Sensitivity of ecological models to their climate drivers: statistical ensembles for forcing.

Global and regional numerical models for terrestrial ecosystem dynamics require fine spatial resolution and temporally complete historical climate fields as input variables. However, because climate observations are unevenly spaced and have incomplete records, such fields need to be estimated. In addition, uncertainty in these fields associated with their estimation are rarely assessed. Ecological models are usually driven with a geostatistical model's mean estimate (kriging) of these fields without accounting for this uncertainty, much less evaluating such errors in terms of their propagation in ecological simulations. We introduce a Bayesian statistical framework to model climate observations to create spatially uniform and temporally complete fields, taking into account correlation in time and space, spatial heterogeneity, lack of normality, and uncertainty about all these factors. A key benefit of the Bayesian model is that it generates uncertainty measures for the generated fields. To demonstrate this method, we reconstruct historical monthly precipitation fields (a driver for ecological models) on a fine resolution grid for a climatically heterogeneous region in the western United States. The main goal of this work is to evaluate the sensitivity of ecological models to the uncertainty associated with prediction of their climate drivers. To assess their numerical sensitivity to predicted input variables, we generate a set of ecological model simulations run using an ensemble of different versions of the reconstructed fields. We construct such an ensemble by sampling from the posterior predictive distribution of the climate field. We demonstrate that the estimated prediction error of the climate field can be very high. We evaluate the importance of such errors in ecological model experiments using an ensemble of historical precipitation time series in simulations of grassland biogeochemical dynamics with an ecological numerical model, Century. We show how uncertainty in predicted precipitation fields is propagated into ecological model results and that this propagation had different modes. Depending on output variable, the response of model dynamics to uncertainty in inputs ranged from uncertainty in outputs that matched that of inputs to those that were muted or that were biased, as well as uncertainty that was persistent in time after input errors dropped.     

The effect of the presence of trace metals on the oxidation of Sb(III) by hydrogen peroxide in aqueous solution

Despite its importance for understanding the behaviour of antimony in the environment, the oxidation kinetics of Sb(III) with natural oxidants is still not well understood. We have studied the oxidation of Sb(III) by hydrogen peroxide on a time scale of hours in the presence of some trace metals, Cu(II), Mn(II), Zn(II) and Pb(II), under pH and concentration conditions close to natural ones. The effects that these trace metals have on Sb(iii) oxidation by hydrogen peroxide vary. Zn(II) had no catalytic effect at all, but Cu(II), Mn(II) and Pb(II) did, though their effects were not uniform. Cu(II) significantly accelerated the reaction, which remained first-order with respect to Sb(III) at any Cu(II) concentration tested. Pb(II) and Mn(II) also enhanced the reaction rates, but the apparent order of the reaction with respect to Sb(III) changed to two. The trace metal effect observed was concentration dependent for Pb(II). The addition of the hydroxyl radical scavenger 2-propanol suggests that the trace metal catalytic effect observed involves the action of hydroxyl radicals, but that they are not responsible for the oxidation of Sb(III) by H2O2 in the absence of trace metals. The fact that Sb(III) can be oxidized by hydroxyl radicals present in water, even if it is not capable of producing them, has important environmental implications because hydroxyl radicals are known to be abundant in many natural waters such as seawater, humic-rich surface waters or rainwater.     

Bayesian entropy for spatial sampling design of environmental data

We develop a spatial statistical methodology to design national air pollution monitoring networks with good predictive capabilities while minimizing the cost of monitoring. The underlying complexity of atmospheric processes and the urgent need to give credible assessments of environmental risk create problems requiring new statistical methodologies to meet these challenges. In this work, we present a new method of ranking various subnetworks taking both the environmental cost and the statistical information into account. A Bayesian algorithm is introduced to obtain an optimal subnetwork using an entropy framework. The final network and accuracy of the spatial predictions is heavily dependent on the underlying model of spatial correlation. Usually the simplifying assumption of stationarity, in the sense that the spatial dependency structure does not change location, is made for spatial prediction. However, it is not uncommon to find spatial data that show strong signs of nonstationary behavior. We build upon an existing approach that creates a nonstationary covariance by a mixture of a family of stationary processes, and we propose a Bayesian method of estimating the associated parameters using the technique of Reversible Jump Markov Chain Monte Carlo. We apply these methods for spatial prediction and network design to ambient ozone data from a monitoring network in the eastern US.     

Use of alternating current for colored water purification by anodic oxidation with SS/PbO2 and Pb/PbO2 electrodes

Environmental Science and Pollution Research - This paper suggests a new alternative for the acceleration of dye removal by adopting alternating current instead of direct current in the treatment...     

Temperature enhanced effects of chlorine exposure on the health status of the sentinel organism Mytilus galloprovincialis

It now is widely recognised that the global temperature is rising, a phenomenon which could alter the effects of pollution on wildlife. In order to assess the role of temperature and exposure to chlorine due to cooling water discharges, a battery of metabolic, oxidative stress and histological parameters were evaluated in Mytilus galloprovincialis after 15 and 30 days at 15 °C and at two increased temperatures (+5 and +10 °C). Diverse gill pathologies such as haemolymphatic sinus dilatation, an increased number of mucocytes and granulocytes as well as a lower number of cilia were observed after 30 days exposure at higher temperatures. Protein, amino acid, triglyceride and fatty acid levels decreased when the temperature increased, as a consequence of higher energetic demand. Similarly, acetylcholinesterase, catalase and glutathione S-transferase activities showed an inhibition at higher temperatures, although gill lipid peroxidation levels remained unaffected. Our results suggest that increased temperatures induce deterioration in the health status of the mussels and in their defensive capacity against a polluted environment.     

