang Chi
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, China
| | - Aijun Ding
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China; National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, Jiangsu Province, 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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Zhang L, Wang L, Liu B, Tang G, Liu B, Li X, Sun Y, Li M, Chen X, Wang Y, Hu B. Contrasting effects of clean air actions on surface ozone concentrations in different regions over Beijing from May to September 2013-2020. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 903:166182. [PMID: 37562614 DOI: 10.1016/j.scitotenv.2023.166182] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 08/06/2023] [Accepted: 08/07/2023] [Indexed: 08/12/2023]
Abstract
Due to the nonlinear impacts of meteorology and precursors, the response of ozone (O3) trends to emission changes is very complex over different regions in megacity Beijing. Based on long-term in-situ observations at 35 air quality sites (four categories, i.e., urban, traffic, northern suburban and southern suburban sites) and satellite data, spatiotemporal variability of O3, gaseous precursors, and O3-VOCs-NOx sensitivity were explored through multiple metrics during the warm season from 2013 to 2020. Additionally, the contribution of meteorology and emissions to O3 was separated by a machine-learning-based de-weathered method. The annual averaged MDA8 O3 and O3 increased by 3.7 and 2.9 μg/m3/yr, respectively, with the highest at traffic sites and the lowest in northern suburb, and the rate of Ox (O3 + NO2) was 0.2 μg/m3/yr with the highest in southern suburb, although NO2 declined strongly and HCHO decreased slightly. However, the increment of O3 and Ox in the daytime exhibited decreasing trends to some extent. Additionally, NOx abatements weakened O3 loss through less NO titration, which drove narrowing differences in urban-suburban O3 and Ox. Due to larger decrease of NO2 in urban region and HCHO in northern suburb, the extent of VOCs-limited regime fluctuated over Beijing and northern suburb gradually shifted to transition or NOx-limited regime. Compared with the directly observed trends, the increasing rate of de-weathered O3 was lower, which was attributed to favorable meteorological conditions for O3 generation after 2017, especially in June (the most polluted month); whereas the de-weathered Ox declined except in southern suburb. Overall, clean air actions were effective in reducing the atmospheric oxidation capacity in urban and northern suburban regions, weakening local photochemical production over Beijing and suppressing O3 deterioration in northern suburb. Strengthening VOCs control and keeping NOx abatement, especially in June, will be vital to reverse O3 increase trend in Beijing.
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Affiliation(s)
- Lei Zhang
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Lili Wang
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Zhejiang Key Laboratory of Ecological and Environmental Big Data (2022P10005), Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China.
| | - Boya Liu
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Guiqian Tang
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Baoxian Liu
- Beijing Key Laboratory of Airborne Particulate Matter Monitoring Technology, Beijing Municipal Ecological Environmental Monitoring Center, Beijing 100048, China
| | - Xue Li
- Beijing Municipal Ecology and Environment Bureau, Beijing 100048, China
| | - Yang Sun
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Mingge Li
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute Chinese Academy of Sciences, Beijing 100101, China
| | - Xianyan Chen
- National Climate Center, China Meteorological Administration, Beijing 100081, China
| | - Yuesi Wang
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Bo Hu
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
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Wang Q, Sheng D, Wu C, Zhao J, Li F, Yao S, Ou X, Li W, Chen J. Exploring ozone formation rules and concentration response to the change of precursors based on artificial neural network simulation in a typical industrial park. Heliyon 2023; 9:e20125. [PMID: 37810165 PMCID: PMC10559865 DOI: 10.1016/j.heliyon.2023.e20125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 09/12/2023] [Accepted: 09/12/2023] [Indexed: 10/10/2023] Open
Abstract
Industrial parks have more complex O3 formation mechanisms due to a higher concentration and more dense emission of precursors. This study establishes an artificial neural network (ANN) model with good performance by expanding the moment and concentration changes of pollutants into general variables of meteorological factors and concentrations of pollutants. Finally, the O3 formation rules and concentration response to the changes of volatile organic compounds (VOCs) and nitrogen oxides (NOx) was explored. The results showed that the studied area belonged to the NOx-sensitive regime and the sensitivity was strongly affected by relative humidity (RH) and pressure (P). The concentration of O3 tends to decrease with a higher P, lower temperature (Temp), and medium to low RH when nitric oxide (NO) is added. Conversely, at medium P, high Temp, and high RH, the addition of nitrogen dioxide (NO2) leads to a larger decrease capacity in O3 concentration. More importantly, there is a local reachable maximum incremental reactivity (MIRL) at each certain VOCs concentration level which linearly increased with VOCs. The general maximum incremental reactivity (MIR) may lead to a significant overestimation of the attainable O3 concentration in NOx-sensitive regimes. The results can significantly support the local management strategies for O3 and the precursors control.
