4.7 Article

Disproportionate exposure to surface-urban heat islands across vulnerable populations in Lima city, Peru

期刊

ENVIRONMENTAL RESEARCH LETTERS
卷 18, 期 7, 页码 -

出版社

IOP Publishing Ltd
DOI: 10.1088/1748-9326/acdca9

关键词

temperature; socioeconomic inequity; urban heat island

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Climate change presents an unprecedented challenge to public health, with extreme temperatures being one of its main direct effects. The variance in temperature within urban areas, known as the surface urban heat island (SUHI) effect, was assessed in Lima, Peru. Land surface temperature (LST) was estimated using satellite data and socioeconomic data were obtained from the census. The study found that blocks with higher socioeconomic status had reduced exposure to SUHI compared to those with lower socioeconomic status. It also revealed significant variations in SUHI exposure among different ethnicities. These findings emphasize the importance of addressing socioeconomic inequalities when designing urban adaptation strategies to mitigate SUHI exposure.
Climate change constitutes an unprecedented challenge for public health and one of its main direct effects are extreme temperatures. It varies between intra-urban areas and this difference is called surface urban heat island (SUHI) effect. We aimed to assess SUHI distribution among socioeconomic levels in Lima, Peru by conducting a cross-sectional study at the block-level. The mean land surface temperature (LST) from 2017 to 2021 were estimated using the TIRS sensor (Landsat-8 satellite [0.5 km scale]) and extracted to block level. SUHI was calculated based on the difference on mean LST values (2017-2021) per block and the lowest LST registered in a block. Socioeconomic data were obtained from the 2017 Peruvian census. A principal component analysis was performed to construct a socioeconomic index and a mixture analysis based on quantile g-computation was conducted to estimate the joint and specific effects of socioeconomic variables on SUHI. A total of 69 618 blocks were included in the analysis. In the Metropolitan Lima area, the mean SUHI estimation per block was 6.44 (SD = 1.44) Celsius degrees. We found that blocks with high socioeconomic status (SES) showed a decreased exposure to SUHI, compared to those blocks where the low SES were predominant (p-value < 0.001) and that there is a significant SUHI exposure variation (p-value < 0.001) between predominant ethnicities per block (Non-White, Afro-American, and White ethnicities). The mixture analysis showed that the overall mixture effect estimates on SUHI was -1.01 (effect on SUHI of increasing simultaneously every socioeconomic variable by one quantile). Our study highlighted that populations with low SES are more likely to be exposed to higher levels of SUHI compared to those who have a higher SES and illustrates the importance to consider SES inequalities when designing urban adaptation strategies aiming at reducing exposure to SUHI.

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