Stand-alone calculation tools are not the answer to embodied carbon assessment

Recent studies have shown that the importance of embodied carbon is growing in relation to assessing the environmental impact of buildings. This paper investigates how designers are looking to tackle this, and the effectiveness of some of the methods chosen. Although a number of commercial and non-commercial organisations are developing in-house tools to calculate embodied carbon, these lack the flexibility to be adopted by a wide range of users as well as the efficiency required to be appealing to designers at the early stages of a design. An alternative to these stand-alone tools is offered through the functionality of Building Information Modelling (BIM) software, which is capable of incorporating embodied carbon assessments as part of the normal design process. The potential of plug-in tools to obtain embodied carbon data from suppliers is an area that remains to be explored further.This is the final published article. It was originally published in Energy Procedia, Volume 62, 2014, Pages 150–159, DOI: 10.1016/j.egypro.2014.12.376

Decision support system for the long-term city metabolism planning problem

A Decision Support System (DSS) tool for the assessment of intervention strategies (Alternatives) in an Urban Water System (UWS) with an integral simulation model called “WaterMet²” is presented. The DSS permits the user to identify one or more optimal Alternatives over a fixed long-term planning horizon using performance metrics mapped to the TRUST sustainability criteria (Alegre et al., 2012). The DSS exposes lists of in-built intervention options and system performance metrics for the user to compose new Alternatives. The quantitative metrics are calculated by the WaterMet² model and further qualitative or user-defined metrics may be specified by the user or by external tools feeding into the DSS. A Multi-Criteria Decision Analysis (MCDA) approach is employed within the DSS to compare the defined Alternatives and to rank them with respect to a pre-specified weighting scheme for different Scenarios. Two rich, interactive Graphical User Interfaces, one desktop and one web-based, are employed to assist with guiding the end user through the stages of defining the problem, evaluating and ranking Alternatives. This mechanism provides a useful tool for decision makers to compare different strategies for the planning of UWS with respect to multiple Scenarios. The efficacy of the DSS is demonstrated on a northern European case study inspired by a real-life urban water system for a mixture of quantitative and qualitative criteria. The results demonstrate how the DSS, integrated with an UWS modelling approach, can be used to assist planners in meeting their long-term, strategic level sustainability objectives

Simulation modelling: Educational development roles for learning technologists

Simulation modelling was in the mainstream of CAL development in the 1980s when the late David Squires introduced this author to the Dynamic Modelling System. Since those early days, it seems that simulation modelling has drifted into a learning technology backwater to become a member of Laurillard's underutilized, ‘adaptive and productive’ media. Referring to her Conversational Framework, Laurillard constructs a pedagogic case for modelling as a productive student activity but provides few references to current practice and available resources. This paper seeks to complement her account by highlighting the pioneering initiatives of the Computers in the Curriculum Project and more recent developments in systems modelling within geographic and business education. The latter include improvements to system dynamics modelling programs such as STELLA®, the publication of introductory textbooks, and the emergence of online resources. The paper indicates several ways in which modelling activities may be approached and identifies some educational development roles for learning technologists. The paper concludes by advocating simulation modelling as an exemplary use of learning technologies ‐ one that realizes their creative‐transformative potential

Simulating the influences of groundwater on regional geomorphology using a distributed, dynamic, landscape evolution modelling platform

A dynamic landscape evolution modelling platform (CLiDE) is presented that allows a variety of Earth system interactions to be explored under differing environmental forcing factors. Representation of distributed surface and subsurface hydrology within CLiDE is suited to simulation at sub-annual to centennial time-scales. In this study the hydrological components of CLiDE are evaluated against analytical solutions and recorded datasets. The impact of differing groundwater regimes on sediment discharge is examined for a simple, idealised catchment, Sediment discharge is found to be a function of the evolving catchment morphology. Application of CLiDE to the upper Eden Valley catchment, UK, suggests the addition of baseflow-return from groundwater into the fluvial system modifies the total catchment sediment discharge and the spatio-temporal distribution of sediment fluxes during storm events. The occurrence of a storm following a period of appreciable antecedent rainfall is found to increase simulated sediment fluxes

