Chemical solutions for greywater recycling

Greywater recycling is now accepted as a sustainable solution to the general increase of the fresh water demand, water shortages and for environment protection. However, the majority of the suggested treatments are biological and such technologies can be affected, especially at small scale, by the variability in strength and flow of the greywater and potential shock loading. This investigation presents the study of alternative processes, coagulation and magnetic ion exchange resin, for the treatment of greywater for reuse. The potential of these processes as well as the influence of parameters such as coagulant or resin dose, pH or contact time were investigated for the treatment of two greywaters of low and high organic strengths. The results obtained revealed that magnetic ion exchange resin and coagulation were suitable treatment solutions for low strength greywater sources. However, they were unable to achieve the required level of treatment for the reuse of medium to high strength greywaters. Consequently, these processes could only be considered as an option for greywater recycling in specific conditions that is to say in case of low organic strength greywater or less stringent standards for reuse.     

Fine particulate matter emissions inventories: comparisons of emissions estimates with observations from recent field programs

Emissions inventories of fine particulate matter (PM2.5) were compared with estimates of emissions based on data emerging from U.S. Environment Protection Agency Particulate Matter Supersites and other field programs. Six source categories for PM2.5 emissions were reviewed: on-road mobile sources, nonroad mobile sources, cooking, biomass combustion, fugitive dust, and stationary sources. Ammonia emissions from all of the source categories were also examined. Regional emissions inventories of PM in the exhaust from on-road and nonroad sources were generally consistent with ambient observations, though uncertainties in some emission factors were twice as large as the emission factors. In contrast, emissions inventories of road dust were up to an order of magnitude larger than ambient observations, and estimated brake wear and tire dust emissions were half as large as ambient observations in urban areas. Although comprehensive nationwide emissions inventories of PM2.5 from cooking sources and biomass burning are not yet available, observational data in urban areas suggest that cooking sources account for approximately 5-20% of total primary emissions (excluding dust), and biomass burning sources are highly dependent on region. Finally, relatively few observational data were available to assess the accuracy of emission estimates for stationary sources. Overall, the uncertainties in primary emissions for PM2.s are substantial. Similar uncertainties exist for ammonia emissions. Because of these uncertainties, the design of PM2.5 control strategies should be based on inventories that have been refined by a combination of bottom-up and top-down methods.     

A sensitive and robust method for the determination of alkylphenol polyethoxylates and their carboxylic acids and their transformation in a trickling filter wastewater treatment plant

This paper presents a method for the determination of alkylphenols, alkylphenol polyethoxylates (APEO) and alkylphenol ethoxycarboxylates (APEC) in the aqueous and particulate phase of wastewater samples. Quantification was achieved by liquid chromatography-tandem mass spectrometry. The sensitivity of the method is demonstrated by low detection limits, in the dissolved phase 1.2-9.6ngl(-1) for alkylphenol, AP(1-3)EO and APEC and 0.1-4.1ngl(-1) for longer chain alkylphenol polyethoxylates. The method detection limit for particulate phase samples ranged from 6 to 60ngg(-1) for AP, AP(1-3)EO and APEC; with the longer chain APEO being from 0.5 to 20ngg(-1). Matrix effects were noted in complex matrix rich samples. There was a distinct change in the distribution of alkylphenol ethoxylates during biological treatment of the wastewater, with the major biotransformation products observed being carboxylated derivatives at concentrations of up to 1768ngl(-1). Shorter chain APEO were present in higher proportions in the suspended solids, due to their higher affinity to particulate matter compared to the long-chain oligomers.     

Quantifying species recovery and conservation success to develop an IUCN Green List of Species

Stopping declines in biodiversity is critically important, but it is only a first step toward achieving more ambitious conservation goals. The absence of an objective and practical definition of species recovery that is applicable across taxonomic groups leads to inconsistent targets in recovery plans and frustrates reporting and maximization of conservation impact. We devised a framework for comprehensively assessing species recovery and conservation success. We propose a definition of a fully recovered species that emphasizes viability, ecological functionality, and representation; and use counterfactual approaches to quantify degree of recovery. This allowed us to calculate a set of 4 conservation metrics that demonstrate impacts of conservation efforts to date (conservation legacy); identify dependence of a species on conservation actions (conservation dependence); quantify expected gains resulting from conservation action in the medium term (conservation gain); and specify requirements to achieve maximum plausible recovery over the long term (recovery potential). These metrics can incentivize the establishment and achievement of ambitious conservation targets. We illustrate their use by applying the framework to a vertebrate, an invertebrate, and a woody and an herbaceous plant. Our approach is a preliminary framework for an International Union for Conservation of Nature (IUCN) Green List of Species, which was mandated by a resolution of IUCN members in 2012. Although there are several challenges in applying our proposed framework to a wide range of species, we believe its further development, implementation, and integration with the IUCN Red List of Threatened Species will help catalyze a positive and ambitious vision for conservation that will drive sustained conservation action.     

