Arsenic (As) is a naturally occurring element that poses a health risk when continually consumed at levels exceeding the Environmental Protection Agencies (EPA) maximum contaminant level (MCL) of 10 ppb. With the Arizona Department of Water Resources considering reliance on other sources of water other than just solely surface water, groundwater proves a reliable, supplemental source. The Salt River Project (SRP) wants to effectively treat their noncompliance groundwater sources to meet EPA compliance. Rapid small-scale column tests (RSSCTs) of two SRP controlled groundwater wells along the Eastern Canal and Consolidated Canal were designed to assist SRP in selection and future design of full-scale packed bed adsorbent media. Main concerns for column choice is effectiveness, design space at groundwater wells, and simplicity. Two adsorbent media types were tested for effective treatment of As to below the MCL: a synthetic iron oxide, Bayoxide E33, and a strong base anion exchange resin, SBG-1. Both media have high affinity toward As and prove effective at treating As from these groundwater sources. Bayoxide E33 RSSCT performance indicated that As treatment lasted to near 60,000 bed volumes (BV) in both water sources and still showed As adsorption extending past this operation ranging from several months to a year. SBG-1 RSSCT performance indicated As, treatment lasted to 500 BV, with the added benefit of being regenerated. At 5%, 13%, and 25% brine regeneration concentrations, regeneration showed that 5% brine is effective, yet would complicate overall design and footprint. Bayoxide E33 was selected as the best adsorbent media for SRP use in full-scale columns at groundwater wells due to its simplistic design and high efficiency.

Vapor intrusion (VI) pathway assessment often involves the collection and analysis of groundwater, soil gas, and indoor air data. There is temporal variability in these data, but little is understood about the characteristics of that variability and how it influences pathway assessment decision-making. This research included the first-ever collection of a long-term high-frequency indoor air data set at a house with VI impacts overlying a dilute chlorinated solvent groundwater plume. It also included periodic synoptic snapshots of groundwater and soil gas data and high-frequency monitoring of building conditions and environmental factors. Indoor air trichloroethylene (TCE) concentrations varied over three orders-of-magnitude under natural conditions, with the highest daily VI activity during fall, winter, and spring months. These data were used to simulate outcomes from common sampling strategies, with the result being that there was a high probability (up to 100%) of false-negative decisions and poor characterization of long-term exposure. Temporal and spatial variability in subsurface data were shown to increase as the sampling point moves from source depth to ground surface, with variability of an order-of-magnitude or more for sub-slab soil gas. It was observed that indoor vapor sources can cause subsurface vapor clouds and that it can take days to weeks for soil gas plumes created by indoor sources to dissipate following indoor source removal. A long-term controlled pressure method (CPM) test was conducted to assess its utility as an alternate approach for VI pathway assessment. Indoor air concentrations were similar to maximum concentrations under natural conditions (9.3 μg/m3 average vs. 13 μg/m3 for 24 h TCE data) with little temporal variability. A key outcome was that there were no occurrences of false-negative results. Results suggest that CPM tests can produce worst-case exposure conditions at any time of the year. The results of these studies highlight the limitations of current VI pathway assessment approaches and demonstrate the need for robust alternate diagnostic tools, such as CPM, that lead to greater confidence in data interpretation and decision-making.

Particulate trace metals can enter the atmosphere as mineral dust, sea spray, anthropogenic emissions, biomass burning, etc. Once in the atmosphere they can undergo a variety of transformations including aqueous phase (cloud) processing, photochemical reactions, interact with gases, and ultimately deposit. Metals in aerosols are of particular interest because of their natural and anthropogenic sources as well as their effects on local (human health) and global (climate change) scales. This work investigates the metal component of atmospheric particles and how it changes during physical and chemical processes at local, regional and global scales, through laboratory and field studies. In the first part of this work, the impact of local dust storms (haboobs) on ambient metal concentrations and speciation is investigated in Tempe, AZ. It was found that metal concentrations substantially increase (> 10 times) during these events before returning to pre-storm levels. In a second part of this work, the impact of fog processing on metal concentrations, solubility and speciation is examined through field observations in California’s Central Valley. The observations show that fog processing has a profound effect on local metal concentrations but the trends are not consistent between sites or even between events, indicating complex processes that need further investigation. For example, fogs have an effect on scavenging and solubility of iron in Davis, while in Fresno soluble iron content is indicative of the source of the aerosol. The last part of the thesis investigates the role of particle size on the solubilization of iron from mineral dust aerosols during global atmospheric transport through laboratory experiments. The experiments showed that mineralogy and pH have the greatest effect on iron solubility in atmospheric aerosols in general while particle size and photochemistry impact mainly the solubility of iron oxides.

