Chemical and spectroscopic characterization of organic matter during the anaerobic digestion and successive composting of pig slurry

In this work, anaerobic digestion of pig slurry and successive composting of the digestate after centrifugation were studied by means of chemical analysis, FTIR and fluorescence spectroscopy as excitation–emission matrix (EEM). Chemical analysis highlighted the organic matter transformation occurring during the processes. A decrease of volatile solids and total organic carbon were observed in the digestate with respect to the fresh pig slurry as a consequence of the consumption of sugars, proteins, amino acids and fatty acids used by microorganisms as a C source. Water Extractable Organic Matter (WEOM) was obtained for all samples and fractionated into a hydrophilic and a hydrophobic fraction. The highest WEOM value was found in the pig slurry indicating a high content of labile organic C. The digestate centrifuged and the digestate composted showed lower hydrophilic and higher hydrophobic contents because of the decrease of labile C. Total phenolic content was lower in the digestate with respect to fresh pig slurry sample (36.7%) as a consequence of phenolic compounds degradation. The strong decrease of total reducing sugars in the digestate (76.6%) as compared to pig slurry confirmed that anaerobic process proceed mainly through consumption of sugars which represent a readily available energy source for microbial activity. FTIR spectra of pig slurry showed bands indicative of proteins and carbohydrates. A drop of aliphatic structures and a decrease of polysaccharides was observed after the anaerobic process along with the increase of the peak in the aromatic region. The composted substrate showed an increase of aromatic and a relative decrease of polysaccharides. EEM spectra provided tryptophan:fulvic-like fluorescence ratios which increased from fresh substrate to digestate because of the OM decompostion. Composted substrate presented the lowest ratio due to the humification process.     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

文思湖底泥COD释放规律模拟研究

采用室内模拟实验方法,研究环境因子（温度、pH、扰动强度、供气量）对底泥释放COD的影响。结果表明,水温升高能加速底泥中有机质的释放;上覆水在弱酸至中性条件下底泥释放有机质最低;扰动上覆水体会加快有机质的释放。     

Linking Climate Trends to Population Dynamics in the Baltic Ringed Seal: Impacts of Historical and Future Winter Temperatures

A global trend of a warming climate may seriously affect species dependent on sea ice. We investigated the impact of climate on the Baltic ringed seals (Phoca hispida botnica), using historical and future climatological time series. Availability of suitable breeding ice is known to affect pup survival. We used detailed information on how winter temperatures affect the extent of breeding ice and a climatological model (RCA3) to project the expected effects on the Baltic ringed seal population. The population comprises of three sub-populations, and our simulations suggest that all of them will experience severely hampered growth rates during the coming 90 years. The projected 30 730 seals at the end of the twenty-first century constitutes only 16 % of the historical population size, and thus reduced ice cover alone will severely limit their growth rate. This adds burden to a species already haunted by other anthropogenic impacts.     

Genotoxicity of sediment extracts of the Berre lagoon (France)

To evaluate the genotoxic risk that contaminated sediment could constitute for benthic organisms, three contaminated (VA, VC and VN) and one uncontaminated (RN) sediment samples were collected in the Berre lagoon (France). Potentially bioavailable contaminants in sediments were obtained using sediment extraction with synthetic seawater adjusted to pH 4 or pH 6, simulating the range of pH prevailing in the digestive tract of benthic organisms. The genotoxic activities of these extracts were evaluated by three short-term bioassays: the Salmonella mutagenicity test using the Salmonella typhimurium strain TA102, the alkaline comet assay and the micronucleus assay on the Chinese Hamster Ovary cells CHO-K1. Results of the Salmonella mutagenicity assay detected a mutagenic response for RN extract at pH 6, and for VA extract at pH 4. Results of the comet and micronucleus assays detected low genotoxic/clastogenic activities for VA and VC extracts at pH 6 and higher activities for RN, VA and VC extracts at pH 4. To identify if metals (Al, Fe, Mn, As, Cd, Co, Cr, Cu, Hg, Ni, Pb and Zn) were involved in these genotoxic activities, their concentrations were determined in the extracts, and their speciation was assessed by thermodynamic calculations. Results showed that extracts from sites VA, VC and VN generally presented the highest trace metal contents for both extractants, while the site RN presented lower trace metal contents but the highest Fe and Mn contents. Thermodynamic calculations indicated that Fe, Mn, As and in a lower extend Co, Ni and Zn were mainly present under free forms in extracts, and were consequently, more likely able to induce a genotoxic effect. Results globally showed no correspondence between free metal contents and genotoxic activities. They suggested that these positive results could be due to uncharacterized compounds, acting as direct genotoxic agents or enhancing the genotoxic properties of analyzed metals.     

The structure of the fire fighting foam surfactant Forafac®1157 and its biological and photolytic transformation products

For several decades, perfluorooctane sulfonate (PFOS) has widely been used as a fluorinated surfactant in aqueous film forming foams used as hydrocarbon fuel fire extinguishers. Due to concerns regarding its environmental persistence and toxicological effects, PFOS has recently been replaced by novel fluorinated surfactants such as Forafac®1157, developed by the DuPont company. The major component of Forafac®1157 is a 6:2 fluorotelomer sulfonamide alkylbetaine (6:2 FTAB), and a link between the trade name and the exact chemical structure is presented here to the scientific community for the first time. In the present work, the structure of the 6:2 FTAB was elucidated by ¹H, ¹³C and ¹⁹F nuclear magnetic resonance spectroscopy and high-resolution mass spectrometry. Moreover, its major metabolites from blue mussel (Mytilus edulis) and turbot (Scophthalmus maximus) and its photolytic transformation products were identified. Contrary to what has earlier been observed for PFOS, the 6:2 FTAB was extensively metabolized by blue mussel and turbot exposed to Forafac®1157. The major metabolite was a deacetylated betaine species, from which mono- and di-demethylated metabolites also were formed. Another abundant metabolite was the 6:2 fluorotelomer sulfonamide. In another experiment, Forafac®1157 was subjected to UV-light induced photolysis. The experimental conditions aimed to simulate Arctic conditions and the deacetylated species was again the primary transformation product of 6:2 FTAB. A 6:2 fluorotelomer sulfonamide was also formed along with a non-identified transformation product. The environmental presence of most of the metabolites and transformation products was qualitatively demonstrated by analysis of soil samples taken in close proximity to an airport fire training facility.     

