A stochastic model for colloid transport and deposition

Profiles of retained colloids in porous media have frequently been observed to be hyper-exponential or non-monotonic with transport depth under unfavorable attachment conditions, whereas filtration theory predicts an exponential profile. In this work we present a stochastic model for colloid transport and deposition that allows various hypotheses for such deviations to be tested. The model is based on the conventional advective dispersion equation that accounts for first-order kinetic deposition and release of colloids. One or two stochastic parameters can be considered in this model, including the deposition coefficient, the release coefficient, and the average pore water velocity. In the case of one stochastic parameter, the probability density function (PDF) is characterized using log-normal, bimodal log-normal, or a simple two species/region formulation. When two stochastic parameters are considered, then a joint log-normal PDF is employed. Simulation results indicated that variations in the deposition coefficient and the average pore water velocity can both produce hyper-exponential deposition profiles. Bimodal formulations for the PDF were also able to produce hyper-exponential profiles, but with much lower variances in the deposition coefficient. The shape of the deposition profile was found to be very sensitive to the correlation of deposition and release coefficients, and to the correlation of pore water velocity and deposition coefficient. Application of the developed stochastic model to a particular set of colloid transport and deposition data indicated that chemical heterogeneity of the colloid population could not fully explain the observed behavior. Alternative interpretations were therefore proposed based on variability of the pore size and the water velocity distributions.     

A screening model for fate and transport of biodegradable polyesters in soil

A numerical model for predicting the fate and transport of biodegradable polyester residues in soil, following successive applications of mulch film, was developed and applied. The polymer, applied on surface soil, was assumed to be converted into by-products (monomers), according to a first order kinetics with constant K(1deg). The monomers released were assumed to sorb on soil organic matter (according to a first-order kinetics with constant K(s)), to be leached with the seepage water, through vertical advection and hydrodynamic dispersion, and biodegraded (according to a first-order kinetics with constant K(b)). Results suggested that, to assess a possible build-up of mulch film (as a polymer) on the surface soil, the degradation constant K(1deg) relating the polymer conversion to by-products should be known, whereas the biodegradation constant K(b) indicates there is no danger of groundwater pollution. Likewise, on the basis of by-product concentration in deep soil, soil pollution should not occur.     

A two-dimensional model for simulating the transport and fate of toxic chemicals in a stratified reservoir

A two-dimensional reservoir toxics model is essential to establishing effective water resources management and protection. In a reservoir, the fate of a toxic chemical is closely connected with flow regimes and circulation patterns. To better understand the kinetic processes and persistence and predict the dissipation of toxic contaminants in the reservoir during a spill or storm runoff event, a toxics submodel was developed and incorporated into an existing laterally integrated hydrodynamics and transport model. The toxics submodel describes the physical, chemical, and biological processes and predicts unsteady vertical and longitudinal distributions of a toxic chemical. The two-dimensional toxicant simulation model was applied to Shasta Reservoir in California to simulate the physico-chemical processes and fate of a volatile toxic compound, methyl isothiocyanate (MITC), during a chemical spill into the Sacramento River in 1991. The predicted MITC concentrations were compared with those observed. The effect of reservoir flow regimes on the transport and fate of the toxic substance was investigated. The results suggested that the persistence of MITC is significantly influenced by different flow regimes. Methyl isothiocyanate is more persistent in the reservoir under an interflow condition due to reduced volatilization from deep layers than under an overflow condition. In the overflow situation, the plume moved more slowly toward the dam and experienced greater dissipation. This analysis can assist in toxic spill control and reservoir management, including field sampling and closure of water intakes.     

