A Review on the Application of Natural Computing in Environmental Informatics

Natural computing offers new opportunities to understand, model and analyze the complexity of the physical and human-created environment. This paper examines the application of natural computing in environmental informatics, by investigating related work in this research field. Various nature-inspired techniques are presented, which have been employed to solve different relevant problems. Advantages and disadvantages of these techniques are discussed, together with analysis of how natural computing is generally used in environmental research.Comment: Proc. of EnviroInfo 201

Adaptive Neuro-Fuzzy Inference System for Waste Prediction

The volume of landfills that are increasingly piled up and not handled properly will have a negative impact, such as a decrease in public health. Therefore, predicting the volume of landfills with a high degree of accuracy is needed as a reference for government agencies and the community in making future policies. This study aims to analyze the accuracy of the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. The prediction results' accuracy level is measured by the value of the Mean Absolute Percentage Error (MAPE). The final results of this study were obtained from the best MAPE test results. The best predictive results for the ANFIS method were obtained by MAPE of 3.36% with a data ratio of 6:1 in the North Samarinda District. The study results show that the ANFIS algorithm can be used as an alternative forecasting method

Municipal solid waste management system: decision support through systems analysis

Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental EngineeringThe present study intends to show the development of systems analysis model applied to solid waste management system, applied into AMARSUL, a solid waste management system responsible for the management of municipal solid waste produced in Setúbal peninsula, Portugal. The model developed intended to promote sustainable decision making, covering the four columns: technical, environmental, economic and social aspects. To develop the model an intensive literature review have been conducted. To simplify the discussion, the spectrum of these systems engineering models and system assessment tools was divided into two broadly-based domains associated with fourteen categories although some of them may be intertwined with each other. The first domain comprises systems engineering models including cost-benefit analysis, forecasting analysis, simulation analysis, optimization analysis, and integrated modeling system whereas the second domain introduces system assessment tools including management information systems, scenario development, material flow analysis, life cycle assessment (LCA), risk assessment, environmental impact assessment, strategic environmental assessment, socio-economic assessment, and sustainable assessment. The literature performed have indicated that sustainable assessment models have been one of the most applied into solid waste management, being methods like LCA and optimization modeling (including multicriteria decision making(MCDM)) also important systems analysis methods. These were the methods (LCA and MCDM) applied to compose the system analysis model for solid waste. The life cycle assessment have been conducted based on ISO 14040 family of norms; for multicriteria decision making there is no procedure neither guidelines, being applied analytic hierarchy process (AHP) based Fuzzy Interval technique for order performance by similarity to ideal solution (TOPSIS). Multicriteria decision making have included several data from life cycle assessment to construct environmental, social and technical attributes, plus economic criteria obtained from collected data from stakeholders involved in the study. The results have shown that solutions including anaerobic digestion in mechanical biological treatment plant plus anaerobic digestion of biodegradable municipal waste from source separation, with energetic recovery of refuse derived fuel (RDF) and promoting pays-as-you-throw instrument to promote recycling targets compliance would be the best solutions to implement in AMARSUL system. The direct burning of high calorific fraction instead of RDF has not been advantageous considering all criteria, however, during LCA, the results were the reversal. Also it refers that aerobic mechanical biological treatment should be closed.Fundação para a Ciência e Tecnologia - SFRH/BD/27402/200

Results of application of modular artificial neural networks for intelligent data analysis (data mining) and forecasting processes in the field of ecology and environment protection

The aim of this work is the use of modular artificial neural networks (ANN) for data mining (Data Mining) and forecasting of various processes in the field of ecology and environmental protection, as well as the comparison of the results of the proposed model with the results of other data analysis methods (the methods of mathematical modeling and mathematical statistics).Метою даної роботи є використання модульних штучних нейронних мереж для виведення даних та прогнозування різних процесів у галузі екології та охорони навколишнього середовища, а також порівняння результатів запропонованої моделі з результатами інших методів аналізу даних (методи математичного моделювання та математичної статистики)

Hydrothermal processing of biogenic residues in Germany: A technology assessment considering development paths by 2030

