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Cha JY, Lee K, Lee SC, Lee EJ, Yim KJ, Ryoo I, Kim M, Ahn J, Yi SM, Park CR, Oh NH. Fossil and non-fossil sources of the carbonaceous component of PM 2.5 in forest and urban areas. Sci Rep 2023; 13:5486. [PMID: 37016024 PMCID: PMC10073123 DOI: 10.1038/s41598-023-32721-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 03/31/2023] [Indexed: 04/06/2023] Open
Abstract
Atmospheric particulate matter (PM2.5) can damage human health. Biogenic organic compounds emitted from trees may increase the concentration of PM2.5 via formation of secondary aerosols. Therefore, the role of biogenic emissions in PM2.5 formation and the sources of PM2.5 need to be investigated. Dual carbon isotope and levoglucosan analyses are powerful tools to track the sources of total carbon (TC) in PM2.5. We collected a total of 47 PM2.5 samples from 2019 to 2020 inside a pine forest and in urban areas in South Korea. The average δ13C and Δ14C of TC in PM2.5 at the Taehwa Research Forest (TRF) were - 25.7 and - 380.7‰, respectively, which were not significantly different from those collected at Seoul National University (SNU) in urban areas. Contribution of fossil fuel, C3-, and C4- plants to carbonaceous component of PM2.5 were 52, 27, and 21% at SNU, whereas those were 46, 35, and 19% at TRF, respectively. The biomass burning tracer, levoglucosan, was most abundant in winter and correlated with the contribution of C4 plants derived carbon. Results indicate that biogenic aerosols emitted from trees is less likely to be an important source of PM2.5 and that trees can act as a bio-filter to reduce PM2.5.
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Affiliation(s)
- Ji-Yeon Cha
- Department of Environmental Planning, Graduate School of Environmental Studies, Seoul National University, Seoul, 08826, Republic of Korea
| | - Kyuyeon Lee
- Department of Environmental Planning, Graduate School of Environmental Studies, Seoul National University, Seoul, 08826, Republic of Korea
| | - Seung-Cheol Lee
- Department of Environmental Planning, Graduate School of Environmental Studies, Seoul National University, Seoul, 08826, Republic of Korea
| | - Eun-Ju Lee
- Environmental Planning Institute, Seoul National University, Seoul, 08826, Republic of Korea
| | - Kwang-Jin Yim
- School of Earth and Environmental Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | - Ilhan Ryoo
- Department of Environmental Health, Graduate School of Public Health, Seoul National University, Seoul, 08826, Republic of Korea
| | - Minhye Kim
- Department of Environmental Health, Graduate School of Public Health, Seoul National University, Seoul, 08826, Republic of Korea
| | - Jinho Ahn
- School of Earth and Environmental Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | - Seung-Muk Yi
- Department of Environmental Health, Graduate School of Public Health, Seoul National University, Seoul, 08826, Republic of Korea
- Institute of Health and Environment, Seoul National University, Seoul, 08826, Republic of Korea
| | - Chan-Ryul Park
- Urban Forests Division, National Institute of Forest Science, Seoul, 02455, Republic of Korea
| | - Neung-Hwan Oh
- Department of Environmental Planning, Graduate School of Environmental Studies, Seoul National University, Seoul, 08826, Republic of Korea.
- Environmental Planning Institute, Seoul National University, Seoul, 08826, Republic of Korea.
