Focus on Environmental Assessments in the Built Environment

Environmental assessments have been developed with increasing emphasis since the wide-scale emergence of environmental concerns in the 1970s. However, after decades there is still plenty of room left for development. These assessments are also rapidly becoming more and more crucial as we seem to be reaching the boundaries of the carrying capacity of our planet. Assessments of the emissions from the built environment and especially of the interactions between human communities and emissions are in a very central role in the quest to solve the great problem of sustainable living. Policy- makers and professionals in various fields urgently need reliable data on the current conditions and realistic future projections, as well as robust and scientifically defensible models for decision making. This recognition was the main motivation to call for this Focus Issue, and the published contributions truly highlight the same point. This editorial provides brief summaries and discussions on the 16 articles of the Focus Issue, depicting the several interesting perspectives they offer to advance the state of the art. Now we encourage academics, practitioners, government, industry, individual consumers, and other decision makers to utilize the available findings and develop the domain of environmental assessment of the built environment further. Indeed, we hope that this Focus Issue is merely a kernel of a significantly large future body of literature.

In our rapidly urbanizing world, sustainable transportation presents a major challenge. Transportation decisions have considerable direct impacts on urban society, both positive and negative, for example through changes in transit times and economic productivity, urban connectivity, tailpipe emissions and attendant air quality concerns, traffic accidents, and noise pollution. Much research has been dedicated to quantifying these direct impacts for various transportation modes. Transportation planning decisions also result in a variety of indirect environmental and human health impacts, a portion of which can accrue outside of the transit service area and so outside of the local decision-making process. Integrated modeling of direct and indirect impacts over the life cycle of different transportation modes provides decision support that is more comprehensive and less prone to triggering unintended consequences than a sole focus on direct tailpipe emissions.

The recent work of Chester et al (2013) in this journal makes important contributions to this research by examining the environmental implications of introducing bus rapid transit and light rail in Los Angeles using life cycle assessment (LCA). Transport in the LA region is dominated by automobile trips, and the authors show that potential shifts to either bus or train modes would reduce energy use and emissions of criteria air pollutants, on an average passenger mile travelled basis. This work compares not just the use of each vehicle, but also upstream impacts from its manufacturing and maintenance, as well as the construction and maintenance of the entire infrastructure required for each mode. Previous work by the lead author (Chester and Horvath 2009), has shown that these non-operational sources and largely non-local can dominate life cycle impacts from transportation, again on an average (or attributional) basis, for example increasing rail-related GHG emissions by >150% over just operational emissions.

While average results are valuable in comparing transport modes generally, they are less representative of local planning decisions, where the focus is on understanding the consequences of new infrastructure and how it might affect traffic, community impacts, and environmental aspects going forward. Chester et al (2013) also present their results using consequential LCA, which provides more detailed insights about the marginal effects of the specific rapid bus and light rail lines under study. The trade-offs between the additional resources required to install the public transit infrastructure (the 'resource debt') and the environmental advantages during the operation of these modes can be considered explicitly in terms of environmental impact payback periods, which vary with the type of environmental impact being considered. For example, bus rapid transit incurs a relatively small carbon debt associated with the GHG emissions of manufacturing new buses and installing transit infrastructure and pays this debt off almost immediately, while it takes half a century for the light rail line to pay off the 'smog debt' of its required infrastructure. This payback period approach, ubiquitous in life cycle costing, has been useful for communicating the magnitude of unintended environmental consequences from other resource and land management decisions, e.g., the release of soil carbon from land conversion to bioenergy crops (Fargione et al 2008), and will likely grow in prevalence as consequential LCA is used for decision support.

