Ridership exceedance exposure risk: Novel indicators to assess PM2.5 health exposure of bike sharing riders
Identifying the fine particulate matter (PM2.5) exposure risk for bicycle riders is crucial for promoting the development of theory and technology in transportation-related air pollution assessment as well as urban health planning. Previous studies have employed daily mean PM2.5 concentrations and d...
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Veröffentlicht in: | Environmental research 2021-06, Vol.197, p.111020-111020, Article 111020 |
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description | Identifying the fine particulate matter (PM2.5) exposure risk for bicycle riders is crucial for promoting the development of theory and technology in transportation-related air pollution assessment as well as urban health planning. Previous studies have employed daily mean PM2.5 concentrations and designed routes to evaluate air pollution exposure risk. However, because the daily mean PM2.5 concentrations cannot fully illustrate the intra-day variations in PM2.5, which are typically higher than daily mean values, the adverse effects of PM2.5 concentrations remain underestimated. Moreover, the quantity and representativeness of monitoring samples make large spatial-scale and multi-temporal-scale analysis challenging. By defining hourly exceedance PM2.5 concentration and sharing bicycle rider data, two novel indicators were proposed in our study: exceedance exposure risk of PM2.5 for sharing bicycle riders (EPSR) and accumulative exceedance exposure risk of PM2.5 for sharing bicycle riders (AEPSR). Standard deviation ellipse analysis was conducted to investigate the multi-temporal variation of ESPR and AEPSR. A geographically weighted regression model was applied to quantify the relationship between city function zones and exceedance PM2.5 exposure risk for sharing bicycle riders. Results revealed that the mean values of EPSR and AEPSR during morning peak periods ranged between 0.109 min μg/m3 and 1.27 min μg/m3 and 6.83 min μg/m3 and 43.41 min μg/m3, respectively, whereas the mean values of EPSR and AEPSR during evening peak periods ranged between 0.19 min μg/m3 and 4.28 min μg/m3 and 14.67 min μg/m3 and 357.66 min μg/m3, respectively. This implied that sharing bicycle riders were exposed to higher PM2.5-related risks during the evening than in the morning. When considering the accumulative effects, the average centers of the AEPSR moved to the north side as compared to the average centers of the EPSR. Expanding areas of EPSR shrunk by 20.25 km2. This indicated that accumulative effects aggregated spatial clusters of exceedance PM2.5 exposure risk for sharing bicycle riders more tightly to the north of the study areas. Spatiotemporal variation of EPSR and AEPSR led us to investigate the mechanism behind this phenomenon. Spatial associations between city function zones and EPSR and AEPSR showed that sharing bicycle riders experienced more severe exceedance PM2.5 exposure risk around financial/corporations and leisure service areas, with R2 values of 0.33 and |
doi_str_mv | 10.1016/j.envres.2021.111020 |
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•Two novel indicators were proposed to evaluate exceedance PM2.5 exposure for sharing bicycle riders.•Accumulative effects shrunk the spatial distribution areas of exceedance exposure risk of PM2.5 for sharing bicycle riders (EPSR) by 20.25 km.•Specific urban function zones were considered to be associated with spatial patterns of EPSR and AEPSR.</description><identifier>ISSN: 0013-9351</identifier><identifier>EISSN: 1096-0953</identifier><identifier>DOI: 10.1016/j.envres.2021.111020</identifier><language>eng</language><publisher>Elsevier Inc</publisher><subject>Bike-sharing riders ; Exceedance exposure risk ; PM2.5 ; Spatiotemporal mapping</subject><ispartof>Environmental research, 2021-06, Vol.197, p.111020-111020, Article 111020</ispartof><rights>2021 Elsevier Inc.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c339t-5963e0d72e2bc73052c9c9153ae4919c0be3f5da67fc244d02c90a2cb144f2643</citedby><cites>FETCH-LOGICAL-c339t-5963e0d72e2bc73052c9c9153ae4919c0be3f5da67fc244d02c90a2cb144f2643</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.envres.2021.111020$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Cao, Zheng</creatorcontrib><creatorcontrib>Gao, Feng</creatorcontrib><creatorcontrib>Li, Shaoying</creatorcontrib><creatorcontrib>Wu, Zhifeng</creatorcontrib><creatorcontrib>Guan, Wenchuan</creatorcontrib><creatorcontrib>Ho, Hung Chak</creatorcontrib><title>Ridership exceedance exposure risk: Novel indicators to assess PM2.5 health exposure of bike sharing riders</title><title>Environmental