Dissertation Research: Race, Class, and Human Ecological Factors in the Spatial Distribution of Manufacturing Emissions

小行星9623747 越来越多的社会运动、政府官员和媒体声称，弱势群体不成比例地受到环境污染的影响，但很少有实证研究来检验这一说法或其对社会分层的重要性。 这项研究结合了美国环境保护署1990年有毒物质释放清单（TRI）的数据和人口普查数据，研究了地方的种族和经济组成与制造业有毒空气释放之间的关系。 该项目将对全国范围内的县级分析结果与对具有异常高水平的制造业污染的选定社区的人口普查区级分析结果进行比较。 该项目将利用地理信息系统技术和空间分析技术，以比大多数环境正义和分层研究所用的更复杂的方式模拟有毒物质排放的扩散。这项研究将大大有助于从社会学的角度理解制造业的污染是如何在社会群体中分布的：（1）阐明关于环境正义研究分析的适当地理单位的辩论;（2）通过使用地理信息系统技术改进对有毒空气污染水平的估计;（3）通过检验观测到的空间自相关关系来利用地理数据的空间性质。 ****

9623747 Leicht A growing number of social movements, government officials, and the media have claimed that disadvantaged communities are disproportionately exposed to environmental pollution, yet there has been little empirical research examining this claim or its importance for social stratification. This research combines data from the U.S. Environmental Protection Agency's 1990 Toxics Release Inventory (TRI) with Census data to examine the relationship between the racial and economic composition of places and toxic air releases from manufacturing. This project will compare results from a nationwide, county-level analysis with census tract level analysis of selected communities that have unusually high levels of manufacturing pollution. The project will use Geographic Information Systems technology and spatial analysis techniques to model the dispersion of toxic releases in a more sophisticated manner than used in most studies of environmental justice and stratification. This research will contribute significantly to the sociological understanding of how pollution from manufacturing is distributed across social groups by (1) shedding light on debates about the appropriate geographic units of analysis for environmental justice research; (2) improving estimates of levels of toxic air pollution by using GIS technology, and; (3) exploiting the spatial nature of geographic data by testing observed relationships for the presence of spatial autocorrelation. ****