INTRODUCTION: There is still interest in a unified methodology to quantify the mass of particulate material emitted into the atmosphere by activities inherent to open-pit mining. For the case of total suspended particles (TSP), the current practice is to estimate such emissions by developing inventories based on the emission factors recommended by the USEPA for this purpose. However, there are disputes over the specific emission factors that must be used for each activity and the applicability of such factors to cases quite different to the ones under which they were obtained. There is also a need for particulate matter with an aerodynamic diameter less than 10 μm (PM₁₀) emission inventories and for metrics to evaluate the emission control programs implemented by open-pit mines. STANDARDIZED EMISSION INVENTORY METHODOLOGY: To address these needs, work was carried out to establish a standardized TSP and PM₁₀ emission inventory methodology for open-pit mining areas. The proposed methodology was applied to seven of the eight mining companies operating in the northern part of Colombia, home to the one of the world’s largest open-pit coal mining operations (∼70 Mt/year). RESULTS: The results obtained show that transport on unpaved roads is the mining activity that generates most of the emissions and that the total emissions may be reduced up to 72% by spraying water on the unpaved roads. Performance metrics were defined for the emission control programs implemented by mining companies. It was found that coal open-pit mines are emitting 0.726 and 0.180 kg of TSP and PM₁₀, respectively, per ton of coal produced. It was also found that these mines are using on average 1.148 m² of land per ton of coal produced per year.

INTRODUCTION: An aerobic denitrifier was isolated from the Hua-Jia-Chi pond in China and identified as Pseudomonas mendocina 3-7 (Genbank No. HQ285879). This isolated strain could express periplasmic nitrate reductase which is essential for aerobic denitrification occurred when the dissolved oxygen (DO) level maintains at 3–10 mg L−1. METHODS: To determine whether the ability of isolated strain is exhibited in the bioremediation of polluted drinking source water, the heterotrophic nitrification and aerobic denitrification characteristics of P. mendocina 3-7 under different cultural conditions such as oxygen level, nitrate and organic concentrations were studied from the nitrogenous balance in the paper. RESULTS AND CONCLUSIONS: By measuring the nitrogen balance in all experiments under different culture conditions, the removal of total organic carbon and ammonium was positively correlated with total nitrogen removal, especially under high substrate level. With substrate concentration decreasing, ammonium and nitrate removal occurred separately, and ammonium was completely utilized first under low substrate concentration. Compared to that under high substrate level, the specific growth rate of P. mendocina 3-7 was not low under the low substrate level and the pollutant removal efficiencies remained high, which implies the stronger nitrogen removal and acclimatization capacities of the strain in oligotrophic niches.

PURPOSE: This study was aimed to the development of an integrated approach for the characterization of particulate matter (PM) pollution events in the South of Italy. METHODS: PM10 and PM2.5 daily samples were collected from June to November 2008 at an urban background site located in Bari (Puglia Region, South of Italy). Meteorological data, particle size distributions and atmospheric dispersion conditions were also monitored in order to provide information concerning the different features of PM sources. RESULTS: The collected data allowed suggesting four indicators to characterize different PM10 exceedances. PM2.5/PM10 ratio, natural radioactivity, aerosol maps and back-trajectory analysis and particle distributions were considered in order to evaluate the contribution of local anthropogenic sources and to determine the different origins of intrusive air mass coming from long-range transport, such as African dust outbreaks and aerosol particles from Central and Eastern Europe. The obtained results were confirmed by applying principal component analysis to the number particle concentration dataset and by the chemical characterization of the samples (PM10 and PM2.5). CONCLUSIONS: The integrated approach for PM study suggested in this paper can be useful to support the air quality managers for the development of cost-effective control strategies and the application of more suitable risk management approaches.

