Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08540.
Humphrey School of Public Affairs, University of Minnesota, Twin Cities, Minneapolis, MN 55455.
Proc Natl Acad Sci U S A. 2021 Jun 15;118(24). doi: 10.1073/pnas.2023554118.
Cities seek nuanced understanding of intraurban inequality in energy use, addressing both income and race, to inform equitable investment in climate actions. However, nationwide energy consumption surveys are limited (<6,000 samples in the United States), and utility-provided data are highly aggregated. Limited prior analyses suggest disparity in energy use intensity (EUI) by income is ∼25%, while racial disparities are not quantified nor unpacked from income. This paper, using new empirical fine spatial scale data covering all 200,000 households in two US cities, along with separating temperature-sensitive EUI, reveals intraurban EUI disparities up to a factor of five greater than previously known. We find 1) annual EUI disparity ratios of 1.27 and 1.66, comparing lowest- versus highest-income block groups (i.e., 27 and 66% higher), while previous literature indicated only ∼25% difference; 2) a racial effect distinct from income, wherein non-White block groups (highest quintile non-White percentage) in the lowest-income stratum reported up to a further ∼40% higher annual EUI than less diverse block groups, providing an empirical estimate of racial disparities; 3) separating temperature-sensitive EUI unmasked larger disparities, with heating-cooling electricity EUI of lowest-income block groups up to 2.67 times (167% greater) that of highest income, and high racial disparity within lowest-income strata wherein high non-White (>75%) population block groups report EUI up to 2.56 times (156% larger) that of majority White block groups; and 4) spatial scales of data aggregation impact inequality measures. Quadrant analyses are developed to guide spatial prioritization of energy investment for carbon mitigation and equity. These methods are potentially translatable to other cities and utilities.
城市需要深入了解城市内部能源使用方面的不平等现象，既要考虑收入因素，也要考虑种族因素，从而为公平投资气候行动提供信息。然而，全国性的能源消耗调查样本有限（美国的调查样本不到 6000 个），而且公用事业提供的数据高度汇总。有限的先前分析表明，收入差距导致的能源使用强度（EUI）差异约为 25%，而种族差异并未从收入角度进行量化或分解。本文利用新的实证精细空间尺度数据，涵盖了美国两个城市的所有 20 万户家庭，并分离出对温度敏感的 EUI，揭示了城市内部 EUI 差异高达此前已知水平的五倍。我们发现：1）比较最低收入和最高收入街区组，年 EUI 差异比为 1.27 和 1.66（即分别高出 27%和 66%），而先前的文献表明差异仅约为 25%；2）一个与收入不同的种族效应，即收入最低阶层中最高非白人比例（最高五分位非白人比例）的街区组报告的年 EUI 比多样性较低的街区组高出约 40%，这提供了种族差异的实证估计；3）分离出对温度敏感的 EUI 揭示了更大的差异，最低收入街区组的冷暖电 EUI 高达最高收入街区组的 2.67 倍（高 167%），在收入最低阶层中，高非白人（>75%）人口街区组的 EUI 比以白人为多数的街区组高 2.56 倍（高 156%），且种族差异较大；4）数据聚合的空间尺度会影响不平等指标。象限分析用于指导碳减排和公平性方面的能源投资的空间优先级排序。这些方法可能适用于其他城市和公用事业。
