A comparative study on the uptake of polycyclic aromatic hydrocarbons by Anodonta californiensis

Uptake of polycyclic aromatic hydrocarbons (PAHs) by the freshwater bivalve mollusc Anodonta californiensis was examined in the presence and absence of surfactant in order to gain further insight into mixture toxicity and to predict whether certain mixtures have negative and/or positive effects on aquatic organisms. In the presence of surfactant, the uptake of anthracene or chrysene was higher than that of naphthalene, given the same concentration in the solution. In the absence of surfactant, the trend was similar, but the uptakes were increased by approximately 100% compared to those in the presence of surfactant. On the uptake of naphthalene, the presence of anthracene showed only minor influence. The uptake of anthracene was affected by both naphthalene and chrysene. The uptake of chrysene was influenced by neither naphthalene nor anthracene. There was no observable displacement of divalent cations from the surface of the gill membrane by any of the PAHs studied.     

Bioremediation of oil-contaminated soil using Candida catenulata and food waste

Even though petroleum-degrading microorganisms are widely distributed in soil and water, they may not be present in sufficient numbers to achieve contaminant remediation. In such cases, it may be useful to inoculate the polluted area with highly effective petroleum-degrading microbial strains to augment the exiting ones. In order to identify a microbial strain for bioaugmentation of oil-contaminated soil, we isolated a microbial strain with high emulsification and petroleum hydrocarbon degradation efficiency of diesel fuel in culture. The efficacy of the isolated microbial strain, identified as Candida catenulata CM1, was further evaluated during composting of a mixture containing 23% food waste and 77% diesel-contaminated soil including 2% (w/w) diesel. After 13 days of composting, 84% of the initial petroleum hydrocarbon was degraded in composting mixes containing a powdered form of CM1 (CM1-solid), compared with 48% of removal ratio in control reactor without inoculum. This finding suggests that CM1 is a viable microbial strain for bioremediation of oil-contaminated soil with food waste through composting processes.     

Impact of separating dairy cattle excretions on ammonia emissions

About 80% of dairy cattle N intake is excreted in urine and feces. Urinary-N is about 75% urea, whereas fecal-N is mostly organic. Urinary-N (urea) can only be volatilized when it is hydrolyzed to ammonia (NH3) in a process catalyzed by urease, which is predominantly found in feces. Minimizing contact between urine and feces may be an effective approach to reducing urea hydrolysis and subsequent NH3 emissions. Previous studies have reported 5 to 99% NH3 emissions mitigation within barns from separation of feces and urine. The objective ofthis study was to compare NH3 emissions mitigation via separation of urine and feces in postcollection storage to a conventional scrape manure handling method where urine and feces are comingled. Laboratory scale studies were conducted to evaluate NH3 emissions from simulated postcollection storag of three waste streams: (i) idealistically separated feces and urine (no contact between urine and feces), (ii) realistically separated urine and feces (limited contact of urine and feces), and (iii) conventionally scraped manure (control). From the results of these studies, NH3 losses ranking in descending order was as follows: aggregate of realistically separated waste streams (3375.9 +/- 54.8 mg), aggregate of idealistically separated urine and feces (3047.0 +/- 738.0 mg), and scrape manure (2034.0 +/- 106.5 mg), respectively. Therefore, on the basis of these results, the extra effort of separating the waste streams would not enhance mitigation of NH3 losses from postcollection storage of the separated waste streams compared to the conventional scrape manure collection system.     

3D QSAR studies of dioxins and dioxin-like compounds using CoMFA and CoMSIA

In the present study we have performed comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) on structurally diverse ligands of Ah (dioxin) receptor to explore the physico-chemical requirements for binding. All CoMFA and CoMSIA models have given q(2) value of more than 0.5 and r(2) value of more than 0.84. The predictive ability of the models was validated by an external test set, which gave satisfactory predictive r(2) values. Best predictions were obtained with CoMFA model of combined modified training set (q(2) = 0.631, r(2) = 0.900), giving predictive residual value = 0.02 log unit for the test compound. Addition of CoMSIA study has elucidated the role of hydrophobicity and hydrogen bonding along with the effect of steric and electrostatic properties revealed by CoMFA. We have suggested a model comprises of four structurally different compounds, which offers a good predictability for various ligands. Our QSAR model is consistent with all previously established QSAR models with less structurally diverse ligands.     

