Cost-Effectiveness of Southern California Public Transportation Projects

by Dan McCabe

California recently established a carbon cap-and-trade program in the interest of improving air quality and fighting global climate change. The tax revenues generated from this program are used to fund projects that help reduce greenhouse gas (GHG) emissions, but policymakers face the challenge of deciding which projects are best suited for this funding. To inform this decision-making process, Matute and Chester (2015) compared the effectiveness of different current and future public transportation projects to determine which is the most cost-effective, in terms of public dollars spent per ton of carbon dioxide equivalent released. The study compared four projects from Los Angeles County: the Orange Bus Rapid Transport (Orange BRT) line in the San Fernando Valley, the Gold Light Rail Transport (Gold LRT) line that runs from Los Angeles to Pasadena, a bicycle and pedestrian pathway along the Orange BRT line, and the California High Speed Rail (CAHSR) project, a plan being developed to expand high-speed rail throughout the state. All four projects were found to have negative costs per ton of carbon dioxide reduced, indicating that they actually save the public money over time. For a 100-year period, the bicycle pathway was found to be most cost-effective, followed by the Gold LRT, Orange BRT, and CAHSR. Continue reading

Large Suburban Carbon Footprints Negate GHG Benefits of Urban Areas

by Dan McCabe

Jones and Kammen (2014) performed a remarkably thorough analysis of the average household carbon footprint (HCF) for nearly every US zip code and examined how dozens of different variables affect greenhouse gas (GHG) emissions. The authors’ analysis used detailed data from the nationwide Residential Energy Consumption Survey, the National Household Travel Survey, and other sources. Their model used these surveys to estimate local emissions due to components such as electricity, housing, transportation, and food, then evaluated possible correlations with 37 independent demographic variables. Continue reading

Intelligent Planning Can Offset Much of Projected Energy Demand Increases

by Dan McCabe

Urban areas account for the majority of global energy consumption and greenhouse gas emissions, which is of growing concern as their populations are projected to double within the next 35 years. In order to inform urban planning efforts to reduce greenhouse gas emissions, Creutzig et al. (2015) studied how a wide array of variables influence the energy consumption of cities across the globe. The authors considered detailed data provided by the World Bank (WB), the Global Energy Assessment (GEA), and the International Association of Public Transport (UITP) for 274 different-sized cities from 60 different countries. A correlation analysis was performed to determine how significant an impact each variable—such as gasoline price, population density, and gross domestic product (GDP)—appeared to have on citywide energy consumption. The dependent variable for this analysis depended on the data set from which information was obtained: per capita energy use for the GEA data, per capita transportation energy use for the UITP data, and per capita greenhouse gas emissions for the WB data. A standard linear regression model was used to determine the significance of each independent variable. Continue reading

Barcelona Study Finds Impact of Urban Green Space Is Appreciable, but Small

by Dan McCabe

One aspect of urban ecology that is often overlooked in development is the biological benefit of vegetation in cities. In order to quantify the environmental impact of urban plants, Baró et al. (2014) analyzed the effect of green spaces on air quality and carbon sequestration in the city of Barcelona, Spain. The authors randomly selected nearly 600 small plots of land within the city limits and collected field data on the plant life and pollutant levels in each. This information, along with meteorological data, was then processed using i-Tree Eco software, which quantified the biological and economic effects of vegetation on both air quality and climate change. In this software model, green space is treated as providing two kinds of ecosystem benefits—defined as air purification and global climate regulation—as well as one harmful consequence, the emission of biogenic volatile organic compounds (BVOCs). For this case study, the model focused only on the levels of particulate matter (PM10) and NO­2 and no other pollutants that harm air quality, because Barcelona has recently had exceedingly high concentrations of these two pollutants. Continue reading

Models Reveal Climatic Impacts of Urban Expansion

by Dan McCabe

Greenhouse gases have earned a bad name for their impacts on global climate, but in modern cities, the built environment itself can contribute to climate change just as much. In order to quantify and analyze the impacts of urbanization on local and regional temperature and hydroclimate, Georgescu et. al. (2014) modeled the impacts of urban expansion in the contiguous United States in a variety of scenarios. The authors considered a range of different predicted population levels in the United States for the year 2100. Using advanced atmospheric models, they found that if no urban climate change mitigation measures were put into place by then, summertime urban-induced warming of 1–3 °C can be expected in cities, with exact values varying by location. These increased temperatures are due solely to the effects of the built environment, as simulations were run using climate data from 2001-2008 without any assumptions about future warming due to increased greenhouse gas emissions. Continue reading