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Self‐organized industrial symbiosis (IS) starts with one actor's decision to invest in a waste recovery plant and the other actors' decision to buy the recovered flow. Technical and institutional conditions of the cluster influence actors' decisions. This paper explores the emergence of IS collaborations in industrial clusters under different techno‐economic conditions in the long term. We propose a mixed‐integer linear programming model that incorporates costs and constraints associated with waste recovery and exchange to study actors' investment decisions and investigate shaped symbiotic exchanges under rising energy prices and limited electricity supply. The approach is implemented in Iran's Persian Gulf Mining and Metals Special Economic Zone as a case study. The results revealed that changes in internal or external condition simultaneously influence the industrial and waste recovery plants. For instance, increasing energy prices without raising product prices significantly decreased the production level of industrial plants and, consequently, heat recovery potential. Furthermore, the waste heat recovery plants' contribution to improving the cluster's economic and environmental performance was not the same. Electricity recovery from a power plant's waste heat can result in 55 PJ grid electricity intake reduction and 720 M€ cluster cash flow increase. Recovered cooling or electricity from the steelmaking plant waste heat was consumed internally rather than shaping IS. These model outcomes show its capability to study IS within the socio‐technical structure of the cluster, not a standalone phenomenon. Implemented conceptualization offers a novel system‐level approach, which could be adjusted to assess other industrial development strategies. [ABSTRACT FROM AUTHOR]

This paper examines the nexus between economic growth and energy consumption shock, over the period 1990-2020, in Iran. We employ a Bayesian vector autoregressive (BVAR) with new prior functions, which will give results more acceptable consequences than the classical methods to study these relationships. This study estimates the relationship between energy consumption shocks and economic growth within a multivariate BVAR framework by including gross capital formation, Labor and carbon dioxide emission. The multivariate impulse responses to shocks in all the variables are obtained. The results show that, there is a positive impact of energy consumption shocks on economic growth in Iran and this means that energy consumption is crucial for economic growth. Also, the responses of economic growth to one-unit shock of gross capital formation and labor force are positive and the responses of economic growth to the one-unit shock of carbon dioxide emission is are negative. [ABSTRACT FROM AUTHOR]

In recent years, the mining of cryptocurrencies such as Bitcoin has attracted much global attention due to the simplicity and high profitability of this business, especially in countries with low electricity rates. The process of cryptocurrency mining using cryptocurrency mining devices requires a significant amount of computing power. This industry, which is increasingly growing in energy and carbon emissions, can cause environmental concerns. Common ways to reduce this amount of energy consumption are to prohibit mining and charge these loads at a higher electricity rate; however, these solution methods are not feasible and applicable in many countries. This paper presents an energy efficiency program to persuade the customers to mine cryptocurrency using high‐efficient cryptocurrency mining devices (CMDs), including informative, regulation, and financial policy instruments. This energy efficiency approach suggests a standard, if implemented, would ban the application of inefficient CMDs, and would encourage the cryptocurrency miners to improve the profitability of their business with high‐efficient CMDs through a penalty‐reward strategy. The performance of this energy efficiency program is studied through an analysis of data gathered from different CMDs used in Iran. The effectiveness of this suggested program is proved through its sufficient incentives for miners using high‐efficient CMDs. [ABSTRACT FROM AUTHOR]

Most scholars support the increase in carbon dioxide (CO2) emissions as one of the major causes of the increase in global climate change. Therefore, reducing CO2 emissions from the main emitter countries, including Iran as the sixth emitter, is important to deal with the harmful effects of global climate change. Accordingly, the main aim of this paper was to analyze the social, economic, and technical factors affecting CO2 emissions in Iran. Previous studies on diverse variables affecting emissions are not very accurate and reliable as they do not consider indirect effects. This study applied a structural equation model (SEM) to estimate the direct and indirect impacts of factors on the emissions by panel data for 28 provinces of Iran from 2003 to 2019. According to geographical location, three distinct regions, the north, center, and south of Iran were considered. The findings suggest that a 1% increase in social factor directly increased CO2 emissions by 2.23% (in the north) and 1.58% (in the center), but indirectly reduced emissions by 0.41% (in the north) and 0.92% (in the center). Hence, the total effects of the social factor on CO2 emissions were estimated at 1.82%, and 0.66% in the northern, and central regions, respectively. In addition, the total effects of the economic factor on CO2 emissions were estimated at 1.52%, and 0.73% in those regions. The results of this study showed that the direct effects of a technical factor on CO2 emissions were negative in the north and center. However, they were positive in the south of Iran. Based on the empirical results of this study, three policy implications are discussed in order to control CO2 emissions in regional distinctions of Iran as follows: First, policymakers should pay attention to the social factor, i.e., the growth of human capital in the southern region with the aim of increasing sustainable development. Second, Iranian policymakers must prevent unilaterally increasing gross domestic product (GDP) and financial development in the north and center. Third, policymakers should pay attention to the technical factor, i.e., improving energy efficiency, as well as upgrading information and communications technology (ICT) in the northern and central regions, and limiting the technical factor in the southern region. [ABSTRACT FROM AUTHOR]

The Iranian transportation industry is an energy‐intensive sector with a wide variety of destructive environmental effects. The use of hydrogen is a promising method to reduce CO2 emissions. Methane decomposition is one of the reliable processes to yield hydrogen. In this paper, the levelized cost, technical parameters, and CO2 emissions of each hydrogen production method are determined and discussed. Finally, it is concluded that steam methane reforming is almost a clean and efficient method of hydrogen production. Besides, maximum generated hydrogen values were obtained using the electrolysis process. To be more precise, in this process, the levelized cost of hydrogen production by photovoltaic, wind, and gas‐combined cycle were evaluated. [ABSTRACT FROM AUTHOR]