Environmental pesticide distribution in horticultural and floricultural periurban production units

The environmental pesticide distribution on non-target systems (soil, drift and agricultural plastics) during the application step at small periurban production units, was studied in open field and greenhouses, for different crops (tomato, lettuce, broccoli, strawberry and flowers) using different pesticides (endosulfan, procymidone, chlorothalonil, chlorpyrifos and deltamethrin). In all cases, soil was the most exposed non-target system. For greenhouses, a general pesticide distribution was found of approximately 2/3 for crop, 1/4 for soil and 1/20 for plastic, of the total amount applied. In horticultural open fields, although the distribution was very dependent on the crop size and type, soil was also the most exposed non-target subsystem. Pesticide drift seems not to be significant in these production units, whilst pesticide accumulation on agricultural plastics reached up to 45% of the total applied, for polyethylene mulching in strawberry fields.     

The microbiota of an unpolluted calcareous soil faces up chlorophenols: Evidences of resistant strains with potential for bioremediation

To highlight the effects of a variety of chlorophenols (CP) in relation to the response of an indigenous bacterial community, an agricultural Mediterranean calcareous soil has been studied in microcosms incubated under controlled laboratory conditions. Soil samples were artificially polluted with 2-monochlorophenol (MCP), 2,4,6-trichlorophenol (TCP) and pentachlorophenol (PCP), at concentrations ranging from 0.1 up to 5000 mg kg⁻¹. Both activity and composition of the microbial community were assessed during several weeks, respectively, by respirometric methods and PCR-DGGE analysis of extracted DNA and RNA. Significant decreases in soil respirometric values and changes in the bacterial community composition were observed at concentrations above 1000 mg kg⁻¹ MCP and TCP, and above 100 mg kg⁻¹ PCP. However, the persistence of several active bacterial populations in soil microcosms contaminated with high concentration of CP, as indicated by DGGE fingerprints, suggested the capacity of these native bacteria to survive in the presence of the pollutants, even without a previous adaptation or contact with them.The isolation of potential CP degraders was attempted by culture plating from microcosms incubated with high CP concentrations. Twenty-three different isolates were screened for their resistance to TCP and PCP. The most resistant isolates were identified as Kocuria palustris, Lysobacter gummosus, Bacillus sp. and Pseudomonas putida, according to 16S rRNA gene homology. In addition, these four isolates also showed the capacity to reduce the concentration of TCP and PCP from 15% to 30% after 5 d of incubation in laboratory assays (initial pollutant concentration of 50 mg L⁻¹). Isolate ITP29, which could be a novel species of Bacillus, has been revealed as the first known member in this bacterial group with potential for CP bioremediation applications, usually wide-spread in the soil natural communities, which has not been reported to date as a CP degrader.     

Removal of imidazolium- and pyridinium-based ionic liquids by Fenton oxidation

The oxidation of imidazolium (1-hexyl-3-methylimidazolium chloride, HmimCl) and pyridinium (1-butyl-4-methylpyridinium chloride, BmpyrCl) ionic liquids (ILs) by Fenton’s reagent has been studied. Complete conversion was achieved for both ILs using the stoichiometric H₂O₂ dose at 70 °C, reaching final TOC conversion values around 45 and 55% for HmimCl and BmpyrCl, respectively. The decrease in hydrogen peroxide dose to substoichiometric concentrations (20–80% stoichiometric dose) caused a decrease in TOC conversion and COD removal and the appearance of hydroxylated oxidation by-products. Working at these substoichiometric H₂O₂ doses allowed the depiction of a possible degradation pathway for the oxidation of both imidazolium and pyridinium ILs. The first step of the oxidation process consisted in the hydroxylation of the ionic liquid by the attack of the ·OH radicals, followed by the ring-opening and the formation of short-chain organic acids, which could be partially oxidized up to CO₂ and H₂O. At H₂O₂ doses near stoichiometric values (80%), the resulting effluents showed non-ecotoxic behaviour and more biodegradable character (BOD₅/COD ratio around 0.38 and 0.58 for HmimCl and BmpyrCl, respectively) due to the formation of short-chain organic acids.

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Characterization of urban solid waste in Chihuahua, Mexico

The characterization of urban solid waste generation is fundamental for adequate decision making in the management strategy of urban solid waste in a city. The objective of this study is to characterize the waste generated in the households of Chihuahua city, and to compare the results obtained in areas of the city with three different socioeconomic levels. In order to identify the different socioeconomic trends in waste generation and characterization, 560 samples of solid waste were collected during 1 week from 80 households in Chihuahua and were hand sorted and classified into 15 weighted fractions. The average waste generation in Chihuahua calculated in this study was 0.676 kg per capita per day in April 2006. The main fractions were: organic (48%), paper (16%) and plastic (12%). Results show an increased waste generation associated with the socioeconomic level. The characterization in amount and composition of urban waste is the first step needed for the successful implementation of an integral waste management system.     

Phytotoxicity,cytotoxicity, and in vivo antifungal efficacy of chitosan nanobiocomposites on prokaryotic and eukaryotic cells

Environmental Science and Pollution Research - Chitosan (CS) nanosystems have potential applications for the control of microorganisms in the medical, environmental, and agrifood fields. In vivo...