Dataset Information

Mortality Benefits and Control Costs of Improving Air Quality in Mexico City: The Case of Heavy Duty Diesel Vehicles.

ABSTRACT: Diesel vehicles are significant contributors to air pollution in Mexico City. We estimate the costs and mortality benefits of retrofitting heavy-duty vehicles with particulate filters and oxidation catalysts. The feasibility and cost-effectiveness of controls differ by vehicle model-year and type. We evaluate 1985 to 2014 model-year vehicles from 10 vehicle classes and five model-year groups. Our analysis shows that retrofitting all vehicles with the control that maximizes expected net benefits for that vehicle type and model-year group has the potential to reduce emissions of primary fine particles (PM_2.5 ) by 950 metric tons/year; cut the population-weighted annual mean concentration of PM_2.5 in Mexico City by 0.90 µg/m³ ; reduce the annual number of deaths attributable to air pollution by over 80; and generate expected annual health benefits of close to 250 million US$. These benefits outweigh expected costs of 92 million US$ per year. Diesel retrofits are but one step that should viewed in the context of other efforts--such as development of an integrated public transportation system, promotion of the rational use of cars, reduction of emissions from industrial sources and fires, and redesign of the Mexico City Metropolitan Area to reduce urban sprawl--that must be analyzed and implemented to substantially control air pollution and protect public health. Even if considering other potential public health interventions, which would offer greater benefits at the same or lower costs, only by conducting, promoting, and publishing this sort of analyses, we can make strides to improve public health cost-effectively.

SUBMITTER: Evans JS

PROVIDER: S-EPMC8247320 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:UNLABELLED:Geostatistical interpolation methods to estimate individual exposure to outdoor air pollutants can be used in pregnancy cohorts where personal exposure data are not collected. Our objectives were to a) develop four assessment methods (citywide average (CWA); nearest monitor (NM); inverse distance weighting (IDW); and ordinary Kriging (OK)), and b) compare daily metrics and cross-validations of interpolation models. We obtained 2008 hourly data from Mexico City's outdoor air monitoring network for PM10, PM2.5, O3, CO, NO2, and SO2 and constructed daily exposure metrics for 1,000 simulated individual locations across five populated geographic zones. Descriptive statistics from all methods were calculated for dry and wet seasons, and by zone. We also evaluated IDW and OK methods' ability to predict measured concentrations at monitors using cross validation and a coefficient of variation (COV). All methods were performed using SAS 9.3, except ordinary Kriging which was modeled using R's gstat package. Overall, mean concentrations and standard deviations were similar among the different methods for each pollutant. Correlations between methods were generally high (r=0.77 to 0.99). However, ranges of estimated concentrations determined by NM, IDW, and OK were wider than the ranges for CWA. Root mean square errors for OK were consistently equal to or lower than for the IDW method. OK standard errors varied considerably between pollutants and the computed COVs ranged from 0.46 (least error) for SO2 and PM10 to 3.91 (most error) for PM2.5. OK predicted concentrations measured at the monitors better than IDW and NM. Given the similarity in results for the exposure methods, OK is preferred because this method alone provides predicted standard errors which can be incorporated in statistical models. The daily estimated exposures calculated using these different exposure methods provide flexibility to evaluate multiple windows of exposure during pregnancy, not just trimester or pregnancy-long exposures. IMPLICATIONS:Many studies evaluating associations between outdoor air pollution and adverse pregnancy outcomes rely on outdoor air pollution monitoring data linked to information gathered from large birth registries, and often lack residence location information needed to estimate individual exposure. This study simulated 1,000 residential locations to evaluate four air pollution exposure assessment methods, and describes possible exposure misclassification from using spatial averaging versus geostatistical interpolation models. An implication of this work is that policies to reduce air pollution and exposure among pregnant women based on epidemiologic literature should take into account possible error in estimates of effect when spatial averages alone are evaluated.

