Operation of motor vehicles is one of the major sources of environmental contamination, especially in the urban environment. In many urban watersheds, tires and brake pads are known to be significant sources of zinc (Zn) and copper (Cu), respectively (Hwang et al., 2016). Other less studied non-exhaust traffic emissions contributing to trace metal contamination include wheel balancing weights, road pavement, and used motor oil. This dissertation is composed of 3 separate studies: 1. Investigation into the contribution of non-exhaust traffic emissions to trace metals in roadside soil, 2. Determining the effect of pavement type (asphalt vs. concrete) on trace metals in road dust, and 3. Development of a transport model for non-exhaust traffic emissions in the urban environment.;In Study 1, roadside soil samples were collected along the State Highway 6 in Sugarland, TX, sieved to separate size fractions, and acid digested following EPA Method 3052. Trace metal concentrations were quantified using Agilent 7500a Inductively Coupled Plasma -- Mass Spectrometer (ICP-MS). In Study 2, road dust samples were collected on concrete and asphalt sections of Highway 59 in Houston, Texas; samples were prepared and analyzed using the method described in Study 1. Enrichment factor analysis and chemical mass balance model is applied to both Studies 1 and 2 to calculate the extent of trace metal enrichment, and source apportionment of metals. In Study 3, a transport model for non-exhaust traffic emissions was developed for 5 major pollutants: particulate matter < 10microm in diameter (PM10), particulate matter < 2.5microm in diameter (PM2.5), and zinc, copper, and lead. Sources of pollutants were identified and median emission factors were assigned using published values and the results of Study 2. Published daily vehicle distance traveled (km) and number of vehicles registered were used in conjunction with source concentration and emission factor to calculate contaminant loads for individual vehicle (kg/veh/yr) and Houston metropolitan area (kg/yr).;In Study 1, enrichment factor analysis suggests that non-exhaust traffic emissions are a major source of Cr, Pb, Zn and Cu to the roadside environment. Linear regression analysis suggests that Cu and Zn are highly influenced by anthropogenic contamination. High coefficient of variation values for Co, Cr, Cu, Pb, and Zn suggest concentrations are a result of diverse/anthropogenic sources. A chemical mass balance model was used to quantify contribution of individual sources to enriched metals. Brake dust, tire wear and abraded wheel weights are primary sources of Cu, Zn, and Pb, respectively. In Study 2, concentrations of trace metals in road dust increased with decreasing particle size, while the mass of deposited particles on pavement surfaces (g/km2) decreased with decreasing particle size. Although < 63microm particles contained highest trace metal concentration, 250-125microm particles contribute to the greatest total mass of trace metals. Enrichment factor analysis indicates Cu and Zn are grossly contaminated in road dust, and primary sources are identified as brake and tire wear, respectively, using a chemical mass balance model. Road pavement is identified as a significant source of Pb, V, Ni, and Co in road dust, while abraded wheel weights are the primary source of Pb. In Study 3, tire wear is calculated to contribute 91 and 93% of total PM10 and PM2.5 generated through non-exhaust traffic emissions, respectively. Brake dust from passenger vehicles contributes over 98% of Cu emissions, and resuspension is shown to be an important force responsible for aerosolizing previously generated PM10 and PM2.5. Non-exhaust traffic emissions release Zn, Cu, and Pb at a rate of approximately 160, 17, and 15 metric tons/yr in Houston Metropolitan area. Although it is likely that these sources contribute significantly to metals entering urban streams, without further research, it is impossible to quantify their contribution compared to other sources of contamination.;There are several factors limiting accuracy and precision when describing trace metal loads entering environmental matrices. However, broad generalizations can be inferred to estimate the effectiveness of green infrastructures (i.e., green roofs, vegetated swales, permeable pavement) by estimating the total amount of trace metals released in a study area, compared to estimates of the amount sequestered in green infrastructures. This model would also be effective in making broad comparisons to quantify the effectiveness of environmental policies (i.e., banning lead from wheel weights, reducing Cu concentration in brake pads, and comparing emissions from different eras: 1960-1980, 1980-2000, 2000-2020, 2020-2050). Quantifiable comparisons are essential for implementing time sensitive environmental policies to reverse the degradation of urban streams, and unnecessary exposure to aquatic life.
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