TY - JOUR
T1 - Optimization model for urban air quality policy design
T2 - A case study in Latin America
AU - Sefair, Jorge A.
AU - Espinosa, Mónica
AU - Behrentz, Eduardo
AU - Medaglia, Andrés L.
N1 - Funding Information:
This study was developed within the Contract 1040 of 2008 between the local environmental authority, the transit company Transporte Tercer Milenio TransMilenio S. A. and Universidad de los Andes in the framework of Bogotá's Air Quality Plan. We appreciate all the technical support provided by the local environmental authority and other official entities during the development of the analyses. We are thankful to the researchers and professors from the School of Engineering, the Business School, and the School of Economics at Universidad de los Andes: Juan M. Benavides, Juan P. Bocarejo, Margarita Canal, Natalia Franco, Ivan D. Lobo, Oscar A. Pardo, Mauricio Sánchez, Lida M. Avila, Juan J. Castillo, Maria F. Cely, Juan F. Franco, Juan C.F. Márquez, Diana C. Obando, Juan P. Orjuela, and Edgar A. Virgez. We would also like to thank FICO for providing us with Xpress-MP licenses under the Academic Partner Program subscribed with Universidad de los Andes.
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/11
Y1 - 2019/11
N2 - Air pollution is a major problem caused by urban growth and poses a high risk to human health. To mitigate the negative impact of pollution, some cities have implemented air quality strategies that regulate emissions from multiple sources. However, when such strategies are applied in isolation they may fail to comply with stringent environmental goals. To support the development of comprehensive urban air quality policy, we propose an optimization model that suggests a portfolio of mitigation actions that captures realistic aspects of air quality policy-making such as implementation cost, pollution goals, interdependencies between alternatives, and managerial and regulatory constraints. We illustrate the advantages of our model with a real case study in Bogotá, Colombia's capital and one of the largest cities of Latin America, where new legislation established a PM10 air quality standard. To achieve the environmental goal, our model suggests an optimal portfolio consisting of six mitigation actions targeting mobile and stationary sources. Interventions in the transport sector alone generate 70% of the emissions reduction. The PM10 goal is achieved with a net incremental cost of US$1 billion with respect to the no-intervention scenario. The optimization model and results presented in this article were formally adopted as the official air quality policy in the city.
AB - Air pollution is a major problem caused by urban growth and poses a high risk to human health. To mitigate the negative impact of pollution, some cities have implemented air quality strategies that regulate emissions from multiple sources. However, when such strategies are applied in isolation they may fail to comply with stringent environmental goals. To support the development of comprehensive urban air quality policy, we propose an optimization model that suggests a portfolio of mitigation actions that captures realistic aspects of air quality policy-making such as implementation cost, pollution goals, interdependencies between alternatives, and managerial and regulatory constraints. We illustrate the advantages of our model with a real case study in Bogotá, Colombia's capital and one of the largest cities of Latin America, where new legislation established a PM10 air quality standard. To achieve the environmental goal, our model suggests an optimal portfolio consisting of six mitigation actions targeting mobile and stationary sources. Interventions in the transport sector alone generate 70% of the emissions reduction. The PM10 goal is achieved with a net incremental cost of US$1 billion with respect to the no-intervention scenario. The optimization model and results presented in this article were formally adopted as the official air quality policy in the city.
KW - Air pollution
KW - Air quality
KW - Integrated assessment modeling
KW - PM
KW - Urban pollution
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U2 - 10.1016/j.compenvurbsys.2019.101385
DO - 10.1016/j.compenvurbsys.2019.101385
M3 - Article
AN - SCOPUS:85070763236
SN - 0198-9715
VL - 78
JO - Computers, Environment and Urban Systems
JF - Computers, Environment and Urban Systems
M1 - 101385
ER -