{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:18:20Z","timestamp":1760059100487,"version":"build-2065373602"},"reference-count":62,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,5,20]],"date-time":"2025-05-20T00:00:00Z","timestamp":1747699200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Commission of Shanghai Municipality","award":["23DZ2308400"],"award-info":[{"award-number":["23DZ2308400"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>Decarbonizing production activities is a critical task in the transition towards carbon neutrality. Traditional carbon footprint accounting tools, such as life-cycle assessment (LCA) and the Greenhouse Gas Protocol, primarily quantify direct and indirect emissions but offer limited guidance on actionable reduction strategies. To address this gap, this study proposes a comprehensive life-cycle carbon footprint optimization framework that integrates LCA with a mixed-integer linear programming (MILP) model. The framework, while applicable to various production contexts, is validated using a university campus as a case study. In 2023, the evaluated university\u2019s net carbon emissions totaled approximately 24,175.07 t CO2-eq. Based on gross emissions (28,306.43 t CO2-eq) before offsetting, electricity accounted for 66.09%, buildings for 15.55%, fossil fuels for 8.67%, and waste treatment for 8.46%. Seasonal analysis revealed that June and December exhibited the highest energy consumption, with emissions exceeding the monthly average by 19.4% and 48.6%, respectively, due to energy-intensive air conditioning demand. Teaching activities emerged as a primary contributor, with baseline emissions estimated at 5485.24 t CO2-eq. Optimization strategies targeting course scheduling yielded substantial reductions: photovoltaic-based scheduling reduced electricity emissions by 7.00%, seasonal load shifting achieved a 26.92% reduction, and combining both strategies resulted in the highest reduction, at 45.95%. These results demonstrate that aligning academic schedules with photovoltaic generation and seasonal energy demand can significantly enhance emission reduction outcomes. The proposed framework provides a scalable and transferable approach for integrating time-based and capacity-based carbon optimization strategies across broader operational systems beyond the education sector.<\/jats:p>","DOI":"10.3390\/systems13050395","type":"journal-article","created":{"date-parts":[[2025,5,20]],"date-time":"2025-05-20T08:41:12Z","timestamp":1747730472000},"page":"395","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Life-Cycle Carbon Reduction Optimization Framework for Production Activity Systems: A Case Study on a University Campus"],"prefix":"10.3390","volume":"13","author":[{"given":"Xiangze","family":"Wang","sequence":"first","affiliation":[{"name":"Innovation Center for Environment and Resources, Shanghai University of Engineering Science, No. 333 Longteng Road, Songjiang District, Shanghai 201620, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingqi","family":"Deng","sequence":"additional","affiliation":[{"name":"Innovation Center for Environment and Resources, Shanghai University of Engineering Science, No. 333 Longteng Road, Songjiang District, Shanghai 201620, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3417-8267","authenticated-orcid":false,"given":"Tingting","family":"Hu","sequence":"additional","affiliation":[{"name":"Innovation Center for Environment and Resources, Shanghai University of Engineering Science, No. 333 Longteng Road, Songjiang District, Shanghai 201620, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dungang","family":"Gu","sequence":"additional","affiliation":[{"name":"Innovation Center for Environment and Resources, Shanghai University of Engineering Science, No. 333 Longteng Road, Songjiang District, Shanghai 201620, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Liu","sequence":"additional","affiliation":[{"name":"Innovation Center for Environment and Resources, Shanghai University of Engineering Science, No. 333 Longteng Road, Songjiang District, Shanghai 201620, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guanghui","family":"Li","sequence":"additional","affiliation":[{"name":"Innovation Center for Environment and Resources, Shanghai University of Engineering Science, No. 333 Longteng Road, Songjiang District, Shanghai 201620, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4996-9539","authenticated-orcid":false,"given":"Nan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Centre for Process Integration, Department of Chemical Engineering and Analytical Science, The University of Manchester, Manchester M13 9PL, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7864-1981","authenticated-orcid":false,"given":"Jiaqi","family":"Lu","sequence":"additional","affiliation":[{"name":"Innovation Center for Environment and Resources, Shanghai University of Engineering Science, No. 333 Longteng Road, Songjiang District, Shanghai 201620, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"124010","DOI":"10.1088\/1748-9326\/aa9def","article-title":"Global Mean Sea-Level Rise in a World Agreed upon in Paris","volume":"12","author":"Bittermann","year":"2017","journal-title":"Environ. 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