The locations of projected emissions is just as important to decision-making as their magnitudes, as policy-making bodies seek to understand effects in their jurisdictions; however, life cycle impact assessment methods typically aggregate results by impact category rather than by source or sink location. Chester et al (2013) address this issue by providing both local (within Los Angeles) and total emissions results, with accompanying local-only payback periods. Much more challenging is the geographic mapping of impacts that these emissions will cause, given the many point and mobile sources of air pollutants over the entire transportation life cycle. Integration of LCA with high-resolution data sets is an active area of model development (Mutel and Hellweg 2009) and will provide site- and population-specific information for impacts ranging from water quality to biodiversity to human respiratory health.

Another complex challenge in modeling environmental impacts of transportation (and cities in general) is the long run, interdependent relationship between transportation technologies and urban form. LCA modeling has tended to assume a fixed pattern of settlements and demand for mobility and then examined changes to a particular technology or practice within the transportation system, such as electric or hybrid vehicles or improved pavement materials. New transit options or other travel demand management strategies might induce mode switching or reduced trips, but the overall pattern of where people live and work is generally assumed in these models to be constant in the short run. In contrast, the automobile has been influencing land-use patterns for a century, and it is the resulting geographic structure that determines the baseline need for transportation, and thus drives the use of material and energy resources used in transportation systems (Kunstler 1994).

We have seen that cities with high population densities tend to have lower tailpipe emissions from transportation (Kennedy et al 2009). Recent studies have modeled how changes in urban land-use or zoning changes the geographic structure of transportation demand and then used LCA to determine the environmental benefits of such policies. For example, Mashayekh et al (2012) summarized travel demand reductions projected from several studies of compact, smart growth, and brownfield in-fill development strategies to find benefits ranging up to 75% reductions in life cycle GHG and air pollutant emissions. A related study in Toronto on life cycle energy use and GHG emissions for high- and low-density development strategies found a ~60% difference in GHG emissions, largely due to transportation (Norman et al 2006). System dynamics and agent-based models may complement LCA in capturing long-term effects of transportation strategies as they are inherently dynamic (Stepp et al 2009), and can internalize spatially resolved decisions about where to settle and work (Waddell 2002).

Transportation planning decisions have both direct and indirect, spatially distributed, often long-term effects on our health and our environment. The accompanying work by Chester et al (2013) provides a well-documented case study that highlights the potential of LCA as a rich source of decision support.

References

Chester M, Pincetl S, Elizabeth Z, Eisenstein W and Matute J 2013 Infrastructure and automobile shifts: positioning transit to reduce life-cycle environmental impacts for urban sustainability goals Environ. Res. Lett. 8 015041

Chester M V and Horvath A 2009 Environmental assessment of passenger transportation should include infrastructure and supply chains Environ. Res. Lett. 4 024008

Fargione J, Hill J, Tilman D, Polasky S and Hawthorne P 2008 Land clearing and the biofuel carbon debt Science 319 1235–8

Kennedy C, Steinberger J, Gasson B, Hansen Y, Hillman T, Havránek M, Pataki D, Phdungsilp A, Ramaswami A and Mendez G V 2009 Greenhouse gas emissions from global cities Environ. Sci. Technol. 43 7297–302

Kunstler J H 1994 Geography of Nowhere: The Rise and Decline of America's Man-Made Landscape (New York: Free Press)

Mashayekh Y, Jaramillo P, Samaras C, Hendrickson C T, Blackhurst M, MacLean H L and Matthews H S 2012 Potentials for sustainable transportation in cities to alleviate climate change impacts Environ. Sci. Technol. 46 2529–37

Mutel C L and Hellweg S 2009 Regionalized life cycle assessment: computational methodology and application to inventory databases Environ. Sci. Technol. 43 5797–803

Norman J, MacLean H L and Kennedy C A 2006 Comparing high and low residential density: life-cycle analysis of energy use and greenhouse gas emissions J. Urban Plann. Dev. 132 10–21

Stepp M D, Winebrake J J, Hawker J S and Skerlos S J 2009 Greenhouse gas mitigation policies and the transportation sector: the role of feedback effects on policy effectiveness Energy Policy 37 2774–87

