{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T16:00:00Z","timestamp":1788019200358,"version":"build-2784847793"},"reference-count":39,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T00:00:00Z","timestamp":1759795200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Fundamental Research Funds for Center Universities of China","award":["J2023-040, 24CAFUC04021"],"award-info":[{"award-number":["J2023-040, 24CAFUC04021"]}]},{"name":"Key Lab. for Civil Aviation Data Governance and Decision Optimization of Civil Aviation Management Institute of China","award":["CAMICCADGDO-2025-01-01"],"award-info":[{"award-number":["CAMICCADGDO-2025-01-01"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["U2033213"],"award-info":[{"award-number":["U2033213"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:p>To address the challenges of increasing carbon dioxide (CO<jats:sub>2<\/jats:sub>) emissions and climate change caused by the growth of air traffic, accurate prediction of CO<jats:sub>2<\/jats:sub> emissions in civil aviation has become crucial. This study proposes a CO<jats:sub>2<\/jats:sub> emission prediction method based on an improved back propagation (BP) neural network, where the Improved Sparrow Search Algorithm (ISSA) is employed to optimize the hyperparameters of the BP neural network, thereby enhancing the prediction capability for CO<jats:sub>2<\/jats:sub> emissions in civil aviation. To overcome the limitations of the traditional SSA, such as the tendency to fall into local optima during population initialization and the search process, this paper introduces Tent mapping for population initialization and incorporates adaptive t-distribution-based perturbation for individual position updates during the mutation operation, aiming to improve the algorithm\u2019s global search ability and convergence performance. Subsequently, the ISSA algorithm is applied to optimize the weights and biases of the BP neural network, further constructing an ISSA-BP neural network-based prediction model for civil aviation CO<jats:sub>2<\/jats:sub> emissions. Experimental results demonstrate that the improved BP neural network outperforms other comparative models in terms of prediction accuracy and error control, enabling accurate prediction of civil aviation CO<jats:sub>2<\/jats:sub> emissions. This research provides a solid theoretical foundation for formulating precise energy-saving and emission-reduction strategies in civil aviation.<\/jats:p>","DOI":"10.1371\/journal.pone.0333226","type":"journal-article","created":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T17:31:36Z","timestamp":1759858296000},"page":"e0333226","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":6,"title":["Air transportation carbon dioxide emission forecasting: An improved back propagation neural network"],"prefix":"10.1371","volume":"20","author":[{"given":"Peiwen","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunan","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6806-764X","authenticated-orcid":true,"given":"Qian","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhifeng","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,10,7]]},"reference":[{"issue":"10417","key":"pone.0333226.ref001","doi-asserted-by":"crossref","first-page":"2055","DOI":"10.1016\/S0140-6736(23)02584-9","article-title":"Further delays in tackling greenhouse gas emissions at COP28 will be an act of negligence","volume":"402","author":"M Romanello","year":"2023","journal-title":"Lancet"},{"issue":"4","key":"pone.0333226.ref002","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1175\/2009BAMS2850.1","article-title":"Impact of aviation on climate: research priorities","volume":"91","author":"GP Brasseur","year":"2010","journal-title":"Bull Am Meteorol Soc"},{"issue":"4","key":"pone.0333226.ref003","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1080\/01441647.2020.1738587","article-title":"Air transport and economic growth: a review of the impact mechanism and causal relationships","volume":"40","author":"F Zhang","year":"2020","journal-title":"Trans Rev"},{"key":"pone.0333226.ref004","unstructured":"Comac. 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