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Xu J, Chen Y, Lu F, Chen L, Dong Z. The Association between Short-Term Exposure to PM 1 and Daily Hospital Admission and Related Expenditures in Beijing. TOXICS 2024; 12:393. [PMID: 38922073 PMCID: PMC11209456 DOI: 10.3390/toxics12060393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 05/16/2024] [Accepted: 05/18/2024] [Indexed: 06/27/2024]
Abstract
Ambient particulate matter (PM) pollution is a leading environmental health threat worldwide. PM with an aerodynamic diameter ≤ 1.0 μm, also known as PM1, has been implicated in the morbidity and mortality of several cardiorespiratory and cerebrovascular diseases. However, previous studies have mostly focused on analyzing fine PM (PM2.5) associated with disease metrics, such as emergency department visits and mortality, rather than ultrafine PM, including PM1. This study aimed to evaluate the association between short-term PM1 exposure and hospital admissions (HAs) for all-cause diseases, chronic obstructive pulmonary disease (COPD), and respiratory infections (RIs), as well as the associated expenditures, using Beijing as a case study. Here, based on air pollution and hospital admission data in Beijing from 2015 to 2017, we performed a time-series analysis and meta-analysis. It was found that a 10 μg/m3 increase in the PM1 concentration significantly increased all-cause disease HAs by 0.07% (95% Confidence Interval (CI): [0, 0.14%]) in Beijing between 2015 and 2017, while the COPD and RI-related HAs were not significantly associated with short-term PM1 exposure. Meanwhile, we estimated the attributable number of HAs and hospital expenditures related to all-cause diseases. This study revealed that an average of 6644 (95% CI: [351, 12,917]) cases of HAs were attributable to ambient PM1, which was estimated to be associated with a 106 million CNY increase in hospital expenditure annually (95% CI: [5.6, 207]), accounting for 0.32% (95% CI: [0.02, 0.62%]) of the annual total expenses. The findings reported here highlight the underlying impact of ambient PM pollution on health risks and economic burden to society and indicate the need for further policy actions on public health.
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Affiliation(s)
- Jingwen Xu
- School of Cancer and Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 1UL, UK
| | - Yan Chen
- Ganzhou People’s Hospital, Ganzhou 341000, China
| | - Feng Lu
- Beijing Municipal Health Big Data and Policy Research Center, Beijing 100034, China
| | - Lili Chen
- School of Public Health, Southeast University, Nanjing 210009, China
| | - Zhaomin Dong
- School of Materials Science and Engineering, Beihang University, Beijing 100191, China
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2
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Li J, Hua C, Ma L, Chen K, Zheng F, Chen Q, Bao X, Sun J, Xie R, Bianchi F, Kerminen VM, Petäjä T, Kulmala M, Liu Y. Key drivers of the oxidative potential of PM 2.5 in Beijing in the context of air quality improvement from 2018 to 2022. ENVIRONMENT INTERNATIONAL 2024; 187:108724. [PMID: 38735076 DOI: 10.1016/j.envint.2024.108724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 04/30/2024] [Accepted: 05/06/2024] [Indexed: 05/14/2024]
Abstract
The mass concentration of atmospheric particulate matter (PM) has been continuously decreasing in the Beijing-Tianjin-Hebei region. However, health endpoints do not exhibit a linear correlation with PM mass concentrations. Thus, it is urgent to clarify the prior toxicological components of PM to further improve air quality. In this study, we analyzed the long-term oxidative potential (OP) of water-soluble PM2.5, which is generally considered more effective in assessing hazardous exposure to PM in Beijing from 2018 to 2022 based on the dithiothreitol assay and identified the crucial drivers of the OP of PM2.5 based on online monitoring of air pollutants, receptor model, and random forest (RF) model. Our results indicate that dust, traffic, and biomass combustion are the main sources of the OP of PM2.5 in Beijing. The complex interactions of dust particles, black carbon, and gaseous pollutants (nitrogen dioxide and sulfur dioxide) are the main factors driving the OP evolution, in particular, leading to the abnormal rise of OP in Beijing in 2022. Our data shows that a higher OP is observed in winter and spring compared to summer and autumn. The diurnal variation of the OP is characterized by a declining trend from 0:00 to 14:00 and an increasing trend from 14:00 to 23:00. The spatial variation in OP of PM2.5 was observed as the OP in Beijing is lower than that in Shijiazhuang, while it is higher than that in Zhenjiang and Haikou, which is primarily influenced by the distribution of black carbon. Our results are of significance in identifying the key drivers influencing the OP of PM2.5 and provide new insights for advancing air quality improvement efforts with a focus on safeguarding human health in Beijing.
