Enhancing sustainability within industrial cooperative networks through the evaluation of economically compromised entities

IntroductionWhile promoting sustainable industrial cluster development using the circular economy perspective, the increased use of underutilized materials results in compromised profitability in the cooperative network. The focus is to evaluate the external financial support required in industrial clusters against specific objectives and highlight the potential beneficiaries and losers in financial terms because of industrial symbiosis while closing material loops.MethodThis study provides an agent-based approach to record the system response based on three case studies to demonstrate the potential cost variations: The first case is about utilizing only naturally available resources by all the industrial entities and is taken as a base case. The second case is about targeting the lowest cost for each product, and the third one provides a sustainable and flexible solution by targeting the best transformation methods and materials.ConclusionThe study concludes with valuable insights to identify the economically compromised entities in an industrial cluster network by considering economic deviations beyond a critical value. It can help take concrete measures in the form of incentives or investors subsidies by governmental organizations, regulators, and policymakers to intervene and stimulate markets through targeted financial support/policies to the compromised entities. This results in improved materials loop closing, essentially promoting sustainable production systems in industrial clusters. Additionally, such financial support/incentives also influence the scarcity or accumulation of by-products or low-value materials, ultimately improving the industrial network's environmental and economic performance

Integrated TOPSIS-COV approach for selecting a sustainable PET waste management technology: A case study in Qatar

In 2018, the global annual consumption of Polyethylene terephthalate (PET) bottles was approximately 27.64 million tons, with one million bottles sold worldwide every minute. Unmanaged PET bottles in the environment lead to a series of negative effects on the health of humans and ecosystems. Therefore, the objective of this research was to evaluate the sustainability of eight different PET waste bottle treatment methods using a holistic multi-criteria decision-making approach that combined the technique for order of preference by similarity to ideal solution (TOPSIS) with analytic hierarchy (AHP; TOPSIS-AHP) and coefficient of variation (COV; TOPSIS-COV) approaches. To the best of our knowledge, TOPSIS-COV has not yet been used for waste management. The treatment methods were compared and analyzed against twelve different performance criteria representing three pillars of sustainability: environmental, economic, and social. Both approaches determined closed-loop recycling to be optimal for treating PET waste bottles. The weights of performance indicators obtained using the COV and AHP approaches were comparable, except for cost, photochemical oxidant potential, and human toxicity. The large dispersion in the values of the photochemical oxidant potential causes it to have a higher weight in the COV approach. For cost, the weight was higher using the AHP approach by approximately 12%, which reflects the preference of decision-makers to reduce costs of ventures. 2022 The Author(s)This work was supported by the Awards GSRA4-1-0524-17104 from Qatar National Research Fund (a member of the Qatar Foundation). The contents herein are solely the responsibility of the authors.Scopu

Evaluation of evapotranspiration models for cucumbers grown under CO2 enriched and HVAC driven greenhouses: A step towards precision irrigation in hyper-arid regions

Evapotranspiration is considered as one of the most crucial surface fluxes describing the water movement from the land to the atmosphere in the form of evaporation from the soil and transpiration from plants. Several evapotranspiration models exist, but their accuracy is subject to change because of the differences between the underlying assumptions used in their formulation and the conditions of the application at hand. The appropriate selection of an evapotranspiration model is necessary to ensure the accurate estimation of crop water requirements. This work compares between 20 different evapotranspiration models for the estimation of transpiration of cucumber crops grown in a cooling-based greenhouse with CO2 enrichment located in a high solar radiation region. The models are classified into temperature-based, radiation-based, mass transfer-based, and combination models. These models are assessed against direct gas exchange measurements in a greenhouse with cucumber crops. The performance of the models is evaluated using nine statistical indicators to determine the most suitable models for the application under study. Results demonstrate that among the temperature-based models, Schendel and Blaney and Criddle models resulted in the best transpiration prediction, contrary to Hargreaves and Samani which presented the worst performance. Transpiration estimates from Rohwer were the closest and that of Trabert were the furthest to the measured data amongst the other mass-transfer based models. The Abtew model was the best transpiration predicting model, while Priestley and Taylor exhibited the worst performance in the radiation-based model category. The combination-based FAO56 Penman Monteith entailed the best performance among all models and can be considered the best suitable method to estimate transpiration for cucumber crops grown in CO2 enriched and HVAC based greenhouses located in high solar radiation regions. Nonetheless, the parametrization of this model is still crucial and should be considered to achieve better estimates and accurately evaluate the effect of high solar radiation, CO2 enrichment and HVAC cooling for this agricultural greenhouse application

Optimizing the utilization of biochar from waste: an energy–water–food nexus assessment approach considering water treatment and soil application scenarios

