Constructed wetlands are considered an inefficient technology for long-term phosphorus (P) removal. The P retention effectiveness of subsurface wetlands can be improved by using appropriate substrates. The objectives of this study were to: (i) use sorption isotherms to estimate the P sorption capacity of the two materials, masonry sand and light weight expanded shale; (ii) describe dissolved P removal in small (2.7 m3) subsurface flow wetlands; (iii) quantify the forms of P retained by the substrates in the pilot cells; and (iv) use resulting data to assess the technical and economic feasibility of the most promising system to remove P. The P sorption capacity of masonry sand and expanded shale, as determined with Langmuir isotherms, was 60 mg/kg and 971 mg/kg respectively. In the pilot cells receiving secondarily treated wastewater, cells containing expanded shale retained a greater proportion of the incoming P (50.8 percent) than cells containing masonry sand (14.5 percent). After a year of operation, samples were analyzed for total P (TP) and total inorganic P (TIP). Subsamples were fractionated into labile-P, Fe+Al-bound P, humic-P, Ca+Mg-bound P, and residual-P. Means and standard deviations of TP retained by the expanded shale and masonry sand were 349 + 169 and 11.9 …

On-road remote sensing has the ability to operate in real-time, and under real world conditions, making it an ideal candidate for detecting gross polluters on major freeways and thoroughfares. In this study, remote sensing was employed to detect carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxide (NO). On-road remote sensing data taken from measurements performed in six states, (Arizona, California, Colorado, Illinois, Texas, and Utah) were cleaned and analyzed. Data mining and exploration were first undertaken in order to search for relationships among variables such as make, year, engine type, vehicle weight, and location. Descriptive statistics were obtained for the three pollutants of interest. The data were found to have non-normal distributions. Applied transformations were ineffective, and nonparametric tests were applied. Due to the extremely large sample size of the dataset (508,617 records), nonparametric tests resulted in "p" values that demonstrated "significance." The general linear model was selected due to its ability to handle data with non-normal distributions. The general linear model was run on each pollutant with output producing descriptive statistics, profile plots, between-subjects effects, and estimated marginal means. Due to insufficient data within certain cells, results were not obtained for gross vehicle weight and engine type. The "year" …