During SO₂ removal from flue gas by coal slurry scrubbing, coal pyrite sulfur can be simultaneously reduced. But satisfactory coal pyrite conversion cannot be achieved under normal scrubbing conditions. In the present work, aluminum oxide and aluminum sulfate were tested as additives to enhance the leaching of coal pyrite during SO₂ removal in a bubbling reactor. It was found that adding aluminum oxide or aluminum sulfate into the coal slurry could increase the coal pyrite conversion and SO₂ removal efficiency. The leaching process could be described by the reaction-controlled shrinking core model. Based on the facts that both aluminum and ferric irons can exist in aqueous solution in the form of sulfate and hydroxide complex ions, it was deduced that the attraction between the oppositely charged ions might promote the coal pyrite leaching reactions, suppress the formation of passive Fe solid products, and increase the concentration of soluble complexed Fe(III) which also acted as coal pyrite oxidant.

The increasing use of herbicides in sugarcane production has increased environmental concern regarding the fate of these compounds, especially when they are used in mixtures. Among the various processes that determine the behavior of molecules in the environment, leaching stands out. In this context, the aim of this study was to evaluate the leaching of a mixture of hexazinone, sulfometuron-methyl, and diuron in soils with contrasting textures. A completely randomized experimental design containing three replications in a 2 × 6 factorial arrangement was used, with two soils (alfisol–Paleudult, sandy clay texture and ultisol–typic Hapludalf, sandy loam texture) and six depths (0–0.05, 0.05–0.10, 0.10–0.15, 0.15–0.20, 0.20–0.25, and 0.25–0.30 m). Three glass columns of 50 cm were used for each soil. The dose used was 391.0 + 33.35 + 1386.9 g a.i. ha⁻¹ of hexazinone, sulfometuron-methyl and diuron, respectively. After applying the mixture to the top of each column, rainfall simulation with 200 mm of 0.01 mol L⁻¹ CaCl₂ solution was applied for 48 h. The leachates were collected at 6, 12, 24, 36, and 48 h. The chromatographic determinations of the herbicides were performed by high-performance liquid chromatography (HPLC) with a UV-Vis detector. For hexazinone, the highest percentage recovery in the soil with a sandy clay texture occurred at a depth of 0.10–0.15 m, with 40 % recovered, while in the soil with a sandy loam texture, the most part was recovered at a depth of 0.25–0.30 m. Diuron demonstrated little mobility in the soil and was detected in most cases only in the surface layer (up to 0.10 m) in both soils. Sulfometuron-methyl, in soil with a sandy clay texture, was detected to a depth of 0.15–0.20 m with the highest concentration found at a depth of 0–0.05 m, while in sandy loam soil, a higher concentration was found at a depth of 0.10–0.15 m; this herbicide was detected down to 0.25–0.30 m. These results show that the soil texture directly influences the leaching of hexazinone, sulfometuron-methyl, and diuron.

The objective of this study was to examine the effect of band gap of photocatalyst on the decolorization of dye new coccine (NC). The concentration of NC in the present of CuO, Fe₂O₃, TiO₂, and ZnO reduced to 50.5, 23.3, 0.1, and 0 mg L⁻¹, respectively, after 5 h solar light irradiation. The concentration of NC in dark condition only decreased to 48.140, 45.079, 35.269, and 31.045 mg L⁻¹ with CuO, Fe₂O₃, TiO₂, and ZnO as photocatalysts, respectively, after 5 h contact time. The absorbance peaks and chemical oxygen demand (COD) concentration of NC in the presence of TiO₂ and ZnO decreased to baseline and zero compared to the CuO and Fe₂O₃. The COD concentration of NC with CuO, Fe₂O₃, TiO₂, and ZnO as photocatalysts reduced to 21, 13, 0, and 0 mg L⁻¹, respectively, after 12 h of solar irradiation. The surface morphology of photocatalysts was examined by scanning electron microscope (SEM), and it was found that the particle size of CuO, Fe₂O₃, TiO₂, and ZnO ranging 250–375, 250–600, 40–100, and 60–500 nm, respectively. In summary, the higher band gap energy level indicated greater photocatalytic degradation and mineralization of NC.

