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The main data that support the findings of this study are available as supplementary tables. Additional data are available from the corresponding authors upon request.
The computer code used to generate the results that are reported in this study are available from the corresponding authors on reasonable request.
The authors acknowledge funding from the EPSRC (J.-F.M., fellowship no. EP/K007254/1), the Newton Fund (J.-F.M. and P.S., EPSRC grant nos. EP/N002504/1 and ES/N013174/1), the ERC (M.A.J.H. and S.V.H., grant no. 62002139 ERC – CoG SIZE 647224), Horizon 2020 (J.-F.M., F.K. and H.P.; Sim4Nexus project no. 689150) and the European Commission (J.-F.M., H.P., F.K. and U.C.; DG ENERGY contract no. ENER/A4/2015-436/SER/S12.716128). F.K. acknowledges participants of the CIRED summer school in Paris (2018) for valuable discussions.
F.K. designed the research and wrote the manuscript, with contributions from all authors. S.V.H. and F.K. performed the life-cycle analysis, with contributions from M.A.J.H. F.K., J.-F.M., U.C. and H.P. ran the model simulations. U.C. and H.P. managed E3ME. J.-F.M. and A.L. developed FTT:Transport. F.K. and J.-F.M. developed FTT:Heat. J.-F.M. and P.S. developed FTT:Power.
The authors declare no competing interests.
Publisher''s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Figs. 1–6 and Methods 1–4.
Supplementary Tables 1–9.
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi /10.1038/s41893-020-0488-7
To reduce greenhouse-gas emissions in the short term, and catalyse longer-term cuts, countries should reduce the carbon intensity of electricity generation to below a universal target of 600 tCO2e GWh−1 by 2020.
The author is grateful for reviews by Daniel Hoornweg and Jan Corfee-Morlot.
Published:
Issue Date:
DOI: https://doi /10.1038/nclimate2494
In a previous article, we explained how an inventory of all inputs and outputs is necessary to conduct a Life Cycle Assessment (LCA). In addition, we explained that the benefit of an LCA is to understand environmental impact. We also demonstrated that for corporations with facilities throughout the world, it’s essential to specify the location. Similarly, when inputs or outputs have various processing options, it’s essential to use the appropriate process option in the LCA model to get a valid and accurate result. For example, electricity is a typical input to most facilities, while waste water is a typical output to most facilities. In this article, we’ll look at two examples using electricity production and waste water disposal.
First, let’s look at an example that demonstrates why it’s crucial to consider where we produce a kWh of electricity. In this example, we''ll use two of the commonly known midpoint impact categories of
The scenario modeled below is a factory with 470K sq ft of manufacturing floor space and 150K sq ft of office space. We are assuming that the factory uses 100kWh/sq ft, and the office uses 20kWh/sq ft annually. Therefore, the total annual consumption of electricity is approximately 50 million kWh.
The point of the chart below is not that this hypothetical factory is using 50 million kWh of electricity. Instead, the illustration shows the environmental impact differing significantly depending on the location of this facility.
The chart above shows the midpoint impact category of Global Warming Air in kg CO2 equivalent. In this example, we see that India''s electricity production releases more than twice the CO2 equivalent compared to the United States'' electricity production.
The chart below shows the kg of 2.5 micron-sized particulate matter released in the air as a result of this amount of electricity production.
Next, let’s look at an example that demonstrates why it’s crucial to consider process details of inputs and outputs. In this hypothetical example, the factory is located in the US and produces 10,000 gallons of wastewater per weekday. The critical consideration here is whether the sewage treatment plant that processes their wastewater sends their sludge output to be
In this example, we see in the chart above that from the perspective of the midpoint impact category of Global Warming
In conclusion, these two examples of electricity production and wastewater disposal highlight the importance of specifying location and process details for accurately modeling midpoint impacts and performing Life Cycle Assessment modeling.
For the production stage, Hao et al.24 estimated GHG emissions from the production of LIBs in China by establishing a LCA framework. For the three types of most commonly used LIBs: the LFP battery, the NMC battery and the LMO battery, the GHG emissions from the production of a 28 kWh battery are 3061 kg CO2-eq, 2912 kg CO2-eq and 2705 kg CO2-eq, respectively.
For the use phase, Zeng et al.25 used BYD Qin Pro series models in China as an example to compare the environmental impact of pure BEVs and plug-in hybrid EVs with traditional internal combustion engine vehicles. The result shows that compared to the gasoline ICEV, BEVs and plug-in hybrid EVs driven by the current average power structure in China reduce global warming potential by 23% and 17%, respectively.
For the recovery and reuse stage, Koroma et al.26 conducted a LCA for three different scenarios combined with battery recycling and found that recycling reduced the climate impact of EVs by almost 8%, with human toxicity and mineral resource scarcity reduced by approximately 22% and 25%, respectively. Yang et al.27 used LCA to study the environmental feasibility of reusing waste LIBs in communication base stations. The results show that in all selected categories, the secondary use of EV LIBs has less environmental impact than the use of lead-acid batteries.
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