Carlos M. González This email address is being protected from spambots. You need JavaScript enabled to view it., Carlos D. Gómez, Beatriz H. Aristizábal

Hydraulic Engineering and Environmental Research Group, Universidad Nacional de Colombia Sede Manizales, Cra 27 64-60 Bloque H Palogrande, Manizales, Colombia


Received: April 30, 2020
Revised: July 22, 2020
Accepted: August 10, 2020

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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González, C.M., Gómez, C.D. and Aristizábal, B.H. (2020). DROVE: An Algorithm for Spatial and Temporal Disaggregation of On-road Vehicle Emission Inventories. Aerosol Air Qual. Res. 20: 2765–2779.


  • DROVE is an algorithm for the disaggregation of on-road vehicle emissions.
  • DROVE allows a spatial emission disaggregation in a wide range of resolutions.
  • Including road type information improves the emission distribution.
  • Increasing spatial resolution allows detailed vehicular emission hotspots.
  • DROVE can be implemented in any region worldwide.


A key component of air quality management in urban areas is the analysis of pollutant emission distribution and hotspots, which are valuable information for developing emission reduction strategies and as input in air quality models. For vehicular emissions, this task is difficult because the sources are in constant movement and the availability of accurate and realistic vehicular activity information is scarce; a common issue in cities of emerging countries. Hence, exercises for estimating atmospheric pollutant emissions are developed only in a macro-scale way, without allocating in space and time the emissions. In this study, we present a new computational algorithm named DROVE, for the disaggregation of on-road vehicle emissions in space and time. DROVE is a free code developed in R and provides emission fluxes distribution from the estimation of disaggregation factors. It was designed with three possible approximations for spatial emissions disaggregation, considering the input information that would be available in the city: length of road segments (LRS), LRS + type of roads; and LRS + traffic flows. Two temporal distribution options are available for obtaining gridded hourly emissions. We evaluated the capabilities of DROVE for performing the PM10 emission distribution fluxes in the medium-sized cities of Manizales, Colombia, Antofagasta, Chile, and the megacity of Bogotá, Colombia. Results suggest that DROVE was able to allocate emission hotspots in zones of high traffic and main avenues (when information of the type of roads or traffic flow is available). Emissions distribution did not reflect this behavior when only LRS was used as input data, obtaining 50% of grid cells with percentage emission differences higher than 100% against the use of LRS + traffic flows. DROVE can be implemented in any region worldwide, could contribute with air quality management and provide disaggregated emission fluxes for air quality modeling.

Keywords: Emission inventories; Spatial-temporal disaggregation; On-road vehicular emissions.

Aerosol Air Qual. Res. 20 :2765 -2779 .  

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