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Affiliation(s)
- Jinwen Li
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Chenjie Hua
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Li Ma
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Kaiyun Chen
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Feixue Zheng
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Qingcai Chen
- School of Environmental Science and Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China
| | - Xiaolei Bao
- Hebei Chemical & Pharmaceutical College, Shijiazhuang 050026, China
| | - Juan Sun
- Jiangsu Nanjing Environmental Monitoring Center, Nanjing 210019, China
| | - Rongfu Xie
- College of Ecology and Environment, Hainan University, Haikou 570228, China
| | - Federico Bianchi
- Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki 00014, Finland
| | - Veli-Matti Kerminen
- Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki 00014, Finland
| | - Tuukka Petäjä
- Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki 00014, Finland
| | - Markku Kulmala
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China; Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki 00014, Finland
| | - Yongchun Liu
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China.
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3
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Yang M, Wu QZ, Zhang YT, Leskinen A, Wang XF, Komppula M, Hakkarainen H, Roponen M, Jin NX, Tan WH, Xu SL, Lin LZ, Liu RQ, Zeng XW, Dong GH, Jalava PI. Toxicological evaluation and concentration of airborne PM 0.1 in high air pollution period in Guangzhou, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 921:171224. [PMID: 38402960 DOI: 10.1016/j.scitotenv.2024.171224] [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: 12/04/2023] [Revised: 01/30/2024] [Accepted: 02/21/2024] [Indexed: 02/27/2024]
Abstract
The emissions and exposure limits for airborne PM0.1 are lacking, with limited scientific data for toxicity. Therefore, we continuously monitored and calculated the number and mass concentrations of airborne PM0.1 in December 2017, January 2018 and March 2018 during the high pollution period in Guangzhou. We collected PM0.1 from the same period and analyzed their chemical components. A549, THP-1 and A549/THP-1 co-cultured cells were selected for exposure to PM0.1, and evaluated for toxicological responses. Our aims are to 1) measure and analyze the number and mass concentrations, and chemical components of PM0.1; 2) evaluate and compare PM0.1 toxicity to different airway cells models at different time points. Guangzhou had the highest mass concentration of PM0.1 in December 2017, while the number concentration was the lowest. Chemical components in PM0.1 vary significantly at different time periods, and the correlation between the chemical composition or source of PM0.1 and the mass and number concentration of PM0.1 was dissimilar. Exposure to PM0.1 disrupted cell membranes, impaired mitochondrial function, promoted the expression of inflammatory mediators, and interfered with DNA replication in the cell cycle. The damage caused by exposure to PM0.1 at different times exhibited variations across different types of cells. PM0.1 in March 2018 stimulated co-cultured cells to secrete more inflammatory mediators, and CMA was significantly related to the expression of them. Our study indicates that it is essential to monitor both the mass and number concentrations of PM0.1 throughout all seasons annually, as conventional toxicological experiments and the internal components of PM0.1 may not effectively reveal the health damages caused by elevated number levels of PM0.1.
