某加油站VOCs排放溯源及源强反演研究

Research on VOCs source inversion and emission intensity of a gas station

为了计算加油站无组织挥发性有机污染物(Volatile Organic Compounds,VOCs)排放的强度,将扩散模型反推法应用于加油站的无组织VOCs排放溯源研究。对加油站区域建立笛卡尔空间坐标系,并构建监测站实测值和基于大气污染物高斯扩散模式预测值之间的代价函数,进而使用有条件约束的最优化方法求解该代价函数,得到该加油站VOCs无组织排放源强的反演模型。研究结果显示,加油站无组织VOCs的排放速率反演结果为1.8~3.8 g/s,该结果与加油站给车辆加油时未采取二次油气回收系统情形下的挥发量相符,反映了加油站无组织排放源强反演模型合理可信。模型参数分析结果表明,大气稳定度的不确定性对模型收敛和反演结果的影响较大,无组织排放溯源和源强反演需要高质量的气象扩散风场观测数据。

To calculate the emission intensity of fugitive volatile organic compounds(VOCs)in a gas station,this paper applied the diffusion model inversion theory to the research of fugitive VOCs emission features in a gas station.In this model,firstly,taking the northwest corner of a gas station as the origin of the coordinates,the east of the origin was the positive x axis,and the south was the positive axis of y axis.We adopted the cost function to evaluate the differences between the observed values from the monitoring micro-station and the predictive values from Gaussian diffusion model,and we use a constraint optimization algorithm to calculate the cost function.The results show that the instantaneous VOCs emission intensity of a gas station was between 1.8 g/s and 3.8 g/s,which is close to the volatile intensity when a refueling gun without a secondary vapor recovery system is working.Therefore,the model we put forward to calculate the fugitive emission intensity of gas stations is reasonable and credible.We calculated the emission intensity and source location under different atmosphere stabilities,and we drew diagrams of the iteration process of parameters x,y,Q and J.The results show that the emission intensity would be smaller when the atmosphere got more stable.The cost function J minimized under the atmosphere stability B,which manifested that differences between the observed values and the predictive values also got minimum.However,the location parameters x and y were convergent to the margin of the gas station area,which was caused by the boundary conditions from the constraint optimization algorithm.The model parameter analysis results show that the uncertainty of atmospheric stability has a great impact on the model convergence and results,and high-quality meteorological observed data is required for the research of fugitive source detection and emission intensity.