Waddell P 2002 UrbanSim: modeling urban development for land use, transportation, and environmental planning J. Am. Plann. Assoc. 68 297–314

Climate change will affect the concentrations of air pollutants in buildings. The resulting shifts in human exposure may influence public health. Changes can be anticipated because of altered outdoor pollution and also owing to changes in buildings effected in response to changing climate. Three classes of factors govern indoor pollutant levels in occupied spaces: (a) properties of pollutants; (b) building factors, such as the ventilation rate; and (c) occupant behavior. Diversity of indoor conditions influences the public health significance of climate change. Potentially vulnerable subpopulations include not only the young and the infirm but also those who lack resources to respond effectively to changing conditions. Indoor air pollutant levels reflect the sum of contributions from indoor sources and from outdoor pollutants that enter with ventilation air. Pollutant classes with important indoor sources include the byproducts of combustion, radon, and volatile and semivolatile organic compounds. Outdoor pollutants of special concern include particulate matter and ozone. To ensure good indoor air quality it is important first to avoid high indoor emission rates for all pollutants and second to ensure adequate ventilation. A third factor is the use of air filtration or air cleaning to achieve further improvements where warranted.

To help address the built environmental issues of both heat island and stormwater runoff, strategies that make pavements cooler and permeable have been investigated through measurements and modeling of a set of pavement test sections. The investigation included the hydraulic and thermal performance of the pavements. The permeability results showed that permeable interlocking concrete pavers have the highest permeability (or infiltration rate, ∼0.5 cm s⁻¹). The two permeable asphalt pavements showed the lowest permeability, but still had an infiltration rate of ∼0.1 cm s⁻¹, which is adequate to drain rainwater without generating surface runoff during most typical rain events in central California. An increase in albedo can significantly reduce the daytime high surface temperature in summer. Permeable pavements under wet conditions could give lower surface temperatures than impermeable pavements. The cooling effect highly depends on the availability of moisture near the surface layer and the evaporation rate. The peak cooling effect of watering for the test sections was approximately 15–35 °C on the pavement surface temperature in the early afternoon during summer in central California. The evaporative cooling effect on the pavement surface temperature at 4:00 pm on the third day (25 h after watering) was still 2–7 °C lower compared to that on the second day, without considering the higher air temperature on the third day. A separate and related simulation study performed by UCPRC showed that full depth permeable pavements, if designed properly, can carry both light-duty traffic and certain heavy-duty vehicles while retaining the runoff volume captured from an average California storm event. These preliminarily results indicated the technical feasibility of combined reflective and permeable pavements for addressing the built environment issues related to both heat island mitigation and stormwater runoff management.

Efforts to reduce the environmental impacts of transportation infrastructure have generally overlooked many of the efficiencies that can be obtained by considering the relevant engineering and economic aspects as a system. Here, we present a framework for quantifying the burdens of ground transportation in urban settings that incorporates travel time, vehicle fuel and pavement maintenance costs. A Pareto set of bi-directional lane configurations for two-lane roadways yields non-dominated combinations of lane width, bicycle lanes and curb parking. Probabilistic analysis and microsimulation both show dramatic mobility reductions on road segments of insufficient width for heavy vehicles to pass bicycles without encroaching on oncoming traffic. This delay is positively correlated with uphill grades and increasing traffic volumes and inversely proportional to total pavement width. The response is nonlinear with grade and yields mixed uphill/downhill optimal lane configurations. Increasing bicycle mode share is negatively correlated with total costs and emissions for lane configurations allowing motor vehicles to safely pass bicycles, while the opposite is true for configurations that fail to facilitate passing. Spatial impacts on mobility also dictate that curb parking exhibits significant spatial opportunity costs related to the total cost Pareto curve. The proposed framework provides a means to evaluate relatively inexpensive lane reconfiguration options in response to changing modal share and priorities. These results provide quantitative evidence that efforts to reallocate limited pavement space to bicycles, like those being adopted in several US cities, could appreciably reduce costs for all users.

