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Guan X, Meng X, Zhong G, Zhang Z, Wang C, Xiao Y, Fu M, Zhao H, Zhou Y, Hong S, Xu X, Bai Y, Kan H, Chen R, Wu T, Guo H. Particulate matter pollution, polygenic risk score and mosaic loss of chromosome Y in middle-aged and older men from the Dongfeng-Tongji cohort study. JOURNAL OF HAZARDOUS MATERIALS 2024; 471:134315. [PMID: 38678703 DOI: 10.1016/j.jhazmat.2024.134315] [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: 12/01/2023] [Revised: 04/04/2024] [Accepted: 04/14/2024] [Indexed: 05/01/2024]
Abstract
Mosaic loss of chromosome Y (mLOY) is the most common somatic alteration as men aging and may reflect genome instability. PM exposure is a major health concern worldwide, but its effects with genetic factors on mLOY has never been investigated. Here we explored the associations of PM2.5 and PM10 exposure with mLOY of 10,158 males measured via signal intensity of 2186 probes in male-specific chromosome-Y region from Illumina array data. The interactive and joint effects of PM2.5 and PM10 with genetic factors and smoking on mLOY were further evaluated. Compared with the lowest tertiles of PM2.5 levels in each exposure window, the highest tertiles in the same day, 7-, 14-, 21-, and 28-day showed a 0.005, 0.006, 0.007, 0.007, and 0.006 decrease in mLRR-Y, respectively (all P < 0.05), with adjustment for age, BMI, smoking pack-years, alcohol drinking status, physical activity, education levels, season of blood draw, and experimental batch. Such adverse effects were also observed in PM10-mLOY associations. Moreover, the unweighted and weighted PRS presented significant negative associations with mLRR-Y (both P < 0.001). Participants with high PRS and high PM2.5 or PM10 exposure in the 28-day separately showed a 0.018 or 0.019 lower mLRR-Y level [β (95 %CI) = -0.018 (-0.023, -0.012) and - 0.019 (-0.025, -0.014), respectively, both P < 0.001], when compared to those with low PRS and low PM2.5 or PM10 exposure. We also observed joint effects of PM with smoking on exacerbated mLOY. This large study is the first to elucidate the impacts of PM2.5 exposure on mLOY, and provides key evidence regarding the interactive and joint effects of PM with genetic factors on mLOY, which may promote understanding of mLOY development, further modifying and increasing healthy aging in males.
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Affiliation(s)
- Xin Guan
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Xia Meng
- Department of Environment Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Guorong Zhong
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Zirui Zhang
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Chenming Wang
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Yang Xiao
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Ming Fu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Hui Zhao
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Yuhan Zhou
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Shiru Hong
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Xuedan Xu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Yansen Bai
- Institute for Chemical Carcinogenesis, School of Public Health, Guangzhou Medical University, Xinzao, Panyu District, Guangzhou 511436, China
| | - Haidong Kan
- Department of Environment Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Renjie Chen
- Department of Environment Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Huan Guo
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China.
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Chen Z, Gao Y, Xia F, Bi C, Mo J. Formation kinetics of SVOC organic films and their impact on child exposure in indoor environments. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168970. [PMID: 38043806 DOI: 10.1016/j.scitotenv.2023.168970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 11/08/2023] [Accepted: 11/27/2023] [Indexed: 12/05/2023]
Abstract
We conducted an SVOC mass transfer and child-exposure modeling analysis considering the combined sorption of multiple SVOCs containing DnBP, BBP, DEHP, DINP and DINCH in indoor environments. A mechanistic model was applied to describe the organic film formation, and a partition-coefficient-prediction model was originally developed for the realistic organic films. The characteristics of film formation on impermeable surfaces were examined based on three different assumptions: the widely-used constant Kns,im assumption, Koa assumption, and the proposed Kom assumption (predicted specifically for the realistic organic films in this study). After long-term SVOC sorption, the organic film reached increasing equilibrium gradually under constant Kns,im assumption. While under Koa and Kom assumption, organic films exhibited nearly linear increases on surfaces, the trends of which agreed well with field studies. However, the film thicknesses calculated under Kom assumption with larger film partition coefficients were approximately twice larger than those under Koa assumption. Meanwhile, Horizontal surfaces with higher deposition rates of particle-phase SVOCs exhibited larger velocities of film growth compared to vertical surfaces. Under the Kom assumption, exposures of hazardous SVOCs for a 3-year-old child increased by 87.5 %-198.7 % even with the weekly cleaning of indoor impermeable surfaces, carpet and cloth. This study is anticipated to provide valuable insights into the film-forming characteristics of multiple SVOCs and the accompanying significant health risks to human beings in indoor environments.
