Public transit systems are often accepted as energy and environmental improvements to automobile travel, however, few life cycle assessments exist to understand the effects of implementation of transit policy decisions. To better inform decision-makers, this project evaluates the decision to construct and operate public transportation systems and the expected energy and environmental benefits over continued automobile use. The public transit systems are selected based on screening criteria. Initial screening included advanced implementation (5 to 10 years so change in ridership could be observed), similar geographic regions to ensure consistency of analysis parameters, common transit agencies or authorities to ensure a consistent management culture, and modes reflecting large infrastructure investments to provide an opportunity for robust life cycle assessment of large impact components. An in-depth screening process including consideration of data availability, project age, energy consumption, infrastructure information, access and egress information, and socio-demographic characteristics was used as the second filter. The results of this selection process led to Los Angeles Metro’s Orange and Gold lines.

In this study, the life cycle assessment framework is used to evaluate energy inputs and emissions of greenhouse gases, particulate matter (10 and 2.5 microns), sulfur dioxide, nitrogen oxides, volatile organic compounds, and carbon monoxide. For the Orange line, Gold line, and competing automobile trip, an analysis system boundary that includes vehicle, infrastructure, and energy production components is specified. Life cycle energy use and emissions inventories are developed for each mode considering direct (vehicle operation), ancillary (non-vehicle operation including vehicle maintenance, infrastructure construction, infrastructure operation, etc.), and supply chain processes and services. In addition to greenhouse gas emissions, the inventories are linked to their potential for respiratory impacts and smog formation, and the time it takes to payback in the lifetime of each transit system.

Results show that for energy use and greenhouse gas emissions, the inclusion of life cycle components increases the footprint between 42% and 91% from vehicle propulsion exclusively. Conventional air emissions show much more dramatic increases highlighting the effectiveness of “tailpipe” environmental policy. Within the life cycle, vehicle operation is often small compared to other components. Particulate matter emissions increase between 270% and 5400%. Sulfur dioxide emissions increase by several orders of magnitude for the on road modes due to electricity use throughout the life cycle. NOx emissions increase between 31% and 760% due to supply chain truck and rail transport. VOC emissions increase due to infrastructure material production and placement by 420% and 1500%. CO emissions increase by between 20% and 320%. The dominating contributions from life cycle components show that the decision to build an infrastructure and operate a transportation mode in Los Angeles has impacts far outside of the city and region. Life cycle results are initially compared at each system’s average occupancy and a breakeven analysis is performed to compare the range at which modes are energy and environmentally competitive.

The results show that including a broad suite of energy and environmental indicators produces potential tradeoffs that are critical to decision makers. While the Orange and Gold line require less energy and produce fewer greenhouse gas emissions per passenger mile traveled than the automobile, this ordering is not necessarily the case for the conventional air emissions. It is possible that a policy that focuses on one pollutant may increase another, highlighting the need for a broad set of indicators and life cycle thinking when making transportation infrastructure decisions.

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.

Objectives: We estimated neighborhood effects of population characteristics and built and natural environments on deaths due to heat exposure in Maricopa County, Arizona (2000–2008).

Methods: We used 2000 U.S. Census data and remotely sensed vegetation and land surface temperature to construct indicators of neighborhood vulnerability and a geographic information system to map vulnerability and residential addresses of persons who died from heat exposure in 2,081 census block groups. Binary logistic regression and spatial analysis were used to associate deaths with neighborhoods.

Results: Neighborhood scores on three factors—socioeconomic vulnerability, elderly/isolation, and unvegetated area—varied widely throughout the study area. The preferred model (based on fit and parsimony) for predicting the odds of one or more deaths from heat exposure within a census block group included the first two factors and surface temperature in residential neighborhoods, holding population size constant. Spatial analysis identified clusters of neighborhoods with the highest heat vulnerability scores. A large proportion of deaths occurred among people, including homeless persons, who lived in the inner cores of the largest cities and along an industrial corridor.

Conclusions: Place-based indicators of vulnerability complement analyses of person-level heat risk factors. Surface temperature might be used in Maricopa County to identify the most heat-vulnerable neighborhoods, but more attention to the socioecological complexities of climate adaptation is needed.

