Life cycle assessment (LCA) is a widely recognized tool for environmental assessment, which has experienced a strong development both in methodology and applications. This paper aimed to perform a bibliometric analysis of LCA research during 2000-2022, considering publication types, publication trends, subject categories, journals, institutions, countries, and author keywords. Social Network Analysis was applied to recognize mapping trends, status, and hot spots in LCA research and to discover co-authorship relations and international collaborations among countries worldwide. The results of this study showed that the number of LCA publications has remarkably increased by more than tenfold over the study period. The United States, with 5885 publications (17.3%), was the most productive country in terms of the number of publications. The keywords “sustainability,” “environmental impact,” “carbon footprint,” “circular economy,” “recycling,” and “climate change” were the most occurred keywords in the literature. The keyword “sustainability,” growing from 221 in 2000-2011 to 2013 in 2011-2022, was the most trending keyword. The keywords "water footprint," "biogas," and "GHG emissions" exhibited the highest increase in frequency, with growth rates of 18.5, 11.2, and 7.1 times, respectively. The outcomes of this study showed the cumulative progression of the literature, thereby establishing a framework for future works in LCA research.
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), as the cause of Coronavirus Disease 2019 (COVID-19), may survive in sewage or wastewater treatment plant (WWTP). This condition increases the risks of reusing treated wastewater (TW), particularly in developing countries. We introduced a new index, Viral Risk Index (VRI), for risk classification based on available knowledge about SARS-CoV-2. It was calculated by six effective parameters on the decay rate of SARS-CoV-2 in wastewater. These parameters are easily quantifiable in WWTPs in developing countries and not limited to specific operational conditions. The concentrations of Fecal coliform (FC) and total suspended solids (TSS) in TW in addition to the temperature, WWTPs’ capacity, retention time (RT), and chemical oxidation demand (COD) removal are the six sub-indices. VRI classifies TW in 5 categories (low-high risks). This classification prioritizes WWTPs for monthly viral surveillance and risk mitigation. Here, 23 WWTPs were examined and prioritized in Iran (April-August 2020). The results indicated that the TW in 14 WWTPs could be safely reused, whereas 9 WWTPs required more surveillance and supplementary viral controls for TW reuse. Here, waste stabilization ponds had slightly safer TW than activated sludge units. Moreover, monitoring could improve the average VRI from 2019 to 2020.
Due to rapid development of cities, number of municipal wastewater treatment plants (WWTP) has faced drastic growth in recent decades. Reviewing the literature indicates that WWTPs in urban areas are one of the essential energy consumers, and it is necessary to evaluate their energy consumption. In Tehran, the capital of Iran, the number of WWTPs has increased to meet the demands of its increasing population. Yet, the energy consumption of these WWTPs in Tehran has not been thoroughly examined. This research aims to measure and provide the specific energy consumption of Tehran WWTPs and bridge the research gap by providing precise measurements for three key performance indicators (KPIs): energy consumption per influent volume (kWh/m3), per population-equivalent (kWh/PE-year), and per kilogram of Chemical Oxygen Demand removed (kWh/kg COD). The South Tehran Wastewater Treatment Plant (STWWTP), the largest WWTP in Tehran, demonstrated highest energy efficiency with consumption rates of 0.21 kWh/m3 for influent volume, 16.75 kWh/PE-year, and 0.48 kWh/kg COD removed. Furthermore, the small-scale WWTPs of Tehran showed a significant variation in specific energy consumption. Zargandeh Wastewater Treatment Plant (ZWWTP) represented the poorest efficiency by consuming 96.34 kWh for each person under its service and 3.66 kWh per kg COD removed. In contrast, Ekbatan Wastewater Treatment Plant (EWWTP), among the small-scale WWTPs, demonstrated great energy efficiency with consumption rates of 33.15 kWh per capita and 0.52 kWh/m3. However, this great variation in energy consumption of Tehran WWTPs needs further investigation, and strategies for improving the energy efficiency of these WWTPs are required.
