Investigating the relationship between environmental quality, socio-spatial segregation and the social dimension of sustainability in US urban areas.

This work is intended to assess the relationship between the three dimensions of sustainability (environmental, economic, and social) and residential segregation broadly across US urban areas. Multivariate indices of segregation and sustainability are created using data aggregated to 933 US Census Core-Based Statistical Areas (CBSAs). The relationship between segregation and sustainability (and dimensions, independently) is analyzed across the CBSAs using correlation and spatial analyses. Results show an inverse relationship between segregation and sustainability, where increasing urban segregation corresponds to decreases in sustainability. Social and economic dimensions of sustainability are negatively correlated with segregation while the environmental dimension is positively correlated. Spatial analysis reveals regional associations between the measures with most of the lower sustainability scores and higher segregation scores occuring mainly in the South. The findings demonstrate an inverse relationship between segregation and sustainability as well as between the environmental and social dimensions. These correlations indicate a need to consider inequalities, and the social dimension of sustainability more broadly, when planning urban revitalization efforts. Spatial scale is also imperative to understanding and improving the social outcomes for all members of the community.

Downscaling a Human Well-Being Index for Environmental Management and Environmental Justice Applications in Puerto Rico.

Human well-being is often an overarching goal in environmental decision-making, yet assessments are often limited to economic, health, or ecological endpoints that are more tangible to measure. Composite indices provide a comprehensive approach to measuring well-being in terms of multi-dimensional components, such as living standards, health, education, safety, and culture. For example, the Human Well-Being Index (HWBI) framework, initially developed for the U.S. fifty states, was recently applied to quantify human well-being for Puerto Rico. However, the paucity of data at spatial scales finer than state or county levels, particularly for social metrics, poses a major limitation to quantifying well-being at neighborhood-scales relevant to decision-making. Here we demonstrate a spatial interpolation method to fill in missing fine-scale data where coarser-scale data is available. Downscaling from municipio (i.e., county-equivalent) to census-tract revealed a greater range of variability in well-being scores across Puerto Rico, in particular, a larger proportion of low well-being scores. Furthermore, while some components of wellbeing (e.g., Education, Health, Leisure Time, Safety and Security, Social Cohesion) showed consistent improvement over time from 2000-2017 across Puerto Rico, others (e.g., Connection to Nature, Cultural Fulfillment, Living Standards) were variable among census tracts, increasing for some but declining for others. We use a case study in the San Juan Bay estuary watershed to illustrate how approaches to quantify baseline levels of well-being can be used to explore potential impacts of management actions on communities, including to identify environmental justice inequalities among neighborhoods. Spatial clustering analysis was used to identify statistically significant cold or hot spots in well-being. This study demonstrates how indicators of well-being, coupled with interpolation methods to overcome limitations of data availability, can help to monitor long-term changes over time and to better communicate the potential value of ecosystem restoration or resource management.

Application of a Multi-Hazard Risk Assessment for Local Planning.

The utility of a multi-hazard risk-scape at the county level is significant for county, state, regional, and national policy makers who rely on broad and consistent assessments of hazard exposure and losses. In previous work, the Patterns of Risk using an Integrated Spatial Multi-Hazard (PRISM) approach creates an index of county risk for this purpose. While helpful across large areas, the approach lacks information needed at more localized scales. In this paper, we employ the PRISM approach to all 2015 census tracts in the US. Use of a land-cover approach, with spatial extents and modeled data from 11 natural and 4 technological hazard types, determines spatial exposures. Furthermore, census counts allow for the estimation of population exposures in each tract by hazard type. The results of the tract-level index reveal exposure patterns that contrast the original PRISM model, with a concentration of risk shifting eastward. The distribution of land-cover and population exposure more closely resemble the county index, revealing the importance of scale and land-cover considerations, along with the need for additional investigation of risk drivers. We provide an application of the risk and multi-hazard exposures in two major metropolitan areas to demonstrate utility of the approach at this scale.

Using Re-scaled Resilience Screening Index Results and Location Quotients for Socio-Ecological Characterizations in U.S. Coastal Regions.

In terms of natural hazard events, resilience characterizations provide a means of identifying risk profiles, degrees of preparedness, and the ability of communities to respond and recover. While nationally consistent measures of community resilience to natural hazards are needed to address widespread socio-ecological impacts from a broad policy perspective, geographically specific resilience characterizations are needed to target local resources to increase community resilience. The Climate Resilience index (CRSI) was developed to characterize the resilience of socio-ecological systems in the context of governance and risk to natural hazard events for all U.S. counties for the years 2000-2015. Those resilience characterizations were based on the full range of nationwide county domain scores. This paper presents a re-scaled application of CRSI, where county domain scores are limited to the range of scores within a specific set of U.S. coastal and shoreline counties within each of eight coastal regions. The re-scaled CRSI values for selected counties/parishes in the Gulf of Mexico (GOM) region are also presented in conjunction with calculated Location Quotients (LQ) values >1.0, which represent a high employment dependence on ocean economy sectors. Using a combination of re-scaled CRSI and LQ values provides a more holistic picture of vulnerability and resilience in these U.S. coastal shoreline counties. The relative resilience assessments presented for coastal regions are useful in identifying potential strengths and weaknesses in resilience aspects given similar hazard profiles, a signature otherwise diluted in nation-wide county-level assessments. The unique approach of combining CRSI and LQ for characterizing natural hazard resilience described could be transferred to other specific geographies as defined by population groups, hazard profiles and economic dependence.