In order to use photocatalysis with solar light, finding more active and especially visible light active photocatalysts is a very important challenge. Also, studies of these photocatalysts should employ a standardized test procedure so that their results can be accurately compared and evaluated with one another. A systematic study of transition metal-modified zinc oxide was conducted to determine whether they are suitable as visible light photocatalysts. The photocatalytic activity of ZnO modified with eight different transition metals (Cu, Co, Fe, Mn, Ni, Ru, Ti, Zr) in three different concentrations (0.01, 0.1, and 1 at.%) was investigated under irradiation with UV as well as with visible light. The employed activity test is the gas-phase degradation of acetaldehyde as described by the ISO standard 22197-2. The results suggest that the UV activity can be improved with almost any modification element and that there exists an optimal modification ratio at about 0.1 at.%. Additionally, Mn- and Ru-modified ZnO display visible light activity. Especially the Ru-modified ZnO is highly active and surpasses the visible light activity of all studied titania standards. These findings suggest that modified zinc oxides may be a viable alternative to titanium dioxide-based catalysts for visible light photocatalysis. Eventually, possible underlying mechanisms are proposed and discussed.

INTRODUCTION: Transconjugant bacteria with combined potential for hydrocarbon utilization and heavy metal resistance were suggested by earlier investigators for bioremediation of soils co-contaminated with hydrocarbons and heavy metals. The purpose of this study was to offer evidence that such microorganisms are already part of the indigenous soil microflora. METHODS: Microorganisms in pristine and oily soils were counted on nutrient agar and a mineral medium with oil as a sole carbon source, in the absence and presence of either sodium arsenate (As V), sodium arsenite (As III) or cadmium sulfate, and characterized via 16S rRNA gene sequencing. The hydrocarbon-consumption potential of individual strains in the presence and absence of heavy metal salts was measured. RESULTS: Pristine and oil-contaminated soil samples harbored indigenous bacteria with the combined potential for hydrocarbon utilization and As and Cd resistance in numbers up to 4 × 105 CFU g−1. Unicellular bacteria were affiliated to the following species arranged in decreasing order of predominance: Bacillus subtilis, Corynebacterium pseudotuberculosis, Brevibacterium linens, Alcaligenes faecalis, Enterobacter aerogenes, and Chromobacterium orangum. Filamentous forms were affiliated to Nocardia corallina, Streptomyces flavovirens, Micromonospora chalcea, and Nocardia paraffinea. All these isolates could grow on a wide range of pure aliphatic and aromatic hydrocarbons, as sole sources of carbon and energy, and could consume oil and pure hydrocarbons in batch cultures. Low As concentrations, and to a lesser extent Cd concentrations, enhanced the hydrocarbon-consumption potential by the individual isolates. CONCLUSION: There is no need for molecularly designing microorganisms with the combined potential for hydrocarbon utilization and heavy metal resistance, because they are already a part of the indigenous soil microflora.

PURPOSE: In the assessment of health risks of environmental pollutants, the method of dose addition and the method of independent action are used to assess mixture effects when no synergistic and/or antagonistic effects are present. Currently, no method exists to quantify synergistic and/or antagonistic effects for mixtures. The purpose of this paper is to develop the theoretical concepts of an overall risk probability (ORP)-based method to quantify the synergistic and antagonistic effects in health risk assessment for mixtures. METHOD: The ORP for health effects of environmental chemicals was determined from the cumulative probabilities of exposure and effects. This method was used to calculate the ORP for independent mixtures and for mixtures with synergistic and antagonistic effects. RESULTS: For the independent mixtures, a mixture ORP can be calculated from the product of the ORPs of individual components. For systems of interacting mixtures, a synergistic coefficient and an antagonistic coefficient were defined respectively to quantify the ORPs of each individual component in the mixture. The component ORPs with synergistic and/or antagonistic effects were then used to calculate the total ORP for the mixture. CONCLUSIONS: An ORP-based method was developed to quantify synergistic and antagonistic effects in health risk assessment for mixtures. This represents a first method to generally quantify mixture effects of interacting toxicants.

