{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,13]],"date-time":"2026-09-13T04:49:18Z","timestamp":1789274958044,"version":"build-2803163510"},"reference-count":52,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T00:00:00Z","timestamp":1768867200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100018693","name":"Horizon Europe","doi-asserted-by":"publisher","award":["101137054"],"award-info":[{"award-number":["101137054"]}],"id":[{"id":"10.13039\/100018693","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,6,30]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Haemodialysis (HD) contributes vastly to greenhouse gas (GHG) emissions. Recognizing this, the German Society for Nephrology initiated a web-based carbon footprint assessment tool to benchmark emissions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study collected data from five pilot HD centres between 2015 and 2023. Emission categories appropriate for HD were defined and included transportation, energy consumption, manufacturing\/disposal and other operational factors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The all-centre, all-period average was 3.72\u00a0\u00b1\u00a00.44\u00a0tons of carbon dioxide equivalents per patient per year, with manufacturing\/disposal, energy consumption and patient transportation as the largest contributions. Over the assessment period, a reduction of 9.1% was achieved, through changes in dialysate flow (\u22120.16\u00a0tons\/patient\/year), solar power system installation (\u22120.21 tons\/patient\/year) and transition to a planetary health\u2013adapted diet (\u22120.10\u00a0tons\/patient\/year). A best-case scenario with modelled implementation of all ready-to-use measures, including 40% of patients switching to automated peritoneal dialysis and 10% to incremental HD, projected a reduction potential of 38.7% or 1.5\u00a0tons\/patient\/year, substantially less than what is needed to reach net zero.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Using available technology, HD-related GHG emissions were reduced by 9% in the short term. Higher future reductions to meet the targets of a 50% reduction by 2030 and net zero by 2045 might necessitate enhancing prevention and transplantation efforts, technological innovation, support chain adaptations and structural changes like increased use of peritoneal dialysis.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ndt\/gfaf263","type":"journal-article","created":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T12:53:36Z","timestamp":1768481616000},"page":"1294-1303","source":"Crossref","is-referenced-by-count":4,"title":["A website calculator to benchmark the carbon footprint of haemodialysis"],"prefix":"10.1093","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1907-825X","authenticated-orcid":false,"given":"Joachim","family":"Beige","sequence":"first","affiliation":[{"name":"Kuratorium for Dialysis and Transplantation , Neu-Isenburg ,","place":["Germany"]},{"name":"Martin Luther University Halle\u2013Wittenberg, Halle\u2013Wittenberg 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