Improved understanding of the relationships between heavy metals fractionation in agricultural soils and biological uptake could be obtained by analysing samples of biota in parallel with sequential extraction of their grown media. The overall goals of this study were to identify the characteristics of metal fractions and their bioavailability to maize and potato plants in the agricultural land of the Ibar River in southern Serbia and northern Kosovo. The concentrations of Pb, Zn, Cd, Ni, Cr and Cu in soil and vegetable samples were determined by the ICP-OES method. Pb/Zn production and industrial waste disposal significantly increased the pseudo-total concentrations of heavy metals in the soil together with their mobile and potentially bioavailable amounts. The Pb concentrations in the vegetable samples were generally above the EU maximum permitted concentrations in foodstuffs. However, the concentrations of Zn, Ni, Cr and Cu in the vegetables were below the critical levels. The results of the present study indicated that the intensive industrial production of Pb/Zn over the years and permanent pollution were responsible for the environmental contamination by heavy metals in the study area, particularly by Pb and Zn. The quantity of the mobile and potentially bioavailable heavy metals in the studied soils threatens the quality of Zea mays L. and Solanum tuberosum L. crops, with a real risk that these elements could enter the food chain.

The primary goal of this research was to evaluate the effect of a ternary mixture of toluene, methanol, and trichloroethylene (TCE) on the elimination of TCE in a biotrickling filter. Two biotrickling filters—Biofilter I and Biofilter II—were run in parallel, each with a different toluene/methanol/TCE loading ratio of 3:2.7:1 and 1.9:0.9:1, respectively. Both systems were seeded with fungal strains grown on diatomaceous earth media and were run at pH 4 maintained by formate buffer. To control excess biomass growth, the systems were “starved” for 2 days a week and run continuously for the rest of the week. TCE loading rates for each system ranged from 1.61 to 6.44 g/m³ h⁻¹ across three phases while toluene and methanol were loaded at rates corresponding to the influent composition ratios. More than 95 % methanol was removed from the gaseous streams throughout, while TCE removal was a function of the influent organic ratio and the corresponding concentrations. At and above loading rates of 3.22 g/m³ h⁻¹, elimination capacities obtained from Biofilter II surpassed those from Biofilter I due to a lower feed of bio-accessible carbon (toluene and methanol) offering reduced competition to TCE removal. While over 90 % toluene was removed from both systems, its elimination capacities dropped as the phases progressed due to competition and TCE cytotoxicity. Most carbon was converted to CO₂ and biomass, and no TCE oxidation by-products were detected.

Poderosa Mine is an abandoned pyrite mine, located in the Iberian Pyrite Belt which pours its acid mine drainage (AMD) waters into the Odiel river (South-West Spain). This work focuses on establishing possible reasons for interdependence between the potential redox and pH, with the load of metals and sulfates, as well as a set of variables that define the physical chemistry of the water—conductivity, temperature, TDS, and dissolved oxygen—transported by a channel from Poderosa mine affected by acid mine drainage, through the use of techniques of artificial intelligence: fuzzy logic and data mining. The sampling campaign was carried out in May of 2012. There were a total of 16 sites, the first inside the tunnel and the last at the mouth of the river Odiel, with a distance of approximately 10 m between each pair of measuring stations. While the tools of classical statistics, which are widely used in this context, prove useful for defining proximity ratios between variables based on Pearson’s correlations, in addition to making it easier to handle large volumes of data and producing easier-to-understand graphs, the use of fuzzy logic tools and data mining results in better definition of the variations produced by external stimuli on the set of variables. This tool is adaptable and can be extrapolated to any system polluted by acid mine drainage using simple, intuitive reasoning.

