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Wang R, Wang L, Li Y, Sun J, Li K, Huang H, You Y, Wang Y. The reward and penalty for ozone pollution control caused by natural sources and regional transport: A case study in Guangdong province. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 949:174984. [PMID: 39053537 DOI: 10.1016/j.scitotenv.2024.174984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Revised: 07/03/2024] [Accepted: 07/21/2024] [Indexed: 07/27/2024]
Abstract
Ground-level O3 pollution in the Pearl River Delta region (PRD) is closely related to anthropogenic, natural emissions and regional transport. However, the interactions among different sources and natural intervention in modulating anthropogenic management have not been comprehensively assessed. Here, the WRF-CMAQ-MEGAN modeling system was utilized to simulate an O3 episode over PRD. The integrated source apportionment method (ISAM) and brute-force top-down combined with factor separation approach (BF-TD-FSA) were applied to quantify source contributions, impacts of individual or multiple sources on O3, and decouple interactions among various emissions; additionally, based on ISAM, O3 isopleths visualized MDA8 O3 response of different source types to anthropogenic perturbations. ISAM concluded considerable MDA8 O3 contributions of regional transport in PRD/NPRD (non-PRD areas in Guangdong province) (38.8 %/35.7 %), followed by anthropogenic (32.7 %/24.8 %), BVOC (biogenic volatile organic compounds, 23.8 %/20.3 %) and SNO (soil NO, ∼4 %) emissions. Compared to concentrated anthropogenic contributions, widespread natural contributions were observed across their source areas and along the transport pathways. The BF-TD also revealed that regional transport had the largest impact (>90 μg m-3) on MDA8 O3 while anthropogenic and BVOC emissions greatly affected downwind PRD (64.5 and 7.7 μg m-3). Negative synergy between anthropogenic and natural emissions (especially BVOC emission) suggested potential natural-induced intensification of anthropogenic impact during O3 management. The MDA8 O3 isopleths further demonstrated significant BVOC-induced reward and regional transport-induced penalty for anthropogenic NOx (ANOx) emission control benefits, leading to additional maximum MDA8 O3 decrease and increase by -27.5 and 13.8 μg m-3 in polluted high-emission grids. The natural-induced reward effect could impose loose requirements on anthropogenic reduction (decreased by 13.3 %-17.7 %) if there were no regional transport-induced control penalty. It is advisable to prioritize ANOx control and seek collaboration on air quality management with neighboring provinces to maximize the natural-induced control reward and achieve desired targets with minimal human efforts.
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Affiliation(s)
- Runyu Wang
- State Key Laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lili Wang
- State Key Laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; 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.
| | - Yuanyuan Li
- Xinjiang Weather Modification Office, Urumqi 830002, China
| | - Jiaren Sun
- Guangdong Province Engineering Laboratory for Air Pollution Control, Guangdong Provincial Key Laboratory of Water and Air Pollution Control, South China Institute of Environmental Sciences, MEE, Guangzhou 510655, China.
| | - Ke Li
- 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
| | - Hanjie Huang
- College of Environment and Climate, Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou 510632, China
| | - Yanbin You
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuesi Wang
- State Key Laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
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Li J, Yuan B, Yang S, Peng Y, Chen W, Xie Q, Wu Y, Huang Z, Zheng J, Wang X, Shao M. Quantifying the contributions of meteorology, emissions, and transport to ground-level ozone in the Pearl River Delta, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 932:173011. [PMID: 38719052 DOI: 10.1016/j.scitotenv.2024.173011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 04/29/2024] [Accepted: 05/01/2024] [Indexed: 05/14/2024]
Abstract
Ozone pollution presents a growing air quality threat in urban agglomerations in China. It remains challenge to distinguish the roles of emissions of precursors, chemical production and transportations in shaping the ground-level ozone trends, largely due to complicated interactions among these 3 major processes. This study elucidates the formation factors of ozone pollution and categorizes them into local emissions (anthropogenic and biogenic emissions), transport (precursor transport and direct transport from various regions), and meteorology. Particularly, we attribute meteorology, which affects biogenic emissions and chemical formation as well as transportation, to a perturbation term with fluctuating ranges. The Community Multiscale Air Quality (CMAQ) model was utilized to implement this framework, using the Pearl River Delta region as a case study, to simulate a severe ozone pollution episode in autumn 2019 that affected the entire country. Our findings demonstrate that the average impact of meteorological conditions changed consistently with the variation of ozone pollution levels, indicating that meteorological conditions can exert significant control over the degree of ozone pollution. As the maximum daily 8-hour average (MDA8) ozone concentrations increased from 20 % below to 30 % above the National Ambient Air Quality Standard II, contributions from emissions and precursor transport were enhanced. Concurrently, direct transport within Guangdong province rose from 13.8 % to 22.7 %, underscoring the importance of regional joint prevention and control measures under adverse weather conditions. Regarding biogenic emissions and precursor transport that cannot be directly controlled, we found that their contributions were generally greater in urban areas with high nitrogen oxides (NOx) levels, primarily due to the stronger atmospheric oxidation capacity facilitating ozone formation. Our results indicate that not only local anthropogenic emissions can be controlled in urban areas, but also the impacts of local biogenic emissions and precursor transport can be potentially regulated through reducing atmospheric oxidation capacity.