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Affiliation(s)
- Mo Yang
- Department of Environmental and Biological Science, University of Eastern Finland, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland; Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Qi-Zhen Wu
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Yun-Ting Zhang
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Ari Leskinen
- Finnish Meteorological Institute, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland; Department of Technical Physics, University of Eastern Finland, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland
| | - Xin-Feng Wang
- Environment Research Institute, Shandong University, Qingdao 266237, China
| | - Mika Komppula
- Finnish Meteorological Institute, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland
| | - Henri Hakkarainen
- Department of Environmental and Biological Science, University of Eastern Finland, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland
| | - Marjut Roponen
- Department of Environmental and Biological Science, University of Eastern Finland, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland
| | - Nan-Xiang Jin
- A.I.Virtanen Institute for Molecular Sciences, University of Eastern Finland, Neulaniementie 2, 70210 Kuopio, Finland
| | - Wei-Hong Tan
- Department of Reproductive Medicine and Genetics Center, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, China
| | - Shu-Li Xu
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Li-Zi Lin
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Ru-Qing Liu
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiao-Wen Zeng
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - Guang-Hui Dong
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - Pasi I Jalava
- Department of Environmental and Biological Science, University of Eastern Finland, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland
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4
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Pouri N, Karimi B, Kolivand A, Mirhoseini SH. Ambient dust pollution with all-cause, cardiovascular and respiratory mortality: A systematic review and meta-analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168945. [PMID: 38042201 DOI: 10.1016/j.scitotenv.2023.168945] [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: 08/21/2023] [Revised: 11/12/2023] [Accepted: 11/25/2023] [Indexed: 12/04/2023]
Abstract
A severe health crisis has been well-documented regarding dust particle exposure. We aimed to present the risk of all-cause, cardiovascular, and respiratory mortality due to particulate matter (PM) exposure during non-dust and dust storm events by performing a meta-analysis. A systematic review of the literature was conducted by an online search of the databases (Google Scholar, Web of Science, Scopus, and PubMed) with no restrictions according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines until December 2022. We performed a random-effects model to compute the pooled rate ratio (RR) of mortality with 95 % confidence intervals (CI). The Office of Health Assessment and Translation (OHAT) risk of bias rating tool was prepared to assess the quality of the individual study. The registration number in PROSPERO was CRD42023423212. We found a 16 % (95 % CI: 0.7 %, 24 %) increase in all-cause, 25 % (95 % CI: 14 %, 37 %) increase in cardiovascular, and 18 % (95 % CI: 13 %, 22 %) increase in respiratory mortality per 10 μg/m3 increment in dust exposure. Furthermore, the RRs per 10 μg/m3 increment in PM10-2.5 were 1.046 (95 % CI: 1.019, 1.072)¸ 1.085 (95 % CI: 1.045, 1.0124), and 1.089 (95 % CI: 0.939, 1.24) for all-cause, cardiovascular, and respiratory mortality, respectively. PM10 during dust days significantly increased the all-cause (1.013, 95 % CI: 1.007, 1.018) cardiovascular mortality risk (1.014, 95 % CI: 1.009, 1.02). We also found significant evidence for all-cause, cardiovascular, and respiratory mortality among females and the elderly age group due to dust particle (PM10-2.5 and PM10) exposure. Our results provided significant evidence about high concentrations of PM10-2.5 and PM10 during dust storm events related to mortality risk.
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Affiliation(s)
- Nasrin Pouri
- Students Research Committee, Arak University of Medical Sciences, Arak, Iran
| | - Behrooz Karimi
- Department of Environmental Health Engineering, Arak University of Medical Sciences, Arak, Iran.
