scholarly journals Price Variance in Hybrid-LCA Leads to Significant Uncertainty in Carbon Footprints

2021 ◽  
Vol 2 ◽  
Author(s):  
Arthur Jakobs ◽  
Simon Schulte ◽  
Stefan Pauliuk
Keyword(s):  
Life Cycle ◽  
Carbon Footprint ◽  
Commodity Prices ◽  
Commodity Price ◽  
Double Counting ◽  
Input Output ◽  
Hybrid Lca ◽  
Carbon Footprints ◽  
Process Database ◽  
Added Uncertainty

Hybrid Life Cycle Assessment (HLCA) methods attempt to address the limitations regarding process coverage and resolution of the more traditional Process- and Input-Output Life Cycle Assessments (PLCA, IOLCA). Due to the use of different units, HLCA methods rely on commodity price information to convert the physical units used in process inventories to the monetary units commonly used in Input-Output models. However, prices for the same commodity can vary significantly between different supply chains, or even between various levels in the same supply chain. The resulting commodity price variance in turn leads to added uncertainty in the hybrid environmental footprint. In this paper we take international trading statistics from BACI/UN-COMTRADE to estimate the variance of commodity prices, and use these in an integrated HLCA model of the process database ecoinvent with the EE-MRIO database EXIOBASE. We show that geographical aggregation of PLCA processes is a significant driver in the price variance of their reference products. We analyse the effect of price variance on process carbon footprint intensities (CFIs) and find that the CFIs of hybridised processes show a median increase of 6–17% due to hybridisation, for two different double counting scenarios, and a median uncertainty of −2 to +4% due to price variance. Furthermore, we illustrate the effect of price variance on the carbon footprint uncertainty in a HLCA study of Swiss household consumption. Although the relative footprint increase due to hybridisation is small to moderate with 8–14% for two different double counting correction strategies, the uncertainty due to price variability of this contribution to the footprint is very high, with 95% confidence intervals of (−28, +90%) and (−23, +68%) relative to the median. The magnitude and high positive skewness of the uncertainty highlights the importance of taking price variance into account when performing hybrid LCA.

scholarly journals Study of the viticultural technical itineraries carbon footprint at fine scale

2019 ◽  
Vol 15 ◽  
pp. 01030
Author(s):  
E. Adoir ◽  
S. Penavayre ◽  
T. Petitjean ◽  
L. De Rességuier
Keyword(s):  
Life Cycle ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Carbon Footprint ◽  
Primary Data ◽  
Life Cycle Approach ◽  
Gas Emissions ◽  
Carbon Footprints ◽  
Life Project ◽  
One Year

Viticulture faces two challenges regarding climate change: adapting and mitigating greenhouse gas emissions. Are these two challenges compatible? This is one of the questions to which Adviclim project (Life project, 2014–2019) provided tools and answers. The assessment of greenhouse gas emissions was implemented at the scale of the plot using a life cycle approach: calculating the carbon footprint. This approach makes it possible to take into account the emissions generated during each stage of the life cycle of a product or a service: in this case, the cultivation of one hectare of vine for one year. Carbon footprint was assessed for the 5 pilot sites of the Adviclim project: Saint-Emilion (France), Coteaux du Layon/Samur (France), Geisenheim (Germany), Cotnari (Romania) and Plompton (United Kingdom). An important work for primary data collection regarding observed practices was carried out with a sample of reresentative farms for these 5 sites, and for one to three vintages depending on the site. Beyond the question asked in the project, the calculation of these carbon footprints made it possible to (i) make winegrowers aware of the life cycle approach and the share of direct emissions generated by viticulture, (ii) acquire new references on the technical itineraries and their associated emissions, (iii) improve the adaptation of the methodology for calculating the carbon footprint to viticulture.

