Murat Kucukvar

A macro-level decision analysis of wind power as a solution for sustainable energy in the USA

This study aims to quantify the socio-economic and environmental impacts of producing electricity by wind power plants for the US electricity mix. To accomplish this goal, all direct and supply chain-related impacts of different onshore and offshore wind turbines are quantified using a hybrid economic input-output-based triple bottom line (TBL) life cycle assessment model. Furthermore, considering TBL sustainability implications of each onshore and offshore wind energy technology, a multi-criteria decision-making tool which is coupled with Monte Carlo simulation is utilised to find the optimal choice of onshore and offshore wind energy. The analysis results indicate that V90-3.0 MW wind turbines have lower impacts than V80-3.0 MW for both socio-economic and environmental indicators. The Monte Carlo simulation results reveal that when environmental issues are more important than socio-economic impacts, V90-3.0 MW offshore is selected among the alternatives.

Economic Input–Output Based Sustainability Analysis of Onshore and Offshore Wind Energy Systems

According to the U.S. Department of Energy’s wind energy scenario, 20% share of the U.S. energy portfolio is to come in from wind power plants by the year 2030. This research aims to quantify the direct and supply chain related indirect environmental impacts of onshore and offshore wind energy technologies in the United States. To accomplish this goal, a hybrid life cycle assessment (LCA) model is developed. On average, offshore wind turbines produce 48% less greenhouse gas emissions per kWh produced electricity than onshore wind turbines. It is also found that the more the capacity of the wind turbine, the less the environmental impact when the turbine generates per kWh electricity.

Eco-Efficiency of Construction Materials: Data Envelopment Analysis

Sustainability assessment tools are critical in the process of achieving sustainable development. Eco-efficiency has emerged as a practical concept that combines environmental and economic performance indicators to measure the sustainability performance of different product alternatives. In this paper, an analytical tool that can be used to assess the eco-efficiency of construction materials is developed. This tool evaluates the eco-efficiency of construction materials by using data envelopment analysis, a linear programming-based mathematical approach. Life-cycle assessment (LCA) and life-cycle cost (LCC) are utilized to derive the eco-efficiency ratios, and data envelopment analysis (DEA) is used to rank material alternatives. Developed mathematical models are assessed by selecting the most eco-efficient exterior wall finish for a building. Percent improvement analysis was carried out to investigate target environmental effect categories that need more reduction to reach 100% eco-efficiency. Through this study, the goal is to show that DEA-based eco-efficiency assessment model could be used to evaluate alternative construction materials and offer vital guidance for decision makers during material selection. DOI: 10.1061/ (ASCE)CO.1943-7862.0000484.

Integration of system dynamics approach toward deepening and broadening the life cycle sustainability assessment framework: a case for electric vehicles

