{"title":"加纳医院医疗废物管理的综合生命周期评估-系统思维方法","authors":"Ebenezer Aquisman Asare , Dickson Abdul-Wahab , Elsie Effah Kaufmann , Rafeah Wahi , Zainab Ngaini , Archibold Buah-Kwofie","doi":"10.1016/j.clwat.2025.100130","DOIUrl":null,"url":null,"abstract":"<div><div>This study integrates life-cycle assessment (LCA) with systems-thinking to evaluate medical-waste treatment options in five Ghanaian hospitals (KBTH, KATH, CCTH, BRH, UCCH). Using a functional unit of 1 kg mixed hospital waste, inventories were modelled in Brightway2/biosphere3 and characterised with CML v4.8 across eight impact categories. We compared current practice and five improvement scenarios and ranked options via entropy-weighted TOPSIS. Autoclaving emerged as the optimal treatment method with a TOPSIS score of 0.994 (CI: 0.992–0.997), followed by pyrolysis (0.990) and microwave treatment (0.986), while incineration plus landfill performed worst across toxicity and climate indicators. Reductions reported herein are relative (%) changes versus the baseline scenario at each facility. Scenario analysis demonstrates that smaller facilities can achieve complete impact reductions (-100 %) across most environmental categories through improved segregation and technology adoption, while larger facilities show varied improvements ranging from −56.4 % to −84.8 % relative to the baseline. Sensitivity analysis indicated that incineration and landfill treatments are highly sensitive to waste composition and segregation efficiency. Systems-feedback analysis highlights waste-segregation efficiency and emission controls as dominant levers. Findings indicate that upgrading segregation to ≥ 80–95 % and deploying non-burn technologies can yield large relative reductions in human-toxicity and climate-change impacts, supporting Ghana’s policy goals. This combined LCA–systems framework provides a transparent, replicable decision basis for hospital and regional planners. This is the first Ghana-focused framework that integrates LCA, systems thinking, and MCDA to rank hospital waste-treatment choices under uncertainty, quantifying facility-specific, relative impact reductions. It operationalizes evidence into a replicable decision tool for Cleaner Production in LMIC health systems. Practical relevance: across five Ghanaian hospitals, pairing non-burn treatment with ≥ 80–95 % segregation delivers 56–100 % relative reductions in toxicity indicators and ∼75–89 % in climate-change impacts versus baseline. The integrated LCA–systems–MCDA tool is directly usable by hospital planners for Cleaner Production decisions.</div></div>","PeriodicalId":100257,"journal":{"name":"Cleaner Water","volume":"4 ","pages":"Article 100130"},"PeriodicalIF":0.0000,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrated life cycle assessment-systems thinking approach for medical waste management in Ghanaian hospitals\",\"authors\":\"Ebenezer Aquisman Asare , Dickson Abdul-Wahab , Elsie Effah Kaufmann , Rafeah Wahi , Zainab Ngaini , Archibold Buah-Kwofie\",\"doi\":\"10.1016/j.clwat.2025.100130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study integrates life-cycle assessment (LCA) with systems-thinking to evaluate medical-waste treatment options in five Ghanaian hospitals (KBTH, KATH, CCTH, BRH, UCCH). Using a functional unit of 1 kg mixed hospital waste, inventories were modelled in Brightway2/biosphere3 and characterised with CML v4.8 across eight impact categories. We compared current practice and five improvement scenarios and ranked options via entropy-weighted TOPSIS. Autoclaving emerged as the optimal treatment method with a TOPSIS score of 0.994 (CI: 0.992–0.997), followed by pyrolysis (0.990) and microwave treatment (0.986), while incineration plus landfill performed worst across toxicity and climate indicators. Reductions reported herein are relative (%) changes versus the baseline scenario at each facility. Scenario analysis demonstrates that smaller facilities can achieve complete impact reductions (-100 %) across most environmental categories through improved segregation and technology adoption, while larger facilities show varied improvements ranging from −56.4 % to −84.8 % relative to the baseline. Sensitivity analysis indicated that incineration and landfill treatments are highly sensitive to waste composition and segregation efficiency. Systems-feedback analysis highlights waste-segregation efficiency and emission controls as dominant levers. Findings indicate that upgrading segregation to ≥ 80–95 % and deploying non-burn technologies can yield large relative reductions in human-toxicity and climate-change impacts, supporting Ghana’s policy goals. This combined LCA–systems framework provides a transparent, replicable decision basis for hospital and regional planners. This is the first Ghana-focused framework that integrates LCA, systems thinking, and MCDA to rank hospital waste-treatment choices under uncertainty, quantifying facility-specific, relative impact reductions. It operationalizes evidence into a replicable decision tool for Cleaner Production in LMIC health systems. Practical relevance: across five Ghanaian hospitals, pairing non-burn treatment with ≥ 80–95 % segregation delivers 56–100 % relative reductions in toxicity indicators and ∼75–89 % in climate-change impacts versus baseline. The integrated LCA–systems–MCDA tool is directly usable by hospital planners for Cleaner Production decisions.</div></div>\",\"PeriodicalId\":100257,\"journal\":{\"name\":\"Cleaner Water\",\"volume\":\"4 \",\"pages\":\"Article 100130\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cleaner Water\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2950263225000687\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cleaner Water","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2950263225000687","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Integrated life cycle assessment-systems thinking approach for medical waste management in Ghanaian hospitals
This study integrates life-cycle assessment (LCA) with systems-thinking to evaluate medical-waste treatment options in five Ghanaian hospitals (KBTH, KATH, CCTH, BRH, UCCH). Using a functional unit of 1 kg mixed hospital waste, inventories were modelled in Brightway2/biosphere3 and characterised with CML v4.8 across eight impact categories. We compared current practice and five improvement scenarios and ranked options via entropy-weighted TOPSIS. Autoclaving emerged as the optimal treatment method with a TOPSIS score of 0.994 (CI: 0.992–0.997), followed by pyrolysis (0.990) and microwave treatment (0.986), while incineration plus landfill performed worst across toxicity and climate indicators. Reductions reported herein are relative (%) changes versus the baseline scenario at each facility. Scenario analysis demonstrates that smaller facilities can achieve complete impact reductions (-100 %) across most environmental categories through improved segregation and technology adoption, while larger facilities show varied improvements ranging from −56.4 % to −84.8 % relative to the baseline. Sensitivity analysis indicated that incineration and landfill treatments are highly sensitive to waste composition and segregation efficiency. Systems-feedback analysis highlights waste-segregation efficiency and emission controls as dominant levers. Findings indicate that upgrading segregation to ≥ 80–95 % and deploying non-burn technologies can yield large relative reductions in human-toxicity and climate-change impacts, supporting Ghana’s policy goals. This combined LCA–systems framework provides a transparent, replicable decision basis for hospital and regional planners. This is the first Ghana-focused framework that integrates LCA, systems thinking, and MCDA to rank hospital waste-treatment choices under uncertainty, quantifying facility-specific, relative impact reductions. It operationalizes evidence into a replicable decision tool for Cleaner Production in LMIC health systems. Practical relevance: across five Ghanaian hospitals, pairing non-burn treatment with ≥ 80–95 % segregation delivers 56–100 % relative reductions in toxicity indicators and ∼75–89 % in climate-change impacts versus baseline. The integrated LCA–systems–MCDA tool is directly usable by hospital planners for Cleaner Production decisions.