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Affiliation(s)
- Zhuo Chen
- Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Department of Building Science, Tsinghua University, Beijing 100084, China
| | - Yilun Gao
- Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Department of Building Science, Tsinghua University, Beijing 100084, China
| | - Fanxuan Xia
- Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Department of Building Science, Tsinghua University, Beijing 100084, China
| | - Chenyang Bi
- Aerodyne Research Inc., Billerica, Massachusetts, 01821, USA
| | - Jinhan Mo
- College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China; Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Department of Building Science, Tsinghua University, Beijing 100084, China; Key Laboratory of Coastal Urban Resilient Infrastructures (Shenzhen University), Ministry of Education, Shenzhen 518060, China; Key Laboratory of Eco Planning & Green Building (Tsinghua University), Ministry of Education, Beijing 100084, China; State Key Laboratory of Subtropical Building and Urban Science, Guangzhou 510641, China.
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Qi J, Wang X, Fan L, Gong S, Wang X, Wang C, Li L, Liu H, Cao Y, Liu M, Han X, Su L, Yao X, Tysklind M, Wang X. Levels, distribution, childhood exposure assessment, and influencing factors of polybrominated diphenyl ethers (PBDEs) in household dust from nine cities in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 874:162612. [PMID: 36871734 DOI: 10.1016/j.scitotenv.2023.162612] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 02/20/2023] [Accepted: 02/28/2023] [Indexed: 06/18/2023]
Abstract
Household dust is an important source of premature exposure to polybrominated diphenyl ethers (PBDEs), especially for children. In this onsite study, 246 dust samples were collected from 224 households in nine Chinese cities during 2018-2019. Questionnaires were administered to explore the association between household-related information and PBDEs in household dust. The median concentration of Σ12PBDEs in household dust from 9 cities was 138 ng/g (94-227 ng/g), with the arithmetic mean of 240 ± 401 ng/g. Among the nine cities, the highest median concentration of Σ12PBDEs in household dust was found in Mianyang (295.57 ng/g), while the lowest was found in Wuxi (23.15 ng/g). BDE-71 was the most dominant congener, ranging from 42.08 % to 98.15 % of the 12 PBDE congeners among 9 cities. Three potential sources for the indoor environment were Penta-BDE, Octa-BDE commercial products, and photolytic bromine from Deca-BDEs based on the largest contribution (81.24 %). Under the moderate exposure scenario, the exposure levels through ingestion and dermal absorption for children were 7.30 × 10-1 ng/kg BW/day and 3.26 × 10-2 ng/kg BW/day, respectively. Temperature, CO2, years of residence, income, family size, household size, use of computers, heating, use of insecticide, and use of humidifiers were influential factors for PBDE concentrations in household dust. Based on the evidence of the correlation between PBDEs and these household parameters, it can be applied to reduce PBDE concentrations in household dust, which is a basis for controlling PBDEs pollution in Chinese households and protecting population health.
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Affiliation(s)
- Jing Qi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province 210000, China
| | - Xiaoli Wang
- Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Lin Fan
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Shuhan Gong
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Xinqi Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Chong Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Li Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Hang Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yun Cao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Mengmeng Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Xu Han
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Liqin Su
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Xiaoyuan Yao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Mats Tysklind
- Department of Chemistry, Umea University, SE-901 87 Umea, Sweden
| | - Xianliang Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province 210000, China.
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Cheng Y, Yin J, Yang L, Xu M, Lu X, Huang W, Dai G, Sun G. Ambient air pollutants in the first trimester of pregnancy and birth defects: an observational study. BMJ Open 2023; 13:e063712. [PMID: 36948563 PMCID: PMC10040071 DOI: 10.1136/bmjopen-2022-063712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/24/2023] Open
Abstract
OBJECTIVES As current studies on the relationships between air pollutants exposure during the first trimester and birth defects were not fully elucidated, this study aimed to assess the association between selected air pollutants and birth defects. DESIGN An observational study. PARTICIPANTS We obtained 70 854 singletons with gestational age <20 weeks who were delivered at a large maternal and child healthcare centre in Wuhan, China. OUTCOME MEASURES Birth defects data and daily average concentration of ambient particulate matter ≤10 µm diameter (PM10), PM ≤2.5 µm diameter (PM2.5), sulfur dioxide (SO2) and nitrogen dioxide (NO2) were obtained. Logistic regression analysis was applied to assess the association between maternal air pollutants exposure during first trimester and total birth defects, congenital heart defects (CHDs), limb defects and orofacial clefts with adjustments of potential covariates. RESULTS There were a total of 1352 birth defect cases included in this study, with a prevalence of 19.08‰. Maternal exposed to high concentrations of PM10, PM2.5, NO2 and SO2 in the first trimester were significantly associated with elevated ORs of birth defects (ORs ranged from 1.13 to 1.23). Additionally, for male fetuses, maternal exposed to high PM2.5 concentration was associated with an elevated odd of CHDs (OR 1.27, 95% CI 1.06 to 1.52). In the cold season, the ORs of birth defects were significantly increased among women exposed to PM2.5 (OR 1.64, 95% CI 1.41 to 1.91), NO2 (OR 1.22, 95% CI 1.08 to 1.38) and SO2 (OR 1.26, 95% CI 1.07 to 1.47). CONCLUSIONS This study showed unfavourable effects of air pollutants exposure during the first trimester on birth defects. Especially, the association between maternal PM2.5 exposure and CHDs was only observed among male fetuses, and stronger effects of PM2.5, NO2 and SO2 exposure on birth defects were observed in the cold season.
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Affiliation(s)
- Yao Cheng
- Obstetrics Department, Maternal and Child Health Hospital of Hubei Province, Wuhan, China
| | - Jieyun Yin
- Department of Epidemiology and Health Statistics, Medical College of Soochow University, Suzhou, China
| | - Lijun Yang
- Obstetrics Department, Maternal and Child Health Hospital of Hubei Province, Wuhan, China
| | - Man Xu
- School of Nursing, Hubei University of Chinese Medicine, Wuhan, China
| | - Xinfeng Lu
- Medical Record Department, Maternal and Child Health Hospital of Hubei Province, Wuhan, China
| | - Wenting Huang
- Science and Education Department, Maternal and Child Health Hospital of Hubei Province, Wuhan, China
| | - Guohong Dai
- Health Care Department, Maternal and Child Health Hospital of Hubei Province, Wuhan, China
| | - Guoqiang Sun
- Obstetrics Department, Maternal and Child Health Hospital of Hubei Province, Wuhan, China
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Shi W, Zhang T, Li Y, Huang Y, Luo L. Association between household air pollution from solid fuel use and risk of chronic diseases and their multimorbidity among Chinese adults. ENVIRONMENT INTERNATIONAL 2022; 170:107635. [PMID: 36413929 DOI: 10.1016/j.envint.2022.107635] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 10/21/2022] [Accepted: 11/14/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Given the increasing burden of chronic conditions, multimorbidity is now a priority for public health systems worldwide. However, the relationship between household air pollution (HAP) exposure with multimorbidity remains unclear. METHODS We used three waves data (2011, 2013, and 2015) including 19,295 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study, to investigate the association between HAP exposure from solid fuel use for heating and cooking with the risk of chronic multimorbidity. Multimorbidity was defined as the coexistence of two or more of 15 chronic diseases (hypertension, diabetes, dyslipidemia, heart disease, stroke, cardiovascular disease, chronic lung disease, asthma, kidney disease, liver disease, digestive disease, cancer, psychiatric disease, memory-related disease, and arthritis). Multiple logistic regression investigated the association between solid fuel use for heating and cooking, separately or simultaneously, with the risk of multimorbidity. Poisson regression with quasi-likelihood estimation explored whether solid fuel exposure could increase the number of morbidities. Stratified analyses and sensitivity analyses examined the effect modification and robustness of the association. RESULTS Of the 19,295 participants (mean age: 58.9 years), 40.9 % have multimorbidity. Compared with participants who used clean fuels for heating and cooking, the risk was higher in mixed fuel (adjusted odds ratio, aOR = 1.26, 95 %CI:1.16-1.36) and solid fuel users (aOR = 1.81, 1.67-1.98) separately. HAP from solid fuel use was positively associated with an increased number of morbidities (adjusted β = 0.329, 0.290 to 0.368), after controlling for confounders. Those living in a one-story building, with poor household cleanliness have a higher risk of multimorbidity. No significant modifications of those associations by the socio-demographic and behaviour characteristics was observed. CONCLUSIONS HAP from solid fuel use is associated with a high risk of chronic multimorbidity in Chinese adults. Our findings provide important implications for reducing chronic disease burden by restricting solid fuel use.
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Affiliation(s)
- Wenming Shi
- School of Public Health, Fudan University, Shanghai 200032, China.
| | - Tiantian Zhang
- School of Social Development and Public Policy, Fudan University, Shanghai 200433, China
| | - Yongzhen Li
- Children's Hospital of Fudan University, Shanghai 201100, China
| | - Yonggang Huang
- Department of Blood Transfusion, Tongling People's Hospital, Tongling 244000, Anhui, China
| | - Li Luo
- School of Public Health, Fudan University, Shanghai 200032, China; Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
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Xu J, Zhang Q, Su Z, Liu Y, Yan T, Zhang Y, Wang T, Wei X, Chen Z, Hu G, Chen T, Jia G. Genetic damage and potential mechanism exploration under different air pollution patterns by multi-omics. ENVIRONMENT INTERNATIONAL 2022; 170:107636. [PMID: 36423397 DOI: 10.1016/j.envint.2022.107636] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 11/02/2022] [Accepted: 11/14/2022] [Indexed: 06/16/2023]
Abstract
Ambient air pollution was classified as carcinogenic to humans (Group 1) for lung cancer. DNA damage was an important first step in the process of carcinogenesis, and could also be induced by air pollution. In this study, intratracheal instillation and real-time air exposure system were combined to establish SHP (short-term high-level PM2.5) and LLPO (long-term low-level PM2.5 and O3) exposure patterns, respectively. Hierarchical levels of genetic biomarkers were analyzed to explore DNA damage effects in rats. Representative DNA repair genes from different repair pathways were selected to explore the relative expression levels. The methylation level of differentially expressed repair genes were also determined. Besides, miRNA sequencing and non-targeted metabolomic analysis were performed in rat lungs. KEGG and multi-omics analysis were used to explore the potential mechanism of genetic damage under different air pollution patterns. We found that LLPO exposure induced DSBs and chromosome damage. SHP exposure could induce DSBs and DNA oxidative damage, and the effects of genetic damage under this pollution pattern could be repaired by natural repair. Repair genes involved in two pattern were different. SHP exposure could induce higher methylation levels of RAD51, which might be a potential epigenetic mechanism for high-level PM2.5 induced down-regulated expression of RAD51 and DSBs. Besides, 29 overlapped alterations in metabolic pathways were identified by metabolomic and miRNA sequencing, including purine metabolism and pyrimidine metabolism after LLPO exposure. Differential miRNAs expression in lung tissue were associated with apoptosis, DNA damage and damage repair. We concluded that under different air pollution patterns, DNA damage biomarkers and activated targets of DNA damage repair network were both different. The genetic damage effects caused by high-level short-term PM2.5 can be alleviated by natural repair. We provided possible mechanisms by multi-omics which could explain the increased carcinogenic risk caused by air pollution.