Virus retention and transport as influenced by different forms of soil organic matter

Organic materials are widespread in natural soil and aquatic environments. Their effect on virus transport is very important in assessing the risk for contamination of ground water by viruses. This study aimed to determine how different forms (mineral-associated and dissolved) of natural organic matter influence the retention and transport of two bacteriophages (MS-2 and phiX174) in two porous media (a sand and a soil). We found that mineral-associated organic matter significantly promoted the transport of one virus (MS-2) but not the other (phiX174) in a phosphate-buffered saline solution. Similarly, MS-2 was retained less in sand columns with increasing concentrations of dissolved humic acid, while little effect was observed for phiX174 under the same conditions. The two viruses have different surface properties and thus exhibited different reactivity to the metal oxides present on sand particles and were affected differently by organic matter. Because the organic matter used in the study was negatively charged and hydrophilic, blocking of virus sorption sites and increasing of virus-medium electrostatic repulsion arising from modification of the sand and virus surface by organic matter are probably responsible for the facilitated transport. For dissolved humic acid, its competition for sorption sites with viruses was an additional mechanism involved. This study suggests that the effect of organic matter varied depending on the organic material properties and the type of viruses involved. As a general trend, the effect of organic matter was dominated by electrostatic rather than hydrophobic interactions.     

Implications of cation exchange on clay release and colloid-facilitated transport in porous media

Column experiments were conducted to study chemical factors that influence the release of clay (kaolinite and quartz minerals) from saturated Ottawa sand of different sizes (710,360, and 240 microm). A relatively minor enhancement of clay release occurred when the pH was increased (5.8 to 10) or the ionic strength (IS) was decreased to deionized (DI) water. In contrast, clay release was dramatically enhanced when monovalent Na+ was exchanged for multivalent cations (e.g., Ca2+ and Mg2+) on the clay and sand and then the solution IS was reduced to DI water. This solution chemistry sequence decreased the adhesive force acting on the clay as a result of an increase in the magnitude of the clay and sand zeta potential with cation exchange, and expansion of the double layer thickness with a decrease in IS to DI water. The amount of clay release was directly dependent on the Na+ concentration of the exchanging solution and on the initial clay content of the sand (0.026-0.054% of the total mass). These results clearly demonstrated the importance of the order and magnitude of the solution chemistry sequence on clay release. Column results and scanning electron microscope (SEM) images also indicated that the clay was reversibly retained on the sand, despite predictions of irreversible interaction in the primary minimum. One plausible explanation is that adsorbed cations increased the separation distance between the clay-solid interfaces as a result of repulsive hydration forces. A cleaning procedure was subsequently developed to remove clay via cation exchange and IS reduction; SEM images demonstrated the effectiveness of this approach. The transport of Cu2+ was then shown to be dramatically enhanced by an order of magnitude in peak concentration by adsorption on clays that were released following cation exchange and IS reduction.     

Simulating endosulfan transport in runoff from cotton fields in Australia with the GLEAMS model

Endosulfan (6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro-6,9methano-2,4,3-benzodioxathiepin 3-oxide), a pesticide that is highly toxic to aquatic organisms, is widely used in the cotton (Gossypium hirsutum L.) industry in Australia and is a risk to the downstream riverine environment. We used the GLEAMS model to evaluate the effectiveness of a range of management scenarios aimed at minimizing endosulfan transport in runoff at the field scale. The field management scenarios simulated were (i) Conventional, bare soil at the beginning of the cotton season and seven irrigations per season; (ii) Improved Irrigation, irrigation amounts reduced and frequency increased to reduce runoff from excess irrigation; (iii) Dryland, no irrigation; (iv) Stubble Retained, increased soil cover created by retaining residue from the previous crop or a specially planted winter cover crop; and (v) Reduced Sprays, a fewer number of sprays. Stubble Retained was the most effective scenario for minimizing endosulfan transport because infiltration was increased and erosion reduced, and the stubble intercepted and neutralized a proportion of the applied endosulfan. Reducing excess irrigation reduced annual export rates by 80 to 90%, but transport in larger storm events was still high. Reducing the number of pesticide applications only reduced transport when three or fewer sprays were applied. We conclude that endosulfan transport from cotton farms can be minimized with a combination of field management practices that reduce excess irrigation and concentration of pesticide on the soil at any point in time; however, discharges, probably with endosulfan concentrations exceeding guideline values, will still occur in storm events.     