Improving the multi-objective evolutionary optimization algorithm for hydropower reservoir operations in the California Oroville-Thermalito complex

This study demonstrates the application of an improved Evolutionary optimization Algorithm (EA), titled Multi-Objective Complex Evolution Global Optimization Method with Principal Component Analysis and Crowding Distance Operator (MOSPD), for the hydropower reservoir operation of the Oroville-Thermalito Complex (OTC) - a crucial head-water resource for the California State Water Project (SWP). In the OTC's water-hydropower joint management study, the nonlinearity of hydropower generation and the reservoir's water elevation-storage relationship are explicitly formulated by polynomial function in order to closely match realistic situations and reduce linearization approximation errors. Comparison among different curve-fitting methods is conducted to understand the impact of the simplification of reservoir topography. In the optimization algorithm development, techniques of crowding distance and principal component analysis are implemented to improve the diversity and convergence of the optimal solutions towards and along the Pareto optimal set in the objective space. A comparative evaluation among the new algorithm MOSPD, the original Multi-Objective Complex Evolution Global Optimization Method (MOCOM), the Multi-Objective Differential Evolution method (MODE), the Multi-Objective Genetic Algorithm (MOGA), the Multi-Objective Simulated Annealing approach (MOSA), and the Multi-Objective Particle Swarm Optimization scheme (MOPSO) is conducted using the benchmark functions. The results show that best the MOSPD algorithm demonstrated the best and most consistent performance when compared with other algorithms on the test problems. The newly developed algorithm (MOSPD) is further applied to the OTC reservoir releasing problem during the snow melting season in 1998 (wet year), 2000 (normal year) and 2001 (dry year), in which the more spreading and converged non-dominated solutions of MOSPD provide decision makers with better operational alternatives for effectively and efficiently managing the OTC reservoirs in response to the different climates, especially drought, which has become more and more severe and frequent in California

Review of trace toxic elements (Pb, Cd, Hg, As, Sb, Bi, Se, Te) and their deportment in gold processing. Part 1: Mineralogy, aqueous chemistry and toxicity

A literature review on the deportment of trace toxic elements (Pb, Cd, Hg, As, Sb, Bi, Se, and Te) in gold processing by cyanidation is presented which compiles the current knowledge in this area and highlights the gaps. This review, together with further research on the gaps in the thermodynamics and kinetics of these systems, aims to support the development of computer models to predict the chemical speciation and deportment of these elements through the various stages of the gold cyanidation process. The first part of this review is a collation of the relevant information on trace element mineralogy, aqueous chemistry and toxicity, together with a comparison of two available software packages (JESS and OLI) for thermodynamic modelling. Chemical speciation modelling can assist in understanding the chemistry of the trace toxic elements in gold cyanidation solutions which remains largely unexplored. Many significant differences exist between the predicted speciation of these trace elements for different types of modelling software due to differences in the thermodynamic data used, the paucity of data that exists under appropriate non-ideal conditions, and the methods used by the software packages to estimate thermodynamic parameters under these conditions. The toxicity and environmental guidelines of the chosen trace element species that exist in aqueous solutions are discussed to better understand the health and environmental risks associated with the presence of these elements in gold ores

Modelling manure NPK flows in organic farming systems to minimise nitrate leaching, ammonia volatilization and nitrous oxide emissions (OF0197)

