Bromination of selected pharmaceuticals in water matrices

The bromination of five selected pharmaceuticals (metoprolol, naproxen, amoxicillin, phenacetin, and hydrochlorothiazide) was studied with these compounds individually dissolved in ultra-pure water. The apparent rate constants for the bromination reaction were determined as a function of the pH, obtaining the sequence amoxicillin > naproxen ? hydrochlorothiazide ≈ phenacetin ≈ metoprolol. A kinetic mechanism specifying the dissociation reactions and the species formed for each compound according to its pK_a value and the pH allowed the intrinsic rate constants to be determined for each elementary reaction. There was fairly good agreement between the experimental and calculated values of the apparent rate constants, confirming the goodness of the proposed reaction mechanism.In a second stage, the bromination of the selected pharmaceuticals simultaneously dissolved in three water matrices (a groundwater, a surface water from a public reservoir, and a secondary effluent from a WWTP) was investigated. The pharmaceutical elimination trend agreed with the previously determined rate constants. The influence of the main operating conditions (pH, initial bromine dose, and characteristics of the water matrix) on the degradation of the pharmaceuticals was established. An elimination concentration profile for each pharmaceutical in the water matrices was proposed based on the use of the previously evaluated apparent rate constants, and the theoretical results agreed satisfactorily with experiment. Finally, chlorination experiments performed in the presence of bromide showed that low bromide concentrations slightly accelerate the oxidation of the selected pharmaceuticals during chlorine disinfection.     

Sociodemographic, reproductive and dietary predictors of organochlorine compounds levels in pregnant women in Spain

Organochlorine pesticides and polychlorinated biphenyls (PCBs) are consistently found in human tissues. Serum levels of organochlorine compounds (OC) in pregnant women in particular have raised concern about possible harm to humans in the early phases of physical and behavioural development. The objective of the present study was to evaluate the association between concentration of OCs in serum of two cohorts of pregnant women from Gipuzkoa and Sabadell in Spain and socioeconomic, reproductive and dietary variables. Concentration of polychlorinated biphenyls (PCBs: 28, 52, 101, 118, 138, 153 and 180), hexachlorobenzene (HCB), beta and gamma-hexachlorocyclohexane (β-HCH and γ-HCH), heptachlor epoxide, dichlorodiphenyl dichloroethylene (p,p'-DDE) and dichlorodiphenyl trichloroethane (p,p'-DDT) were measured in the serum of 1259 pregnant women. Associations between OCs and potential predictor variables were assessed using linear regression models adjusted for potential confounders. The compounds most commonly found in the serum were p,p'-DDE (99% of the samples) and PCB-153 (95% of the samples). Geometric means of serum concentrations (ng g?1 lipid) of organochlorine pesticides were 110.0, 19.1, and 33.5 for p,p'-DDE, β-HCH, and HCB respectively, while the geometric means of PCBs were 21.8, 38.9 and 26.9 for PCB 138, 153, and 180 respectively. The levels of all OCs increased with age. BMI was positively associated with the concentration of organochlorine pesticides but inversely related to PCB concentrations. The serum levels of OCs fell only after a cumulative period of breastfeeding of over a year. Levels of PCBs were related to fish intake, but in general dietary factors did not improve the explained variability of the concentrations of OCs. Overall, the levels of OCs found in the study are at the lower end of the range reported in Spain and other countries.     

Plant communities in relation to flooding and soil contamination in a lowland Rhine River floodplain

Using canonical correspondence analysis (CCA), relationships were investigated between plant species composition and flooding characteristics, heavy metal contamination and soil properties in a lowland floodplain of the Rhine River. Floodplain elevation and yearly average flooding duration turned out to be more important for explaining variation in plant species composition than soil heavy metal contamination. Nevertheless, plant species richness and diversity showed a significant decrease with the level of contamination. As single heavy metal concentrations seemed mostly too low for causing phytotoxic effects in plants, this trend is possibly explained by additive effects of multiple contaminants or by the concomitant influences of contamination and non-chemical stressors like flooding. These results suggest that impacts of soil contamination on plants in floodplains could be larger than expected from mere soil concentrations. In general, these findings emphasize the relevance of analyzing effects of toxic substances in concert with the effects of other relevant stressors.     

Integrated analysis of the effects of agricultural management on nitrogen fluxes at landscape scale

The integrated modelling system INITIATOR was applied to a landscape in the northern part of the Netherlands to assess current nitrogen fluxes to air and water and the impact of various agricultural measures on these fluxes, using spatially explicit input data on animal numbers, land use, agricultural management, meteorology and soil. Average model results on NH₃ deposition and N concentrations in surface water appear to be comparable to observations, but the deviation can be large at local scale, despite the use of high resolution data. Evaluated measures include: air scrubbers reducing NH₃ emissions from poultry and pig housing systems, low protein feeding, reduced fertilizer amounts and low-emission stables for cattle. Low protein feeding and restrictive fertilizer application had the largest effect on both N inputs and N losses, resulting in N deposition reductions on Natura 2000 sites of 10% and 12%, respectively.     