A Comparison of Carbon Footprint Calculations for End of Life Product Recovery Methods Using PAS 2050

2010 ◽  
Author(s):  
Michaela R. Appleby ◽  
Adam B. Buckley ◽  
Chris G. Lambert ◽  
Allan E. W. Rennie
Keyword(s):  
Life Cycle ◽  
End Of Life ◽  
Carbon Footprint ◽  
Product Recovery ◽  
Recovery Method ◽  
Specific Data ◽  
Carbon Footprints ◽  
North West ◽  
Government Legislation ◽  
Recovery Methods

This paper demonstrates a comparison of product recovery methods, by carbon footprint calculation, for repaired products with remanufactured products and the environmental impact that they have when they reach their end-of-life (EOL). Growing concerns of climate change and government legislation have changed the way in which consumers can dispose of used or broken products. Items can no longer be sent to landfill and it is now the responsibility of the producers to dispose of products in a more sustainable manner and take into consideration all stages of the products life cycle. A standardised method for calculating carbon footprints has been used and a carbon footprint carried out for each product recovery method. Specific data was collected, from a manufacturing company in England’s North West region, about the processes involved during each recovery method and have identified that repairing has a lower carbon footprint than remanufacturing. However, repairing only extends the existing life cycle of a product, whereas remanufacturing can be carried out up to three times, and provides the product with a new life cycle. Therefore, remanufacturing is seen as the most preferable method of product recovery in terms of carbon emissions and sustainable waste disposal.

scholarly journals Standardized Recipes and Their Influence on the Environmental Impact Assessment of Mixed Dishes: A Case Study on Pizza

2020 ◽  
Vol 12 (22) ◽  
pp. 9466
Author(s):  
Katerina S. Stylianou ◽  
Emily McDonald ◽  
Victor L. Fulgoni III ◽  
Olivier Jolliet
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Carbon Footprint ◽  
Environmental Performance ◽  
Food Systems ◽  
Decomposition Methods ◽  
Carbon Footprints ◽  
Improvement Potential ◽  
The U.S

Food and diet life cycle assessment (LCA) studies offer insights on the environmental performance and improvement potential of food systems and dietary patterns. However, the influence of ingredient resolution in food-LCAs is often overlooked. To address this, four distinct decomposition methods were used to determine ingredients for mixed dishes and characterize their environmental impacts, using the carbon footprint of the U.S. daily pizza intake as a case study. Pizza-specific and daily pizza intake carbon footprints varied substantially between decomposition methods. The carbon footprint for vegetarian pizza was 0.18–0.45 kg CO2eq/serving, for meat pizza was 0.56–0.73 kg CO2eq/serving, and for currently consumed pizzas in the U.S. (26.3 g/person/day; 75 pizzas types) was 0.072–0.098 kg CO2eq/person/day. These ranges could be explained by differences in pizza coverage, ingredient resolution, availability of ingredient environmental information, and ingredient adjustability for losses between decomposition methods. From the approaches considered, the USDA National Nutrient Database for Standard Reference, which reports standardized food recipes in relative weights, appears to offer the most appropriate and useful food decompositions for food-LCAs. The influence and limitations of sources of reference flows should be better evaluated and acknowledged in food and diet LCAs.

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.

scholarly journals Carbon Footprint of Honey in Different Beekeeping Systems

2021 ◽  
Vol 13 (19) ◽  
pp. 11063
Author(s):  
Arianna Pignagnoli ◽  
Stefano Pignedoli ◽  
Emanuele Carpana ◽  
Cecilia Costa ◽  
Aldo Dal Prà
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Carbon Footprint ◽  
Food Chains ◽  
Natural Ecosystems ◽  
Iso 14040 ◽  
Carbon Footprints ◽  
Honey Production ◽  
Processing Plants ◽  
Geographical Locations

Life Cycle Assessment (LCA) has been increasingly used for the improvement of the environmental performance of products and services, including agro-food chains. Pollination by honeybees can be regarded as one of the functions of an apicultural system and is of utmost importance for both natural ecosystems and agriculture. Furthermore, the beekeeping chain can represent an instrument for the protection and conservation of honeybee diversity when local subspecies are used. The Carbon Footprint of honey evaluates greenhouse gas emissions throughout the Life Cycle Assessment—more specifically, emissions of carbon dioxide, nitrous oxide, and methane. To this aim, data from beekeeping farms were collected, including data on annual honey production, other hive products, the geographical locations of the apiaries, processing plants, technologies used, and fuel and energy consumption. Based on the ISO 14040 method for the use of Life Cycle Assessment, the Carbon Footprints that were calculated for honey ranged from 1.40 to 2.20 kg CO2e/kg of honey for migratory beekeeping and from 0.380 to 0.48 kg CO2e/kg of honey for non-migratory beekeeping. The movements for the management of migratory beehives (on average, 44 km/hive for farm 1, 32 km/hive for farm 2, and 13 km/hive for farm 3) represented the main impact in migratory beekeeping systems, and they were quantified as 1.234, 1.113, and 0.68 CO2e/kg of honey. However, electricity represented the main impact of systems without migratory practices.