This study aimed to assess the micronuclei formation in Tradescantia pallida var. purpurea through active and passive biomonitoring of air genotoxicity and its relation with abiotic environmental factors, and to analyze the concentrations of trace elements in flower buds and leaves, in order to determine the importance of these parameters to atmospheric quality monitoring. For 2 years, active biomonitoring was conducted with exposure of cuttings with flower buds at three sites in the metropolitan area of Porto Alegre in southern Brazil, and indoor (negative control). For passive biomonitoring, flower buds were collected from beds at the same sites. Meteorological and vehicular traffic data were recorded during the exposures. The micronuclei (MCN) frequencies obtained by active and passive biomonitoring for Canoas, Esteio, and São Leopoldo (respectively means of 5.44, 5.34, 4.17 and of 3.01, 2.47, 2.72) were significantly higher than those of the negative control. Furthermore, the sensitivity of the flower buds used for active biomonitoring was greater compared to those used for the passive biomonitoring, which was evidenced by significantly higher MCN frequencies. The multivariate analysis indicated two main components responsible for 74.58 % of the variances observed, and pointed to a strong relation between micronuclei frequency from active biomonitoring and vehicular traffic. Temperature and relative air humidity did not relate with the formation of micronuclei in both biomonitoring systems. Flower buds proved to be efficient bioaccumulators of trace elements, as they accumulated concentrations of up to three times more than the leaves.

Given the 24-h turn-around time before swimming advisories are released, advisories issued to protect public health really only indicates ‘it may be unsafe to swim yesterday’. Predictive modelling for Escherichia coli concentrations at inflow-impacted beaches may be a favourable alternative to the current, routinely criticised monitoring approach. Using a total of 482 sets of meteorological and bacteriological data covering 14 swimming seasons, as well as environmental data of 10 inflow streams, this study developed models that could be used for predicting E. coli concentrations at five Lake Rotorua beaches. The models include predictor variables such as wind speed, antecedent rainfall, suspended solids at Puarenga, Utuhina and Ngongotaha stream inflows and particulate inorganic phosphorus concentration at Puarenga stream inflow. The combined 2011–2012 models had an average-adjusted R ² of 0.73, root mean square error (RMSE) of 0.33 logCFU/100 mL and captured 38 % of the variance in the validation data when used to predict E. coli concentrations for an additional 2 years (2013–2014). Among the individual beach models, predictive accuracy ranged from 88.89 to 92.31 % for the three beaches considered in the study. The developed models can provide a faster estimation of E. coli condition, potentially assisting local beach managers in the decision process related to swimming advisories issuance.

China is experiencing serious acid rain contamination, with Beijing among the worst-hit areas. To understand the chemical feature and the origin of inorganic ions in precipitation of Beijing, 128 precipitation samples were collected and analyzed for major water-soluble ions and δ³⁴S. The pH values ranged from 3.68 to 7.81 and showed a volume weighted average value (VWA) of 5.02, with a frequency of acid rain of 26.8 %. The VWA value of electrical conductivity (EC) was 68.6 μS/cm, which was nearly 4 times higher than the background value of northern China. Ca²⁺ represented the main cation; SO₄²⁻ and NO₃⁻ were the dominant anion in precipitation. Our study showed that SO₄²⁻ and NO₃⁻ originated from coal and fossil fuel combustion; Ca²⁺, Mg²⁺, and K⁺ were from the continental sources. The δ³⁴S value of SO₄²⁻ in precipitation ranged from +2.1 to +12.8‰ with an average value of +4.7‰. The δ³⁴S value showed a winter maximum and a summer minimum tendency, which was mainly associated with temperature-dependent isotope equilibrium fractionation as well as combustion of coal with relatively positive δ³⁴S values in winter. Moreover, the δ³⁴S values revealed that atmospheric sulfur in Beijing are mainly correlated to coal burning and traffic emission; coal combustion constituted a significant fraction of the SO₄²⁻ in winter precipitation.