Environmental Impacts of Urban Growth

The aggregate potential for urban mitigation of global climate change is insufficiently understood. Our analysis, using a dataset of 274 cities representing all city sizes and regions worldwide, demonstrates that economic activity, transport costs, geographic factors, and urban form explain 37% of urban direct energy use and 88% of urban transport energy use. If current trends in urban expansion continue, urban energy use will increase more than threefold, from 240 EJ in 2005 to 730 EJ in 2050. Our model shows that urban planning and transport policies can limit the future increase in urban energy use to 540 EJ in 2050 and contribute to mitigating climate change. However, effective policies for reducing urban greenhouse gas emissions differ with city type. The results show that, for affluent and mature cities, higher gasoline prices combined with compact urban form can result in savings in both residential and transport energy use. In contrast, for developing-country cities with emerging or nascent infrastructures, compact urban form, and transport planning can encourage higher population densities and subsequently avoid lock-in of high carbon emission patterns for travel. The results underscore a significant potential urbanization wedge for reducing energy use in rapidly urbanizing Asia, Africa, and the Middle East.

That urban and rural places are connected through trade, people, and policies has long been recognized. The urban land teleconnections (ULT) framework aims advancing conventional conceptualizations of urbanization and land. The conceptual framework thus opens way to identify and examine the processes that link urbanization dynamics and associated land changes that are not necessarily colocated. In this paper, we review recent literature on four manifestations of urbanization that, along the lines of the ULT framework, highlight the importance of process-based conceptualizations of urbanization and land along a continuum of land systems. We then discuss potential approaches to improve the knowledge base on how and where urbanization is driving land change.

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.

Urbanization is a demographic, economic, and land transformation process. Building construction and operation are integral aspects of urban land use change and contribute to material and energy resources consumption and the resulting carbon dioxide (CO₂) emissions in urban areas. In this paper, we ask two questions regarding the urbanization process: 1) Do the land, material, and energy use efficiencies associated with the construction and operation of buildings increase over time? 2) Do the gains in resource use efficiencies offset the increases in resource demands due to the magnitude of urbanization? To answer these questions, we use a systematic approach similar to a material flow analysis and apply it to the Pearl River Delta, a rapidly urbanizing region in China. We use a combination of satellite data and official statistics to evaluate changes in urban population density and building density from 1988 to 2008. Both density measures decrease from 1988 to 2003; after 2003, building density increases while population density continues to decline. We also track the indirect impacts of urban land expansion on material and energy demands and associated CO₂ emissions using concrete and heating/cooling as proxies for building construction and operation, respectively. Throughout the study period, structural changes and efficiency gains decrease the demand per unit floor area for both building materials and energy. However, the efficiency gains are outstripped by the magnitude of urban expansion, therefore leading to an increase in the demand for resources and CO₂ emissions per capita. Our results show that focusing only on gains in efficiency for individual buildings without considering the scale of urban expansion results in underestimate of the cumulative energy, material, and greenhouse gas emissions impacts of urbanization. We emphasize the distinction between the rates versus the accumulations of these impacts over spatial and temporal scales. We discuss the relevance of the Environmental Kuznets approaches to tackling environmental impacts that are cumulative in nature and may lead to irreversible changes in the environment. We conclude that tracking the energy, materials, and emissions impacts of urbanization requires a multi-scale approach that ranges from the individual building to the urban region.

This paper introduces urban land teleconnections as a conceptual framework that explicitly links land changes to underlying urbanization dynamics. We illustrate how three key themes that are currently addressed separately in the urban sustainability and land change literatures can lead to incorrect conclusions and misleading results when they are not examined jointly: the traditional system of land classification that is based on discrete categories and reinforces the false idea of a rural–urban dichotomy; the spatial quantification of land change that is based on place-based relationships, ignoring the connections between distant places, especially between urban functions and rural land uses; and the implicit assumptions about path dependency and sequential land changes that underlie current conceptualizations of land transitions. We then examine several environmental “grand challenges” and discuss how urban land teleconnections could help research communities frame scientific inquiries. Finally, we point to existing analytical approaches that can be used to advance development and application of the concept.

Editorial overview written for issue of Current Opinion in Environmental Sustainability entitled “Human settlements and industrial systems.” The overview discusses the confluence of urbanization and global environmental change and introduces articles found in the issue. 

