ARSENIC CONSUMPTION AND HEALTH RISK PERCEPTIONS IN A RURAL WESTERN U.S. AREA1

ABSTRACT: Churchill County, Nevada, has approximately 23,000 residents, among whom an estimated 13,500 relied on private wells for water supply in 2002. This study examined exposure to arsenic in water supplies among residents with private domestic wells and factors related to householder choice to consume tap water. It compared opinions and concerns about water quality with consumption habits and observed concentrations from tap water samples. The results from 351 households indicated that a majority (75 percent) of respondents consumed tap water and that a minority (38 percent) applied treatment. Approximately 66 percent of those who consumed tap water were exposed to concentrations of arsenic that exceeded 10 ppb. Water consumption was related to application of treatment. Among 98 respondents who were not at all concerned about the health effects of aqueous arsenic, 59 (60 percent) reported consuming tap water with concentrations of arsenic exceeding 10 ppb. Conversely, among 86 respondents who were highly concerned about arsenic, 33 (37 percent) consumed tap water with concentrations of arsenic exceeding 10 ppb. Results from a national sampling effort showed that 620 of 5,304 private wells sampled (11.7 percent) had arsenic concentrations above 10 ppb. The paradox of awareness of arsenic in water supplies coupled with consumption of aqueous arsenic in concentrations greater than 10 ppb may be common in other parts of the nation. Enhanced educational efforts, especially related to tap water sampling and explanations of efficacy of available treatment, may be useful means of reducing exposure through private water supplies.     

COMPARISON OF STOCHASTIC AND DETERMINISTIC DYNAMIC PROGRAMMING FOR RESERVOIR OPERATING RULE GENERATION1

ABSTRACT: Two dynamic programming models — one deterministic and one stochastic — that may be used to generate reservoir operating rules are compared. The deterministic model (DPR) consists of an algorithm that cycles through three components: a dynamic program, a regression analysis, and a simulation. In this model, the correlation between the general operating rules, defined by the regression analysis and evaluated in the simulation, and the optimal deterministic operation defined by the dynamic program is increased through an iterative process. The stochastic dynamic program (SDP) describes streamflows with a discrete lag-one Markov process. To test the usefulness of both models in generating reservoir operating rules, real-time reservoir operation simulation models are constructed for three hydrologically different sites. The rules generated by DPR and SDP are then applied in the operation simulation model and their performance is evaluated. For the test cases, the DPR generated rules are more effective in the operation of medium to very large reservoirs and the SDP generated rules are more effective for the operation of small reservoirs.     

Estimates of animal methane emissions

The enteric methane emissions into the atmospheric annually from domestic animals total about 77 Tg. Another 10 to 14 Tg are likely released from animal manure disposal systems. About 95% of global animal enteric methane is from ruminants, a consequence of their large populations, body size and appetites combined with the extensive degree of anaerobic microbial fermentation occurring in their gut. Accurate methane estimates are particularly sensitive to cattle and buffalo census numbers and estimated diet consumption. Since consumption is largely unknown and must be predicted, accuracy is limited often by the information required, i.e., distribution of animals by class, weight and productivity. Fraction of the diet lost as enteric methane mostly falls into the range of 5.5–6.5% of gross energy intake for the world's cattle, sheep and goats. Manure methane emissions are heavily influenced by fraction of disposal by anaerobic lagoon. Non-ruminants, i.e., swine, become major contributors to these emissions.     

Risk perception by offshore workers on UK oil and gas platforms

This paper reports the first investigation of risk perception by workers on offshore oil and gas installations on the UK Continental Shelf, following changes in offshore safety legislation in the wake of the Piper Alpha disaster in 1988. The Offshore Safety Case regulations (Health and Safety Executive, 1992, A Guide to the Offshore Installations (Safety Case) Regulations) put the onus on the operator to identify the major hazards and to reduce the risks to As Low As is Reasonably Practicable (ALARP). The regulations specifically state that Quantitative Risk Assessments (QRA) must be used when preparing the Safety Case. However, people do not use QRA when making everyday judgements about risk; they make subjective judgements known as risk perceptions, which are influenced by a number of different factors. This study was designed to complement the extensive QRA calculations that have already been carried out in the development of Safety Cases. The aim was to measure subjective risk perception in offshore personnel and examine how this relates to the more objective risk data available, namely accident records and QRA calculations. This paper describes the Offshore Risk Perception Questionnaire developed to collect the data and reports on UK offshore workers' perceptions of the risks associated with major and minor hazards, work tasks and other activities aboard production platforms.     

