{"title":"改进飞机起降活动模型,提高对航空二氧化碳和污染物排放的估计","authors":"Chaoyu Wen, Jianlei Lang, Yunya Fu, Zekang Yang, Xiaoqing Cheng, Ying Zhou, Shaojun Zhang, Dongsheng Chen, Shuiyuan Cheng","doi":"10.1038/s41612-025-01195-6","DOIUrl":null,"url":null,"abstract":"<p>Air transport has become the fastest-growing carbon/air pollutant emission sources. Landing-takeoff (LTO) management is a cost-effective way to address aviation’s low-emission, decarbonization and energy-conservation challenges. Accurate estimation of LTO fuel and emissions is crucial. However, the widely-used International Civil Aviation Organization (ICAO) method with constant time-in-mode resulted in huge uncertainties. We established the Aircraft Landing-takeoff Time, Fuel, and Emission Model (ALTFEM), substantially improving the capability of dynamically capturing time-in-mode, to estimate LTO fuel consumption and emissions for each flight. The time-in-mode estimation errors of ALTFEM-estimated taxi in/out durations were reduced by 30.2% and 118% compared to ICAO-suggested defaults (taxi-in:420 s, taxi-out:1140 s). Our work improved the accuracy of airport-specific estimates for fuel, HC, NOx, and CO<sub>2</sub> by 14%–40%, compared to ICAO-based results. Unexpected higher (1.1–1.2 times) energy-saving potentials during low-traffic periods were found in busy airports with longer taxi durations (e.g., the Shanghai-Pudong-International-Airport), implying a potential effective mitigation direction.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"28 1","pages":""},"PeriodicalIF":8.4000,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Refined aircraft landing-takeoff activity modeling to improve the estimation of aviation CO2 and pollutants emissions\",\"authors\":\"Chaoyu Wen, Jianlei Lang, Yunya Fu, Zekang Yang, Xiaoqing Cheng, Ying Zhou, Shaojun Zhang, Dongsheng Chen, Shuiyuan Cheng\",\"doi\":\"10.1038/s41612-025-01195-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Air transport has become the fastest-growing carbon/air pollutant emission sources. Landing-takeoff (LTO) management is a cost-effective way to address aviation’s low-emission, decarbonization and energy-conservation challenges. Accurate estimation of LTO fuel and emissions is crucial. However, the widely-used International Civil Aviation Organization (ICAO) method with constant time-in-mode resulted in huge uncertainties. We established the Aircraft Landing-takeoff Time, Fuel, and Emission Model (ALTFEM), substantially improving the capability of dynamically capturing time-in-mode, to estimate LTO fuel consumption and emissions for each flight. The time-in-mode estimation errors of ALTFEM-estimated taxi in/out durations were reduced by 30.2% and 118% compared to ICAO-suggested defaults (taxi-in:420 s, taxi-out:1140 s). Our work improved the accuracy of airport-specific estimates for fuel, HC, NOx, and CO<sub>2</sub> by 14%–40%, compared to ICAO-based results. Unexpected higher (1.1–1.2 times) energy-saving potentials during low-traffic periods were found in busy airports with longer taxi durations (e.g., the Shanghai-Pudong-International-Airport), implying a potential effective mitigation direction.</p>\",\"PeriodicalId\":19438,\"journal\":{\"name\":\"npj Climate and Atmospheric Science\",\"volume\":\"28 1\",\"pages\":\"\"},\"PeriodicalIF\":8.4000,\"publicationDate\":\"2025-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"npj Climate and Atmospheric Science\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1038/s41612-025-01195-6\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Climate and Atmospheric Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1038/s41612-025-01195-6","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Refined aircraft landing-takeoff activity modeling to improve the estimation of aviation CO2 and pollutants emissions
Air transport has become the fastest-growing carbon/air pollutant emission sources. Landing-takeoff (LTO) management is a cost-effective way to address aviation’s low-emission, decarbonization and energy-conservation challenges. Accurate estimation of LTO fuel and emissions is crucial. However, the widely-used International Civil Aviation Organization (ICAO) method with constant time-in-mode resulted in huge uncertainties. We established the Aircraft Landing-takeoff Time, Fuel, and Emission Model (ALTFEM), substantially improving the capability of dynamically capturing time-in-mode, to estimate LTO fuel consumption and emissions for each flight. The time-in-mode estimation errors of ALTFEM-estimated taxi in/out durations were reduced by 30.2% and 118% compared to ICAO-suggested defaults (taxi-in:420 s, taxi-out:1140 s). Our work improved the accuracy of airport-specific estimates for fuel, HC, NOx, and CO2 by 14%–40%, compared to ICAO-based results. Unexpected higher (1.1–1.2 times) energy-saving potentials during low-traffic periods were found in busy airports with longer taxi durations (e.g., the Shanghai-Pudong-International-Airport), implying a potential effective mitigation direction.
期刊介绍:
npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols.
The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.