The greenhouse gas emissions of a German hospital - A case study of an easy-to-use approach based on financial data

Autor: Mattis Keil
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Cleaner Environmental Systems, Vol 11, Iss , Pp 100140- (2023)
Druh dokumentu: article
ISSN: 2666-7894
DOI: 10.1016/j.cesys.2023.100140
Popis: To reduce the impact of anthropogenic climate change, healthcare has to transform to a low greenhouse gas emissions sector. Hospitals are a fundamental part of healthcare provision and can play an important role in mitigating the climate impact of healthcare. To help decision-makers and policy-makers, information on the greenhouse gas emissions of individual hospitals is needed. The aim of this paper is to provide an assessment of a hospital in north-western Germany with a cost-based approach based on financial data from the Profit& Loss Statement. Direct emissions and emissions through energy usage were calculated using quantity-based bottom-up emission intensities. Indirect emissions were calculated using monetary-based top-down emission intensities. To determine these emission intensities for the reported cost groups, 8,772 transactions from the profit and loss statement of a German hospital were assigned to industry sectors provided by two input-output databases. In the final model, the emission intensities of cost groups with large differences between the two databases were substituted with bottom-up data. In total, between 10,398 and 11,147 t CO2eq were emitted by the hospital in 2019. Direct emissions sources were responsible for 37%–40%, electricity production was responsible for 13%–14%, and upstream and downstream processes were responsible for 47%–50% of total emissions. The production of medical supplies accounted for 32%–52% of those processes and was the largest emitter among cost groups. The study shows that the calculation of the carbon footprint of a hospital is possible using a hybrid model based on standardized financial data. The study's results are limited by the chosen system boundaries, by methodological limitations of the chosen top-down approach, and data availability.
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