In continuation of the previous part, this paper comprehensively focuses on energy, exergy, exergo-economic, and environmental (4E) analyses of two prioritized clean hydrogen (H 2) supply chains pathways. The first scenario relies on domestic demand , involves blue H 2 production and storage using steam methane reforming coupled with carbon capture and storage through H 2 conversion to hydrogen carriers in liquid form (ammonia and methanol) aligned with the existing infrastructure. The second scenario involves green H 2 production from photovoltaic panels as the power source follows by storing H 2 in liquid form which is more suitable to export. The findings indicate that the blue H 2 system outperforms the green H 2 system in terms of energy and exergy, boasting 41.38% and 22.15% compared to 12.16% and 12.75%, respectively. However, when examining economic parameters, the blue H 2 system shows a total cost rate of 1976 US$/h, a net profit of $747.2 million (mn) at the end of its lifetime, and a payback period of approximately nine years. Conversely, the green H 2 system demonstrates economic indicators of a 125.2 $/h as a total cost rate, $1.26 billion (bn) net profit, and an 8.17 year payback period. Moreover, the production cost rates for blue and green H 2 are 1.32 $/kg and 2.55 $/kg, respectively; while the CO 2 emissions rate in the blue H 2 system is 10.71 kg/s. The green H 2 system prevents 19.84 kg/s of CO 2 emissions resulted a significant environmental cost reduction of 2.28 $/kg H 2. This analysis facilitates a thorough comparison of these two clean H 2 production and storage systems, offering insights for policymakers across performance, economic, and environmental dimensions. • A comprehensive 4E analysis was applied for the selected H 2 value chain scenarios. • Blue H 2 scenario is superior economically while environmentally the green one takes precedence. • Carbon credit makes the green H 2 scenario emerges frontrunner utilizing PV solar technology. • Methanol was recognized as the most cost-effective H 2 carrier for storage in Iran. [ABSTRACT FROM AUTHOR]

In recent decades, the risks and environmental damage caused by economic growth, population growth and energy consumption have become more apparent. Meanwhile, one of the new advances in the study of the relationship between economic factors affecting environmental quality is the attention to the spatial nature of environmental phenomena. Therefore, the aim of this study was to model the relationship between carbon dioxide (CO2) emissions and economic growth along with other influential factors. CO2 emissions as a criterion for environmental pollution in Iran have been studied using the Spatial Durbin Model (SDM) and in the framework of spatial panel data among the provinces of Iran during the period 2003-2017. The results of this study show that in total, real GDP per capita increases CO2 emissions at the provincial level, because the positive real GDP per capita coefficient is larger than the negative real GDP per capita coefficient of space. Another very important variable in increasing CO2 emissions in the provinces is the intensity of energy consumption and its spatial interruption, which has the highest significant and positive coefficients in the model of this paper. Also, the weighted price of provincial energy and its space interruption have had a significant and negative effect on CO2 emissions. Although increasing the degree of urbanization has not had a significant effect on CO2 emissions in the same province, but increasing the degree of urbanization in neighboring provinces has increased CO2 emissions. Finally, the spatial interruption coefficient of the dependent variable is significant and positive, which shows that the increase in CO2 emissions in neighboring provinces has increased CO2 emissions in the same province. [ABSTRACT FROM AUTHOR]

Off‐grid renewable energy systems are a solution for power generation in areas where access to the grid is not possible or cost‐effective; in particular, low population rural areas located far away from grid lines or in rugged terrains. Furthermore, over‐reliance on fossil fuels for supplying global energy demand has led to the depletion of nonrenewable resources and environmental issues. This paper presents a feasibility assessment of an off‐grid hybrid renewable energy system for a remote rural area in Kohgiluye and Boyer‐Ahmad Province in Iran. Regarding the available energy resources in the region, a photovoltaic (PV)‐biomass energy system is considered. HOMER Pro software is utilized to find the optimized sizing of the PV‐biomass system to fulfill this load demand. The objective function in this optimization is the system's total net present cost. Due to the rapid fluctuation of economic factors in the country, several rates of inflation and discount rate are considered to investigate their influence on the costs of the system. The optimization result for the current inflation rate of 40% and the discount rate of 18% in the country proposes a hybrid energy system consisting of a 3 kW biogas‐fueled generator, 4.74 kW PV, 10 kWh battery, and 2.07 kW converter to meet the 2.64 kW peak load and 14.53 kWh/day consumption of the community. The total net present cost and cost of energy are $93,057 and 0.0933 $/kWh, respectively. Finally, the environmental assessment of the proposed hybrid system shows an annual CO2 emission of 2.95 kg, which means 99.9% CO2 emissions mitigation compared to a conventional coal‐based electrical plant. [ABSTRACT FROM AUTHOR]

The transition to renewable energy is key for sustainable development. Therefore, one of the sustainable development goals (SDG) of United Nations (UN) is to shift towards clean energy. However, in many resource-rich countries several factors can stand as barriers towards the transition process. In this regard, this paper examines the influence of higher oil price, CO 2 emissions, and income on renewable energy consumption in Iran from 1980 to 2019, employing General to Specific (Gets) modeling approach. Estimation results indicated that oil price and CO 2 emissions both have statistically significant and negative impact on renewable energy consumption. The negative influence of higher oil prices on renewable energy consumption may be interpreted as sign of satisfaction coming from higher oil prices, which postpones the transition from traditional energy sources to renewable for Iran. Furthermore, we concluded that income does not have a statistically significant influence on renewable energy use. The paper discusses alternative policies to promote renewable energy consumption. • The effect of higher oil price on renewable energy consumption was studied. • A novel version of General to Specific (Gets) modeling approach was employed. • We found significant, negative impact of oil price on renewable energy use in Iran. • The paper discusses alternative policies for Iran to promote renewable energy use. [ABSTRACT FROM AUTHOR]

This paper focuses on hybrid renewable energy systems (HRES) as an alternative for conventional energy systems, especially fossil fuels. The problem is to find the optimal number of components of a standalone hybrid system, based on minimizing the value of the annualized cost of the system (ACS), in the presence of the constraints. To reduce the CO2 particles as one of the most threatening particles for the planet, an additional constraint is added to the objective function. For solving the problem of system sizing, Harmony Search and Ring Theory-based Evolutionary Algorithm have drawn attention to be preferred to numerous techniques. In addition,a combination of both, which has never been used before, is proposed. The proposed hybrid algorithm shows its ability to mitigate both the emissions and costs of the system promisingly in comparison with the others. Clearly, with Carbond = 15 and different values of LPSPMax as well as using RTHS, RTEA and HS algorithms for PV/WT/BSS/DG configuration, the best performance in terms of ACS minimization belongs to RTHS algorithm with the minimum cost of $1528.2. Also, considering LPSP = 0 and changing carbon from 0 to 20 tons/year, the ACS of the PV/WT/BSS/DG configuration is reduced from $38586.3 to $21153.5 (45% reduction). • Using a hybrid algorithm called RTHS to minimize the annual costs of the system. • Considering the LPSP constraint to supply the load demand at an acceptant level. • Reducing CO 2 emissions to increase the renewables penetration. • Considering uncertainty on both the generation and demand sides. • Validating of the proposed method based on real data for a case study in Iran.. [ABSTRACT FROM AUTHOR]

