首页|数据驱动的机场航空器污染物排放清单及特征分析

数据驱动的机场航空器污染物排放清单及特征分析

Data-driven airport aircraft pollutant emission inventory and characteristics analysis

扫码查看
提高机场航空器污染物排放清单精度是发展绿色民航的重要前提.本文首先以2019年广州白云国际机场航班运行数据和航空例行天气报告数据为数据驱动,对发动机燃油流量、污染物排放指数、混合层高度和航班运行阶段时长等关键参数进行计算修正;其次,基于国际民航组织标准模型和数据驱动修正模型(简称修正模型)建立碳氢化合物(HC)、一氧化碳(CO)和氮氧化物(NOx)的排放清单并进行对比分析;最后,从航空器类型、时间和空间3个维度探究污染物的排放特征.结果表明:修正模型得到的HC、CO、NOx年排放量比标准模型分别降低了10.26%、11.94%、26.03%;A320机型具有较低的排放强度;08:00-10:00为3类污染物的高峰排放时段,而02:00-03:00为低峰时段;HC和CO全年排放变化较小,而NOx在混合层高度偏高和相对湿度偏低的11-12月排放偏高;3类污染物排放主要分布于离港航路点LMN、YIN、VIBOS所对应的空间方向.
Improving the accuracy of the airport aircraft pollutant emission inventory is an important prerequisite for the de-velopment of green civil aviation.Firstly,this study uses the data of flight operation and aviation routine weather report of Guangzhou Baiyun International Airport in 2019 as the driving force to calculate and correct key parame-ters such as flow rate of engine fuel,pollutant emission index,mixing layer height and flight operation stage dura-tion.Secondly,the emission inventories for hydrocarbons(HC),carbon monoxide(CO)and nitrogen oxides(NOx)are established and compared based on the standard model of International Civil Aviation Organization and data-driven correction model(abbreviated as correction model),and comparative analysis is conduced.Finally,the pol-lutant emission characteristics are explored from three dimensions including aircraft type,time and space.The re-sults show that the annual emissions of HC,CO and NOx obtained by the corrected model are 10.26%,11.94%,and 26.03%lower than those of the standard model.A320 aircraft type has lower emission intensities.The peak emis-sions of three pollutants occur from 08:00 to 10:00,while the off-peak emission times are from 02:00 to 03:00.HC and CO emissions change little throughout the year,in contrast,NOx emissions are higher in November and December when the mixing layer height is higher and the relative humidity is lower.The emissions of the three pol-lutants are concentrated in the directions corresponding to the departure route points of LMN,YIN and VIBOS.

emission inventorydata-drivenairport areaaircraftemission characteristics

孙娇娇、胡荣、潘肖然、邓松武、官兆玮

展开 >

南京航空航天大学民航学院,南京 211106

广东省机场管理集团有限公司,广东韶关 512000

广西低空飞行服务站,南宁 530012

排放清单 数据驱动 机场区域 航空器 排放特征

2024

中国民航大学学报
中国民航大学

中国民航大学学报

影响因子:0.363
ISSN:1674-5590
年,卷(期):2024.42(5)