| | - Ali Kolivand
- Department of Environmental Health Engineering, Arak University of Medical Sciences, Arak, Iran
| | - Seyed Hamed Mirhoseini
- Department of Environmental Health Engineering, Arak University of Medical Sciences, Arak, Iran
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5
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Kearns KA, Naeher LP, McCracken JP, Boyd Barr D, Saikawa E, Hengstermann M, Mollinedo E, Panuwet P, Yakimavets V, Lee GE, Thompson LM. Estimating personal exposures to household air pollution and plastic garbage burning among adolescent girls in Jalapa, Guatemala. CHEMOSPHERE 2024; 348:140705. [PMID: 37981014 PMCID: PMC10714129 DOI: 10.1016/j.chemosphere.2023.140705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 11/10/2023] [Accepted: 11/11/2023] [Indexed: 11/21/2023]
Abstract
Waste collection services are uncommon in rural areas of low-resource countries, causing waste accumulation and subsequent dumping and burning of garbage. Air pollution from household garbage burning, including plastics, has been observed in Jalapa, Guatemala in addition to household air pollution (HAP) from cooking. Adolescent girls often help with these cooking and household tasks, but little is known about their exposures. We characterized 24-h exposures to HAP and household garbage burning in adolescent girls by measuring fine particulate matter (PM2.5), black carbon (BC), urinary biomarkers of polycyclic aromatic hydrocarbons (PAHs), bisphenol A (BPA), and phthalates. We recruited 60 girls between 13 and 17 years of age who helped with cooking activities and lived with participants of the Household Air Pollution Intervention Network (HAPIN) trial. We recruited n = 30 girls each from the control (wood-burning stove) and intervention (liquefied petroleum gas stove) arms. We also measured real-time kitchen concentrations of BC in 20 homes (33%). PM2.5 and BC were measured in n = 21 control and n = 20 intervention participants. Median concentrations of personal PM2.5 and BC and kitchen BC were lower (p < 0.05) in the intervention arm by 87%, 80%, and 85%, respectively. PAH metabolite concentrations were lower (p < 0.001) for all nine metabolites in intervention (n = 26) compared to control participants (n = 29). Urinary BPA concentrations were 66% higher in participants who reported using cosmetics (p = 0.02), and phthalate concentrations were 63% higher in participants who had reported using hair products during the sample period (p = 0.05). Our results suggest that gas stoves can reduce HAP exposures among adolescents who are not primary cooks at home. Biomarkers of plastic exposure were not associated with intervention status, but some were elevated compared to age- and sex-matched participants of the National Health and Nutrition Examination Survey (NHANES).
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Affiliation(s)
- Katherine A Kearns
- University of Georgia, Department of Environmental Health Science, College of Public Health, Athens, GA, USA
| | - Luke P Naeher
- University of Georgia, Department of Environmental Health Science, College of Public Health, Athens, GA, USA
| | - John P McCracken
- University of Georgia, Department of Environmental Health Science, College of Public Health, Athens, GA, USA; Center for Health Studies, Universidad del Valle de Guatemala, Guatemala City, Guatemala
| | - Dana Boyd Barr
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Eri Saikawa
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Mayari Hengstermann
- Center for Health Studies, Universidad del Valle de Guatemala, Guatemala City, Guatemala
| | - Erick Mollinedo
- University of Georgia, Department of Environmental Health Science, College of Public Health, Athens, GA, USA; Center for Health Studies, Universidad del Valle de Guatemala, Guatemala City, Guatemala
| | - Parinya Panuwet
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Volha Yakimavets
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Grace E Lee
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Lisa M Thompson
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA.