• Application of solar energy according to land use/land cover map. • Electrification of transportation sectors based on local renewable energies. • Comparison of conversion and storage efficiencies of different energy forms in transportation. • Reducing transportation and urban environmental impacts. • Multi-criteria decision-making of sustainable transportation based on sustainable development pillars. The main aim of this paper is the decarbonization of the transportation sector in Tabriz City regarding sustainable development aims and beyond-2-degrees-scenario by focusing on electric vehicles, as well as on appropriate infrastructures. Quantitative and simulation research methods are used to analysis of total energy, exergy, and losses analysis according to different resources and vehicles. Next, the solar potential of the city is simulated using the Grasshopper plug-in-Rhino simulator and PVsyst software. A LULC analysis has been done using ArcMap 10.8. With renewable electrification, energy consumption will plunge from 15.5 TWh input-energy content of different carbon-based resources to 3.7 TWh with 0.17 MtonCO 2 /year instead of 2.13 MtonCO 2 /year emissions. In this paper, the overall system efficiency of electric vehicles is around 55% which is significantly higher than internal combustion engines. Fully electrification of the transportation systems based on renewable resources mitigates CO 2 emissions of internal combustion engines 15 times, besides reducing the emissionsa variety of harmful pollutants. In terms of multi-criteria decision-making, the technique for order of preference by similarity to the ideal solution was used to rank 50 popular vehicles according to interconnected sustainable development criteria. This paper highlights that conventional internal combustion engines can be replaced by electric vehicles by applying combination of appropriate taxes, tariffs, and incentives. [ABSTRACT FROM AUTHOR]

The purpose of this article is to pay attention to the coverage distance of stores, as one of the key features of the consumer market. This factor can have many effects on economic and environmental issues as well as on the service level. In this paper, two models are proposed. In the first model, the location and allocation of stores are discussed using the maximum coverage method, and in the second model, the optimal number of products is calculated and the network costs and pollution are minimized. GAMS software with CPLEX solver was used to solve mixed linear integer programming under the uncertainty of demand parameters, maximum coverage distance, and carbon trade price in different scenarios. Due to the lack of law to minimize the amount of pollution caused by transportation in Iran, the cap-and-trade policy was used in the supply chain of the Bistoon sugar factory in Kermanshah. The results showed that increasing the coverage distance, in addition to reducing the level of customer service, will also increase the overall costs of the manufacturer and network pollution. Also, despite the costly implementation of environmental policies, by replacement of green vehicles, the overall costs of the network have not increased. [ABSTRACT FROM AUTHOR]

Background and Objective: Among greenhouse gases, CO2 has a crucial role; thus, its impact on health indicators such as life expectancy is of great importance. Hence, one of the most important challenges in the health sector has been the impact of the environmental pollutants emission, namely CO2, on life expectancy of men and women. Materials and Methods: This is a descriptive-analytical and applied design with the health economics approach. The present paper examined the impact of pollutant emissions, namely CO2, per capita income, death rate and birth rate, separately on Iranians’ life expectancy. This analysis was conducted using Quantile regression with EViews10 software during the period 1960 - 2019. In this study, first, the impact of pollutant emissions on life expectancy of all Iranians was calculated. Then, the impact of CO2 on life expectancy of Iranian men and women in different quantiles was estimated. Results: The results confirm the impact of carbon dioxide emissions per capita on total life expectancy was -0.133 and the impact of this pollutant emission on life expectancy obtained -0.170 and -0.127 for men and women, respectively. Both effects were estimated as negative and significant. This effect on life expectancy of men was 0.43% higher than that of women. Furthermore, the impact of death on life expectancy was negative, while the effect of per capita income on life expectancy was positive. Also, birth rate had a positive impact on women's life expectancy, whereas, it showed a negative impact on men. Conclusion: The study revealed that CO2 emissions had a negative impact on total life expectancy of both men and women. Thus, in order to increase life expectancy in Iran, pollutants emission, namely CO2, should be controlled. These results can be a good guide to decision makers and macro-policy makers in Iran to control environmental pollutants to increase life expectancy. [ABSTRACT FROM AUTHOR]

The costs of gas transportation and its environmental/security impacts in Iran have led to evaluating geothermal/solar renewable sources instead. Regarding the high potential of geothermal/solar in Sistan/Baluchestan province, Iran, which have still no access to the global gas network, these resources create a desirable plan. This paper attempted to present/compare four possible solar-assisted ground source heat pumps to supply four purposes of electricity demand, heating/cooling, and domestic hot water. First, the energy needed in the region was designed with DesignBuilder. Then, each proposed system was modeled in Polysun software using a photovoltaic-thermal and a vertical geothermal heat exchanger. Afterward, all probable plans were evaluated and compared technically, economically, and environmentally. The results indicated that the maximum/minimum values of the coefficient of heat pump performance for direct heat exchanger and series systems were 4.39/3.87. Also, the optimal plan was introduced with 4957/10667 kWh electricity consumption/production. Besides, an economic analysis was estimated for the optimal strategy with an investment return of 7years. The designed system prevented 5089kgCO 2 emissions annually. By means of this integrating hybrid system, Sistan/Baluchestan province would become a significant renewable power plant globally, and a considerable techno-economic and environmental challenge would be dissolved in Iran. • A novel geothermal/solar hybrid system was introduced and analyzed technically, economically and environmentally. • The proposed hybrid system could supply heating/cooling/electricity demands. • One of significant challenge, non-renewable resources usage, would be dissolved in Iran by using a renewable hybrid system. • The proposed plan could reduce CO2 emissions significantly. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of reliable and green routing in a road-rail multimodal transportation network. To enhance network reliability, types of disruptions occurring simultaneously in each node and arc are identified. Additionally, carbon emission is considered a risk caused by transportation process disruptions for achieving green routing. A combination of rating methods such as DEMATEL-based Analytic Network Process (DANP) and the Combined Compromise Solution (COCOSO), along with Failure mode and effects analysis (FMEA) Criticality reliability assignment method, is used to evaluate disruptions and select a safe route from origins to destinations. The DANP method produces a ranking of sub-criteria, and the COCOSO method produces a ranking of criteria in the network. The FMEA Criticality reliability assignment method is used to assign reliability to each option. Next, the route with the highest reliability from each origin to each destination is selected. The presented model investigates a cement road-rail transportation network in Iran. After analyzing the sensitivity of criteria and sub-criteria, the results provide best routes with increased reliability and reduced emissions risk. • Identifying risks in each node and arc in the transportation network. • Prioritizing criteria, sub-criteria, and options using a mix of DANP and COCOSO ranking methods. • Assessing the reliability of each option using the FMEA Criticality method. • Selecting the best path with the highest reliability and the less carbon emission risk in each O-D pair. • Considering a case study in the cement road-rail transportation network in Iran. [ABSTRACT FROM AUTHOR]