Life cycle assessment of ECF bleaching sequences with ocus on carbon footprint

TAPPI Journal ◽  
2015 ◽  
Vol 14 (1) ◽  
pp. 17-24 ◽  
Author(s):  
PIA JOUR ◽  
KARIN HALLDÉN ◽  
EVA WACKERBERG
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Carbon Footprint ◽  
Total Carbon ◽  
Base Case ◽  
Pulp Bleaching ◽  
Carbon Footprints ◽  
Bleached Pulp ◽  
Eucalyptus Kraft Pulp ◽  
Pulp Production

This paper presents a life cycle assessment (LCA) of bleached eucalyptus kraft pulp production in Brazil. The entire production system was investigated, starting with forestry and ending with bleached pulp at the gate of the pulp mill. Alternative bleaching sequences were compared for three different scenarios using somewhat different elemental chlorine-free (ECF) sequences: Dhot(EPO)DD, Dhot(EPO)DP, and aZeDP. The main difference between the scenarios investigated was the magnitude of the carbon footprint contribution from bleaching. For the base case and chemical island scenarios (both reflecting Brazilian conditions), the contribution was 15%-18% of the total carbon footprint. For the ecoinvent scenario, the corresponding share was 34%-41%. The ecoinvent scenario represents generic LCA data for bleaching chemicals. Ecoinvent is a public database commonly included in commercial LCA software. For each scenario, the alternative bleaching sequences studied resulted in similar carbon footprints of the bleached pulp. A comparison of the data from the different scenarios showed a large range of carbon footprints for the chemicals used for pulp bleaching. It is crucial to select data sets that are relevant in terms of geography and technology. The most dominant contributors to the carbon footprint of the unbleached pulp were forestry and pulp production. Although the focus has been on carbon footprints, the contributions to other environmental effects commonly included in LCAs were also assessed and only minor differences between the alternative bleaching sequences were found.

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

scholarly journals Assessing Carbon Footprint and Inter-Regional Carbon Transfer in China Based on a Multi-Regional Input-Output Model

2018 ◽  
Vol 10 (12) ◽  
pp. 4626 ◽  
Author(s):  
Min Huang ◽  
Yimin Chen ◽  
Yuanying Zhang
Keyword(s):  
Economic Development ◽  
Carbon Footprint ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Central China ◽  
Input Output ◽  
Carbon Footprints ◽  
Carbon Transfer ◽  
Per Capita

China has been the largest carbon emitter in the world since 2007 and is thus confronted with huge emission reduction pressures. The regional differences in socio-economic development lead to complex inter-provincial carbon transfer in China, which hinders the determination of the emission reduction responsibilities for the various provinces. Based on the latest multi-regional input-output data, this study analyzes the carbon footprint, inter-provincial carbon transfer, and the corresponding variations of 30 provinces in China from 2007 to 2010. The results show that the domestic carbon footprint increased from 4578 Mt in 2007 to 6252 Mt in 2010. Provinces with high carbon footprints were mainly found in central China, such as Shandong, Jiangsu, and Henan. Carbon footprints of the developed coastal provinces were greater than those of less developed provinces in Northwestern China. Per capita GDP (Gross Domestic Product) was positively correlated to the per capita carbon footprint, indicating a positive relationship between the economic development level and corresponding carbon emissions. Provincial carbon inflows were found to have increased steadily (ranging between 32% and 41%) from 2007 to 2010. The increases in direct carbon emissions varied largely among different provinces, ranging from below 30% in the developed provinces to more than 60% in the moderately developed provinces (e.g., Sichuan and Chongqing). The embodied carbon transferred from moderately developed or remote provinces to those developed ones. In other words, the carbon emission pressures of the developed provinces were shifted to the less developed provinces. The major paths of carbon flow include the transfers from Hebei to Jiangsu (32.07 Mt), Hebei to Beijing (26.78 Mt), Hebei to Zhejiang (25.60 Mt), and Liaoning to Jilin (27.60 Mt).

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