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Air Quality-Related Sustainable Transportation Planning and Optimization in Smart Cities

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Special Issue Editors

Prof. Dr. Pedro José Pérez-Martínez

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Guest Editor

School of Civil Engineering, Architecture and Urban Design, University of Campinas, Campinas 13083-889, Brazil
Interests: atmospheric sciences; urban air pollution monitoring and characterization; aerosol optical properties; air quality and human health

Prof. Dr. Regina Maura De Miranda

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Guest Editor

School of Arts, Sciences, and Humanities, University of São Paulo, São Paulo 03828-000, Brazil
Interests: atmospheric sciences; urban air pollution monitoring and characterization; aerosol optical properties; air quality and human health

Special Issue Information

Dear Colleagues,

Air quality related diseases represent an unprecedented global health crisis and the effects may be associated with environmental and socio-economic factors. Traffic-related atmospheric emissions of greenhouse gases and toxic air pollutants are a serious environmental problem that affects climate change and air quality in smart cities. Many current planning models and policies around the world ignore the potential impact of general exposure to anthropogenic emissions and underestimate local exposure, especially at significant locations such as traffic hotspots.

This Special Issue aims to develop innovative methodologies using econometric models for vehicular activities and socioeconomic parameters, and demonstrate their applicability to urban smart agglomerations. Our aim is to find non-linear relationships between long-term transport mobility data, sociodemographic parameters and cardio and respiratory diseases. Large biases in regional studies that rely on pollution enhancement as a linear predictor of disease growth based on dose–response relationships are expected. This subject will provide a basis for establishing sound climate change policies in other areas, such as public health and urban planning.

Potential topics include, but are not limited to, sustainable mobility, transport geography, human health and exposure, urban air pollution, universal accessibility, transport energy and climate change, and transport planning and smart cities.

We look forward to receiving your contributions.

Prof. Dr. Pedro José Pérez-Martínez
Prof. Dr. Regina Maura De Miranda
Guest Editors

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21 pages, 5595 KiB

Open AccessArticle

Speed Limits in São Paulo and the Actions for Road Safety and Air Quality

by Douglas Gonçalves, Regina Maura de Miranda, Celio Daroncho, Janini de Oliveira Dias da Silva, Fabrício Rodrigues Teixeira, João Augusto Dunck Dalosto and Pedro José Pérez-Martínez

Sustainability 2024, 16(18), 8065; https://doi.org/10.3390/su16188065 - 15 Sep 2024

Viewed by 311

Abstract

Studies carried out have revealed that every day around three thousand people lose their lives in the world due to traffic accidents and poor air quality. Large cities, with their millions of inhabitants and vehicles, face many problems relating to vehicular traffic. In 2015, the speed limit was modified on several roads in the city of São Paulo, Brazil. However, in 2017, the speed limits were increased again, but not on all previous routes. This study analyzed the impact of this change on the number of accidents and pollutant concentrations, over a period of ten years, comparing the periods before and after the implementation of the measure, using real data collected and provided by the authorities of the city and the state transit and environmental companies, on more than forty routes and two nearby air-quality stations. The results showed a clear reduction in the number of accidents without victims on the roads of the city of São Paulo, starting in 2010. Although the restrictive measures imposed by government officials may have contributed to the decrease in the number of accidents, the number of fatalities has not changed so much. Air pollution has not improved substantially with speed changes, as new speed increases have been linked to new episodes of congestion. The average number of fatalities due to accidents has been increasing since 2010 and accidents are becoming more serious. The application of a general linear statistical model (GLM) estimated the impact of the speed reduction policy in terms of the number of injuries avoided per month: 43.4 and 14.1 on other roads and on the Pinheiros highways, respectively. The results highlight the need for a constant data collection by the authorities in cities with high vehicle traffic. The important temporal time trend in terms of reduction of injuries, but not in terms of fatalities and air quality, shows the need to apply joint public policies, not only speed reduction, but also the use of new technologies and raising drivers’ awareness of the problem. Full article

(This article belongs to the Special Issue Air Quality-Related Sustainable Transportation Planning and Optimization in Smart Cities)

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18 pages, 59151 KiB

Open AccessArticle

Methodology for the Identification of Vehicle Congestion Based on Dynamic Clustering

by Gary Reyes, Roberto Tolozano-Benites, Laura Lanzarini, César Estrebou, Aurelio F. Bariviera and Julio Barzola-Monteses

Sustainability 2023, 15(24), 16575; https://doi.org/10.3390/su152416575 - 6 Dec 2023

Cited by 1 | Viewed by 1325

Abstract

Addressing sustainable mobility in urban areas has become a priority in today’s society, given the growing population and increasing vehicular flow in these areas. Intelligent Transportation Systems have emerged as innovative and effective technological solutions for addressing these challenges. Research in this area has become crucial, as it contributes not only to improving mobility in urban areas but also to positively impacting the quality of life of their inhabitants. To address this, a dynamic clustering methodology for vehicular trajectory data is proposed which can provide an accurate representation of the traffic state. Data were collected for the city of San Francisco, a dynamic clustering algorithm was applied and then an indicator was applied to identify areas with traffic congestion. Several experiments were also conducted with different parameterizations of the forgetting factor of the clustering algorithm. We observed that there is an inverse relationship between forgetting and accuracy, and the tolerance allows for a flexible margin of error that allows for better results in precision. The results showed in terms of precision that the dynamic clustering methodology achieved high match rates compared to the congestion indicator applied to static cells. Full article

(This article belongs to the Special Issue Air Quality-Related Sustainable Transportation Planning and Optimization in Smart Cities)

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