Over the past few decades, sustainability has attracted massive attention at the local, regional, and national levels. The building and construction industry is one of the main areas in which, due to its nature of activities, prioritizing and identifying its key supply chain parameters are core elements of sustainable development programs. In this paper, economic, social, and environmental indicators are investigated using a developed hybrid model based on BWM, AHP, and SWARA to identify and prioritize the significant parameters in this field. 21 different indicators are analyzed by the Likert scale according to their role in progress toward sustainable development. The criteria weights are achieved through a survey of 10 academic and industrial experts whose research interests are sustainability and supply chain management. The Copeland methodology has been used to integrate the output of three models and draw the final result. The results showed that from economic point of view ‘Tech-econ evaluation’, in social aspects ‘employees’ health and safety’, and in environmental aspects ‘Developing green technologies in supply chain’ have reported the highest final dominant scores in Copeland methodology respectively. The proposed model is expected to help industrial experts and managers to identify key sustainable parameters of supply chain in construction industry and set their goals toward sustainability accordingly.
Encouraging foreign and private sectors to participate in renewable projects in developing countries, which not only experience rapid growth in energy demand but also encounter challenges in financing clean projects, presents a complex issue for their governments. To address this challenge, two contentious issues must be addressed concurrently: 1) accurate long-term valuation of Renewable Energy (RE) projects and 2) the assessment of the ideal timing for investments. This paper introduces a binomial tree real-option-based model as a valuable tool for valuing Renewable Energy (RE) projects and determining the optimal timing for investments in developing countries. Three key factors influencing project cash flow were considered in the calculation: Feed-in Tariff (FiT), Maintenance and Operation (M&O) costs, and energy production. Three scenarios were analyzed for exercising option to either improve project profitability, maintain the current profit, or prevent further losses. A real life case study involving a solar photovoltaic (PV) park in Iran has also been investigated to validate and verify the proposed model. The results revealed that, unlike traditional methods such as Net Present Value (NPV) which yielded a negative value suggesting that the project lacks financial viability, the option-based model demonstrated the project's investment potential by generating a positive value through the incorporation of option values inherent in growth projects.
Climate change is one of the most important trends in the world. As the world grapples with the increasing impacts of climate change, the need for innovative and sustainable solutions has never been more critical. One such solution is the circular economy, a transformative approach that redefines our production and consumption systems to minimize waste, conserve resources in use, and restore natural systems. This article examines the role of the circular economy in dealing with climate change, the approaches of the circular economy are presented in this research and its concept is examined with sustainability and sustainable development, then the functions of the circular economy are analyzed and then sustainable solutions to adapt to Climate change is investigated. presented and its conceptual model is analyzed with related economic approaches and finally the relationship of each of the sustainability solutions with 10 circular economy categories is presented and emphasizes the importance of adopting this model for a sustainable future.
In Tehran, Iran's most populous province, there has been a notable surge in livestock production in recent years, prompting a critical examination of water resource allocation through the water footprint indicator. This study uniquely concentrates on livestock productions at a provincial level, specifically within four key counties boasting the highest production rates in Tehran province. Employing the methodology introduced by Mekonnen and Hoekstra (2012), a comprehensive analysis of the water footprints (WFs) associated with various livestock productions is conducted. The results underscore that milk production holds the highest average water footprint at 13,007 cubic meters per ton, significantly surpassing other products. Conversely, lamb exhibits the lowest water footprint at 2,266.7 cubic meters per ton among livestock productions. Evaluation of fresh water sources in relation to animal water footprints highlights unsustainable conditions in southern counties, particularly Islamshahr, due to a pronounced disparity between their product water footprint and available water resources. In contrast, northern counties demonstrate lower water footprints, aligning with their abundant water resources. A scrutiny of water resources reveals vulnerability in Tehran's dams, approaching long-term minimum water volume despite the escalating levels of livestock production. While Varamin features a wastewater treatment unit contributing substantial volume (160 million cubic meters) and recycled water to the system, wells and Qanats play a role in water provision but prove inadequate. Given the substantial productions and water resource scarcity, a recommendation is made to discontinue all livestock production; however, if production persists, focusing solely on sheep meat (lamb) in northern counties is deemed a feasible strategy.
Energy and its related services are crucial to the well-being of society. Access to clean water and sanitation is dependent on energy supply, and so is the provision of quality education and healthcare services. Of equal importance is the manner in which energy is produced and consumed, as the livelihood of future generations depends largely on this. Recently, policymakers have found themselves in a pickle, having to strike a balance between meeting the energy demands of the current generation without compromising the environmental needs of future generations. Given this context, the crux of this study was to examine the impact of renewable and non-renewable energy sources on environmental sustainability in the BRICS region. The findings revealed that non-renewable energy sources, particularly coal and natural gas, augment higher levels of carbon dioxide emissions both in the short run and long run. In contrast, renewable energy sources such as hydro, wind and solar energy were found to lessen the burden of carbon dioxide emissions on the environment. As such, this study cautions against the heavy reliance on non-renewable energy sources, as they threaten livelihoods and biodiversity.
