Journal of Environmental Engineering

Spatial interpolation methods are frequently used to estimate values of physical or chemical constituents in locations where they are not measured. Very little research has been conducted, however, to investigate the relative performance of different interpolation methods in surface waters. The study reported here uses archived water quality data from the Chesapeake Bay to compare three spatial interpolation methods: inverse distance weighting, ordinary kriging, and a universal kriging method that incorporates output from a process-based water quality model. Interpolations were performed on salinity, water temperature, and dissolved oxygen “snap shots” (cruise-based data sets) taken between 1985 and 1994 at 21 different depths for multiple locations in the mainstem Bay, using data compiled by the prototypical Chesapeake Bay Environmental Observatory. The kriging methods generally outperform inverse distance weighting for all parameters and depths. Incorporating output from the water quality model through universal kriging appears to improve some of the interpolations by specifically accounting for some physical and biogeochemical features of the estuary. Such integration of process-based information with statistical interpolation warrants further study.

In urban drainage, metals partition between dissolved $\left(f_d\right)$ and particulate $\left(f_p\right)$ phases. Metals also distribute across particulate matter (PM) gradations. In this study, granulometric metal distributions were examined for similar urban paved source areas in Baton Rouge, La.; Cincinnati; New Orleans; Little Rock, Ark.; and N. Little Rock, Ark. Metal distributions were examined for PM fractions from $<25\mu \text{m}$ to $>4,750\mu \text{m}$ , as suspended $\left(<\sim 25\mu \text{m}\right)$ , settleable $\left(\sim 25–75\mu \text{m}\right)$ , and sediment ( $>75\mu \text{m}$ bed load) fractions. For all areas, analysis of PM indicated that metal mass and concentration $\left(\text{mole}/{\text{m}}^2\right)$ were distributed across the gradation. A cumulative gamma distribution constitutive model related metal mass and PM size. The study focused on Baton Rouge, La. where event-based and composited PM metal distributions were statistically similar. For influent and settled runoff, $f_p$ dominated Cr, Cu, Zn, As, Cd, and Pb partitioning. Influent Cu, Zn, Cd, and Pb exceeded discharge criteria for receiving water beneficial uses on a total metal basis. A constitutive model for Pb and Zn mass distributions at Baton Rouge, La. was combined with Newtonian settling and ideal overflow rate to examine two limiting cases of storm events loading a screened hydrodynamic separator. For low and high flow events, modeling reproduced metal mass of eluted PM (2 to $\sim 250\mu \text{m}$ ) from an HS within 4% of measurement, but when influent Pb and Zn exceeded discharge criteria so did HS effluent. As a separate unit operation, 1 h of quiescent settling did reduce Pb, but not Cu, Zn, and Cd to discharge criteria levels.

The porous matrix and long residence time of snow in traffic corridors can result in the accretion of particulate matter (PM) and metals. This temporary repository contributes PM-based and dissolved metals to surrounding environs during snowmelt. This study focused on distribution and settling of PM-based metals (Al, As, Cd, Cr, Cu, Fe, Pb, and Zn) in snow. Snow was sampled from six sites during four winter seasons. PM-based metals are examined herein as a function of PM granulometry, specifically particle-size distributions (PSDs) and PM surface area. Cumulative metal mass distributions across each PSD are modeled as gamma functions. Results indicate Al (15 g/kg) and Fe (4.2 g/kg) are the highest PM-based concentrations; Cd (0.18 mg/kg) and As (4.9 mg/kg) are the lowest. The PM size $\left(d_{50\text{m}}\right)$ associated with the median metal mass ranges from 179 to $542\mu \text{m}$ . The constitutive gamma results are integrated with Hazen’s settling algorithm to model PM-bound metal separation for a sedimentation basin at a local snow storage site. Flows are modeled in the storm water management model (SWMM) from snowmelt and historical rainfall time series. Results indicate that Type I sedimentation is capable of separating the sediment fraction $\left(>75\mu \text{m}\right)$ and majority of metal mass. While the basin is effective at separation of coarser PM-based metals, additional practices such as pavement and drainage appurtenance cleaning, as well as adsorptive-filtration can further manage suspended PM and metals, as well as dissolved metals.

