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Lan Q, Peng L, Ti C, Wang S, Tao L, Fan J, Yan X. Vertical and horizontal variabilities of ammonia in an agricultural area of Southeast China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2025; 373:123828. [PMID: 39721384 DOI: 10.1016/j.jenvman.2024.123828] [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: 10/28/2024] [Revised: 12/15/2024] [Accepted: 12/21/2024] [Indexed: 12/28/2024]
Abstract
Ammonia (NH3) plays a crucial role in the global nitrogen cycle, the increased NH3 emissions from agricultural activities impacting air, soil, water quality, and human health. Accurately estimating both the vertical and horizontal transport distances of NH3 are important for effective pollution control. Therefore, we used a helium-filled balloon mounted sampler to analyze the vertical profiles of NH3 emissions and their seasonal variations in an agricultural area of southeast China. The annual mean concentration of NH3 in this area was 6.49 ± 0.39 μg m⁻3. Vertical measurements revealed a gradual and steady decrease with increasing height, though no significant variation detected between different heights. Seasonal variations showed that the highest concentration occurred in summer (9.98 ± 0.11 μg m⁻3) and the lowest in winter (4.65 ± 0.02 μg m⁻3). Concentrations in summer significantly higher than those in the other three seasons. NH3 concentrations during the fertilizer application period were much higher than those in the non-fertilizer application time. We also monitored the horizontal transport distance of NH3 after fertilization. It is indicated that NH3 concentrations emitted from agricultural activities decreased exponentially with horizontal transport distance and could only be transported over short distances, up to 250 m. Therefore, local emissions are the dominant source of atmospheric NH3. Abetments such as enhanced-efficiency fertilizer could reduce agriculture NH3 emission to promote air quality.
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Affiliation(s)
- Qiao Lan
- School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China; State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China; University of Chinese Academy of Sciences, Nanjing, 211135, China
| | - Lingyun Peng
- State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China; University of Chinese Academy of Sciences, Beijing, 100049, China; University of Chinese Academy of Sciences, Nanjing, 211135, China
| | - Chaopu Ti
- State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China; University of Chinese Academy of Sciences, Beijing, 100049, China; University of Chinese Academy of Sciences, Nanjing, 211135, China.
| | - Shuwei Wang
- State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Limin Tao
- State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Jianling Fan
- School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Xiaoyuan Yan
- State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China; University of Chinese Academy of Sciences, Beijing, 100049, China; University of Chinese Academy of Sciences, Nanjing, 211135, China
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Zheng X, Liu J, Zhong B, Wang Y, Wu Z, Chuduo N, Ba B, Yuan X, Fan M, Cao F, Zhang Y, Chen W, Zhou L, Ma N, Yu P, Li J, Zhang G. Insights into anthropogenic impact on atmospheric inorganic aerosols in the largest city of the Tibetan Plateau through multidimensional isotope analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 929:172643. [PMID: 38649049 DOI: 10.1016/j.scitotenv.2024.172643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 04/18/2024] [Accepted: 04/18/2024] [Indexed: 04/25/2024]
Abstract
Particulate inorganic nitrogen aerosols (PIN) significantly influence air pollution and pose health risks worldwide. Despite extensive observations on ammonium (pNH4+) and nitrate (pNO3-) aerosols in various regions, their key sources and mechanisms in the Tibetan Plateau remain poorly understood. To bridge this gap, this study conducted a sampling campaign in Lhasa, the Tibetan Plateau's largest city, with a focus on analyzing the multiple isotopic signatures (δ15N, ∆17O). These isotopes were integrated into a Bayesian mixing model to quantify the source contributions and oxidation pathways for pNH4+ and pNO3-. Our results showed that traffic was the largest contributor to pNH4+ (31.8 %), followed by livestock (25.4 %), waste (21.8 %), and fertilizer (21.0 %), underscoring the impact of vehicular emissions on urban NH3 levels in Lhasa. For pNO3-, coal combustion emerged as the largest contributor (27.3 %), succeeded by biomass burning (26.3 %), traffic emission (25.3 %), and soil emission (21.1 %). In addition, the ∆17O-based model indicated a dominant role of NO2 + OH (52.9 %) in pNO3- production in Lhasa, which was similar to previous observations. However, it should be noted that the NO3 + volatile organic component (VOC) contributed up to 18.5 % to pNO3- production, which was four times higher than the Tibetan Plateau's background regions. Taken together, the multidimensional isotope analysis performed in this study elucidates the pronounced influence of anthropogenic activities on PIN in the atmospheric environment of Lhasa.