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Affiliation(s)
- Qiaoli Wang
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Dongping Sheng
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Chengzhi Wu
- Trinity Consultants, Inc. (China Office), Hangzhou, 310012, China
| | - Jingkai Zhao
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Feili Li
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Shengdong Yao
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Xiaojie Ou
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Wei Li
- Key Laboratory of Biomass Chemical Engineering of the Ministry of Education, Institute of Industrial Ecology and Environment, College of Chemical and Biological Engineering, Zhejiang University (Zijingang Campus), Hangzhou, 310030, China
| | - Jianmeng Chen
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
- Zhejiang University of Science & Technology, Hangzhou, 310023, China
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9
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Chen H, Hu Y, Ying Z, Xia Y, Ye J, Zhao J, Zhang S. BiOI-SnO 2 Heterojunction Design to Boost Visible-Light-Driven Photocatalytic NO Purification. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:4009. [PMID: 36901018 PMCID: PMC10001884 DOI: 10.3390/ijerph20054009] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/20/2023] [Accepted: 02/22/2023] [Indexed: 05/28/2023]
Abstract
The efficient, stable, and selective photocatalytic conversion of nitric oxide (NO) into harmless products such as nitrate (NO3-) is greatly desired but remains an enormous challenge. In this work, a series of BiOI/SnO2 heterojunctions (denoted as X%B-S, where X% is the mass portion of BiOI compared with the mass of SnO2) were synthesized for the efficient transformation of NO into harmless NO3-. The best performance was achieved by the 30%B-S catalyst, whose NO removal efficiency was 96.3% and 47.2% higher than that of 15%B-S and 75%B-S, respectively. Moreover, 30%B-S also exhibited good stability and recyclability. This enhanced performance was mainly caused by the heterojunction structure, which facilitated charge transport and electron-hole separation. Under visible light irradiation, the electrons gathered in SnO2 transformed O2 to ·O2- and ·OH, while the holes generated in BiOI oxidized H2O to produce ·OH. The abundantly generated ·OH, ·O2-, and 1O2 species effectively converted NO to NO- and NO2-, thus promoting the oxidation of NO to NO3-. Overall, the heterojunction formation between p-type BiOI and n-type SnO2 significantly reduced the recombination of photo-induced electron-hole pairs and promoted the photocatalytic activity. This work reveals the critical role of heterojunctions during photocatalytic degradation and provides some insight into NO removal.
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Affiliation(s)
- Han Chen
- Key Laboratory for Technology in Rural Water Management of Zhejiang Province, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China
| | - Yutao Hu
- Key Laboratory of Microbial Technology for Industrial Pollution Control of Zhejiang Province, College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
| | - Zanyun Ying
- College of Science & Technology, Ningbo University, Ningbo 315212, China
| | - Yinfeng Xia
- Key Laboratory for Technology in Rural Water Management of Zhejiang Province, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China
| | - Jiexu Ye
- Key Laboratory of Microbial Technology for Industrial Pollution Control of Zhejiang Province, College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
| | - Jingkai Zhao
- Key Laboratory of Microbial Technology for Industrial Pollution Control of Zhejiang Province, College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
| | - Shihan Zhang
- Key Laboratory of Microbial Technology for Industrial Pollution Control of Zhejiang Province, College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
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10
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Chen L, Pang X, Li J, Xing B, An T, Yuan K, Dai S, Wu Z, Wang S, Wang Q, Mao Y, Chen J. Vertical profiles of O 3, NO 2 and PM in a major fine chemical industry park in the Yangtze River Delta of China detected by a sensor package on an unmanned aerial vehicle. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 845:157113. [PMID: 35787910 DOI: 10.1016/j.scitotenv.2022.157113] [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: 05/09/2022] [Revised: 06/27/2022] [Accepted: 06/28/2022] [Indexed: 06/15/2023]
Abstract
The vertical profiles and diurnal variations of air pollutants at different heights in the fine chemical industry park (FCIP) were systematically studied in this study. Air pollutants in a major FCIP in the Yangtze River Delta of China within 500 m above ground level (AGL) detected by a sensor package on an unmanned aerial vehicle (UAV). The air pollutants including ozone (O3), nitrogen dioxide (NO2), particulate matter (PM), total volatile organic compounds (TVOCs) and carbon monoxide (CO), respectively, had been measured through more than one hundred times of vertical flights from Aug. 2020 to Jul. 2021. The concentrations of NO2 and CO generally decreased with the height while the concentrations of O3 increased with the height within 500 m AGL. The photochemical reaction resulted in a strong inverse relationship between the vertical profiles of O3 and that of NO2. The concentrations of PM2.5 and TVOCs generally decreased with the height below 100 m AGL and were fully mixed above 100 m AGL. The vertical profiles of different particle sizes were well consistent with the R2 value of 0.97 between PM1 and PM2.5 and 0.93 between PM2.5 and PM10. The NO2 and PM2.5 concentrations sometimes increased with height maybe due to the influence of temperature inversion layer or long-distance transportation from northern China. The diurnal variations of NO2, O3, TVOCs and CO concentrations at different heights within 500 m AGL were basically consistent. The diurnal variations range of PM2.5 concentrations below 100 m AGL was large and different from other heights, which should be greatly influenced by the local emissions. The unstable atmospheric stability was accompanied by strong photochemical reactions and convective activities, resulting in low concentrations of NO2 and PM2.5, while high concentrations of O3.