The atmosphere contains a substantial amount of water soluble organic material, yet despite years of efforts, little is known on the structure, composition and properties of this organic matter. Aqueous phase processing by fogs and clouds of the gas and particulate organic material is poorly understood despite the importance for air pollution and climate. On one hand, gas phase species can be processed by fog/cloud droplets to form lower volatility species, which upon droplet evaporation lead to new aerosol mass, while on the other hand larger nonvolatile material can be degraded by in cloud oxidation to smaller molecular weight compounds and eventually CO2.

In this work High Performance Size Exclusion Chromatography coupled with inline organic carbon detection (SEC-DOC), Diffusion-Ordered Nuclear Magnetic Resonance spectroscopy (DOSY-NMR) and Fluorescence Excitation-Emission Matrices (EEM) were used to characterize molecular weight distribution, functionality and optical properties of atmospheric organic matter. Fogs, aerosols and clouds were studied in a variety of environments including Central Valley of California (Fresno, Davis), Pennsylvania (Selinsgrove), British Columbia (Whistler) and three locations in Norway. The molecular weight distributions using SEC-DOC showed smaller molecular sizes for atmospheric organic matter compared to surface waters and a smaller material in fogs and clouds compared to aerosol particles, which is consistent with a substantial fraction of small volatile gases that partition into the aqueous phase. Both, cloud and aerosol samples presented a significant fraction (up to 21% of DOC) of biogenic nanoscale material. The results obtained by SEC-DOC were consistent with DOSY-NMR observations.

Cloud processing of organic matter has also been investigated by combining field observations (sample time series) with laboratory experiments under controlled conditions. Observations revealed no significant effect of aqueous phase chemistry on molecular weight distributions overall although during cloud events, substantial differences were apparent between organic material activated into clouds compared to interstitial material. Optical properties on the other hand showed significant changes including photobleaching and an increased humidification of atmospheric material by photochemical aging. Overall any changes to atmospheric organic matter during cloud processing were small in terms of bulk carbon properties, consistent with recent reports suggesting fogs and clouds are too dilute to substantially impact composition.

Chloroform (CHCl3) is an important atmospheric pollutant by its direct health effects as well as by its contribution to photochemical smog formation. Chloroform outgassing from swimming pools is not typically considered a source of atmospheric CHCl3 because swimming pools are scarce compared to other sources. However, large urban areas in hot climates such as Phoenix, AZ contain a substantial amount of swimming pools, potentially resulting in significant atmospheric fluxes. In this study, CHCl3 formation potential (FP) from disinfection of swimming pools in Phoenix was investigated through laboratory experiments and annual CHCl3 emission fluxes from swimming pools were estimated based on the experimental data.

Swimming pool water (collected in June 2014 in Phoenix) and model contaminants (Pharmaceuticals and Personal Care Products (PPCPs), Endocrine Disrupting Compounds (EDCs), artificial sweeteners, and artificial human waste products) were chlorinated in controlled laboratory experiments. The CHCl3 production during chlorination was determined using Gas Chromatography-Mass Spectrometry (GC-MS) following solid-phase microextraction (SPME). Upon chlorination, all swimming pool water samples and contaminants produced measureable amounts of chloroform. Chlorination of swimming pool water produced 0.005-0.134 mol CHCl3/mol C and 0.004-0.062 mol CHCl3/mol Cl2 consumed. Chlorination of model contaminants produced 0.004-0.323 mol CHCl3/mol C and 0.001-0.247 mol CHCl3/mol Cl2 consumed. These numbers are comparable and indicate that the model contaminants react similarly to swimming pool water during chlorination. The CHCl3 flux from swimming pools in Phoenix was estimated at approximately 3.9-4.3 Gg/yr and was found to be largely dependent on water temperature and wind speed while air temperature had little effect. This preliminary estimate is orders of magnitude larger than previous estimates of anthropogenic emissions in Phoenix suggesting that swimming pools might be a significant source of atmospheric CHCl3 locally.