profiling areas of ground water contamination by pesticides in california: phase ii – evaluation and modification of a statistical model

A well sampling study was conducted to evaluate anempirical approach to classifying areasof land in California as vulnerable to ground watercontamination by pesticides (Troiano et al., 1994). Wells were sampled from sections of land that had noprevious detections of pesticideresidues. The sections had been classified into vulnerablesoil clusters or into a not-classified groupusing a procedure based on Principal Components Analysis(PCA). Grape, citrus, and olive growingareas of Fresno and Tulare Counties were targeted, areas wherepre-emergence herbicide residues hadbeen detected in well water. Overall, herbicide residues weredetected in 75 of 176 sampled wells, ahigh frequency of detection in relation to results fromprevious targeted well sampling studies. Sinceresidues were also detected in the not-classified group, theclassification procedure was modified usingan approach based on Canonical Variates Analysis (CVA). Moresections were classified intovulnerable soil clusters with the CVA approach than with thePCA method. Data from two otherexplanatory variables, depth to ground water and amount ofpesticide used per section, were includedto illustrate how additional information can be incorporatedinto this approach of identifying vulnerable areas.     

a study of the temporal variability of atrazine in private well water. part ii: analysis of data

In 1988, the Iowa Department of Natural Resources, along withthe University of Iowa, conducted the Statewide Rural WellWater Survey, commonly known as SWRL. A total of 686private rural drinking water wells was selected by use of aprobability sample and tested for pesticides and nitrate. A subsetof these wells, the 10% repeat wells, were additionally sampledin October, 1990 and June, 1991. Starting in November, 1991,the University of Iowa, with sponsorship from the United StatesEnvironmental Protection Agency, revisited the 10% repeat wellsto begin a study of the temporal variability of atrazine and nitratein wells. Other wells, which had originally tested positive foratrazine in SWRL but were not in the 10% population, wereadded to the study population. Temporal sampling for a year-long period began in February of 1992 and concluded in Januaryof 1993. All wells were sampled monthly, a subset was sampledweekly, and a second subset was sampled for 14 day consecutiveperiods. Of the 67 wells in the 10% population tested monthly,7 (10.4%) tested positive for atrazine at least once during theyear, and 3 (4%) were positive each of the 12 months. Theaverage concentration in the 7 wells was 0.10 µg/L. Fornitrate, 15 (22%) wells in the 10% repeat population monthlysampling were above the Maximum Contaminant Level of 10 mg/L at least once. This paper, the second of two papers on thisstudy, describes the analysis of data from the survey. The firstpaper (Lorber et al., 1997) reviews the study design, theanalytical methodologies, and development of the data base.     

Use of cluster and principal component analyses to profile areas in California where ground water has been contaminated by pesticides

An empirical approach to profiling areas of ground water contamination by pesticides was devised that did not rely upon determining the level of vulnerability between land areas and that did not assume any particular pathway for ground water contamination. Climatic and soil data were obtained for 1-square mile sections of land in California where pesticide residues had been found in well water samples and the detection was attributed to legal agricultural applications. These sections were designated as known contaminated (KC) sections. Climate and soil data were also obtained for sections which lacked either well sampling data or a positive pesticide detection. These sections were designated as candidate sections. Statistical procedures were used to cluster groups of KC sections first with respect to climate characteristics and then with respect to soil characteristics. Principal components analysis (PCA) was used to construct a statistical profile of soil variables for each cluster of KC sections. A method based on the PCA was developed to compare the similarity of soil profiles derived for each KC section cluster to individual candidate sections. Since the profiling scheme was based only on data from KC sections, candidate sections that did not match any KC cluster profile could only be considered dissimilar to contaminated sections, receiving a status of not-classified. This profiling method is flexible and it can be revised to incorporate updated well sampling information.