Community-scale big data reveals disparate impacts of the Texas winter storm of 2021 and its managed power outage

TLDR

Aggregated community‑scale data can reveal how extreme weather events, such as the February 2021 Texas winter storm that triggered rolling blackouts to avert grid collapse, disproportionately affect vulnerable populations through power outages, burst pipes, and food inaccessibility. The study aims to expose how managed power outages during the February 2021 Texas winter storm disproportionately affected vulnerable subpopulations in Harris County. The authors collected community‑scale data and applied statistical and trend‑classification analyses to assess the impacts. The analysis revealed that low‑income and minority groups experienced longer and more severe power outages, burst pipes, and food access disruptions, underscoring inequality in outage management and highlighting the utility of community‑scale data for rapid post‑event impact assessment.

Abstract

Aggregated community-scale data could be harnessed to provide insights into the disparate impacts of managed power outages, burst pipes, and food inaccessibility during extreme weather events. During the winter storm that brought historically low temperatures, snow, and ice to the entire state of Texas in February 2021, Texas power-generating plant operators resorted to rolling blackouts to prevent collapse of the power grid when power demand overwhelmed supply. To reveal the disparate impact of managed power outages on vulnerable subpopulations in Harris County, Texas, which encompasses the city of Houston, we collected and analyzed community-scale big data using statistical and trend classification analyses. The results highlight the spatial and temporal patterns of impacts on vulnerable subpopulations in Harris County. The findings show a significant disparity in the extent and duration of power outages experienced by low-income and minority groups, suggesting the existence of inequality in the management and implementation of the power outage. Also, the extent of burst pipes and disrupted food access, as a proxy for storm impact, were more severe for low-income and minority groups. Insights provided by the results could form a basis from which infrastructure operators might enhance social equality during managed service disruptions in such events. The results and findings demonstrate the value of community-scale big data sources for rapid impact assessment in the aftermath of extreme weather events.