
arXiv: 1807.03935
SummaryGround level ozone and particulate matter pollutants are associated with a variety of health issues and increased mortality. For this reason, Mexican environmental agencies regulate pollutant levels. In addition, Mexico City defines pollution emergencies by using thresholds that rely on regional maxima for ozone and for particulate matter with diameter less than 10 μm, PM10. To predict local pollution emergencies and to assess compliance to Mexican ambient air quality standards, we analyse hourly ozone and PM10-measurements from 24 stations across Mexico City from 2017 by using a bivariate spatiotemporal model. With this model, we predict future pollutant levels by using current weather conditions and recent pollutant concentrations. Employing hourly pollutant projections, we predict regional maxima needed to estimate the probability of future pollution emergencies. We discuss how predicted compliance to legislated pollution limits varies across regions within Mexico City in 2017. We find that the predicted probability of pollution emergencies is limited to a few time periods. In contrast, we show that predicted exceedance of Mexican ambient air quality standards is a common, nearly daily occurrence.
particulate matter, FOS: Computer and information sciences, Bayesian inference, environmental exposure, Applications of statistics, Statistics - Applications, spatiotemporal modelling, ozone, Applications (stat.AP)
particulate matter, FOS: Computer and information sciences, Bayesian inference, environmental exposure, Applications of statistics, Statistics - Applications, spatiotemporal modelling, ozone, Applications (stat.AP)
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