Manure is an important source of organic matter and nutrients in organic farming systems, principally nitrogen (N), phosphorus (P) and potassium (K). Careful management is required during storage, handling and land-spreading to (a) ensure the most efficient use of the nutrients in the farming system and (b) to limit emissions of nitrate (NO3), ammonia (NH3), nitrous oxide (N2O), methane (CH4) and P to the wider environment. With a likely increase in the organically farmed area, information is needed on best practices for manure management in organic systems to minimise the environmental impacts of these systems. The aim was that software would calculate NPK fluxes associated with each aspect of the livestock system, and provide options to explore the impact of management change at key stages in the manure management process. The end point was to be a working prototype model/decision support system (DSS), which we could be demonstrated to a group of organic farmers and used for discussion of the NPK flows in their systems. Most of the effort in this short-term project was spent on three aspects: 1. Developing databases and the underlying model calculations. 2. Developing the software for the prototype system. 3. Limited validation of the output. The two main challenges in the project were (a) allowing a quick and easy representation of the manure management system, which is often complex and (b) being able to represent complex interactions, simply but robustly. The Manure Model (MANMOD) DSS was developed to allow an iconographic-based model representation of individual farm manure management systems to be readily constructed from a library of system components using a 'drag and drop' operation. This allows the user to construct a diagram of connecting components or ‘nodes’ (e.g. manure source, housing system, storage system) which direct and limit the flow pathway of nutrients through the farming system. Each component or node represents a key stage of the system. Once the system has been constructed, pressing the calculation button calculates the following variates for each component of the system: output (i.e. the amounts of N, P and K that will be transferred from that component of the system to the next); balance (i.e. the amount residing in that component of the system); losses (gaseous and ‘leachate’). Workshops were held at the start and end of the project. The following observations were made as a result of this exercise: - The approach is a relatively quick and simple way of constructing manure management systems. However, it is still quite complex, given the complexity of many management systems. - It may be that it is a better tool for advisers so that they can use it for several clients and become more familiar with the tool, compared with a farmer who might use it as a one-off during planning. - Even at its simplest, some detailed information is required – and in units that the farmer may not be familiar with. For example, washdown volume for the hardstanding, amount of straw (kg/animal/month), etc. However, this is not really a reason for not pursuing this information if it will provide an improvement in management. - One value is the option to scenario test. However, this is reliant on the model being sufficiently refined to be able to fairly represent the changes in response to the system. The aim of the project was to produce a prototype system. We have done this, but because of the complexity of the systems that we are trying to represent, we recognise that much more detailed validation of the model is required before it can be disseminated. There are now several Defra-funded studies that could be used in the next phase of the work. (A more detailed summary is available at the start of the main report

Data mining as a tool for environmental scientists

Over recent years a huge library of data mining algorithms has been developed to tackle a variety of problems in fields such as medical imaging and network traffic analysis. Many of these techniques are far more flexible than more classical modelling approaches and could be usefully applied to data-rich environmental problems. Certain techniques such as Artificial Neural Networks, Clustering, Case-Based Reasoning and more recently Bayesian Decision Networks have found application in environmental modelling while other methods, for example classification and association rule extraction, have not yet been taken up on any wide scale. We propose that these and other data mining techniques could be usefully applied to difficult problems in the field. This paper introduces several data mining concepts and briefly discusses their application to environmental modelling, where data may be sparse, incomplete, or heterogenous

Characterisation of the porous structure of Gilsocarbon graphite using pycnometry, cyclic porosimetry and void-network modeling

file: :C$$:/pdf/1-s2.0-S000862231400164X-main.pdf:pdfThe cores of the fourteen Advanced Gas-cooled nuclear Reactors (AGRs) within the UK comprise Gilsocarbon graphite, a manufactured material surrounded predominantly by CO2 at high pressure and temperature to provide heat exchange. The intense ionising radiation within the reactors causes radiolytic oxidation, and the resulting mass loss is a primary factor in determining reactor lifetime. The void structure of the porous Gilsocarbon graphite affects the permeability and diffusion of the carbon dioxide, and the sites of oxidation. To model this void structure, the porosities and densities of ten virgin Gilsocarbon graphite samples have been measured by powder and helium pycnometry. For comparison, results are also presented for highly ordered pyrolytic graphite (HOPG), and a fine-grained Ringsdorff graphite. Samples have been examined at a range of magnifications by electron microscopy. Total porosities and percolation characteristics have been measured by standard and cyclic mercury porosimetry up to an applied mercury pressure of 400MPa. Inverse modelling of the cyclic intrusion curves produces simulated void structures with characteristics which closely match those of experiment. Void size distributions of the structures are presented, together with much Supplementary Information. The simulated void networks provide the bases for future simulations of the radiolytic oxidation process itself