Purpose
Ethylene and propylene production is currently included in life cycle assessment (LCA) databases using an attributional life cycle inventory (LCI) modelling approach. This approach entails modelling both products as co-products of the steam cracking process. In this article, we provide what, to the best of our knowledge, constitutes the first attempt to construct a consequential LCI model for ethylene and propylene production, focusing on European conditions and using publicly available data.
Methods
A market analysis for the European market was conducted, showing that steam cracking of naphtha is the marginal production route for ethylene, while for propylene the marginal production route is propane dehydrogenation (PDH). This market analysis also identifies propane as a constrained feedstock and suggests that an increase in demand for propane will induce a shift to gasoline consumption by ‘autogas’ vehicles. Following these findings, we develop a consequential LCI model including PDH, steam cracking, treatment of steam cracking by-products (butadiene extraction, pyrolysis gasoline hydrotreatment, benzene-toluene-xylenes extraction), and marginal production routes for all substituted products, such as hydrogen, butadiene, benzene, toluene, and mixed xylenes, among others. The LCI model was linked to the background ecoinvent database.
Results and discussion
The model was evaluated at the impact assessment level, focusing only on greenhouse-gas (GHG) emissions per kg product, showing that they are larger for ethylene (1.83 kg CO2e) compared to propylene (1.35 kg CO2e). In both cases, the main contribution is the supply of feedstock, namely naphtha and propane, respectively, although total emissions are highly influenced by substitutions associated with by-products. For ethylene, several substituted products occur, especially benzene, hydrogen, and propylene, while for propylene the only relevant substitution is for hydrogen. A sensitivity analysis shows that the results for both propylene and ethylene are highly sensitive to how the propane constraint is addressed. In particular, GHG emissions for propylene drop by 48% and those for ethylene increase by 22% when the marginal propane user shifts to natural gas instead of gasoline.
Conclusions
A consequential approach shows that a demand for ethylene and propylene, respectively, triggers and affects different production processes, thereby yielding distinct cradle-to-gate environmental impacts for each product. This stands in contrast to typical attributional models employing mass allocation (partitioning), which results in identical impacts per kilogram. Future research efforts should be aimed at validating the presented model, as well as expanding it to cover regions other than Europe, where marginal propylene production routes may vary.
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An effective climate labelling scheme requires a methodology, a database, and a label format that allows consistent comparison both within and across product categories. To this end, we analyse the EU product environmental footprint (PEF) methodology, the state of databases on climate footprints, the current knowledge on effective label design, and relevant EU regulation. Based on this analysis, we conclude that further preparation is required before a voluntary, horizontal climate labelling scheme can be established under Union law, across all product categories. Specific improvements are proposed to harmonise and simplify the PEF methodology. We also propose that a globally complete, consistent, and open background database is established and maintained, with an acceptable level of product detail. A label design is proposed that allows seamless cross-category comparison and consideration of the 'monetary rebound' effect, as well as easy communication of uncertainty. The development of a roadmap is also proposed. This should consider the broader context of environmental and sustainability labelling and the need to improve international product life cycle assessment standards and harmonise conflicting EU calculation rules.
Major technological transitions are necessary to avoid the catastrophic consequences of climate change and other environmental damage (IPCC 2021). However, many of the technologies needed to achieve net zero greenhouse gas emissions by 2050 are still in the early stages of development (IEA 2021a). The implementation of these technologies is expected to occur once they are mature enough to enter the market. Some technologies will require significant capital and time to develop. Therefore, a good understanding of these technologies’ potential environmental impacts and guidance to minimize these impacts before such investments are made are crucial to meet environmental targets.
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This project developed a methodology and data for calculating the greenhouse gas (GHG) emissions, nitrogen and phosphate leached to water, and phosphate leftover in the soil, related to the cultivation of crops. The GHG emissions include dinitrogen monoxide, ammonia, nitrogen oxides, and carbon dioxide. These emissions, leaches, and leftovers were calculated using a model described by the intergovernmental panel on climate change (IPCC). The calculations are summarised in a report (Schmidt J and Sørensen J I (2022). LCA Crop Database Methodology Report), where the inputs and the outputs of the model are also outlined.
