Does the nutrition profile of vitamins, fatty acids and microelements counteract the negative impact from organohalogen pollutants on bone mineral density in Greenland sledge dogs (Canis familiaris)?

There is a great need for understanding the impact from dietary OHCs (organohalogen compounds) on bone mineral composition - and thereby osteoporosis - in especially arctic wildlife such as polar bears (Ursus maritimus) as well as humans. For that purpose, we measured BMD (bone mineral density) by DXA scanning (g/cm(-2)) in 15 age and weight normalized sledge dog (Canis familiaris) bitches and their 26 pups divided into a control group (n=26) given 50-200 g/day clean pork (Suis scrofa) fat and a treated group (n=15) given 50-200 g/day OHC polluted minke whale (Balaenoptera acutorostrata) blubber as main lipid sources. The results showed that BMD increased significantly with age (linear regression: p<0.0001, r(2)=0.83, n=41) while no sex difference was found in the F-generation (two-way ANOVA: all p>0.3). No differences in BMD(femur) or BMD(vertebrae) between exposed and control individuals in the bitch generation were found (linear mixed effect model: both p>0.38). Likewise, no difference between exposed and control subadults and juveniles in the F-generation was found (two-way ANOVA: all p>0.33). Correlation analyses between BMD(femur), BMD(vertebrae) and groups of OHCs, respectively, did not show any statistically significant relationships nor a clear or decreasing trend (Pearson's: p: 0.07-0.78; r: -0.2-0.59; n: 10-18). As the groups were similar regarding genetics, age and sex are the only factors that can explain this observation. Either the pollutants did not have an impact on BMD using the present time frame and OHC concentrations (threshold levels not reached), or the difference in food composition (mainly vitamins and n3 fatty acids) conceal the potential OHC impact on BMD. Such information is important when evaluating the positive and negative health consequences from eating polluted marine species.     

A spatial risk assessment methodology to support the remediation of contaminated land

When soil and groundwater contaminations occur over large areas, remediation measures should be spatially prioritized on the basis of the risk posed to human health and in compliance with technological and budget constraints. Within this scope, the application of human health risk assessment algorithms in a spatially resolved environment raises a number of methodological and technical complexities. In this paper, a methodology is proposed and applied in a case study to support the entire formulation process of remediation plans, encompassing hazard assessment, exposure assessment, risk characterisation, uncertainty assessment and allocation of risk reduction measures. In the hazard assessment, it supports the selection of Contaminants of Concern (CoC) with regard to both their average concentrations and peak concentrations, i.e. hot spots. In the exposure assessment, it provides a zoning of the site based on the geostatistical mapping of contaminant. In the risk characterisation, it generates vector maps of Risk Factors on the basis of the risk posed by multiple substances and allows the interrogation of most relevant CoC and exposure pathways for each zone of the site. It also supports the Monte Carlo based probabilistic estimation of the Risk Factors and generates maps of the associated uncertainty. In the risk reduction phase, it supports the formulation of remediation plans based on the stepwise spatial allocation of remediation interventions and the on-time simulation of risk reduction performances. The application of this methodology is fully supported by an easy-to-use and customized Geographical Information System and does not require high expertise for interpretation. The proposed methodology is the core module of a Decision Support System (DSS) that was implemented in the DESYRE software aimed at supporting the risk-based remediation of megasites.     

Methodological complexities of product carbon footprinting: a sensitivity analysis of key variables in a developing country context

Product carbon footprinting schemes adopt different analytical methodologies. The calculations can also be affected by limited data availability and uncertainty surrounding the value of key variables. The combination of these factors reduces the validity of comparing carbon footprints between products and countries.We used data from sugar production in Zambia and Mauritius to test how variations in methodology affected the product carbon footprint (PCF). We calculated a PCF according to PAS 2050 and explored the sensitivity of the results to the variation of key variables.Results showed that land use change emissions can dominate PCFs. The largest potential impact came from assuming global worst case data for land use change emissions where a product's origin is unknown (+1900%). The issue of land use change can lead to high carbon footprints for products from developing countries where more natural vegetation is still being converted and data are most lacking. When land use change is not important, variables such as electricity emission factors, capital inputs and loss of soil carbon had significant impacts on the PCF.This analysis highlights the large effect of methodology on PCFs. These results are of particular concern for developing countries where data are scarce and the use of global worst case data may be prescribed. We recommend the development of more precise emission factors for tropical countries and bio-regions, and encourage the transparent use of PCF methodologies, where data sources, uncertainties and variability are explicitly noted.     