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Affiliation(s)
- Lang Chen
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Xiaobing Pang
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China.
| | - Jingjing Li
- Shaoxing Ecological and Environmental Monitoring Center of Zhejiang Province, Shaoxing 312000, China.
| | - Bo Xing
- Shaoxing Ecological and Environmental Monitoring Center of Zhejiang Province, Shaoxing 312000, China
| | - Taicheng An
- Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, School of Environmental Science and Engineering, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou 510006, China
| | - Kaibin Yuan
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Shang Dai
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Zhentao Wu
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Shuaiqi Wang
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Qiang Wang
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Yiping Mao
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Jianmeng Chen
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China.
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11
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Liu X, Li Z, Zhang J, Guo M, Lu F, Xu X, Deginet A, Liu M, Dong Z, Hu Y, Liu M, Li Y, Wu M, Luo Y, Tao L, Lin H, Guo X. The association between ozone and ischemic stroke morbidity among patients with type 2 diabetes in Beijing, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 818:151733. [PMID: 34800453 DOI: 10.1016/j.scitotenv.2021.151733] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 11/12/2021] [Accepted: 11/12/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND The association between ozone and ischemic stroke has been widely reported; however, the association among patients with type 2 diabetes (T2D) has remained largely unknown. METHODS The time series data of daily morbidity and concentrations of ozone from 2014 to 2018 were collected in Beijing, China. A time-stratified case-crossover study combined with a distributed lag nonlinear model was used to estimate the ozone effect on stroke morbidity among T2D patients. Based on principal diagnosis, ischemic stroke cases were identified according to the International Classification of Diseases (I63), and a history of T2D was coded as E12. RESULTS A total of 149,757 hospital admissions for ischemic stroke among T2D patients were recorded in Beijing. Approximately U-shaped exposure-response curves were observed for ozone and ischemic stroke morbidity among T2D patients. With a reference at 54.91 μg/m3, extreme-low (5th: 9.59 μg/m3) ozone was significantly associated with a decreased risk for ischemic stroke [RR = 0.88, 95% confidence interval (CI): 0.80-0.98]. Subgroup analysis showed that extremely low-ozone (5th) level only had a significant protective effect in males and elderly population, with a RR value of 0.86 (95% CI: 0.76-0.97) and 0.85 (95% CI: 0.75-0.96), respectively. Extreme-high ozone (99th: 157.06 μg/m3) was significantly associated with an increased risk for ischemic stroke (RR = 1.33, 95% CI: 1.12-1.57). The effect size was 1.34 (95% CI: 1.10-1.63) for males and 1.32 (95% CI: 1.07-1.63) for females, and the difference was not significant (Z = -0.29, P = 0.77). The effect size in younger adults was significantly higher than that in participants aged ≥65 years [1.52 (95% CI: 1.21-1.91) vs. 1.22 (95% CI: 1.01-1.47), Z = -1.62, P < 0.05]. CONCLUSIONS U-shaped associations were observed between ozone and ischemic stroke morbidity in T2D patients. Men and elderly population are vulnerable to low-ozone level, and the younger adults are more susceptible to extremely high-ozone level than the elderly.
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Affiliation(s)
- Xiangtong Liu
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Zhiwei Li
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Jie Zhang
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Moning Guo
- Beijing Municipal Health Commission Information Center, Beijing 100034, China.
| | - Feng Lu
- Beijing Municipal Health Commission Information Center, Beijing 100034, China.
| | - Xiaolin Xu
- The University of Queensland, Brisbane, Australia; School of Public Health, Zhejiang University, Hangzhou 310058, China.
| | - Aklilu Deginet
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Mengmeng Liu
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Zhaomin Dong
- School of Space and Environment, Beihang University, Beijing 100191, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100191, China.
| | - Yaoyu Hu
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Mengyang Liu
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Yutong Li
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Mengqiu Wu
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Yanxia Luo
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Lixin Tao
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - Xiuhua Guo
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
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