research</title><description>Identifying the fine particulate matter (PM2.5) exposure risk for bicycle riders is crucial for promoting the development of theory and technology in transportation-related air pollution assessment as well as urban health planning. Previous studies have employed daily mean PM2.5 concentrations and designed routes to evaluate air pollution exposure risk. However, because the daily mean PM2.5 concentrations cannot fully illustrate the intra-day variations in PM2.5, which are typically higher than daily mean values, the adverse effects of PM2.5 concentrations remain underestimated. Moreover, the quantity and representativeness of monitoring samples make large spatial-scale and multi-temporal-scale analysis challenging. By defining hourly exceedance PM2.5 concentration and sharing bicycle rider data, two novel indicators were proposed in our study: exceedance exposure risk of PM2.5 for sharing bicycle riders (EPSR) and accumulative exceedance exposure risk of PM2.5 for sharing bicycle riders (AEPSR). Standard deviation ellipse analysis was conducted to investigate the multi-temporal variation of ESPR and AEPSR. A geographically weighted regression model was applied to quantify the relationship between city function zones and exceedance PM2.5 exposure risk for sharing bicycle riders. Results revealed that the mean values of EPSR and AEPSR during morning peak periods ranged between 0.109 min μg/m3 and 1.27 min μg/m3 and 6.83 min μg/m3 and 43.41 min μg/m3, respectively, whereas the mean values of EPSR and AEPSR during evening peak periods ranged between 0.19 min μg/m3 and 4.28 min μg/m3 and 14.67 min μg/m3 and 357.66 min μg/m3, respectively. This implied that sharing bicycle riders were exposed to higher PM2.5-related risks during the evening than in the morning. When considering the accumulative effects, the average centers of the AEPSR moved to the north side as compared to the average centers of the EPSR. Expanding areas of EPSR shrunk by 20.25 km2. This indicated that accumulative effects aggregated spatial clusters of exceedance PM2.5 exposure risk for sharing bicycle riders more tightly to the north of the study areas. Spatiotemporal variation of EPSR and AEPSR led us to investigate the mechanism behind this phenomenon. Spatial associations between city function zones and EPSR and AEPSR showed that sharing bicycle riders experienced more severe exceedance PM2.5 exposure risk around financial/corporations and leisure service areas, with R2 values of 0.33 and 0.35, respectively. This spatial association tended to be more significant during the evening peak periods. By developing two novel indicators, the increasing health threats for bicycle riders caused by exceedance PM2.5 were investigated in this study. The mechanism results should be included for developing mitigation strategies to alleviate the adverse effects of air pollution for public rider participators and achieving the goal of eco-health cities.
•Two novel indicators were proposed to evaluate exceedance PM2.5 exposure for sharing bicycle riders.•Accumulative effects shrunk the spatial distribution areas of exceedance exposure risk of PM2.5 for sharing bicycle riders (EPSR) by 20.25 km.•Specific urban function zones were considered to be associated with spatial patterns of EPSR and AEPSR.</description><subject>Bike-sharing riders</subject><subject>Exceedance exposure risk</subject><subject>PM2.5</subject><subject>Spatiotemporal mapping</subject><issn>0013-9351</issn><issn>1096-0953</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kE1PwzAMhiMEEmPwDzjkyKXFSdpO4YCEEF_S-BCCc5SlLsvWNSPuJvj3ZCoSN062Zb-v7YexUwG5AFGdL3LsthEplyBFLoQACXtsJEBXGehS7bMRgFCZVqU4ZEdEi1SKUsGILV99jZHmfs3xyyHWtnOY0nWgTUQePS0v-FPYYst9V3tn-xCJ94FbIiTiL48yL_kcbdvP_2Sh4TO_RE5zG333kWx2S47ZQWNbwpPfOGbvtzdv1_fZ9Pnu4fpqmjmldJ-VulII9USinLmJglI67XQ612KhhXYwQ9WUta0mjZNFUUPqg5VuJoqikVWhxuxs8F3H8LlB6s3Kk8O2tR2GDRlZgpRCFgnJmBXDqIuBKGJj1tGvbPw2AsyOrVmYga3ZsTUD2yS7HGSY3th6jIacx0Su9hFdb-rg_zf4Abl-hLw</recordid><startdate>202106</startdate><enddate>202106</enddate><creator>Cao, Zheng</creator><creator>Gao, Feng</creator><creator>Li, Shaoying</creator><creator>Wu, Zhifeng</creator><creator>Guan, Wenchuan</creator><creator>Ho, Hung Chak</creator><general>Elsevier Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>202106</creationdate><title>Ridership exceedance exposure risk: Novel indicators to assess PM2.5 health exposure of bike sharing riders</title><author>Cao, Zheng ; Gao, Feng ; Li, Shaoying ; Wu, Zhifeng ; Guan, Wenchuan ; Ho, Hung Chak</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c339t-5963e0d72e2bc73052c9c9153ae4919c0be3f5da67fc244d02c90a2cb144f2643</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Bike-sharing riders</topic><topic>Exceedance