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Affiliation(s)
- Jin Li
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 511443, China
| | - Bin Yuan
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 511443, China.
| | - Suxia Yang
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 511443, China
| | - Yuwen Peng
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 511443, China
| | - Weihua Chen
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 511443, China
| | - Qianqian Xie
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 511443, China
| | - Yongkang Wu
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 511443, China
| | - Zhijiong Huang
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 511443, China
| | - Junyu Zheng
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 511443, China
| | - Xuemei Wang
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 511443, China
| | - Min Shao
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 511443, China
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Li L, Bai G, Han H, Wu Y, Xie S, Xie W. Localized biogenic volatile organic compound emission inventory in China: A comprehensive review. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 353:120121. [PMID: 38281423 DOI: 10.1016/j.jenvman.2024.120121] [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: 11/02/2023] [Revised: 12/29/2023] [Accepted: 01/13/2024] [Indexed: 01/30/2024]
Abstract
Volatile organic compounds (VOCs) are the precursors of forming ozone (O3) and fine particulate matter (PM2.5). Accurate estimates of biogenic VOC (BVOC) emissions is essential for understanding the formation mechanism of O3 and PM2.5 pollution and precise reduction on anthropogenic emissions and thereby mitigating O3 and PM2.5 pollution. To gain comprehensive knowledge of BVOC emissions and improve the accuracy of their estimation, this study reviewed localized national, regional, and municipal emission estimations in China. From their comparisons, BVOC emission characteristics and deficiencies in the inventory compilation methodology were also investigated. The estimated BVOC emissions in China ranged between 10 and 58.9 Tg yr-1 and 10.9-18.9 Tg C yr-1, with diverse contributions for different BVOC categories. The simulated historical and future BVOC emissions exhibited an increasing trend. The uncertainty of the BVOC estimates was mainly from the applications of incomplete emission models, less localized accurate emission factors, deficient vegetation cover information, and low-resolution meteorological data in the inventory compilation. The regional and municipal BVOC emission inventories mainly focused on the Beijing-Tianjin-Hebei, Pearl River Delta, Sichuan Basin, and Yangtze River Delta regions, as well as the cities therein. For the same area, different studies reported diverse BVOC emissions by a maximum of two orders of magnitude. There is usually a lack of basic data with more detailed investigations and higher precision for estimation of BVOC emissions. By summarizing the measurements on terrestrial and marine BVOC emission fluxes, they are mainly focused on the Guangdong, Zhejiang and Jiangxi provinces, and Yellow Sea, East China Sea, and South China Sea, respectively. Expanding the temporal and spatial scales of observations is encouraged to enhance our understanding on the emissions and improve the emission estimates.
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Affiliation(s)
- Lingyu Li
- College of Environmental Sciences and Engineering, Carbon Neutrality and Eco-Environmental Technology Innovation Center of Qingdao, Qingdao University, Qingdao 266071, China.
| | - Guangkun Bai
- College of Environmental Sciences and Engineering, Carbon Neutrality and Eco-Environmental Technology Innovation Center of Qingdao, Qingdao University, Qingdao 266071, China
| | - Huijuan Han
- College of Environmental Sciences and Engineering, Carbon Neutrality and Eco-Environmental Technology Innovation Center of Qingdao, Qingdao University, Qingdao 266071, China
| | - Yan Wu
- School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China
| | - Shaodong Xie
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Wenxia Xie
- College of Environmental Sciences and Engineering, Carbon Neutrality and Eco-Environmental Technology Innovation Center of Qingdao, Qingdao University, Qingdao 266071, China.
