Statistical modeling of crystalline silica exposure by trade in the construction industry using a database compiled from the literature

A quantitative determinants-of-exposure analysis of respirable crystalline silica (RCS) levels in the construction industry was performed using a database compiled from an extensive literature review. Statistical models were developed to predict work-shift exposure levels by trade. Monte Carlo simulation was used to recreate exposures derived from summarized measurements which were combined with single measurements for analysis. Modeling was performed using Tobit models within a multimodel inference framework, with year, sampling duration, type of environment, project purpose, project type, sampling strategy and use of exposure controls as potential predictors. 1346 RCS measurements were included in the analysis, of which 318 were non-detects and 228 were simulated from summary statistics. The model containing all the variables explained 22% of total variability. Apart from trade, sampling duration, year and strategy were the most influential predictors of RCS levels. The use of exposure controls was associated with an average decrease of 19% in exposure levels compared to none, and increased concentrations were found for industrial, demolition and renovation projects. Predicted geometric means for year 1999 were the highest for drilling rig operators (0.238 mg m(-3)) and tunnel construction workers (0.224 mg m(-3)), while the estimated exceedance fraction of the ACGIH TLV by trade ranged from 47% to 91%. The predicted geometric means in this study indicated important overexposure compared to the TLV. However, the low proportion of variability explained by the models suggests that the construction trade is only a moderate predictor of work-shift exposure levels. The impact of the different tasks performed during a work shift should also be assessed to provide better management and control of RCS exposure levels on construction sites.     

Validation of evacuated canisters for sampling volatile organic compounds in healthcare settings

Healthcare settings present a challenging environment for assessing low-level concentrations of specific volatile organic compounds (VOCs) in the presence of high background concentrations of alcohol from the use of hand sanitizers and surface disinfectants. The purposes of this laboratory-based project were to develop and validate a sampling and analysis methodology for quantifying low-level VOC concentrations as well as high-level alcohol concentrations found together in healthcare settings. Sampling was conducted using evacuated canisters lined with fused silica. Gas chromatography/mass spectrometry analysis was performed using preconcentration (for ppb levels) and loop injection (for ppm levels). For a select list of 14 VOCs, bias, precision, and accuracy of both the preconcentration and loop injection methods were evaluated, as was analyte stability in evacuated canisters over 30 days. Using the preconcentration (ppb-level) method, all validation criteria were met for 13 of the 14 target analytes-ethanol, acetone, methylene chloride, hexane, chloroform, benzene, methyl methacrylate, toluene, ethylbenzene, m,p-xylene, o-xylene, alpha-pinene, and limonene. Using the loop injection (ppm-level) method, all validation criteria were met for each analyte. At ppm levels, alpha-pinene and limonene remained stable over 21 days, while the rest of the analytes were stable for 30 days. All analytes remained stable over 30 days at ppb levels. This sampling and analysis approach is a viable (i.e., accurate and stable) methodology that will enable development of VOC profiles for mixed exposures experienced by healthcare workers.     

The Impacts of Different Meteorology Data Sets on Nitrogen Fate and Transport in the SWAT Watershed Model

In this study, we investigated how different meteorology data sets impacts nitrogen fate and transport responses in the Soil and Water Assessment Tool (SWAT) model. We used two meteorology data sets: National Climatic Data Center (observed) and Mesoscale Model 5/Weather Research and Forecasting (simulated). The SWAT model was applied to two 10-digit hydrologic unit code watersheds in the Coastal Plain and Piedmont zones of North Carolina. Nitrogen cycling and loading response to these meteorological data were investigated by exploring 19 SWAT nitrogen outputs relating to landscape delivery, biogeochemical assimilation, and atmospheric deposition. The largest difference in model output using both meteorology data sets was for large loads/fluxes. Landscape delivery outputs (e.g., NO^? ₃ watershed discharge, groundwater NO^? ₃ flux, soil NO^? ₃ percolation) showed the largest difference across all values. Use of the two weather data sources resulted in a nearly twofold difference in NO^? ₃ watershed discharge and groundwater NO^? ₃ flux. Differences for many nitrogen outputs were greater than those for sub-basin flow. Nitrogen outputs showed the greatest difference for agricultural land covers and there was no flow-related pattern in output differences across sub-basins or over time (years). In general, nitrogen parameter models that had a greater number of nitrate concentration, flow, and temperature terms (equation variables) in each transport model showed the greatest difference between both meteorology applications.     