Buildup/wash-off (BUWO) models are widely used to estimate pollutant export from urban and suburban watersheds. Here, we propose that the mass of washed-off particulate during a storm event is insensitive to the time between storm events (the traditional predictor of particulate accumulation in BUWO models). Our analysis employed USGS data of total suspended solids and discharge data for nonsnow events in a $9.4{\text{-km}}^2$ suburban catchment in Madison, Wis. Kinetic energy of rainfall was calculated using National Weather Service NEXRAD radar reflectivity. A regression analysis found that storm event runoff volume and rainfall kinetic energy explained 81% of the variability in event particulate load; volume alone explained 69% of the variability in event loads. Time between storm events was not significant. Additionally, we simulated storm event particulate loads using a BUWO model and a model assuming a constant mass available for wash-off. Both models produced very similar predictions over a range of parameterizations, suggesting that buildup models could perhaps be simplified under many circumstances.

Linear regression techniques were used to develop practical models to predict total organic carbon (TOC) breakthrough in bituminous granular activated carbon (GAC) adsorbers. Models were developed for two field-scale GAC sizes ( $8\times 30$ and $12\times 40\text{mesh}$ ) and two empty bed contact times (EBCTs) (10 and 20 min). Model input parameters include two water quality variables, influent TOC concentration $\left({\text{TOC}}_0\right)$ and pH, that impact performance. The dependent variables for the models were normalized breakthrough time, throughput in bed volumes, to six fractional ( $\text{TOC}/{\text{TOC}}_0=0.2$ , 0.3, 0.4, 0.5, 0.6, and 0.7) and three mass ( $\text{TOC}=1.0$ , 1.5, and 2.0 mg/L) effluent concentrations. Model development was performed using small-scale breakthrough data from 35 different source waters; external model validation was performed with small-scale breakthrough data from 14 source waters; a sensitivity analysis was performed to ensure that the models effectively capture expected breakthrough trend; and a scalability test was performed to verify the models’ ability to predict breakthrough for field-scale GAC adsorbers.

Aerobic methane oxidation coupled to denitrification (AME-D) is a process in which aerobic methanotrophs oxidize methane and release organic compounds that are used by coexisting denitrifiers as electron donors for denitrification. This process is potentially promising for denitrification of wastewater or landfill leachate poor in organic carbon using methane produced onsite as external electron donor. We studied the kinetics of an aerobic methane-oxidizing denitrifying culture and investigated the effect of dissolved oxygen (DO) concentration and air supply rate on AME-D using a batch reactor and a semicontinuous reactor setup. At methane concentrations of 18–33% in air and air flow rates of $15–35\text{mL}\text{air}{\text{L}}^{-1}\text{liquid}{\text{min}}^{-1}$ , the DO concentration was less than $0.01\text{mg}{\text{L}}^{-1}$ and the nitrate removal reached a maximum value of $56.7\text{mg}{\text{NO}}_3–\text{N}{\text{g}}^{-1}\text{VSS}{d}^{-1}$ with 79% being attributed to denitrification. When the air supply rate was increased to $70\text{mL}\text{air}{\text{L}}^{-1}\text{liquid}{\text{min}}^{-1}$ resulting in a drop in methane content to 10%, the DO concentration in the bioreactor rose to about $0.8–1.0\text{mg}{\text{L}}^{-1}$ and the total nitrate removal dropped to about $10\text{mg}{\text{NO}}_3–\text{N}{\text{g}}^{-1}\text{VSS}{d}^{-1}$ with none of it being attributed to denitrification.

