Urban land use and transportation planning for climate change mitigation: A theoretical framework

Highlights

• Develop a theoretical framework for sustainable urban land use and transportation planning.

• Social planner solves a utility maximization problem with greenhouse gas damages.

• Analytical insights are obtained from the problem’s optimality conditions.

• Results provide theoretical support for mitigation via compact urban form and public transit.

• Transportation mitigation strategies can be effective even if suboptimal land use is locked in.

Abstract

Cities account for 75% of global greenhouse gas (GHG) emissions from energy use, and their share is increasing due to rapid urbanization. While compact urban forms with public transit are viewed as important strategies for reducing emissions, environmental benefits must be weighed against the costs of public transit infrastructure, road improvements to alleviate congestion in dense urban space, and more expensive housing resulting from land use restrictions. The literature largely lacks a theoretical framework for assessing these tradeoffs. This paper derives analytical insights into urban land use and transportation planning for climate change mitigation by formulating a social planner’s utility maximization problem. The planner chooses the residential densities of urban zones as well as investments in road and public transit infrastructures that link these zones to the city center. Road travel is subject to congestion. Any feasible solution must accommodate a fixed total population and ensure that residents of all zones have the same maximum utility. GHG emissions associated with housing, road travel, and public transit generate damages. Analytical results show that incorporating GHG damages into urban planning always leads to an optimal solution with a more compact urban form, and reduces automobile travel in each zone if a specific condition involving the marginal congestion cost and the marginal effectiveness of road investment is satisfied. Numerical examples demonstrate that near-optimal emissions reductions and utility improvements can be achieved via public transit investment and mode shifting even if the planner inherits and cannot modify a suboptimal land use and road configuration.

Introduction

The global urban population surpassed the number of rural dwellers for the first time in human history in 2008, and we are now a majority urban civilization (Marshall, 2008). The United Nations (2018) projects that rapid and persistent urbanization will result in 68% of the global population residing in urban areas in 2050. Between now and then, cities around the world will gain 2.5 billion net inhabitants. While urbanization is occurring in all regions of the world, 90% of these new urban residents will live in Asia and Africa (United Nations, 2018).

Cities already account for 75% of all global carbon dioxide (CO₂) emissions from energy use, and their share of greenhouse gas (GHG) emissions will continue to rise along with urbanization (Bai et al., 2018). There is growing recognition that climate change mitigation must increasingly take place in urban contexts. For instance, the Intergovernmental Panel on Climate Change (IPCC) hosted its first Cities and Climate Change Science Conference in 2018 (Prieur-Richard et al., 2018), and researchers have called for demand-side climate solutions at the urban scale that could collectively add up to an urban mitigation wedge (Creutzig, Baiocchi, Bierkandt, Pichler, Seto, 2015, Creutzig, Roy, Lamb, Azevedo, de Bruin, Dalkmann, Edelenbosch, Geels, Grübler, Hepburn, Hertwich, Khosla, Mattauch, Minx, Ramakrishnan, Rao, Steinberger, Tavoni, Ürge-Vorsatz, Weber, 2018, Marshall, 2008). City governments around the world are heeding the call to action, and are becoming more prominent climate policy players in the midst of uncertainty about the Paris Climate Agreement (Deetjen, Conger, Leibowicz, Webber, 2018, Solecki, Rosenzweig, Dhakal, Roberts, Barau, Schultz, Ürge-Vorsatz, 2018). In fact, the C40 Cities Climate Leadership Group committed to achieving the 1.5^∘C goal of the Paris Agreement has expanded to include over 90 cities around the world that represent more than 700 million people and a quarter of the global economy (C40 Cities, 2019).

Decades of empirical research have confirmed that urban form – which essentially encompasses land use patterns and the layouts of transportation infrastructures (Marshall, 2008) – is a major driver of urban GHG emissions, especially in the residential and transportation sectors. In the residential sector, Ewing and Rong (2008) find that residents of more sprawling U.S. counties are more likely to live in larger homes and more likely to live in detached houses, both of which increase energy use and emissions. Glaeser and Kahn (2010) discover that more geographically concentrated urban areas in the U.S. consume less electricity per capita, and that central city residents tend to consume less electricity than suburban residents within the same metropolitan area. Similarly, Navamuel, Rubiera Morollón, and Moreno Cuartas (2018) find that urban households consume significantly less electricity than small municipality and rural households in Spain, and Belaïd (2016) concludes that residential energy consumption in France increases moving from urban to suburban to rural settings. In the transportation sector, Newman and Kenworthy (1989) show in their landmark paper that per-capita gasoline consumption is negatively related to urban core population density and the proportion of jobs in the city center. The close relationship between compact urban form and low gasoline consumption holds across a sample of U.S. cities as well as a sample of global cities. This finding is corroborated by many more recent studies (Karathodorou, Graham, & Noland, 2010), including analyses that use personal vehicle travel (Marshall, 2008) or transportation GHG emissions per capita (Kennedy, Steinberger, Gasson, Hansen, Hillman, Havranek, Pataki, Phdungsilp, Ramaswami, Mendez, 2009, Ma, Liu, Chai, 2015, VandeWeghe, Kennedy, 2007) as the dependent variable. The latter specification captures another mechanism by which compact urban form lowers GHG emissions: in addition to reducing trip distances, it makes public transit (which tends to be less GHG-intensive than personal vehicle travel) more viable (Lohrey, Creutzig, 2016, Pan, Shen, Zhang, 2009).

