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However, the marginal effects and spatial heterogeneity of this impact is worth noting. To this end, we calculated the taxis\u2019 emissions on weekdays and weekends in Chengdu, China, and investigated the impact of the built environment on taxis\u2019 emissions by applying multi-source data and several spatial regression models. The results showed that the taxis\u2019 daily emissions on weekdays were higher than the emissions on weekends. The time heterogeneity of hourly taxis\u2019 emissions was not significant, while the spatial heterogeneity of taxis\u2019 emissions was significant. Except the HHI, the selected built environment variables both had a significant positive effect on taxis\u2019 emissions on the global scale. There was a marginal effect of some built environment variables on taxis\u2019 emissions, such as the density of bus stops and population density. The former exhibited an inhibitory effect on taxis\u2019 emissions only when it was greater than 9 stops\/km2, while the latter showed an inhibitory effect only in the range between 16,000 people\/km2 and 22,000 people\/km2. There were some spatial variations in the effects of built environment factors on taxis\u2019 emissions, with HHI, road density, and accommodation service facilities density showing the most significant variation. The marginal effect and spatial variation of the impact needs to be considered when developing strategies to reduce taxis\u2019 pollutant emissions.<\/jats:p>","DOI":"10.3390\/ijerph192416962","type":"journal-article","created":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T05:55:43Z","timestamp":1671429343000},"page":"16962","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Marginal Effects and Spatial Variations of the Impact of the Built Environment on Taxis\u2019 Pollutant Emissions in Chengdu, China"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3311-9062","authenticated-orcid":false,"given":"Guanwei","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zeyu","family":"Pan","sequence":"additional","affiliation":[{"name":"School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muzhuang","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,16]]},"reference":[{"key":"ref_1","unstructured":"Energy Research Institute Group (2012). 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