The mining, processing, and use of finite natural resources is associated with significant interventions in the natural environment. Thus, these and other negative consequences make it necessary to reduce resource consumption. An important field of action is the more efficient use of biogenic residues as secondary raw materials. However, high water containing biomasses are still a problem since they need an energy- and cost-intensive pre-treatment for many conversion processes, which can make their use uneconomical. Hydrothermal processes (HTP) seem to be promising, since they require an aqueous environment for optimal processing anyway. Although technological progress within the industry is recognisable, however, to date HTP have not been established in industrial continuous operation in Germany. The core of this work is identifying reasons for this sluggish development and deriving appropriate recommendations for action. Based on the hypothesis that HTP can contribute to the efficient utilisation of biogenic residues in the future, potentials and obstacles for the development of HTP in Germany are identified using a literature review, expert survey, expert workshop, and SWOT analysis. To estimate the future potential of HTP in a systematic and structured way, a multi-criteria technology assessment approach is developed based on the results. To this end, assessment criteria for HTP are derived, weighted by expert judgment, and integrated into a transparent and structured procedure. In addition, mainly based on a Delphi-survey key factors of HTP development by 2030 in Germany are identified and three development alternatives for HTP in Germany by 2030 are derived. Using a system analysis and a comparative multi-criteria analysis at plant level, these scenarios are analysed for their possible future impact. Based on this methodology, the work shows that the production costs for the end products, the energy efficiency of the process, and the proportion of recycled phosphorus are of high relevance to the techno-economic success of HTP compared to reference systems, and they are therefore of high importance for its future development on the plant level. In addition, further key factors for the future development of HTP in Germany on the system level are found to be mainly in the political-legal (e.g. legal waste status of products from HTP) and techno-economic (e.g. cost-effective process water treatment) areas. According to this, important fields of action are the identification and use of cost reduction potentials (e.g. heat waste use), the development of system integrated decentralised plant concepts with integrated nutrient recycling (e.g. phosphorus), and the development of cost-effective ways to treat process water. System integration, cost-effective process water treatment, and nutrient recycling are all closely linked to production costs, investment costs, and potential revenues, and can contribute to improved process economics. For these areas, there is promising future potential to achieve higher competitiveness with reference technologies that are currently more economical.:Bibliographic description Curriculum Vitae Selbstständigkeitserklärung Danksagung List of Publications Contribution to the Publications Contents List of Acronyms List of Tables List of Figures Part I Introductory Chapters 1 Introduction and Background Hydrothermal processes: Introduction and status quo State of the art in the research field and knowledge gaps Objective and research framework Expected value added of this work 2 Materials and methods Derivation of HTP evaluation metrics and technology assessment tool Derivation of key HTP development factors and scenarios Performing the system-level scenario analysis Plant-level scenario analysis and test application of the assessment tool Derivation of core recommendations 3 Results and discussion Key development factors for HTP in Germany and scenarios System-level scenario analysis Test application of the assessment tool on plant level scenarios Recommendations Discussion 4 Conclusion and outlook Future research Further fields for the application of the developed methods 5 References Part II Appended Articles Paper I Paper II Paper III Paper IV Paper V Paper VIDer Abbau, die Verarbeitung und die Nutzung endlicher natürlicher Ressourcen sind mit erheblichen Eingriffen in die natürliche Umwelt verbunden. Diese