Improving the design stage of air pollution studies based on wind patterns.

A growing literature in economics and epidemiology has exploited changes in wind patterns as a source of exogenous variation to better measure the acute health effects of air pollution. Since the distribution of wind components is not randomly distributed over time and related to other weather parameters, multivariate regression models are used to adjust for these confounding factors. However, this type of analysis relies on its ability to correctly adjust for all confounding factors and extrapolate to units without empirical counterfactuals. As an alternative to current practices and to gauge the extent of these issues, we propose to implement a causal inference pipeline to embed this type of observational study within an hypothetical randomized experiment. We illustrate this approach using daily data from Paris, France, over the 2008-2018 period. Using the Neyman-Rubin potential outcomes framework, we first define the treatment of interest as the effect of North-East winds on particulate matter concentrations compared to the effects of other wind directions. We then implement a matching algorithm to approximate a pairwise randomized experiment. It adjusts nonparametrically for observed confounders while avoiding model extrapolation by discarding treated days without similar control days. We find that the effective sample size for which treated and control units are comparable is surprisingly small. It is however reassuring that results on the matched sample are consistent with a standard regression analysis of the initial data. We finally carry out a quantitative bias analysis to check whether our results could be altered by an unmeasured confounder: estimated effects seem robust to a relatively large hidden bias. Our causal inference pipeline is a principled approach to improve the design of air pollution studies based on wind patterns.

The effects of an air quality alert program on premature mortality: A difference-in-differences evaluation in the region of Paris.

BACKGROUND: Daily exposure to air pollution has been shown to increase cardiovascular and respiratory mortality. While increases in short-term exposure to air pollutants at any daily concentrations has been shown to be associated to adverse health outcomes, days with extreme levels, also known as air pollution peaks based on specific thresholds, have been used to implement air quality alerts in various cities across the globe. OBJECTIVES: We aimed at evaluating the potential effects of the Air Quality Alerts (AQA) system on different causes of premature mortality in Paris, France. METHODS: Air quality alerts (AQA) based on particulate matter (PM10) levels and related interventions were implemented in the region of Paris in 2008 and were revised to be more stringent in 2011. In this study, we applied a difference-in-differences (DID) approach coupled with propensity-score matching (PSM) to daily mortality data for the period 2000 to 2015 to evaluate the effects of the Paris AQA program on different causes of premature mortality for the entire population and for adults > 75 years old. RESULTS: Overall, results did not show evidence of a reduction in mortality of the PM10 AQA program when first implemented in 2008 with initial thresholds (80 µg/m3); DID estimates were slightly above 1 for cardiovascular and respiratory mortality. However, when evaluating the drastic reduction in revised thresholds in 2011 (50 µg/m3) to trigger interventions, we identified a reduction in cardiovascular (DID = 0.84, 95% CI: 0.755 to 0.930) mortality, but no change in respiratory mortality was detected (DID = 0.97, 95% CI: 0.796, 1.191). DISCUSSION: Our study suggests that AQA may not have health benefits for the population when thresholds are set at high daily PM10 levels. Given that such policies are implemented in many other metropolitan areas across the globe, evaluating the effectiveness of AQA is important to provide public authorities and researchers a rationale for defining specific thresholds and extending the scope of these policies to lower air pollution levels.