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Yu Z, Sun Z, Liu L, Li C, Zhang X, Amat G, Ran M, Hu X, Xu Y, Zhao X, Zhou J. Environmental surveillance in Jinan city of East China (2014-2022) reveals improved air quality but remained health risks attributable to PM2.5-bound metal contaminants. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 343:123275. [PMID: 38163628 DOI: 10.1016/j.envpol.2023.123275] [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: 11/03/2023] [Revised: 12/22/2023] [Accepted: 12/29/2023] [Indexed: 01/03/2024]
Abstract
PM2.5-bound metal contaminants are associated with multiple chronic diseases in human. At global level, the contamination status has not been well controlled yet. Here we report findings from a long-term air pollution surveillance in Jinan city of Shandong, China. During 2014-2022, the dynamics and trends of PM2.5-bound heavy metal contaminants were monitored in an industrial area and a downtown area. The surveillance targets included: antimony (Sb), aluminum (Al), arsenic (As), beryllium (Be), cadmium (Cd), chromium (Cr), mercury (Hg), lead (Pb), manganese (Mn), nickel (Ni), selenium (Se). The human exposure and health risks were calculated and we found that the health risks of most contaminants showed peak values in autumn and winter. But Al, Mn, Hg and Be were found to result in highest health risk in spring or summer in the downtown area. In the industrial area we identified 100% alarming health index >1 (ranged from 1.12 to 3.35) in autumn and winter. In winter the total non-carcinogenic HI was all above 1 (peak value 2.21). Mn and As together posed >85% non-carcinogenic risk. As and Cd were ranked as major drivers of carcinogenic risks (5.84 × 10-6 and 2.78 × 10-6). Pd and Cd both showed non-negligible environmental levels but risk assessment model for their air-exposure associated non-carcinogenic risks are not yet available. This study updates air pollution data and status for air pollution status in China. This study provides valuable 9 year long-term reference to experimental and field studies in the related fields.
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Affiliation(s)
- Zhigang Yu
- Institute of Physical and Chemical Analysis, Jinan Municipal Center for Disease Control and Prevention, Jinan, Shandong, 250021, China.
| | - Zhan Sun
- Institute of Physical and Chemical Analysis, Jinan Municipal Center for Disease Control and Prevention, Jinan, Shandong, 250021, China.
| | - Lanzheng Liu
- Jinan Municipal Center for Disease Control and Prevention, Jinan, Shandong, 250021, China.
| | - Chao Li
- Shandong Academy of Occupational Health and Occupational Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, 250062, China.
| | - Xin Zhang
- Institute of Physical and Chemical Analysis, Jinan Municipal Center for Disease Control and Prevention, Jinan, Shandong, 250021, China.
| | - Gzalnur Amat
- School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250021, China.
| | - Mohan Ran
- School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250021, China.
| | - Xiaoyue Hu
- School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250021, China.
| | - Yunxiang Xu
- School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250021, China.
| | - Xiulan Zhao
- Department of Toxicology and Nutrition, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250021, China.
| | - Jun Zhou
- Department of Toxicology and Nutrition, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250021, China.
