Programs and Communities
The collection collates collections by schools, centers, programs, and research groups.
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- All Subjects: Climate Change
- All Subjects: Newark, New Jersey
Maricopa County, Arizona, anchor to the fastest growing megapolitan area in the United States, is located in a hot desert climate where extreme temperatures are associated with elevated risk of mortality. Continued urbanization in the region will impact atmospheric temperatures and, as a result, potentially affect human health. We aimed to quantify the number of excess deaths attributable to heat in Maricopa County based on three future urbanization and adaptation scenarios and multiple exposure variables.
Two scenarios (low and high growth projections) represent the maximum possible uncertainty range associated with urbanization in central Arizona, and a third represents the adaptation of high-albedo cool roof technology. Using a Poisson regression model, we related temperature to mortality using data spanning 1983–2007. Regional climate model simulations based on 2050-projected urbanization scenarios for Maricopa County generated distributions of temperature change, and from these predicted changes future excess heat-related mortality was estimated. Subject to urbanization scenario and exposure variable utilized, projections of heat-related mortality ranged from a decrease of 46 deaths per year (− 95%) to an increase of 339 deaths per year (+ 359%).
Projections based on minimum temperature showed the greatest increase for all expansion and adaptation scenarios and were substantially higher than those for daily mean temperature. Projections based on maximum temperature were largely associated with declining mortality. Low-growth and adaptation scenarios led to the smallest increase in predicted heat-related mortality based on mean temperature projections. Use of only one exposure variable to project future heat-related deaths may therefore be misrepresentative in terms of direction of change and magnitude of effects. Because urbanization-induced impacts can vary across the diurnal cycle, projections of heat-related health outcomes that do not consider place-based, time-varying urban heat island effects are neglecting essential elements for policy relevant decision-making.
Global environmental change and sustainability science increasingly recognize the need to address the consequences of changes taking place in the structure and function of the biosphere. These changes raise questions such as: Who and what are vulnerable to the multiple environmental changes underway, and where? Research demonstrates that vulnerability is registered not by exposure to hazards (perturbations and stresses) alone but also resides in the sensitivity and resilience of the system experiencing such hazards. This recognition requires revisions and enlargements in the basic design of vulnerability assessments, including the capacity to treat coupled human–environment systems and those linkages within and without the systems that affect their vulnerability. A vulnerability framework for the assessment of coupled human–environment systems is presented.
Research on global environmental change has significantly improved our understanding of the structure and function of the biosphere and the human impress on both (1). The emergence of “sustainability science” (2–4) builds toward an understanding of the human–environment condition with the dual objectives of meeting the needs of society while sustaining the life support systems of the planet. These objectives, in turn, require improved dialogue between science and decision making (5–8). The vulnerability of coupled human–environment systems is one of the central elements of this dialogue and sustainability research (6, 9–11). It directs attention to such questions as: Who and what are vulnerable to the multiple environmental and human changes underway, and where? How are these changes and their consequences attenuated or amplified by different human and environmental conditions? What can be done to reduce vulnerability to change? How may more resilient and adaptive communities and societies be built?
Answers to these and related questions require conceptual frameworks that account for the vulnerability of coupled human–environment systems with diverse and complex linkages. Various expert communities have made considerable progress in pointing the way toward the design of these frameworks (10, 11). These advances are briefly reviewed here and, drawing on them, we present a conceptual framework of vulnerability developed by the Research and Assessment Systems for Sustainability Program (http://sust.harvard.edu) that produced the set of works in this Special Feature of PNAS. The framework aims to make vulnerability analysis consistent with the concerns of sustainability and global environmental change science. The case study by Turner et al. (12) in this issue of PNAS illustrates how the framework informs vulnerability assessments.
The New Jersey Childhood Obesity Study was designed to provide vital information for planning, implementing, and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by the Robert Wood Johnson Foundation’s New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity. Effective interventions for addressing childhood obesity require community-specific information on
who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community. Based on comprehensive research, a series of reports are being prepared for each community to assist in planning effective interventions.
The main components of the study were:
• A household telephone survey of 1700 families with 3–18 year old children,
• De-identified heights and weights measured at public schools,
• Assessment of the food and physical activity environments using objective data.
This report presents the results from the household survey. Reports based on school body mass index (BMI) data and food and physical activity environment data are available at www.cshp.rutgers.edu/childhoodobesity.htm.
The maps in this chartbook describe the food environment in ewark in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.
• Food environment maps were created using geo-coded commercially available data of food outlets (InfoUSA, 2008 and Trade Dimensions, 2008) in Newark and in a 1 mile buffer area around Newark.
•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likelihood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.
• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.
• Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy foods in neighborhoods with different characteristics.
Data Sources: Info USA food outlet 2008 data
Trade Dimensions food outlet 2008 data
Census 2000 data
New Jersey Department of Education 2008-2009 data
The maps in this chartbook describe the food environment in Trenton in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.
•Food environment maps were created using geo-coded commercially available data of food outlets (InfoUSA, 2008 and Trade Dimensions, 2008) in Trenton and in a 1 mile buffer area around Trenton.
•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likelihood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.
• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.
•Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy foods in neighborhoods with different characteristics.
Data Sources: Info USA food outlet 2008 data
Trade Dimensions food outlet 2008 data
Census 2000 data
New Jersey Department of Education 2008-2009 data
The maps in this chartbook describe the physical activity environment in Newark in terms of geographic distribution of parks and physical activity facilities. Research shows that people who have access to these facilities are more likely to be physically active.
• The maps in this chartbook were created using physical activity facilities data from a commercial database (lnfoUSA, 2008), data from city departments, as well as information obtained from systematic web searches. The maps present data for the city of Newark and for a 1 mile buffer area around Newark.
• Physical activity centers include private and public facilities which offer physical activity opportunities for children 3-18 years of age.
• Physical activity environment maps are compared with Census 2000 data to visualize accessibility of physical activity opportunities in neighborhoods with different characteristics.
• Poverty level presented in this chartbook are based on the 2000 Federal Poverty Guidelines.
• Crime rates in Newark are presented at the census block group level as relative crime risk (CrimeRisk) obtained from a commercial data source (Applied Geographic Solutions, 2008). CrimeRisk - an index value derived from modeling the relationship between crime rates and demographics data - is expressed as the risk of crime occurring in a specific block group relative to the national average. For this chartbook, data on total CrimeRisk, which includes personal and property crimes, are reported.
This brief summarizes the different types of food stores open in Newark, New Jersey and in a one mile radius around the city during 2008 to 2014.
The City of Phoenix Street Transportation Department partnered with the Rob and Melani Walton Sustainability Solutions Service at Arizona State University (ASU) and researchers from various ASU schools to evaluate the effectiveness, performance, and community perception of the new pavement coating. The data collection and analysis occurred across multiple neighborhoods and at varying times across days and/or months over the course of one year (July 15, 2020–July 14, 2021), allowing the team to study the impacts of the surface treatment under various weather conditions.