The influence of metal source uncertainty on cost-effective allocation of mine water pollution abatement in catchments

In mine water pollution abatement, it is commonly assumed that known mine waste sites are the major pollution sources, thus neglecting the possibility of significant contribution from other old and diffuse sources within a catchment. We investigate the influence of different types of pollution source uncertainty on cost-effective allocation of abatement measures for mine water pollution. A catchment-scale cost-minimization model is developed and applied to the catchment of the river Dalälven, Sweden, in order to exemplify important effects of such source uncertainty. Results indicate that, if the pollution distribution between point and diffuse sources is partly unknown, downstream abatement measures, such as constructed wetlands, at given compliance boundaries are often cost-effective. If downstream abatement measures are not practically feasible, the pollution source distribution between point and diffuse mine water sources is critical for cost-effective solutions to abatement measure allocation in catchments. In contrast, cost-effective solutions are relatively insensitive to uncertainty in total pollutant discharge from mine water sources.     

A retrospective comparison of model-based forecasted PM2.5 concentrations with measurements

This study presents an assessment of the performance of the Community Multiscale Air Quality (CMAQ) photochemical model in forecasting daily PM2.5 (particulate matter < or = 2.5 microm in aerodynamic diameter) mass concentrations over most of the eastern United States for a 2-yr period from June 14, 2006 to June 13, 2008. Model predictions were compared with filter-based and continuous measurements of PM2.5 mass and species on a seasonal and regional basis. Results indicate an underprediction of PM2.5 mass in spring and summer, resulting from under-predictions in sulfate and total carbon concentrations. During winter, the model overpredicted mass concentrations, mostly at the urban sites in the northeastern United States because of overpredictions in unspeciated PM2.5 (suggesting possible overestimation of primary emissions) and sulfate. A comparison of observed and predicted diurnal profiles of PM2.5 mass at five sites in the domain showed significant discrepancies. Sulfate diurnal profiles agreed in shape across three sites in the southern portion of the domain but differed at two sites in the northern portion of the domain. Predicted organic carbon (OC) profiles were similar in shape to mass, suggesting that discrepancies in mass profiles probably resulted from the underprediction in OC. The diurnal profiles at a highly urbanized site in New York City suggested that the overpredictions at that site might be resulting from overpredictions during the morning and evening hours, displayed as sharp peaks in predicted profiles. An examination of the predicted planetary boundary layer (PBL) heights also showed possible issues in the modeling of PBL.     

Impact of dry deposition of semi-volatile organic compounds on secondary organic aerosols

Dry deposition of semi-volatile organic compounds (SVOC) is not currently treated in most chemical transport models of air quality and this omission has been identified as a possible major source of uncertainty. The effect of dry deposition of SVOC on the concentration of secondary organic aerosols (SOA) is investigated in summertime with the chemical transport model CHIMERE that simulates SOA concentrations by means of molecular SOA surrogate species. Omitting dry deposition could overestimate SOA concentrations by as much as 50%. This overestimation is larger during nighttime due to higher relative humidity.     

Assessing computer waste generation in Chile using material flow analysis

The quantities of e-waste are expected to increase sharply in Chile. The purpose of this paper is to provide a quantitative data basis on generated e-waste quantities. A material flow analysis was carried out assessing the generation of e-waste from computer equipment (desktop and laptop PCs as well as CRT and LCD-monitors). Import and sales data were collected from the Chilean Customs database as well as from publications by the International Data Corporation. A survey was conducted to determine consumers’ choices with respect to storage, re-use and disposal of computer equipment. The generation of e-waste was assessed in a baseline as well as upper and lower scenarios until 2020.The results for the baseline scenario show that about 10,000 and 20,000 tons of computer waste may be generated in the years 2010 and 2020, respectively. The cumulative e-waste generation will be four to five times higher in the upcoming decade (2010–2019) than during the current decade (2000–2009). By 2020, the shares of LCD-monitors and laptops will increase more rapidly replacing other e-waste including the CRT-monitors. The model also shows the principal flows of computer equipment from production and sale to recycling and disposal. The re-use of computer equipment plays an important role in Chile. An appropriate recycling scheme will have to be introduced to provide adequate solutions for the growing rate of e-waste generation.     

Investigation into the effect of high concentrations of volatile fatty acids in anaerobic digestion on methanogenic communities

A study was conducted to determine whether differences in the levels of volatile fatty acids (VFAs) in anaerobic digester plants could result in variations in the indigenous methanogenic communities. Two digesters (one operated under mesophilic conditions, the other under thermophilic conditions) were monitored, and sampled at points where VFA levels were high, as well as when VFA levels were low. Physical and chemical parameters were measured, and the methanogenic diversity was screened using the phylogenetic microarray ANAEROCHIP. In addition, real-time PCR was used to quantify the presence of the different methanogenic genera in the sludge samples. Array results indicated that the archaeal communities in the different reactors were stable, and that changes in the VFA levels of the anaerobic digesters did not greatly alter the dominating methanogenic organisms. In contrast, the two digesters were found to harbour different dominating methanogenic communities, which appeared to remain stable over time. Real-time PCR results were inline with those of microarray analysis indicating only minimal changes in methanogen numbers during periods of high VFAs, however, revealed a greater diversity in methanogens than found with the array.     