• Multi-generation system integrated with NZEB for different climates of Iran. • Energy, exergy, exergoeconomic, economic and environmental (5E) analyses. • Dynamic supply of electrical, heating, cooling and freshwater loads. • Multi-objective optimization utilizing TOPSIS tool for different seasons. • The maximum exergy efficiency of 26.3 %, and the best payback time of 5 years. Proposing a practical multi-generational system for different climates can be the key for setting up renewable-based systems as an alternative to fossil fuels in different countries. This paper introduced a flexible renewable energy system that is capable of generating multiple forms of energy using solar energy and hydrogen storage, and can operate under diverse weather conditions across four cities in Iran. The system was equipped with a solar unit, photovoltaic panels (PV), heating and cooling units, a desalination technology, a hydrogen production unit, and a fuel cell to supply heating, cooling, electricity and freshwater loads for a residential building. Mashhad (normal), Tabriz (cold), Bandar Abbas (humid), and Yazd (hot and dry) cities were considered as different climates in Iran to suggest the best city based on the present system. Analysis and simulation were conducted, taking into account five perspectives, namely energy, exergy, exergoeconomic, economic, and environmental (5E). This was done utilizing the TRNSYS and Engineering Equation Solver (EES) packages. Multi-objective optimization was carried out to achieve the best performance using the TOPSIS method for the four cities mentioned. The system was grid-connected to sell excess power when there is no need for electricity and receive power when it is needed. Optimization showed that Bandar Abbas has the highest exergy efficiency of the system by 26.3 % and the lowest total cost rate of the whole components by 6.08 $/h. Moreover, the maximum net output power of 28.72 kW was reported in Tabriz. Environmental analysis revealed that the system had the ability to lower CO 2 emissions through the generation of clean electricity and avoiding the use of natural gas. This was particularly significant in Bandar Abbas and Yazd, where the maximum reductions in CO 2 emissions were obtained at 23.3 tons and 4.4 tons, respectively. In conclusion, the payback period for Mashhad, Tabriz, Bandar Abbas, and Yazd cities was obtained at 6.5 years, 5.8 years, 5.5 years, and 5 years, respectively. [ABSTRACT FROM AUTHOR]

Conditions governing industrial activities during and after global shocks with societal and economic transformations such as the COVID-19 pandemic have led to the loss of effectiveness of conventional approaches to dealing with uncertainties. The occurrence of sharp fluctuations in the essential parameters has left decision-makers in an unpredictable situation. Therefore, proactive efforts should be made to develop current approaches for adapting to new conditions. This paper establishes a strategic, tactical, and operational decision-making framework under the COVID-19 outbreak by developing a new uncertainty type called deep dynamic uncertainty. In the first step, a Mixed-Integer Linear Programming (MILP) model is proposed for the green and reliable closed-loop supply chain network design. The proposed model allows the decision-maker (DM) to manage and control co 2 emissions and e-waste generation. In the second step, a new three-step algorithm called Augmented Adjustable Column-Wise Robust Optimization (AACWRO) is first proposed. Then, by combining the proposed column-wise uncertainty with multi-stage stochastic programming (MSSP) approach, deep dynamic uncertainty is theorized for modeling the demand uncertainty under pandemic conditions. The model's performance under deep dynamic uncertainty has been carefully investigated based on the real ventilator and infusion pump supply chain network in Iran. The model under deep dynamic uncertainty, while maintaining tractability and adjustability, provides flexibility in entering data into the problem and significantly increases the coverage of modeling uncertainties. The results clearly demonstrate the efficiency of the proposed approach. The model under deep dynamic uncertainty at all levels of conservatism has on average 42.96% lower cost and 32% higher stability than the MSSP model. • Green and reliable closed-loop medical device supply chain network are studied. • A mechanism is proposed for the management of co 2 emission and e-waste generation. • Stochastic programming and novel robust optimization are considered simultaneously. • Deep dynamic uncertainty is introduced to deal with COVID-19 uncertainties. • The model efficiency is evaluated based on the ventilator and infusion pump industry. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic causes a severe threat to human lives worldwide. Convalescent plasma as supportive care for COVID-19 is critical in reducing the death rate and staying in hospitals. Designing an efficient supply chain network capable of managing convalescent plasma in this situation seems necessary. Although many researchers investigated supply chains of blood products, no research was conducted on the planning of convalescent plasma in the supply chain framework with specific features of COVID-19. This gap is covered in the current work by simultaneous regular and convalescent plasma flow in a supply chain network. Besides, due to the growing importance of environmental problems, the resulting carbon emission from transportation activities is viewed to provide a green network. In other words, this study aims to plan the integrated green supply chain network of regular and convalescent plasma in the pandemic outbreak of COVID-19 for the first time. The presented mixed-integer multi-objective optimization model determines optimal network decisions while minimizing the total cost and total carbon emission. The Epsilon constraint method is used to handle the considered objectives. The model is applied to a real case study from the capital of Iran. Sensitivity analyses are carried out, and managerial insights are drawn. Based on the obtained results, product demand impacts the objective functions significantly. Moreover, the systems' total carbon emission is highly dependent on the flow of regular plasma. The results also reveal that changing transportation emission unit causes significant variation in the total emission while the total cost remains fixed. [ABSTRACT FROM AUTHOR]