Introduction: As a result of the rapid increase in population and depletion of natural resources, particularly energy and water, approximately 200 million people are expected to face hunger by 2030. Going forward, the sustainability of energy, water, and food (EWF) resources can be enhanced by considering a nexus approach, which supports effective resource management by identifying synergies and trade-offs. Furthermore, the regeneration of biomass into value-added products, such as biochar (BC), can reduce cross-sectoral environmental impacts and support the EWF nexus.Methodology: This research investigates the optimum options for utilizing BC within the context of the EWF nexus for both wastewater treatment and soil applications whilst considering the optimal blending ratio of various biomass (camel manure, date pits, sewage sludge, and coffee waste) for both single-end use and multi-end use stages to fulfill various objectives within defined scenarios based on maximum savings in energy, water, cost, and emissions.Results and discussion: The single-end use stage considered using BC for wastewater treatment (WWT) and as a soil amendment (SA) individually, and 18 optimal solutions were collected for this stage. The optimization of the multi-end use stage resulted in 70 optimal solutions, where BC was applied for both WWT and SA. The solutions that leaned toward SA application suggested that BC should consist of 97%–99% of date pits with relatively smaller proportions of the other biomass. On the other hand, the other solutions that leaned toward the WWT pathway suggested that the optimum biomass mix should consist of relatively equal proportions of camel manure, sewage sludge, and coffee waste of 29%—33% and smaller amounts of date pits of approximately 2%–5%

A systematic review of heat recovery from roads for mitigating urban heat island effects: current state and future directions

Heat recovery from roads is a promising technology to address the urban heat island effect. This review paper aims to provide a comprehensive analysis of the current state and future directions of heat recovery from roads to address the urban heat island effect while generating renewable energy. The study covers various aspects such as theoretical background, economic feasibility, environmental impact, and materials design techniques. A systematic search of relevant literature was conducted to analyze and synthesize different heat recovery systems’ efficiency, performance, and potential. The paper also discusses the economic feasibility and environmental impact of these systems, including installation and maintenance costs, revenue generation, and local ecosystem impact. The review explores the role of different materials, such as PEX pipe, asphalt mix, and carbon nanotubes, in improving heat harvesting systems’ efficiency. The paper concludes with a discussion of research gaps and future directions in the field of heat recovery from roads. This study provides a valuable resource for researchers, practitioners, and policymakers interested in sustainable and efficient energy system development

Assessing plastic and biomass-based biochar's potential for carbon sequestration: an energy-water-environment approach

Biochar from waste has emerged as a vital solution for multiple contemporary issues. While the organic content and porous structure of biochar have granted it multiple benefits. Where the use of biochar is proven to be beneficial for enhancing the soil structure and water and nutrients retention ability, therefore, saving water and boosting yields in arid regions. Moreover, biochar is capable to sequester carbon from the atmosphere and permanently store it within the soil. As such, this study evaluates the potential for carbon sequestration through biochar obtained from the pyrolysis of feedstock mixtures including camel manure, date pits, high-density polyethylene (HDPE) and low-density polyethylene (LDPE), and how it can enhance water and food security. Multiple energy and water supplying sources have been considered for different project scenarios to provide a broader understanding of biochar potentials. The lifecycle analysis (LCA) approach is utilized for the assessment of net emissions, while an economic study is conducted in Aspen Process Economic Analyser (APEA) to evaluate the feasibility of the different scenarios. Finally, single-objective optimization and multi-objective optimizations were carried out using excel and MATLAB genetic algorithm respectively to select optimal biomass blending and utilities options to fulfill the low cost and negative emissions targets. The assessment conducted for a Qatar case study indicates that the best waste blending scenario for maximum carbon sequestration potential was obtained at a mixing ratio of 20.4% Camel manure: 27% date pits: 26.3% LDPE: 26.4% HDPE. Furthermore, the optimum char blend for maximum carbon sequestration corresponding to the minimum cost of char mix was computed. The optimal biochar mixing percentage for highest net emission was obtained at a feedstock mixing ratio of 96.8% of date pits, 1.5% of LDPE, and 1.7% of HDPE with 0% of camel manure with an optimal cost of 313.55 $/kg biochar. Solar PV was selected as the best energy source in this pyrolysis study due to its reduced carbon emissions in comparison to other sources studied such as natural gas, coal and diesel. However, natural gas is selected to fulfill the economic objective. Moreover, the optimal water source was investigated including wastewater treatment, multi-stage flash and reverse osmosis desalination, where treated wastewater is selected as the optimal supply to fulfill both, economic and environmental objectives

How sustainable is liquefied natural gas supply chain? An integrated life cycle sustainability assessment model

