Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data. Data are analyzed at the Census Block Group levels using Spearman’s correlation, ordinary least squares regression (OLS), and a spatial autoregressive model (SAR). Across all cities there is a strong positive correlation between UTC cover and median household income. Negative correlations between race and UTC cover exist in bivariate models for some cities, but they are generally not observed using multivariate regressions that include additional variables on income, education, and housing age. SAR models result in higher r-square values compared to the OLS models across all cities, suggesting that spatial autocorrelation is an important feature of our data. Similarities among cities can be found based on shared characteristics of climate, race/ethnicity, and size. Our findings suggest that a suite of variables, including income, contribute to the distribution of UTC cover. These findings can help target simultaneous strategies for UTC goals and environmental justice concerns

Supporting Global Environmental Change Research: A Review of Trends and Knowledge Gaps in Urban Remote Sensing

This paper reviews how remotely sensed data have been used to understand the impact of urbanization on global environmental change. We describe how these studies can support the policy and science communities’ increasing need for detailed and up-to-date information on the multiple dimensions of cities, including their social, biological, physical, and infrastructural characteristics. Because the interactions between urban and surrounding areas are complex, a synoptic and spatial view offered from remote sensing is integral to measuring, modeling, and understanding these relationships. Here we focus on three themes in urban remote sensing science: mapping, indices, and modeling. For mapping we describe the data sources, methods, and limitations of mapping urban boundaries, land use and land cover, population, temperature, and air quality. Second, we described how spectral information is manipulated to create comparative biophysical, social, and spatial indices of the urban environment. Finally, we focus how the mapped information and indices are used as inputs or parameters in models that measure changes in climate, hydrology, land use, and economics

Stewardship of the Biosphere in the Urban Era

We are entering a new urban era in which the ecology of the planet as a whole is increasingly influenced by human activities (Ellis 2011; Steffen et al. 2011a, b; Folke et al. 2011). Cities have become a central nexus of the relationship between people and nature, both as crucial centres of demand of ecosystem services, and as sources of environmental impacts. Approximately 60 % of the urban land present in 2030 is forecast to be built in the period 2000–2030 (Chap. 21). Urbanization therefore presents challenges but also opportunities. In the next two to three decades, we have unprecedented chances to vastly improve global sustainability through designing systems for increased resource efficiency, as well as through exploring how cities can be responsible stewards of biodiversity and ecosystem services, both within and beyond city boundaries

A Long View of Polluting Industry and Environmental Justice in Baltimore

Purpose This study examines the density of polluting industry by neighborhoods in Baltimore over the long term, from 1950 to 2010, to determine if high pollution burdens correspond spatially with expected demographic and housing variables predicted in the environmental justice literature. For 1960–1980 we use data on heavy industry from Dun and Bradstreet directories and for 1990–2010 the US EPA’s Toxics Release Inventory to calculate a Hazards Density Index. Drawing on the decennial censuses for 1960–2010, we populate census tracts from corresponding years with data on race, ethnicity, educational attainment, income, and housing tenure. Findings Density of polluting industry is positively correlated with low-income neighborhoods and renter-occupied housing in 1960 and by 2010 with white, Hispanic, and low educational attainment populations. In general, over time density of polluting facilities shifts from an association with wealth to race and ethnicity while educational attainment remains a significant variable throughout. This study confirms earlier analyses on Baltimore that white neighborhoods are more likely than African–American neighborhoods (1990–2010) to contain polluting facilities but reveals for the first time that educational attainment is also significant. The paper concludes with a discussion of the Baltimore Sustainability Plan and its weak efforts to address persistent environmental injustices

Global Scenarios of Urban Density and Its Impacts on Building Energy Use Through 2050

Although the scale of impending urbanization is well-acknowledged, we have a limited understanding of how urban forms will change and what their impact will be on building energy use. Using both top-down and bottom-up approaches and scenarios,we examine building energy use for heating and cooling. Globally, the energy use for heating and cooling by the middle of the century will be between 45 and 59 exajoules per year (corresponding to an increase of 7–40% since 2010). Most of this variability is due to the uncertainty in future urban densities of rapidly growing cities in Asia and particularly China. Dense urban development leads to less urban energy use overall. Waiting to retrofit the existing built environment until markets are ready in about 5 years to widely deploy the most advanced renovation technologies leads to more savings in building energy use. Potential for savings in energy use is greatest in China when coupled with efficiency gains. Advanced efficiency makes the least difference compared with the business-as-usual scenario in South Asia and Sub-Saharan Africa but significantly contributes to energy savings in North America and Europe. Systemic efforts that focus on both urban form, of which urban density is an indicator, and energy-efficient technologies, but that also account for potential co-benefits and trade-offs with human well-being can contribute to both local and global sustainability. Particularly in growing cities in the developing world, such efforts can improve the well-being of billions of urban residents and contribute to mitigating climate change by reducing energy use in urban areas

