Environmental sustainability benchmarking of the U.S. and Canada metropoles:an expert judgment-based multi-criteria decision making approach

In this paper, environmental sustainability performance assessment of 27 U.S. and Canada metropoles is addressed. A four-step hierarchical fuzzy multi-criteria decision-making approach is developed. In the first step, the proposed methodology is established by determining the sustainability performance indicators (a total of 16 sustainability indicators are considered), collecting the data and contacting experts from academia, U.S. government agencies and within the industry. In the second step, experts are contacted and the entire list is finalized; sustainability performance evaluation forms are delivered; and then expert judgment results are obtained and quantified, respectively. In the third step, the proposed Multi-criteria Intuitionistic Fuzzy Decision Making model is developed and sustainability performance scores are quantified by using the collected data, multi-criteria decision making model and sustainability indicator weights obtained from expert judgment phase. In the final step, the sustainability scores and rankings of the 27 metropoles, results analysis and discussions, and statistical highlights about the research findings are provided. Results indicated that the average sustainability performance score is found to be 0.524 over scale between 0 and 1. The metropole with the greatest sustainability performance score is found to be New York with 0.703 and the poorest performing city is identified as Cleveland with 0.394. The results of the statistical analysis indicate that the greatest significant correlations are obtained with carbon dioxide (CO2) emissions per person (-0.749 - significant negative correlation with sustainability performance score) and share of workers traveling by public transport (+0.753 - significant positive correlation with sustainability performance score). Therefore, the CO2 emissions and public transport are found to have the most significant impact on the sustainability scores

Supply chain-linked sustainability assessment of the US manufacturing:an ecosystem perspective

Locate full-text(opens in a new window)| Export | Download | Add to List | More... Sustainable Production and Consumption Volume 5, January 01, 2016, Pages 65-81 Supply chain-linked sustainability assessment of the US manufacturing: An ecosystem perspective (Article) Egilmez, G.a , Kucukvar, M.b , Park, Y.S.c a Department of Mechanical and Industrial Engineering, University of New Haven, 300 Boston Post Road, West Haven, CT, United States b Department of Industrial Engineering, Istanbul Sehir University, Kusbakisi Cad. No:27 East Campus (Suit:125), Uskudar, Istanbul, Turkey c Upper Great Plains Transportation Institute, North Dakota State University, Fargo, ND, United States View additional affiliations View references (77) Abstract This paper addresses the ecological resource consumption extents of the US manufacturing industries with a specific focus on renewable and non-renewable resource indicators from the national economic viewpoint. A hierarchical methodology was employed to quantify renewable and non-renewable resource life cycle inventory associated with the nation's manufacturing sectors and to evaluate the ecological sustainability performance. Therefore, first, ecological life cycle inventory of renewable and non-renewable resource consumption of 53 national manufacturing sectors was quantified with the ecologically-based life cycle assessment framework, and then, ecological sustainability performance assessment was performed based on well-known metrics such as loading ratio (LR), renewability ratio (RR) and non-renewable based eco-efficiency (NREE). Results indicated that nonferrous metal and nonmetallic mineral product manufacturing sectors were the drivers of non-renewable resource consumption, which caused these industries, have the least nonrenewable eco-efficiency (NREE) scores, renewability ratios (RRs) and the highest environmental loading ratios (LRs). Ecological life cycle inventory results indicated that nonferrous metal production and processing non-renewable resource consumption shares ranged between 46% and 55% in the entire supply chain network. Additionally, nonmetallic mineral product manufacturing had usage share of various non-renewable resources between 23% and 74% of the supply chains' total usage. Besides, food, tobacco and apparel manufacturing were found to have the highest RRs where the average NREE was found to be 0.4. Furthermore, sensitivity analysis of non-renewable resource indicators to NREE scores indicated that the average sensitivity ratios ranged between 5.1% and 22.4%, where 'Talc and pyrophyllite' was found to have the highest sensitivity

Emergy and end-point impact assessment of agricultural and food production in the United States:a supply chain-linked ecologically-based life cycle assessment

The concept of tracing the ecologically-based life cycle impacts of agricultural and food industries (AFIs)has become a topic of interest worldwide due to their criticalassociation with the climate change,water and land footprint, and food security. In this study, an indepth analysis of ecology resourceconsumption, atmospheric emissions, land and water footprints of 54 agricultural and food industriesinthe U.S. were examined extensively. Initially, the supply-chain linked ecological life cycle assess-ment was performed with Ecologically-based Life Cycle Assessment (Eco-LCA) tool. Then, the results oflife cycle inventory were used to assess the mid and end-point impacts by using the ReCiPe approach.Thirdly, ecological performance assessment was performed using well-known metrics, including loadingand renewability ratios and eco-efficiency analysis. As a novel comprehensive approach, the integratedframework that consists of the Eco-LCA, ReCiPe and linear programming-based ecological performance assessment is of importance to have an overall understanding about the extent of impacts related to agri-cultural and food production activities across the U.S. Results indicated that grain farming, dairy food,and animal production-related sectors were found to have the greatest shares in both environmentaland ecological impact categories as well as endpoint impacts on human health, ecosystem and resources. In terms of climate change, animal (except poultry) slaughtering, rendering, and processing (ASRP), cat-tle ranching and farming (CRF), fertilizer manufacturing (FM), grain farming (GF), fluid milk and buttermanufacturing (FMBM) were found to be the top five dominant industries in climate change impactsaccounting for about 60% share of the total impact

