Linking of built environment inequalities with air quality: A case study

Agudelo-Castañeda, Dayana Milena; Arellana, Julián; Gamero, Wendy Beatriz Morgado; Paoli, Fabrício De; Portz, Luana

doi:10.1016/j.trd.2023.103668

Cited by 8 publications

(1 citation statement)

References 78 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Limitations include that traditional air quality stations require high financial funding in resource-limited countries which make them logistically prohibitive since it is not cost-effective. Consequently, given the limited resources of good air quality data, modeling emerges as a possible tool to derive management measures (Agudelo-Castañeda et al 2023 ). However, high-resolution spatial estimations of long-term exposure to air pollutants are scarce in LAC and development of LUR models for some pollutants have been reported only for the cities of Mexico, Sao Paulo, Quito, and Medellín (Alvarez-Mendoza et al 2019 ; Habbermann and Gouveia 2007 ; Londoño and Cañon 2015 ; Luminati et al 2021 ; Son et al 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Intra-urban variability of long-term exposure to PM2.5 and NO2 in five cities in Colombia

Rodriguez-Villamizar,

Rojas,

Grisales

et al. 2023

Environ Sci Pollut Res

View full text Add to dashboard Cite

Rapidly urbanizing cities in Latin America experience high levels of air pollution which are known risk factors for population health. However, the estimates of long-term exposure to air pollution are scarce in the region. We developed intraurban land use regression (LUR) models to map long-term exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in the five largest cities in Colombia. We conducted air pollution measurement campaigns using gravimetric PM2.5 and passive NO2 sensors for 2 weeks during both the dry and rainy seasons in 2021 in the cities of Barranquilla, Bucaramanga, Bogotá, Cali, and Medellín, and combined these data with geospatial and meteorological variables. Annual models were developed using multivariable spatial regression models. The city annual PM2.5 mean concentrations measured ranged between 12.32 and 15.99 µg/m3 while NO2 concentrations ranged between 24.92 and 49.15 µg/m3. The PM2.5 annual models explained 82% of the variance (R2) in Medellín, 77% in Bucaramanga, 73% in Barranquilla, 70% in Cali, and 44% in Bogotá. The NO2 models explained 65% of the variance in Bucaramanga, 57% in Medellín, 44% in Cali, 40% in Bogotá, and 30% in Barranquilla. Most of the predictor variables included in the models were a combination of specific land use characteristics and roadway variables. Cross-validation suggests that PM2.5 outperformed NO2 models. The developed models can be used as exposure estimate in epidemiological studies, as input in hybrid models to improve personal exposure assessment, and for policy evaluation.

show abstract