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6
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Wang Y, Liu Q, Tian Z, Cheng B, Guo X, Wang H, Zhang B, Xu Y, Sun L, Hu B, Chen G, Sheng J, Liang C, Tao F, Wei J, Yang L. Short-term effects of ambient PM 1, PM 2.5, and PM 10 on internal metal/metalloid profiles in older adults: A distributed lag analysis in China. ENVIRONMENT INTERNATIONAL 2023; 182:108341. [PMID: 38006770 DOI: 10.1016/j.envint.2023.108341] [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: 07/29/2023] [Revised: 10/24/2023] [Accepted: 11/20/2023] [Indexed: 11/27/2023]
Abstract
There is limited evidence linking exposure to ambient particulate matter (PM) with internal doses of metals and metalloids (metal(loid)s). This study aimed to evaluate the effects of short-term exposure to ambient PM on urine metal(loid)s among Chinese older adults. Biological monitoring data of 15 urine metal(loid)s collected in 3, 970 community-dwelling older adults in Fuyang city, Anhui Province, China, from July to September 2018, were utilized. PMs with an aerodynamic diameter ≤ 1 µm (PM1), ≤ 2.5 µm (PM2.5), and ≤ 10 µm (PM10) up to eight days before urine collection were estimated by space-time extremely randomized trees (STET) model. Residential greenness was reflected by Normalized Difference Vegetation Index (NDVI). We used generalized additive model (GAM) combined with distributed lag linear/non-linear models (DLMs/DLNMs) to estimate the associations between short-term PM exposure and urine metal(loid)s. The results suggested that the cumulative exposures to PM1, PM2.5, or PM10 over two days (lag0-1 days) before urine collection were associated with elevated urine metal(loid)s in DLMs, while exhibited linear or "inverted U-shaped" relationships with seven urine metal(loid)s in DLNMs, including Gallium (Ga), Arsenic (As), Aluminum (Al), Magnesium (Mg), Calcium (Ca), Uranium (U), and Barium (Ba). Aforementioned results indicated robust rather than spurious associations between PMs and these seven metal(loid)s. After standardizations for three PMs, PM1 was the greatest contributor to U, PM2.5 made the greatest contributions to Ga, As, Al, and Ba, and PM10 contributed the most to Mg and Ca. Furthermore, the effects of three PMs on urine Ga, As, Al, Mg, Ca, and Ba were reduced when exposed to higher levels of NDVI. Overall, short-term exposures to ambient PMs contribute to elevated urinary metal(loid) levels in older adults, and three PMs exhibit various contributions to different urine metal(loid)s. Moreover, residential greenness may attenuate the effects of PMs on urine metal(loid)s.
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Affiliation(s)
- Yuan Wang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China; Scientific Research Center in Preventive Medicine, School of Public Health, Anhui Medical University, Hefei 230032, Anhui, China
| | - Qiang Liu
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China; Scientific Research Center in Preventive Medicine, School of Public Health, Anhui Medical University, Hefei 230032, Anhui, China
| | - Ziwei Tian
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China; Scientific Research Center in Preventive Medicine, School of Public Health, Anhui Medical University, Hefei 230032, Anhui, China
| | - Beijing Cheng
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing 210009, Jiangsu, China
| | - Xianwei Guo
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China
| | - Hongli Wang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China
| | - Bo Zhang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China
| | - Yan Xu
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China
| | - Liang Sun
- Fuyang Center for Diseases Prevention and Control, Fuyang, Anhui 236069, China
| | - Bing Hu
- Fuyang Center for Diseases Prevention and Control, Fuyang, Anhui 236069, China
| | - Guimei Chen
- School of Health Services Management, Anhui Medical University, Hefei, Anhui 230032, China
| | - Jie Sheng
- Scientific Research Center in Preventive Medicine, School of Public Health, Anhui Medical University, Hefei 230032, Anhui, China
| | - Chunmei Liang
- School of Public Health, Department of Hygiene Inspection and Quarantine, Anhui Medical University, Hefei, Anhui 230032, China
| | - Fangbiao Tao
- Anhui Provincial Key Laboratory of Population Health and Aristogenics, Hefei 230032, Anhui, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA.
| | - Linsheng Yang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China; Scientific Research Center in Preventive Medicine, School of Public Health, Anhui Medical University, Hefei 230032, Anhui, China.