A novel life cycle-based principal component analysis framework for eco-efficiency analysis:case of the United States manufacturing and transportation nexus

In this study, the relationship between the U.S. manufacturing and transportation industries was studied from economic and environmental life cycle sustainability perspective. The main objectives were 1) to quantify the life cycle impacts of national freight transportation activities that were triggered by the U.S. manufacturing industries and supply chains, a.k.a. manufacturing transportation nexus, and 2) assess the transportation-focused sustainability performance of manufacturing sectors based on eco-efficiency. Three environmental impact categories were focused, namely: greenhouse gas (GHG) emissions, energy use, and water withdrawals along with the economic outputs. To achieve the goals, a novel integrated methodology that consists of Economic Input-Output Life-Cycle Assessment (EIO-LCA) and Principal Component Analysis (PCA) was utilized. The scope of the study consists of 276 U.S manufacturing sectors' economic and environmental impacts associated with four transportation modes including air, rail, truck, and water transportation. Based on EIO-LCA results, food manufacturing sector was found to be responsible for the highest environmental impacts and economic output with a share of over 20% for GHG emissions, energy use, and water withdrawals and about 12% for economic output. Motor vehicle manufacturing and motor vehicle body, trailer and parts manufacturing were found to have the second and third largest share of environmental impacts and economic output, respectively. From the result of the eco-efficiency analysis, ordinance and accessory manufacturing (0.719) was found to have the highest and iron and steel mills manufacturing and agricultural chemical manufacturing (0.130) were found to have the least eco-efficiency scores. It was also critical to address that a significant negative correlation was observed between the eco-efficiency and the ton-km transportation trends

AHP TABANLI VIKOR YÖNTEMİYLE OPTİMUM STADYUM KURULUŞ YERİNİN BELİRLENMESİ: BOLU İLİ ÖRNEĞİ

Optimal yer seçimi, tüm işletmelerin en önemli ve uzun vadeli kararlardanbiridir. Şehir stadyumu gibi büyük ve maliyetli yapılar genelde devlet desteklikurulan yapılardır. Bu yapıların yer seçiminde sosyal, ekonomik, kültürel vepolitik birçok etken vardır. Bu çalışmada Bolu’da yapılması planlanan futbolstadyumu için belirlenen kriterler çerçevesinde dört yer alternatif arasından enoptimal yer seçimi çok kriterli karar verme yöntemleriyle belirlenmeyeçalışılmıştır. 3 alan, 3 ulaşım ve ağırlama, 3 şehre katkı ve 4 teknik ve yasalkriter olmak üzere toplam 13 kriterin kullanıldığı çalışmada, kriterlerin önemdereceleri Analitik Hiyerarşi Süreci yöntemiyle elde edilmiştir. Optimal yerinseçiminde alternatifler VİKOR yöntemiyle değerlendirilmiş ve sıralanmıştır.Elde edilen sonuçlara göre en optimal yerin Karaçayır Yerleşkesi olduğu ve bunusırasıyla Gölköy Yerleşkesi, Geçitveren Yerleşkesi ve Mevcut yerin takip ettiğigörülmektedir.Optimal site selection is one of the most important and long-term decisions of all businesses. Large and costly structures, such as the city stadium, are generally state-funded. There are many social, cultural and political factors in the selection of these structures. In this study, it is tried to determine the most optimal location in Bolu by using multi criteria decision making methods among the 4 alternative places within the criteria determined for the football stadium planned to be built. In the study, total of 13 criteria were used, 3 of which were area, 3 of which were transportation and hospitality, 3 of which were contribution to the city and 4 of which were technical and legal criteria.The importance of the criteria was obtained through the Analytical Hierarchy Process and the alternatives in choosing the optimal location are evaluated and sorted by the VIKOR method. According to the results, the most optimal location is Karaçayır campus, followed by Gölköy campus, Geçitveren campus and the current place respectivel

A Comparative Time-Series Investigation of China and U.S. Manufacturing Industries’ Global Supply-Chain-Linked Economic, Mid and End-Point Environmental Impacts