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Hu F, Xie P, Tian X, Xu J, Li A, Lupaşcu A, Butler T, Hu Z, Lv Y, Zhang Z, Zheng J. Integrated analysis of the transport process and source attribution of an extreme ozone pollution event in Hefei at different vertical heights: A case of study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167237. [PMID: 37739071 DOI: 10.1016/j.scitotenv.2023.167237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 09/17/2023] [Accepted: 09/19/2023] [Indexed: 09/24/2023]
Abstract
The Yangtze River Delta (YRD) region frequently experiences ozone pollution events during the summer and autumn seasons. High-concentration events are typically related to synoptic weather patterns, which impact the transport and photochemical production of ozone at multiple scales, ranging from the local to regional scale. To better understand the regional ozone pollution problem, studies on ozone source attribution are needed, especially regarding the contributions of sources at different vertical heights based on tagging the region or time periods. Between September 3 and 8, 2020, an episode of ozone concentration anomaly high was observed in Hefei through ground-based stations and ozone Lidar. The mechanism behind this event was uncovered through synoptic weather pattern analysis and using the Weather Research and Forecasting Chemistry model (WRF-Chem). Because an approaching typhoon caused variable wind direction, the O3-rich air masses (ORMs) arising from the YRD region were transported to Hefei via the nocturnal residual layer and descended to the ground through horizontal advection and vertical mixing processes the next day. Based on geographic source tagging, the anthropogenic NOx emissions (ANEs) from local and regional sources were the main contributors to the heavy ozone pollution over Hefei on September 6. Furthermore, the intra-regional transported ozone from southern Jiangsu (SJS), southern Anhui (SAH), and Zhejiang (ZJ) in the YRD was the main driving factor of the surface and upper atmosphere ozone pollution. Based on time period tagging, The ozone generated due to ANEs from September 3 to 5 significantly contributed to this episode. It is important to pay attention to the impact of ANEs on September 5 on the surface peak ozone concentration the following day (i.e., September 6). Our findings provide significant insights into the regional ozone transport mechanism in the YRD and optimization of measures to prevent and control heavy ozone pollution on spatiotemporal scales.
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Affiliation(s)
- Feng Hu
- 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.
| | - 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.
| | - 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
| | - Aurelia Lupaşcu
- Research Institute for Sustainability - Helmholtz Centre Potsdam (RIFS Potsdam), Potsdam 14467, Germany; now at European Centre for Medium Range Weather Forecasts, Bonn, Germany
| | - Tim Butler
- Research Institute for Sustainability - Helmholtz Centre Potsdam (RIFS Potsdam), Potsdam 14467, Germany; Freie Universität Berlin, Institut für Meteorologie, Berlin, Germany
| | - Zhaokun Hu
- 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
| | - 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
| | - Jiangyi Zheng
- Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
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Cao J, Pan G, Zheng B, Liu Y, Zhang G, Liu Y. Significant land cover change in China during 2001-2019: Implications for direct and indirect effects on surface ozone concentration. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 335:122290. [PMID: 37524236 DOI: 10.1016/j.envpol.2023.122290] [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: 05/25/2023] [Revised: 07/06/2023] [Accepted: 07/28/2023] [Indexed: 08/02/2023]
Abstract
China has become one of the most prominent areas of global land cover change during the past few decades. These changes can directly influence meteorological parameters thus further regulating tropospheric ozone (O3) formation. Moreover, changes in biogenic emissions due to land cover variation can also have an indirect effect on O3 concentration. This study applied the Community Multiscale Air Quality model to comprehensively evaluate the impacts of significant land cover change on O3 levels in China during summertime between 2001 and 2019. The results showed that the daily maximum 8-h average O3 concentration (MDA8 O3) increased by 3.6-8.9 μg/m3, 2.8-8.0 μg/m3, 3.8-9.6 μg/m3, -1.5-6.2 μg/m3, and -0.6-2.5 μg/m3 in Beijing-Tianjin-Hebei region, Yangtze River Delta, Pearl River Delta, Sichuan Basin, and Fenwei Plain, respectively, in response to land cover variation. The research identified that the direct effect was the primary factor in raising O3 levels which mainly altered O3 concentration by changing vertical import and dry deposition velocity. Moreover, land cover variation tended to decrease biogenic nitric oxide emission and increase biogenic volatile organic compounds emission on the whole, and cause an obvious increase of MDA8 O3 by 1.8-4.9 μg/m3 in Pearl River Delta due to the indirect effect. This study offered valuable insights into the impacts of land cover change on O3 levels, highlighting the need for policymakers to consider land cover variation on air pollutants concentration for devising comprehensive multi-pollutant control strategies.
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Affiliation(s)
- Jingyuan Cao
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Guanfu Pan
- National Institute of Metrology, Beijing, 100029, China
| | - Boyue Zheng
- Institute of Energy, Peking University, Beijing, 100871, China
| | - Yang Liu
- College of Environmental Sciences and Engineering, North China Electric Power University, Beijing, 102206, China
| | - Guobin Zhang
- College of Environmental Sciences and Engineering, North China Electric Power University, Beijing, 102206, China
| | - Yang Liu
- National Institute of Metrology, Beijing, 100029, China.