Integrating sustainability into the distribution network process is a significant problem for any industry hoping to prosper or survive in today's fast-paced environment. Since gas is one of the world's most important fuel sources, sustainability is more important for the gas industry. While such environmental and economic effects have been extensively researched in the literature, there is little emphasis on the full social sustainability of natural gas production and supply chains in terms of the triple bottom line. This research aims to perform the first hybrid life cycle sustainability assessment (LCSA) of liquefied natural gas and evaluate its performance from the natural gas extraction stage to LNG regasification after delivery through maritime transport carriers. LCSA is used for estimating the social, economic, and environmental impacts of processes, and our life cycle model included the multi-region input–output analysis, Aspen HYSYS, and LNG maritime transport operations sustainability assessment tools. The results spot the light on the most contributors of CO2-eq emission. It is found that LNG loading (export terminal) is the source that generated the highest carbon footprint, followed by the MDEA sweetening unit with the contribution of 40% and 24%, respectively. Socially, around 73% of human health impact comes from SRU and TGTU units which are the most contributors to the particulate matter emission. Based on the interpretation of life cycle results, the environmental indicators show better performance in the pre-separation unit and LNG receiving terminal representing a sustainability factor equal to 1. In terms of social and economic impacts, the natural gas extraction stage presents the best performance among all other stages, with a sustainability factor equal to 1. Based on this study's findings, an integrated framework model is proposed. Various suggestions for sustainability strategies and policies that consider business sustainability and geopolitics risk are presented

How circular design can contribute to social sustainability and legacy of the FIFA World Cup Qatar 2022™? The case of innovative shipping container stadium

The circular economy proposes a paradigm shift from the ‘take-make-waste’ type of economic system and aims to foster innovation, resource efficiency, and waste prevention. Mega sporting events can be considered great opportunities to promote sustainable cities and communities and leave a lasting positive legacy after the post-game stage. Qatar will organize the upcoming FIFA World Cup in 2022 and Ras Abu Aboud (RAA) is designed as a fully reusable and modular shipping container stadium, which will be dismantled, relocated, and reused after the tournament. This study aims to present the first comprehensive analysis on the social sustainability and legacy aspects of a circular and sharing economy application for the FIFA World Cup organization. The research analyzes the entire life cycle phases of the RAA stadium including the raw material production, construction, operations, and end-of-life. The Ecoinvent v.3.7.1 is used to quantify the midpoint environmental and endpoint human health impacts. For its operation phase assessment, two operation scenarios are comparatively analyzed: one-year temporary operation (Scenario 1) and 50 years of permanent operation (Scenario 2). Later, a simulation-based sensitivity analysis is conducted. Finally, we discussed how circular and modular design thinking can bring long-lasting legacy post-event, through reuse and recycling from a socio-economic perspective. An important finding shows that circular design under Scenario 1 can save up to 60% of human health impacts and significantly reduce the material footprint and dependence on imported construction materials. This research will enhance future awareness for sustainability benefits of circular and sharing economy application adopted by mega sporting events concerning the United Nations 2030 Agenda for Sustainable Development and FIFA's post-game legacy and sustainability strategies

Sustainable food security decision-making : an agent-based modelling approach.

Ensuring a consistent and regular availability of food is crucial for food security. Food markets, supplied through both domestic production and international trade, are governed by several risks emerging from unpredictable supply chain disruptions, volatility of commodity prices, along with other unforeseen circumstances such as natural disasters. To mitigate the challenges threatening the stability of food systems, decision-making within the food sector should be enhanced and robust to accommodate any changes that might cause food shortages. Dynamic models, that can predict the behavior of food systems in order to avoid potential future knock-on effects and deficits, are incumbent to ensure the sustainable performance of food systems. This study proposes a dynamic decision-making scheme that simulates strategies of the perishable food market under different circumstances. An agent-based model (ABM) is developed and implemented using python MESA library for a case study in Qatar, illustrating the potential performance of tomato under three different scenarios to be considered, namely: (a) baseline scenario - aiming to reflect current production and market conditions; (b) water resource efficiency scenario - basing decisions on crop water requirement (CWR) depending on weather conditions; and (c) economic risk scenario - applying the concept of forward contracts to hedge against future uncertainties in crop prices. The findings of this study demonstrate that under the baseline conditions, a tomato crop can be supplied through a combination of domestic production and imports depending on the available inventories and prices imposed by exporters. The results obtained for the CWR scenario suggest the need for total reliance on imports in order to meet domestic demand, as there is potentially high-water loss, which amounts to an average of 4.9 Billion m3 per year, if tomato is grown locally. In contrast, the results from the forward contract scenario recommend a 57% dependency on local production in order to mitigate the effects of volatility in global food prices, which contributes to a 63% reduction in environmental emissions. Findings of this research provide insight into the factors that influence strategic decision making by the food sector to enhance its economic and environmental performances under diverse circumstances

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed