Matthew Thomas Clement

Chapter 2 Growth Machines and Carbon Emissions: A County-Level Analysis of how U.S. Place-Making Contributes to Global Climate Change

Purpose – To combine insights from urban and environmental sociology to examine local drivers of carbon emissions in the United States, with particular focus on demographic, economic, and consumptive dynamics. Design/methodology/approach – Apply spatial regression analysis to a novel county-level data set to test hypotheses about how different conditions and activities relate independently and positively to total carbon emissions at the local level. Findings – Results provide strong support for theoretically derived hypotheses, even after controlling for other factors, including spatial autocorrelation. The implication is that within a social system that treats land as a commodity, efforts to increase the exchange value of this commodity tend to drive up local carbon emissions, thereby contributing to global climate change. Originality/value – Complements previous sociological work on greenhouse gas emissions at the national level. Shows how local processes in general and urbanization in particular contribute to global climate change at and from the local areas where they occur.

The impacts of technology: a re-evaluation of the STIRPAT model

The STochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model has become a widely employed methodological approach within social science research, largely used to understand the complex relationships between human social systems and the non-human environment. The general assumption of the model is that anthropogenic environmental impacts are a multiplicative function of population, affluence, and technology. While previous STIRPAT research has examined the impact of technology in terms of urbanization, estimating the specific effect of urban population, we argue that this measure is better understood as a proxy for modernization. As an alternative, we frame urbanization as a multidimensional driver of environmental change, and we operationalize the technology dimension through cross-national data on impervious surface area, or what we call ‘terrestrial technology’. To demonstrate the potential of this example for environmental sociology, we draw from political economy to show how operationalizing technology offers a stronger, more nuanced understanding of the socioeconomic drivers of environmental degradation. Analytically, we employ a spatial regression model that estimates the effect of terrestrial technology on total carbon emissions for 173 countries. Our results show that impervious surface area is positively related to total carbon output and thus should be considered an operational measure of technology in future STIRPAT analyses.

Urban density and the metabolic reach of metropolitan areas: A panel analysis of per capita transportation emissions at the county-level.

We engage a tension in the urban environment literature that positions cities as both drivers of environmental destruction and loci of environmental protection. We argue that the traditional binary view of cities as either harmful or beneficial is too simplistic; we advance a more nuanced understanding of cities to study their internal and external metabolic effects in terms of carbon emissions from on-road transportation at the county-level across the continental United States between 2002 and 2007. First, utilizing satellite imagery from the National Land Cover Database, we create a novel measure of population density by quantifying the number of people per square mile of impervious surface area. Second, we develop a measure of metropolitan adjacency from the rural classifications datasets published by the USDA. In spatial regression models, we find that while higher density reduces emissions, counties that are geographically isolated from metropolitan areas actually have lower per capita emissions, all else equal. We elaborate on the conceptual, methodological, and practical implications of our study in the conclusion.

Ecovillages, Restitution, and the Political-Economic Opportunity Structure: An Urban Case Study in Mitigating the Metabolic Rift

In cities around the world, environmental concerns have spurred urban activists to organize alternative forms of settlement. Here, we assess efforts by one ecovillage in the Pacific Northwest to change their lifestyles in accordance with ecological principles. Drawing from the concepts of restitution and the political-economic opportunity structure (PEOS), we find that ecovillagers intend to mitigate the antagonism between humans and nature, but they face limitations from the larger urban and political-economic contexts. As such, this study describes the routine practices and experiences of urban ecovillagers as an example of the micro-level dynamics and tensions implied in metabolic rift theory.

Developing spatial inequalities in carbon appropriation: A sociological analysis of changing local emissions across the United States

This study examines an overlooked dynamic in sociological research on greenhouse gas emissions: how local areas appropriate the global carbon cycle for use and exchange purposes as they develop. Drawing on theories of place and space, we hypothesize that development differentially drives and spatially decouples use- and exchange-oriented emissions at the local level. To test our hypotheses, we integrate longitudinal, county-level data on residential and industrial emissions from the Vulcan Project with demographic, economic and environmental data from the U.S. Census Bureau and National Land Change Database. Results from spatial regression models with two-way fixed-effects indicate that alongside innovations and efficiencies capable of reducing environmentally harmful effects of development comes a spatial disarticulation between carbon-intensive production and consumption within as well as across societies. Implications for existing theory, methods and policy are discussed.

How do Slums Change the Relationship between Urbanization and the Carbon Intensity of Well-Being?

This study examines how the relationship between urbanization (measured as the percentage of total population living in urban areas) and the carbon intensity of well-being (CIWB) (measured as a ratio of carbon dioxide emissions and life expectancy) in most nations from 1960–2013 varies based on the economic context and whereabouts of a substantial portion of a nation’s urban population. To accomplish this, we use the United Nations’ (UN) definition of slum households to identify developing countries that have substantial slum populations, and estimate a Prais-Winsten regression model with panel-corrected standard errors (PCSE), allowing for disturbances that are heteroskedastic and contemporaneously correlated across panels. Our findings indicate that the rate of increase in CIWB for countries without substantial slum populations begins to slow down at higher levels of urbanization, however, the association between urbanization and CIWB is much smaller in countries with substantial slum populations. Overall, while urbanization is associated with increases in CIWB, the relationship between urban development and CIWB is vastly different in developed nations without slums than in under-developed nations with slums.