Environmental pollution is a serious threat to the sustainable development of Middle East countries, especially Iran. Therefore, in this article was analyzed the decoupling relationship between CO2 emissions energy-related and economic growth in 6 Middle East countries in period 1990-2019. First, CO2 emissions driving mechanisms were quantified using Logarithmic Mean Divisia Index (LMDI) method, and then decomposed into factors of CO2 emission coefficient, energy intensity, economic activity and population. The decoupling state findings using the Tapio model show that population and economic activities factors were main drivers of CO2 emissions in these countries. The results of decoupling elasticity showed that Iran was in a weak decoupling state in period of 1990-1999 and 2015-2019; It means the simultaneous increase of economic growth and carbon emissions, of course, by faster economic growth; Iran had also an expansive coupling state in period of 2000-2014, which indicates that CO2 emissions increase along economic growth. The UAE and Saudi Arabia have reached an ideal situation in recent years. These countries have moved from a negative decoupling and expansive coupling state to a strong decoupling state, where economic growth has been accompanied by a reduction in carbon emissions. The Kuwait and Turkey have been in weak decoupling and negative expansive decoupling states in the last 3 decades, in which economic growth was accompanied by an increase in carbon emissions. At the beginning, the Egypt has changed to a weak decoupling state and then moved to an expansive negative decoupling state. [ABSTRACT FROM AUTHOR]

This study seeks to address pertinent economic and environmental issues associated with natural gas flaring, especially for the world's leading natural gas flaring economies (i.e. Russia, Iraq, Iran, the United States, Algeria, Venezuela, and Nigeria). By applying relevant empirical panel and country-specific approaches, the study found that fuel energy export positively impacts economic growth with elasticity of ~ 0.22 to ~ 0.24 for the panel examination. It is further revealed that environmental quality in the panel is hampered by increase in economic growth, gas flaring, fuel energy export, and urbanization. Moreover, for the country-wise inference, government quality desirably moderates economic and environmental aspects of gas flaring in Venezuela and Nigeria, and in Russia and Iran respectively. However, government quality moderates gas flaring to cause economic downturn in the USA. Additionally, economic growth increased with increase in urbanisation (in Iraq and the USA), gas flaring (in Iran and the USA), government quality (only in the USA), and fuel energy export (only in Algeria) while economic growth downturn is due to increase urbanisation in Russia and the USA, increase in fuel energy export in the USA, and increase in government quality in Russia. Meanwhile, environmental quality is worsened through intense carbon dioxide emission from increased urbanisation activity (in Iraq, Iran, Algeria, and Nigeria), increased fuel energy export (in Nigeria), increased natural gas flaring (in Algeria and Nigeria), increased GDP (in Russia, Iran, USA, Algeria, and Venezuela), and high government quality (in Iran). Interestingly, the result revealed that increase in GDP (in Nigeria), increase in urbanisation (in the USA), and increase in gas flaring (in Algeria and Nigeria) dampens environmental quality. Importantly, this study offers policy insight into sustainable approaches in natural gas production, government effectiveness, and regulatory quality. [ABSTRACT FROM AUTHOR]

Energy subsidies can incentivise the overconsumption of energy resources and contribute to other economic or social distortions. In this paper, an ex-post analysis is presented that explores the extent to which electricity subsidy reform could have reduced Iran's energy demand during the period 1984–2017. It also quantifies the techno-economic and environmental benefits that could have been achieved through such reforms. A time-varying econometric model is linked to an energy systems optimisation model. The former estimates electricity demand under different subsidy removal scenarios, and the latter identifies the cost-optimal generation mix to meet the demand. The results of cost-optimal transition pathways under subsidy removal scenarios are compared with the real-world energy system development during the study horizon. The comparison reveals that the subsidy reform could have reduced the total cumulative electricity consumption by 22%. Renewable share in power generation could have increased from 5% to 15%. Moreover, the reform combined with a cost-optimal generation pathway would have saved $69 billion and avoided 944 million tons of CO 2 emissions. The analysis also shows that every five-year delay in subsidy removal causes about 100 million tons of additional CO 2 emissions. Finally, the paper presents lessons learnt for future energy modelling. • An ex-post analysis quantifies the benefits of energy subsidy reform in the power sector. • The total cumulative electricity consumption could have been reduced by 22%. • Renewable share in power generation could have tripled. • Subsidy reforms combined with cost-optimal generation could have saved $69 billion. • The paper presents lessons learnt for future energy modelling. [ABSTRACT FROM AUTHOR]

A large amount of the Iranian energy demand is related to the building sector, mainly due to its obsolescence. In this paper, a second-skin system has been implemented as a retrofit action for an office building, evaluating the effect of a tensile material as second-skin in terms of primary energy saving, carbon dioxide equivalent emissions, and simple payback period. The analysis was carried out through numerical simulations across a whole year and for four Iranian cities (Tabriz, Teheran, Yazd, and Bandar Abbas) in four different climates (cold, temperate, hot-dry, and hot-wet), and with the building aligned at either north-south or east-west. Moreover, an economic analysis was carried out suggesting different incentive policies to promote building energy refurbishment. The simulation results highlighted a favorable orientation for buildings in Iran, suggesting a guideline for new constructions. Indeed, the best results were achieved for an east-west orientation of the building (up to a primary energy saving of 13.6% and reduction of carbon dioxide equivalent emissions of 45.5 MgCO2,eq, in Yazd), with a decrease of the annual specific total (cooling and thermal) energy demand of 37.9 kWh/m2/year. The simple payback period values were also lower in the east-west orientation than the north-south one. [ABSTRACT FROM AUTHOR]

In Generation Expansion Planning (GEP), the power plants lifetime is one of the most important factors which to the best knowledge of the authors, has not been investigated in the literature. In this article, the power plants lifetime effect on GEP is investigated. In addition, the deep learning-based approaches are widely used for time series forecasting. Therefore, a new version of Long short-term memory (LSTM) networks known as Bi-directional LSTM (BLSTM) networks are used in this paper to forecast annual peak load of the power system. For carbon emissions, the cost of carbon is considered as the penalty of pollution in the objective function. The proposed approach is evaluated by a test network and then applied to Iran power system as a large-scale grid. The simulations by GAMS (General Algebraic Modeling System, Washington, DC, USA) software show that due to consideration of lifetime as a constraint, the total cost of the GEP problem decreases by 5.28% and 7.9% for the test system and Iran power system, respectively. [ABSTRACT FROM AUTHOR]

