基于大涡模拟的甲烷点源排放无人机观测实验：排放速率及其不确定度估算

赵昭; 孙世玮; 周博闻; 孙鉴泞; 陈辉林

引用本文:	赵昭,孙世玮,周博闻,孙鉴泞,陈辉林.基于大涡模拟的甲烷点源排放无人机观测实验：排放速率及其不确定度估算[J].环境监控与预警,2023,15(5):65-74
	ZHAO Zhao,SUN Shiwei,ZHOU Bowen,SUN Jianning,CHEN Huilin.An Experiment on UAV Observation of Methane Point Source Emissions Based on Large Eddy Simulation： Estimation of Emission Rates and Their Uncertainties[J].Environmental Monitoring and Forewarning,2023,15(5):65-74

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基于大涡模拟的甲烷点源排放无人机观测实验：排放速率及其不确定度估算
赵昭¹，孙世玮²，周博闻¹，孙鉴泞¹，陈辉林^1*
1.南京大学，大气科学学院，江苏南京 210023；2.南京气象科技创新研究院，中国气象局交通气象重点开放实验室，江苏南京 210041

摘要:

无人机已被证明是适用于甲烷点源排放速率估算的一种新颖且有效的观测平台，然而对其估算的准确度与不确定度尚缺乏有效分析与量化。利用包含已知排放速率被动示踪物的大涡模拟，再现了1种强湍流混合环境下的甲烷羽流并对羽流进行了连续多次模拟飞行观测实验，通过逆高斯方法（IG）和质量平衡方法（MB）对排放速率进行了估算并量化了其准确度与不确定度，最后对不同的飞行时间安排及差异化的空间飞行策略进行了探究以提升估算效果。结果表明，对于研究所涉及的大气混合条件，通过IG和MB方法对多次模拟飞行估算的排放均值可达到既定排放值的95.3%和86.1%，不确定度为56.6%和56.9%；通过单架无人机多次重复飞行采样进行估算可显著降低不确定度，5次重复飞行可降至＜30%；2架无人机在不同高度的同步飞行可使MB方法估算的不确定度降至35.2%～51.9%，IG方法则对该措施不敏感。研究仅考虑甲烷的传输扩散过程，结果也适用于其他被动示踪物的点源排放估算。

关键词: 甲烷点源排放无人机观测大涡模拟大气湍流

DOI：10.3969/j.issn.1674-6732.2023.05.010

分类号:X831

基金项目:国家重点研发计划（2022YFE0209100）；国家自然科学基金-青年科学基金项目（42105151）；中国气象科学研究院-基本科研业务费专项资金项目（2021Y008）

An Experiment on UAV Observation of Methane Point Source Emissions Based on Large Eddy Simulation： Estimation of Emission Rates and Their Uncertainties

ZHAO Zhao¹， SUN Shiwei²， ZHOU Bowen¹， SUN Jianning¹， CHEN Huilin^1*

1.School of Atmospheric Sciences， Nanjing University， Nanjing， Jiangsu 210023， China；2. Key Laboratory of Transportation Meteorology of China Meteorological Administration， Nanjing Joint Institute for Atmospheric Sciences， Nanjing， Jiangsu 210041， China

Abstract:

Unmanned aerial vehicles(UAV) have been shown to be a novel and effective observation platform for the estimation of methane point source emission rates， however， quantitative analysis of the accuracy and the uncertainty of UAV estimates is still lacking. In this study， we have simulated a passive methane plume released from a point source at a constant emission rate in a strongly turbulent mixing environment using large eddy simulation. Furthermore， we have performed multiple consecutive flight observation experiments based on the simulated plume， and estimated the emission rates using both inverse Gaussian(IG) and mass balance(MB) methods. The accuracy and the uncertainty of the estimates have been assessed. Moreover， we have investigated different flight schedules and patterns to improve the estimation performance. The results show that the mean values of the emissions estimated from multiple simulated flights by both IG and MB methods can reach 95% and 86% of the actual emissions， with uncertainties of 56.6% and 56.9% respectively; the uncertainty can be significantly reduced by repeated flights using a single UAV， e.g.， to less than 30% with five flights; Simultaneous flights using two UAVs at different altitudes reduce the uncertainty of the MB method estimate to 35.2%～51.9%， while the IG method is insensitive to this measure. As this study considers the transport and dispersion of methane only， the results are applicable to the estimates of emission rates of other point sources of passive pollutants.

Key words: Methane Point source UAV observation Large Eddy Simulation Atmospheric turbulence