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7
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Yu YQ, Zhu T. Effects of endogenous and exogenous reductants in lung fluid on the bioaccessible metal concentration and oxidative potential of ultrafine particles. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 882:163652. [PMID: 37094683 DOI: 10.1016/j.scitotenv.2023.163652] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 03/14/2023] [Accepted: 04/18/2023] [Indexed: 05/03/2023]
Abstract
Health risk posed by ultrafine particles (UFPs) is potentially increased by reducing substances present in lung fluid, although knowledge of the underlying mechanisms is insufficient. Here, UFPs mainly consisting of metals and quinones were prepared. The reducing substances examined included lung endogenous and exogenous reductants. UFPs were extracted in simulated lung fluid containing reductants. Extracts were used to analyze metrics relevant to health effects, including the bioaccessible metal concentration (MeBA) and oxidative potential (OPDTT). The MeBA of Mn (974.5-9896.9 μg L-1) was higher than those of Cu (155.0-599.6 μg L-1) and Fe (79.9-500.9 μg L-1). Correspondingly, UFPs containing Mn had higher OPDTT (2.07-12.0 pmol min-1 μg-1) than those containing Cu (2.03-7.11 pmol min-1 μg-1) and Fe (1.63-5.34 pmol min-1 μg-1). Endogenous and exogenous reductants can increase MeBA and OPDTT, and the increments were generally higher for composite than pure UFPs. Positive correlations between OPDTT and MeBA of UFPs in the presence of most reductants emphasized the importance of the bioaccessible metal fraction in UFPs for inducing oxidative stress by reactive oxygen species (ROS)-generating reactions between quinones, metals, and lung reductants. Present findings provide novel insight into the toxicity and health risks of UFPs.
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Affiliation(s)
- Ya-Qi Yu
- BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; School of Environmental Science and Engineering, Qingdao University, Qingdao 266071, P.R. China
| | - Tong Zhu
- BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
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8
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Yang M, Zeng HX, Wang XF, Hakkarainen H, Leskinen A, Komppula M, Roponen M, Wu QZ, Xu SL, Lin LZ, Liu RQ, Hu LW, Yang BY, Zeng XW, Dong GH, Jalava P. Sources, chemical components, and toxicological responses of size segregated urban air PM samples in high air pollution season in Guangzhou, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 865:161092. [PMID: 36586693 DOI: 10.1016/j.scitotenv.2022.161092] [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: 09/28/2022] [Revised: 12/16/2022] [Accepted: 12/17/2022] [Indexed: 06/17/2023]
Abstract
The sources, sizes, components, and toxicological responses of particulate matter (PM) have demonstrated remarkable spatiotemporal variability. However, associations between components, sources, and toxicological effects in different-sized PM remain unclear. The purposes of this study were to 1) determine the sources of PM chemical components, 2) investigate the associations between components and toxicology of PM from Guangzhou high air pollution season. We collected size-segregated PM samples (PM10-2.5, PM2.5-1, PM1-0.2, PM0.2) from December 2017 to March 2018 in Guangzhou. PM sources and components were analyzed. RAW264.7 mouse macrophages were treated with PM samples for 24 h followed by measurements of toxicological responses. The concentrations of PM10-2.5 and PM1-0.2 were relatively high in all samples. Water-soluble ions and PAHs were more abundant in smaller-diameter PM, while metallic elements were more enriched in larger-diameter PM. Traffic exhaust, soil dust, and biomass burning/petrochemical were the most important sources of PAHs, metals and ions, respectively. The main contributions to PM were soil dust, coal combustion, and biomass burning/petrochemical. Exposure to PM10-2.5 induced the most significant reduction of cell mitochondrial activity, oxidative stress and inflammatory response, whereas DNA damage, an increase of Sub G1/G0 population, and impaired cell membrane integrity were most evident with PM1-0.2 exposure. There were moderate or strong correlations between most single chemicals and almost all toxicological endpoints as well as between various toxicological outcomes. Our findings highlight those various size-segregated PM-induced toxicological effects in cells, and identify chemical components and sources of PM that play the key role in adverse intracellular responses. Although fine and ultrafine PM have attracted much attention, the inflammatory damage caused by coarse PM cannot be ignored.
