Compartmentation and effects of lead (Pb) in the collembolan,Folsomia candida

Environmental Science and Pollution Research - The impact of soil lead (Pb) pollution on survival, growth, and reproduction of the collembolan, Folsomia candida, and Pb compartmentation in its gut...     

A biomarker model of sublethal genotoxicity (DNA single-strand breaks and adducts) using the sentinel organism Aporrectodea longa in spiked soil

There is a need to develop risk biomarkers during the remediation of contaminated land. We employed the earthworm, Aporrectodea longa (Ude), to determine whether genotoxicity measures could be applied to this organism's intestinal tissues. Earthworms were added, for 24h or 7 days, to soil samples spiked with benzo[a]pyrene (B[a]P) and/or lindane. After exposure, intestinal tissues (crop/gizzard or intestine) were removed prior to the measurement in disaggregated cells of DNA single-strand breaks (SSBs) by the alkaline comet assay. Damage was quantified by comet tail length (CTL, microm). B[a]P 24-h exposure induced dose-related increases (P<0.0001) in SSBs. Earthworm intestine was significantly (P<0.0001) more susceptible than crop/gizzard to B[a]P and/or lindane. However, both tissues appeared to acquire resistance following 7-day exposure. B[a]P-DNA adducts, measured by (32)P-postlabelling, showed a two-adduct-spot pattern. This preliminary investigation suggests that earthworm tissues may be incorporated into genotoxicity assays to facilitate hazard identification within terrestrial ecosystems.     

Analysis of 3-year observations of CFC-11, CFC-12 and CFC-113 from a semi-rural site in China

In-situ measurements of atmospheric chlorofluorocarbons (CFCs) can be used to the assess their global and regional emissions and to check for compliance with phase-out schedules under Montreal protocol and its amendments. The atmospheric mixing ratios of CFC-11 (CCl₃F), CFC-12 (CCl₂F₂) and CFC-113 (CCl₂F–CClF₂) have been measured by an automated in-situ GC-ECDs system at the regional Chinese Global Atmosphere Watch (GAW) station Shangdianzi (SDZ), from November 2006 to October 2009. The time series for these three principal CFCs showed large episodic events and background conditions occurred for approximately 30% (CFC-11), 52% (CFC-12) and 56% (CFC-113) of the measurements. The mean background mixing ratios for CFC-11, CFC-12 and CFC-113 were 244.8 ppt (parts per trillion, 10^?12, molar) 539.6 ppt and 76.8 ppt, respectively, for 2006–2009. The enhanced CFC mixing ratios compared to AGAGE sites such as Trinidad Head (THD), US and Mace Head (MHD), Ireland suggest regional influences even during background conditions at SDZ, which is much closer to highly-populated areas. Between 2006 and 2009 background CFCs exhibited downward trends at rates of ?2.0 ppt yr^?1 for CFC-11, ?2.5 ppt yr^?1 for CFC-12 and ?0.7 ppt yr^?1 for CFC-113. De-trended 3-year average background seasonal cycles displayed small fluctuations with peak-to-trough amplitudes of 1.0 ± 0.02 ppt (0.4%) for background CFC-11, 1.3 ± 2.1 ppt (0.3%) for CFC-12 and 0.2 ± 0.4 ppt (0.3%) for CFC-113. On the other hand, during pollution periods these CFCs showed much larger seasonal cycles of 11.2 ± 10.7 ppt (5%) for CFC-11, 7.5 ± 6.5 ppt (2%) for CFC-12 and 1.0 ± 1.2 ppt (1.2%) for CFC-113, with apparent winter minima and early summer maxima. This enhancement was attributed to prevailing wind directions from urban regions in summer and to enhanced anthropogenic sources during the warm season. In general, horizontal winds from northeast showed negative contribution to atmospheric CFCs loading, whereas South Western advection (urban sector: Beijing) had positive contributions.     

Determination of microbial activity in activated sewage sludge by dimethyl sulphoxide reduction

A method was developed to determine the dimethyl sulphoxide (DMSO) reduction rate in activated sewage sludge at nearly natural conditions. Linearity of microbially produced dimethyl sulphide with incubation time and sample size was shown. Apart from a fast, sensitive and highly reproducible automatic analysis of dimethyl sulphide, simultaneous determination of mineralisation, respiration and phenol degradation rates was possible. The DMSO reduction rate of samples taken from a municipal sewage plant ranged between 2 and 3 μmol/(g dry matter · h), respiration and mineralisation rates between 30 and 80 μmol/(g · h). Added¹³C₆-phenol was completely degradated after 96 h of incubation. A half-life of 14 h was calculated assuming first order decay. Dose response curves were obtained by incubating samples for 2, 6, 25, and 96 hours after addition of pentachlorophenol. At an incubation time of 6 h, the EC₅₀ values ranged from 20 mg/L (DMSO reduction) to 30 mg/L (phenol degradation) up to 180 mg/L (respiration and mineralisation). Increasing the incubation time to 96 h resulted in a lower EC₅₀ of 9 mg/L for DMSO reduction, whereas it increased to 500 mg/L for respiration and mineralisation.     

