Ground-Truthing Validation to Assess the Effect of Facility Locational Error on Cumulative Impacts Screening Tools

Rethinking of Environmental Health Risks: A Systematic Approach of Physical-Social Health Vulnerability Assessment on Heavy-Metal Exposure through Soil and Vegetables

In the field of environmental health risk assessment and management research, heavy metals in soil are a constant focus, largely because of mining and metallurgical activities, and other manufacturing or producing. However, systematic vulnerability, and combined research of social and physical vulnerability of the crowd, have received less attention in the research literature of environmental health risk assessment. For this reason, tentative design modelling for comprehensive environmental health vulnerability, which includes the index of physical and social vulnerability, was conducted here. On the basis of experimental data of heavy-metal pollution in soil and vegetables, and population and societal survey data in Daye, China, the physical, social, and comprehensive environmental health vulnerabilities of the area were analyzed, with each village as an evaluation unit. First, the polluted and reference areas were selected. Random sampling sites were distributed in the farmland of the villages in these two areas, with two sampling sites per village. Then, 204 vegetable samples were directly collected from the farmland from which the soil samples had been collected, composed of seven kinds of vegetables: cowpea, water spinach, amaranth, sweet potato leaves, tomato, eggplant, and pepper. Moreover, 400 questionnaires were given to the local residents in these corresponding villages, and 389 valid responses were obtained. The results indicated that (1) the average physical vulnerability values of the population in the polluted and reference areas were 3.99 and 1.00, respectively; (2) the village of Weiwang (WW) had the highest physical vulnerability of 8.55; (3) vegetable intake is exposure that should be paid more attention, as it contributes more than 90% to physical vulnerability among the exposure pathways; (4) arsenic and cadmium should be the priority pollutants, with average physical vulnerability value contributions of 63.9% and 17.0%, respectively; (5) according to the social vulnerability assessment, the village of Luoqiao (LQ) had the highest social vulnerability (0.77); (6) for comprehensive environmental health vulnerability, five villages near mining activities and two villages far from mine-affected area had high physical and social vulnerability, and are the urgent areas for environmental risk management. In order to promote environmental risk management, it is necessary to prioritize identifying vulnerable populations in the village-scale dimension as an innovative discovery.

Towards Smart Campus Management: Defining Information Requirements for Decision Making through Dashboard Design

At universities worldwide, the notion of a ‘smart campus’ is becoming increasingly appealing as a response to the multitude of challenges that impact campus development and operation. Smart campus tools are widely used to support students and employees, optimise space use and save energy. Although smart campus tools are supposed to support campus managers in their decision-making processes, the use of the information delivered by smart campus tools and their application in organisational processes has received little attention. In this paper, we focus on the use of dashboards in the connection of IoT information to strategic decision-making processes in the management of university campuses. To this end, we developed a briefing approach for dashboards that expresses the needs of campus management and matches the structure of decision-making processes. In two cases, dashboards based on this approach were use-tested by stakeholders for defining information requirements for IoT applications. The results suggest that users are able to use dashboards for assessing portfolio performance and determining interventions. Through iteration the usability of the dashboard is improved and information requirements are refined, resulting in a brief for a campus management dashboard. The results suggest that the briefing approach can be used to determine IoT information requirements, though further research is required to study indications and contra-indications of the proposed method.

Racialized Structural Vulnerability: Neighborhood Racial Composition, Concentrated Disadvantage, and Fine Particulate Matter in California

This study contributes to previous research by advancing a “racialized structural vulnerability” framework and presenting a new empirical analysis of the relationship between neighborhood Asian, Black, and Latinx composition; extrinsic and intrinsic vulnerability; and PM_2.5 exposures in California with secondary data from 2004–2014. Principal component analyses revealed that tract Latinx composition was highly correlated with extrinsic vulnerability (economic disadvantage and limited English-speaking ability), and that tract Black composition was highly correlated with intrinsic vulnerability (elevated prevalence of asthma-related emergency department visits and low birth weight). Spatial lag regression models tested hypotheses regarding the association between Asian, Black, and Latinx population vulnerability factors and the 2009–2011 annual average PM_2.5 percentile rankings, net of emissions and spatial covariates. Results indicated that the percent Latinx population, followed by the regional clustering of PM_2.5, and the percent of non-Latinx Black and non-Latinx Asian population were the strongest positive multivariable correlates of PM_2.5 percentile rankings, net of other factors. Additional analyses suggested that despite shifting demographic and spatial correlates of 2012–2014 PM_2.5 exposures, the tracts’ Black and Latinx composition and location in the San Joaquin Valley remain important vulnerability factors with implications for future research and policy.

