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Social and behavioral research is crucial for securing environmental sustainability and improving human living environments. Although the majority of people now live in urban areas, we have limited empirical evidence of the anticipated behavioral response to climate change. Using empirical data on daily household residential water use and temperature, our research examines the implications of future climate conditions on water conservation behavior in 501 households within the Portland (OR) metropolitan region. We ask whether and how much change in ambient temperatures impact residential household water use, while controlling for taxlot characteristics. Based on our results, we develop a spatially explicit description about the changes in future water use for the study region using a downscaled future climate scenario. The results suggest that behavioral responses are mediated by an interaction of household structural attributes, and magnitude and temporal variability of weather parameters. These findings have implications for the way natural resource managers and planning bureaus prepare for and adapt to future consequences of climate change.

Understanding how local land use and land cover (LULC) shapes intra-urban concentrations of atmospheric pollutants—and thus human health—is a key component in designing healthier cities. Here, NO2 is modeled based on spatially dense summer and winter NO2 observations in Portland-Hillsboro-Vancouver (USA), and the spatial variation of NO2 with LULC investigated using random forest, an ensemble data learning technique. The NO2 random forest model, together with BenMAP, is further used to develop a better understanding of the relationship among LULC, ambient NO2 and respiratory health. The impact of land use modifications on ambient NO2, and consequently on respiratory health, is also investigated using a sensitivity analysis. We find that NO2 associated with roadways and tree-canopied areas may be affecting annual incidence rates of asthma exacerbation in 4–12 year olds by +3000 per 100,000 and −1400 per 100,000, respectively. Our model shows that increasing local tree canopy by 5% may reduce local incidences rates of asthma exacerbation by 6%, indicating that targeted local tree-planting efforts may have a substantial impact on reducing city-wide incidence of respiratory distress. Our findings demonstrate the utility of random forest modeling in evaluating LULC modifications for enhanced respiratory health.

Reducing exposure to degraded air quality is essential for building healthy cities. Although air quality and population vary at fine spatial scales, current regulatory and public health frameworks assess human exposures using county- or city-scales. We build on a spatial analysis technique, dasymetric mapping, for allocating urban populations that, together with emerging fine-scale measurements of air pollution, addresses three objectives: (1) evaluate the role of spatial scale in estimating exposure; (2) identify urban communities that are disproportionately burdened by poor air quality; and (3) estimate reduction in mobile sources of pollutants due to local tree-planting efforts using nitrogen dioxide. Our results show a maximum value of 197% difference between cadastrally-informed dasymetric system (CIDS) and standard estimations of population exposure to degraded air quality for small spatial extent analyses, and a lack of substantial difference for large spatial extent analyses. These results provide the foundation for improving policies for managing air quality, and targeting mitigation efforts to address challenges of environmental justice.

The health impacts of urban air pollution are a growing concern in our rapidly urbanizing world. Urban air pollutants show high intra-urban spatial variability linked to urban land use and land cover (LULC). This correlation of air pollutants with LULC is widely recognized; LULC data is an integral input into a wide range of models, especially land use regression models developed by epidemiologists to study the impact of air pollution on human health. Given the demonstrated links between LULC and urban air pollution, and between urban air pollution and health, an interesting question arises: what is the potential of LULC modifications to mitigate the health impacts of urban air pollution?In this dissertation we assess the potential of LULC modifications to mitigate the health impacts of NO 2 , a respiratory irritant and strong marker for combustionrelated air pollution, in the Portland-Vancouver metropolitan area in northwestern USA. We begin by measuring summer and winter NO 2 in the area using a spatially dense network of passive NO 2 samplers. We next develop an annual average model for NO 2 based on the observational data, using random forestfor the first time in the realm of urban air pollution -to disentangle the effects of highly correlated LULC variables on ambient NO 2 concentrations. We apply this random forest (LURF) model to a 200m spatial grid covering the study area, and use this 200m LURF model to quantify the effect of different urban land use ii categories on ambient concentrations of NO 2 . Using the changes in ambient NO 2 concentrations resulting from land use modifications as input to BenMAP (a health benefits assessment tool form the US EPA), we assess the NO 2 -related health impact associated with each land use category and its modifications. We demonstrate how the LURF model can be used to assess the respiratory health benefits of competing land use modifications, including city-wide and local-scale mitigation strategies based on modifying tree canopy and vehicle miles traveled (VMT).Planting trees is a common land cover modification strategy undertaken by cities to reduce air pollution. Statistical models such as LUR and LURF demonstrate a correlation between tree cover and reduced air pollution, but they cannot demonstrate causation. Hence, we run the atmospheric chemistry and transport model CMAQ to examine to what extent the dry deposition mechanism can explain the reduction of NO 2 which statistical models associate with tree canopy.Results from our research indicate that even though the Portland-Vancouver area is in compliance with the US EPA NO 2 standards, ambient concentrations of NO 2 still create an annual health burden of at least $40 million USD. Our model suggests that NO 2 associated with high intensity development and VMT may be creating an annual health burden of $7 million and $3.3 million USD respectively.Existing tree canopy, on the other hand, is associated with an annual health iii benefit of $1.4 million USD. LULC modifications can mitigate some fraction of...