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Affiliation(s)
- Xueqin Zheng
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Junwen Liu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China.
| | - Bingqian Zhong
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Yujing Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Department of Environmental Science and Engineering, School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an 710049, China
| | - Zeyan Wu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Nima Chuduo
- Lhasa Meteorological Administration, Lhasa 850010, China
| | - Bian Ba
- Lhasa Meteorological Administration, Lhasa 850010, China
| | - Xin Yuan
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Meiyi Fan
- School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Fang Cao
- School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Yanlin Zhang
- School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Weihua Chen
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Luxi Zhou
- Guangzhou Institute of Tropical and Marine Meteorology, Meteorological Administration, Guangzhou 510640, China
| | - Nan Ma
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Pengfei Yu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Jun Li
- State Key Laboratory of Organic Geochemistry and Guangdong-Hong Kong-Macao Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Gan Zhang
- State Key Laboratory of Organic Geochemistry and Guangdong-Hong Kong-Macao Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
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3
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Zhang W, Wu F, Luo X, Song L, Wang X, Zhang Y, Wu J, Xiao Z, Cao F, Bi X, Feng Y. Quantification of NO x sources contribution to ambient nitrate aerosol, uncertainty analysis and sensitivity analysis in a megacity. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 926:171583. [PMID: 38461977 DOI: 10.1016/j.scitotenv.2024.171583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 02/06/2024] [Accepted: 03/06/2024] [Indexed: 03/12/2024]
Abstract
Dual isotopes of nitrogen and oxygen of NO3- are crucial tools for quantifying the formation pathways and precursor NOx sources contributing to atmospheric nitrate. However, further research is needed to reduce the uncertainty associated with NOx proportional contributions. The acquisition of nitrogen isotopic composition from NOx emission sources lacks regulation, and its impact on the accuracy of contribution results remains unexplored. This study identifies key influencing factors of source isotopic composition through statistical methods, based on a detailed summary of δ15N-NOx values from various sources. NOx emission sources are classified considering these factors, and representative means, standard deviations, and 95 % confidence intervals are determined using the bootstrap method. During the sampling period in Tianjin in 2022, the proportional nitrate formation pathways varied between sites. For suburban and coastal sites, the ranking was [Formula: see text] (NO2 + OH radical) > [Formula: see text] (N2O5 + H2O) > [Formula: see text] (NO3 + DMS/HC), while the rural site exhibited similar fractional contributions from all three formation pathways. Fossil fuel NOx sources consistently contributed more than non-fossil NOx sources in each season among three sites. The uncertainties in proportional contributions varied among different sources, with coal combustion and biogenic soil emission showing lower uncertainties, suggesting more stable proportional contributions than other sources. The sensitivity analysis clearly identifies that the isotopic composition of 15N-enriched and 15N-reduced sources significantly influences source contribution results, emphasizing the importance of accurately characterizing the localized and time-efficient nitrogen isotopic composition of NOx emission sources. In conclusion, this research sheds light on the importance of addressing uncertainties in NOx proportional contributions and emphasizes the need for further exploration of nitrogen isotopic composition from NOx emission sources for accurate atmospheric nitrate studies.