A Multiple Criteria Decision Analysis Model Based on ELECTRE TRI-C for Erosion Risk Assessment in Agricultural Areas

This paper deals with a real-world decision-aiding problem for zoning the risk of erosion, total suspended solids emissions, and ecological consequences of their transfers towards the streams. One of these consequences is the decrease of fishes into the streams in agricultural watersheds, because of the clogging of spawning areas. Given the multiple criteria nature of the problem, the originality of our research is to adapt a new decision-aiding sorting method, ELECTRE TRI-C, for identifying risk zones in rural areas, where measures must be taken. The developed model was applied in a small watershed (Low Normandy, France) where the objective was to assess the most appropriate intervention for protecting the reproduction habitat of the salmonid fishes. Agricultural parcels were evaluated on multiple criteria for grouping them into four risk categories, which are related to risk levels as well as priorities on the improvement works. The decision-aiding sorting model is co-constructed, within a constructive approach, through an interaction process between decision-aiding analysts, environmental experts, and local actors for improving transparency and communication on the results. This model is linked with a geographical information system (GIS) for assessing a set of criteria and the visualization of the farming parcels along with their type of intervention they should be submitted to best practices. The assignment results were validated by the environmental experts. These results have a strong impact on the agricultural practices of the farmers into the watersheds. The model proposed in this paper can be considered as a useful decision aid tool in any regions for implementing public agricultural and environmental policies for protecting the ecological areas.     

Potential Impact of Clean Air Act Regulations on Nitrogen Fate and Transport in the Neuse River Basin: a Modeling Investigation Using CMAQ and SWAT

There has been extensive analysis of Clean Air Act Amendment (CAAA) regulation impacts to changes in atmospheric nitrogen deposition; however, few studies have focused on watershed nitrogen transfer particularly regarding long-term predictions. In this study, we investigated impacts of CAAA NOx emissions on the fate and transport of nitrogen for two watersheds in the Neuse River Basin. We applied the Soil and Water Assessment Tool (SWAT) using simulated deposition rates from the Community Multiscale Air Quality (CMAQ) model. Two scenarios were investigated: one that considered CAAA emission controls in CMAQ simulation (with) and a second that did not (without). By 2020, results showed a 70 % drop in nitrogen discharge for the Little River watershed and a 50 % drop for the Nahunta watershed from 1990 levels under the with-CAAA scenario. Denitrification and plant nitrogen uptake played important roles in nitrogen discharge from each watershed. Nitrogen watershed response time to a change in atmospheric nitrogen deposition was 4 years for Nahunta and 2 years for Little River. We attribute these differences in nitrogen response time to contrasts in agricultural land use and diversity of crop types. Soybean, hay, and corn land covers had comparatively longer response times to changes in atmospheric deposition. The studied watersheds demonstrate relatively large nitrogen retention: ≥80 % of all delivered nitrogen.     

Long-term seasonal changes of the Danube River eco-chemical status in the region of Serbia

Seasonal spatial and temporal changes of selected eco-chemical parameters in section of the Danube River flowing through Serbia were analyzed. Data for electrical conductivity (EC), dry and suspended matter, residue on ignition, chemical oxygen demand (COD), biochemical oxygen demand (BOD-5), ultraviolet extinction, dissolved oxygen (DO), oxygen saturation, pH, nitrates, total phosphorus, and nitrogen were collected between 1992 and 2006. The use of monthly medians combined with linear regression and two-sided t test has been proven to be the best approach for resolving trends from natural variability of investigated parameters and for determining trend significance. Patterns of temporal changes between different months were examined. It was also determined that spatial trends of some parameters oscillate in predictable manner, increasing in one part of the year and declining in the other. Regression slope coefficients, an excellent indicator for determining when the water quality is changing the most along the course of the Danube, reach their maximum during summer for temperature (t), electric conductivity, nitrates, and total N, while in the same season suspended matter, COD, BOD-5, DO, and oxygen saturation coefficients reach their minimum. Correlations for used data sets of selected parameters were analyzed for better understanding of their behavior and mutual relations. It was observed that as Danube flows through Serbia, its general eco-chemical status either stagnates or improves, but the rate of river self-purification often depends on the season of the year.     