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Ma H, Chen W, Zhang Q, Wan C, Mo Y, Liu F, Dong G, Zeng X, Chen D, Yu Z, Li J, Zhang G. Pollution source and chemicals structure of the water-soluble fractions in PM 2.5 that induce apoptosis in China. ENVIRONMENT INTERNATIONAL 2023; 173:107820. [PMID: 36842384 DOI: 10.1016/j.envint.2023.107820] [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: 11/08/2022] [Revised: 01/27/2023] [Accepted: 02/11/2023] [Indexed: 06/18/2023]
Abstract
Identify risk drivers is the key condition in air pollution control, and biological effect-directed analysis is the most commented method for combing chemical identify and human health. The water-soluble organic matter contained in PM2.5 plays an important role in human health, while it is also the most difficult to identify its chemical information. Exploring the structural characteristics and pollution sources of its key toxic components is the optimized strategy to meet this question. In this study, the induction of apoptosis by the water-soluble fractions (WSF) of PM2.5 samples collected in 10 major cities in China over a period of 1 year was observed in vitro in Beas-2b cells. Organic carbon structures were examined using nuclear magnetic resonance; air potential sources were identified using δ13C and 14C isotopic markers. Apoptosis induction by WSF in PM2.5 was generally stronger in northern cities than in southern cities, and in winter than in summer. Organic compounds with aromatic and double-bond carbon structures from secondary products of motor vehicle exhausts, coal-derived emissions, and emissions derived from the burning of core residues may be primarily responsible for apoptosis induction by PM2.5. Our results will contribute to understanding the toxic substances contained in WSF and provide basic data for accurate pollution control.
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Affiliation(s)
- Huimin Ma
- State Key Laboratory of Organic Geochemistry and Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China.
| | - Wenjing Chen
- State Key Laboratory of Organic Geochemistry and Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qianyu Zhang
- State Key Laboratory of Organic Geochemistry and Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Cong Wan
- State Key Laboratory of Organic Geochemistry and Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yangzhi Mo
- State Key Laboratory of Organic Geochemistry and Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Fei Liu
- School of Business Administration, South China University of Technology, Guangzhou 510641, China
| | - Guanghui Dong
- Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiaowen Zeng
- Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Duohong Chen
- Department of Air Quality Forecasting and Early Warning, Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou 510308, China
| | - Zhiqiang Yu
- State Key Laboratory of Organic Geochemistry and Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Jun Li
- State Key Laboratory of Organic Geochemistry and Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Gan Zhang
- State Key Laboratory of Organic Geochemistry and Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
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Zhou Y, Xia X, Lang J, Zhao B, Chen D, Mao S, Zhang Y, Liu J, Li J. A coupled framework for estimating pollutant emissions from open burning of specific crop residue: A case study for wheat. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 844:156731. [PMID: 35772556 DOI: 10.1016/j.scitotenv.2022.156731] [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: 04/21/2022] [Revised: 06/08/2022] [Accepted: 06/12/2022] [Indexed: 06/15/2023]
Abstract
Crop residue open burning is considered to be one of the main sources of pollutant emissions from rural areas. It is necessary to accurately establish an emissions inventory of specific crops which could reflect the specific spatiotemporal distribution characteristics of crop residue burning emissions. However, the information for emission estimation of specific crop in each province and year is seriously data-deficient, resulting in a large uncertainty in the emissions inventory. In this study, taking the open burning of wheat residue as an example, we propose a framework for estimating pollutant emissions for specific crop residue by combining phenological information, land use data, field investigation/statistical data, and fire detection information. The wheat residue open burning proportion (OBP) and the corresponding pollutant emissions were estimated for each province in mainland China from 2003 to 2019. The national average OBP and emissions of wheat crop residue open burning first increased and then decreased during this period, with the peak in 2012. The gridded spatial distribution showed that high-emission areas were mainly concentrated in central-eastern China, and the emission areas gradually shifted from south to north from April to September. The change of daily emissions from large-scale concentrated emissions to small-scale emissions demonstrated that straw open burning prohibition policies were effective in reducing the annual emissions and peak daily emissions. This study provides a promising method for the combination of data from multiple sources to estimate open burning of crop residues. The method can be used to obtain accurate and detailed emissions data to support research into biomass burning and the development of targeted mitigation strategies.