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Tan W, Wang H, Su J, Sun R, He C, Lu X, Lin J, Xue C, Wang H, Liu Y, Liu L, Zhang L, Wu D, Mu Y, Fan S. Soil Emissions of Reactive Nitrogen Accelerate Summertime Surface Ozone Increases in the North China Plain. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:12782-12793. [PMID: 37596963 DOI: 10.1021/acs.est.3c01823] [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: 08/21/2023]
Abstract
Summertime surface ozone in China has been increasing since 2013 despite the policy-driven reduction in fuel combustion emissions of nitrogen oxides (NOx). Here we examine the role of soil reactive nitrogen (Nr, including NOx and nitrous acid (HONO)) emissions in the 2013-2019 ozone increase over the North China Plain (NCP), using GEOS-Chem chemical transport model simulations. We update soil NOx emissions and add soil HONO emissions in GEOS-Chem based on observation-constrained parametrization schemes. The model estimates significant daily maximum 8 h average (MDA8) ozone enhancement from soil Nr emissions of 8.0 ppbv over the NCP and 5.5 ppbv over China in June-July 2019. We identify a strong competing effect between combustion and soil Nr sources on ozone production in the NCP region. We find that soil Nr emissions accelerate the 2013-2019 June-July ozone increase over the NCP by 3.0 ppbv. The increase in soil Nr ozone contribution, however, is not primarily driven by weather-induced increases in soil Nr emissions, but by the concurrent decreases in fuel combustion NOx emissions, which enhance ozone production efficiency from soil by pushing ozone production toward a more NOx-sensitive regime. Our results reveal an important indirect effect from fuel combustion NOx emission reduction on ozone trends by increasing ozone production from soil Nr emissions, highlighting the necessity to consider the interaction between anthropogenic and biogenic sources in ozone mitigation in the North China Plain.
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Affiliation(s)
- Wanshan Tan
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Haolin Wang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Jiayin Su
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Ruize Sun
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Cheng He
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Xiao Lu
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Jintai Lin
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, People's Republic of China
| | - Chaoyang Xue
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), CNRS-Université Orléans-CNES, CEDEX 2 Orléans 45071, France
| | - Haichao Wang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Yiming Liu
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Lei Liu
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, People's Republic of China
| | - Lin Zhang
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, People's Republic of China
| | - Dianming Wu
- Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, People's Republic of China
- Institute of Eco-Chongming (IEC), Shanghai 202162, People's Republic of China
| | - Yujing Mu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Shaojia Fan
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
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Zhang B, Qiao L, Han H, Xie W, Li L. Variations in VOCs Emissions and Their O 3 and SOA Formation Potential among Different Ages of Plant Foliage. TOXICS 2023; 11:645. [PMID: 37624151 PMCID: PMC10458546 DOI: 10.3390/toxics11080645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 07/21/2023] [Accepted: 07/22/2023] [Indexed: 08/26/2023]
Abstract
Volatile organic compounds (VOCs) emitted by plant foliage play an important role in ozone (O3) and secondary organic aerosol (SOA) formation. Their emissions can be influenced by the leaf age. We explored the VOCs emissions and their effects on the formation of O3 and SOA from plant foliage in different ages. VOCs emissions from the young, mature, and senescent leaves of Ginkgo biloba, Ligustrum lucidum, and Forsythia suspensa were measured using the dynamic enclosure system and the TD-GC-MS technique. Based on the emission rates of quantified compounds, their potential to form O3 and SOA was estimated. Results showed that there were significant differences in the VOCs emission rate and their composition among leaves in different ages. The emission rate of the total VOCs by young leaves was the highest, while the lowest by senescent leaves. Monoterpenes were the dominant VOCs category, and isoprene emission had the lowest contribution for the leaves at each age. With increasing leaf age, the proportion of monoterpenes emission increased, and the proportion of sesquiterpenes decreased. The variations of isoprene and other VOCs were different. The potentials of total VOCs, isoprene, monoterpenes, sesquiterpenes, and other VOCs to form O3 (OFP) and SOA (SOAP) varied significantly among leaves at different ages. The total OFP and SOAP were the highest by young leaves, while the lowest by senescent leaves. With increasing leaf age, the contribution of monoterpenes to OFP and SOAP also increased, while that of sesquiterpenes decreased. Our study will provide support for the more accurate parameterization of the emission model and help to understand the VOCs emissions and study the precise prevention and control of complex air pollution at different times.
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Affiliation(s)
| | | | | | - Wenxia Xie
- College of Environmental Sciences and Engineering, Carbon Neutrality and Eco-Environmental Technology Innovation Center of Qingdao, Qingdao University, Qingdao 266071, China; (B.Z.); (L.Q.); (H.H.)
| | - Lingyu Li
- College of Environmental Sciences and Engineering, Carbon Neutrality and Eco-Environmental Technology Innovation Center of Qingdao, Qingdao University, Qingdao 266071, China; (B.Z.); (L.Q.); (H.H.)
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