Fish scales as indicators of wastewater toxicity from an international water channel Tung Dhab drain

The effect of wastewater exposure on scales and chromatophores of freshwater fish Channa punctatus was studied using wastewater dilutions (60–100%) from an international water channel Tung Dhab drain at an interval of 15 and 30 days. The exposed fish showed significant alterations such as uprooted and damaged lepidonts and dispersal of chromatophores. These observations strongly suggest that fish scales can be successfully employed as indicators of wastewater pollution.     

Groundwater contamination evolution in the Guadiamar and Agrio aquifers after the Aznalcóllar spill: assessment and environmental implications

In 1998, the Agrio and Guadiamar rivers underwent an enormous environmental disaster caused by the rupture of the Aznalcóllar tailings dam and the release of 6 hm³ of pyrite sludge and acidic water. Both rivers run over recent alluvial materials which form a small-sized aquifer which is however important because underground water feeds the flow of the rivers. This work analyzes the state of groundwater 10 years after the spill. Before the dam failure, this aquifer was already contaminated in the zone nearest to the mine, to which the impact of the spill was added. Contamination levels in the alluvial aquifer of the Agrio River have decreased remarkably. However, they are still important, with acidic pH values and high concentrations of toxic elements (maximum values of 16 mg/L of Zn and 15 mg/L of Al). There are also important levels of contamination in the Guadiamar alluvial area closest to the mine, as well as in specific zones located further south. The concentration of toxic elements is mainly controlled by pH. The evolution of contaminant levels show a sharp decrease after the first years following the spill, followed by a subsequent stabilization. It is necessary to take measures for the recovery of the aquifer because, otherwise, groundwater will continue contributing contaminants into the Agrio and Guadiamar rivers.     

Development of geomorphologic instantaneous unit hydrograph for a large watershed

Hill torrents cause a lot of environmental and property damage in Pakistan every year. Proper assessment of direct runoff in the form of hill torrents is essential for protection of environment, property, and human life. In this paper, direct surface runoff hydrograph (DSRH) was derived for a large catchment using the geomorphologic instantaneous unit hydrograph concept. The catchment with hill torrent flows in semi-arid region of Pakistan was selected for this study. It was divided into series of linear cascades and hydrologic parameters required for Nash's conceptual model, and were estimated using geomorphology of the basin. Geomorphologic parameters were derived from satellite images of the basin and ERDAS and ArcGIS were used for data processing. Computer program was developed to systematically estimate the dynamic velocity, its related parameters by optimization and thereby to simulate the DSRH. The data regarding rainfall-runoff and satellite images were collected from Punjab Irrigation and Power Department, Pakistan. Model calibration and validation was made for 15 rainfall-runoff events. Ten events were used for calibration and five for validation. Model efficiency was found to be more than 90% and root mean square error to be about 5%. Impact of variation in model parameters (shape parameter and storage coefficient) on DSRH was investigated. For shape parameter, the number of linear cascades varied from 1 to 3 and it was found that the shaper parameter value of 3 produced the best DSRH. Various values of storage coefficient were used and it was observed that the value determined from geomorphology and the dynamic velocity produced the best results.     

A survey on the utility of the USEPA CADDIS stressor identification procedure

The Environmental Protection Agency (EPA) has made available on the worldwide web a systematic stream stressor identification procedure, the “Causal Analysis/Diagnosis Decision Information System” or CADDIS. We report here the results of a survey of regulators and scientists in 11 states who use CADDIS or another stressor identification procedure in their work. The 13 survey questions address guidelines as to what impairment scenarios to approach with stressor identification, what information is needed to perform stressor identification, and what the stakeholder role is in performing stressor identification. At the time of this survey (the summer of 2009), the EPA CADDIS website was less commonly used among the state regulators surveyed than the published EPA stressor identification document on which it is based. The respondents generally find the EPA stressor identification procedure useful and capable of being adapted to their individual needs. Survey respondents all use stressor identification in their Total Maximum Daily Load work, but also in a wide variety of other applications. All the “types of evidence” included in the CADDIS stressor identification procedure are used by the practitioners surveyed with the exception of the results of ecological simulation models. While the CADDIS documentation encourages the involvement of stakeholders in stressor identification, most respondents do not assemble stakeholder teams of local officials and citizens to participate in stressor analyses.