Spatial Heterogeneity of Air Pollution and Health Impacts in Sensitive Groups in Urban India

EPA Grant Number: FP917821
Title: Spatial Heterogeneity of Air Pollution and Health Impacts in Sensitive Groups in Urban India
Investigators: Nori-Sarma, Amrutasri Ashwini
Institution: Yale University
EPA Project Officer: Lee, Sonja
Project Period: September 1, 2015 through August 31, 2018
Project Amount: $132,000
RFA: STAR Graduate Fellowships (2015) RFA Text |  Recipients Lists
Research Category: Academic Fellowships

Objective:

In South India, rapid urbanization is dramatically increasing urban populations, and especially the concentration of urban poor communities in slums. As urbanization increases, it is important to identify the built environment and other characteristics that determine air pollution exposure. This research will investigate the heterogeneity in air pollution exposure among urban poor communities living in large and growing cities of South India. This project will identify important social and environmental exposure variables, as well as explore methodologies suitable for understanding exposure and health in growing cities in India.

Approach:

Pilot air pollution sampling in Chennai and Mysore, India indicate that there is a high degree of spatial heterogeneity in air pollution levels, even within urban neighborhoods. In addition to traffic sources, urban air pollution in India may be impacted by a large number of point sources of pollution, as well as other urban environment characteristics. A land-use regression model has been selected as the preferred method to help understand exposure to NO2 among urban residents living in low-income neighborhoods in these selected cities, integrating all of these factors that may influence air pollution exposure patterns. To develop the model, four NO2 sampling campaigns for each season will be conducted in each city, in neighborhoods selected based on socioeconomic characteristics that are indicative of low-income neighborhoods (e.g., housing density). In addition, meteorological and environmental (e.g., land use, road network) data will be collected for inclusion in the land-use regression model. The NO2 exposure model developed will be used to determine air pollution exposure differentials among sensitive urban poor communities, and will be related to field samples of lung function among these sensitive communities using linear mixed effects models.

Expected Results:

A map of annual average NO2 exposure will be created for urban areas in South India, specifically focused on neighborhoods that are determined to be of interest because of their socioeconomic characteristics. The proportion of the total population exposed to high air pollution and associated neighborhood features will be determined. Resulting maps will showcase issues of environmental injustice, including the differential of air pollution exposure between transient and non-transient communities. Important variables, methods for exploring exposure to air pollution in places like South India, and ways a model developed in Western cities can be improved for implementation in other similar growing cities in South Asia will be identified.

Supplemental Keywords:

air pollution, exposure, sensitive sub-populations, urban, health

Progress and Final Reports:

  • 2016
  • 2017
  • Final