Review of greenhouse gas emissions from crop production systems and fertilizer management effects

Fertilizer nitrogen (N) use is expanding globally to satisfy food, fiber, and fuel demands of a growing world population. Fertilizer consumers are being asked to improve N use efficiency through better management in their fields, to protect water resources and to minimize greenhouse gas (GHG) emissions, while sustaining soil resources and providing a healthy economy. A review of the available science on the effects of N source, rate, timing, and placement, in combination with other cropping and tillage practices, on GHG emissions was conducted. Implementation of intensive crop management practices, using principles of ecological intensification to enhance efficient and effective nutrient uptake while achieving high yields, was identified as a principal way to achieve reductions in GHG emissions while meeting production demands. Many studies identified through the review involved measurements of GHG emissions over several weeks to a few months, which greatly limit the ability to accurately determine system-level management effects on net global warming potential. The current science indicates: (1) appropriate fertilizer N use helps increase biomass production necessary to help restore and maintain soil organic carbon (SOC) levels; (2) best management practices (BMPs) for fertilizer N play a large role in minimizing residual soil nitrate, which helps lower the risk of increased nitrous oxide (N₂O) emissions; (3) tillage practices that reduce soil disturbance and maintain crop residue on the soil surface can increase SOC levels, but usually only if crop productivity is maintained or increased; (4) differences among fertilizer N sources in N₂O emissions depend on site- and weather-specific conditions; and (5) intensive crop management systems do not necessarily increase GHG emissions per unit of crop or food production; they can help spare natural areas from conversion to cropland and allow conversion of selected lands to forests for GHG mitigation, while supplying the world's need for food, fiber, and biofuel. Transfer of the information to fertilizer dealers, crop advisers, farmers, and agricultural and environmental authorities should lead to increased implementation of fertilizer BMPs, and help to reduce confusion over the role of fertilizer N on cropping system emissions of GHGs. Gaps in scientific understanding were identified and will require the collaborative attention of agronomists, soil scientists, ecologists, and environmental authorities in serving the immediate and long-term interests of the human population.     

Bacterial antibiotic resistance levels in Danish farmland as a result of treatment with pig manure slurry

Resistance to tetracycline, macrolides and streptomycin was measured for a period of 8 months in soil bacteria obtained from farmland treated with pig manure slurry. This was done by spread plating bacteria on selective media (Luria Bertani (LB) medium supplemented with antibiotics). To account for seasonal variations in numbers of soil bacteria, ratios of resistant bacteria divided by total count on nonselective plates were calculated. Soil samples were collected from four different farms and from a control soil on a fifth farm. The control soil was not amended with animal manure. The occurrence of tetracycline-resistant bacteria was elevated after spread of pig manure slurry but declined throughout the sampling period to a level corresponding to the control soil. Higher load of pig manure slurry yielded higher occurrence of tetracycline resistance after spreading; however, the tetracycline resistance declined to normal occurrence defined by the tetracycline resistance occurrence in the control soil. Concentrations of tetracycline in soil and in pig manure slurry were measured using HPLC. No tetracycline exceeding the detection limit was found in soil samples. Manure slurry concentrations of tetracycline for three of the farms were 42, 81 and 698 microg/l, respectively. For streptomycin and macrolides, only minor variations in resistance levels were detected. Results obtained in this study thus indicate that tetracycline resistance levels in soil are temporarily influenced by the addition of pig manure slurry. The results indicate also that increased amount of pig manure slurry amendment may result in increased levels of tetracycline resistance in the soil.     