Using internet search behavior to assess public awareness of protected wetlands

Improving public awareness of protected wetlands facilitates sustainable wetland management, which depends on public participation. One way of gauging public interest is by tracking Internet search behavior (ISB). We assessed public awareness of issues related to protected wetland areas (PWAs) in South Korea by examining the frequencies of specific queries (PWAs, Ramsar, Upo wetland, Sunchon Bay, etc.) using relative search volumes (RSVs) obtained from an Internet search engine. RSV shows how many times a search term is used relative to a second search term during a specific period. Public awareness of PWAs changed from 2007 to 2013. Initially the majority of Internet searches were related to the most well‐known tidal and inland wetlands Sunchon Bay and Upo wetlands, which are the largest existing wetlands in Korea with the greatest historical exposure. Public awareness, as reflected in RSVs, of wetlands increased significantly following PWA designation for the wetlands in 2008, which followed the Ramsar 10th Conference of Contracting Parties to the Convention on Wetlands (COP10) meeting. Public interest was strongly correlated to the number of news articles in the popular media, as evidenced by the increase in Internet searches for specific wetlands and words associated with specific wetlands. Correspondingly, the number of visitors to specific wetlands increased. To increase public interest in wetlands, wetland aspects that enhance wetland conservation should be promoted by the government and enhanced via public education. Our approach can be used to gauge public awareness and participation in a wide range of conservation efforts.     

Decision-Tree-based data mining and rule induction for predicting and mapping soil bacterial diversity

Soilmicrobial ecology plays a significant role in global ecosystems. Nevertheless, methods of model prediction and mapping have yet to be established for soil microbial ecology. The present study was undertaken to develop an artificial-intelligence- and geographical information system (GIS)-integrated framework for predicting and mapping soil bacterial diversity using pre-existing environmental geospatial database information, and to further evaluate the applicability of soil bacterial diversity mapping for planning construction of eco-friendly roads. Using a stratified random sampling, soil bacterial diversity was measured in 196 soil samples in a forest area where construction of an eco-friendly road was planned. Model accuracy, coherence analyses, and tree analysis were systematically performed, and four-class discretized decision tree (DT) with ordinary pair-wise partitioning (OPP) was selected as the optimal model among tested five DT model variants. GIS-based simulations of the optimal DT model with varying weights assigned to soil ecological quality showed that the inclusion of soil ecology in environmental components, which are considered in environmental impact assessment, significantly affects the spatial distributions of overall environmental quality values as well as the determination of an environmentally optimized road route. This work suggests a guideline to use systematic accuracy, coherence, and tree analyses in selecting an optimal DT model from multiple candidate model variants, and demonstrates the applicability of the OPP-improved DT integrated with GIS in rule induction for mapping bacterial diversity. These findings also provide implication on the significance of soil microbial ecology in environmental impact assessment and eco-friendly construction planning.     

Geochemical occurrences of arsenic and fluoride in bedrock groundwater: a case study in Geumsan County,Korea

Bedrock groundwaters in Geumsan County, Korea, were surveyed to investigate the distribution and geochemical behaviors of arsenic and fluoride, mobilized through geogenic processes. The concentrations were enriched up to 113 μg/L for arsenic and 7.54 mg/L for fluoride, and 16% of 150 samples exceeded World Health Organization drinking water guidelines for each element. Simple Ca-HCO₃ groundwater types and positive correlations with pH, Ca, SO₄, and HCO₃ were characteristics of high (>10 μg/L) As groundwaters. The oxidation reaction of sulfide minerals in metasedimentary rocks and locally mineralized zones seems to be ultimately responsible for the existence of arsenic in groundwater. Desorption process under high pH conditions may also control the arsenic mobility in the study area. High (>1.5 mg/L) F groundwaters were found in the Na-HCO₃ type and with greater depth. Fluoride seemed to be enriched by deep groundwater interaction with granitic rocks, and continuous supply to shallow Ca-HCO₃-type groundwater kept the concentration high. In the study area, drinking water management should include periodic As and F monitoring in groundwater.

     

Estimate of zearalenone exposure through the intake of white and brown rice in the Korean population

Rice samples (n = 482) harvested for 2010–2012 in South Korea were analyzed for zearalenone content by high-performance liquid chromatography and fluorescence detection. The exposure of the Korean populations was assessed by a deterministic approach. Because the proportion of non-detectable results was >80% in white rice but less than <60% in brown rice, the zearalenone levels for white rice were reported as 0.52 µg kg^?1 as lower bound and 2.54 µg kg^?1 as upper bound, while for brown rice the middle bound value was 13.9 µg kg^?1. The average dietary intake of zearalenone from white and brown rice by the Korean population was estimated to be 1.5 ng kg^?1 body weight (bw) day^?1 each. For heavy consumers, the average intakes were 18.5 and 10.1 ng kg^?1 bw day^?1, respectively. The age groups with the highest zearalenone intake were 1–2-year-old children for white rice and 3–6-year-old children for brown rice. Overall, the dietary exposure of the Korean population to zearalenone from white and brown rice was found to be lower than the provisional maximum tolerable daily intake of 0.5 μg kg^?1 bw day^?1.