The volume and structure of household's consumption have an important role in energy consumption and related air pollutant emissions. This study extended the input–output structural decomposition analysis (I–O SDA) to investigate the effect of changes in the volume and structure of household consumption in urban and rural areas on indirect CO2 emission in Iran during 2011–2016. The results showed that total consumption of urban households have played a major role in increasing indirect carbon dioxide emissions. At the sectoral level, the sectors of "Electricity" and "Transport" are the most contributors of increasing the carbon dioxide emission in Iran during study period. Changes in consumption structure in both urban and rural areas have reduced carbon emissions. Changes in consumption structure in urban area have led to decrease of 41.94 Mt–CO2. The reduction of carbon dioxide emissions due to changes in consumption structure in rural area was equal to 25.76 million tons. [ABSTRACT FROM AUTHOR]

The synergic use of satellite data at moderate spatial resolution (i.e., 20–30 m) from the new Collection 2 (C2) Landsat-8/9 (L8/9) Operational Land Imager (OLI) and Sentinel-2 (S2) Multispectral Instrument (MSI) provides a new perspective in the remote sensing applications for gas flaring (GF) identification and monitoring, thanks to a significant improvement in the revisiting time (up to ~3 days). In this study, the daytime approach for gas flaring investigation (DAFI), recently developed for identifying, mapping and monitoring GF sites on a global scale using the L8 infrared radiances, has been ported on a virtual constellation (VC) (formed by C2 L8/9 + S2) to assess its capability in understanding the GF characteristics in the space-time domain. The findings achieved for the regions of Iraq and Iran, ranked at the second and third level among the top 10 gas flaring countries in 2022, demonstrate the reliability of the developed system, with improved levels of accuracy and sensitivity (+52%). As an outcome of this study, a more realistic picture of GF sites and their behavior is achieved. A new step aimed at quantifying the GFs radiative power (RP) has been added in the original DAFI configuration. The preliminary analysis of the daily OLI- and MSI-based RP, provided for all the sites by means of a modified RP formulation, revealed their good matching. An agreement of 90% and 70% between the annual RPs computed in Iraq and Iran and both their gas-flared volumes and carbon dioxide emissions were also recorded. Being that gas flaring is one of the main sources of greenhouse gases (GHG) worldwide, the RP products may concur to infer globally the GHGs GF emissions at finer spatial scales. For the presented achievements, DAFI can be seen as a powerful satellite tool able to automatically assess the gas flaring dimension on a global scale. [ABSTRACT FROM AUTHOR]

Orosi is a traditional Iranian window which is made of colorful glasses embedded in wooden latticed frame. This window was designed in traditional courtyard houses located in central Iran and behaved as a passive strategy to control light intensity, provide privacy and aesthetics. However, this type of window is rarely used nowadays due to a lack of acoustic and thermal insulation and high construction costs. This paper explores the possibility of using double-glazed window with colored microalgae inspired by Orosi to improve its light performance and energy consumption compared to the traditional Orosi window design A series of experimental tests and a set of computer simulations are conducted to evaluate and compare the two designs. The experimental results showed that while the light intensity in the indoor space is approximately equal to the corresponding magnitude measured for the Orosi window, the inside temperature witnessed a small increase approximately 1° Celsuis. Likewise, relative humidity, which has a significant impact on thermal comfort perceived by occupants, increased from 25% to nearly 70% in the algae window. Based on results obtained, nearly 500 ppm of CO 2 was absorbed due to the low height of the photobioreactor. Results of computer simulations indicated that the amount of annual energy consumption in terms of cooling electric energy, heating fuel energy and electric equipment within the two simulated models were similar. However, the best performance of the colored algae window in terms of UDI was observed when the microalgae concentration was between 40% and 50%. • For the first time, a colored microalgae window inspired by Iranian Orosi is evaluated as an energy efficient design. • Using this window could result in reviving Iranian architecture and absorb CO 2 emissions and decrease energy consumption. • Indoor lux levels are found to be very similar for both designs. • Indoor temperature and RH value of the double-glazed algae photobioreactor window was higher. • Energy consumption for heating and cooling were similar for both window designs. [ABSTRACT FROM AUTHOR]

The primary aim of this study is that whether Granger causality (GC) among CO2 emissions, energy consumption (EC) and economic growth (EG) in different regimes in Iran is similar and sustainable. We answer this question using Markov Switching Vector Autoregressive (MS-VAR) approach and the quarterly data from 1970Q1 to 2015Q4. The findings show that the causal relationship switches among these variables in different regimes. In the first regime, the results show a positive unilateral GC from EG to EC. In the second regime, the study shows a negative GC from EC to EG, and a positive causality from EG to EC, and a negative unilateral causality from CO2 emissions to EG. The results indicate no causality from EG and EC to CO2 emissions in the first and second regimes. The results further show that the probability of sustainability in this first regime, where the rate of EG is at a low level but the amounts of EC and CO2 emissions are at a high level, will be high compared to the second regime. These findings call for more attention to the various effects of these variables on each regime before the policy implementation. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate the impacts of economic growth, energy consumption, and the economic globalization process on ecological footprints in the top 10 countries that cause the highest carbon dioxide emissions in the world. The analyses were conducted on annual observations from 1970 to 2017 (a different range for each country) employing the Fourier bootstrap ARDL cointegration method developed by Yilanci et al. (2020) and the Fourier bootstrap Toda–Yamamoto causality method developed by Nazlioglu et al. (2016). In the cointegration approach, an additional F-test provides better insights to define degenerate cases and the bootstrap test performance is powerful than the asymptotic test. In this context, Fourier bootstrap ARDL test results revealed that there is a long-term relationship between ecological footprint and economic growth, energy consumption, and economic globalization in seven countries—namely, Canada, China, Germany, India, Indonesia, Iran, and Saudi Arabia. According to long-run coefficients, in general, economic growth and energy consumption have negative effects on ecological footprint, whereas economic globalization has a positive effect on the ecological footprint for these countries. To evaluate it more specifically, (i) real gross domestic product per capita has positive and statistically significant coefficients on the ecological footprint in China, India, Indonesia, Iran, and Saudi Arabia, except for Germany. (ii) Energy consumption per capita also has positive and statistically significant coefficients on the ecological footprint in China, Germany, Iran, and Saudi Arabia, except for Indonesia. (iii) Finally, the economic globalization process has negative and statistically significant coefficients on the ecological footprint in Canada, China, India, and Saudi Arabia, except for Indonesia. On the other hand, Fourier bootstrap Toda–Yamamoto causality test results show a mixed character. Governments should take action to reduce the negative effects of the climate crisis as immediate as possible, which has been widely expressed recently. Among these, increasing the use of renewable energy sources and new carbon-free technologies in the production process appears as important policy tools. [ABSTRACT FROM AUTHOR]