In 2008, the global urban population exceeded the nonrural population for the first time in history, and it is estimated that by 2050, 70% of the world population will live in urban areas, with more than half of them concentrated in Asia. Although there are projections of future urban population growth, there is significantly less information about how these changes in demographics correspond with changes in urban extent. Urban land-use and land-cover changes have considerable impacts on climate. It has been well established that the urban heat island effect is more significant during the night than day and that it is affected by the shape, size, and geometry of buildings as well as the differences in urban and rural gradients. Recent research points to mounting evidence that urbanization also affects cycling of water, carbon, aerosols, and nitrogen in the climate system. This review highlights advances in the understanding of urban land-use trends and associated climate impacts, concentrating on peer-reviewed papers that have been published over the last two years.

China is home to one-fifth of the world’s population and that population is increasingly urban. The landscape is also urbanizing. Although there are studies that focus on specific elements of urban growth, there is very little empirical work that incorporates feedbacks and linkages to assess the interactions between the dynamics of urban growth and their environmental impacts. In this study, we develop a system dynamics simulation model of the drivers and environmental impacts of urban growth, using Shenzhen, South China, as a case study. We identify three phases of urban growth and develop scenarios to evaluate the impact of urban growth on several environmental indicators: land use, air quality, and demand for water and energy. The results show that all developable land will be urban by 2020 and the increase in the number of vehicles will be a major source of air pollution. Demand for water and electricity will rise, and the city will become increasingly vulnerable to shortages of either. The scenarios also show that there will be improvements in local environmental quality as a result of increasing affluence and economic growth. However, the environmental impacts outside of Shenzhen may increase as demands for natural resources increase and Shenzhen pushes its manufacturing industries out of the municipality. The findings may also portend to changes other cities in China and elsewhere in the developing world may experience as they continue to industrialize.

Remote sensing data have been proposed as a potential tool for monitoring environmental treaties. However, to date, satellite images have been used primarily for visualization, but not for systematic monitoring of treaty compliance. In this paper, we present a methodology to operationalize the use of satellite imagery to assess the impact of the Ramsar Convention on Wetlands. The approach uses time series analysis of landscape pattern metrics to assess land cover conditions before and after designation of Ramsar status to monitor compliance with the Convention. We apply the methodology to two case studies in Vietnam and evaluate the success of Ramsar using four metrics: (1) total mangrove extent; (2) mangrove fragmentation; (3) mangrove density; and (4) aquaculture extent. Results indicate that the Ramsar Convention did not slow the development of aquaculture in the region, but total mangrove extent has remained relatively constant, primarily due to replanting efforts. Yet despite these restoration efforts, the mangroves have become fragmented and survival rates for replanting efforts are low. The methodology is cost effective and especially useful to evaluate Ramsar sites that rely mainly on self-reporting methods and where third parties are not actively involved in the monitoring process. Finally, the case study presented in this paper demonstrates that with the appropriate satellite record, in situ measurements and field observations, remote sensing is a promising technology that can help monitor compliance with international environmental agreements.

The ability to predict spatial patterns of species richness using a few easily measured environmental variables would facilitate timely evaluation of potential impacts of anthropogenic and natural disturbances on biodiversity and ecosystem functions. Two common hypotheses maintain that faunal species richness can be explained in part by either local vegetation heterogeneity or primary productivity. Although remote sensing has long been identified as a potentially powerful source of information on the latter, its principal application to biodiversity studies has been to develop classified vegetation maps at relatively coarse resolution, which then have been used to estimate animal diversity. Although classification schemes can be delineated on the basis of species composition of plants, these schemes generally do not provide information on primary productivity. Furthermore, the classification procedure is a time- and labour-intensive process, yielding results with limited accuracy. To meet decision-making needs and to develop land management strategies, more efficient methods of generating information on the spatial distribution of faunal diversity are needed. This article reports on the potential of predicting species richness using single-date Normalized Difference Vegetation Index (NDVI) derived from Landsat Thematic Mapper (TM). We use NDVI as an indicator of vegetation productivity, and examine the relationship of three measures of NDVI—mean, maximum, and standard deviation—with patterns of bird and butterfly species richness at various spatial scales. Results indicate a positive correlation, but with no definitive functional form, between species richness and productivity. The strongest relationships between species richness of birds and NDVI were observed at larger sampling grains and extent, where each of the three NDVI measures explained more than 50% of the variation in species richness. The relationship between species richness of butterflies and NDVI was strongest over smaller grains. Results suggest that measures of NDVI are an alternative approach for explaining the spatial variability of species richness of birds and butterflies.