Farm, land, and soil nitrogen budgets for agriculture in Europe calculated with CAPRI

We calculated farm, land, and soil N-budgets for countries in Europe and the EU27 as a whole using the agro-economic model CAPRI. For EU27, N-surplus is 55 kg N ha⁻¹ yr⁻¹ in a soil budget and 65 kg N₂O–N ha⁻¹ yr⁻¹ and 67 kg N ha⁻¹ yr⁻¹ in land and farm budgets, respectively. NUE is 31% for the farm budget, 60% for the land budget and 63% for the soil budget. NS values are mainly related to the excretion (farm budget) and application (soil and land budget) of manure per hectare of total agricultural land. On the other hand, NUE is best explained by the specialization of the agricultural system toward animal production (farm NUE) or the share of imported feedstuff (soil NUE). Total N input, intensive farming, and the specialization to animal production are found to be the main drivers for a high NS and low NUE.     

Assessing the recovery potential of alpine moss-sedge heath: reciprocal transplants along a nitrogen deposition gradient

The potential of alpine moss-sedge heath to recover from elevated nitrogen (N) deposition was assessed by transplanting Racomitrium lanuginosum shoots and vegetation turfs between 10 elevated N deposition sites (8.2-32.9 kg ha⁻¹ yr⁻¹) and a low N deposition site, Ben Wyvis (7.2 kg ha⁻¹ yr⁻¹). After two years, tissue N of Racomitrium shoots transplanted from higher N sites to Ben Wyvis only partially equilibrated to reduced N deposition whereas reciprocal transplants almost matched the tissue N of indigenous moss. Unexpectedly, moss shoot growth was stimulated at higher N deposition sites. However, moss depth and biomass increased in turfs transplanted to Ben Wyvis, apparently due to slower shoot turnover (suggested to result partly from decreased tissue C:N slowing decomposition), whilst abundance of vascular species declined. Racomitrium heath has the potential to recover from the impacts of N deposition; however, this is constrained by the persistence of enhanced moss tissue N contents.     

N deposition as a threat to the World's protected areas under the Convention on Biological Diversity

This paper combines the world’s protected areas (PAs) under the Convention on Biological Diversity (CBD), common classification systems of ecosystem conservation status, and current knowledge on ecosystem responses to nitrogen (N) deposition to determine areas most at risk. The results show that 40% (approx. 11% of total area) of PAs currently receive >10 kg N/ha/yr with projections for 2030 indicating that this situation is not expected to change. Furthermore, 950 PAs are projected to receive >30 kg N/ha/yr by 2030 (approx. twice the 2000 number), of which 62 (approx. 11,300 km²) are also Biodiversity Hotspots and G200 ecoregions; with forest and grassland ecosystems in Asia particularly at risk. Many of these sites are known to be sensitive to N deposition effects, both in terms of biodiversity changes and ecosystem services they provide. Urgent assessment of high risk areas identified in this study is recommended to inform the conservation efforts of the CBD.     

Modelling the impact of nitrogen deposition, climate change and nutrient limitations on tree carbon sequestration in Europe for the period 1900-2050

We modelled the combined effects of past and expected future changes in climate and nitrogen deposition on tree carbon sequestration by European forests for the period 1900-2050. Two scenarios for deposition (current legislation and maximum technically feasible reductions) and two climate scenarios (no change and SRES A1 scenario) were used. Furthermore, the possible limitation of forest growth by calcium, magnesium, potassium and phosphorus is investigated. The area and age structure of the forests was assumed to stay constant to observations during the period 1970-1990. Under these assumptions, the simulations show that the change in forest growth and carbon sequestration in the past is dominated by changes in nitrogen deposition, while climate change is the major driver for future carbon sequestration. However, its impact is reduced by nitrogen availability. Furthermore, limitations in base cations, especially magnesium, and in phosphorus may significantly affect predicted growth in the future.     

Modeling transit bus fuel consumption on the basis of cycle properties

A method exists to predict heavy-duty vehicle fuel economy and emissions over an "unseen" cycle or during unseen on-road activity on the basis of fuel consumption and emissions data from measured chassis dynamometer test cycles and properties (statistical parameters) of those cycles. No regression is required for the method, which relies solely on the linear association of vehicle performance with cycle properties. This method has been advanced and examined using previously published heavy-duty truck data gathered using the West Virginia University heavy-duty chassis dynamometer with the trucks exercised over limited test cycles. In this study, data were available from a Washington Metropolitan Area Transit Authority emission testing program conducted in 2006. Chassis dynamometer data from two conventional diesel buses, two compressed natural gas buses, and one hybrid diesel bus were evaluated using an expanded driving cycle set of 16 or 17 different driving cycles. Cycle properties and vehicle fuel consumption measurements from three baseline cycles were selected to generate a linear model and then to predict unseen fuel consumption over the remaining 13 or 14 cycles. Average velocity, average positive acceleration, and number of stops per distance were found to be the desired cycle properties for use in the model. The methodology allowed for the prediction of fuel consumption with an average error of 8.5% from vehicles operating on a diverse set of chassis dynamometer cycles on the basis of relatively few experimental measurements. It was found that the data used for prediction should be acquired from a set that must include an idle cycle along with a relatively slow transient cycle and a relatively high speed cycle. The method was also applied to oxides of nitrogen prediction and was found to have less predictive capability than for fuel consumption with an average error of 20.4%.