Risk assessment of linear alkylbenzene sulphonates, LAS, in agricultural soil revisited: robust chronic toxicity tests for Folsomia candida (Collembola), Aporrectodea caliginosa (Oligochaeta) and Enchytraeus crypticus (Enchytraeidae)

To obtain robust data on the toxicity of LAS, tests with the collembolan Folsomia candida L., the oligochaetes Aporrectodea caliginosa Savigny (earthworm) and Enchytraeus crypticus Westheide and Graefe (enchytraeid) were performed in a sandy loam soil. Additionally limited tests with LAS spiked to sewage sludge, and subsequently mixed into soil, were performed. For the endpoint of interest, reproduction in soil, we found an EC10 of 205 mg LAS kg(-1) soil [8.6-401] [95% confidence limits] for F. candida and an EC10 of 46 mg LAS kg(-1) soil [13-80] for A. caliginosa after 28 days. E. crypticus was not affected by concentrations up to 120 mg LAS kg(-1) soil. When adding (low contaminated) non-spiked sludge to soil, high stimulation of reproduction was observed for E. crypticus and A. caliginosa but not for F. candida. We argue that this difference in stimulative response between the tested species is related to the difference in feeding behaviour. Sludge spiked with LAS did not significantly affect the reproduction of F. candida (fertility: number of juvenile offspring) and A. caliginosa (fecundity: number of cocoons) (dose equivalent to 181 g and 91 g LAS kg(-1) sludge, respectively). Significantly reduced reproduction was observed for E. crypticus (at 120 mg LAS kg(-1) soil+sludge corresponding to 72 g LAS kg(-1) sludge) compared to non-spiked sludge. The reproduction by E. crypticus was, however, comparable to the reproduction observed in the control soil without sludge. Compared to LAS directly spiked to soil, the reproductive output of organisms exposed to spiked sludge was either not significantly different (F. candida, E. crypticus) or significantly improved (A. caliginosa). More studies are needed in order to make firm conclusions on the potential effect of artificially contaminated sludge in soil systems.     

Dioxin screening in fish product by pattern recognition of biomarkers

Two alternative, cost- and time-effective dioxin screening methods relying on two categories of potential lipid biomarkers were investigated. A dioxin range varying from 1.1 to 47.1 pg PCDD/F TEQ-WHO/g lipid using 64 fish meal samples was used for model calibration. The methods were based on multivariate models using either (1) fatty acid composition monitored by GC-FID or (2) fluorescence landscape signals analysed using the PARAFAC model and in both cases predicting dioxin content as pgPCDD/F TEQ-WHO/g lipid. In both cases, Partial Least Squares (PLS) regression was performed for predicting the dioxin content of a sample. The GC-FID data analyses was based on automatic peak alignment and integration, enabling extraction of the area of 140 peaks from the gas chromatograms, as opposed to the 31 fatty acids usually considered for fish oil characterisation. In addition to classic PLS employing the whole dataset for calibration, a two-step local PLS modeling approach was performed based upon an initial selection of k number of calibration samples providing the best match to the prediction sample using a so-called k Nearest Neighbors (kNN) approach, then followed by PLS calibration on these kNN selected samples for dioxin prediction. Fluorescence spectroscopy offers a promising non-invasive and ultra-rapid technique, with less than two minutes analysis time. However, fluorescence spectroscopy using the pattern recognition "kNN-PLS" yielded a correlation of 0.76 (r2) and a high root mean square error of prediction of 11.4 pg PCDD/F TEQ-WHO/g lipid. The predictions were improved when the PLS calibration was performed on all the sample with a root mean square error of prediction of 7.0 pg PCDD/F TEQ-WHO/g lipid. Unfortunately, these results failed to demonstrate the potential of fluorophore monitoring as a screening method. In contrast, the overall best screening performance was obtained with the fatty acid profile, when the kNN-PLS combination employed for pattern recognition (kNN) all the areas of the 140 detected peaks and the PLS regression used the areas of 46 selected peaks. This "kNN-PLS" prediction with three latent variables and based upon the 12 nearest neighbors selected out of the 64 x 2 fatty acid profiles (duplicate analyses), yielded a correlation of 0.85 (r2) and a root mean square error of prediction of 2.1 pg PCDD/F TEQ-WHO/g lipid and resulted in a total analysis time of one and half hour per sample.     

