Geochemistry of Iron and Sulfur in the Zone of Microbial Sulfate Reduction in Mine Tailings

The cycling of iron and sulfur in mine tailings depends on various chemical and microbial reactions. The present study was undertaken in order to assess the role played by populations of sulfate-reducing bacteria (SRB) on the fate of Fe and SO₄ ^2- in Cu–Zn and Au tailings. Samples were taken along a 50-cm deep profile at all sites and analyzed for SRB populations, solid-phase mineralogy and porewater geochemistry. Results indicated that the Cu–Zn tailings were highly oxidized near the surface, as shown by the very low pH, high redox potential, large concentrations of soluble Cu, Zn and sulfate in the porewaters, and the depletion of pyrite. On the other hand, Au tailings were more pH neutral, slightly anoxic, and showed low concentrations of Fe and SO₄ ^2- in the porewaters and very little pyrite oxidation. SRB populations in the Cu–Zn tailings increased with depth, just below the oxic/anoxic interface and were linked to a decline of sulfate and DOC concentrations around the same depths. However, large concentrations of dissolved Fe were also observed around the same depth intervals. Our results suggest that SRB could be involved in sulfate reduction in the Cu–Zn tailings, because the solubility of sulfate was not controlled by the precipitation of sulfate-rich minerals. However, the presence of soluble Fe in the reduced portion of the tailings was also indicative of the presence of iron reducing bacteria (IRB). These bacteria were not enumerated in the present study, but their co-occurrence with SRB has been reported in the past in similar mining environments. The decline of sulfate and the release of soluble iron into the porewaters were also paralleled by a pH increase and the generation of alkalinity. In the Au tailings, SRB populations were generally constant throughout the depth profile and could not be ascribed to sulfate reduction in the porewaters. The solubilities of sulfate and iron in these tailings were partially controlled by jarosite and Fe-oxide minerals. It is then clear that SRB populations could be recovered from various mining sites, but their activity cannot be ascertained based on microbial enumeration and geochemical data.     

Vegetation dynamics in impounded marshes along the Indian River Lagoon,Florida, USA

Data are presented on the vegetation dynamics of two impounded marshes along the Indian River Lagoon, in east-central Florida, USA. Vegetation in one of the marshes (IRC 12) was totally eliminated by overflooding and by hypersaline conditions (salinities over 100 ppt) that developed there in 1979 after the culvert connecting the marsh with the lagoon was closed. Over 20% recovery of the herbaceous halophytesSalicornia virginica, S. bigelovii, andBatis maritima was observed at that site after the culvert was reopened in 1982, but total cover in the marsh remains well below the original 75%. No recovery of mangroves was observed at this site. The second site (SLC 24), while remaining isolated from the lagoon during much of the study, did not suffer the complete elimination of vegetation experienced at the first site. At this location, mangroves increased in cover and frequency with a concomitant decrease in herbaceous halophytes. Considerable damage to the vegetation was evident at IRC 12 when the impoundment was closed and flooded for mosquito control in 1986. Although the damage was temporary, its occurrence emphasizes the need of planning and constant monitoring and adjustment of management details as conditions within particular marshes change. Storms and hurricanes may be important in promoting a replacement of black mangroves by red mangroves in closed impoundments because the former cannot tolerate pneumatophore submergence for long periods of time. University of Florida-IFAS Journal Series R-00521.     

PREDICTION OF PEAK FLOWS ON SMALL WATERSHEDS IN OREGON FOR USE IN CULVERT DESIGN1

ABSTRACT: Using data from 80 Oregon watersheds that ranged in size from 0.54 km² to 27.45 km², equations were developed to predict peak flows for use in culvert design on forest roads. Oregon was divided into six physiographic regions based on previous studies of flood frequency. In each region, data on annual peak flow from gaging stations with more than 20 years of record were analyzed using four flood frequency distributions: type 1 extremal, two parameter-log normal, three parameter-log normal, and log-Pearson type III. The log-Pearson type III distribution was found to be suitable for use in all regions of the State, based on the chi-square goodness-of-fit-test. Flood magnitudes having recurrence intervals of 10, 25, 50, and 100 years were related to physical and climatic characteristics of drainage basins by multiple regression. Drainage basin size was the most important variable in explaining the variation of flood peaks in all regions. Mean basin elevation and mean annual precipitation were also significantly related to flood peaks in two regions of western Oregon. The standard error of the estimate for the regression relationships ranged from 26 to 84 percent.     