Dynamic temperature model for proton exchange membrane fuel cell using online variations in load current and ambient temperature

This paper presents a dynamic temperature model for a proton exchange membrane fuel cell (PEMFC) system. The proposed model overcomes the complexity of conventional models using first-order expressions consisting of load current and ambient temperature. The proposed model also incorporates a PEMFC cooling system, which depends upon the temperature difference between events. A dynamic algorithm is developed to detect load changing events and calculate instantaneous PEMFC temperature variations. The parameters of the model are extracted by employing the lightning search algorithm (LSA). The temperature characteristics of the NEXA 1.2 kW PEMFC system are experimentally studied to validate model performance. The results show that the proposed model output and the temperature data obtained from experiments for linear and abrupt changes in PEMFC load current are in agreement. The root-mean-square error between the model output and experimental results is less than 0.9. Moreover, the proposed model outperforms the conventional models and provides advantages such as simplicity and adaptability for low and high sampling data rates of input variables, namely, load current and ambient temperature. The model is not only helpful for simulations but also suitable for dynamic real-time controllers and emulators.     

A European model for waste and material flows

The use of materials and the generation of waste are linked to economic activities and in many projections these are assumed to be a constant ratio of the economic activities. This may be the case considering detailed economic activities and unchanged technology. However, the assumption of constant coefficients is questionable when linking material use and waste generation to aggregated economic activities. Therefore, in this paper, econometrics is used to test the assumption of constant waste coefficients empirically. The analyses show that an assumption of constant waste coefficients is not supported, generally, and a model allowing for trendwise changing coefficients is developed and used for projections of waste and material flows in 25 European countries.     

A multi-period optimization model for energy planning with CO2 emission consideration

A novel deterministic multi-period mixed-integer linear programming (MILP) model for the power generation planning of electric systems is described and evaluated in this paper. The model is developed with the objective of determining the optimal mix of energy supply sources and pollutant mitigation options that meet a specified electricity demand and CO₂ emission targets at minimum cost. Several time-dependent parameters are included in the model formulation; they include forecasted energy demand, fuel price variability, construction lead time, conservation initiatives, and increase in fixed operational and maintenance costs over time. The developed model is applied to two case studies. The objective of the case studies is to examine the economical, structural, and environmental effects that would result if the electricity sector was required to reduce its CO₂ emissions to a specified limit.     

A model recycling program for Alabama

Solid waste disposal is becoming a difficult problem for many states. Since 1960, the amount of municipal solid waste (MSW) has been increasing at a rate of 1% per year. More than 75% of the waste is comprised of recyclable materials. Several states have mandated recycling to decrease the volume of waste intended for disposal. Those mandated programs are very popular, but depend on many political, social, and economic factors for success. While Alabama has the manufacturing infrastructure to support a mandated recycling program, no recycling legislation has been promulgated. At this time recycling is only being done on a voluntary basis. A mandatory program with the proper support, education and funding could allow Alabama to recycle much of the 5.2 million tons of waste that are generated within its borders each year.     

An engineering-economic model of pipeline transport of CO2 with application to carbon capture and storage