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Affiliation(s)
- Wenhui Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Fuliang Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Xi Luo
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Lilai Song
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Xuehan Wang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Jianhui Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Zhimei Xiao
- Tianjin Eco-Environmental Monitoring Center, Tianjin 300191, China
| | - Fang Cao
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Xiaohui Bi
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
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Wang Q, Du W, Zhou W, Zhang Y, Xie C, Zhao J, Xu W, Tang G, Fu P, Wang Z, Sun Y, Peng L. Characteristics of sub-micron aerosols above the urban canopy in Beijing during warm seasons. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 926:171989. [PMID: 38547971 DOI: 10.1016/j.scitotenv.2024.171989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 03/15/2024] [Accepted: 03/24/2024] [Indexed: 04/06/2024]
Abstract
To understand the characteristics of atmospheric pollution above the urban canopy in warm seasons, the characteristics of sub-micron aerosol (PM1) was studied based on high-altitude observations at the Beijing 325 m meteorological tower. The PM1 at 260 m was 34, 29 and 21 μg m-3 in May 2015, June 2015, and June 2017, respectively, indicating a reduction in PM1 pollution above the urban canopy. Meanwhile, an overall decrease was also observed in the concentrations of all PM1 chemical species (excluding Chl and BC) and organic aerosol (OA) factors. Previous instances of heavy haze in Beijing often coincided with high humidity and stagnant weather conditions. However, the heightened pollution episodes in June 2017 were accompanied by high wind speeds and low relative humidity. Compared to May 2015, the contribution of secondary components to PM1 in June 2017 was more prominent, with the total proportion of SNA (sulfate, nitrate, and ammonium) and more-oxidized oxygenated OA (MO-OOA) to PM1 increased by approximately 10 %. Secondary species of NH4NO3, (NH4)2SO4, and MO-OOA, as well as black carbon, collectively contributed the vast majority of aerosol extinction coefficient (bext), with the four species contributing a total of ≥96 % to bext at 260 m. Hydrocarbon-like OA, cooking OA, and less-oxidized oxygenated OA have undergone significant reductions, so continued emphasis on controlling local sources to reduce these three aerosol species and addressing regional sources to further mitigate overall aerosol species is imperative. In lower pollution situation, the diurnal variation of PM was smoother, and its pollution sources were more regionally uniform, which might be attributed to the reduced diversity and complexity in the physical and chemical processes in air pollution.
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Affiliation(s)
- Qingqing Wang
- Engineering Research Center of Clean and Low-carbon Technology for Intelligent Transportation, Ministry of Education, School of Environment, Beijing Jiaotong University, Beijing 100044, China; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
| | - Wei Du
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Institute for Atmospheric and Earth System Research / Physics, Faculty of Science, University of Helsinki, Finland
| | - Wei Zhou
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, 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
| | - Yingjie Zhang
- School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083, China
| | - Conghui Xie
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Laboratory of Gas Instrument Testing, Center for Environmental Metrology, National Institute of Metrology, Beijing 100029, China
| | - Jian Zhao
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Institute for Atmospheric and Earth System Research / Physics, Faculty of Science, University of Helsinki, Finland
| | - Weiqi Xu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, 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
| | - Guiqian Tang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Pingqing Fu
- Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, China
| | - Zifa Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, 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; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, 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; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Lin Peng
- Engineering Research Center of Clean and Low-carbon Technology for Intelligent Transportation, Ministry of Education, School of Environment, Beijing Jiaotong University, Beijing 100044, China.
