在成本,排放和适应性优化场景中,美国的多模式和多谷物粮食运输模式
Deniz Berfin Karakoc1, Megan Konar2
1Arizona State University, School of Computing and Augmented Intelligence, 699 S Mill Ave, Tempe, Arizona 85281, United States.
Environmental science & technology
|August 21, 2025
概括
在美国重新设计谷物运输可以大大减少二氧化碳排放. 战略转向铁路和水路,以及高速公路,提供可持续的农业食品运输解决方案.
科学领域:
- 农业物流
- 供应链管理
- 环境科学
背景情况:
- 谷物是美国数百万人的必需,负担得起的主食.
- 目前的运输方式,主要是长途柴油卡车,对环境产生重大影响.
- 谷物的不易腐烂性质可以优化运输.
研究的目的:
- 将目前的美国谷物谷物运输模式与优化场景进行比较.
- 评估粮食运输成本,碳排放和适应性之间的权衡.
- 提供可持续农业食品物流战略的信息.
主要方法:
- 开发一个数据驱动的多目标优化模型.
- 经验性的多式联运和多谷物谷物运输数据的分析.
- 与成本,排放和适应性情景对比目前的模式.
主要成果:
- 现有的谷物谷物运输模式显示出高度的适应性.
- 在高速公路,铁路和水路上进行粮食战略分配可以减少排放.
- 优化的情景显示,散装运输的碳足迹可能更低.
结论:
- 美国的谷物运输可以变得更加可持续.
- 通过优化物流可以实现效率,弹性和环境影响的平衡.
- 这些发现支持为更绿色的农业食品供应链做出明智的决策.
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