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首页> 外文期刊>Journal of Industrial Ecology >Using spatially explicit commodity flow and truck activity data to map urban material flows
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Using spatially explicit commodity flow and truck activity data to map urban material flows

机译:使用空间明确的商品流量和卡车活动数据来映射城市材料流动

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摘要

To analyze and promote resource efficiency in urban areas, it is important to characterize urban metabolism and particularly, material flows. Material flow analysis (MFA) offers a means to capture the dynamism of cities and their activities. Urban-scale MFAs have been conducted in many cities, usually employing variants of the Eurostat methodology. However, current methodologies generally reduce the study area into a "black box," masking details of the complex processes within the city's metabolism. Therefore, besides the aggregated stocks and flows of materials, the movement of materials-often embedded in goods or commodities-should also be highlighted. Understanding the movement and dispersion of goods and commodities can allow for more detailed analysis of material flows. We highlight the potential benefits of using high-resolution urban commodity flows in the context of understanding material resource use and opportunities for conservation. Through the use of geographic information systems and visualizations, we analyze two spatially explicit datasets: (1) commodity flow data in the United States, and (2) Global Positioning System-based commercial vehicle (truck) driver activity data in Singapore. In the age of "big data," we bring advancements in freight data collection to the field of urban metabolism, uncovering the secondary sourcing of materials that would otherwise have been masked in typical MFA studies. This brings us closer to a consumption-based, finer-resolution approach to MFA, which more effectively captures human activities and its impact on urban environments.
机译:为了分析和促进城市地区的资源效率,重要的是表征城市新陈代谢,特别是材料流动。材料流量分析(MFA)提供捕捉城市的动态和活动的手段。城市规模的MFA已经在许多城市进行,通常使用欧盟统计局方法的变体。然而,目前的方法通常将研究区域减少到“黑匣子”中掩盖了城市新陈代谢内复杂过程的细节。因此,除了汇总的股票和材料的流动之外,还应强调材料 - 通常嵌入货物或商品中的运动 - 也应该被突出。了解商品和商品的运动和分散可以允许对材料流动进行更详细的分析。我们突出了在理解物资资源使用和保护机会的背景下使用高分辨率城市商品流动的潜在好处。通过使用地理信息系统和可视化,我们分析了两个空间显式数据集:(1)美国商品流量数据,(2)新加坡的全球定位系统的商用车(卡车)驾驶员活动数据。在“大数据”时代,我们带来了运费数据收集到城市新陈代谢领域,揭示了否则在典型的MFA研究中掩盖的材料的二次采购。这使我们更接近基于消费,更精细分辨率的MFA方法,这更有效地捕捉人类活动及其对城市环境的影响。

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