The environmental and economic assessment of neighborhood-scale transit-oriented urban form changes should include initial construction impacts through long-term use to fully understand the benefits and costs of smart growth policies. The long-term impacts of moving people closer to transit require the coupling of behavioral forecasting with environmental assessment. Using new light rail and bus rapid transit in Los Angeles, California as a case study, a life-cycle environmental and economic assessment is developed to assess the potential range of impacts resulting from mixed-use infill development. An integrated transportation and land use life-cycle assessment framework is developed to estimate energy consumption, air emissions, and economic (public, developer, and user) costs. Residential and commercial buildings, automobile travel, and transit operation changes are included and a 60-year forecast is developed that compares transit-oriented growth against growth in areas without close access to high-capacity transit service. The results show that commercial developments create the greatest potential for impact reductions followed by residential commute shifts to transit, both of which may be effected by access to high-capacity transit, reduced parking requirements, and developer incentives. Greenhouse gas emission reductions up to 470 Gg CO₂-equivalents per year can be achieved with potential costs savings for TOD users. The potential for respiratory impacts (PM₁₀-equivalents) and smog formation can be reduced by 28-35%. The shift from business-as-usual growth to transit-oriented development can decrease user costs by $3,100 per household per year over the building lifetime, despite higher rental costs within the mixed-use development.

Wind measurements are fundamental inputs for the evaluation of potential energy yield and performance of wind farms. Three-dimensional scanning coherent Doppler lidar (CDL) may provide a new basis for wind farm site selection, design, and control. In this research, CDL measurements obtained from multiple wind energy developments are analyzed and a novel wind farm control approach has been modeled. The possibility of using lidar measurements to more fully characterize the wind field is discussed, specifically, terrain effects, spatial variation of winds, power density, and the effect of shear at different layers within the rotor swept area. Various vector retrieval methods have been applied to the lidar data, and results are presented on an elevated terrain-following surface at hub height. The vector retrieval estimates are compared with tower measurements, after interpolation to the appropriate level. CDL data is used to estimate the spatial power density at hub height. Since CDL can measure winds at different vertical levels, an approach for estimating wind power density over the wind turbine rotor-swept area is explored. Sample optimized layouts of wind farm using lidar data and global optimization algorithms, accounting for wake interaction effects, have been explored. An approach to evaluate spatial wind speed and direction estimates from a standard nested Coupled Ocean and Atmosphere Mesoscale Prediction System (COAMPS) model and CDL is presented. The magnitude of spatial difference between observations and simulation for wind energy assessment is researched. Diurnal effects and ramp events as estimated by CDL and COAMPS were inter-compared. Novel wind farm control based on incoming winds and direction input from CDL's is developed. Both yaw and pitch control using scanning CDL for efficient wind farm control is analyzed. The wind farm control optimizes power production and reduces loads on wind turbines for various lidar wind speed and direction inputs, accounting for wind farm wake losses and wind speed evolution. Several wind farm control configurations were developed, for enhanced integrability into the electrical grid. Finally, the value proposition of CDL for a wind farm development, based on uncertainty reduction and return of investment is analyzed.

Life cycle assessment (LCA) is a powerful framework for environmental decision making because the broad boundaries called for prevent shifting of burden from one life-cycle phase to another. Numerous experts and policy setting organizations call for the application of LCA to developing nanotechnologies. Early application of LCA to nanotechnology may identify environmentally problematic processes and supply chain components before large investments contribute to technology lock in, and thereby promote integration of environmental concerns into technology development and scale-up (enviro-technical integration). However, application of LCA to nanotechnology is problematic due to limitations in LCA methods (e.g., reliance on data from existing industries at scale, ambiguity regarding proper boundary selection), and because social drivers of technology development and environmental preservation are not identified in LCA. This thesis proposes two methodological advances that augment current capabilities of LCA by incorporating knowledge from technical and social domains. Specifically, this thesis advances the capacity for LCA to yield enviro-technical integration through inclusion of scenario development, thermodynamic modeling, and use-phase performance bounding to overcome the paucity of data describing emerging nanotechnologies. With regard to socio-technical integration, this thesis demonstrates that social values are implicit in LCA, and explores the extent to which these values impact LCA practice and results. There are numerous paths of entry through which social values are contained in LCA, for example functional unit selection, impact category selection, and system boundary definition - decisions which embody particular values and determine LCA results. Explicit identification of how social values are embedded in LCA promotes integration of social and environmental concerns into technology development (socio-enviro-technical integration), and may contribute to the development of socially-responsive and environmentally preferable nanotechnologies. In this way, tailoring LCA to promote socio-enviro-technical integration is a tangible and meaningful step towards responsible innovation processes.