Title
Quantifying and spatial disaggregation of air pollution emissions from ground transportation in a developing country context: Case study for the Lima Metropolitan Area in Peru
Date Issued
01 January 2020
Access level
metadata only access
Resource Type
journal article
Author(s)
Publisher(s)
Elsevier B.V.
Abstract
Ambient air pollution contributes approximately 3.7 million premature deaths annually worldwide with air pollution from ground transportation posing a significant threat in urban areas. This concern is especially relevant in cities with fast-growing economies in the developing countries, as is the case of Lima Metropolitan Area (LMA) in Peru. Currently, there is a limited understanding of the impacts of ground transportation emissions on air pollution and population health in the LMA. In this study we quantified air pollution emissions from ground transportation, by combining local transportation and meteorological data with emission factors determined by the United States Environmental Protection Agency's (US-EPA's) Motor Vehicle Emission Simulator (MOVES). Total annual emissions of carbon monoxide, nitrogen oxides, sulfur dioxide and particulate matter (PM2.5) were quantified, temporally resolved and then spatially disaggregated within the LMA study domain. Our study, therefore, provides an approach for quantifying transportation emissions for a large metropolitan area in a developing country where detailed data is not available. This research sets the need of future work aiming at understanding the impact of ground transportation emissions, air pollution levels and their subsequent effects on human health. Capsule: We provide a framework for computing and spatially disaggregating air pollution emissions from ground transportation in a rapidly growing economy in a developing country context.
Volume
698
Language
English
OCDE Knowledge area
Ciencias del medio ambiente
Subjects
Scopus EID
2-s2.0-85072053031
PubMed ID
Source
Science of the Total Environment
ISSN of the container
00489697
Sponsor(s)
This research was funded by the MIT International Science and Technology Initiatives (MISTI) and MISTI-Peru Universidad de Ingenieria y Tecnologia Seed Fund program. Also, this project was supported by the Senseable City Laboratory and the Energy Engineering Department at Universidad de Ingenieria y Tecnologia - UTEC .
Sources of information:
Directorio de Producción Científica
Scopus