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Affiliation(s)
- Ying Zhou
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China.
| | - Xiangchen Xia
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Jianlei Lang
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Beibei Zhao
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China
| | - Dongsheng Chen
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Shushuai Mao
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Yuying Zhang
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Jing Liu
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Jia Li
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
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Jin Q, Wang W, Zheng W, Innes JL, Wang G, Guo F. Dynamics of pollutant emissions from wildfires in Mainland China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 318:115499. [PMID: 35717695 DOI: 10.1016/j.jenvman.2022.115499] [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: 09/30/2021] [Revised: 06/06/2022] [Accepted: 06/06/2022] [Indexed: 06/15/2023]
Abstract
We analyzed the dynamics of pollutant emissions from wildfires in mainland China from 2001 to 2019 using MODIS fire products combined with the measurements of emission factors of different vegetation types. The biomass distribution in Mainland China has heterogeneous temporal and spatial pattern, with inter-year variations and a decreasing trend from east to west. Overall, from 2001 to 2019, biomass combustion in Mainland China reached 479.59 Tg (25.24 Tg·a-1), in which northeast, north, east, south, central, northwest, and southwest regions accounted for 20.95%, 31.14%, 8.89%, 9.06%, 3.98%, 0.33% and 25.64% of total biomass combustion, respectively. The emissions of CO, CO2, CxHy, NOx, PM2.5, TC, OC and EC were 47.30, 288.05, 12.90, 0.40, 1.43, 0.83, 0.70, and 0.12 Tg (1 Tg = 1012g), respectively. PM2.5, TC and OC emissions increased in the southwest, while all pollutant emissions declined significantly in the southern region. For particulate matter from wildfires, both the ratio of its emissions to total dust and the ratio of its concentration to atmospheric PM2.5 showed an increasing trend, implying that the relative environmental impacts of particulate emissions from wildfires may be rising. In addition, our results show that the current Chinese wildfire management has successfully reduced on average more than 80% of pollutant emissions from wildfire from 2001 to 2019 compared to the natural wildfire regime (no strict wildfire management). This research on the temporal-spatial changes of pollutant emissions from wildfires in Mainland China provides support for further exploration of wildfire impacts on regional environments, and indicates the effectiveness of Chinese current wildfire policy on the pollutant emission mitigation.
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Affiliation(s)
- Quanfeng Jin
- College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, PR China; College of Forestry Science and Technology, LiShui Vocational and Technical College, Lishui, 323000, PR China
| | - Weiwei Wang
- Department of Forest Resources Management, Faculty of Forestry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Wenxia Zheng
- College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, PR China
| | - John L Innes
- Department of Forest Resources Management, Faculty of Forestry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Guangyu Wang
- Department of Forest Resources Management, Faculty of Forestry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
| | - Futao Guo
- College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, PR China.
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Hong Y, Cao F, Fan MY, Lin YC, Gul C, Yu M, Wu X, Zhai X, Zhang YL. Impacts of chemical degradation of levoglucosan on quantifying biomass burning contribution to carbonaceous aerosols: A case study in Northeast China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 819:152007. [PMID: 34856277 DOI: 10.1016/j.scitotenv.2021.152007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 11/23/2021] [Accepted: 11/23/2021] [Indexed: 06/13/2023]
Abstract
Biomass burning (BB) is an important source of carbonaceous aerosols in Northeast China (NEC). Quantifying the original contribution of BB to organic carbon (OC) [BB-OC] can provide an essential scientific information for the policy-makers to formulate the control measures to improve the air quality in the NEC region. Daily PM2.5 samples were collected in the rural area of Changchun city over the NEC region from May 2017 to May 2018. In addition to carbon contents, BB tracers (e.g., levoglucosan and K+BB, defined as potassium from BB) were also determined, in order to investigate the relative contribution of BB-OC. The results showed that OC was the dominant (28%) components of PM2.5 during the sampling period. Higher concentrations of OC, levoglucosan, and K+BB were observed in the autumn followed by the winter, spring, and summer, indicating that the higher BB activities during autumn and winter in Changchun. By using the Bayesian mixing model, it was found that burning of crop residues were the dominant source (65-79%) of the BB aerosols in Changchun. During the sampling period, the aging in air mass (AAM) ratio was 0.14, indicating that ~86% of levoglucosan in Changchun was degraded. Without considering the degradation of levoglucosan in the atmosphere, the BB-OC ratios were 23%, 28%, 7%, and 4% in the autumn, winter, spring, and summer, respectively, which were 1.4-4.8 time lower than those (14-42%) with consideration of levoglucosan degradation. This illustrated that the relative contribution of BB to OC would be underestimated (~59%) without considering degradation effects of levoglucosan. Although some uncertainty was existed in our estimation, our results did highlight that the control of straw burning was an efficient way to decrease the airborne PM2.5, improving the air quality in the NEC plain.
