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A Method to Assess and Reduce Pollutant Emissions of Logistic Transportation under Adverse Weather
With the increase of vehicle activities and adverse weather under the background of modernization and global warming, more attention should be paid to vehicle emissions reduction in such circumstances for environmental protection and sustainable transportation. Different from some typical measures, e.g., relevant government policies, improvement of vehicle hardware technologies, and optimization of traffic management, this paper develop a new method based on emergency path optimization to evaluate and reduce pollutant emissions of logistic transportation under adverse weather. Firstly, we establish a calculation model of pollutant emissions (LT-PE model) to calculate the amount of vehicle pollutant emissions produced under adverse weather. Then, a co-evolving path optimization (CEPO) method-based ripple-spreading algorithm is proposed in order to reduce pollutant emissions. To validate the effectiveness of the proposed method, this paper selects fruit logistics transportation affected by typhoon in China’s Hainan Island as a case study. The results show that total vehicle pollutant emissions from the fruit transportation of 35 farms under the typhoon are 28.1% more than when there is no typhoon. The proposed method can reduce pollutant emissions by 21.2% compared with the traditional methods under typhoon.
A Method to Assess and Reduce Pollutant Emissions of Logistic Transportation under Adverse Weather
With the increase of vehicle activities and adverse weather under the background of modernization and global warming, more attention should be paid to vehicle emissions reduction in such circumstances for environmental protection and sustainable transportation. Different from some typical measures, e.g., relevant government policies, improvement of vehicle hardware technologies, and optimization of traffic management, this paper develop a new method based on emergency path optimization to evaluate and reduce pollutant emissions of logistic transportation under adverse weather. Firstly, we establish a calculation model of pollutant emissions (LT-PE model) to calculate the amount of vehicle pollutant emissions produced under adverse weather. Then, a co-evolving path optimization (CEPO) method-based ripple-spreading algorithm is proposed in order to reduce pollutant emissions. To validate the effectiveness of the proposed method, this paper selects fruit logistics transportation affected by typhoon in China’s Hainan Island as a case study. The results show that total vehicle pollutant emissions from the fruit transportation of 35 farms under the typhoon are 28.1% more than when there is no typhoon. The proposed method can reduce pollutant emissions by 21.2% compared with the traditional methods under typhoon.
A Method to Assess and Reduce Pollutant Emissions of Logistic Transportation under Adverse Weather
Mingkong Zhang (author) / Xiaobing Hu (author) / Jingai Wang (author)
2019
Article (Journal)
Electronic Resource
Unknown
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