Studies undertaken at two aerated stabilization basins (ASBs) treating industrial effluents showed that the benthal solids characteristics varied substantially with location in three dimensions. The top 15–30 cm layer of the deposited solids was found to be the most active biodegradation zone with relatively little activity in the deeper layers. Ammonia and phosphate were present in high concentrations throughout the benthal solids and thus are not believed to limit biological growth and its associated benthal solids degradation kinetics. The nutrient concentrations were particularly higher in the downstream cells than those in the upstream cells. Implementing a suitable strategy to recycle these nutrients could result in minimized discharge and cost savings when treating nutrient-deficient industrial wastewaters. Dewatering properties of the benthal solids also substantially varied from one cell of an ASB to another. The selection and dose optimization of the dewatering polymers should therefore be completed separately for individual cells (or major zones) within an ASB system. Insights provided in this paper could be instrumental in proposing remedies to enhance in situ degradation of benthal solids and to better design and operate ASBs treating industrial effluents.

The objectives of this work were to identify differences between the composition, bulk properties, contaminant diffusivity and solubility for new high-density polyethylene (HDPE) pipe and crosslinked polyethylene (PEX) pipe, as well as determine which contaminant and polymer properties are useful for predicting contaminant fate in water pipe. Variations in PE pipe density $\left(0.9371–0.9547\text{g}/{\text{cm}}^3\right)$ , crystallinity (69–72%), crosslinking (60 and 76%), and oxidative induction time (33 to $>295\text{min}$ .) were detected. While numerically these differences seem minor, results show that slight material differences have a notable effect on contaminant diffusivity and solubility. Nonpolar contaminant diffusivity and solubility were best predicted by bulk density. Polar contaminants were more soluble and diffused faster through PEX than HDPE pipes because PEX pipes contained a greater amount of oxygen. For all materials, dipole moment and Log $K_{\text{ow}}$ were good predictors of contaminant fate and molecular volume was only useful for predicting diffusivity and solubility values for haloalkane and nonpolar aromatic contaminants.

Many water treatment technologies for arsenic removal that are used today produce arsenic-bearing residuals which are disposed in nonhazardous landfills. Previous works have established that many of these residuals will release arsenic to a much greater extent than predicted by standard regulatory leaching tests (e.g., the toxicity characteristic leaching procedure) and, consequently, require stabilization to ensure benign behavior after disposal. In this work, a four-step sequential extraction method was developed in an effort to determine the proportion of arsenic in various phases in untreated as well as stabilized iron-based solid matrices. The solids synthesized using various potential stabilization techniques included: amorphous arsenic-iron sludge (ASL), reduced ASL via reaction with zero valent iron (RASL), amorphous ferrous arsenate (PFA), a mixture of PFA and SL (M1), crystalline ferrous arsenate (HPFA), and a mixture of HPFA and SL (M2). The overall arsenic mobility of the tested samples increased in the following order: $\text{ASL}>\text{RASL}>\text{PFA}>\text{M}1>\text{HPFA}>\text{M}2$ .

An arsenic filtration experiment using iron oxide coated sand was modeled using the USGS geochemical program PHREEQC. Despite some uncertainty regarding the initial conditions of the groundwater and the simplicity of the model, it replicated the experimental results within 10%. The original experiment filtered 165 bed volumes to concentrations less than 0.01 mg/L As and approximately 210 bed volumes to 0.05 mg/L As. The model filtered 168 bed volumes to 0.01 mg/L As and 228 bed volumes to 0.05 mg/L.

Alternative measures of terrestrial pollutant loading were investigated to identify those that are better predictors of water quality in urban streams. Results from 18 watersheds with the same climatic conditions show that the density of terrestrial fecal-coliform loading is a better indicator of median instream concentrations than total terrestrial fecal-coliform loading. Watersheds with fecal-coliform loading densities less than around $2\times {10}^{11}\text{cfu}{\text{km}}^{-2}{\text{day}}^{-1}$ generally had median instream concentrations less than the reference water-quality standard of 400 cfu/100 mL. Median instream concentrations were also less than the reference water-quality standard for population densities less than around $400\text{persons}{\text{km}}^{-2}$ . For any given terrestrial loading intensity or population density, summer conditions of high rainfall and high temperature generally resulted in the greatest water-quality impacts. These results are particularly useful in determining terrestrial loading reductions in support of TMDLs, and in focusing best management practices.