Simulation of a 100-MW solar-powered thermo-chemical air separation system combined with an oxy-fuel power plant for bio-energy with carbon capture and storage (BECCS)

The combination of concentrated solar power–chemical looping air separation (CSP-CLAS) with an oxy-fuel combustion process for carbon dioxide (CO₂) capture is a novel system to generate electricity from solar power and biomass while being able to store solar power efficiently. In this study, the computer program Advanced System for Process Engineering Plus (ASPEN Plus) was used to develop models to assess the process performance of such a process with manganese (Mn)-based oxygen carriers on alumina (Al₂O₃) support for a location in the region of Seville in Spain, using real solar beam irradiance and electricity demand data. It was shown that the utilisation of olive tree prunings (Olea europaea) as the fuel—an agricultural residue produced locally—results in negative CO₂ emissions (a net removal of CO₂ from the atmosphere). Furthermore, it was found that the process with an annual average electricity output of 18 MW would utilise 2.43% of Andalusia’s olive tree prunings, thereby capturing 260.5 k-tonnes of CO₂, annually. Drawbacks of the system are its relatively high complexity, a significant energy penalty in the CLAS process associated with the steam requirements for the loop-seal fluidisation, and the gas storage requirements. Nevertheless, the utilisation of agricultural residues is highly promising, and given the large quantities produced globally (~?4 billion tonnes/year), it is suggested that other novel processes tailored to these fuels should be investigated, under consideration of a future price on CO₂ emissions, integration potential with a likely electricity grid system, and based on the local conditions and real data.

     

Analysing the sensitivity behaviour of two hydrology models

Recently, the New Morris Method has been presented as an effective sensitivity analysis tool for mathematical models. The New Morris Method estimates the sensitivity of an output parameter to a given set of input parameters (first-order effects) and the extent these parameters interact with each other (second-order effects). This method requires the specification of two parameters (runs and resolution) that control the sampling of the output parameter to determine its sensitivity to various inputs. The criteria for these parameters have been set on the analysis of a well-behaved analytical function (see Cropp and Braddock, Reliab. Eng. Syst. Saf. 78:77–83, 2002), which may not be applicable to other physical models that describe complex processes. This paper will investigate the appropriateness of the criteria from (Cropp and Braddock, 2002) and hence the effectiveness of the New Morris Method to determine the sensitivity behaviour of two hydrologic models: the Soil Erosion and Deposition System and Griffith University Representation of Urban Hydrology. In the first case, this paper will separately analyse the sensitivity of an output parameter on a set of input parameters (first- and second-order effects) for each model and discuss the physical meaning of these sensitivities. This will be followed by an investigation into the sampling criteria by exploring the convergence of the sensitivity behaviour for each model as the sampling of the parameter space is increased. By comparing these trends to the convergence behaviour from Cropp and Braddock (2002), we will determine how well the New Morris Method estimates the sensitivity for each model and whether the sampling criteria are appropriate for these models. It will be shown that the New Morris Method can provide additional insight into the functioning of these models, and that, under a different metric, the sensitivity behaviour of these models does converge confirming the sampling criteria set by Cropp and Braddock.     

Environmental quality control and environmental games

Conclusion  In this paper we have considered a specific environmental game emphasizing both control-prevention efforts and the propensity to pollute by a firm which adopts a given pollution abatement technology. A random payoff game was constructed and solved under a risk neutral assumption and quadratic utilities for both the firm and the environmental controller. The game thus defined, provides a wide range of interpretations and potential approaches for selecting a control-inspection policies to prevent environmental risks. There are of course many facets to this problem, which could be considered and have not been considered in sufficient depth. For example, more complex control mechanisms and liabilities, the effects of insurance and risk sharing, the application of cooperative efforts and subvention of pollution abatement investments (through tax incentives and their like), etc. have not been considered [5,7]. These are topics for further research. The basic presumption of this paper is that it is very difficult to fully enforce pollution prevention by firms, as a result, some controls are needed to ensure that firms be controlled so that appropriate efforts are carried.     

Examples of the role of analytical chemistry in environmental risk management research

Analytical chemistry is an important tier of environmental protection and has been traditionally linked to compliance and/or exposure monitoring activities for environmental contaminants. The adoption of the risk management paradigm has led to special challenges for analytical chemistry applied to environmental risk analysis. Namely, methods developed for regulated contaminants may not be appropriate and/or applicable to risk management scenarios. This paper contains examples of analytical chemistry applied to risk management challenges broken down by the analytical approach and analyte for some selected work in our laboratory. Specific techniques discussed include stable association complex electrospray mass spectrometry (cESI-MS), gas chromatography-mass spectrometry (GC-MS), split-flow thin cell (SPLITT) fractionation and matrix-assisted laser desorption time of flight mass spectrometry (MALDI-ToF-MS). Specific analytes include haloacetic acids (HAA9), perchlorate, bromate, triazine degradation products, metal-contaminated colloids and Cryptosporidium parvum oocysts.     

a study of the temporal variability of atrazine in private well water. part ii: analysis of data