The sustainable development of brownfields reflects a fundamental, yet logical, shift in thinking and policymaking regarding pollution prevention. Life-cycle assessment (LCA) is a tool that can be used to assist in determining the conformity of brownfield development projects to the sustainability paradigm. LCA was applied to the process of a real brownfield redevelopment project, now known as the Chicago Center for Green Technology, to determine the cumulative energy required to complete the following redevelopment stages: (1) brownfield assessment and remediation, (2) building rehabilitation and site development and (3) ten years of operation. The results of the LCA have shown that operational energy is the dominant life-cycle stage after ten years of operation. The preservation and rehabilitation of the existing building, the installation of renewable energy systems (geothermal and photovoltaic) on-site and the use of more sustainable building products resulted in 72 terajoules (TJ) of avoided energy impacts, which would provide 14 years of operational energy for the site.

Public transportation systems are often part of strategies to reduce urban environmental impacts from passenger transportation, yet comprehensive energy and environmental life-cycle measures, including upfront infrastructure effects and indirect and supply chain processes, are rarely considered. Using the new bus rapid transit and light rail lines in Los Angeles, near-term and long-term life-cycle impact assessments are developed, including consideration of reduced automobile travel. Energy consumption and emissions of greenhouse gases and criteria pollutants are assessed, as well the potential for smog and respiratory impacts. Results show that life-cycle infrastructure, vehicle, and energy production components significantly increase the footprint of each mode (by 48–100% for energy and greenhouse gases, and up to 6200% for environmental impacts), and emerging technologies and renewable electricity standards will significantly reduce impacts. Life-cycle results are identified as either local (in Los Angeles) or remote, and show how the decision to build and operate a transit system in a city produces environmental impacts far outside of geopolitical boundaries. Ensuring shifts of between 20–30% of transit riders from automobiles will result in passenger transportation greenhouse gas reductions for the city, and the larger the shift, the quicker the payback, which should be considered for time-specific environmental goals.

An extensive body of literature demonstrates how higher density leads to more efficient energy use and lower greenhouse gas (GHG) emissions from transport and housing. However, our current understanding seems to be limited on the relationships between the urban form and the GHG emissions, namely how the urban form affects the lifestyles and thus the GHGs on a much wider scale than traditionally assumed. The urban form affects housing types, commuting distances, availability of different goods and services, social contacts and emulation, and the alternatives for pastimes, meaning that lifestyles are actually situated instead of personal projects. As almost all consumption, be it services or products, involves GHG emissions, looking at the emissions from transport and housing may not be sufficient to define whether one form would be more desirable than another. In the paper we analyze the urban form–lifestyle relationships in Finland together with the resulting GHG implications, employing both monetary expenditure and time use data to portray lifestyles in different basic urban forms: metropolitan, urban, semi-urban and rural. The GHG implications are assessed with a life cycle assessment (LCA) method that takes into account the GHG emissions embedded in different goods and services. The paper depicts that, while the direct emissions from transportation and housing energy slightly decrease with higher density, the reductions can be easily overridden by sources of indirect emissions. We also highlight that the indirect emissions actually seem to have strong structural determinants, often undermined in studies concerning sustainable urban forms. Further, we introduce a concept of 'parallel consumption' to explain how the lifestyles especially in more urbanized areas lead to multiplication of consumption outside of the limits of time budget and the living environment. This is also part I of a two-stage study. In part II we will depict how various other contextual and socioeconomic variables are actually also very important to take into account, and how diverse GHG mitigation strategies would be needed for different types of area in different locations towards a low-carbon future.