Carbon dioxide capture and storage (CCS) involves the capture of CO₂ at a large industrial facility, such as a power plant, and its transport to a geological (or other) storage site where CO₂ is sequestered. Previous work has identified pipeline transport of liquid CO₂ as the most economical method of transport for large volumes of CO₂. However, there is little published work on the economics of CO₂ pipeline transport. The objective of this paper is to estimate total cost and the cost per tonne of transporting varying amounts of CO₂ over a range of distances for different regions of the continental United States. An engineering-economic model of pipeline CO₂ transport is developed for this purpose. The model incorporates a probabilistic analysis capability that can be used to quantify the sensitivity of transport cost to variability and uncertainty in the model input parameters. The results of a case study show a pipeline cost of US$ 1.16 per tonne of CO₂ transported for a 100 km pipeline constructed in the Midwest handling 5 million tonnes of CO₂ per year (the approximate output of an 800 MW coal-fired power plant with carbon capture). For the same set of assumptions, the cost of transport is US$ 0.39 per tonne lower in the Central US and US$ 0.20 per tonne higher in the Northeast US. Costs are sensitive to the design capacity of the pipeline and the pipeline length. For example, decreasing the design capacity of the Midwest US pipeline to 2 million tonnes per year increases the cost to US$ 2.23 per tonne of CO₂ for a 100 km pipeline, and US$ 4.06 per tonne CO₂ for a 200 km pipeline. An illustrative probabilistic analysis assigns uncertainty distributions to the pipeline capacity factor, pipeline inlet pressure, capital recovery factor, annual O&M cost, and escalation factors for capital cost components. The result indicates a 90% probability that the cost per tonne of CO₂ is between US$ 1.03 and US$ 2.63 per tonne of CO₂ transported in the Midwest US. In this case, the transport cost is shown to be most sensitive to the pipeline capacity factor and the capital recovery factor. The analytical model elaborated in this paper can be used to estimate pipeline costs for a broad range of potential CCS projects. It can also be used in conjunction with models producing more detailed estimates for specific projects, which requires substantially more information on site-specific factors affecting pipeline routing.     

A model for phosphorus transformation and runoff loss for surface-applied manures

Agricultural P transport in runoff is an environmental concern. An important source of P runoff is surface-applied, unincorporated manures, but computer models used to assess P transport do not adequately simulate P release and transport from surface manures. We developed a model to address this limitation. The model operates on a daily basis and simulates manure application to the soil surface, letting 60% of manure P infiltrate into soil if manure slurry with less than 15% solids is applied. The model divides manure P into four pools, water-extractable inorganic and organic P, and stable inorganic and organic P. The model simulates manure dry matter decomposition, and manure stable P transformation to water-extractable P. Manure dry matter and P are assimilated into soil to simulate bioturbation. Water-extractable P is leached from manure when it rains, and a portion of leached P can be transferred to surface runoff. Eighty percent of manure P leached into soil by rain remains in the top 2 cm, while 20% leaches deeper. This 2-cm soil layer contributes P to runoff via desorption. We used data from field studies in Texas, Pennsylvania, Georgia, and Arkansas to build and validate the model. Validation results show the model accurately predicted cumulative P loads in runoff, reflecting successful simulation of the dynamics of manure dry matter, manure and soil P pools, and storm-event runoff P concentrations. Predicted runoff P concentrations were significantly related to (r2=0.57) but slightly less than measured concentrations. Our model thus represents an important modification for field or watershed scale models that assess P loss from manured soils.     

Indicators for hydraulic and pollution retention assessment of stormwater infiltration basins

Infiltration basins are frequently used for stormwater management even though their long-term evolution is not well understood nor controlled. The two main problems encountered are clogging which compromises the hydraulic capacity of the basin and possible contamination of underlying soil and groundwater. This paper defines a framework for evaluating the hydraulic and pollution retention performance of infiltration basins in the long-term. Sets of context and performance indicators are proposed, along with two complementary modes of evaluation. Context indicators are identified in order to define the clogging and contamination states of the basins. Performance indicators are developed to assess several aspects of basin performance: drainage duration, overflow frequency, predictive life period, particle filtration and pollution trapping. Modes of evaluation include field investigation and long-term simulation modeling. Indicators are tested on five infiltration basins in suburban Lyon (France). Both context indicators and hydraulic performance indicators are reliable and their evaluation is representative of basin behavior. This is not the case for pollution retention performance indicators. Their assessment is difficult because of data quality. Field data has high uncertainties. The model is satisfactory for the hydraulic simulation and the evolution of clogging. Improvements are necessary for pollution flow simulation and the acquisition of better quality data is required.     