Water quality prediction of copper-molybdenum mining-beneficiation wastewater based on the PSO-SVR model

● Data acquisition and pre-processing for wastewater treatment were summarized. ● A PSO-SVR model for predicting COD_eff in wastewater was proposed. ● The COD_eff prediction performances of the three models in the paper were compared. ● The COD_eff prediction effects of different models in other studies were discussed. The mining-beneficiation wastewater treatment is highly complex and nonlinear. Various factors like influent quality, flow rate, pH and chemical dose, tend to restrict the effluent effectiveness of mining-beneficiation wastewater treatment. Chemical oxygen demand (COD) is a crucial indicator to measure the quality of mining-beneficiation wastewater. Predicting COD concentration accurately of mining-beneficiation wastewater after treatment is essential for achieving stable and compliant discharge. This reduces environmental risk and significantly improves the discharge quality of wastewater. This paper presents a novel AI algorithm PSO-SVR, to predict water quality. Hyperparameter optimization of our proposed model PSO-SVR, uses particle swarm optimization to improve support vector regression for COD prediction. The generalization capacity tested on out-of-distribution (OOD) data for our PSO-SVR model is strong, with the following performance metrics of root means square error (RMSE) is 1.51, mean absolute error (MAE) is 1.26, and the coefficient of determination (R²) is 0.85. We compare the performance of PSO-SVR model with back propagation neural network (BPNN) and radial basis function neural network (RBFNN) and shows it edges over in terms of the performance metrics of RMSE, MAE and R², and is the best model for COD prediction of mining-beneficiation wastewater. This is because of the less overfitting tendency of PSO-SVR compared with neural network architectures. Our proposed PSO-SVR model is optimum for the prediction of COD in copper-molybdenum mining-beneficiation wastewater treatment. In addition, PSO-SVR can be used to predict COD on a wide variety of wastewater through the process of transfer learning.     

Transport and biodegradation of creosote compounds in clayey till, a field experiment

The transport and biodegradation of 12 organic compounds (toluene, phenol, o-cresol, 2,6-, 3,5-dimethylphenol, naphthalene, 1-methylnaphthalene, benzothiophene, dibenzofuran, indole, acridine, and quinoline) were studied at a field site located on the island of Funen, Denmark, where a clayey till 10–15 m deep overlies a sandy aquifer. The upper 4.8 m of till is highly fractured and the upper 2.5 m contains numerous root and worm holes. A 1.5–2 m thick sand lens is encountered within the till at a depth of 4.8 m. Sampling points were installed at depths of 2.5 m, 4 m, and in the sand lens (5.5 m) to monitor the downward migration of a chloride tracer and the organic compounds. Water containing organic compounds and chloride was infiltrated into a 4 m×4.8 m basin at a rate of 8.8 m³ day⁻¹ for 7 days. The mass of naphthalene relative to chloride was 0.39–0.98 for the sampling points located at a depth of 2.5 m, 0.11–0.61 for the sampling points located at a depth of 4 m, and 0–0.02 for the sampling points located in the sand lens. A similar pattern was observed for eight organic compounds for which reliable results were obtained (toluene, phenol, o-cresol, 2,6-, 3,5-dimethylphenol, 1-methylnaphthalene, benzothiophene, and quinoline). This shows that the organic compounds were attenuated during the downward migration through the till despite the high infiltration rate. The attenuation process may be attributed to biodegradation.     

Evidential role of municipal solid waste and liquid effluent on environment and public health

