New York State Air Pollution Health Effects By Mariana de Brito, Daniela Hamann-Nazaroff, Megan Klevze, and Marilu Corona
Air pollution has serious public health implications causing between 22,000-52,000 premature deaths and countless cases of illness in the United States of America each year (Mokdad et al, 2004). The goal of this project was to estimate the spatial distribution and magnitude of health impacts from air pollution, specifically exposure to fine particulate matter and ozone, over one year in New York State (NYS). Mariana, Daniela, Megan and Marilu hope to provide the population of NYS with a resource to better understand the harmful effects of poor air quality and the motivation to address sources of air pollution.
Pollutant concentrations of ozone (O3) and fine particulate matter (PM2.5) measured by air quality
monitors were interpolated over the area of New York using Empirical Bayesian Kriging and averaged
over each census block in the state. Based on these interpolated concentrations of O3 and PM2.5, they
calculated incidence of asthma, bronchitis, congestive heart failure in elderly, risk of death from cancer,
hospital admissions due to pollution exposure, and premature death for each census block’s population.
Using data primarily from 2010, they estimated 6,000 premature deaths are attributed to air pollution in
NYS annually and thousands of cases of the other health indicators.
They also analyzed the distribution and magnitude of stationary point-source PM2.5 emissions from industrial-scale combustion facilities using a hot spot analysis and ordinary least squares regression. They found no statistically significant correlation between stationary point source emissions and air concentrations, likely due to the high level of uncertainty in our interpolated concentrations which does not capture local variability, as well as the lack of other important factors such as meteorological conditions. Finally, they investigated the correlation between pollution exposure and various demographic groups and at-risk populations, but found no statistically significant difference in exposure among any group. Maps showing air pollution concentrations, potential pollutant sources, populations at risk, and estimated health impacts were created to visualize the results.
Riders For Health: A Case Study on Improving Health Care Accessibility via Transportation in the Southern Province of Zambia By Vincent Chen, Justine Fedronic, Sarah McCurdy, and Tyler Stutzman
In countries with large rural populations, health care accessibility is largely dependent on transportation conditions. Riders for Health, a UK based NGO, aims to increase accessibility by providing fleet management services, such as training health workers to use vehicles responsibly in the face of the challenging Zambian landscape. To determine whether these services areeffective in improving accessibility to healthcare, this paper aims to analyze 1) if Riders for Health has increased service outreach efforts, and 2) if population, precipitation, and accessibility (combing terrain and distance factors) impacts the distribution of service points.
Water Availability in Kenya: By Jeff Ho and Maeva Fincker
In order to assess disparities in the accessibility of drinking water in Kenya, Jeff and Maeva created an index of drinking water accessibility based on the quantity of available water, the water supply type, the level of water treatment employed, and the temporal accessibility of water sources. They employed the Demographic and Health Survey (DHS) dataset to georeference data pertaining to water fetch-times, water treatment before drinking, and water supply type. They also employed an annual average of precipitation across Kenya, and assessed proximity to water sources using basemaps with water-body polygons, and hydrologic data on the distribution of groundwater reservoirs and annual yields. The four parameters (quality, type, treatment, and time) were converted to raster datasets, reclassified, then summed using the Raster Calculator to produce a final index of drinking water accessibility (DWAI). Based on their results, while most Kenyan populations have poor to moderate drinking water accessibility, the spatial variation in DWAI is not statistically correlated to variation in wealth, health, education, or distance from major urban centers.
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