In 1988, the Iowa Department of Natural Resources, along withthe University of Iowa, conducted the Statewide Rural WellWater Survey, commonly known as SWRL. A total of 686private rural drinking water wells was selected by use of aprobability sample and tested for pesticides and nitrate. A subsetof these wells, the 10% repeat wells, were additionally sampledin October, 1990 and June, 1991. Starting in November, 1991,the University of Iowa, with sponsorship from the United StatesEnvironmental Protection Agency, revisited the 10% repeat wellsto begin a study of the temporal variability of atrazine and nitratein wells. Other wells, which had originally tested positive foratrazine in SWRL but were not in the 10% population, wereadded to the study population. Temporal sampling for a year-long period began in February of 1992 and concluded in Januaryof 1993. All wells were sampled monthly, a subset was sampledweekly, and a second subset was sampled for 14 day consecutiveperiods. Of the 67 wells in the 10% population tested monthly,7 (10.4%) tested positive for atrazine at least once during theyear, and 3 (4%) were positive each of the 12 months. Theaverage concentration in the 7 wells was 0.10 µg/L. Fornitrate, 15 (22%) wells in the 10% repeat population monthlysampling were above the Maximum Contaminant Level of 10 mg/L at least once. This paper, the second of two papers on thisstudy, describes the analysis of data from the survey. The firstpaper (Lorber et al., 1997) reviews the study design, theanalytical methodologies, and development of the data base.     

Integrating disciplinary research into an interdisciplinary framework: A case study in sustainability research

The complexity of today’s research problems increasingly demands that scientists move beyond the confines of their own discipline. In this special issue, the basics of a transdisciplinary framework are established and problems analyzed in a specific discipline are successfully integrated in this transdisciplinary network. The intent has been to go beyond only statements about the importance of enabling early stage researchers to work across disciplinary boundaries, and to show that important discoveries are being made at the intersection of disciplines. Embedding various research projects in a more global framework can meet the demands of an interdisciplinary or transdisciplinary approach (especially for early stage researchers) and contribute significantly to sustainable research.     

A study on the orbit of air temperature movement

In this paper, we describe an air temperature movement by mapping its time series to the polar coordinates: the value of the time series is plotted on the radial coordinate and the time on the angular coordinate. In this way, both the yearly and daily air temperature movements from five different locations of China are used to demonstrate that, in an intuitionistic view, air temperature movement is neither random nor chaotic, but has its own orbit. We then propose an elliptic orbit model for the air temperature movement. Our proposed model provides quite good results when it is applied to the evaluation of yearly air temperature movements in eight locations in various parts of the world, and the evaluation of daily air temperature movements in five locations in Hunan Province of China on December 17, 2005. Results show that our approach provides a concise and helpful model for air temperature analysis.     

Assessing land use impacts on flood processes in complex terrain by using GIS and modeling approach

A distributed hydrologic modeling and GIS approach is applied for the assessment of land use impact in the Steinsel sub-basin, Alzette, Grand-Duchy of Luxembourg. The assessment focuses on the runoff contributions from different land use classes and the potential impact of land use changes on runoff generation. The results show that the direct runoff from urban areas is dominant for a flood event compared with runoff from other land use areas in this catchment, and tends to increase for small floods and for the dry season floods, whereas the interflow from forested, pasture and agricultural field areas contributes to the recession flow. Significant variations in flood volume, peak discharge, time to the peak, etc., are found from the model simulation based on the three hypothetical land use change scenarios.     

Application of a checklist for quality assistance in environmental modelling to an energy model

Large, complex energy models present considerable challenges to develop and test. Uncertainty assessments of such models provide only partial guidance on the quality of the results. We have developed a model quality assistance checklist to aid in this purpose. The model checklist provides diagnostic output in the form of a set of pitfalls for the model application. The checklist is applied here to an energy model for the problem of assessing energy use and greenhouse gas emissions. Use of the checklist suggests that results on this issue are contingent on a number of assumptions that are highly value-laden. When these assumptions are held fixed, the model is deemed capable of producing moderately robust results of relevance to climate policy over the longer term. Checklist responses also indicate that a number of details critical to policy choices or outcomes on this issue are not captured in the model, and model results should therefore be supplemented with alternative analyses.     

Using Multiple Antibiotic Resistance and land use characteristics to determine sources of fecal coliform bacterial pollution

Multiple Antibiotic Resistance (MAR) analysis and regression modeling techniques were used to identify surface water areas impacted by fecal pollution from human sources, and to determine the effects of land use on fecal pollution in Murrells Inlet, a small, urbanized, high-salinity estuary located between Myrtle Beach and Georgetown, South Carolina. MAR analysis was performed to identify areas in the estuary that are impacted by human-source fecal pollution. Additionally, regression analysis was performed to determine if an association exists between land use and fecal coliform densities over the ten-year period from 1989 to 1998. Land-use variables were derived using Geographic Information System (GIS) techniques and were used in the regression analysis.MAR analyses were conducted by comparing the frequency and patterns of antibiotic resistance found in Escherichia coli isolates derived from surface water samples and from sewage sources in the Murrells Inlet sewage collection system. The MAR results suggest that the majority of the fecal pollution detected in the Murrells Inlet estuary may be from non-human sources, including fecal coliforms isolated from areas in close proximity to high densities of active septic tanks.A MAR Index, which measures the frequency of antibiotic resistance, was calculated for each of twenty-three water samples and nine sewage samples. The antibiotic resistance pattern comparisons were performed using cluster analysis. Although the MAR indices indicated that several surface water sites had potential human-source contamination, the cluster analysis suggests that only one sampling site had MAR patterns that were similar to those found in the sewage samples. This site was in close proximity to several large pleasure boats as well as a sewage collection system lift station, but was not near areas with active septic tanks. The results of the regression analysis also suggest that sewage sources and rainfall runoff from urbanized areas may contribute to fecal pollution in the estuary.