Unexpected effects of sublethal doses of insecticide on the peripheral olfactory response and sexual behavior in a pest insect

Pesticides have long been used as the main solution to limit agricultural pests, but their widespread use resulted in chronic or diffuse environmental pollutions, development of insect resistances, and biodiversity reduction. The effects of low residual doses of these chemical products on organisms that affect both targeted species (crop pests) but also beneficial insects became a major concern, particularly because low doses of pesticides can induce unexpected positive—also called hormetic—effects on insects, leading to surges in pest population growth at greater rate than what would have been observed without pesticide application. The present study aimed to examine the effects of sublethal doses of deltamethrin, one of the most used synthetic pyrethroids, known to present a residual activity and persistence in the environment, on the peripheral olfactory system and sexual behavior of a major pest insect, the cotton leafworm Spodoptera littoralis. We highlighted here a hormetic effect of sublethal dose of deltamethrin on the male responses to sex pheromone, without any modification of their response to host-plant odorants. We also identified several antennal actors potentially involved in this hormetic effect and in the antennal detoxification or antennal stress response of/to deltamethrin exposure.     

Estimation and simulation for geospatial porosity and permeability data

Reservoir simulation of \(\hbox {CO}_2\) sequestration, energy recovery, and environmental contamination scenarios must be accompanied by uncertainty quantification. Typically this is done by stochastically modeling porosity and permeability fields, simulating realizations based on the model, and then numerically simulating flow and transport. The challenge is to generate simulated porosity and permeability fields with characteristics as similar as possible to those known of the reservoir under study. In this paper we focus on the first two steps above in analyzing a large 3-dimensional array of geospatial porosity data and using the results to produce simulated data with characteristics mimicking those of the original porosity observations. The spatial covariance is empirically approximated from horizontal cross sections of the data via a kernel principle component analysis yielding dimension reduction. Simulations in three dimensions are produced by linking consecutive parallel cross sections via conditioning on a small subarray of the data. The conditional simulations effectively reproduce observed channeling, an important large scale feature of interest in the sub-surface relevant to transport of contaminates. The original porosity data is non-Gaussian and requires additional analysis and transformation to generate both porosity and permeability fields.     

Development and Evaluation of a Method to Determine Indicator Microorganisms in Air Emissions and Residue from Medical Waste Incinerators

To allow testing of microbial destruction in medical waste incinerators, methods were developed to determine indicator microorganisms (Bacillus Stearothermophilus spores) in incinerator air emissions and residue. The emission trapping train consisted of a water cooled glass probe and impingers containing a neutral phosphate buffer. In field tests, spores were injected directly into the probe, and results showed that approximately 60 percent of the spores were recovered. Spores were analyzed with adequate precision using a microbial membrane filter unit. Lab experiments indicated that spores were stable in neutral pH phosphate buffer for up to 20 days, and heat shocking samples (heating to 80°C for 20 minutes) reduced spore numbers in acidic or basic buffer. Laboratory tests also showed that 60 to 70 percent of spores initially added to ash were recovered up to 22 days after addition of the spores. In addition, lab tests showed that spores can be effectively recovered from residue test pipes spiked with indicator spores.     

A rapid method for screening of the Stockholm Convention POPs in small amounts of human plasma using SPE and HRGC/HRMS

A rapid analytical screening method allowing simultaneous analysis of 23 persistent organic pollutants (POPs) in human plasma was developed. Sample preparation based on solid-phase extraction (SPE) with additional clean-up using small multilayer silica gel columns. SPE was performed using a custom made polystyrene-divinylbenzene sorbent for the extraction of chlorinated and brominated POPs. Special efforts to reduce sample volume and improve speed and efficiency of the analytical procedure were made. Determination of 16 polychlorinated biphenyls (PCBs), 5 organochlorine (OC) pesticides, octachlorinated dibenzo-p-dioxin (OCDD) and polybrominated diphenyl ether (BDE #47) in 0.5 mL human plasma was performed by using high resolution gas chromatography coupled to high resolution mass spectrometry (HRGC/HRMS). Recovery of POPs ranged between 46% and 110%, and reproducibility was below 25% relative standard deviation (RSD) for all target compounds, except for trans-nonachlor and OCDD, which were present only at low levels. Limits of detection (LOD) were for the PCBs between 0.8 and 117.7 pg mL⁻¹ plasma and for the OC pesticides between 5.9 and 89.1 pg mL⁻¹ plasma. The LOD for OCDD and BDE #47 were 1.4 pg mL⁻¹ plasma, and 9.2 pg mL⁻¹ plasma, respectively. The presented method was successfully applied to 1016 human plasma samples from an epidemiological study on cardiovascular disease.