QUALITY STUDY OF GRAYWATER TREATMENT SYSTEMS1

ABSTRACT: A residential single family dwelling was retrofitted to recycle graywater for landscape irrigation and toilet flushing. The objective of this study was to determine improvements in graywater quality by evaluating five simple graywater treatment systems that were easily adapted to the household plumbing. The treatment systems consisted of (1) water hyacinths and sand filtration, (2) water hyacinths, copper ion disinfection, and sand filtration, (3) copper ion disinfection and sand filtration, (4) copper/silver ion disinfection and sand filtration, and (5) 20–μm cartridge filtration. Water quality parameters measured were fecal and total coliform indicator bacteria, nitrates, suspended solids, and turbidity. Reductions in bacterial concentration, suspended solids and turbidity were achieved by all systems tested. Treatment reduced nitrate concentrations to an average of 2.6 mg/liter. Reductions in suspended solids, and turbidity were influenced more by the quality of the graywater entering the treatment system than the efficiency of the systems themselves. The water hyacinths and sand filtration system provided the best graywater quality in terms of the concentrations of fecal indicator bacteria. The system providing the best water quality in regard to average suspended solids after treatment was the water hyacinths, copper ion, and sand filtration system, and the best average turbidity was achieved by the copper/silver ion generating unit with sand filtration. All systems were capable of significant reductions in fecal indicator bacteria, suspended solids, and turbidity; however, additional treatment or disinfection would be necessary to further reduce the level of coliform and fecal coliform bacteria to achieve regulatory standards in the State of Arizona.     

GROUND WATER SOLUTE TRANSPORT,OPTIMAL REMEDIATION PLANNING,AND DECISION MAKING UNDER UNCERTAINTY1

ABSTRACT: A groundwater quality modeling advisory system has been developed for the U.S. Air Force for use in investigating remediation alternatives for the cleanup of subsurface contamination. The system is capable of accounting for uncertainty, not only in the prediction of solute transport but also in the optimization of the remediation scheme through chance constraints. The system guides users in the selection of appropriate transport models through an algorithm independently tested with machine learning codes. An application to Hill Air Force Base, Utah, is presented for which different pump-and-treat strategies are considered: the results are evaluated in terms of the cumulative distribution of the contaminant concentration for each case and the tradeoff relationship between the cost of remediation and the probability that the remediation strategy exceeds an established maximum allowable contaminant concentration.     

ESTIMATING IRRIGATION WATER USE THROUGH SELECTIVE MONITORING: A NORTH FLORIDA CASE STUDY1

ABSTRACT: Selective placement - under a rigorous statistical sampling design - of newly available monitoring equipment on irrigation systems may provide effective and economical estimates of total irrigation water use in areas where complete water use inventories are impractical. In 1979, a joint effort by the U.S. Geological Survey and Florida's Suwannee River Water Management District was launched to estimate the District's 1979 irrigation water use using a selective monitoring approach. Analysis of previous inventories of irrigation equipment and amounts of water applied in the District indicated that total 1979 water use estimates with six to nine percent sampling error could be obtained using selective monitoring, given the time and equipment limitations for the monitoring program. Restricting monitoring to a sample of farms can introduce systematic error to water use estimates if farmers' participation is related to their water use methods. Preliminary results of the 1979 study indicate tht declining participation rates, if unchecked, could lead to serious systematic eror in future North Florida selective monitoring studies.     

Mixed-model statistical analysis of fuel, equipment, mileage, and driving schedule effects on particulate matter emissions from heavy diesel-powered vehicles

An extensive experimental program has been conducted to evaluate the comparative effects of California Air Resources Board diesel fuel and an ultra-low-sulfur (S) diesel (with and without aftermarket passive filtering devices) on mass emissions of particulate matter (PM) in heavy vehicles. Tests have been performed on 20 Class 8 trucks at two high-mileage levels using two different driving schedules. The design of the test program facilitates the use of mixed-model statistical analysis, which allows more appropriate treatment of the explanatory variables than normally achieved. The analysis suggests that the ultra-low-S diesel fuel yields extremely low mean PM emissions when used in conjunction with a particulate filter, even at high mileage, but that the estimates are highly variable. The high degree of uncertainty, caused at least in part by large vehicle-to-vehicle variation, may obscure the true PM response and adversely impact attainment of increasingly more stringent diesel PM emissions standards in the United States.     