Footprints on ammonia concentrations from environmental regulations

Releases of ammonia (NH3) to the atmosphere contribute significantly to the deposition of nitrogen to both terrestrial and aquatic ecosystems. This is the background for the national NH3 emission ceilings in Europe. However, in some countries the national legislation aims not only to meet these ceilings but also to reduce the atmospheric nitrogen deposition to local ecosystems. Such measures to reduce the load of nitrogen to local ecosystems were introduced in Denmark in 1994. In this paper we demonstrate that this regulation is reflected in the NH3 concentrations in Denmark. The Danish legislation forces farmers to applying manure to the fields during the crop-growing season. We have analyzed the seasonal variation in local NH3 concentrations over the time period of 1989-2003. During this period the seasonal variation has changed from having moderate spring and autumn concentration peaks to having a single and much more pronounced spring peak. In the analysis we apply an NH3 emission model to demonstrate that these changes in the seasonal variation are a result of the changes in the Danish legislation. The analysis demonstrates the strength of using a high-resolution emission model in the analysis of routine monitoring data.     

Evaluation of environmental impacts from municipal solid waste management in the municipality of Aarhus, Denmark (EASEWASTE).

A new computer based life cycle assessment model (EASEWASTE) was used to evaluate a municipal solid waste system with the purpose of identifying environmental benefits and disadvantages by anaerobic digestion of source-separated household waste and incineration. The most important processes that were included in the study are optical sorting and pre-treatment, anaerobic digestion with heat and power recovery, incineration with heat and power recovery, use of digested biomass on arable soils and finally, an estimated surplus consumption of plastic in order to achieve a higher quality and quantity of organic waste to the biogas plant. Results showed that there were no significant differences in most of the assessed environmental impacts for the two scenarios. However, the use of digested biomass may cause a potential toxicity impact on human health due to the heavy metal content of the organic waste. A sensitivity analysis showed that the results are sensitive to the energy recovery efficiencies, to the extra plastic consumption for waste bags and to the content of heavy metals in the waste. A model such as EASEWASTE is very suitable for evaluating the overall environmental consequences of different waste management strategies and technologies, and can be used for most waste material fractions existing in household waste.     

Environmental modelling of use of treated organic waste on agricultural land: a comparison of existing models for life cycle assessment of waste systems.

Modelling of environmental impacts from the application of treated organic municipal solid waste (MSW) in agriculture differs widely between different models for environmental assessment of waste systems. In this comparative study five models were examined concerning quantification and impact assessment of environmental effects from land application of treated organic MSW: DST (Decision Support Tool, USA), IWM (Integrated Waste Management, U.K.), THE IFEU PROJECT (Germany), ORWARE (ORganic WAste REsearch, Sweden) and EASEWASTE (Environmental Assessment of Solid Waste Systems and Technologies, Denmark). DST and IWM are life cycle inventory (LCI) models, thus not performing actual impact assessment. The DST model includes only one water emission (biological oxygen demand) from compost leaching in the results and IWM considers only air emissions from avoided production of commercial fertilizers. THE IFEU PROJECT, ORWARE and EASEWASTE are life cycle assessment (LCA) models containing more detailed land application modules. A case study estimating the environmental impacts from land application of 1 ton of composted source sorted organic household waste was performed to compare the results from the different models and investigate the origin of any difference in type or magnitude of the results. The contributions from the LCI models were limited and did not depend on waste composition or local agricultural conditions. The three LCA models use the same overall approach for quantifying the impacts of the system. However, due to slightly different assumptions, quantification methods and environmental impact assessment, the obtained results varied clearly between the models. Furthermore, local conditions (e.g. soil type, farm type, climate and legal regulation) and waste composition strongly influenced the results of the environmental assessment.