PurposeQuantitative life cycle sustainable assessment requires a complex and multidimensional understanding, which cannot be fully covered by the current portfolio of reductionist-oriented tools. Therefore, there is a dire need on a new generation of modeling tools and approaches that can quantitatively assess the economic, social, and environmental dimensions of sustainability in an integrated way. To this end, this research aims to present a practical and novel approach for (1) broadening the existing life cycle sustainability assessment (LCSA) framework by considering macrolevel environmental, economic, and social impacts (termed as the triple bottom line), simultaneously, (2) deepening the existing LCSA framework by capturing the complex dynamic relationships between social, environmental, and economic indicators through causal loop modeling, (3) understanding the dynamic complexity of transportation sustainability for the triple bottom line impacts of alternative vehicles, and finally (4) investigating the impacts of various vehicle-specific scenarios as a novel approach for selection of a macrolevel functional unit considering all of the complex interactions in the environmental, social, and economic aspects.MethodsTo alleviate these research objectives, we presented a novel methodology to quantify macrolevel social, economic, and environmental impacts of passenger vehicles from an integrated system analysis perspective. An integrated dynamic LCSA model is utilized to analyze the environmental, economic, and social life cycle impact as well as life cycle cost of alternative vehicles in the USA. System dynamics modeling is developed to simulate the US passenger transportation system and its interactions with economy, the environment, and society. Analysis covers manufacturing and operation phase impacts of internal combustion vehicles (ICVs), hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs). In total, seven macrolevel indicators are selected; global warming potential, particulate matter formation, photochemical oxidant formation, vehicle ownership cost, contribution to gross domestic product, employment generation, and human health impacts. Additionally, contribution of vehicle choices to global atmospheric temperature rise and public welfare is investigated.Results and discussionBEVs are found to be a better alternative for most of sustainability impact categories. While some of the benefits such as contribution to employment and GDP, CO2 emission reduction potential of BEVs become greater toward 2050, other sustainability indicators including vehicle ownership cost and human health impacts of BEVs are higher than the other vehicle types on 2010s and 2020s. While the impact shares of manufacturing and operation phases are similar in the early years of 2010s, the contribution of manufacturing phase becomes higher as the vehicle performances increase toward 2050. Analysis results revealed that the US transportation sector, alone, cannot reduce the rapidly increasing atmospheric temperature and the negative impacts of the global climate change, even though the entire fleet is replaced with BEVs. Reducing the atmospheric climate change requires much more ambitious targets and international collaborative efforts. The use of different vehicle types has a small impact on public welfare, which is a function of income, education, and life expectancy indexes.ConclusionsThe authors strongly recommend that the dynamic complex and mutual interactions between sustainability indicators should be considered for the future LCSA framework. This approach will be critical to deepen the existing LCSA framework and to go beyond the current LCSA understanding, which provide a snapshot analysis with an isolated view of all pillars of sustainability. Overall, this research is a first empirical study and an important attempt toward developing integrated and dynamic LCSA framework for sustainable transportation research.

Evaluating environmental impacts of alternative construction waste management approaches using supply-chain-linked life-cycle analysis

Waste management in construction is critical for the sustainable treatment of building-related construction and demolition (C&D) waste materials, and recycling of these wastes has been considered as one of the best strategies in minimization of C&D debris. However, recycling of C&D materials may not always be a feasible strategy for every waste type and therefore recycling and other waste treatment strategies should be supported by robust decision-making models. With the aim of assessing the net carbon, energy, and water footprints of C&D recycling and other waste management alternatives, a comprehensive economic input–output-based hybrid life-cycle assessment model is developed by tracing all of the economy-wide supply-chain impacts of three waste management strategies: recycling, landfilling, and incineration. Analysis results showed that only the recycling of construction materials provided positive environmental footprint savings in terms of carbon, energy, and water footprints. Incineration is a better option as a secondary strategy after recycling for water and energy footprint categories, whereas landfilling is found to be as slightly better strategy when carbon footprint is considered as the main focus of comparison. In terms of construction materials’ environmental footprint, nonferrous metals are found to have a significant environmental footprint reduction potential if recycled.

Sustainability Assessment of U.S. Construction Sectors: Ecosystems Perspective

AbstractThe U.S. construction industry accounts for approximately 4% of the gross domestic product. Although quantifying and analyzing the cumulative ecological resource consumption of the construction industry is of great importance, it has not been studied sufficiently. This paper aims to account for the total ecological resource consumption of the construction industry, including its supply chains. This analysis is achieved by using an ecologically based life-cycle assessment model. The impacts on the ecosystem were calculated on the basis of the economic data in terms of cumulative mass, energy, industrial exergy, and ecological exergy. U.S. construction sectors are holistically evaluated by using various sustainability metrics, such as resource intensity, efficiency ratio, and loading ratio. Total ecological exergy values were generally found to be larger for the sectors with higher economic output values. Heavy construction industry sectors, including construction and maintenance of highways, bridge...