In this study we characterized the relationship between temperature and mortality in central Arizona desert cities that have an extremely hot climate. Relationships between daily maximum apparent temperature (ATmax) and mortality for eight condition-specific causes and all-cause deaths were modeled for all residents and separately for males and females ages <65 and ≥65 during the months May–October for years 2000–2008. The most robust relationship was between ATmax on day of death and mortality from direct exposure to high environmental heat. For this condition-specific cause of death, the heat thresholds in all gender and age groups (ATmax = 90–97 °F; 32.2‒36.1 °C) were below local median seasonal temperatures in the study period (ATmax = 99.5 °F; 37.5 °C). Heat threshold was defined as ATmax at which the mortality ratio begins an exponential upward trend. Thresholds were identified in younger and older females for cardiac disease/stroke mortality (ATmax = 106 and 108 °F; 41.1 and 42.2 °C) with a one-day lag. Thresholds were also identified for mortality from respiratory diseases in older people (ATmax = 109 °F; 42.8 °C) and for all-cause mortality in females (ATmax = 107 °F; 41.7 °C) and males <65 years (ATmax = 102 °F; 38.9 °C). Heat-related mortality in a region that has already made some adaptations to predictable periods of extremely high temperatures suggests that more extensive and targeted heat-adaptation plans for climate change are needed in cities worldwide.

Human exposure to excessively warm weather, especially in cities, is an increasingly important public health problem. This study examined heat-related health inequalities within one city in order to understand the relationships between the microclimates of urban neighborhoods, population characteristics, thermal environments that regulate microclimates, and the resources people possess to cope with climatic conditions. A simulation model was used to estimate an outdoor human thermal comfort index (HTCI) as a function of local climate variables collected in 8 diverse city neighborhoods during the summer of 2003 in Phoenix, USA. HTCI is an indicator of heat stress, a condition that can cause illness and death. There were statistically significant differences in temperatures and HTCI between the neighborhoods during the entire summer, which increased during a heat wave period. Lower socioeconomic and ethnic minority groups were more likely to live in warmer neighborhoods with greater exposure to heat stress. High settlement density, sparse vegetation, and having no open space in the neighborhood were significantly correlated with higher temperatures and HTCI. People in warmer neighborhoods were more vulnerable to heat exposure because they had fewer social and material resources to cope with extreme heat. Urban heat island reduction policies should specifically target vulnerable residential areas and take into account equitable distribution and preservation of environmental resources.

In an extreme heat event, people can go to air-conditioned public facilities if residential air-conditioning is not available. Residences that heat slowly may also mitigate health effects, particularly in neighborhoods with social vulnerability. We explored the contributions of social vulnerability and these infrastructures to heat mortality in Maricopa County and whether these relationships are sensitive to temperature. Using Poisson regression modeling with heat-related mortality as the outcome, we assessed the interaction of increasing temperature with social vulnerability, access to publicly available air conditioned space, home air conditioning and the thermal properties of residences. As temperatures increase, mortality from heat-related illness increases less in census tracts with more publicly accessible cooled spaces. Mortality from all internal causes of death did not have this association. Building thermal protection was not associated with mortality. Social vulnerability was still associated with mortality after adjusting for the infrastructure variables. To reduce heat-related mortality, the use of public cooled spaces might be expanded to target the most vulnerable.

We conducted microclimate simulations in ENVI-Met 3.1 to evaluate the impact of vegetation in lowering temperatures during an extreme heat event in an urban core neighborhood park in Phoenix, Arizona. We predicted air and surface temperatures under two different vegetation regimes: existing conditions representative of Phoenix urban core neighborhoods, and a proposed scenario informed by principles of landscape design and architecture and Urban Heat Island mitigation strategies. We found significant potential air and surface temperature reductions between representative and proposed vegetation scenarios:

1. A Park Cool Island effect that extended to non-vegetated surfaces.
2. A net cooling of air underneath or around canopied vegetation ranging from 0.9 °C to 1.9 °C during the warmest time of the day.
3. Potential reductions in surface temperatures from 0.8 °C to 8.4 °C in areas underneath or around vegetation.

