Elkafoury Ahmed, Negm Abdelazim M, Aly Mohamed Hafez, Bady Mahmoud F, Ichimura Teijiro
Environmental Engineering Department, School of Energy Resources, Environmental, Chemical and Petrochemical Engineering, Egypt-Japan University of Science and Technology (E-JUST), New Borg Al-Arab City, Alexandria, 21934, Egypt.
Transportation Engineering Department, Faculty of Engineering, University of Alexandria, Alexandria, 21532, Egypt.
Environ Sci Pollut Res Int. 2016 Aug;23(16):15899-910. doi: 10.1007/s11356-015-4319-8. Epub 2015 Mar 21.
The greater the use of energy in the transportation sectors, the higher the emission of carbon monoxide (CO), and hence inevitable harm to environment and human health. In this concern, measuring and predicting of CO emission from transportation sector-especially large cities-is important as it constitute 90 % of all CO emission. Many urban cities in developing world have not properly experienced such measurements or predictions. In this paper, for the first time, field measurements of traffic characteristics data and corresponding CO concentration have been performed for developing a model for predicting CO emissions from transportation sector for New Borg El Arab (NBC), Egypt. The performance of Swiss-German Handbook Emission Factors for Road Transport (HBEFA v3.1) model has been assessed for predicting the CO concentration at roadside in the study area. Results indicated that HBEFA v3.1 underestimate emission figures. The developed CO dynamic emission model involves the traffic flow characteristics with roadside CO concentrations. Acceptable representation of measured CO concentration has been shown by the developed dynamic CO emission model which introduces R (2) = 0.77, mean biases and frictional biases of -0.27 mg m(-3) and 0.09, respectively. A comparison between predicted CO concentrations using HBEFA v3.1 and the promoted dynamic model indicate that HBEFA v3.1 estimates CO emission concentrations in the study area with a mean error and frictional biases 159.26 and 233.33 %, respectively, higher than those of the developed model.
交通运输部门的能源使用量越大，一氧化碳（CO）的排放量就越高，从而不可避免地对环境和人类健康造成危害。鉴于此，测量和预测交通运输部门（尤其是大城市）的一氧化碳排放量非常重要，因为其排放量占一氧化碳排放总量的90%。发展中世界的许多城市尚未进行过此类测量或预测。本文首次对埃及新博格艾尔阿拉伯（NBC）交通运输部门的交通特征数据和相应的一氧化碳浓度进行了实地测量，以建立一个预测该部门一氧化碳排放量的模型。对瑞士 - 德国道路运输手册排放因子（HBEFA v3.1）模型在预测研究区域路边一氧化碳浓度方面的性能进行了评估。结果表明，HBEFA v3.1低估了排放数据。所开发的一氧化碳动态排放模型涉及交通流特征和路边一氧化碳浓度。所开发的动态一氧化碳排放模型对测量的一氧化碳浓度有可接受的表示，其R（2） = 0.77，平均偏差和摩擦偏差分别为 -0.27 mg m⁻³ 和 0.09。使用HBEFA v3.1预测的一氧化碳浓度与所推广的动态模型之间的比较表明，HBEFA v3.1估计研究区域一氧化碳排放浓度的平均误差和摩擦偏差分别比所开发模型高159.26%和233.33%。
