scholarly journals Carbon footprint stock analysis of US manufacturing: a time series input-output LCA

2017 ◽  
Vol 117 (5) ◽  
pp. 853-872 ◽  
Author(s):  
Gokhan Egilmez ◽  
Khurrum Bhutta ◽  
Bulent Erenay ◽  
Yong Shin Park ◽  
Ridvan Gedik
Keyword(s):  
Time Series ◽  
Life Cycle Assessment ◽  
Supply Chain ◽  
Life Cycle ◽  
Carbon Footprint ◽  
Manufacturing Industries ◽  
Input Output ◽  
Content Type ◽  
The Us ◽  
Manufacturing Sectors

Purpose The purpose of this paper is to provide an input-output life cycle assessment model to estimate the carbon footprint of US manufacturing sectors. To achieve this, the paper sets out the following objectives: develop a time series carbon footprint estimation model for US manufacturing sectors; analyze the annual and cumulative carbon footprint; analyze and identify the most carbon emitting and carbon intensive manufacturing industries in the last four decades; and analyze the supply chains of US manufacturing industries to help identify the most critical carbon emitting industries. Design/methodology/approach Initially, the economic input-output tables of US economy and carbon footprint multipliers were collected from EORA database (Lenzen et al., 2012). Then, economic input-output life cycle assessment models were developed to quantify the carbon footprint extents of the US manufacturing sectors between 1970 and 2011. The carbon footprint is assessed in metric tons of CO2-equivalent, whereas the economic outputs were measured in million dollar economic activity. Findings The salient finding of this paper is that the carbon footprint stock has been increasing substantially over the last four decades. The steep growth in economic output unfortunately over-shadowed the potential benefits that were obtained from lower CO2 intensities. Analysis of specific industry results indicate that the top five manufacturing sectors based on total carbon footprint share are “petroleum refineries,” “Animal (except poultry) slaughtering, rendering, and processing,” “Other basic organic chemical manufacturing,” “Motor vehicle parts manufacturing,” and “Iron and steel mills and ferroalloy manufacturing.” Originality/value This paper proposes a state-of-art time series input-output-based carbon footprint assessment for the US manufacturing industries considering direct (onsite) and indirect (supply chain) impacts. In addition, the paper provides carbon intensity and carbon stock variables that are assessed over time for each of the US manufacturing industries from a supply chain footprint perspective.

Layer analysis of CO2 sources in the US economic supply chains: an input output LCA study

2017 ◽  
Vol 117 (10) ◽  
pp. 2171-2193 ◽  
Author(s):  
Gokhan Egilmez ◽  
N. Muhammad Aslaam Mohamed Abdul Ghani ◽  
Ridvan Gedik
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Carbon Footprint ◽  
Sustainability Assessment ◽  
Chain Structure ◽  
Total Carbon ◽  
Input Output ◽  
Content Type ◽  
The Us ◽  
Supply Chain Structure

Purpose Carbon footprint assessment requires a holistic approach, where all possible lifecycle stages of products from raw material extraction to the end of life are considered. The purpose of this paper is to develop an analytical sustainability assessment framework to assess the carbon footprint of US economic supply chains from two perspectives: supply chain layers (tiers) and carbon footprint sources. Design/methodology/approach The methodology consists of two phases. In the first phase, the data were collected from EORA input output and environmental impact assessment database. In the second phase, 48 input-output-based lifecycle assessment models were developed (seven CO2 sources and total CO2 impact, and six supply chain tiers). In the third phase, the results are analyzed by using data visualization, data analytics, and statistical approaches in order to identify the heavy carbon emitter industries and their percentage shares in the supply chains by each layer and the CO2 source. Findings Vast majority of carbon footprint was found to be attributed to the power generation, petroleum refineries, used and secondhand goods, natural gas distribution, scrap, and truck transportation. These industries dominated the entire supply chain structure and found to be the top drivers in all six layers. Practical implications This study decomposes the sources of the total carbon footprint of US economic supply chains into six layers and assesses the percentage contribution of each sector in each layer. Thus, it paves the way for quantifying the carbon footprint of each layer in today’s complex supply chain structure and highlights the importance of handling CO2 source in each layer separately while maintaining a holistic focus on the overall carbon footprint impacts in the big picture. In practice, one size fits all type of policy making may not be as effective as it could be expected. Originality/value This paper provides a two-dimensional viewpoint for tracing/analyzing carbon footprint across a national economy. In the first dimension, the national economic system is divided into six layers. In the second dimension, carbon footprint analysis is performed considering specific CO2 sources, including energy production, solvent, cement and minerals, agricultural burning, natural decay, and waste. Thus, this paper contributes to the state-of-art sustainability assessment by providing a comprehensive overview of CO2 sources in the US economic supply chains.

