Seven Approaches to Manage Complex Coupled Human and Natural Systems: A Sustainability Toolbox

Monitoring sustainable waste management in OECD countries: A Malmquist productivity approach

Sustainable waste management (SWM) practices are crucial for tackling environmental concerns under a circular economy (CE) scope. Thirty-one OECD countries have been evaluated on their national SWM performance via Malmquist data envelopment analysis (DEA) methodology from 2000 to 2021. The Malmquist (MPI) and Malmquist-Luenberger (MLPI) productivity indices are compared based on their total factor productivity (TFP) and its elements (i.e., efficiency and technological changes). Both models have the gross domestic product (GDP) as a desirable output, but MLPI also incorporates municipal solid waste (MSW) generation and greenhouse gases (GHGs, i.e. CO2 and CH4) as undesirable outputs. MLPI has a lower average performance (1.74%) than MPI (4.42%), meaning that the incorporation of waste and GHGs has diminished an OECD country's SWM performance by 2.5 times on average. In essence, it is innovation that drives TFP in the selected countries. Overall, the synergistic implementation of SWM practices, Malmquist DEA-based methodology, and CE principles is crucial for advancing sustainable development and achieving a circular and resilient future. The manuscript also offers policy implications regarding the need of financial incentives, vocational training, and fostering stakeholder encouragement in the waste sectors to implement CE solutions.

Prioritizing the Best Potential Regions for Brine Concentration Systems in the USA Using GIS and Multicriteria Decision Analysis

We propose a methodology for identifying and prioritizing the best potential locations for brine concentration facilities in the contiguous United States. The methodology uses a geographic information system and multicriteria decision analysis (GIS-MCDA) to prioritize the potential locations for brine concentration facilities based on thermodynamic, economic, environmental, and social criteria. By integrating geospatial data with a computational simulation of a real brine concentration system, an objective weighting method identifies the weights for 13 subcriteria associated with the main criteria. When considering multiple dimensions for decision making, brine concentration facilities centered in Florida were consistently selected as the best location, due to the high second-law efficiency, low transportation cost, and high capacity for supplying municipal water needs to nearby populations. For inland locations, Southeast Texas outperforms all other locations for thermodynamic, economic, and environmental priority cases. A sensitivity analysis evaluates the consistency of the results as the priority of a main criterion varies relative to other decision-making criteria. Focusing on a single subcriterion misleads decision making when identifying the best location for brine concentration systems, identifying the importance of the multicriteria methodology.

Methodology for Determining Sustainable Water Consumption Indicators for Buildings

The objective of this study was the definition and determination of sustainable water consumption indicators for activity categories, as well as the evolution of water consumption in commercial buildings. These indicators were determined through statistical analyses using Shewhart charts. Within a broader scope, the research proposed a methodology to automate sustainable management of water consumption in building operation using BIM–IoT–FM integration. The scientific rigor of the methodology was based on the precepts of design science research. The methods proposed for the construction of functionalities and the application of the reference indicators provided an optimized analysis of water consumption and the detection of excess consumption and leaks. The methodology, implemented in an online prototype, AquaBIM, could deliver a significant advance for building management. A conceptual test of AquaBIM evaluated the consumption indicators and validated our methodology through its application in a commercial building. The building consumption analyses showed a potential for approximately 15% savings. In addition, five requirements of the international sustainability certification AQUAHQE were met. The results of our research provide an innovative approach for the automation of sustainable building management and could be expanded to monitor and report on the consumption of other critical resources such as electricity and gas.

Application of attached algae flow-ways for coupling biomass production with the utilization of dilute non-point source nutrients in the Upper Laguna Madre, TX

The purpose of this study is to determine the potential for an attached algae flow-way system to efficiently produce algal biomass in estuarine surface waters by utilizing dilute non-point source nutrients from local urban, industrial, and agricultural discharges into the Upper Laguna Madre, Corpus Christi, Texas. The study was conducted over the course of two years to establish seasonal base-line biomass productivity and composition for bioproducts applications, and to identify key environmental factors and flow-way cohorts impacting biomass production. For the entire cultivation period, continuous ash-free biomass production at 4 to 10 g/m²/day (corresponding to nutrient recovery at 300 to 500 mg of nitrogen/m²/day and 15 to 30 mg of phosphorus/m²/day) was successfully achieved without system restart. Upon start-up, a latency period was observed which indicates roles for species succession from relatively low productivity, high ash content pioneer periphytic culture composed primarily of benthic diatoms from the source waters to higher productivity, reduced ash content, and more resilient culture mainly composed of filamentous chlorophyta, Ulva lactuca. Principal Component Analysis (PCA) was used to identify environmental factors driving biomass production, and machine learning (ML) models were constructed to assess the predictive capability of the data set for system performance using the local multi-season environmental variations. Environmental datasets were segregated for ML training, validation, and testing using three methods: regression tree, ensemble regression, and Gaussian process regression (GPR). The predicted ash-free biomass productivity using ML models resulted in root-squared-mean-errors (RSME) from 1.78 to 1.86 g/m²/day, and R² values from 0.67 to 0.75 using different methods. The greatest contributor to net productivity was total solar irradiation, followed by air temperature, salinity, and pH. The results of the study should be useful as a decision-making tool to application of attached algae flow-ways for biomass production while preventing algal blooms in the environment.

Water Cycle and Circular Economy: Developing a Circularity Assessment Framework for Complex Water Systems

Water - the most vital resource, negatively affected by the linear pattern of growth - still tries to find its positioning within the emerging concept of circular economy. Fragmented, sectorial circularity approaches hide the risk of underestimating both the preservation of and impacts to water resources and natural capital. In this study, a game changing circularity assessment framework is developed (i.e. MSWCA). The MSWCA follows a multi-sectoral systems approach, symbiotically managing key water-related socio-economic (i.e. urban water, agro-food, energy, industry and waste handling) and non-economic (i.e. natural environment) sectors. The MSWCA modelling framework enables the investigation of the feedback loops between the nature-managed and human-managed systems to assess water and water-related resources circularity. The three CE principles lie at the core of the developed framework, enabling the consideration of physical, technical, environmental and economic aspects. An indicators database is further developed, including all the relevant data requirements, as well as existing and newly developed indicators assessing multi-sectoral systems' circularity. The MSWCA framework is conceptually applied to a fictional city, facilitating its understanding and practical use.

Re-Envisioning Sanitation As a Human-Derived Resource System

Sanitation remains a global challenge, both in terms of access to toilet facilities and resource intensity (e.g., energy consumption) of waste treatment. Overcoming barriers to universal sanitation coverage and sustainable resource management requires approaches that manage bodily excreta within coupled human and natural systems. In recent years, numerous analytical methods have been developed to understand cross-disciplinary constraints, opportunities, and trade-offs around sanitation and resource recovery. However, without a shared language or conceptual framework, efforts from individual disciplines or geographic contexts may remain isolated, preventing the accumulation of generalized knowledge. Here, we develop a version of the social-ecological systems framework modified for the specific characteristics of bodily excreta. This framework offers a shared vision for sanitation as a human-derived resource system, where people are part of the resource cycle. Through sanitation technologies and management strategies, resources including water, organics, and nutrients accumulate, transform, and impact human experiences and natural environments. Within the framework, we establish a multitiered lexicon of variables, characterized by breadth and depth, to support harmonized understanding and development of models and analytical approaches. This framework's refinement and use will guide interdisciplinary study around sanitation to identify guiding principles for sanitation that advance sustainable development at the nature-society interface.