Montserrat Fuentes

Learn More
There is a growing interest in quantifying the health impacts of climate change. This paper examines the risks of future ozone levels on non-accidental mortality across 19 urban communities in Southeastern United States. We present a modeling framework that integrates data from climate model outputs, historical meteorology and ozone observations, and a(More)
Particulate matter (PM) has been linked to a range of serious cardiovascular and respiratory health problems, including premature mortality. The main objective of our research is to quantify uncertainties about the impacts of fine PM exposure on mortality. We develop a multivariate spatial regression model for the estimation of the risk of mortality(More)
Constructing maps of dry deposition pollution levels is vital for air quality management, and presents statistical problems typical of many environmental and spatial applications. Ideally, such maps would be based on a dense network of monitoring stations, but this does not exist. Instead, there are two main sources of information for dry deposition levels(More)
Fine particulate matter (PM 2.5) is an atmospheric pollutant that has been linked to serious health problems, including mortality. PM 2.5 is a mixture of pollutants, and it has five main components: sulfate, nitrate, total carbonaceous mass, ammonium, and crustal material. These components have complex spatial-temporal dependency and cross dependency(More)
SUMMARY Estimating the probability of extreme temperature events is difficult because of limited records across time and the need to extrapolate the distributions of these events, as opposed to just the mean, to locations where observations are not available. Another related issue is the need to characterize the uncertainty in the estimated probability of(More)
Fine particulate matter (PM 2.5) is a mixture of pollutants that has been linked to serious health problems, including premature mortality. Since the chemical composition of PM 2.5 varies across space and time, the association between PM 2.5 and mortality could also change with space and season. In this work we develop and implement a statistical(More)
Visualizing data by graphing a response against certain factors, and conditioning on other factors, has arisen independently in many contexts. One is the interaction plots used in the analysis of data from designed experiments; these plots show conditional dependence based on the output of methods and models applied to the data. Trellis display, a framework(More)
SUMMARY Gridded estimated rainfall intensity values at very high spatial and temporal resolution levels are needed as main inputs for weather prediction models to obtain accurate precipitation forecasts, and to verify the performance of precipitation forecast models. These gridded rainfall fields are also the main driver for hydrological models that(More)