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Hang Y, Meng X, Li T, Wang T, Cao J, Fu Q, Dey S, Li S, Huang K, Liang F, Kan H, Shi X, Liu Y. Assessment of long-term particulate nitrate air pollution and its health risk in China. iScience 2022; 25:104899. [PMID: 36039292 PMCID: PMC9418855 DOI: 10.1016/j.isci.2022.104899] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 06/26/2022] [Accepted: 08/04/2022] [Indexed: 11/06/2022] Open
Abstract
Air pollution is a major environmental and public health challenge in China and the Chinese government has implemented a series of strict air quality policies. However, particulate nitrate (NO3−) concentration remains high or even increases at monitoring sites despite the total PM2.5 concentration has decreased. Unfortunately, it has been difficult to estimate NO3− concentration across China due to the lack of a PM2.5 speciation monitoring network. Here, we use a machine learning model incorporating ground measurements and satellite data to characterize the spatiotemporal patterns of NO3−, thereby understanding the disease burden associated with long-term NO3− exposure in China. Our results show that existing air pollution control policies are effective, but increased NO3− of traffic emissions offset reduced NO3− of industrial emissions. In 2018, the national mean mortality burden attributable to NO3− was as high as 0.68 million, indicating that targeted regulations are needed to control NO3− pollution in China. We build a NO3− model using machine learning techniques incorporating satellite data We estimate spatiotemporal variations of NO3− concentration in China from 2005–2018 In 2018, the national mean mortality burden attributable to NO3− was about 0.68 million Targeted regulations on vehicle emissions are needed to control NO3− pollution in China
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Affiliation(s)
- Yun Hang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Xia Meng
- School of Public Health, Fudan University, Shanghai 200032, China
| | - Tiantian 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
| | - Tijian Wang
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
| | - Junji Cao
- Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100101, China
| | - Qingyan Fu
- State Ecologic Environmental Scientific Observation and Research Station at Dianshan Lake, Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Sagnik Dey
- Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India
| | - Shenshen Li
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences, Beijing 100101, China
| | - Kan Huang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Fengchao Liang
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen 518055, China
| | - Haidong Kan
- School of Public Health, Fudan University, Shanghai 200032, China
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yang Liu
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
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Itazawa T, Kanatani KT, Hamazaki K, Inadera H, Tsuchida A, Tanaka T, Nakayama T, Go T, Onishi K, Kurozawa Y, Adachi Y, Konishi I, Heike T, Konishi Y, Sato K, Egawa M, Takahashi Y, Watanabe M, Yasumi R, Hirabayashi K, Morita M, Konishi K, Hirooka Y, Fukumoto S, Teshima R, Inoue T, Harada T, Kanzaki S, Maegaki Y, Ohno K, Koeda T, Amano H, Masumoto T. The impact of exposure to desert dust on infants' symptoms and countermeasures to reduce the effects. Allergy 2020; 75:1435-1445. [PMID: 31886894 DOI: 10.1111/all.14166] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 09/24/2019] [Accepted: 10/08/2019] [Indexed: 01/26/2023]
Abstract
BACKGROUND The association between particulate matter (PM), including desert dust, and allergic symptoms has not been well studied. We examined whether PM exacerbated nose/eye/respiratory symptoms in infants, with a focus on the desert dust element, and assessed possible countermeasures. METHODS We conducted a panel study of 1492 infants from October 2014 to July 2016 in 3 regions in Japan as an adjunct study of the Japan Environment and Children's Study. Infants' daily symptom scores and behaviors were acquired by web-based questionnaires sent to mothers, who answered within a day using mobile phones. Odds ratios (OR) for symptom development per increased fine PM or desert dust exposure were estimated. Regular use of medications and behaviors on the day of exposure were investigated as possible effect modifiers. RESULTS Infants developed nose/eye/respiratory symptoms significantly more often in accordance with fine particulate levels (adjusted OR per 10 µg/m3 increase: 1.04, 95% confidence interval [CI]: 1.01-1.07). A model including both fine particulates and desert dust showed reduced OR for fine particulates and robust OR for desert dust (adjusted OR per 0.1/km increase: 1.16, 95% CI: 1.09-1.23). An increased OR was observed both in infants who had previously wheezed and in those who had never wheezed. Receiving information on the particulate forecast, reducing time outdoors, closing windows, and regular use of leukotriene receptor antagonists were significant effect modifiers. CONCLUSIONS Transborder desert dust arrival increased the risk of nose/eye/respiratory symptoms development in infants. Regular use of leukotriene receptor antagonists and other countermeasures reduced the risk.
