| Identifying low-PM2.5 exposure commuting routes for cyclists through modeling with the random forest algorithm based on low-cost sensor measurements in three Asian cities | |
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| 년도 | 2022 |
| 날짜 | Feb |
| 페이지 / 학회지명 |
294:118597 / Environmental Pollution |
| 논문저자 | Tzong-Gang Wu 1, Yan-Da Chen 2, Bang-Hua Chen 3, Kouji H Harada 4, Kiyoung Lee 5, Furong Deng 6, Mark J Rood 7, Chu-Chih Chen 8, Cong-Thanh Tran 9, Kuo-Liong Chien 10, Tzai-Hung Wen 11, Chang-Fu Wu 12 |
| Link |
https://www.sciencedirect.com/science/article/abs/pii/S026974912102179…
248회 연결
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1 Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, No. 17, Xuzhou Rd, Taipei, 10055, Taiwan; Innovation and Policy Center for Population Health and Sustainable Environment, College of Public Health, National Taiwan University, No. 17, Xuzhou Rd, Taipei, 10055, Taiwan. 2 Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, No. 17, Xuzhou Rd, Taipei, 10055, Taiwan; Department of Health and Environmental Sciences, Kyoto University Graduate School of Medicine, Kyoto University, Yoshida-konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan. 3 Institute of Occupational Medicine and Industrial Hygiene, College of Public Health, National Taiwan University, No. 17, Xuzhou Rd, Taipei, 10055, Taiwan. 4 Department of Health and Environmental Sciences, Kyoto University Graduate School of Medicine, Kyoto University, Yoshida-konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan. 5 Department of Environmental Health Sciences, Graduate School of Public Health, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea. 6 Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing, 100191, China. 7 Department of Civil and Environmental Engineering, University of Illinois, 205 N. Mathews Ave., Urbana, IL, 61801, USA. 8 Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, 35, Keyan Road, Zhunan Town, Miaoli County, 35053, Taiwan. 9 University of Science, Vietnam National University Ho Chi Minh City, 227 Nguyen Van Cu Street, Dist. 5, Ho Chi Minh City, Viet Nam; Institute of Epidemiology and Preventive Medicine, National Taiwan University, No. 17, Xuzhou Rd, Taipei, 10055, Taiwan. 10 Institute of Epidemiology and Preventive Medicine, National Taiwan University, No. 17, Xuzhou Rd, Taipei, 10055, Taiwan. 11 Department of Geography, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, 10617, Taiwan. 12 Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, No. 17, Xuzhou Rd, Taipei, 10055, Taiwan; Innovation and Policy Center for Population Health and Sustainable Environment, College of Public Health, National Taiwan University, No. 17, Xuzhou Rd, Taipei, 10055, Taiwan. Electronic address: changfu@ntu.edu.tw. Abstract Cyclists can be easily exposed to traffic-related pollutants due to riding on or close to the road during commuting in cities. PM2.5 has been identified as one of the major pollutants emitted by vehicles and associated with cardiopulmonary and respiratory diseases. As routing has been suggested to reduce the exposures for cyclists, in this study, PM2.5 was monitored with low-cost sensors during commuting periods to develop models for identifying low exposure routes in three Asian cities: Taipei, Osaka, and Seoul. The models for mapping the PM2.5 in the cities were developed by employing the random forest algorithm in a two-stage modeling approach. The land use features to explain spatial variation of PM2.5 were obtained from the open-source land use database, OpenStreetMap. The total length of the monitoring routes ranged from 101.36 to 148.22 km and the average PM2.5 ranged from 13.51 to 15.40 μg/m³ among the cities. The two-stage models had the standard k-fold cross-validation (CV) R2 of 0.93, 0.74, and 0.84 in Taipei, Osaka, and Seoul, respectively. To address spatial autocorrelation, a spatial cross-validation approach applying a distance restriction of 100 m between the model training and testing data was employed. The over-optimistic estimates on the predictions were thus prevented, showing model CV-R2 of 0.91, 0.67, and 0.78 respectively in Taipei, Osaka, and Seoul. The comparisons between the shortest-distance and lowest-exposure routes showed that the largest percentage of reduced averaged PM2.5 exposure could reach 32.1% with the distance increases by 37.8%. Given the findings in this study, routing behavior should be encouraged. With the daily commuting trips expanded, the cumulative effect may become significant on the chronic exposures over time. Therefore, a route planning tool for reducing the exposures shall be developed and promoted to the public. Keywords: Asian city; Cyclist; PM2.5; Random forest; Routing; Spatial autocorrelation. |
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