According to the information content of financial reports, this research aims to investigate the effect of Voluntary Disclosure (VD) on the quality of information, the quality of decision and the behavior of shareholders. The population of the research is the firms listed in Tehran Stock Exchange. Based on the screening, 138 firms were selected between 2013 and 2021. The required data was extracted through the website of the stock exchange organization. The collected data were analyzed through econometric models and EViews software. According to the results, there is a significant relationship between VD, disclosure quality, decision quality and shareholders' behavior. Therefore, the amount of stock transactions can be a function of the amount of disclosure characteristics and the quality of the decision. By focusing on the shareholders, the results can provide a basis for making managers' decisions to meet their information needs and improve the transparency of the financial market.
This study investigates the implementation of green information technology (GIT) mechanisms within the Trade Promotion Organization of Iran (TPOI), emphasizing the increasing need for sustainable practices in the IT sector. The research explores the multidimensional aspects of GIT adoption, including environmental, economic, and social impacts. By employing a systemic approach and causal loop diagrams (CLD), the study identifies critical factors such as management budget, IT infrastructure, employee training, and compliance with environmental standards that influence GIT development. The data collection involved an extensive review of documentation, interviews with TPOI managers and experts, and surveys from employees. The findings highlight the complex interplay of various factors affecting the success of GIT implementation. For instance, the allocation of budget significantly impacts the ability to upgrade IT infrastructure and support employee training programs, both of which are crucial for advancing GIT. Additionally, the study found that adherence to environmental standards not only promotes sustainable practices but also enhances the organization's reputation and compliance with regulatory requirements. The research underscores the importance of a comprehensive, holistic approach in integrating green technologies within organizational settings. It provides a strategic framework that can guide other organizations in improving their environmental performance. The study's implications extend to environmental policy, offering a valuable reference for policymakers aiming to promote green IT initiatives across different sectors. The holistic understanding of GIT adoption presented in this research contributes to the broader discourse on sustainable development and highlights the potential for technology to drive environmental and economic benefits.
AbstractThis research investigates the effect of earning risk and earning smoothing on the GDP of companies listed on the Tehran Stock Exchange. The current research method is applied research in the descriptive-correlation research group. The information required for this research was collected from the financial statements of 110 companies in 2011-2022 from Rahavard Novin software and the websites of CBI and CODAL. Multivariate regression with panel data was used to test the hypotheses. The final data analysis was also done with the help of Eviews version 12. In line with the research topic, three criteria of risk of total earning, risk of cash items of earning and risk of accrual items of earning were used. The findings of the research hypotheses test show that the measure of earning risk cash items significantly affects the GDP rate, and smoothing does not statistically moderate the above influence This issue is a new achievement in the field of macro accounting researches.
This study presents a comprehensive carbon footprint analysis of polypropylene production within an Iranian petrochemical facility, employing a broad scope that encompasses all relevant processes across the entire factory, rather than focusing solely on the polypropylene production unit. Utilizing a life cycle assessment (LCA) approach aligned with ISO standards, the research quantifies greenhouse gas (GHG) emissions from each production stage, including raw material processing, energy generation, and waste management, to provide a holistic view of environmental impacts. Key findings reveal that energy-intensive units, particularly power generation and steam production, are the primary contributors, accounting for over 90% of total emissions. The study's broadened scope offers a more accurate depiction of the facility's environmental burden and highlights significant areas for emission reductions. By identifying these critical areas, the research not only advances our understanding of polypropylene's environmental profile but also suggests targeted interventions such as the adoption of renewable energy sources and efficiency improvements. This analysis not only sets a benchmark for future environmental assessments within the industry but also serves as a crucial tool for policymakers and industry leaders aiming to implement more sustainable manufacturing practices. The findings underscore the importance of expanding the system boundaries in carbon footprint assessments to include all associated processes for a more accurate and actionable environmental impact evaluation.