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Affiliation(s)
- Yihang Hong
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, 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; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China.
| | - Mei-Yi Fan
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Yu-Chi Lin
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Chaman Gul
- Reading Academy, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China
| | - Mingyuan Yu
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Xia Wu
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Xiaoyao Zhai
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Yan-Lin Zhang
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
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Chen L, Xiong M. WITHDRAWN: The impact of industry cluster and environmental policies on residents' health risk evaluation using big data. Work 2021:WOR205374. [PMID: 34308889 DOI: 10.3233/wor-205374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Ahead of Print article withdrawn by publisher.
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Affiliation(s)
- Limin Chen
- Beijing Normal University, Zhuhai, China
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Somayajulu M, Ekanayaka S, McClellan SA, Bessert D, Pitchaikannu A, Zhang K, Hazlett LD. Airborne Particulates Affect Corneal Homeostasis and Immunity. Invest Ophthalmol Vis Sci 2020; 61:23. [PMID: 32301974 PMCID: PMC7401652 DOI: 10.1167/iovs.61.4.23] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Purpose To determine the effects of airborne particulate matter (PM) <2.5 µm in vitro and on the normal and Pseudomonas aeruginosa (PA)-infected cornea. Methods An MTT viability assay tested the effects of PM2.5 on mouse corneal epithelial cells (MCEC) and human corneal epithelial cells (HCET). MCEC were tested for reactive oxygen species using a 2′,7′-dichlorodihydrofluorescein assay; RT-PCR determined mRNA levels of inflammatory and oxidative stress markers in MCEC (HMGB1, toll-like receptor 2, IL-1β, CXCL2, GPX1, GPX2, GR1, superoxide dismutase 2, and heme oxygenase 1) and HCET (high mobility group box 1, CXCL2, and IL-1β). C57BL/6 mice also were infected and after 6 hours, the PM2.5 was topically applied. Disease was graded by clinical score and evaluated by histology, plate count, myeloperoxidase assay, RT-PCR, ELISA, and Western blot. Results After PM2.5 (25–200 µg/mL), 80% to 90% of MCEC and HCET were viable and PM exposure increased reactive oxygen species in MCEC and mRNA expression levels for inflammatory and oxidative stress markers in mouse and human cells. In vivo, the cornea of PA+PM2.5 exposed mice exhibited earlier perforation over PA alone (confirmed histologically). In cornea, plate counts were increased after PA+PM2.5, whereas myeloperoxidase activity was significantly increased after PA+PM2.5 over other groups. The mRNA levels for several proinflammatory and oxidative stress markers were increased in the cornea in the PA+PM2.5 over other groups; protein levels were elevated for high mobility group box 1, but not toll-like receptor 4 or glutathione reductase 1. Uninfected corneas treated with PM2.5 did not differ from normal. Conclusions PM2.5 triggers reactive oxygen species, upregulates mRNA levels of oxidative stress, inflammatory markers, and high mobility group box 1 protein, contributing to perforation in PA-infected corneas.
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