Manufacturing activities of China and the U.S. account for a substantial portion of the global manufacturing output and environmental sustainability impacts. The two countries’ economies account for one third of the global economic output. Their supply chains are critically linked with and serve most of the production and service industries across the globe. Recent global trends in manufacturing necessitate a study that comparatively analyzes the two countries’ manufacturing industries from an economic and environmental perspective. In this paper, U.S. and China manufacturing industries were investigated to analyze the economic and mid and endpoint environmental impacts over a 20-year study period. The literature is abundant with single period and single country focused works, and this study contributes to the state-of-art by extending the temporal dimension to 20 years and spatial focus to the global economy (40 countries and rest of the world). In terms of the methodology, Multi-region input-output (MRIO) models were built using the World Input-Output Database (WIOD) as the primary database, global input-output tables, environmental impact and economic output multipliers, and manufacturing industries’ final demand. Twenty MRIO models, each comprised of 40 major economies and the rest of the world (ROW), were built to cover the global trade linkages, which yielded the global supply chain linked cradle-to-gate life cycle inventory (LCI) of economic outputs and environmental impacts. The environmental LCI was extended to midpoint (Global Warming Potential (GWP) and Ozone Depletion Potential (ODP)) and endpoint (human health and ecosystem) impact dimensions by ReCipe framework. Lastly, the relative impact of a unit change in Leontief inverse, final demand and Green House Gas (GHG) emission multipliers on the total economic output and environmental impacts were explored with structural decomposition analysis (SDA). Results indicated that both countries’ manufacturing industries experienced positive economic output growth, in which China was more dominant in recent years. Both countries’ manufacturing industries’ midpoint and endpoint impacts were found to be steeply rising despite the negative growth observed in emissions intensities. The amount of GHG emissions and related midpoint (global warming and ozone depletion) and endpoint (damage to ecosystems and human life) impacts seemed to be quickly worsening in China compared to the USA

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

Purpose Quantitativelife 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 ofsustainabilityin anintegratedway. To thisend, thisresearchaimstopresentapracticalandnovelapproachfor (1)broadeningtheexistinglifecyclesustainabilityassessment (LCSA) framework by considering macrolevel environmental, economic, and social impacts (termed as the triple bottom line),simultaneously,(2)deepeningtheexistingLCSAframework by capturing the complex dynamic relationships betweensocial,environmental,andeconomicindicatorsthrough 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 consideringallofthecomplexinteractionsintheenvironmental, social, and economic aspects. Methods To alleviate these research objectives, we presented anovelmethodologytoquantifymacrolevelsocial,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 electricvehicles(BEVs). Intotal,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 discussion BEVs 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 ownershipcostand human healthimpactsofBEVs arehigher than the other vehicle types on 2010s and 2020s. While the impactsharesofmanufacturingand operation phasesare similarintheearlyyearsof2010s,thecontributionofmanufacturing phase becomes higher as the vehicle performances increase toward 2050. Analysis results revealed that the US transportationsector,alone,cannotreducetherapidlyincreasing atmospheric temperature and the negative impacts of the globalclimate change, eventhoughtheentirefleet 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. Conclusions The authors strongly recommend that the dynamiccomplexandmutualinteractionsbetweensustainability 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

Energy-climate-manufacturing nexus:new insights from the regional and global supply chains of manufacturing industries

The main objectives of this research are to improve our understanding of energy-climate-manufacturing nexus within the context of regional and global manufacturing supply chains as well as show the significance of full coverage of entire supply chain tiers in order to prevent significant underestimations, which might lead to invalid policy conclusions. With this motivation, a multi region input–output (MRIO) sustainability assessment model is developed by using the World Input–Output Database, which is a dynamic MRIO framework on the world’s 40 largest economies covering 1440 economic sectors. The method presented in this study is the first environmentally-extended MRIO model that harmonizes energy and carbon footprint accounts for Turkish manufacturing sectors and a global trade-linked carbon and energy footprint analysis of Turkish manufacturing sectors is performed as a case study. The results are presented by distinguishing the contributions of five common supply chain phases such as upstream suppliers, onsite manufacturing, transportation, wholesale, and retail trade. The findings showed that onsite and upstream supply chains are found to have over 90% of total energy use and carbon footprint for all industrial sectors. Electricity, Gas and Water Supply sector is usually found to be as the main contributor to global climate change, and Coke, Refined Petroleum, and Nuclear Fuel sector is the main driver of energy use in upstream supply chains. Overall, the largest portion of total carbon emissions of Turkish manufacturing industries is found in Turkey’s regional boundary that ranged between 40% and 60% of total carbon emissions. In 2009, China, United States, and Rest-of-the-World’s contribution is found to be more than 50% of total energy use of Turkish manufacturing. The authors envision that a global MRIO framework can provide a vital guidance for policy makers to analyze the role of global manufacturing supply chains and prevent significant underestimations due to inclusion of limited number of tiers for sustainable supply chain management research

From green buildings to green supply chains:an integrated input-output life cycle assessment and optimization framework for carbon footprint reduction policy making

Purpose–ThepurposeofthispaperistofocusontracingGHGemissionsacrossthesupplychainindustries associated with the US residential, commercial and industrial building stock and provides optimized GHG reduction policy plans for sustainable development. Design/methodology/approach – 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. Findings – 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 eachbuildingconstructioncategorieswerealsohighlightedasthehot-spotsinthesupplychainswithrespect to the GHG emission reduction (percent) requirements. Practical implications – 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. Originality/value – 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