Metropolitan Planning Organizations and Climate Change Action

Metropolitan Planning Organizations (MPO) sit at a unique nexus of government arrangements and missions that could be effective for addressing issues of climate change. Using survey and secondary data this study investigates the potential of metropolitan planning organizations to play a formative role in climate change action and policy. We examine factors that promote MPOs involvement in climate change issues by bridging two types of literatures in a quantitative modeling framework: the institutional responses to environmental change, driven by conceptualization of urban systems as social-ecological systems, and the public policy, regional planning and local politics literature. We find robust MPOs, capacity and the organization members\u27 mental models play significant predictors for MPOs engagement in activities directly or indirectly related to climate change

The benefits and costs of agglomeration: insights from economics and complexity

There are many benefits and costs that come from people and firms clustering together in space. Agglomeration economies, in particular, are the manifestation of centripetal forces that make larger cities disproportionately more wealthy than smaller cities, pulling together individuals and firms in close physical proximity. Measuring agglomeration economies, however, is not easy, and the identification of its causes is still debated. Such association of productivity with size can arise from interactions that are facilitated by cities ("positive externalities"), but also from more productive individuals moving in and sorting into large cities ("self-sorting"). Under certain circumstances, even pure randomness can generate increasing returns to scale. In this chapter, we discuss some of the empirical observations, models, measurement challenges, and open question associated with the phenomenon of agglomeration economies. Furthermore, we discuss the implications of urban complexity theory, and in particular urban scaling, for the literature in agglomeration economies.Comment: Compendium of Urban Complexity. 31 pages, 4 figures, 1 tabl

Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data. Data are analyzed at the Census Block Group levels using Spearman\u27s correlation, ordinary least squares regression (OLS), and a spatial autoregressive model (SAR). Across all cities there is a strong positive correlation between UTC cover and median household income. Negative correlations between race and UTC cover exist in bivariate models for some cities, but they are generally not observed using multivariate regressions that include additional variables on income, education, and housing age. SAR models result in higher r-square values compared to the OLS models across all cities, suggesting that spatial autocorrelation is an important feature of our data. Similarities among cities can be found based on shared characteristics of climate, race/ethnicity, and size. Our findings suggest that a suite of variables, including income, contribute to the distribution of UTC cover. These findings can help target simultaneous strategies for UTC goals and environmental justice concerns

Does Size Matter? Scaling of CO\u3csub\u3e2\u3c/sub\u3e Emissions and U.S. Urban Areas

Urban areas consume more than 66% of the world’s energy and generate more than 70% of global greenhouse gas emissions. With the world’s population expected to reach 10 billion by 2100, nearly 90% of whom will live in urban areas, a critical question for planetary sustainability is how the size of cities affects energy use and carbon dioxide (CO2) emissions. Are larger cities more energy and emissions efficient than smaller ones? Do larger cities exhibit gains from economies of scale with regard to emissions? Here we examine the relationship between city size and CO2 emissions for U.S. metropolitan areas using a production accounting allocation of emissions. We find that for the time period of 1999–2008, CO2 emissions scale proportionally with urban population size. Contrary to theoretical expectations, larger cities are not more emissions efficient than smaller ones

A Synthesis of Global Urbanization Projections

This chapter reviews recent literature on global projections of future urbanization, covering the population, economic and physical extent perspectives. We report on several recent findings based on studies and reports on global patterns of urbanization. Specifically, we review new literature that makes projections about the spatial pattern, rate, and magnitude of urbanization change in the next 30–50 years. While projections should be viewed and utilized with caution, the chapter synthesis reports on several major findings that will have significant socioeconomic and environmental impacts including the following: By 2030, world urban population is expected to increase from the current 3.4 billion to almost 5 billion; Urban areas dominate the global economy – urban economies currently generate more than 90 % of global Gross Value Added; From 2000 to 2030, the percent increase in global urban land cover will be over 200 % whereas the global urban population will only grow by a little over 70 %. Our synthesis of recent projections suggest that between 50%–60% of the total urban land in existence in 2030 will be built in the first three decades of the 21st century. Challenges and limitations of urban dynamic projections are discussed, as well as possible innovative applications and potential pathways towards sustainable urban futures