A formal model for consensus and negotiation in environmental management

Environmental management decisions typically lie at the interface of science and public policy. Consequently, these decisions involve a number of stakeholders with competing agendas and vested interests in the ultimate decision. In such cases, it is appropriate to adopt formal methods for consensus building to ensure transparent and repeatable decisions. In this paper, we use an environmental management case study to demonstrate the utility of a mathematical consensus convergence model in aggregating values (or weights) across groups. Consensus models are applicable when all parties agree to negotiate in order to resolve conflict. The advantage of this method is that it does not require that all members of the group reach agreement, often an impossible task in group decision making. Instead, it uses philosophical foundations in consensus building to aggregate group members' values in a way that guarantees convergence towards a single consensual value that summarizes the group position. We highlight current problems with ad hoc consensus and negotiation methods, provide justification for the adoption of formal consensus convergence models and compare the consensus convergence model with currently used methods for aggregating values across a group in a decision making context. The model provides a simple and transparent decision support tool for group decision making that is straightforward to implement.     

Best management practices for nutrient and sediment retention in urban stormwater runoff

Stormwater management infrastructure is utilized in urban areas to alleviate flooding caused by decreased landscape permeability from increased impervious surface cover (ISC) construction. In this study, we examined two types of stormwater detention basins, SDB-BMPs (stormwater detention basin-best management practice), and SDB-FCs (stormwater detention basin-flood control). Both are constructed to retain peak stormwater flows for flood mitigation. However, the SDB-BMPs are also designed using basin topography and wetland vegetation to provide water quality improvement (nutrient and sediment removal and retention). The objective of this study was to compare SDB (both SDB-BMP and SDB-FC) surface soil P concentrations, P saturation, and Fe chemistry with natural riparian wetlands (RWs), using sites in Fairfax County, Virginia as a model system. The SDB-BMPs had significantly greater surface soil total P (P(t)) concentrations than the RWs and SDB-FCs (831.9 +/- 32.5 kg ha(-1), 643.3 +/- 19.1 kg ha(-1), and 652.1 +/- 18.8 kg ha(-1), respectively). The soil P sorption capacities of SDB-BMPs were similar to the RWs, and were greater than those of SDB-FCs, appearing to result in greater soil P removal and retention in SDB-BMPs compared with SDB-FCs. Increased Fe concentrations and relatively greater amounts of more crystalline forms of Fe in SDB-BMP soils suggested increased sediment deposition compared with RW and SDB-FC soils. Data suggest that SDB nutrient and sediment retention is facilitated in SDB-BMPs. When stormwater management is necessary, use of SDB-BMPs instead of SDB-FCs could foster more responsible urban development and be an appropriate mitigation action for receiving aquatic ecosystems.     

A model for improving endangered species recovery programs

This paper discusses common organizational problems that cause inadequate planning and implementation processes of endangered species recovery across biologically dissimilar species. If these problems occur, even proven biological conservation techniques are jeopardized. We propose a solution that requires accountability in all phases of the restoration process and is based on cooperative input among government agencies, nongovernmental conservation organizations, and the academic community. The first step is formation of a task-oriented recovery team that integrates the best expertise into the planning process. This interdisciplinary team should be composed of people whose skills directly address issues critical for recovery. Once goals and procedures are established, the responsible agency (for example, in the United States, the US Fish and Wildlife Service) could divest some or all of its obligation for implementing the plan, yet still maintain oversight by holding implementing entities contractually accountable. Regular, periodic outside review and public documentation of the recovery team, lead agency, and the accomplishments of implementing bodies would permit evaluation necessary to improve performance. Increased cooperation among agency and nongovernmental organizations provided by this model promises a more efficient use of limited resources toward the conservation of biodiversity.     

