长三角近实时机动车大气污染物排放清单建立研究  

Study on the near real-time vehicle emission inventory of air pollutants inYangtze River Delta

作　　者：卞元东 顾晨 杨金亚 赵瑜[1] BIAN Yuandong;GU Chen;YANG Jinya;ZHAO Yu(State Key Laboratory of Pollution Control&Resource Reuse and School of Environment,Nanjing University,Nanjing 210023)

机构地区：[1]南京大学环境学院,南京大学污染控制与资源化研究国家重点实验室,南京210023

出　　处：《环境科学学报》2025年第2期418-429,共12页Acta Scientiae Circumstantiae

基　　金：国家自然科学基金(No.42177080);江苏省重大科技示范项目(No.BE2022838)。

摘　　要：近实时机动车排放清单的建立有助于及时捕捉和追踪机动车动态排放变化特征,识别机动车排放周期性规律,从而支持精细化管控政策的制定.本研究融合多渠道获取的活动水平数据、国际机动车排放模型(IVE)、实时拥堵延时指数和“标准道路长度法”,构建长三角地区近实时机动车排放清单表征体系;建立了2022年高时空分辨率机动车排放清单和2023年近实时机动车排放清单,探究人为活动方式对机动车排放的影响.结果表明,2022年长三角机动车CO、VOC、NOx和PM_(2.5)污染物排放量分别为353.6×10^(4)、64.9×10^(4)、60.6×10^(4)和7.8×10^(4)t.污染物排放高值主要集中在长三角东部路网密集、交通流量大的城市;排放日变化呈现出“两峰一谷”的特征.人为活动模式变化对机动车排放影响显著:受春节假期和新冠病毒常态化防控措施的影响,排放在2022年中2月初和12月下旬出现较大波动;与日均排放量相比,2022年和2023年春节期间CO排放量分别减少30.4%和23.0%;2022年底常态化防控措施解除后,CO排放量减少15.7%.本研究提升了区域机动车大气污染物排放表征的精细度和时效性,为未来大气污染防治措施的制定提供了科学依据.Development of near real-time vehicle emission inventory is helpful for timely capturing and tracking the dynamic change of vehicle emissions,identifying their periodic pattern,and supporting the policy making of refined controls.Combining the activity level data obtained from multiple channels,International Vehicle Emissions model(IVE),real-time congestion delay index and the“standard road length method”,we constructed a framework of near real-time vehicle emission inventory of air pollutants for Yangtze River Delta(YRD),China.Based on the framework,we developed a vehicle emission inventory with high spatiotemporal resolution for 2022 and a near real-time vehicle emission inventory for 2023,to explore the impact of human activity patterns on air pollutant emissions.The results show that the emissions of CO,VOC,NOx and PM_(2.5)from vehicles in YRD in 2022 were 3536×10^(3),649×10^(3),606×10^(3)and 78×10^(3)t,respectively.The high emissions of air pollutants occurred mainly in the cities with dense road network and large traffic flows in the eastern Yangtze River Delta.The diurnal variation of emissions shows a pattern of"two peaks and one valley".Changes in human activity patterns had a significant impact on vehicle emissions.Due to the impact of the Spring Festival holiday and the regular prevention and control measures of the novel coronavirus,the emission fluctuated greatly in early February and late December 2022.Compared to the average daily emissions,CO emissions from vehicles during the Spring Festival in 2022 and 2023 decreased by 30.4%and 23.0%,respectively.Lifting the regular prevention and control measures resulted in a decline of daily CO emissions by 15.7%.This study improved the precision and timeliness of estimation of regional air pollutant emissions from vehicles and provided scientific evidence for the formulation of air pollution prevention measures.

关 键 词：机动车排放 高时空分辨率 近实时排放清单 日变化 

分 类 号：X51[环境科学与工程—环境工程]