Relação entre concentrações de material particulado e localização de armazéns para o transporte de carga: análise de vulnerabilidade da população

Abstract

Urban Freight Transportation (UFT) plays a fundamental role in ensuring the availability of products for the population. However, its execution is associated with externalities, such as the emission of pollutants, and phenomena such as logistical sprawl, which is characterized by the location of warehouses in peripheral zones, which are areas often inhabited by vulnerable populations. Furthermore, environmental justice has been a topic of growing interest in global research. Its study can be applied to reducing social differences in exposure to pollutants. It is noteworthy that there is still a lack of further research in the Latin American context, including the description of what the difference is between the most vulnerable groups in terms of exposure to pollutants. In order to bring this line of research to Latin America, the aim of this work is to analyze the interrelationship between the location of wholesalers used for Urban Freight Transport (UFT) and how this logistical decision relates to the concentration of pollutants (Particulate Matter - PM2.5) in a large city in Brazil. In parallel, the aim is to study how this phenomenon impacts on urban communities. The method outlined consists of obtaining data on pollutants, wholesale locations and social vulnerability data. The relationship between the selected variables is analyzed both temporally and spatially. A database with precise information on historical locations throughout the city is used for the attack sites. With regard to PM2.5, a machine learning model calibrated with data from a monitoring station present at eight points in the city between 2020 and 2023 was developed. This model was then used to project the entire city using satellite data. Social vulnerability was measured using an index based on three variables: the Human Development Index (HDI), the number of hospital visits for respiratory diseases and registration in the National System for Vulnerable People (CadÚnico). The analysis is carried out spatially (neighborhoods and hexagons) and temporally (monthly, from 2000 to 2023). As not all databases are available for the entire period, complementary models such as backcasting were used. The analysis seeks to explore the relationship between the selected variables in a temporal and spatial manner, using classic indicators such as Moran and LISA, as well as time series indices such as the concentration and cointegration index. The results show that there is a relationship between UFT, PM2.5 concentration and social vulnerability in some neighborhoods, mainly in the western part of the city. In addition, the concentration of UFT increased in specific areas, and there is evidence of a temporal relationship between the concentration of UFT and the location of vulnerable populations, highlighting the need for public policies for a more equitable distribution of logistics activities, especially in the west of the city. It is hoped that the results can be applied to different contexts, as well as offering a relevant methodological contribution to data analysis at a local level.