A mathematical model for a hybrid anaerobic reactor

A mathematical model for a hybrid anaerobic reactor (HAR), which uses self-immobilized anaerobic bacterial granules under completely fluidized condition, has been developed. Stoichiometry of glucose fermentation into methane has been considered in this model. The model includes: (1) a biofilm model which describes substrate conversion kinetics within a single granule; (2) a bed fluidization model which describes the distribution of biogranules within the fluidized bed and (3) a reactor model which links the above two to predict the substrate and products concentration profile along the reactor height. Product and pH inhibition for each group of bacteria has been considered in the kinetic model. The spatial distribution of each group of anaerobic bacteria within granules has been found to play a vital role in bringing about the conversion. Experiments were conducted in the reactor using a synthetic effluent containing glucose as the carbon source to study the treatment efficiency. The model was simulated first assuming a 3-layered distribution [MacLeod, F.A., Guiot, S.R., Costerton, J.W., 1990. Layered structure of bacterial aggregates produced in an upflow anaerobic sludge bed and filter reactor. Applied and Environmental Microbiology 56, 1598-1607.] of anaerobic bacteria within granules and then homogeneous distribution [Grotenhuis, J.T.C., Smit, M., Plugge, C.M., Yuansheng, X., van Lammeren, A.A.M., Stams, A.J.M., Zehnder, A.J.B., 1991. Bacterial composition and structure of granular sludge adapted to different substrates. Applied and Environmental Microbiology 57, 1942-1949.] of anaerobic bacteria. The predictions of model simulation with the assumption of layered structure closely represented the experimental data.     

A model recycling process for low density polyethylene

A dissolution/reprecipitation process has been developed for recycling low density polyethylene. In this paper model experiments on virgin material, either in the form of pellets or film for greenhouses, are presented. It is proposed dissolution of the plastic in an appropriate solvent, reprecipitation by means of non-solvents, washing of the material obtained and drying. The solvent mixtures involved are separated by distillation for further reuse. Toluene/acetone proved to be the most satisfactory solvent/non-solvent system. The recycled material was evaluated in terms of the following properties: melt flow index (MFI), crystallinity, mechanical performance in tensile mode and grain size analysis.     

Local or global food markets: A comparison of energy use for transport

Abstract

This study compares energy use for food transport to a farmers' market in Sweden with energy use for transport in the conventional food system. The farmers' market was investigated through data sampling from on-site investigations. The conventional food system was studied with the aid of life cycle assessments reported in the literature. Overall, the study found no significant differences in levels of energy use for transport to the farmers' market compared with the conventional food system. For certain products, such as fresh fruits and vegetables, transport-related energy use was much lower in the local system although the season in Sweden for this kind of product is restricted to two or three months at the end of the summer. However, there is considerable potential to increase energy efficiency in local food systems by organizing the selling in new ways and by using more energy efficient vehicles.     

A spatial model approach for assessing windbreak growth and carbon stocks

Agroforestry, the deliberate integration of trees into agricultural operations, sequesters carbon (C) while providing valuable services on agricultural lands. However, methods to quantify present and projected C stocks in these open-grown woody systems are limited. As an initial step to address C accounting in agroforestry systems, a spatial Markov random field model for predicting the natural logarithm (log) of the mean aboveground volume of green ash ( Marsh.) within a shelterbelt, referred to as the log of aboveground volume, was developed using data from an earlier study and web-available soil and climate information. Windbreak characteristics, site, and climate variables were used to model the large-scale trend of the log of aboveground volume. The residuals from this initial model were correlated among sites up to 24 km from a point of interest. Therefore, a spatial dependence parameter was used to incorporate information from sites within 24 km into the prediction of the log of the aboveground volume. Age is an important windbreak characteristic in the model. Thus, the log of aboveground volume can be predicted for a given windbreak age and for values of other explanatory variables associated with a site of interest. Such predictions can be exponentiated to obtain predictions of aboveground volume for windbreaks without repeated inventory. With the capability of quantifying uncertainty, the model has the potential for large regional planning efforts and C stock assessments for many deciduous tree species used in windbreaks and riparian buffers once it is calibrated.