This report presents the methodology and data for calculating the greenhouse gas (GHG) emissions, nitrogen and phosphate leached to water, and phosphate leftover in the soil, related to the cultivation of crops. The GHG emissions include dinitrogen monoxide, ammonia, nitrogen oxides, and carbon dioxide.
The emissions, leaches, and leftovers are calculated using a model described by the intergovernmental panel on climate change (IPCC). Following the calculations are a summary where the inputs and the outputs of the model are outlined.
Life cycle assessment (LCA) and environmentally extended input output analysis (EEIOA) are two widely used approaches to assess the environmental impacts of products and services with the aim of providing decision support. Here, we compare carbon footprint (CF) results for products and services in the ecoinvent 3.4 cut-off and the hybrid version of EXIOBASE. While we find that there is good agreement for certain sectors, more than half of the matched products differ by more than a factor 2. Best fits are observed in the energy, manufacturing, and agricultural sectors, although deviations are substantial for renewable energy. Poorer fits are observed for waste treatment and mining sectors. Both databases have a limited differentiation in the service sector. Differences can, to some degree, be explained by methodological differences, such as system boundaries and approaches used to resolve multi-functionality, and data differences. The common finding that, due to incomplete economic coverage (truncation error), LCA-based CFs should be lower than EEIOA-based CFs, could not be confirmed. The comparison of CFs from LCA and EEIOA databases can provide additional insights into the uncertainties of CF results, which is important knowledge when guiding decision makers. An approach that uses the coefficient of variation to identify strategic database improvement potentials is also presented and highlights several product groups that could deserve additional attention in both databases. Further strategic database improvements are crucial to reduce uncertainties and increase the robustness of decision support that the industrial ecology community can provide for the economic transformations ahead of us.
A.P. Moeller Maersk is taking a stand to move the company towards a more ambitious corporate climate commitment. This has led to a top rating by the Climate Corporate Responsibility Monitor in February 2022 for the integrity of the Maersk net zero pledge.
Maersk is one of the biggest players in the global logistics market. We work with Maersk in their quest to reduce the impacts from their hard-to-abate transport business, with the explicit goal of helping Maersk push the entire market toward greener modes of operation.
2.-0 LCA consultants provide science-based support on:
Read more here on Maersk’s own pages on climate change
Data collection guideline for pressure indicators for Life Cycle based Sustainability Assessment” that covers the specific issues of each pressure category indicator (in LCA parlance called inventory indicators) in the above framework. The pressure category indicators are organised in groups, covering the triple bottom line of economic, ecosystem (resources and emissions), and social (mainly occupational) indicators that are relevant for data collection in the foreground system, i.e., the activities that are under direct control of a decision maker.
This guideline is prepared by Bo P. Weidema of 2.-0 LCA consultants, Denmark, for the 2.-0 SDG Club and the UNEP Life Cycle Initiative as part of the project “Linking the UN Sustainable Development Goals to life cycle impact pathway frameworks”.
We are grateful to UNEP Life Cycle Initiative and the following business members of the project for supporting the development:
• ArcelorMittal (corporate.arcelormittal.com)
• Corbion (Corbion.com)
• Janus (janus.co.jp)
• Novozymes (Novozymes.com)
Around 40% of global raw materials that are extracted every year accumulate as in-use stocks in the form of buildings, infrastructure, transport equipment, and other durable goods. Material inflows to in-use stocks are a key component in the circularity transition, since the reintegration of those materials back into the economy, at the end of the stock's life cycle, means that less extraction of raw materials is required. Thus, understanding the geographical, material, and sectoral distribution of material inflows to in-use stocks globally is crucial for circular economy policies. Here we quantify the geographical, material, and sectoral distributions of material inflows to in-use stocks of 43 countries and 5 rest-of-the-world regions in 2011, using the global, multiregional hybrid units input–output database EXIOBASE v3.3. Among all regions considered, China shows the largest amount of material added to in-use stocks in 2011 (around 46% of global material inflows to in-use stocks), with a per capita value that is comparable to high income regions such as Europe and North America. In these latter regions, more than 90% of in-use stock additions are comprised of non-metallic minerals (e.g., concrete, brick/stone, asphalt, and aggregates) and steel. We discuss the importance of understanding the distribution and composition of materials accumulated in society for a circularity transition. We also argue that future research should integrate the geographical and material resolution of our results into dynamic stock-flow models to determine when these materials will be available for recovery and recycling.
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