und andere negative Folgen machen es daher erforderlich, den Ressourcenverbrauch zu senken. Ein wichtiges Handlungsfeld ist die effizientere Nutzung biogener Reststoffe als Sekundärrohstoffe. Stark wasserhaltige Biomassen sind jedoch ein Problem, da sie für viele Umwandlungsprozesse eine energie- und kostenintensive Vorbehandlung benötigen, was ihre Verwendung unwirtschaftlich machen kann. Hydrothermale Prozesse (HTP) scheinen für diese Reststoffe allerdings vielversprechend zu sein, da sie ohnehin eine wässrige Umgebung für eine optimale Verarbeitung benötigen. Obwohl der technologische Fortschritt innerhalb der Branche erkennbar ist, wurde HTP in Deutschland bisher nicht im industriellen Dauerbetrieb etabliert. Der Kern dieser Arbeit besteht darin, Gründe für diese schleppende Entwicklung zu ermitteln und geeignete Handlungsempfehlungen abzuleiten. Basierend auf der Hypothese, dass HTP in Zukunft zur effizienten Nutzung biogener Reststoffe beitragen können, werden Potenziale und Hindernisse für deren Entwicklung in Deutschland anhand einer Literaturrecherche, einer Expertenumfrage, eines Expertenworkshops und einer SWOT-Analyse ermittelt. Um das zukünftige Potenzial von HTP systematisch und strukturiert abzuschätzen, wird basierend auf den Ergebnissen ein multi-kriterieller Technologiebewertungsansatz entwickelt. Zu diesem Zweck werden Bewertungskriterien für HTP abgeleitet, nach Expertenmeinung gewichtet und in ein transparentes und strukturiertes Verfahren integriert. Darüber hinaus werden hauptsächlich auf der Grundlage einer Delphi-Umfrage Schlüsselfaktoren für die HTP-Entwicklung bis 2030 in Deutschland identifiziert und drei Entwicklungsalternativen für HTP in Deutschland bis 2030 abgeleitet. Mithilfe einer Systemanalyse und einer vergleichenden multi-kriteriellen Analyse auf Anlagenebene werden diese Szenarien auf ihre möglichen zukünftigen Auswirkungen hin analysiert. Basierend auf dieser Methodik zeigen sich als Ergebnisse, dass die Produktionskosten für die Endprodukte, die Energieeffizienz der Prozesse und der Anteil an recyceltem Phosphor für den techno-ökonomischen Erfolg von HTP im Vergleich zu Referenzsystemen von hoher Relevanz und daher auch von hoher Bedeutung für die zukünftige Entwicklung auf Anlagenebene sind. Darüber hinaus liegen weitere Schlüsselfaktoren für die künftige Entwicklung von HTP in Deutschland auf Systemebene hauptsächlich im politisch-rechtlichen (z. B. legalen Abfallstatus von Produkten aus HTP) und techno-ökonomischen (z. B. kostengünstige Prozesswasseraufbereitung)) Bereichen. Wichtige Handlungsfelder sind demnach die Ermittlung und Nutzung von Kostensenkungspotentialen (zB Abwärmenutzung), die Entwicklung systemintegrierter dezentraler Anlagenkonzepte mit integriertem Nährstoffrecycling (z.B. Phosphor) und die Entwicklung kostengünstiger Wege zur Prozesswasserbehandlung. Systemintegration, kostengünstige Prozesswasseraufbereitung und Nährstoffrecycling hängen eng mit Produktionskosten, Investitionskosten und potenziellen Einnahmen zusammen und können zu einer verbesserten Wirtschaftlichkeit der Prozesse beitragen. Für diese Bereiche besteht ein vielversprechendes Zukunftspotenzial für eine höhere Wettbewerbsfähigkeit zu Referenztechnologien, die derzeit noch wirtschaftlicher sind.:Bibliographic description Curriculum Vitae Selbstständigkeitserklärung Danksagung List of Publications Contribution to the Publications Contents List of Acronyms List of Tables List of Figures Part I Introductory Chapters 1 Introduction and Background Hydrothermal processes: Introduction and status quo State of the art in the research field and knowledge gaps Objective and research framework Expected value added of this work 2 Materials and methods Derivation of HTP evaluation metrics and technology assessment tool Derivation of key HTP development factors and scenarios Performing the system-level scenario analysis Plant-level scenario analysis and test application of the assessment tool Derivation of core recommendations 3 Results and discussion Key development factors for HTP in Germany and scenarios System-level scenario analysis Test application of the assessment tool on plant level scenarios Recommendations Discussion 4 Conclusion and outlook Future research Further fields for the application of the developed methods 5 References Part II Appended Articles Paper I Paper II Paper III Paper IV Paper V Paper V