exposure risk</topic><topic>PM2.5</topic><topic>Spatiotemporal mapping</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cao, Zheng</creatorcontrib><creatorcontrib>Gao, Feng</creatorcontrib><creatorcontrib>Li, Shaoying</creatorcontrib><creatorcontrib>Wu, Zhifeng</creatorcontrib><creatorcontrib>Guan, Wenchuan</creatorcontrib><creatorcontrib>Ho, Hung Chak</creatorcontrib><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Environmental research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cao, Zheng</au><au>Gao, Feng</au><au>Li, Shaoying</au><au>Wu, Zhifeng</au><au>Guan, Wenchuan</au><au>Ho, Hung Chak</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Ridership exceedance exposure risk: Novel indicators to assess PM2.5 health exposure of bike sharing riders</atitle><jtitle>Environmental research</jtitle><date>2021-06</date><risdate>2021</risdate><volume>197</volume><spage>111020</spage><epage>111020</epage><pages>111020-111020</pages><artnum>111020</artnum><issn>0013-9351</issn><eissn>1096-0953</eissn><abstract>Identifying the fine particulate matter (PM2.5) exposure risk for bicycle riders is crucial for promoting the development of theory and technology in transportation-related air pollution assessment as well as urban health planning. Previous studies have employed daily mean PM2.5 concentrations and designed routes to evaluate air pollution exposure risk. However, because the daily mean PM2.5 concentrations cannot fully illustrate the intra-day variations in PM2.5, which are typically higher than daily mean values, the adverse effects of PM2.5 concentrations remain underestimated. Moreover, the quantity and representativeness of monitoring samples make large spatial-scale and multi-temporal-scale analysis challenging. By defining hourly exceedance PM2.5 concentration and sharing bicycle rider data, two novel indicators were proposed in our study: exceedance exposure risk of PM2.5 for sharing bicycle riders (EPSR) and accumulative exceedance exposure risk of PM2.5 for sharing bicycle riders (AEPSR). Standard deviation ellipse analysis was conducted to investigate the multi-temporal variation of ESPR and AEPSR. A geographically weighted regression model was applied to quantify the relationship between city function zones and exceedance PM2.5 exposure risk for sharing bicycle riders. Results revealed that the mean values of EPSR and AEPSR during morning peak periods ranged between 0.109 min μg/m3 and 1.27 min μg/m3 and 6.83 min μg/m3 and 43.41 min μg/m3, respectively, whereas the mean values of EPSR and AEPSR during evening peak periods ranged between 0.19 min μg/m3 and 4.28 min μg/m3 and 14.67 min μg/m3 and 357.66 min μg/m3, respectively. This implied that sharing bicycle riders were exposed to higher PM2.5-related risks during the evening than in the morning. When considering the accumulative effects, the average centers of the AEPSR moved to the north side as compared to the average centers of the EPSR. Expanding areas of EPSR shrunk by 20.25 km2. This indicated that accumulative effects aggregated spatial clusters of exceedance PM2.5 exposure risk for sharing bicycle riders more tightly to the north of the study areas. Spatiotemporal variation of EPSR and AEPSR led us to investigate the mechanism behind this phenomenon. Spatial associations between city function zones and EPSR and AEPSR showed that sharing bicycle riders experienced more severe exceedance PM2.5 exposure risk around financial/corporations and leisure service areas, with R2 values of 0.33 and 0.35, respectively. This spatial association tended to be more significant during the evening peak periods. By developing two novel indicators, the increasing health threats for bicycle riders caused by exceedance PM2.5 were investigated in this study. The mechanism results should be included for developing mitigation strategies to alleviate the adverse effects of air pollution for public rider participators and achieving the goal of eco-health cities.
•Two novel indicators were proposed to evaluate exceedance PM2.5 exposure for sharing bicycle riders.•Accumulative effects shrunk the spatial distribution areas of exceedance exposure risk of PM2.5 for sharing bicycle riders (EPSR) by 20.25 km.•Specific urban function zones were considered to be associated with spatial patterns of EPSR and AEPSR.</abstract><pub>Elsevier Inc</pub><doi>10.1016/j.envres.2021.111020</doi><tpages>1</tpages></addata></record> |
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subjects | Bike-sharing riders Exceedance exposure risk PM2.5 Spatiotemporal mapping |
title | Ridership exceedance exposure risk: Novel indicators to assess PM2.5 health exposure of bike sharing riders |
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