Urban ecosystems are subjected to high temperatures—extreme heat events, chronically hot weather, or both—through interactions between local and global climate processes. Urban vegetation may provide a cooling ecosystem service, although many knowledge gaps exist in the biophysical and social dynamics of using this service to reduce climate extremes. To better understand patterns of urban vegetated cooling, the potential water requirements to supply these services, and differential access to these services between residential neighborhoods, we evaluated three decades (1970–2000) of land surface characteristics and residential segregation by income in the Phoenix, Arizona, USA metropolitan region. We developed an ecosystem service trade‐offs approach to assess the urban heat riskscape, defined as the spatial variation in risk exposure and potential human vulnerability to extreme heat. In this region, vegetation provided nearly a 25°C surface cooling compared to bare soil on low‐humidity summer days; the magnitude of this service was strongly coupled to air temperature and vapor pressure deficits.

To estimate the water loss associated with land‐surface cooling, we applied a surface energy balance model. Our initial estimates suggest 2.7 mm/d of water may be used in supplying cooling ecosystem services in the Phoenix region on a summer day. The availability and corresponding resource use requirements of these ecosystem services had a strongly positive relationship with neighborhood income in the year 2000. However, economic stratification in access to services is a recent development: no vegetation–income relationship was observed in 1970, and a clear trend of increasing correlation was evident through 2000. To alleviate neighborhood inequality in risks from extreme heat through increased vegetation and evaporative cooling, large increases in regional water use would be required. Together, these results suggest the need for a systems evaluation of the benefits, costs, spatial structure, and temporal trajectory for the use of ecosystem services to moderate climate extremes. Increasing vegetation is one strategy for moderating regional climate changes in urban areas and simultaneously providing multiple ecosystem services. However, vegetation has economic, water, and social equity implications that vary dramatically across neighborhoods and need to be managed through informed environmental policies.

Context:
With rapidly expanding urban regions, the effects of land cover changes on urban surface temperatures and the consequences of these changes for human health are becoming progressively larger problems.

Objectives:
We investigated residential parcel and neighborhood scale variations in urban land surface temperature, land cover, and residents’ perceptions of landscapes and heat illnesses in the subtropical desert city of Phoenix, AZ USA.

Methods:
We conducted an airborne imaging campaign that acquired high resolution urban land surface temperature data (7 m/pixel) during the day and night. We performed a geographic overlay of these data with high resolution land cover maps, parcel boundaries, neighborhood boundaries, and a household survey.

Results:
Land cover composition, including percentages of vegetated, building, and road areas, and values for NDVI, and albedo, was correlated with residential parcel surface temperatures and the effects differed between day and night. Vegetation was more effective at cooling hotter neighborhoods. We found consistencies between heat risk factors in neighborhood environments and residents’ perceptions of these factors. Symptoms of heat-related illness were correlated with parcel scale surface temperature patterns during the daytime but no corresponding relationship was observed with nighttime surface temperatures.

Conclusions:
Residents’ experiences of heat vulnerability were related to the daytime land surface thermal environment, which is influenced by micro-scale variation in land cover composition. These results provide a first look at parcel-scale causes and consequences of urban surface temperature variation and provide a critically needed perspective on heat vulnerability assessment studies conducted at much coarser scales.

This study seeks to determine the role of land architecture—the composition and configuration of land cover—as well as cadastral/demographic/economic factors on land surface temperature (LST) and the surface urban heat island effect of Phoenix, Arizona. It employs 1 m National Agricultural Imagery Program data of land-cover with 120mLandsat-derived land surface temperature, decomposed to 30 m, a new measure of configuration, the normalized moment of inertia, and U.S. Census data to address the question for two randomly selected samples comprising 523 and 545 residential neighborhoods (census blocks) in the city. The results indicate that, contrary to most other studies, land configuration has a stronger influence on LST than land composition. In addition, both land configuration and architecture combined with cadastral, demographic, and economic variables, capture a significant amount of explained variance in LST. The results indicate that attention to land architecture in the development of or reshaping of neighborhoods may ameliorate the summer extremes in LST.