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Affiliation(s)
- Toshiko Itazawa
- Department of Pediatrics Faculty of Medicine University of Toyama Toyama Japan
| | - Kumiko T. Kanatani
- Japan Environment and Children's Study Kyoto Regional Center Kyoto University Graduate School of Medicine Kyoto Japan
| | - Kei Hamazaki
- Department of Public Health Faculty of Medicine University of Toyama Toyama Japan
| | - Hidekuni Inadera
- Department of Public Health Faculty of Medicine University of Toyama Toyama Japan
| | - Akiko Tsuchida
- Department of Public Health Faculty of Medicine University of Toyama Toyama Japan
| | - Tomomi Tanaka
- Department of Pediatrics Faculty of Medicine University of Toyama Toyama Japan
| | - Takeo Nakayama
- Department of Health Informatics Kyoto University School of Public Health Kyoto Japan
| | - Tohshin Go
- Japan Environment and Children's Study Kyoto Regional Center Kyoto University Graduate School of Medicine Kyoto Japan
| | - Kazunari Onishi
- Division of Environmental Health Graduate School of Public Health St.Luke's International University Tokyo Japan
- Division of Health Administration and Promotion Faculty of Medicine Tottori University Tottori Japan
| | - Yoichi Kurozawa
- Division of Health Administration and Promotion Faculty of Medicine Tottori University Tottori Japan
| | - Yuichi Adachi
- Department of Pediatrics Faculty of Medicine University of Toyama Toyama Japan
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Analyses of air pollution control measures and co-benefits in the heavily air-polluted Jinan city of China, 2013-2017. Sci Rep 2020; 10:5423. [PMID: 32214211 PMCID: PMC7096483 DOI: 10.1038/s41598-020-62475-0] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Accepted: 03/09/2020] [Indexed: 11/08/2022] Open
Abstract
China has made great efforts in air pollution control since 2013. However, there is a lack of evaluation of environmental, health and economic co-benefits associated with the national and local air pollution control measures at a city level. We analyzed local air pollution control policies and implementation in Jinan, one of the most heavily air-polluted cities in China between 2013 and 2017. We assessed the changes in exhaust emissions, air quality, mortality and morbidity of associated specific-diseases, and related economic benefits. We also projected the future scenarios of PM2.5 concentration dropped to 15 μg/m3. There were significant decreases in exhaust emissions of SO2 and NOx in Jinan during the study period. Annual reductions in ambient air pollution were 72.6% for SO2, 43.1% for PM2.5, and 34.2% for PM10. A total of 2,317 (95%CI: 1,533-2,842) premature deaths and 15,822 (95%CI: 8,734-23,990) related morbidity cases had been avoided in 2017, leading to a total of US$ 317.7 million (95%CI: 227.5-458.1) in economic benefits. Decreasing PM2.5 concentrations to 15 μg/m3 would result in reductions of 70% in total PM2.5-related non-accidental mortality and 95% in total PM2.5-related morbidity, which translates into US$ 1,289.5 million (95%CI: 825.8-1,673.6) in economic benefits. The national and local air pollution control measures have brought significant environmental, health and economic benefits to a previously heavy polluted Chinese city.
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Liu L, Wang X, Chen J, Xue L, Wang W, Wen L, Li D, Chen T. Understanding unusually high levels of peroxyacetyl nitrate (PAN) in winter in Urban Jinan, China. J Environ Sci (China) 2018; 71:249-260. [PMID: 30195683 DOI: 10.1016/j.jes.2018.05.015] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 05/15/2018] [Accepted: 05/16/2018] [Indexed: 06/08/2023]
Abstract
Peroxyacetyl nitrate (PAN), as a major secondary pollutant, has gained increasing worldwide attentions, but relevant studies in China are still quite limited. During winter of 2015 to summer of 2016, the ambient levels of PAN were measured continuously by an automatic gas chromatograph equipped with an electron capture detector (GC-ECD) analyzer at an urban site in Jinan (China), with related parameters including concentrations of O3, NO, NO2, PM2.5, HONO, the photolysis rate constant of NO2 and meteorological factors observed concurrently. The mean and maximum values of PAN concentration were (1.89 ± 1.42) and 9.61 ppbv respectively in winter, and (2.54 ± 1.44) and 13.47 ppbv respectively in summer. Unusually high levels of PAN were observed during severe haze episodes in winter, and the formation mechanisms of them were emphatically discussed. Study showed that high levels of PAN in winter were mainly caused by local accumulation and strong photochemical reactions during haze episodes, while mass transport played only a minor role. Accelerated photochemical reactions (compared to winter days without haze) during haze episodes were deduced by the higher concentrations but shorter lifetimes of PAN, which was further supported by the sufficient solar radiation in the photolysis band along with the high concentrations of precursors (NO2, VOCs) and HONO during haze episodes. In addition, significant PAN accumulation during calm weather of haze episodes was verified by meteorological data.