Municipal solid waste management (MSWM) is a critical challenge in rapidly urbanizing cities, especially in coastal areas like Babolsar, Iran. This study aims to evaluate the environmental impacts of various MSWM scenarios using the Life Cycle Assessment (LCA) methodology with the IWM-2 model. Seven scenarios were examined, ranging from landfilling without energy recovery to advanced combinations incorporating composting, recycling, and energy recovery. Data were sourced from the Babolsar City Municipality, encompassing waste generation, composition, and current management practices. The results indicate significant differences in environmental impacts across scenarios. Scenario 1 (100% landfilling) exhibited the highest environmental burdens, including greenhouse gas emissions and toxic outputs. In contrast, Scenarios 4, 5, and 6, which integrate composting, recycling, and energy recovery, demonstrated substantial reductions in these impacts. Specifically, Scenario 6 emerged as the most environmentally favorable option, significantly lowering greenhouse gas emissions and energy consumption. These findings highlight the importance of a diversified waste management strategy that incorporates multiple treatment methods to minimize environmental impacts. The study's comprehensive assessment provides valuable insights for decision-makers and policymakers aiming to enhance sustainability in urban waste management systems. The implications of these findings extend to similar urban areas seeking to optimize their waste management practices for better environmental outcomes.
Accurately predicting industrial electricity consumption is essential for optimizing energy efficiency, and reducing costs in industrial operations. This study presents a novel hybrid prediction model based on radial basis function neural network (RBFNN) and kernelized support vector regression (KSVR) methods (RBFNN-KSVR) for estimating industrial electricity consumption. Key input variables include population, electricity price in the industry sector, gross domestic product (GDP), and the number of electricity subscribers. The proposed hybrid model was implemented in a real-world case study to estimate industrial electricity consumption in Iran and compared against base methods (RBFNN, SVR, and KSVR). Extensive evaluation reveals the superior performance of the RBFNN-KSVR model in predicting industrial electricity consumption. This study provides a robust and reliable approach for industrial stakeholders to enhance energy planning, identify energy-saving opportunities, and ensure a stable power supply. The findings have significant implications for optimizing energy usage, improving efficiency, and reducing costs in industrial operations.
The rapid growth of urbanization, along with the extensive construction of infrastructure and real estate projects, has resulted in higher rates of Construction and Demolition Waste (C&D waste). This condition, combined with the lack or inefficiency of municipal programs to manage C&D waste, has exacerbated urban issues related to C&D waste collection, transportation, and disposal. The purpose of the present study is to apply the Life Cycle Assessment methodology to evaluate the environmental performance of the current management of C&D waste and to identify critical aspects and possible improvement actions in Tehran City. Impact 2002+ performs LCA of the base case (19% recycling), two treatment scenarios. These scenarios included the combined use of landfill, sorting and recycling, and the use of C&D waste in varying percentages. The life cycle inventory analysis was carried out using primary data from field studies and secondary data from the Ecoinvent 3.7 database and the literature. The results demonstrate the benefits of C&D waste recycling in terms of avoided impacts of non-renewable energy, global warming, non-carcinogens, and potentially generated respiratory inorganics and organics from landfill. Thus, our results help ensure that decision-making processes are based on environmental and technical aspects and not just economic and political factors and motivate producers to reduce sources and encourage recyclers and concerned organizations to continuously improve the performance of C&D waste management systems across Iran, and also provide data and support for other LCA studies on C&D waste.
Virtual power plants (VPPs) have gained significant attention in recent years as a promising solution for optimizing the operation of power systems. VPPs allow for the integration and coordination of Distributed Energy Resources (DERs), such as renewable energy sources, to provide grid support and stabilize the power supply. This paper presents a VPP that utilizes a three-phase power flow analysis for its modeling. This approach allows for an accurate representation of the power flow in the VPP, considering the dynamic nature of the power system. In addition to the three-phase power flow analysis, the authors propose a tabu continuous ant colony search (TCACS) to optimize the operation of the VPP, which combines tabu search and ant colony optimization to find near-optimal solutions for complex optimization problems. It uses a tabu list to guide the search towards promising solutions while avoiding getting stuck in local minima. The performance of the proposed VPP has been evaluated through simulation studies, and the results show that it is effective at minimizing power loss and improving the stability of the power system. The proposed VPP can be a valuable tool for utilities to manage their power generation and distribution, particularly in the context of increasing renewable energy integration.