Validating and Refining EPA's Traffic Exposure Screening Measure

Exposure to high air pollutant concentrations results in significant health risks. Many communities of color and low-income communities face disproportionately higher levels of air pollution exposure. Environmental justice (EJ) screening tools play a critical role in focusing early attention on areas with a high likelihood of disparate health impacts. In 2015, the United States Environmental Protection Agency (US EPA) released EJScreen, a screening tool with indicators of a range of pollution burdens across the US. However, little is known about the accuracy of the screening estimates of pollution exposure. This study compares EJScreen's traffic proximity air quality metric to dispersion modeling results. Using the area around the Houston Ship Channel, we conduct fine-grained air pollution dispersion modeling to evaluate how closely EJScreen's indicator approximates estimated roadway air pollution concentrations. We find low correlation between modeled concentrations and the EJScreen roadway air pollution indicator. We extend EJScreen's roadway air pollution screening method in three ways: (1) using a smaller unit of analysis, (2) accounting for the length of each road segment, and (3) accounting for wind direction. Using the Houston region, we use two of the methods and show that the proposed extensions provide a more accurate transportation air pollution screening assessment at the regional and local level.

Advice and Frequently Asked Questions (FAQs) for Citizen-Science Environmental Health Assessments

Citizen science provides quantitative results to support environmental health assessments (EHAs), but standardized approaches do not currently exist to translate findings into actionable solutions. The emergence of low-cost portable sensor technologies and proliferation of publicly available datasets provides unparalleled access to supporting evidence; yet data collection, analysis, interpretation, visualization, and communication are subjective approaches that must be tailored to a decision-making audience capable of improving environmental health. A decade of collaborative efforts and two citizen science projects contributed to three lessons learned and a set of frequently asked questions (FAQs) that address the complexities of environmental health and interpersonal relations often encountered in citizen science EHAs. Each project followed a structured step-by-step process in order to compare and contrast methods and approaches. These lessons and FAQs provide advice to translate citizen science research into actionable solutions in the context of a diverse range of environmental health issues and local stakeholders.

Retooling CalEnviroScreen: Cumulative Pollution Burden and Race-Based Environmental Health Vulnerabilities in California

The California Community Environmental Health Screening Tool (CalEnviroScreen) advances research and policy pertaining to environmental health vulnerability. However, CalEnviroScreen departs from its historical foundations and comparable screening tools by no longer considering racial status as an indicator of environmental health vulnerability and predictor of cumulative pollution burden. This study used conceptual frameworks and analytical techniques from environmental health and inequality literature to address the limitations of CalEnviroScreen, especially its inattention to race-based environmental health vulnerabilities. It developed an adjusted measure of cumulative pollution burden from the CalEnviroScreen 2.0 data that facilitates multivariate analyses of the effect of neighborhood racial composition on cumulative pollution burden, net of other indicators of population vulnerability, traffic density, industrial zoning, and local and regional clustering of pollution burden. Principal component analyses produced three new measures of population vulnerability, including Latina/o cumulative disadvantage that represents the spatial concentration of Latinas/os, economic disadvantage, limited English-speaking ability, and health vulnerability. Spatial error regression analyses demonstrated that concentrations of Latinas/os, followed by Latina/o cumulative disadvantage, are the strongest demographic determinants of adjusted cumulative pollution burden. Findings have implications for research and policy pertaining to cumulative impacts and race-based environmental health vulnerabilities within and beyond California.

Retooling CalEnviroScreen: Cumulative Pollution Burden and Race-Based Environmental Health Vulnerabilities in California

The California Community Environmental Health Screening Tool (CalEnviroScreen) advances research and policy pertaining to environmental health vulnerability. However, CalEnviroScreen departs from its historical foundations and comparable screening tools by no longer considering racial status as an indicator of environmental health vulnerability and predictor of cumulative pollution burden. This study used conceptual frameworks and analytical techniques from environmental health and inequality literature to address the limitations of CalEnviroScreen, especially its inattention to race-based environmental health vulnerabilities. It developed an adjusted measure of cumulative pollution burden from the CalEnviroScreen 2.0 data that facilitates multivariate analyses of the effect of neighborhood racial composition on cumulative pollution burden, net of other indicators of population vulnerability, traffic density, industrial zoning, and local and regional clustering of pollution burden. Principal component analyses produced three new measures of population vulnerability, including Latina/o cumulative disadvantage that represents the spatial concentration of Latinas/os, economic disadvantage, limited English-speaking ability, and health vulnerability. Spatial error regression analyses demonstrated that concentrations of Latinas/os, followed by Latina/o cumulative disadvantage, are the strongest demographic determinants of adjusted cumulative pollution burden. Findings have implications for research and policy pertaining to cumulative impacts and race-based environmental health vulnerabilities within and beyond California.