INTRODUCTION: In this paper, a novel method in the estimation and prediction of PM10 is introduced using wavelet transform-based artificial neural networks (WT-ANN). DISCUSSION: First, the application of wavelet transform, selected for its temporal shift properties and multiresolution analysis characteristics enabling it to reduce disturbing perturbations in input training set data, is presented. Afterward, the circular statistical indices which are used in this method are formally introduced in order to investigate the relation between PM10 levels and circular meteorological variables. Then, the results of the simulation of PM10 based on WT-ANN by use of MATLAB software are discussed. The results of the above-mentioned simulation show an enhanced accuracy and speed in PM10 estimation/prediction and a high degree of robustness compared with traditional ANN models.

PURPOSE: To assess groundwater exposure to pesticides, in agricultural areas of ‘Ribatejo’ region (Portugal), and the influence of some key factors in that exposure, field, laboratory and modelling studies were carried out. METHODS: The study was performed in maize, potato, sugar beet, tomato and vegetables agricultural areas, located in a shallow aquifer, with pesticides use and, in most cases, with irrigation practices. Pesticides used in the studied agricultural areas and having leaching potential were selected, being considered also other pesticides included in priority lists, defined in Europe. Evaluation of groundwater exposure to pesticides was carried out by successively: (1) groundwater sampling in seven campaigns over the period 2004–2006; (2) pesticide analysis [including isolation and concentration from the groundwater samples and further determination by gas chromatography–mass spectrometry (GC–MS) of 14 herbicides, four insecticides and two metabolites]; and (3) analysis and discussion of the results by applying joint correspondence analysis (JCA). RESULTS: From the 20 pesticides and metabolites selected for the study, 11 were found in groundwater. Pesticides and metabolites most frequently detected were atrazine, alachlor, metolachlor, desethylatrazine, ethofumesate, α-endosulfan, metribuzine, lindane and β-endosulfan. The results showed that groundwater exposure to pesticides is influenced by local factors—either environmental or agricultural, as precipitation, soil, geology, crops and irrigation practices. Spring and autumn were more associated with the detection of pesticides being more likely to observe mixtures of these compounds in a groundwater sample in these transition seasons. CONCLUSIONS: This work evidences the importance of models, which evaluate pesticides environmental behaviour, namely their water contamination potential (as Mackay multicompartimental fugacity model) and, specially, groundwater contamination potential (as GUS and Bacci and Gaggi leaching indices), in pesticide selection. Moreover, it reveals the importance to adapt proper statistical methods according to level of left-censored data. Using JCA was still possible to establish relations between pesticides and their temporal trend in a case study where there were more than 80% of data censored. This study will contribute to the Tagus river basin management plan with information on the patterns of pesticide occurrence in the alluvial aquifer system.

PURPOSE: A multiple inputs and multiple outputs (MIMO) fuzzy-logic-based model was proposed to estimate color and chemical oxygen demand (COD) removal efficiencies in the post-treatment of anaerobically pretreated poultry manure wastewater effluent using Fenton's oxidation process. Three main input variables including initial pH, Fe+2, and H2O2 dosages were fuzzified in a new numerical modeling scheme by the use of an artificial intelligence-based approach. MATERIALS AND METHODS: Trapezoidal membership functions with eight levels were conducted for the fuzzy subsets, and a Mamdani-type fuzzy inference system was used to implement a total of 70 rules in the IF–THEN format. The product (prod) and the center of gravity (centroid) methods were applied as the inference operator and defuzzification methods, respectively. Fuzzy-logic predicted results were compared with the outputs of two first-order polynomial regression models derived in the scope of this study. Estimated results were also compared to the multiple regression approach by means of various descriptive statistical indicators, such as root mean-squared error, index of agreement, fractional variance, proportion of systematic error, etc. RESULTS AND DISCUSSION: Results of the statistical analysis clearly revealed that, compared to conventional regression models, the proposed MIMO fuzzy-logic model produced very smaller deviations and demonstrated a superior predictive performance on forecasting of color and COD removal efficiencies with satisfactory determination coefficients over 0.98. CONCLUSIONS: Due to high capability of the fuzzy-logic methodology in capturing the non-linear interactions, it was demonstrated that a complex dynamic system, such as Fenton's oxidation, could be easily modeled.