Life cycle assessment of organic Parmesan Cheese considering the whole dairy supply chain

2019 ◽  
Author(s):  
Giulia Borghesi ◽  
Giuseppe Vignali
Keyword(s):  
Life Cycle Assessment ◽  
Supply Chain ◽  
Life Cycle ◽  
Environmental Impact ◽  
Carbon Footprint ◽  
Water Consumption ◽  
Organic Agriculture ◽  
Water Footprint ◽  
Dairy Farm ◽  
Parmesan Cheese

Agriculture and food manufacturing have a considerable effect on the environment emissions: holdings and farms play an important role about greenhouse gas emissions and water consumption. This study aims at evaluating the environmental impact of one of the most important Italian DOP product: organic Parmesan Cheese. Environmental performances of the whole dairy supply chain have been assessed according to the life cycle assessment approach (LCA). In this analysis Parmesan Cheese is made from an organic dairy farm in Emilia Romagna, which uses the milk from three different organic livestock productions. Organic agriculture is different from conventional; the major difference is represented by the avoidance of the use of synthetic fertilizers and pesticides made in chemical industry process. Organic agriculture uses organic fertilizers to encourage the natural fertility of the soil respecting the environment and the agro-system. In this case, life cycle approach is used to assess the carbon footprint and the water footprint of organic Parmesan Cheese considering the milk and cheese production. The object at this level is investigating the environmental impact considering the situation before some improvement changes. The functional unit is represented by 1 kg of organic Parmesan Cheese; inventory data refer to the situation in year 2017 and system boundaries consider the inputs related to the cattle and dairy farm until the ripening (included). The carbon footprint is investigated using IPCC 2013 Global Warming Potential (GWP) 100a method, developed by Intergovernmental Panel on Climate Change, and reported in kg of CO2eq. Otherwise, water footprint allows to measure the water consumption and in this work it is assessed using AWARE method (Available Water REmaining).

Life Cycle Assessment and Carbon Footprint in the Wine Supply-Chain

2012 ◽  
Vol 49 (6) ◽  
pp. 1247-1258 ◽  
Author(s):  
Claudio Pattara ◽  
Andrea Raggi ◽  
Angelo Cichelli
Keyword(s):  
Life Cycle Assessment ◽  
Supply Chain ◽  
Life Cycle ◽  
Carbon Footprint

Hydroponic cultivation: life cycle assessment of substrate choice

2019 ◽  
Vol 121 (8) ◽  
pp. 1801-1812 ◽  
Author(s):  
Giuliana Vinci ◽  
Mattia Rapa
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Carbon Footprint ◽  
Environmental Sustainability ◽  
Impact Analysis ◽  
Content Type ◽  
Hydroponic Cultivation ◽  
Hydroponic Systems ◽  
Total Impact ◽  
Rock Wool