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Affiliation(s)
- Lu Liu
- Environment Research Institute, School of Environmental Science and Engineering, Shandong University, Ji'nan 250100, China
| | - Xinfeng Wang
- Environment Research Institute, School of Environmental Science and Engineering, Shandong University, Ji'nan 250100, China
| | - Jianmin Chen
- Environment Research Institute, School of Environmental Science and Engineering, Shandong University, Ji'nan 250100, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, China; Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University, Nanjing 210008, China.
| | - Likun Xue
- Environment Research Institute, School of Environmental Science and Engineering, Shandong University, Ji'nan 250100, China; Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University, Nanjing 210008, China
| | - Wenxing Wang
- Environment Research Institute, School of Environmental Science and Engineering, Shandong University, Ji'nan 250100, China
| | - Liang Wen
- Environment Research Institute, School of Environmental Science and Engineering, Shandong University, Ji'nan 250100, China
| | - Dandan Li
- Environment Research Institute, School of Environmental Science and Engineering, Shandong University, Ji'nan 250100, China
| | - Tianshu Chen
- Environment Research Institute, School of Environmental Science and Engineering, Shandong University, Ji'nan 250100, China
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Wang Y, Zu Y, Huang L, Zhang H, Wang C, Hu J. Associations between daily outpatient visits for respiratory diseases and ambient fine particulate matter and ozone levels in Shanghai, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2018; 240:754-763. [PMID: 29778811 DOI: 10.1016/j.envpol.2018.05.029] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Revised: 05/06/2018] [Accepted: 05/09/2018] [Indexed: 05/26/2023]
Abstract
Air pollution in China has been very serious during the recent decades. However, few studies have investigated the effects of short-term exposure to PM2.5 and O3 on daily outpatient visits for respiratory diseases. We examined the effects of PM2.5 and O3 on the daily outpatient visits for respiratory diseases, explored the sensitivities of different population subgroups and analyzed the relative risk (RR) of PM2.5 and O3 in different seasons in Shanghai during 2013-2016. The generalized linear model (GLM) was applied to analyze the exposure-response relationship between air pollutants (daily average PM2.5 and daily maximum 8-h average O3), and daily outpatient visits due to respiratory diseases. The sensitivities of males and females at the ages of 15-60 yr-old and 60+ yr-old to the pollutants were also studied for the whole year and for the cold and warm months, respectively. Finally, the results of the single-day lagged model were compared with that of the moving average lag model. At lag 0 day, the RR of respiratory outpatients increased by 0.37% with a 10 μg/m3 increase in PM2.5. Exposure to PM2.5 (RR, 1.0047, 95% CI, 1.0032-1.0062) was more sensitive for females than for males (RR, 1.0025, 95% CI, 1.0008-1.0041), and was more sensitive for the 15-60 yr-old (RR, 1.0041, 95% CI, 1.0027-1.0055) than the 60+ yr-old age group (RR, 1.0031, 95% CI, 1.0014-1.0049). O3 was not significantly associated with respiratory outpatient visits during the warm periods, but was negatively associated during the cold periods. PM2.5 was more significantly in the cold periods than that in the warm periods. The results indicated that control of PM2.5, compared to O3, in the cold periods would be more beneficial to the respiratory health in Shanghai. In addition, the single-day lagged model underestimated the relationship between PM2.5 and O3 and outpatient visits for respiratory diseases compared to the moving average lag model.
