Avoidable mortality due to long-term exposure to PM2.5 in Colombia 2014-2019

Particulate matter 2.5 exposure during pregnancy and birth outcomes: Evidence from Colombia

Particulate matter is a type of air pollution that consists of fine particles with a diameter <2.5 μm (PM2.5), which can easily penetrate the respiratory system and enter the bloodstream, increasing health risks for pregnant women and their unborn babies. Recent reports have suggested that there is a positive association between PM2.5 exposure and adverse pregnancy outcomes. However, most evidence of this relationship comes from Western countries. Thus, the objective of this study was to evaluate the association between PM2.5 exposure during pregnancy and birth outcomes among pregnant women in Colombia. This study included 542,800 singletons born in 2019 to Colombian women, aged 15+ years, residing in 981 municipalities. Data on parental, child and birth characteristics were extracted from anonymized live birth records. Satellite-based estimates of monthly PM2.5 concentrations at the surface level were extracted for each municipality from the Atmospheric Composition Analysis Group (ACAG). PM2.5 exposure during pregnancy was indicated by the monthly average of PM2.5 concentrations across the pregnancy duration for the municipality where the child was born. The associations of municipality-level PM2.5 concentration during pregnancy with pre-term birth (PTB) and low birth weight (LBW) were tested in separate two-level logistic regression models, with babies nested within municipalities. The prevalence of PTB and LBW were 8.6 % and 8.3 %, respectively. The mean PM2.5 concentration across the 981 municipalities was 18.26 ± 3.30 μg/m3, ranging from 9.11 to 31.44 μg/m3. Greater PM2.5 concentration at municipality level was associated with greater odds of PTB (1.05; 95%CI: 1.04-1.06) and LBW (1.04; 95%CI: 1.03-1.05), after adjustment for confounders. Our findings provide new evidence on the association between PM2.5 on adverse pregnancy outcomes from a middle-income country.

Air pollution analysis in Northwestern South America: A new Lagrangian framework

This study examines the spatiotemporal variations of PM2.5, PM10, SO2, O3, NO, and NO2 concentrations in Northwestern South America (NWSA). We assess the efficacy of existing policies, identify underlying phenomena, and highlight areas for further research. Significant findings have emerged by analyzing reanalysis and in-situ data, employing the WRF-Chem model, and utilizing a new Lagrangian framework designed to overcome some drawbacks common to analysis of pollution Long-Range Transport. Wildfires in the first half of the year and volcanic activity (for SO2) in July-August contribute to over 90 % of the pollutant's advection, leading to high pollution levels in urban areas. SO2 volcanic emissions contribute to secondary PM, explaining the peak in PM concentrations in Cali in July. In the second half of the year, pollutant behavior varies based on factors such as city characteristics, vehicular-volume, air temperature, wind speed, and boundary layer height, and O3 is influenced by solar radiation and the NO/NO2 ratio. Diurnal variations of PM and NOx correlate with vehicular density, SO2 with industrial activity, and O3 depends on solar radiation. Trend analysis reveals decreasing PM10 levels except in three Cundinamarca cities and Cali suggesting the need to implement/evaluate control plans in those locations. Although data is limited, NO and NO2 levels show an increasing trend due to the rising number of vehicles. SO2 levels are decreasing, except in Cali, potentially influenced by the nearby industrial and polluted city of Yumbo. O3 displays a downward trend in most cities, except Bogotá, due to the NO/NO2 ratio favoring O3 increase. These findings provide a starting point for further research to deepen our understanding of NWSA air pollution. Such investigations are essential before modifying existing policies or enacting new ones. Collaborative efforts at the international, regional, and inter-city levels are crucial for effective air quality management.

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

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.