Cities in Bangladesh produce large amounts of solid waste (SW) through various human activities which severely pollutes our native environment. As a result, SW pollutes the three basic environmental elements (air, water, and soil) by increasing pathogenic microbial load, which might be hazardous to public health directly or indirectly. In this study, we conducted 30 samples (i.e., soil, water, and air) collected from areas where municipal solid wastes are dumped (Tangail Sadar Upazila, Bangladesh). All the samples were analyzed to assess bacteriological quality for presumptive viable and coliform count using different agar media. We performed serial dilution 10⁻³–10⁻¹⁰ times for soil and water samples, and the diluted samples were spread on Mac-Conkey agar and nutrient agar plates. For the air sample, the sterile media containing petri-dish was placed adjacent to the dumpsite of the municipal waste and kept for an hour. Then all the samples were incubated at 37°C overnight for total viable count (TVC) and total coliform count (TCC). Biochemical tests and PCR were performed for the identification of these microorganisms. The antibiogram study was performed to reveal their (identified bacteria) susceptibility against clinically used antibiotics according to the standard disk diffusion technique. The highest bacterial loads were found in the air: TVC 3.273 × 10³ and TCC 1.059 × 10³ CFU/plate; tube-well water: TVC 8.609 × 10³, and TCC 8.317 × 10³ CFU/mL; in surface water: TVC 6.24 × 10¹³ CFU/mL and TCC 2.2 × 10¹² CFU/mL; in soil: TVC 2.88 × 10¹¹ and TCC 1.02 × 10¹¹ CFU/g, respectively. Microbes from SW can be transmitted through air, dust particles, or flies, and here we found an average of 1120 microbes spread over 63.61 cm² area per hour. Eight bacterial isolates (Pseudomonas spp., Klebsiella spp., E. coli, Proteus spp., V. cholera, Salmonella spp., Shigella spp., and Vibrio spp.) were identified by the biochemical test. Among them, E. coli and Shigella spp. were further ensured by PCR targeting bfpA and ipaH genes. Antibiotic susceptibility test results showed that E. coli isolates were highly resistant to erythromycin (80%); Shigella spp. were resistant to nalidixic acid (90%), whereas Salmonella spp. was found resistant to kanamycin (90%). Vibrio spp. were also resistant to azithromycin (80%) and erythromycin (80%), which should be a great concern for us. A semi-structured survey revealed that 63% of respondents suffered from different clinical conditions (intestinal diseases) due to SW pollution. So, steps should be taken to improve the proper management and disposal of solid waste and liquid effluent to save our environment and public health.     

Variability and predictability of sea-level extremes in the Hawaiian and U.S.-Trust Islands—a knowledge base for coastal hazards management

The objective of this study is to provide an improved climatology of sea level extremes on seasonal and long-term time scales for Hawaii and the U.S-Trust islands. Observations revealed that the Hawaiian and U.S.-Trust islands, by and large, display a strong annual cycle. For estimating the statistics of return period, the three-parameter generalized extreme value (GEV) distribution is fitted using the method of L-moments. In the context of extremes (20- to 100-year return periods), the deviations in most of the Hawaiian Islands (except at Nawiliwili and Hilo) displayed a moderate sea-level rise (i.e., close to 200 mm), but the deviations in the U.S.-Trust islands displayed a considerably higher rise (i.e., more than 300 mm) in some seasons due to typhoon-related storm surges. This rise may cause damage to roads, harbors, and unstable sandy beaches. Correlations between the El Niño-Southern Oscillation (ENSO) climate cycle and the variability of seasonal sea level have been investigated. Results show that correlation for the station located west of the International Date Line (DL) is strong, but it is moderate or even weaker for stations east of the DL. The skill of SST-based Canonical Correlation Analyses (CCA) forecasts was found to be weak to moderate (0.4–0.6 for Honolulu, Kahului, Hilo, and Wake, and 0.3 or below for Kahului, Mokuoloe, and Johnston). Finally, these findings are synthesized for evaluating the potential implications of sea level variability in these islands.     

Direct and indirect effects of climate and habitat factors on butterfly diversity

Many factors, including climate, resource availability, and habitat diversity, have been proposed as determinants of global diversity, but the links among them have rarely been studied. Using structural equation modeling (SEM), we investigated direct and indirect effects of climate variables, host-plant richness, and habitat diversity on butterfly species richness across Britain, at 20-km grid resolution. These factors were all important determinants of butterfly diversity, but their relative contributions differed between habitat generalists and specialists, and whether the effects were direct or indirect. Climate variables had strong effects on habitat generalists, whereas host-plant richness and habitat diversity contributed relatively more for habitat specialists. Considering total effects (direct and indirect together), climate variables had the strongest link to butterfly species richness for all groups of species. The results suggest that different mechanistic hypotheses to explain species richness may be more appropriate for habitat generalists and specialists, with generalists hypothesized to show direct physiological limitations and specialists additionally being constrained by trophic interactions (climate affecting host-plant richness).