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Affiliation(s)
- Mo Yang
- Department of Environmental and Biological Science, University of Eastern Finland, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland; Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Hui-Xian Zeng
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xin-Feng Wang
- Environment Research Institute, Shandong University, Qingdao 266237, China
| | - Henri Hakkarainen
- Department of Environmental and Biological Science, University of Eastern Finland, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland
| | - Ari Leskinen
- Finnish Meteorological Institute, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland; Department of Applied Physics, University of Eastern Finland, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland
| | - Mika Komppula
- Finnish Meteorological Institute, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland
| | - Marjut Roponen
- Department of Environmental and Biological Science, University of Eastern Finland, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland
| | - Qi-Zhen Wu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Shu-Li Xu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Li-Zi Lin
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Ru-Qing Liu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Li-Wen Hu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Bo-Yi Yang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiao-Wen Zeng
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Guang-Hui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - Pasi Jalava
- Department of Environmental and Biological Science, University of Eastern Finland, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland
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Lv S, Liu X, Li Z, Lu F, Guo M, Liu M, Wei J, Wu Z, Yu S, Li S, Li X, Gao W, Tao L, Wang W, Xin J, Guo X. Causal effect of PM 1 on morbidity of cause-specific respiratory diseases based on a negative control exposure. ENVIRONMENTAL RESEARCH 2023; 216:114746. [PMID: 36347395 DOI: 10.1016/j.envres.2022.114746] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 10/27/2022] [Accepted: 11/04/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Extensive studies have linked PM2.5 and PM10 with respiratory diseases (RD). However, few is known about causal association between PM1 and morbidity of RD. We aimed to assess the causal effects of PM1 on cause-specific RD. METHODS Hospital admission data were obtained for RD during 2014 and 2019 in Beijing, China. Negative control exposure and extreme gradient boosting with SHapley Additive exPlanation was used to explore the causality and contribution between PM1 and RD. Stratified analysis by gender, age, and season was conducted. RESULTS A total of 1,183,591 admissions for RD were recorded. Per interquartile range (28 μg/m3) uptick in concentration of PM1 corresponded to a 3.08% [95% confidence interval (CI): 1.66%-4.52%] increment in morbidity of total RD. And that was 4.47% (95% CI: 2.46%-6.52%) and 0.15% (95% CI: 1.44%-1.78%), for COPD and asthma, respectively. Significantly positive causal associations were observed for PM1 with total RD and COPD. Females and the elderly had higher effects on total RD, COPD, and asthma only in the warm months (Z = 3.03, P = 0.002; Z = 4.01, P < 0.001; Z = 3.92, P < 0.001; Z = 2.11, P = 0.035; Z = 2.44, P = 0.015). Contribution of PM1 ranked first, second and second for total RD, COPD, and asthma among air pollutants. CONCLUSION PM1 was causally associated with increased morbidity of total RD and COPD, but not causally associated with asthma. Females and the elderly were more vulnerable to PM1-associated effects on RD.
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Affiliation(s)
- Shiyun Lv
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China
| | - Xiangtong Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China
| | - Zhiwei Li
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China
| | - Feng Lu
- Beijing Municipal Health Commission Information Center, Beijing, 100034, China
| | - Moning Guo
- Beijing Municipal Health Commission Information Center, Beijing, 100034, China
| | - Mengmeng Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China; National Institute for Data Science in Health and Medicine, Capital Medical University, Beijing, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA
| | - Zhiyuan Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China
| | - Siqi Yu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China
| | - Shihong Li
- Department of Respiratory, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Xia Li
- Department of Mathematics and Statistics, La Trobe University, Melbourne, 3086, Australia
| | - Wenkang Gao
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Lixin Tao
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China
| | - Wei Wang
- School of Medical Sciences and Health, Edith Cowan University, WA6027, Perth, Australia
| | - Jinyuan Xin
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.
| | - Xiuhua Guo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China; National Institute for Data Science in Health and Medicine, Capital Medical University, Beijing, China.
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