Tracking nitrogen losses in a greenhouse crop rotation experiment in North China using the EU-Rotate_N simulation model

Vegetable production in China is associated with high inputs of nitrogen, posing a risk of losses to the environment. Organic matter mineralisation is a considerable source of nitrogen (N) which is hard to quantify. In a two-year greenhouse cucumber experiment with different N treatments in North China, non-observed pathways of the N cycle were estimated using the EU-Rotate_N simulation model. EU-Rotate_N was calibrated against crop dry matter and soil moisture data to predict crop N uptake, soil mineral N contents, N mineralisation and N loss. Crop N uptake (Modelling Efficiencies (ME) between 0.80 and 0.92) and soil mineral N contents in different soil layers (ME between 0.24 and 0.74) were satisfactorily simulated by the model for all N treatments except for the traditional N management. The model predicted high N mineralisation rates and N leaching losses, suggesting that previously published estimates of N leaching for these production systems strongly underestimated the mineralisation of N from organic matter.     

Setting the most robust effluent level under severe uncertainty: Application of information-gap decision theory to chemical management

Decisions in ecological risk management for chemical substances must be made based on incomplete information due to uncertainties. To protect the ecosystems from the adverse effect of chemicals, a precautionary approach is often taken. The precautionary approach, which is based on conservative assumptions about the risks of chemical substances, can be applied selecting management models and data. This approach can lead to an adequate margin of safety for ecosystems by reducing exposure to harmful substances, either by reducing the use of target chemicals or putting in place strict water quality criteria. However, the reduction of chemical use or effluent concentrations typically entails a financial burden. The cost effectiveness of the precautionary approach may be small. Hence, we need to develop a formulaic methodology in chemical risk management that can sufficiently protect ecosystems in a cost-effective way, even when we do not have sufficient information for chemical management. Information-gap decision theory can provide the formulaic methodology. Information-gap decision theory determines which action is the most robust to uncertainty by guaranteeing an acceptable outcome under the largest degree of uncertainty without requiring information about the extent of parameter uncertainty at the outset. In this paper, we illustrate the application of information-gap decision theory to derive a framework for setting effluent limits of pollutants for point sources under uncertainty. Our application incorporates a cost for reduction in pollutant emission and a cost to wildlife species affected by the pollutant. Our framework enables us to settle upon actions to deal with severe uncertainty in ecological risk management of chemicals.     

Effects of input uncertainty and variability on the modelled environmental fate of organic pollutants under global climate change scenarios

Global climate change (GCC) is expected to influence the fate, exposure and risks of organic pollutants to wildlife and humans. Multimedia chemical fate models have been previously applied to estimate how GCC affects pollutant concentrations in the environment and biota, but previous studies have not addressed how uncertainty and variability of model inputs affect model predictions. Here, we assess the influence of climate variability and chemical property uncertainty on future projections of environmental fate of six polychlorinated biphenyl congeners under different GCC scenarios using a spreadsheet version of the ChemCAN model and the Crystal Ball® software. Regardless of emission mode, results demonstrate: (i) uncertainty in degradation half-lives dominates the variance of modelled absolute levels of PCB congeners under GCC scenarios; (ii) when the ratios of predictions under GCC to predictions under present day climate are modelled, climate variability dominates the variance of modelled ratios; and (iii) the ratios also indicate a maximum of about a factor of 2 change in the long-term average environmental concentrations due to GCC that is forecasted between present conditions and the period between 2080 and 2099. We conclude that chemical property uncertainty does not preclude assessing relative changes in a GCC scenario compared to a present-day scenario if variance in model outputs due to chemical properties and degradation half-lives can be assumed to cancel out in the two scenarios.     

Zebrafish embryos/larvae for rapid determination of effects on hypothalamic-pituitary-thyroid (HPT) and hypothalamic-pituitary-interrenal (HPI) axis: mRNA expression

To identify and prioritize chemicals that may affect thyroid and adrenal/interregnal endocrine system and to reduce cost and animal use by conventional toxicity assay, an in vivo screening assay was developed using zebrafish embryos/larvae based on measurement of expression of genes that were suggested to play important roles in hypothalamic-pituitary-thyroid (HPT) and hypothalamic-pituitary-interrenal (HPI) axis. Model chemicals that could modulate HPT and HPI axis in adult fish were selected in assay validation, including anti-thyroid agent 6-Propyl-2-thiouracil (PTU) and cytochrome P450 11B (Cyp11b) enzyme inhibitor metyrapone (MET). Zebrafish embryos were exposed to different concentrations of model chemical from 4 h post-fertilization (hpf) to 5 d post-fertilization (dpf). Exposure to PTU increased mRNA expression of sodium iodide symporter (nis) and thyroglobulin (tg) involved in HPT axis, and MET treatment up-regulated all the mRNA expression tested involved in HPI axis by a compensatory mechanism. These results suggested that HPT and HPI axis were active upon chemical exposure at least at 5 dpf zebrafish. Furthermore, we studied the effects of PTU or MET on the cross-talk between HPT and HPI axis. The results demonstrated that PTU and MET could affect cross-talk responses in zebrafish embryos/larvae.