Characterizing sources of nitrate leaching from an irrigated dairy farm in Merced County, California

Dairy farms comprise a complex landscape of groundwater pollution sources. The objective of our work is to develop a method to quantify nitrate leaching to shallow groundwater from different management units at dairy farms. Total nitrate loads are determined by the sequential calibration of a sub-regional scale and a farm-scale three-dimensional groundwater flow and transport model using observations at different spatial scales. These observations include local measurements of groundwater heads and nitrate concentrations in an extensive monitoring well network, providing data at a scale of a few meters and measurements of discharge rates and nitrate concentrations in a tile-drain network, providing data integrated across multiple farms. The various measurement scales are different from the spatial scales of the calibration parameters, which are the recharge and nitrogen leaching rates from individual management units. The calibration procedure offers a conceptual framework for using field measurements at different spatial scales to estimate recharge N concentrations at the management unit scale. It provides a map of spatially varying dairy farming impact on groundwater nitrogen. The method is applied to a dairy farm located in a relatively vulnerable hydrogeologic region in California. Potential sources within the dairy farm are divided into three categories, representing different manure management units: animal exercise yards and feeding areas (corrals), liquid manure holding ponds, and manure irrigated forage fields. Estimated average nitrogen leaching is 872 kg/ha/year, 807 kg/ha/year and 486 kg/ha/year for corrals, ponds and fields respectively. Results are applied to evaluate the accuracy of nitrogen mass balances often used by regulatory agencies to assess groundwater impacts. Calibrated leaching rates compare favorably to field and farm scale nitrogen mass balances. These data and interpretations provide a basis for developing improved management strategies.     

Source to sink tracking of selected human pharmaceuticals from two Oslo city hospitals and a wastewater treatment works

The occurrence of twenty pharmaceutical compounds was quantitatively determined in effluents from two major Oslo city hospitals, Rikshospitalet and Ullev?l, along with influent, sludge and final effluent from the city's VEAS wastewater treatment works (WTW). Composite hospital effluents were collected over a twelve week period and were showed to contain paracetamol, metoprolol, diclofenac, ibuprofen, 17beta-Estradiol, estriol, estrone, oxytetracycline, tetracycline, doxycycline, chlorotetracycline, demeclocycline, trimethoprim, ciprofloxacin, sulfamethoxazole, cyclophosphamide and ifosfamide. Three pharmaceuticals were not detected above the limit of detection; cefuroxime, 17alpha-ethinylestradiol and meclocycline. Composite influent, sludge and effluent samples were collected from VEAS WTW over a seven week period. The influent into VEAS WTW contained all of the same selected substances detected in the hospital effluents, except for oxytetracycline, chlorotetracycline, demeclocycline, cyclophosphamide and ifosfamide. The percentage of pharmaceuticals entering the works from the hospitals was <10% for all of the selected compounds. VEAS sludge samples contained a different profile of substances reflecting their physico-chemical properties. Hydrophobic antibiotics, such as oxytetracycline, tetracycline and ciprofloxacin, were detected in all of the collected sludge samples. Their absence in the collected influent samples suggests that they enter the works bound to effluent particles, with the dissolved fraction observed in the hospital effluents partitioning onto particulate matter within the sewerage network. The final effluent from VEAS WTW contained reduced concentrations of many pharmaceuticals, including paracetamol, ibuprofen and sulfamethoxazole. For other compounds, such as metoprolol, diclofenac and trimethoprim, there were often higher concentrations in the effluent than the influent. These effluent concentrations represent median inputs varying from low g day(-1) (e.g. paracetamol and ibuprofen) to nearly 200 g day(-1) (e.g. metoprolol and trimethoprim) into Oslofjord. A simple risk assessment showed that the antibiotic ciprofloxacin may at times pose an acute risk to the Oslofjord aquatic environment.     

Prediction models of CO, SPM and SO2 concentrations in the Campo de Gibraltar Region, Spain: a multiple comparison strategy

The 'Campo de Gibraltar' region is a very industrialized area where very few air pollution studies have been carried out. Up to date, no model has been developed in order to predict air pollutant levels in the different towns spread in the region. Carbon monoxide (CO), Sulphur dioxide (SO(2)) and suspended particulate matter (SPM) series have been investigated (years 1999-2000-2001). Multilayer perceptron models (MLPs) with backpropagation learning rule have been used. A resampling strategy with two-fold crossvalidation allowed the statistical comparison of the different models considered in this study. Artificial neural networks (ANN) models were compared with Persistence and ARIMA models and also with models based on standard Multiple Linear Regression (MLR) over test sets with data that had not been used in the training stage. The models based on ANNs showed better capability of generalization than those based on MLR. The designed procedure of random resampling permits an adequate and robust multiple comparison of the tested models. Principal component analysis (PCA) is used to reduce the dimensionality of data and to transform exogenous variables into significant and independent components. Short-term predictions were better than medium-term predictions in the case of CO and SO(2) series. Conversely, medium-term predictions were better in the case of SPM concentrations. The predictions are significantly promising (e.g., d (SPM 24-ahead) = 0.906, d (CO 1-ahead) = 0.891, d (SO2 1-ahead) = 0.851).     

Advanced REACH Tool (ART): calibration of the mechanistic model

The mechanistic model of the Advanced Reach Tool (ART) provides a relative ranking of exposure levels from different scenarios. The objectives of the calibration described in this paper are threefold: to study whether the mechanistic model scores are accurately ranked in relation to exposure measurements; to enable the mechanistic model to estimate actual exposure levels rather than relative scores; and to provide a method of quantifying model uncertainty. Stringent data quality guidelines were applied to the collated data. Linear mixed effects models were used to evaluate the association between relative ART model scores and measurements. A random scenario and company component of variance were introduced to reflect the model uncertainty. Stratified analyses were conducted for different forms of exposure (abrasive dust, dust, vapours and mists). In total more than 2000 good quality measurements were available for the calibration of the mechanistic model. The calibration showed that after calibration the mechanistic model of ART was able to estimate geometric mean (GM) exposure levels with 90% confidence for a given scenario to lie within a factor between two and six of the measured GM depending upon the form of exposure.