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Interviews illuminate impacts of the Great Lakes Restoration Initiative (GLRI), a United States’ federal program designed to improve the Great Lakes by restoring the region’s most polluted harbors and coastal landscapes. To see how GLRI funds caused changes in the built environment and to attitudes toward place, semi-structured interviews were conducted with private- and public-sector leaders. Case studies are four EPA-designated Areas of Concern receiving substantial GLRI funds in Buffalo, New York; Duluth-Superior, Minnesota and Wisconsin; Muskegon, Michigan, and Sheboygan, Wisconsin. Results show that GLRI serves as a catalyst in three principal ways: The program leveraged local and state funds, both private and public. GLRI also leads to greater socio-spatial consciousness regarding rehabilitated places. Also, GLRI had led to stronger and deeper senses of place. This study reveals interviews help to calculate a more holistic return on investment for a prominent federal program. This study offers a way forward for ecosystem services research to take a more holistic view than has traditionally been done, in that semi-structured interviews illuminate impacts that traditional economic modeling alone cannot. Concurrently, this research is an example of how a prominent federal program affects community perceptions integral to holistic coastal planning processes. © Copyright © 2021 by the American Geographical Society of New York.
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Grid resilience and reliability are pivotal in the transition to low and zero carbon energy systems. Tree-trimming operations (TTOs) have become a pivotal tool for increasing the resilience power grids, especially in highly forested regions. Building on recent literature, we aim at assessing the temporal and spatial extents of the benefits that TTOs produce on the grid from three perspectives: the frequency, extent, and duration of outages. We use a unique dataset provided by Eversource Energy, New England's largest utility company, with outage events from 2009 to 2015. We employ spatial econometrics to investigate both the legacy and spatial extent of TTOs. Our results show TTOs benefits occur for all three metrics for at least 4 years, and benefits spillover to up to 2 km throughout the treated areas, with significant spatial spillovers across the state greater than direct effects. Implications lead to supporting TTOs as part of the hardening policies for utility companies, especially as home-based activities increase in importance in a post-COVID19 world. © 2021 Elsevier Ltd
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We apply recent developments in data-mining and statistics, using affinity propagation (AP) to identify regional typologies in the European Union (EU) and characterize major factors between rural–rural and rural–urban regional differences, without predetermined thresholds. We identify a representative ‘exemplar’ within each cluster using the drivers of Copus enriched with climate and land-cover/land-use variables to provide geographical context and pinpoint differences driven by natural and human–natural landscapes. Building upon the works of Dijkstra and the Eudora Project, we expand the dimensions of regional differences, introducing a threshold-less, data-driven model able to identify exemplars, and the main characteristics of each cluster or regional typology. © 2021 Regional Studies Association.
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This study demonstrates the application of affinity propagation as a data-driven approach to identifying and mapping typologies of place along the urban-rural continuum. The authors characterize Zip Code Tabulation Areas using demographic, economic, land cover, and accessibility to transportation infrastructure, which results in 22 clusters, 15 of which have a major rural component. The spatial pattern of these clusters varies, reflecting the heterogeneity in U.S. rurality. Rural is not a single concept that can be simply defined by population density. By comparing three economic indicators before and after the global financial crisis of 2007 to 2012, the authors find that the degree of economic recovery is captured by rural typologies. They compare both the methodological results and analysis of socioeconomic resilience to two of the most used threshold-based regional typologies, one developed by the U.S. Department of Agriculture Economic Research Service and one used by the American Communities Project.
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The United States has only recently begun investing in commercial-scale offshore wind energy (OWE). Although the United States is slow to progress, it is uniquely positioned to build on the existing knowledge that coastal European countries have applied for their own energy transitions. In this study, we analyze how federal and regional plans for expanding the OWE sector in the United States brought to the surface decade-long tensions related to multi-scale governance mismatches, jurisdictional conflicts, and unclear pathways for implementing national industrial policies. Drawing upon the European experience with OWE, we employ a dynamic multi-level perspective framework enriched by socio-ecological elements to examine the United States energy transition through its most promising technology. From our framework we identify six categories of OWE developments characterized by both unique and shared elements between the United States and European coastal countries. These elements are: (1) role of local communities, (2) governance structures, (3) multi-scale government interactions, (4) regional socioeconomic structures, (5) socio-ecological impacts, and (6) relationships with existing industries. Drawing upon our analysis, we identify and conceptually map four research areas in need of further development for the United States and the research community— (1) knowledge, (2) potential, (3) adaptation, and (4) learning. These insights provide critical information to ensure that the United States expansion into offshore energy generation is characterized by elements of justice, equity, and inclusive regional economic development.
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The U.S. coal industry is in the midst of a transition. Changes in regulation and technological innovation from other fossils and renewables have affected its competitiveness. These could have significant impacts on the labor market where jobs could be lost. In this study, we investigate how changes in employment in the coal industry affect wages in 20 industries in 10 U.S. coal producing states. We assess how these transitions impact welfare programs, since coal producing regions are associated with higher poverty levels. Results show that in the long run, migration of coal workers decreased wages in the construction, manufacturing sectors. Point estimates reveal that an increase in separations of coal workers increase Supplemental Nutrition Assistance Program (SNAP) caseloads. In states where coal mining has a smaller contribution to GDP, an increase in coal employment increases SNAP caseloads.
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- English (5)