While the empirical literature shows that more compact urban forms with public transit reduce GHG emissions, these benefits must be weighed against a variety of costs in order to make sound urban planning decisions. Public transit infrastructure is costly to provide, especially in low-density settings (Lohrey & Creutzig, 2016). To cope with traffic congestion in a denser urban space, road infrastructure might need to be improved (Çolak, Lima, & González, 2016). In addition, realizing a more compact urban form via land use restrictions can come at a cost to residents due to higher housing prices (Grout, Jaeger, Plantinga, 2011, Leibowicz, 2017). Urban space is a complex system that involves tradeoffs among myriad conflicting objectives, and the literature largely lacks a theoretical framework for guiding urban land use and transportation planning strategies to reduce GHG emissions while limiting adverse impacts.

The research community studying cities and climate change has increasingly called attention to this research gap. According to Acuto, Parnell, and Seto (2018), urban science “remains trapped in the twentieth-century tradition of the systematic study of individual cities.” The IPCC Fifth Assessment Report attests that “the literature on urban form and infrastructure drivers of GHG emissions... is dominated by case studies of cities in developed countries” (Seto et al., 2014). As a result, urban planners seeking to reduce emissions through land use and transportation planning are often forced to extrapolate lessons gleaned from limited case study experiences from specific places and times, which can lead to inappropriate policy prescriptions. This issue is particularly problematic given that case studies have overwhelmingly taken place in developed country cities, but the greatest potential for urban climate change mitigation exists in developing countries where urbanization is in its early stages (Seto et al., 2014). Bai et al. (2016) conclude that “a systems approach is urgently needed in urban research and policy analysis,” one that captures “tradeoffs between the positive and negative consequences of policy actions.” The present study addresses this gap in the literature.

This paper derives analytical insights into urban land use and transportation planning for climate change mitigation by formulating a social planner’s utility maximization problem. The planner chooses the residential densities of urban zones as well as investments in road and public transit infrastructures that link these zones to the city center. Road travel is subject to congestion. Any feasible solution must accommodate a fixed total population, ensure that residents of all zones have the same maximum utility level, and remain within a total resource budget. GHG emissions associated with housing, road travel, and public transit travel generate damages that reduce utility, and thus factor into the planner’s problem.

Based on this model formulation, several important properties of the optimal urban land use and transportation plan are derived analytically. These analytical findings constitute generalizable insights in that they do not stem from any particular functional forms or numerical parameterization of the model, but rather are guaranteed to hold under a fairly standard and minimal set of structural assumptions. The main analytical results of this paper are asserted in four propositions that characterize the optimal urban planning response to climate change. A key element of the optimal strategy is to pursue a more compact urban form with more residents living in central locations. Even as the planner spatially reallocates households across zones to reduce emissions (with some central zones absorbing additional residents), the absolute level of personal automobile travel should decline in each zone if a specific analytical condition involving the marginal cost of congestion and the marginal effectiveness of road capacity investment is satisfied.

Following the theoretical analysis, the model is fully specified with functional forms and parameter values, and solved numerically for four scenarios. The scenarios differ in terms of whether the planner accounts for GHG damages and the degree of flexibility the planner has to optimize various aspects of the urban form. Results show that even if the planner inherits and cannot modify a land use plan and road infrastructure that are suboptimal under climate change, the planner can achieve most of the GHG emissions reduction and utility improvement that are achieved in the unrestricted optimum. This demonstrates how effective public transit investment and transportation mode shifting can be as mitigation measures, and is encouraging from a practical standpoint.

The remainder of this article is structured as follows. The literature review in Section 2 summarizes the most relevant urban planning models from the urban economics and operations research literatures. The model developed for the present study is presented in Section 3. In Section 4, theoretical results are obtained by analyzing the optimality conditions of the model in a highly general setting. Numerical examples are solved and visualized in Section 5 to illustrate the theoretical results from the previous section and explore the implications of different decision-making scenarios. Section 6 clarifies limitations of the methodology. Section 7 concludes with a summary of the most important findings and possible directions for future research.