Purpose Nowadays, hydroponic cultivation represents a widely used agricultural methodology. The purpose of this paper is to study comparatively on hydroponic substrates. This study is highlighting the best substrate to be involved in hydroponic systems, considering its costs and its sustainability. Design/methodology/approach Seven substrates were evaluated: rock wool, perlite, vermiculite, peat, coconut fibres, bark and sand. Life cycle assessment (life cycle inventory, life cycle impact assessment (LCIA) and life cycle costing (LCC)) was applied to evaluate the environmental and economic impact. Through the results of the impacts, the carbon footprint of each substrate was calculated. Findings Perlite is the most impacting substrate, as highlighted by LCIA, followed by rock wool and vermiculite. The most sustainable ones, instead, are sand and bark. Sand has the lower carbon footprint (0.0121 kg CO2 eq.); instead, bark carbon footprint results in one of the highest (1.1197 kg CO2 eq.), while in the total impact analysis this substrate seems to be highly sustainable. Also for perlite the two results are in disagreement: it has a high total impact but very low carbon footprint (0.0209 kg CO2 eq.) compared to the other substrates. From the LCC analysis it appears that peat is the most expensive substrate (€6.67/1,000 cm3), while sand is the cheaper one (€0.26/1,000 cm3). Originality/value The LCA and carbon footprint methodologies were applied to a growing agriculture practice. This study has highlighted the economic and environmental sustainability of seven substrates examined. This analysis has shown that sand can be the best substrate to be involved in hydroponic systems by considering its costs and its sustainability.

Comparative study on adoption of sustainable supply chain management practices in Indian manufacturing industries

2019 ◽  
Vol 14 (4) ◽  
pp. 1006-1022 ◽  
Author(s):  
Deepak Mathivathanan ◽  
K. Mathiyazhagan ◽  
A. Noorul Haq ◽  
Vishnu Kaippillil
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Manufacturing Industries ◽  
Successful Implementation ◽  
Sustainable Supply Chain ◽  
Implementation Framework ◽  
Chain Management ◽  
Content Type ◽  
Sustainable Supply Chain Management ◽  
Manufacturing Sectors

Purpose Sustainable supply chain management (SSCM) concepts have received immense attention in the recent past in both academia and industries. Especially, manufacturing industries in developing countries realize the importance of adopting sustainability concepts in their supply chain. The SSCM adoption has not been to the same level across different manufacturing sectors and hence a single implementation framework will not have the same effect across sectors. This paper aims to compare the adoption level of 25 SSCM practices across three major manufacturing sectors, namely, automobile, electronics and textile, in an emerging economy, India. Design/methodology/approach A questionnaire-based data collection technique is used to obtain adoption levels of each of the identified SSCM practices on a five-point Likert-type scale with “1” representing not considering presently to “5” indicating successful implementation. Second, a hypothesis is framed and tested to compare the adoption levels across sectors using a one-way single-factor ANOVA followed by a post hoc test by Tukey’s test. Findings The results derived suggest that though the industries across different sectors are in the course of adopting SSCM practices, the level of adoption is found to be not the same. The textile sector has adopted the least, and the electronic sector edges ahead of the automobile sector in terms of successful transformation to SSCM. Originality/value This study focuses on the differences and similarities in the adoption of policies in the automobile, electronics and textile sectors using statistical data analysis tools. A total of 25 individual practices are identified from existing literature and classified into six groups, namely, management, supplier, collaboration, design, internal and society, based on their similarities. Based on a detailed questionnaire survey with industrial experts in relevant fields as respondents, the adoption levels of practices are rated individually and categorically.

Evaluating the carbon footprint of a Spanish city through environmentally extended input output analysis and comparison with life cycle assessment

2020 ◽  
pp. 143133
Author(s):  
Manuel Rama ◽  
Eduardo Entrena-Barbero ◽  
Ana Cláudia Dias ◽  
María Teresa Moreira ◽  
Gumersindo Feijoo ◽  
...  
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Carbon Footprint ◽  
Input Output ◽  
Output Analysis ◽  
Input Output Analysis

From green buildings to green supply chains

2017 ◽  
Vol 28 (4) ◽  
pp. 532-548 ◽  
Author(s):  
N. Muhammad Aslaam Mohamed Abdul Ghani ◽  
Gokhan Egilmez ◽  
Murat Kucukvar ◽  
M. Khurrum S. Bhutta
Keyword(s):  
Sustainable Development ◽  
Supply Chain ◽  
Life Cycle ◽  
Supply Chains ◽  
Ghg Emissions ◽  
Industrial Building ◽  
Building Structures ◽  
Building Stock ◽  
Content Type ◽  
The Us

Purpose 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. 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 each building construction categories were also highlighted as the hot-spots in the supply chains with respect 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.

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