Study of the environmental outcomes of urban densification is a highly context-dependent task. Our study shows that collecting and processing place-based survey data by means of the softGIS method is clearly helpful here. With the map-based internet questionnaire each response remains connected to both the physical environment and the everyday life of the respondent. In our study of the Kuninkaankolmio area (located in the Helsinki metropolitan region) the survey data were combined with urban density variables calculated from register-based data on the existing built environment. The regression analysis indicated that the participants in the survey preferred the same density factors for their future residence as they enjoyed in their current neighbourhood. In the second analysis we related the densities of planned infill developments with the interest respondents had shown in these projects. The results show that new and even quite dense infill developments have been found to be rather attractive, with them often being viewed as interesting supplements to the current urban texture. These findings contribute to the ongoing scientific discussion on the feasibility of densification measures and encourage the Kuninkaankolmio planners to proceed, albeit carefully, with the planned infill developments.

Three broad approaches have emerged for energy and greenhouse gas (GHG) accounting for individual cities: (a) purely in-boundary source-based accounting (IB); (b) community-wide infrastructure GHG emissions footprinting (CIF) incorporating life cycle GHGs (in-boundary plus trans-boundary) of key infrastructures providing water, energy, food, shelter, mobility–connectivity, waste management/sanitation and public amenities to support community-wide activities in cities—all resident, visitor, commercial and industrial activities; and (c) consumption-based GHG emissions footprints (CBF) incorporating life cycle GHGs associated with activities of a sub-set of the community—its final consumption sector dominated by resident households. The latter two activity-based accounts are recommended in recent GHG reporting standards, to provide production-dominated and consumption perspectives of cities, respectively. Little is known, however, on how to normalize and report the different GHG numbers that arise for the same city. We propose that CIF and IB, since they incorporate production, are best reported per unit GDP, while CBF is best reported per capita. Analysis of input–output models of 20 US cities shows that GHG^CIF/GDP is well suited to represent differences in urban energy intensity features across cities, while GHG^CBF/capita best represents variation in expenditures across cities. These results advance our understanding of the methods and metrics used to represent the energy and GHG performance of cities.

US cities are beginning to experiment with a regulatory approach to address information failures in the real estate market by mandating the energy benchmarking of commercial buildings. Understanding how a commercial building uses energy has many benefits; for example, it helps building owners and tenants identify poor-performing buildings and subsystems and it enables high-performing buildings to achieve greater occupancy rates, rents, and property values. This paper estimates the possible impacts of a national energy benchmarking mandate through analysis chiefly utilizing the Georgia Tech version of the National Energy Modeling System (GT-NEMS). Correcting input discount rates results in a 4.0% reduction in projected energy consumption for seven major classes of equipment relative to the reference case forecast in 2020, rising to 8.7% in 2035. Thus, the official US energy forecasts appear to overestimate future energy consumption by underestimating investments in energy-efficient equipment. Further discount rate reductions spurred by benchmarking policies yield another 1.3–1.4% in energy savings in 2020, increasing to 2.2–2.4% in 2035. Benchmarking would increase the purchase of energy-efficient equipment, reducing energy bills, CO₂ emissions, and conventional air pollution. Achieving comparable CO₂ savings would require more than tripling existing US solar capacity. Our analysis suggests that nearly 90% of the energy saved by a national benchmarking policy would benefit metropolitan areas, and the policy's benefits would outweigh its costs, both to the private sector and society broadly.

Cities now consume resources and produce waste in amounts that are incommensurate with the populations they contain. Quantifying and benchmarking the environmental impacts of cities is essential if urbanization of the world's growing population is to occur sustainably. Urban metabolism (UM) is a promising assessment form in that it provides the annual sum material and energy inputs, and the resultant emissions of the emergent infrastructural needs of a city's sociotechnical subsystems. By fusing UM and life cycle assessment (UM–LCA) this study advances the ability to quantify environmental impacts of cities by modeling pressures embedded in the flows upstream (entering) and downstream (leaving) of the actual urban systems studied, and by introducing an advanced suite of indicators. Applied to five global cities, the developed UM–LCA model provided enhanced quantification of mass and energy flows through cities over earlier UM methods. The hybrid model approach also enabled the dominant sources of a city's different environmental footprints to be identified, making UM–LCA a novel and potentially powerful tool for policy makers in developing and monitoring urban development policies. Combining outputs with socioeconomic data hinted at how these forces influenced the footprints of the case cities, with wealthier ones more associated with personal consumption related impacts and poorer ones more affected by local burdens from archaic infrastructure.

