Li Run-Kui, Zhao Tong, Li Zhi-Peng, Ding Wen-Jun, Cui Xiao-Yong, Xu Qun, Song Xian-Feng
Huan Jing Ke Xue. 2014 Apr;35(4):1245-9.
On-road vehicle emissions have become the main source of urban air pollution and attracted broad attentions. Vehicle emission factor is a basic parameter to reflect the status of vehicle emissions, but the measured emission factor is difficult to obtain, and the simulated emission factor is not localized in China. Based on the synchronized increments of traffic flow and concentration of air pollutants in the morning rush hour period, while meteorological condition and background air pollution concentration retain relatively stable, the relationship between the increase of traffic and the increase of air pollution concentration close to a road is established. Infinite line source Gaussian dispersion model was transformed for the inversion of average vehicle emission factors. A case study was conducted on a main road in Beijing. Traffic flow, meteorological data and carbon monoxide (CO) concentration were collected to estimate average vehicle emission factors of CO. The results were compared with simulated emission factors of COPERT4 model. Results showed that the average emission factors estimated by the proposed approach and COPERT4 in August were 2.0 g x km(-1) and 1.2 g x km(-1), respectively, and in December were 5.5 g x km(-1) and 5.2 g x km(-1), respectively. The emission factors from the proposed approach and COPERT4 showed close values and similar seasonal trends. The proposed method for average emission factor estimation eliminates the disturbance of background concentrations and potentially provides real-time access to vehicle fleet emission factors.
道路机动车排放已成为城市空气污染的主要来源,并引起了广泛关注。机动车排放因子是反映机动车排放状况的一个基本参数,但实测排放因子难以获取,且模拟排放因子在中国缺乏本地化。基于早高峰时段交通流量与空气污染物浓度的同步增加,在气象条件和背景空气污染浓度相对稳定的情况下,建立了靠近道路的交通量增加与空气污染浓度增加之间的关系。对无限长线源高斯扩散模型进行变换,用于反演平均机动车排放因子。以北京一条主干道为例进行了研究。收集交通流量、气象数据和一氧化碳(CO)浓度,以估算CO的平均机动车排放因子。将结果与COPERT4模型的模拟排放因子进行比较。结果表明,该方法和COPERT4模型在8月份估算的平均排放因子分别为2.0 g·km⁻¹和1.2 g·km⁻¹,12月份分别为5.5 g·km⁻¹和5.2 g·km⁻¹。该方法和COPERT4模型得到的排放因子数值接近,季节趋势相似。所提出的平均排放因子估算方法消除了背景浓度的干扰,并有可能实时获取机动车队排放因子。