Greenhouse gas (GHG) emissions contribute considerably to global warming and climate change. Since energy systems notably influence GHG emissions, such emissions can be modeled at the national level based on the energy sources utilized by a country. Economic activity also affects GHG emissions. In this work, an Artificial Neural Network (ANN) approach, Group Method of Data Handling (GMDH), is used for determining emissions of carbon dioxide, the most significant GHG, on the basis of shares of various energy sources used as primary energy supply and GDP as an indicator of economic activity. Five countries are considered as case studies: Iran, Kuwait, Qatar, Saudi Arabia, and United Arab Emirates (UAE). Comparing the results achieved by the developed model and actual quantities shows that the ANN model has acceptable accuracy for predicting CO2 emissions. The average absolute relative error and the R-squared values of the GMDH model are 2.3% and 0.9998, respectively. These values demonstrate the precision of the model in forecasting emissions of CO2. [ABSTRACT FROM AUTHOR]

One thing that should be considered in environmental considerations and climate change is the transportation sector's contribution to producing carbon dioxide. Unfortunately, in developing countries such as Iran, due to high tariff support, manufacturers have no incentive to improve the combustion quality of their products. Most likely, significant restrictions on CO2 emissions will be applied in the coming years, and companies whose activities or products are related to high-level greenhouse gas emissions will be affected by these restrictions. Therefore, due to the application of these restrictions, investors are most concerned about the risk associated with the return of purchased shares. Considering these cases, it can be expected that the risk related to carbon emissions will be reflected in the yield level and, thus, the stock price. Therefore, the present study deals with the effect of CO2 gas emissions on the market value, price and stock returns of Iranian automobile companies. The data collected as tabular data include six automobile companies from 2018–2019. By conducting various tests and panel data estimations, especially the dynamic panel data method, it was determined that CO2 emissions reduce stock prices, returns and market value of automobile companies. In addition, the results of the causality test indicate that the direction of causality is only from CO2 emissions to stock returns. [ABSTRACT FROM AUTHOR]

With an accelerated process of urbanization and improved standards of living, metropolises have a great responsibility and high potential to mitigate the global carbon emissions and Shiraz city is not an exception. There has been no comprehensive understanding of the carbon emissions in this area. So, the present study aimed to evaluate the environmental performance and trend prediction for five sub-sectors of urban management, namely transportation, municipal buildings, residential buildings, municipal waste disposal, and wastewater in Shiraz metropolis, Iran. In this study, the first section evaluated the environmental emissions, and in the second section, CO2-eq emissions were predicted based on two factors, population growth rate and GDP per capita, for Shiraz metropolis, Iran. For this purpose, the CURB tool was used to calculate the CO2-eq of each sector. Data were collected from the 2018 Shiraz Municipality statistical yearbook, published articles related to each sector, subsector annual statistical reports, and the World Bank, OECD, and IPCC. The results showed that the residential and urban transport sectors had the highest impact on total CO2-eq emissions. The residential sector accounted for the highest share (2,233,532 t CO2-eq) (60%), followed by the urban transport sector (1,169,927 t CO2-eq) (31%). The results of the second section indicated that 5,881,360 tons of carbon dioxide equivalent can be emitted in this city in the future (in 2035). The results indicated that Shiraz city does not have a significant share in greenhouse gas emissions compared with similar cities from two perspectives of development level and climate similarity index. [ABSTRACT FROM AUTHOR]

Fifteen million tons of bread is annually produced in Iran of which the 80% of share in production belongs to traditional bakeries. The present study examines the aspects of the energetic, economic, and environmental impacts of production of Iranian breads (Barbari, Lavash, and Sangak). The results showed that energy demand of a typical baking process of Iranian breads is 22.93–26.08 MJ kg−1. The annual energy utilization of these bakeries is 239.57 TJ, accompanied with 13,308 ton year−1 of CO2 emissions. Sangak bread production had the highest energy efficiency, energy productivity, and the lowest rejected energy. In terms of economic aspects, the highest net income, profit to cost, and economic productivity, were related to Barbari bread production. Sangak bread production had the least environmental impacts. Lavash bread production, although it is the thinnest bread, had the highest energy consumption, was responsible for emitting the largest share of Greenhouse Gas (GHG) to the atmosphere and it had the lowest economic return. The flour was the most influential input on the energy efficiency, cost, and GHG emissions among the three examined types of bread production. Therefore, improving wheat cultivars and flour production process, may reduce the energy consumption and the GHG emissions in the bread industry. [ABSTRACT FROM AUTHOR]

Industrial plants in Iran, similar to many other developing countries, use diesel or natural gas generators mainly as backup power during a grid outage. Depending on the electricity network configuration, these emergency generators might be able to deliver electricity to the grid and thereby contribute to demand response (DR) programs. Hence, Iran's Ministry of Energy (MOE) has policies and incentives to promote the use of emergency generators during peak hours. This paper investigates the economic and carbon dioxide emission implications of such DR policies by the MOE. Results show that the current policy promotes diesel generators that are economically beneficial to the companies but are more carbon intensive than the natural gas generators. To mitigate the climate change with a minimum impact on the economic interest of the companies, the future DR policies can be amended. The revised incentive structure proposed by this study is simple but effective and ensures that the lower carbon emitting natural gas generators would become more economically attractive than diesel generators. Following the proposed approach to set the incentives, the natural gas generators would be more beneficial according to the MOE policy in 2019 if the difference between the diesel incentive and natural gas incentive was less than 711 Rial. • Current Iranian demand response programs promote fuels that are more pollutant. • Investing in diesel generators is more profitable compared to natural gas gensets. • Difference between diesel and natural gas incentives should be less than 711 Rial. [ABSTRACT FROM AUTHOR]