System Dynamics Model For Hospital Waste Characterisation and Generation in Developing Countries.

Waste management policy makers always face the problem of how to predict the future amount and composition of medical solid waste, which in turn will help determine the most appropriate treatment, recycling and disposal strategy. An accurate prediction can assist in both the planning and design of medical solid waste management systems. Insufficient budget and unavailable management capacity are the main reasons for the scarcity of medical solid waste quantities and components historical records, which are so important in long-term system planning and short-term expansion programs. This paper presents a new technique, using system dynamics modelling, to predict generated medical solid waste in a developing urban area, based on a set of limited samples from Jenin District hospitals, Palestine. The findings of the model present the trend of medical solid waste generation together with its different components and indicate that a new forecasting approach may cover a variety of possible causative models and track inevitable uncertainties when traditional statistical least-squared regression methods are unable to handle such issues

Prediction of municipal solid waste generation : an investigation of the effect of clustering techniques and parameters on ANFIS model performance

Abstract: The present waste management system and facilities in most developing countries are insufficient to combat the challenge of increasing rate of solid waste generation. To achieve success in sustainable solid waste management, planning plays a crucial role. Accurate prediction of waste quantities generated will immensely help to overcome the challenge of deficient-planning of sustainable waste management. This challenge has necessitated the need for modelling approach. In modelling the complexity within a system, a paradigm-shift from classical-model to artificial intelligent model has been necessitated. Previous researches which used Adaptive Neuro-Fuzzy Inference System (ANFIS) for waste generation forecast did not investigate the effect of clustering-techniques and parameters on the performance of the model despite its significance in achieving accurate prediction. This study therefore investigates the impact of the parameters of three clustering-technique namely: Fuzzy c-means (FCM), Grid-Partitioning (GP) and Subtractive-Clustering (SC) on the performance of the ANFIS model in predicting waste generation using South Africa as a case study. Socio-economic and demographic provincial-data for the period 2008-2016 were used as input-variables and provincial waste quantities as output-variable. ANFIS model clustered with GP using triangular input membership-function (tri-MF) and a linear type output membership-function (ANFIS-GP1) is the optimal model with Mean Absolute Percentage Error (MAPE), Mean Absolute Deviation (MAD), Root Mean Square Error (RMSE) and Correlation Co-efficient (R2) values of 12.6727, 0.6940, 1.2372 and 0.9392 respectively. Based on the result in this study, ANFIS-GP with a triangular membership-function is recommended for modelling waste generation. The tool presented in this study can be utilized for the national repository of waste generation data by the South Africa Waste Information Centre (SAWIC) in South Africa and it is also applicable to waste-planners in developing countries for reliable and accurate prediction of annual waste generation

Systems Analysis For Urban Water Infrastructure Expansion With Global Change Impact Under Uncertainties

Over the past decades, cost-effectiveness principle or cost-benefit analysis has been employed oftentimes as a typical assessment tool for the expansion of drinking water utility. With changing public awareness of the inherent linkages between climate change, population growth and economic development, the addition of global change impact in the assessment regime has altered the landscape of traditional evaluation matrix. Nowadays, urban drinking water infrastructure requires careful long-term expansion planning to reduce the risk from global change impact with respect to greenhouse gas (GHG) emissions, economic boom and recession, as well as water demand variation associated with population growth and migration. Meanwhile, accurate prediction of municipal water demand is critically important to water utility in a fast growing urban region for the purpose of drinking water system planning, design and water utility asset management. A system analysis under global change impact due to the population dynamics, water resources conservation, and environmental management policies should be carried out to search for sustainable solutions temporally and spatially with different scales under uncertainties. This study is aimed to develop an innovative, interdisciplinary, and insightful modeling framework to deal with global change issues as a whole based on a real-world drinking water infrastructure system expansion program in Manatee County, Florida. Four intertwined components within the drinking water infrastructure system planning were investigated and integrated, which consists of water demand analysis, GHG emission potential, system optimization for infrastructure expansion, and nested minimax-regret (NMMR) decision analysis under uncertainties. In the water demand analysis, a new system dynamics model was developed to reflect the intrinsic relationship between water demand and changing socioeconomic iv environment. This system dynamics model is based on a coupled modeling structure that takes the interactions among economic and social dimensions into account offering a satisfactory platform. In the evaluation of GHG emission potential, a life cycle assessment (LCA) is conducted to estimate the carbon footprint for all expansion alternatives for water supply. The result of this LCA study provides an extra dimension for decision makers to extract more effective adaptation strategies. Both water demand forecasting and GHG emission potential were deemed as the input information for system optimization when all alternatives are taken into account simultaneously. In the system optimization for infrastructure expansion, a multiobjective optimization model was formulated for providing the multitemporal optimal facility expansion strategies. With the aid of a multi-stage planning methodology over the partitioned time horizon, such a systems analysis has resulted in a full-scale screening and sequencing with respect to multiple competing objectives across a suite of management strategies. In the decision analysis under uncertainty, such a system optimization model was further developed as a unique NMMR programming model due to the uncertainties imposed by the real-world problem. The proposed NMMR algorithm was successfully applied for solving the real-world problem with a limited scale for the purpose of demonstration