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Affiliation(s)
- Yiyi Wang
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China
| | - Yaqun Zu
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China
| | - Lin Huang
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China
| | - Hongliang Zhang
- Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, 77803, LA, USA.
| | - Changhui Wang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, 200072, China
| | - Jianlin Hu
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China.
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Onishi K, Sekiyama TT, Nojima M, Kurosaki Y, Fujitani Y, Otani S, Maki T, Shinoda M, Kurozawa Y, Yamagata Z. Prediction of health effects of cross-border atmospheric pollutants using an aerosol forecast model. ENVIRONMENT INTERNATIONAL 2018; 117:48-56. [PMID: 29727752 DOI: 10.1016/j.envint.2018.04.035] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 03/31/2018] [Accepted: 04/20/2018] [Indexed: 05/21/2023]
Abstract
Health effects of cross-border air pollutants and Asian dust are of significant concern in Japan. Currently, models predicting the arrival of aerosols have not investigated the association between arrival predictions and health effects. We investigated the association between subjective health symptoms and unreleased aerosol data from the Model of Aerosol Species in the Global Atmosphere (MASINGAR) acquired from the Japan Meteorological Agency, with the objective of ascertaining if these data could be applied to predicting health effects. Subjective symptom scores were collected via self-administered questionnaires and, along with modeled surface aerosol concentration data, were used to conduct a risk evaluation using generalized estimating equations between October and November 2011. Altogether, 29 individuals provided 1670 responses. Spearman's correlation coefficients were determined for the relationship between the proportion of the participants reporting the maximum score of two or more for each symptom and the surface concentrations for each considered aerosol species calculated using MASINGAR; the coefficients showed significant intermediate correlations between surface sulfate aerosol concentration and respiratory, throat, and fever symptoms (R = 0.557, 0.454, and 0.470, respectively; p < 0.01). In the general estimation equation (logit link) analyses, a significant linear association of surface sulfate aerosol concentration, with an endpoint determined by reported respiratory symptom scores of two or more, was observed (P trend = 0.001, odds ratio [OR] of the highest quartile [Q4] vs. the lowest [Q1] = 5.31, 95% CI = 2.18 to 12.96), with adjustment for potential confounding. The surface sulfate aerosol concentration was also associated with throat and fever symptoms. In conclusion, our findings suggest that modeled data are potentially useful for predicting health risks of cross-border aerosol arrivals.
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Affiliation(s)
- Kazunari Onishi
- Center for Birth Cohort Studies, Interdisciplinary Graduate School of Medicine, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi 409-3898, Japan.
| | - Tsuyoshi Thomas Sekiyama
- Meteorological Research Institute, 1-1 Nagamine, Tsukuba 305-0052, Japan; Arid Land Research Center, Tottori University, 1390 Hamasaka, Tottori 680-0001, Japan
| | - Masanori Nojima
- Center for Translational Research, The Institute of Medical Science Hospital, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku 108-8639, Japan
| | - Yasunori Kurosaki
- Arid Land Research Center, Tottori University, 1390 Hamasaka, Tottori 680-0001, Japan
| | - Yusuke Fujitani
- Division of Health Administration and Promotion, Department of Social Medicine, Faculty of Medicine, Tottori University, 86 Nishi-cho, Yonago 683-8503, Japan
| | - Shinji Otani
- International Platform for Dryland Research and Education, Tottori University, 1390 Hamasaka, Tottori 680-0001, Japan
| | - Takashi Maki
- Meteorological Research Institute, 1-1 Nagamine, Tsukuba 305-0052, Japan
| | - Masato Shinoda
- Graduate School of Environmental Studies, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan
| | - Youichi Kurozawa
- Division of Health Administration and Promotion, Department of Social Medicine, Faculty of Medicine, Tottori University, 86 Nishi-cho, Yonago 683-8503, Japan
| | - Zentaro Yamagata
- Center for Birth Cohort Studies, Interdisciplinary Graduate School of Medicine, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi 409-3898, Japan; Department of Health Sciences, School of Medicine, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi 409-3898, Japan
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