Simulation of herbicide impacts on a plant community: comparing model predictions of the plant community model IBC-grass to empirical data

Background

Semi-natural plant communities such as field boundaries play an important ecological role in agricultural landscapes, e.g., provision of refuge for plant and other species, food web support or habitat connectivity. To prevent undesired effects of herbicide applications on these communities and their structure, the registration and application are regulated by risk assessment schemes in many industrialized countries. Standardized individual-level greenhouse experiments are conducted on a selection of crop and wild plant species to characterize the effects of herbicide loads potentially reaching off-field areas on non-target plants. Uncertainties regarding the protectiveness of such approaches to risk assessment might be addressed by assessment factors that are often under discussion. As an alternative approach, plant community models can be used to predict potential effects on plant communities of interest based on extrapolation of the individual-level effects measured in the standardized greenhouse experiments. In this study, we analyzed the reliability and adequacy of the plant community model IBC-grass (individual-based plant community model for grasslands) by comparing model predictions with empirically measured effects at the plant community level.

Results

We showed that the effects predicted by the model IBC-grass were in accordance with the empirical data. Based on the species-specific dose responses (calculated from empirical effects in monocultures measured 4 weeks after application), the model was able to realistically predict short-term herbicide impacts on communities when compared to empirical data.

Conclusion

The results presented in this study demonstrate an approach how the current standard greenhouse experiments—measuring herbicide impacts on individual-level—can be coupled with the model IBC-grass to estimate effects on plant community level. In this way, it can be used as a tool in ecological risk assessment.

     

Assessment of the effects of urbanization on trace elements of toe bones

Amphibians, particularly frogs and toads, are increasingly used as bioindicators of contaminant accumulation in pollution studies. We developed an analytical technique to analyse their elemental contents based on a small amount of toe bone samples. This method is environment-friendly as, unlike traditional methods, it is not necessary to kill animals during sampling. Using this technique, we explored the effects of urbanization on the elemental contents of toe bones. Bufo bufo specimens were collected from an urban and two rural ponds. The ratios of Ca and P at the ponds were: 20.5% Ca and 14.6% P at the urban pond and 30.4% and 29.6% Ca, 22.4% and 21.7% P at the rural ponds, respectively. For the other elements, the following percentage ratios were found: 0.7% B, 0.3% Mg and 0.06% Zn at the urban pond and 1.1% and 0.4% B, 0.4% Mg and 0.05% Zn at the rural ponds, respectively. Canonical discriminant analysis indicated the separation of the urban and the rural ponds based on the elemental concentrations of toe bones. Significant differences were found between the concentrations of Ca, P, Mg, B and Zn at the urban and the rural ponds (p?相似文献   

Conservation decision-making in large state spaces

When looking for the best course of management decisions to efficiently conserve metapopulation systems, a classic approach in the ecology literature is to model the optimisation problem as a Markov decision process and find an optimal control policy using exact stochastic dynamic programming techniques. Stochastic dynamic programming is an iterative procedure that seeks to optimise a value function at each timestep by evaluating the benefits of each of the actions in each state of the system defined in the Markov decision process.Although stochastic dynamic programming methods provide an optimal solution to conservation management questions in a stochastic world, their applicability in metapopulation problems has always been limited by the so-called curse of dimensionality. The curse of dimensionality is the problem that adding new state variables inevitably results in much larger (often exponential) increases in the size of the state space, which can make solving superficially small problems impossible. The high computational requirements of stochastic dynamic programming methods mean that only simple metapopulation management problems can be analysed. In this paper we overcome the complexity burden of exact stochastic dynamic programming methods and present the benefits of an on-line sparse sampling algorithm proposed by Kearns, Mansour and Ng (2002). The algorithm is particularly attractive for problems with large state spaces as the running time is independent of the size of the state space of the problem. This appealing improvement is achieved at a cost: the solutions found are no longer guaranteed to be optimal.We apply the algorithm of Kearns et al. (2002) to a hypothetical fish metapopulation problem where the management objective is to maximise the number of occupied patches over the management time horizon. Our model has multiple management options to combat the threats of water abstraction and waterhole sedimentation. We compare the performance of the optimal solution to the results of the on-line sparse sampling algorithm for a simple 3-waterhole case. We find that three look-ahead steps minimises the error between the optimal solution and the approximation algorithm. This paper introduces a new algorithm to conservation management that provides a way to avoid the effects of the curse of dimensionality. The work has the potential to allow us to approximate solutions to much more complex metapopulation management problems in the future.