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Affiliation(s)
- Jiayu Xu
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100083, China
| | - Qiaojian Zhang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100083, China
| | - Zekang Su
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100083, China
| | - Yu Liu
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100083, China
| | - Tenglong Yan
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100083, China
| | - Yali Zhang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100083, China
| | - Tiancheng Wang
- Department of Clinical Laboratory, Third Hospital of Peking University, Beijing 100083, China
| | - Xuetao Wei
- Department of Toxicology, School of Public Health, Peking University, Beijing 100083, China
| | - Zhangjian Chen
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100083, China
| | - Guiping Hu
- School of Medical Science and Engineering, Beihang University, Beijing 100191, China
| | - Tian Chen
- School of Public Health and Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, China
| | - Guang Jia
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100083, China.
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Zhu YD, Li X, Fan L, Li L, Wang J, Yang WJ, Wang L, Yao XY, Wang XL. Indoor air quality in the primary school of China-results from CIEHS 2018 study. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 291:118094. [PMID: 34517175 DOI: 10.1016/j.envpol.2021.118094] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 08/06/2021] [Accepted: 08/31/2021] [Indexed: 06/13/2023]
Abstract
Indoor air quality ((IAQ) in classrooms was associated with the daily exposure of school-age children who are particularly vulnerable to air pollutants exposure, while few data exist to evaluate classroom indoor air quality nationwide in China. The subsample of the CIEHS 2018 study was performed in 66 classrooms of 22 primary schools nationwide in China. Temperature, relative humidity, PM2.5, PM10, CO2, CO, formaldehyde concentrations, bacteria and fungi were detected in all classrooms by using the instruments that meet the specified accuracy. The ratios of indoor to outdoor (I/O) of PM2.5 were calculated in each classroom to identify whether the indoor environment the pollutants comes from outdoors. The indoor PM2.5, PM10, CO, HCHO, bacteria and fungi GM concentration are 47.40 μg/m3, 72.91 μg/m3, 0.37 mg/m3, 0.02 mg/m3, 347.51 CFU/m3 and 362.76 CFU/m3, respectively. We observed that there were 66.5%, 52.6%, 22.4%, 1.8%, and 9.6% of the classrooms that exceeded the guideline values of PM2.5, PM10, CO2, HCHO, and bacteria, respectively. It should be attention that all of the classroom's PM2.5 concentrations in Shijiazhuang and Nanning, PM10 concentrations in Nanning, CO2 concentration in Lanzhou were exceeded the suggested values. Bacteria contamination in Shijiazhuang's classrooms is also serious. All classroom CO concentrations meet the requirement. The results indicated that classroom indoor PM2.5 was significantly positively correlated with indoor PM10 and CO2, while was negative correlated with temperature, CO, and fungi. Our results suggest that indoor air pollution in classrooms was a severe problem in Chinese primary schools. It is necessary to strengthen ventilation in the classroom to improve indoor air quality. What's more, a healthy learning environment should be created for primary school students.
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Affiliation(s)
- Yuan-Duo Zhu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Xu Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Lin Fan
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Li Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Jiao Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Wen-Jing Yang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Lin Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Xiao-Yuan Yao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Xian-Liang Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
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