Integrating expert weighting and multi-criteria decision making into eco-efficiency analysis: the case of US manufacturing

In this paper, the effect of weighting strategies on sustainability performance assessment is addressed. Eco-efficiency is used as the main metric for sustainability performance evaluation. An integrated input-output life cycle assessment (LCA) and multi criteria decision making (MCDM) approach is employed. The US manufacturing sectors’ LCA results are used in conjunction with the proposed MCDM framework to perform the eco-efficiency evaluation of 276 US manufacturing sectors. Five environmental impact categories are considered as the negative factors, namely: greenhouse gas emissions, energy use, water withdrawal, hazardous waste generation and toxic releases into air and the economic output of each manufacturing sector is considered to be the positive output. To study the overall impact of different weighting strategies; twenty weighting scenarios are designed. Five pairs of weights considered for the overall economic versus environmental impacts along with four specific weighting strategies based on Harvard, SAB, EPP and Equal weighting for each pair. According to the results of the statistical analysis, it is concluded that the weighing strategies applied to the overall environmental impacts and economic outputs cause statistically significant differences in the eco-efficiency scores.

Environmental footprint analysis of on-shore and off-shore wind energy technologies

Wind energy technologies have gained a tremendous interest worldwide to mitigate the environmental impacts related to power generation. In this study, we assess on-shore and off-shore by tracing all of the economy-wide supply chain requirements of wind power plants. The wind turbines consist of two onshore (V80-2.0 MW and V90-3.0 MW) and two offshore (V80-2.0 MW and V90-3.0 MW) turbines, all manufactured by the Vestas Wind Systems A/S.

From Green Buildings to Green Supply Chains: An Integrated Input Output Life Cycle Assessment and Optimization Framework for Carbon Footprint Reduction Policy Making

The purpose of this paper is to focus on tracing GHG emissions across the supply chain industries associated with the US residential, commercial and industrial building stock and provides optimized GHG reduction policy plans for sustainable development.,A two-step hierarchical approach is developed. First, Economic Input-Output-based Life Cycle Assessment (EIO-LCA) is utilized to quantify the GHG emissions associated with the US residential, commercial and industrial building stock. Second, a mixed integer linear programming (MILP) based optimization framework is developed to identify the optimal GHG emissions’ reduction (percent) for each industry across the supply chain network of the US economy.,The results indicated that “ready-mix concrete manufacturing”, “electric power generation, transmission and distribution” and “lighting fixture manufacturing” sectors were found to be the main culprits in the GHG emissions’ stock. Additionally, the majorly responsible industries in the supply chains of each building construction categories were also highlighted as the hot-spots in the supply chains with respect to the GHG emission reduction (percent) requirements.,The decision making in terms of construction-related expenses and energy use options have considerable impacts across the supply chains. Therefore, regulations and actions should be re-organized around the systematic understanding considering the principles of “circular economy” within the context of sustainable development.,Although the literature is abundant with works that address quantifying environmental impacts of building structures, environmental life cycle impact-based optimization methods are scarce. This paper successfully fills this gap by integrating EIO-LCA and MILP frameworks to identify the most pollutant industries in the supply chains of building structures.

Congestion Relief Based on Intelligent Transportation Systems in Florida: Analysis of Triple Bottom Line Sustainability Impact

With the dramatic increase of traffic volume, traffic congestion has become a topic of considerable interest in the United States. Congestion has resulted in enormous economic and environmental losses, and the use of intelligent transportation systems (ITS) has been found to be an effective solution to relieve congestion in urbanized areas. The study presented in this paper aimed to advance the body of knowledge on sustainability impacts through a triple bottom line (TBL) evaluation of congestion relief in Florida. Rather than consider only the direct economic benefits as in traditional projects, this study strove to fill the gap for decision makers in the analysis of sustainability impacts from a holistic perspective. A critical approach to this research was to include both the direct and the indirect environmental, economic, and ecologic impacts associated with the chain of supply paths of ITS. To meet this goal, economic input-output tables, published by the Bureau of Economic Analysis, were linked to various TBL sustainability indicators to gain better insight into the sustainability impact of congestion relief. Study results indicated that 1.38 E+05 tons of greenhouse gas emissions (tons of carbon dioxide equivalent) and 3.00 E+04 global hectares of carbon dioxide uptake land were saved in Florida in 2010. Moreover, annual delay reduction costs savings were