Project description:Meteorology and long-term trends in air pollutant concentrations may obscure the results from short-term policies implemented to improve air quality. This study presents changes in CO, NO2, O3, SO2, PM10, and PM2.5 based on their anomalies during the COVID-19 partial (Phase 2) and total (Phase 3) lockdowns in Mexico City (MCMA). To minimise the impact of the air pollutant long-term trends, pollutant anomalies were calculated using as baseline truncated Fourier series, fitted with data from 2016 to 2019, and then compared with those from the lockdown. Additionally, days with stagnant conditions and heavy rain were excluded to reduce the impact of extreme weather changes. Satellite observations for NO2 and CO were used to contrast the ground-based derived results. During the lockdown Phase 2, only NO2 exhibited significant decreases (p < 0.05) of between 10 and 23% due to reductions in motor vehicle emissions. By contrast, O3 increased (p < 0.05) between 16 and 40% at the same sites where NO2 decreased. During Phase 3, significant decreases (p < 0.05) were observed for NO2 (43%), PM10 (20%), and PM2.5 (32%) in response to the total lockdown. Although O3 concentrations were lower in Phase 3 than during Phase 2, those did not decrease (p < 0.05) from the baseline at any site despite the total lockdown. SO2 decreased only during Phase 3 in a near-road environment. Satellite observations confirmed that NO2 decreased and CO stabilised during the total lockdown. Air pollutant changes during the lockdown could be overestimated between 2 and 10-fold without accounting for the influences of meteorology and long-term trends in pollutant concentrations. Air quality improved significantly during the lockdown driven by reduced NO2 and PM2.5 emissions despite increases in O3, resulting in health benefits for the MCMA population. A health assessment conducted suggested that around 588 deaths related to air pollution exposure were averted during the lockdown. Our results show that to reduce O3 within the MCMA, policies must focus on reducing VOCs emissions from non-mobile sources. The measures implemented during the COVID-19 lockdowns provide valuable information to reduce air pollution through a range of abatement strategies for emissions other than from motor vehicles.

Project description:Biodiesel is regarded by many as a "greener" alternative fuel to petroleum diesel with potentially lower health risk. However, recent studies examining biodiesel particulate matter (PM) characteristics and health effects are contradictive, and typically utilize PM generated by passenger car engines in laboratory settings. There is a critical need to analyze diesel and biodiesel PM generated in a "real-world" setting where heavy duty-diesel (HDD) engines and commercially purchased fuel are utilized. This study compares the mass concentrations, chemical composition and cytotoxicity of real-world PM from combustion of both petroleum diesel and a waste grease 20% biodiesel blend (B20) at a community recycling center operating HDD nonroad equipment. PM was analyzed for metals, elemental/organic carbon (EC/OC), polycyclic aromatic hydrocarbons (PAHs), and nitro-polycyclic aromatic hydrocarbons (N-PAHs). Cytotoxicity in a human lung epithelial cell line (BEAS-2B) following 24h exposure to the real-world particles was also evaluated. On average, higher concentrations for both EC and OC were measured in diesel PM. B20 PM contained significantly higher levels of Cu and Mo whereas diesel PM contained significantly higher concentrations of Pb. Principal component analysis determined Mo, Cu, and Ni were the metals with the greatest loading factor, suggesting a unique pattern related to the B20 fuel source. Total PAH concentration during diesel fuel use was 1.9 times higher than during B20 operations; however, total N-PAH concentration was 3.3 times higher during B20 use. Diesel PM cytotoxicity was 8.5 times higher than B20 PM (p<0.05) in a BEAS-2B cell line. This study contributes novel data on real-world, nonroad engine sources of metals, PAH and N-PAH species, comparing tailpipe PM vs. PM collected inside the equipment cabin. Results suggest PM generated from burning petroleum diesel in nonroad engines may be more harmful to human health, but the links between exposure, composition and toxicity are not straightforward.

Dataset Information

Mortality Benefits and Control Costs of Improving Air Quality in Mexico City: The Case of Heavy Duty Diesel Vehicles.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets