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

摘要

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 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. (C) 2019 Elsevier B.V. All rights reserved.