Banks play an important role in the country's macroeconomics, they have a special importance in the economic pillars of the country, instability in macroeconomic policies, both in the supervision sector and in the real and financial sectors, makes banks as the last buffer against these shocks. Therefore, it is necessary to have an efficient warning system by benefiting from special economic forecasting tools in order to prevent their bankruptcy; This research tries to analyze the challenges and strategies of more effective development of the rapid warning system of banks' bankruptcy so that it can identify the existing obstacles and adopt appropriate approaches. The current research follows the post-positivist paradigm and in terms of its purpose, it is applied research, the results of which have been analyzed based on grounded theory. In the category of Early Warning System (EWS) development for bankruptcy, 11 main criteria and their various considerations were extracted; 10 key challenges and current problems and limitations were introduced and about 80 approaches and strategies were introduced for these 10 challenges, finally 13 main approaches were proposed to make the development of the banking bankruptcy warning system more effective.
This study investigates how pulverized wood-derived biochar affects leaching and release behavior of Chromium (Cr), Copper (Cu), and Nickel (Ni) from construction and demolition waste (CDW) towards groundwater. CDW constitutes a large portion of total waste generation in both developed and developing countries, prompting attention due to its substantial volume, resource implications and environmental risks. Involvement of dissolved organic carbon (DOC) and turbidity in mobilization and release of heavy metals in pulverized biochar-amended CDW has been addressed for the first time in this research. Leaching and release of heavy metals from CDW was evaluated using column leaching test. Wood-derived biochar, produced at temperatures up to 750°C, was incorporated into columns. Leachates, collected at regular intervals, were analyzed for heavy metals using inductively coupled plasma-mass spectrometry (ICP-MS). Results indicated initial high mobilization followed by rapid decline in leached concentrations of heavy metals. Biochar incorporation reduced cumulative release of heavy metals from CDW into the aqueous phase, with a more pronounced impact for Cu and Ni. Higher biochar content led to increased initial mobilization of Cr, Cu, and Ni. Positive correlations were observed between leached concentrations of Cr, Cu, and Ni from CDW with both DOC and turbidity, with DOC making a more significant contribution in pulverized biochar-amended CDW. Although biochar demonstraed promise in reducing heavy metal leaching from CDW, its efficacy plateaued at higher application rates. This highlights the necessity to optimize biochar dosage for immobilizing heavy metals in CDW and safeguarding groundwater.
Global attention has focused on the general deterioration of water quality due to rapid industrialization, population growth and a steady decline in the amount of safe water available. This study provides a new framework for waste load allocation from an fair and equitable perspective. First, the optimal scenarios are generated by calling the (Streeter-Phelps) S-P equation with the Nod-dominated Genetic Algorithm-II (NSGA-II) optimization algorithm. In addition, using two fairness measures from Rawls' theory of justice, two optimization problems specifying have been defined with three objective functions, such as minimizing total treatment costs and violating standards. Then the Complex Proportional Assessment (COPRAS) method has been used to select and compare most waste load allocation scenarios. Results indicated that optimal waste load allocation scenarios based on Rawls justice theory in addition to reduce of the violation rate of the DO could effectively configure a system to allocate treatment cost fairly.
The current research was an attempt to investigate the use and maintenance of Sistan's irrigation network from the point of view of local experts and farmers. Gray system theory was used to find the appropriate operation and maintenance model for irrigation networks. The results indicate the positive effect of delegating network management on increasing employment, reducing rural migration, increasing the productivity of agricultural products, increasing farmers' confidence in providing food and income, proper distribution of water, increasing the use of irrigation networks, reducing wastage of water resources, increasing the sense of responsibility and confidence of the irrigation network systems was under the management/protection of the farmers. Also, the results showed that the most basic adverse consequences include lack of trust in carrying out responsibilities, lack of understanding and cooperation of water users, differences of opinion among farmers in water distribution, insufficient attention to training and development, lack of experience, lack of optimal use of resources and It was attention. Among the economic issues faced by water users, we can mention the lack of understanding and cooperation of the users. Since neither the main farmers nor the established cooperatives have enough knowledge about their obligations in the field of management, operation and maintenance of irrigation networks and taking necessary measures, the best possible solution is comprehensive training of farmers. Progress in this area depends on delegating the irrigation network management to proper alternatives.