Development of a Multi-Hazard Landscape for Exposure and Risk Interpretation: The PRISM Approach.

Multi-hazard risk assessment has long been centered on small scale needs, whereby a single community or group of communities' exposures are assessed to determine potential mitigation strategies. While this approach has advanced the understanding of hazard interactions, it is limiting on larger scales or when significantly different hazard types are present. In order to address some of these issues, an approach is developed where multiple hazards coalesce with losses into an index representing the risk landscape. Exposures are assessed as a proportion of land-area, allowing for multiple hazards to be combined in a single calculation. Risk calculations are weighted by land-use types (built, dual-benefit, natural) in each county. This allows for a more detailed analysis of land impacts and removes some of the bias introduced by monetary losses in heavily urbanized counties. The results of the quantitative analysis show a landscape where the risk to natural systems is high and the western United States is exposed to a bulk of the risk. Land-use and temporal profiles exemplify a dynamic risk-scape. The calculation of risk is meant to inform community decisions based on the unique set of hazards in that area over time.

Application of the Human Well-Being Index to Sensitive Population Divisions: A Children's Well-Being Index Development.

The assessment of community well-being is critical as an end-point measure that will facilitate decision support and assist in the identification of sustainable solutions to address persistent problems. While the overall measure is important, it is equally vital to distinguish variations among groups within the population who may be impacted in a different manner. The U.S. Environmental Protection Agency (US EPA) developed the Human Well-Being Index (HWBI), as a way of measuring these outcomes and assessing community characteristics. The HWBI approach produces a suite of indicators, domains and a final composite index appropriate for characterizing well-being of a population. While generalized approaches are needed, it is important to also recognize variations in well-being across community enclaves. This paper presents an adaption of the HWBI for child populations to test the applicability of the index framework to specific community enclaves. First, an extensive literature review was completed to ensure the theoretical integrity of metric and indicator substitutions from the original HWBI framework. Metric data were then collected, refined, imputed where necessary and evaluated to confirm temporal and spatial availability. A Children's Well-Being Index (CWBI) value, representing the same indicators and domains of well-being as the original HWBI, was calculated for the population under age 18 across all US counties for 2011. Implications of this research point to an effective, holistic end-point measure that can be tracked over time. Similarly, there is great potential for the application of the original HWBI method to other statistical population segments within the greater US population. These adaptations could help identify and close gaps in equity of resource distribution among these groups.

Measuring Community Resilience to Natural Hazards: The Natural Hazard Resilience Screening Index (NaHRSI)-Development and Application to the United States.

Natural disasters often impose significant and long-lasting stress on financial, social, and ecological systems. From Atlantic hurricanes to Midwest tornadoes to Western wildfires, no corner of the United States is immune from the threat of a devastating natural hazard event. Across the nation, there is a recognition that the benefits of creating environments resilient to adverse natural hazard events help promote and sustain county and community success over time. The challenge for communities is in finding ways to balance the need to preserve the socioecological systems on which they depend in the face of constantly changing natural hazard threats. The Natural Hazard Resilience Screening Index (NaHRSI; previously entitled Climate Resilience Screening Index) has been developed as an endpoint for characterizing county resilience outcomes that are based on risk profiles and responsive to changes in governance, societal, built, and natural system characteristics. The NaHRSI framework serves as a conceptual roadmap showing how natural hazard events impact resilience after factoring in county characteristics. By evaluating the factors that influence vulnerability and recoverability, an estimation of resilience can quantify how changes in these characteristics will impact resilience given specific hazard profiles. Ultimately, this knowledge will help communities identify potential areas to target for increasing resilience to natural hazard events.

Conceptualizing Holistic Community Resilience to Climate Events: Foundation for a Climate Resilience Screening Index.

The concept of resilience has been evolving over the past decade as a way to address the current and future challenges nations, states and cities face from a changing climate. Understanding how the environment (natural and built), climate event risk, societal interactions and governance reflect community resilience for adaptive management is critical for envisioning urban and natural environments that can persist through extreme weather events and longer-term shifts in climate. To be successful, this interaction of these five domains must result in maintaining quality of life and ensuring equal access to the benefits or the protection from harm for all segments of the population. An exhaustive literature review of climate resilience approaches was conducted examining the two primary elements of resilience - vulnerability and recoverability. The results of this review were examined to determine if any existing frameworks addressed the above five major areas in an integrated manner. While some aspects of a resilience model were available for existing sources, no comprehensive approach was available. A new conceptual model for resilience to climate events is proposed that incorporates some available structures and addresses these five domains at a national, regional, state and county spatial scale for a variety of climate-induced events ranging from superstorms to droughts and their concomitant events such as wildfires, floods, and pest invasions. This conceptual model will be developed in a manner that will permit comparisons among governance units (e.g., counties) and permit an examination of best reliance practices.