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Investigating Traffic Emission and Pollution with Big Data
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Investigating Traffic Emission and Pollution with Big Data

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Science and Engineering".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 5096

Special Issue Editor

Prof. Dr. Feng Lu

E-Mail Website
Guest Editor
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Interests: trajectory data mining; computational transportation science; natural language processing and knowledge graph

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to publish original researches or review articles that focus on state-of-the-art big data technologies used to investige environmental pollution caused by traffic activities. Traffic emissions contribute a large part of overall air quality and soil environment problems. They are a major source for a number of pollutants and greenhouse gases. It will further deteriorate living environment and result in public health risks. With the rapid development of sensor networks, big data acquisition, and analysis technologies, many novel researches to model and forecast traffic emissions in a fine-grained spatio-temporal resolution have emerged over the years. Furthermore, numerous scenario simulations have been conducted to predict the possible effects for the potential measures or policies to alleviate traffic pollutions. Traffic emissions and pollutions are undoubtedly relevant with a variety of human activities and are greatly influenced by economic and social situations. The complexity of social systems and human mobility, as well as the chemical reaction of emissions, require more cross-disciplinary approaches, in order to improve the accuracy and robustness of traffic emissions. In particular, we are interested in studies that involve the integration of GIS, remotely sensed imageries, crowd-sourced big data, traffic emission and diffusion models, spatiao-temporal data mining, and machine learning technologies.

Prof. Dr. Feng Lu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Prof. Dr. Feng Lu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • traffic emissions
  • pollutants
  • Big Data
  • spatio-temporal data mining
  • emission inventory
  • human mobility
  • public health risk
  • scenario simulation
  • GIS
  • remote sensing

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Published Papers (2 papers)

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Research

19 pages, 3470 KiB  
Article
Marginal Effects and Spatial Variations of the Impact of the Built Environment on Taxis’ Pollutant Emissions in Chengdu, China
by Guanwei Zhao, Zeyu Pan and Muzhuang Yang
Int. J. Environ. Res. Public Health 2022, 19(24), 16962; https://doi.org/10.3390/ijerph192416962 - 16 Dec 2022
Viewed by 1717
Abstract
Understanding the impact of the urban built environment on taxis’ emissions is crucial for sustainable transportation. However, the marginal effects and spatial heterogeneity of this impact is worth noting. To this end, we calculated the taxis’ emissions on weekdays and weekends in Chengdu, [...] Read more.
Understanding the impact of the urban built environment on taxis’ emissions is crucial for sustainable transportation. However, the marginal effects and spatial heterogeneity of this impact is worth noting. To this end, we calculated the taxis’ emissions on weekdays and weekends in Chengdu, China, and investigated the impact of the built environment on taxis’ emissions by applying multi-source data and several spatial regression models. The results showed that the taxis’ daily emissions on weekdays were higher than the emissions on weekends. The time heterogeneity of hourly taxis’ emissions was not significant, while the spatial heterogeneity of taxis’ emissions was significant. Except the HHI, the selected built environment variables both had a significant positive effect on taxis’ emissions on the global scale. There was a marginal effect of some built environment variables on taxis’ emissions, such as the density of bus stops and population density. The former exhibited an inhibitory effect on taxis’ 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’ 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’ pollutant emissions. Full article
(This article belongs to the Special Issue Investigating Traffic Emission and Pollution with Big Data)
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21 pages, 11197 KiB  
Article
The Impact of Community Shuttle Services on Traffic and Traffic-Related Air Pollution
by Zilong Zhao, Mengyuan Fang, Luliang Tang, Xue Yang, Zihan Kan and Qingquan Li
Int. J. Environ. Res. Public Health 2022, 19(22), 15128; https://doi.org/10.3390/ijerph192215128 - 16 Nov 2022
Cited by 1 | Viewed by 2954
Abstract
Community shuttle services have the potential to alleviate traffic congestion and reduce traffic pollution caused by massive short-distance taxi-hailing trips. However, few studies have evaluated and quantified the impact of community shuttle services on urban traffic and traffic-related air pollution. In this paper, [...] Read more.
Community shuttle services have the potential to alleviate traffic congestion and reduce traffic pollution caused by massive short-distance taxi-hailing trips. However, few studies have evaluated and quantified the impact of community shuttle services on urban traffic and traffic-related air pollution. In this paper, we propose a complete framework to quantitatively assess the positive impacts of community shuttle services, including route design, traffic congestion alleviation, and air pollution reduction. During the design of community shuttle services, we developed a novel method to adaptively generate shuttle stops with maximum service capacity based on residents’ origin–destination (OD) data, and designed shuttle routes with minimum mileage by genetic algorithm. For traffic congestion alleviation, we identified trips that can be shifted to shuttle services and their potential changes in traffic flow. The decrease in traffic flow can alleviate traffic congestion and indirectly reduce unnecessary pollutant emissions. In terms of environmental protection, we utilized the COPERT III model and the spatial kernel density estimation method to finely analyze the reduction in traffic emissions by eco-friendly transportation modes to support detailed policymaking regarding transportation environmental issues. Taking Chengdu, China as the study area, the results indicate that: (1) the adaptively generated shuttle stops are more responsive to the travel demands of crowds compared with the existing bus stops; (2) shuttle services can replace 30.36% of private trips and provide convenience for 50.2% of commuters; (3) such eco-friendly transportation can reduce traffic emissions by 28.01% overall, and approximately 42% within residential areas. Full article
(This article belongs to the Special Issue Investigating Traffic Emission and Pollution with Big Data)
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