Over the last few years, economic uncertainty has become a global concern. Not only has its impact on economic activities, but there are pieces of evidence that show uncertainty can be the reason for CO2 emissions. It is also expected that the economic policy uncertainty may decrease or delay economic production, which may lead to a reduction in carbon emissions. Furthermore, uncertainty may decrease friendly environment policies and budgets, which cause an increase in carbon emissions. Thus, there may be an asymmetric relationship between economic uncertainty and the amount of CO2 emissions. This study investigates the effects of economic policy uncertainty and economic activity on carbon emission applying a nonlinear autoregressive distributed lag (NARDL) cointegration approach in Iran between 1971 and 2018. Findings show that both policy uncertainty and economic growth contribute to CO2 emissions. The negative and positive shocks of GDP and uncertainty index on CO2 emissions in both the short run and long run are significant. Based on the results, there is an asymmetric effect of economic production on CO2 emissions in Iran. The results of analyzing asymmetric effects of economic uncertainty show a symmetric relationship between uncertainty index and CO2 emissions, in a way that a shock in the uncertainty index lowers carbon emission. To sum up, since uncertainty may affect the analysis of carbon emissions incorrectly, some environmental policies such as allocating a budget for R&D on clean energy and environmental taxes must be implemented. [ABSTRACT FROM AUTHOR]

An increasing amount of CO2 emissions from the household sector of Iran led us to analyze the inequality and understand the possible driving force behind the CO2 emissions. The study of inequality provides information to policy-makers to point policies in the right direction. By considering the differences in the socio-economic factors of provinces, the study aims to analyze the inequality in CO2 emissions and different kinds of energy consumption, including oil, gas and electricity, for the household sector of Iran's provinces between 2000 and 2017. For this aim, the Theil index and Kaya factor, as a simple and common method, were considered to evaluate the inequality in both CO2 emissions and energy consumption, and determine the driving factor behind CO2 emissions. According to the results, inequality in oil and natural gas consumption were increasing, electricity was almost constant; however, CO2 emissions experienced a decreasing trend for the study period. The Theil index changed from 0.4 to 0.65 for oil, from 0.18 to 0.22 for natural gas, from 0.17 to 0.15 for electricity, and from 0.2 to 0.14 for CO2 emissions between 2001 and 2017. In addition, the results of the inequality study indicated that most of the inequalities belong to within-group inequalities in energy consumption and CO2 emissions. The results of the Kaya factor indicate that the second factor, energy efficiency, with a 0.21 value was the main driving factor of inequalities in CO2 emissions; however, the first factor, energy consumption, can be a potential factor for inequality in the following years, as it increased from 0.00 to 0.11 between 2001 and 2017. It seems that by removing the energy subsidy policy in 2010 and 2013, low-standard and energy-wasting old vehicles were the most effective factors of energy inefficiency in the household sector, which need more accurate policy-making. [ABSTRACT FROM AUTHOR]

Background: Carbon emissions and global warming have increased as a result of population growth and greater usage of fossil fuels. Finding a long-term replacement for fossil fuels, such as biofuels, has become a major problem for energy supply management in recent years. Sustainability must be addressed as a key problem in building biofuel supply chains (BSCs), given the pressing need for societies to limit environmental consequences and promote social responsibility of company activities. Various modeling frameworks have been established so far to design a BSC. At the same time, no research exists that examines both the sustainable development paradigm and the influence of various carbon regulatory policies on the strategic and operational decisions made by BSCs. Methods: This study develops a multi-objective, multi-period, multi-echelon BSC from switch grass regarding the economic, environmental and social aspects of sustainability. Four carbon policies are taken into account when assessing the environmental aspect: the carbon cap, the carbon tax, the carbon trade, and the carbon offset. To solve the multi-objective model, the fuzzy interactive programming method is used, and the fuzzy best–worst method is used to weight the social objective components. Results: An actual case study in Iran is studied to demonstrate the model's applicability. Under various carbon policies, different network configurations are obtained based on the location of switch grass resources and installed facilities. Biofuel production and transportation activities account for approximately 28% and 51% of total carbon emissions, respectively, according to numerical results. Furthermore, these activities account for roughly 62% of overall expenses. In the suggested case study, implementing the carbon trade policy reduces carbon emissions by more than 30% while increasing total profit by about 27%. In comparison to other policies, the carbon trade policy has a substantial impact on enhancing social considerations. Overall, the carbon trade policy can greatly improve the economic and environmental components of sustainability without significantly decreasing in the social sustainability. Conclusions: The proposed model can assist policymakers and governments in simultaneously optimizing BSC profitability, carbon emission reduction, and social concern. Highlights: Developing a multi-period and multi-objective model for BSC design. Considering the proposed model's economic, environmental, and social components of the sustainable development paradigm. Considering the effects of various carbon regulatory policies on strategic and operational decisions. Weighting social indicators using the fuzzy best-worth method. Validate the proposed model using a real-life case study in Iran. [ABSTRACT FROM AUTHOR]

The tourism sectors consume a high amount of electrical power, which in most cases is supplied by the electrical grid and diesel generator. As a result, the electricity supply of large-scale tourism sectors is an important challenge in many countries. In current study, the feasibility study for applying the hybrid renewable energy systems to provide the power demand in social areas is investigated. Since Iran has a lot of tourism areas with a high amount of electricity consumption, a popular and crowded tourism sector in the Qom (a city in the center of Iran) is selected as the case study. The electricity consumption of this social area is found to be 23,808.91 kWh/day, which in the current system is supplied by the electricity grid. Also, the values of cost of energy and carbon dioxide emissions of current system are calculated to be 0.0931$/kWh and 5,741,214 kg/year, respectively. Regarding the available renewable resources of Qom city and the space limitations of this tourism sector, several combined renewable scenarios are simulated and assessed applying the HOMER Pro simulator. In continue, to identify the optimal scenarios, the techno–economic–environmental evaluation is implemented. The hybrid photovoltaic (PV)/wind turbine (WT)/battery (Bat)/diesel generator (DG)/biogas generator (BG), and grid/PV/WT are found as the optimum configurations for the off-grid and grid-connected systems, respectively. It was found that the Grid/PV/WT has a net present cost of 6.63 M$ and a cost of energy of 0.0234 $/kWh. Also, the cost of energy and net present cost of hybrid PV/WT/Bat/DG/BG are accounted for 0.1251$/kWh and 18.1 M$, respectively. By using this stand-alone system instead of current system, the CO2 emissions reduce by 61.87% (2,189,231 kg/year). In following, to assess the effects of load growth and PV degradation on system performance, the multi-year module of this software is employed. Based on the obtained findings, by applying the hybrid PV/WT/Bat/DG/BG instead of the current system, the contribution of emissions penalties to the overall net present cost diminishes from 15.47% to 0.73%. Finally, the heat map sensitivity analyses are applied to the economic and environmental parameters. [ABSTRACT FROM AUTHOR]