Current Status of Air Quality Models for Particulate Matter

ABSTRACT

The current status of the mathematical modeling of atmospheric particulate matter (PM) is reviewed in this paper. Simulating PM requires treating various processes, including the formation of condensable species, the gas/ particle partitioning of condensable compounds, and in some cases, the evolution of the particle size distribution. The algorithms available to simulate these processes are reviewed and discussed. Eleven 3-dimensional (3-D) Eulerian air quality models for PM are reviewed in terms of their formulation and past applications. Results of past performance evaluations of 3-D Eulerian PM models are presented. Currently, 24-hr average PM_2.5 concentrations appear to be predicted within 50% for urban-scale domains. However, there are compensating errors among individual particulate species. The lowest errors tend to be associated with SO₄ ^2-, while NO₃ ^-, black carbon (BC), and organic carbon (OC) typically show larger errors due to uncertainties in emissions inventories and the prediction of the secondary OC fraction. Further improvements and performance evaluations are recommended.     

Demonstrating Attainment of the Air Quality Standards: Integration of Observations and Model Predictions into the Probabilistic Framework

ABSTRACT

This paper introduces an integrated observational-modeling approach to transform the deterministic nature of attainment demonstrations of the National Ambient Air Quality Standard (NAAQS) into the probabilistic framework. While the methods presented here can be used to address any air quality standard that is based on extreme values, this paper focuses on the application to the 1-hr and 8-hr NAAQS for ozone. Extreme value statistics and resampling techniques are applied to estimate the probability of exceeding the NAAQS for both 1-hr and 8-hr ozone concentrations. Within the integrated observation-modeling analysis approach, we show that the model-to-model differences in the predicted responses to emission reductions are smaller than the model-to-model differences in predicted absolute ozone concentrations. We illustrate that the emission reductions stemming from a real-world emission control strategy would substantially reduce the probability of exceeding the NAAQS over a large portion of the eastern United States, especially for the 8-hr average ozone concentrations.     

Phospholipid fatty acid biomarkers in a freshwater periphyton community exposed to uranium: discovery by non-linear statistical learning

Phospholipid fatty acids (PLFA) have been widely used to characterize environmental microbial communities, generating community profiles that can distinguish phylogenetic or functional groups within the community. The poor specificity of organism groups with fatty acid biomarkers in the classic PLFA-microorganism associations is a confounding factor in many of the statistical classification/clustering approaches traditionally used to interpret PLFA profiles. In this paper we demonstrate that non-linear statistical learning methods, such as a support vector machine (SVM), can more accurately find patterns related to uranyl nitrate exposure in a freshwater periphyton community than linear methods, such as partial least squares discriminant analysis. In addition, probabilistic models of exposure can be derived from the identified lipid biomarkers to demonstrate the potential model-based approach that could be used in remediation. The SVM probability model separates dose groups at accuracies of ∼87.0%, ∼71.4%, ∼87.5%, and 100% for the four groups; Control (non-amended system), low dose (amended at 10 μg U L⁻¹), medium dose (amended at 100 μg U L⁻¹), and high dose (500 μg U L⁻¹). The SVM model achieved an overall cross-validated classification accuracy of ∼87% in contrast to ∼59% for the best linear classifier.     

Distribution of antidepressants and their metabolites in brook trout exposed to municipal wastewaters before and after ozone treatment--evidence of biological effects

This study examined the tissues distribution of selected serotonin reuptake inhibitors (SSRIs) in brook trout exposed for 3 months to continuous flow-through primary-treated effluent before and after ozone treatment. A reliable analytical method was developed for the quantification of trace amounts of antidepressants in small tissue homogenate extracts. Levels of six antidepressants and four of their N-desmethyl metabolites were determined using liquid chromatography-tandem mass spectrometry. Significant amounts of the SSRIs were found in fish tissue-in decreasing order: liver>brain>muscle. Sertraline and its metabolite desmethylsertraline were the predominant substances observed in most tissues (0.04-10.3 ng g(-1)). However, less SSRIs (0.08-1.17 ng g(-1)) were bioaccumulated in the ozonated effluent. The early molecular effects of these SSRIs on the Na/K-dependent ATPase pump activity in brain synaptosomes where also investigated in vitro and in fish exposed to the municipal effluents. With respect to their potential biological effects, in vitro exposure to selected SSRIs induced a reduction of the brain Na/K-ATPase activity in synaptosomes in a dose-dependent manner. Results showed that Na/K-ATPase activity was readily inhibited by exposure to municipal effluent before and, to a lesser extent, after ozone treatment. Moreover, the Na/K-ATPase activity was significantly and negatively correlated with brain tissue concentrations of fluoxetine (r=-0.57; p<0.03), desmethylsertraline (r=-0.84; p<0.001), and sertraline (r=-0.82; p<0.001). The present study reveals that SSRIs are readily available in fish, biologically active and corroborates previous findings on the serotonergic properties of municipal effluents to aquatic organisms.     

Quantification of nitrate leaching from German forest ecosystems by use of a process oriented biogeochemical model

Simulations with the process oriented Forest-DNDC model showed reasonable to good agreement with observations of soil water contents of different soil layers, annual amounts of seepage water and approximated rates of nitrate leaching at 79 sites across Germany. Following site evaluation, Forest-DNDC was coupled to a GIS to assess nitrate leaching from German forest ecosystems for the year 2000. At national scale leaching rates varied in a range of 0–>80 kg NO₃–N ha⁻¹ yr⁻¹ (mean 5.5 kg NO₃–N ha⁻¹ yr⁻¹). A comparison of regional simulations with the results of a nitrate inventory study for Bavaria showed that measured and simulated percentages for different nitrate leaching classes (0–5 kg N ha⁻¹ yr⁻¹:66% vs. 74%, 5–15 kg N ha⁻¹ yr⁻¹:20% vs. 20%, >15 kg N ha⁻¹ yr⁻¹:14% vs. 6%) were in good agreement. Mean nitrate concentrations in seepage water ranged between 0 and 23 mg NO₃–N l⁻¹.