A growing body of literature discusses the CO₂ emissions of cities. Still, little is known about emission patterns across density gradients from remote rural places to highly urbanized areas, the drivers behind those emission patterns and the global emissions triggered by consumption in human settlements—referred to here as the carbon footprint. In this letter we use a hybrid method for estimating the carbon footprints of cities and other human settlements in the UK explicitly linking global supply chains to local consumption activities and associated lifestyles. This analysis comprises all areas in the UK, whether rural or urban. We compare our consumption-based results with extended territorial CO₂ emission estimates and analyse the driving forces that determine the carbon footprint of human settlements in the UK. Our results show that 90% of the human settlements in the UK are net importers of CO₂ emissions. Consumption-based CO₂ emissions are much more homogeneous than extended territorial emissions. Both the highest and lowest carbon footprints can be found in urban areas, but the carbon footprint is consistently higher relative to extended territorial CO₂ emissions in urban as opposed to rural settlement types. The impact of high or low density living remains limited; instead, carbon footprints can be comparatively high or low across density gradients depending on the location-specific socio-demographic, infrastructural and geographic characteristics of the area under consideration. We show that the carbon footprint of cities and other human settlements in the UK is mainly determined by socio-economic rather than geographic and infrastructural drivers at the spatial aggregation of our analysis. It increases with growing income, education and car ownership as well as decreasing household size. Income is not more important than most other socio-economic determinants of the carbon footprint. Possibly, the relationship between lifestyles and infrastructure only impacts carbon footprints significantly at higher spatial granularity.

The relationship between urban form and greenhouse gas (GHG) emissions has been studied extensively during the last two decades. The prevailing paradigm arising from these studies is that a dense or compact urban form would best enable low-carbon living. However, the vast majority of these studies have actually concentrated on transportation and/or housing energy, whereas a growing number of studies argue that the GHG implications of other consumption should be taken into account and the relationships evaluated. With this two-part study of four different area types in Finland we illustrate the importance of including all the consumption activities into the GHG assessment. Furthermore, we add to the discussion the idea that consumption choices, or lifestyles, and the resulting GHGs are not just a product of the values of individuals but actually tied to the form of the surrounding urbanization: that is, lifestyles are situated. In part I (Heinonen et al 2013 Environ. Res. Lett. 8 025003) we looked into this situation in Finland, showing how the residents of the most urbanized areas bring about the highest GHG emissions due to their higher consumption volumes and the economies-of-scale advantages in the less urbanized areas. In part II here, we concentrate only on the middle-income segment and look for differences in the lifestyles when the budget constraints are equal. Here we also add the variables housing type and motorization into the assessment. The same time-use and private expenditure data as in part I and the same GHG assessment method are used here to maintain high transparency and comparability between the two parts. The results of the study imply that larger family sizes and economies-of-scale effects in the less dense areas offset the advantages of more dense living when the emissions are assessed on per capita basis. Also, at equal income levels the carbon footprints vary surprisingly little due to complementary effects of the majority of low-carbon lifestyle choices. Motorization was still found to increase the emissions, but a similar pattern regarding housing type was not found.