Estimated hourly personal exposures to ambient and nonambient particulate matter among sensitive populations in Seattle, Washington

Epidemiological studies of particulate matter (PM) routinely use concentrations measured with stationary outdoor monitors as surrogates for personal exposure. Despite the frequently reported poor correlations between ambient concentrations and total personal exposure, the epidemiologic associations between ambient concentrations and health effects depend on the correlation between ambient concentrations and personal exposure to ambient-generated PM. This paper separates personal PM exposure into ambient and nonambient components and estimates the outdoor contribution to personal PM exposures with continuous light scattering data collected from 38 subjects in Seattle, WA. Across all subjects, the average exposure encountered indoors at home was lower than in all other microenvironments. Cooking and being at school were associated with elevated levels of exposure. Previously published estimates of particle infiltration (Finf) were combined with time-location data to estimate an ambient contribution fraction (alpha, mean = 0.66+/-0.21) for each subject. The mean alpha was significantly lower for subjects monitored during the heating season (0.55+/-0.16) than for those monitored during the nonheating season (0.80+/-0.17). Our modeled alpha estimates agreed well with those estimated with the sulfur-tracer method (slope = 1.08; R2 = 0.67). We modeled exposure to ambient and nonambient PM with both continuous light scattering and 24-hr gravimetric data and found good agreement between the two methods. On average, ambient particles accounted for 48% of total personal exposure (range = 21-80%). The personal activity exposure was highly influenced by time spent away from monitored microenvironments. The median hourly longitudinal correlation between central site concentrations and personal exposures was 0.30. Although both alpha and the nonambient sources influence the personal-central relationship, the latter seems to dominate. Thus, total personal exposure may be poorly predicted by stationary outdoor monitors, particularly among persons whose PM exposure is dominated by nonambient exposures, for example, those living in tightly sealed homes, those who cook, and children.     

Real-world vehicle emissions: a summary of the 14th coordinating research council on-road Vehicle Emissions Workshop

The Coordinating Research Council held its 14th Vehicle Emissions Workshop in March 2004, where results of the most recent on-road vehicle emissions research were presented. We summarize ongoing work from researchers who are engaged in improving our understanding of the contribution of mobile sources to ambient air quality and emission inventories. Participants in the workshop discussed efforts to improve mobile source emission models, light- and heavy-duty vehicle emissions measurements, on- and off-road emissions measurements, effects of fuels and lubricating oils on emissions, as well as topics for future research.     

Survey of waste comminglers' VOC exposures

Twelve U.S. universities performing hazardous waste solvent commingling operations were surveyed for waste handler exposures to 45 U.S. Environmental Protection Agency (EPA)-designated volatile organic compounds (VOCs). Personal exposures (n = 33) and area concentrations (n = 30) were determined using gas chromatography/ mass spectrometry (GC/MS) analysis of passively collected samples. Air monitoring data were used to determine the veracity of laboratory-generated reports of waste container contents. Participants completed a questionnaire concerning the use of personal protective equipment, ventilation, and other appropriate safety equipment for their specific commingling operation. Follow-up telephone interviews were conducted to elucidate safeguards in place. Results showed that personal exposures exceeded area concentrations in 70% of operations. For the contaminant concentrations reported, 17% of personal samples exceeded Occupational Safety & Health Administration (OSHA) time-weighted average or ceiling limit values. Methylene chloride was a frequently seen airborne contaminant not listed on drum inventory sheets. When airborne constituents were compared with container content tags, 44% of the chemicals detected in air were omitted from the waste tags. This study concluded that the most frequently necessary safeguard is respiratory protection, preferably a supplied-air-type. The use of local exhaust ventilation systems rather than dilution or natural systems and facility operation in a totally explosion-safe manner are also recommended.