We propose innovative methods of modeling and analysis of respiratory health outcomes and economic and policy responses in relation to recently implemented air quality regulation in Delhi, the 10th most polluted city in the world in terms of total suspended particulate (TSP), and its neighboring districts, largely unaffected by these regulations. We first develop a simple model that captures household health and residence choices and how they interact with the labor and land markets in determining the distributonal effects of changes in industrial zoning enforcement. Our empirical analysis builds on this model and exploits unanticipated changes in the degree of enforcement of residential zoning and the conversion of commerical vehicles to compressed natural gas (CNG) in late 2000 that are thought to have importantly influenced air quality. As a result, we plan to understand space-time dynamics of air quality in pre and post regulation periods by analyzing aerosol optical thickness (AOT [a surrogate of air quality in urban areas]) in the troposphere. This data will be retrieved from remote sensing satellites and validated through TSP 2.5 and AOT ground meaurements that we will start recording at the beginning of January 2005 at the 150 control points to be determined by distances from air pollution sources, city center, urban density and structure etc. We have already started a socio-economic and respiratory health survey in the study area. A sample of households was selected using a newly developed location based sampling technique. To begin with the study area was stratified using 5 factors: air quality, distances from the main highway, thermal plants, industrial sites and city center. Finally we generated 1700 random points in the residential areas of the identified strata. These random points are navigated with the help of global positioning system (GPS) to acquire household consent, and for the survey component that includes information related to household, individual and their lung function. In the first round, we expect to cover 1500 households likely to be completed by mid March. The entire survey data is being geocoded in order to understand the spatial dependency of air quality and respiratory health responses. Spatial-statistical and econometric models will be employed to investigate interaction between air quality, economic choices and respiratory health responses. In additon, we will examine the cost of morbidity, caused by exposure to poor air quality and people's willingness to pay for clean air, which is central to the environmental regulations debate. We propose a second round of survey of the same households in June-August 2006 that will allow us to understand the effects of temporal and seasonal variations in air quality on respiratory health.
| Liang, Dong; Kumar, Naresh (2013) Time-space Kriging to address the spatiotemporal misalignment in the large datasets. Atmos Environ (1994) 72:60-69 |
| Kumar, Naresh (2012) Uncertainty in the Relationship between Criteria Pollutants and Low Birth Weight in Chicago. Atmos Environ 49:171-179 |
| Foster, Andrew; Kumar, Naresh (2011) Health Effects of Air Quality Regulations in Delhi, India. Atmos Environ (1994) 45:1675-1683 |
| Kumar, Naresh; Foster, Andrew D (2009) Air quality interventions and spatial dynamics of air pollution in Delhi and its surroundings. Int J Environ Waste Manag 4:85-111 |
| Kumar, Naresh (2009) An Optimal Spatial Sampling Design for Intra-Urban Population Exposure Assessment. Atmos Environ (1994) 43:1153 |