High-resolution numerical simulations of the urban heat island (UHI) effect with the widely-used Weather Research and Forecasting (WRF) model are assessed. Both the sensitivity of the results to the simulation setup, and the quality of the simulated fields as representations of the real world, are investigated. Results indicate that the WRF-simulated surface temperatures are more sensitive to the planetary boundary layer (PBL) scheme choice during nighttime, and more sensitive to the surface thermal roughness length parameterization during daytime. The urban surface temperatures simulated by WRF are also highly sensitive to the urban canopy model (UCM) used. The implementation in this study of an improved UCM (the Princeton UCM or PUCM) that allows the simulation of heterogeneous urban facets and of key hydrological processes, together with the so-called CZ09 parameterization for the thermal roughness length, significantly reduce the bias (<1.5 °C) in the surface temperature fields as compared to satellite observations during daytime. The boundary layer potential temperature profiles are captured by WRF reasonable well at both urban and rural sites; the biases in these profiles relative to aircraft-mounted senor measurements are on the order of 1.5 °C. Changing UCMs and PBL schemes does not alter the performance of WRF in reproducing bulk boundary layer temperature profiles significantly. The results illustrate the wide range of urban environmental conditions that various configurations of WRF can produce, and the significant biases that should be assessed before inferences are made based on WRF outputs. The optimal set-up of WRF-PUCM developed in this paper also paves the way for a confident exploration of the city-scale impacts of UHI mitigation strategies in the companion paper (Li et al 2014).

Mitigation of the urban heat island (UHI) effect at the city-scale is investigated using the Weather Research and Forecasting (WRF) model in conjunction with the Princeton Urban Canopy Model (PUCM). Specifically, the cooling impacts of green roof and cool (white/high-albedo) roof strategies over the Baltimore-Washington metropolitan area during a heat wave period (7 June–10 June 2008) are assessed using the optimal set-up of WRF-PUCM described in the companion paper by Li and Bou-Zeid (2014). Results indicate that the surface UHI effect (defined based on the urban–rural surface temperature difference) is reduced significantly more than the near-surface UHI effect (defined based on urban–rural 2 m air temperature difference) when these mitigation strategies are adopted. In addition, as the green and cool roof fractions increase, the surface and near-surface UHIs are reduced almost linearly. Green roofs with relatively abundant soil moisture have comparable effect in reducing the surface and near-surface UHIs to cool roofs with an albedo value of 0.7. Significant indirect effects are also observed for both green and cool roof strategies; mainly, the low-level advection of atmospheric moisture from rural areas into urban terrain is enhanced when the fraction of these roofs increases, thus increasing the humidity in urban areas. The additional benefits or penalties associated with modifications of the main physical determinants of green or cool roof performance are also investigated. For green roofs, when the soil moisture is increased by irrigation, additional cooling effect is obtained, especially when the 'unmanaged' soil moisture is low. The effects of changing the albedo of cool roofs are also substantial. These results also underline the capabilities of the WRF-PUCM framework to support detailed analysis and diagnosis of the UHI phenomenon, and of its different mitigation strategies.

Globally, urban areas are expanding, and their regional, spatially cumulative, environmental impacts from transportation projects are not typically assessed. However, incorporation of a Regional Advance Mitigation Planning (RAMP) framework can promote more effective, ecologically sound, and less expensive environmental mitigation. As a demonstration of the first phase of the RAMP framework, we assessed environmental impacts from 181 planned transportation projects in the 19 368 km² San Francisco Bay Area. We found that 107 road and railroad projects will impact 2411–3490 ha of habitat supporting 30–43 threatened or endangered species. In addition, 1175 ha of impacts to agriculture and native vegetation are expected, as well as 125 crossings of waterways supporting anadromous fish species. The extent of these spatially cumulative impacts shows the need for a regional approach to associated environmental offsets. Many of the impacts were comprised of numerous small projects, where project-by-project mitigation would result in increased transaction costs, land costs, and lost project time. Ecological gains can be made if a regional approach is taken through the avoidance of small-sized reserves and the ability to target parcels for acquisition that fit within conservation planning designs. The methods are straightforward, and can be used in other metropolitan areas.