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Feng X, Chen Y, Chen S, Peng Y, Liu Z, Jiang M, Feng Y, Wang L, Li L, Chen J. Dominant Contribution of NO 3 Radical to NO 3- Formation during Heavy Haze Episodes: Insights from High-Time Resolution of Dual Isotopes Δ 17O and δ 18O. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:20726-20735. [PMID: 38035574 DOI: 10.1021/acs.est.3c07590] [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: 12/02/2023]
Abstract
δ18O is widely used to track nitrate (NO3-) formation but overlooks NO3 radical reactions with hydrocarbons (HCs), particularly in heavily emitting hazes. This study introduces high-time resolution Δ17O-NO3- as a powerful tool to quantify NO3- formation during five hazes in three cities. Results show significant differences between Δ17O-NO3- and δ18O-NO3- in identifying NO3- formation. δ18O-NO3- results suggested N2O5 hydrolysis (62.0-88.4%) as the major pathway of NO3- formation, while Δ17O-NO3- shows the NO3- formation contributions of NO2 + OH (17.7-66.3%), NO3 + HC (10.8-49.6%), and N2O5 hydrolysis (22.9-33.3%), revealing significant NO3 + HC contribution (41.7-56%) under severe pollution. Furthermore, NO3- formation varies with temperatures, NOx oxidation rate (NOR), and pollution levels. Higher NO2 + OH contribution and lower NO3 + HC contribution were observed at higher temperatures, except for low NOR haze where higher NO2 + OH contributions were observed at low temperatures (T ← 10 °C). This emphasizes the significance of NO2 + OH in emission-dominated haze. Contributions of NO2 + OH and NO3 + HC relate to NOR as positive (fP1 = 3.0*NOR2 - 2.4*NOR + 0.8) and negative (fP2 = -2.3*NOR2 + 1.8*NOR) quadratic functions, respectively, with min/max values at NOR = 0.4. At mild pollution, NO2 + OH (58.1 ± 22.2%) dominated NO3- formation, shifting to NO3 + HC (35.5 ± 16.3%) during severe pollution. Additionally, high-time resolution Δ17O-NO3- reveals that morning-evening rush hours and high temperatures at noon promote the contributions of NO3 + HC and NO2 + OH, respectively. Our results suggested that the differences in the NO3- pathway are attributed to temperatures, NOR, and pollution levels. Furthermore, high-time resolution Δ17O-NO3- is vital for quantifying NO3 + HC contribution during severe hazes.
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Affiliation(s)
- Xinxin Feng
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, P.R. China
| | - Yingjun Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, P.R. China
- Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
| | - Shaofeng Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, P.R. China
| | - Yu Peng
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, P.R. China
| | - Zeyu Liu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, P.R. China
| | - Minjun Jiang
- Institute of Environmental Pollution and Health, School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
| | - Yanli Feng
- Institute of Environmental Pollution and Health, School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
| | - Lina Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, P.R. China
| | - Li Li
- Institute of Environmental Pollution and Health, School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
| | - Jianmin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, P.R. China
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Yuan Z, Pei CL, Li HX, Lin L, Hou R, Liu S, Zhang K, Cai MG, Xu XR. Vertical distribution and transport of microplastics in the urban atmosphere: New insights from field observations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 895:165190. [PMID: 37385506 DOI: 10.1016/j.scitotenv.2023.165190] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/19/2023] [Accepted: 06/26/2023] [Indexed: 07/01/2023]
Abstract
The distribution and transport of atmospheric microplastics (AMPs) have raised concerns regarding their potential effects on the environment and human health. Although previous studies have reported the presence of AMPs at ground level, there is a lack of comprehensive understanding of their vertical distribution in urban environments. To gain insight into the vertical profile of AMPs, field observations were conducted at four different heights (ground level, 118 m, 168 m and 488 m) of the Canton Tower in Guangzhou, China. Results showed that the profiles of AMPs and other air pollutants had similar layer distribution patterns, although their concentrations differed. The majority of AMPs were composed of polyethylene terephthalate and rayon fibers ranging from 30 to 50 μm. As a result of atmospheric thermodynamics, AMPs generated at ground level were only partially transported upward, leading to a decrease in their abundance with increasing altitude. The study found that the stable atmospheric stability and lower wind speed between 118 m and 168 m resulted in the formation of a fine layer where AMPs tended to accumulate instead of being transported upward. This study for the first time delineated the vertical profile of AMPs within the atmospheric boundary layer, providing valuable data for understanding the environmental fate of AMPs.
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Affiliation(s)
- Zhen Yuan
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Cheng-Lei Pei
- Guangzhou Sub-branch of Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510006, China
| | - Heng-Xiang Li
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China
| | - Lang Lin
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China
| | - Rui Hou
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China
| | - Shan Liu
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China
| | - Kai Zhang
- National Observation and Research Station of Coastal Ecological Environments in Macao, Macao Environmental Research Institute, Macau University of Science and Technology, Macao SAR, China
| | - Ming-Gang Cai
- State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen 361102, China
| | - Xiang-Rong Xu
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China.
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