Understanding temperature related health risk in context of urban land use changes

Avashia, Vidhee; Garg, Amit; Dholakia, Hem H.

doi:10.1016/j.landurbplan.2021.104107

Cited by 28 publications

(9 citation statements)

References 49 publications

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“…As the core area of the agricultural economy on Yunnan, the significant decrease of DTR is mainly caused by the significant rise of temperature at night. The rise of night‐time temperature can be explained by the combined effects of increasing concentration of greenhouse gas, increasing aerosols that can absorb nocturnal radiation, population growth, urbanization, and atmospheric circulation on Yunnan (Avashia et al ., 2021; Chen and Dong, 2021; Elhacham and Alpert, 2021; Sun et al ., 2021). The 10‐year mean value of the warm extreme temperature indices continued to increase after the 1980s, and the 10‐year mean value of the extreme cold temperature indices continued to decrease after the 1980s.…”

Section: Discussionmentioning

confidence: 99%

Elevation gradient dependence of extreme climate indices on Yunnan Plateau, China

Yan

2022

Intl Journal of Climatology

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The acceleration of global warming leads to frequent extreme weather events. The sensitivity of high-elevation regions to global warming makes their extremes more prominent. Based on the software Rclimdex1.0, 15 extreme climate indices from 120 meteorological stations in Yunnan from 1960 to 2019 were calculated. Trend analysis, correlation analysis, and cross-correlation analysis were used to investigate the spatiotemporal variation characteristics of these extreme climate indices. The results showed that, except CDD, other extreme precipitation indices were negatively correlated with the increase of elevation. The extreme warming indices (SU25, WSDI, TX90p, TN90p) showed an increasing trend with the increase of elevation, while the extreme cold indices (CSDI, FD0, TX10p, TN10p) showed a decreasing trend with the increase of elevation. The rate of nocturnal warming at high elevations is higher than that at low elevations. The change rate of extreme warmth indices (SU25, WSDI, TX90p, TN90p) and extreme cold indices (FD0, CSDI, TX10p, TN10p) was negatively correlated (p < .05) in all elevation ranges, and this correlation was most significant in the elevation range of 1,500-2,000 m. These results highlight that the rate of drying and warming at higher elevations is higher than that at lower elevations, providing case support and scientific basis for sensitivity of high-altitude regions to extreme climate.

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Section: Discussionmentioning

confidence: 99%

Elevation gradient dependence of extreme climate indices on Yunnan Plateau, China

Yan

2022

Intl Journal of Climatology

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“…Yu et al monitored urban sprawl at a regional scale by using Landsat images [12]. Additionally, many research studies were committed to investigating the consequent effects of LULC change in the context of urbanization, including environmental deterioration [13], climate change [14], urban heat islands [15], food security [16] and so on.…”

Section: Introductionmentioning

confidence: 99%

Understanding Spatio-Temporal Patterns of Land Use/Land Cover Change under Urbanization in Wuhan, China, 2000–2019

et al. 2021

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Exploring land use structure and dynamics is critical for urban planning and management. This study attempts to understand the Wuhan development mode since the beginning of the 21st century by profoundly investigating the spatio-temporal patterns of land use/land cover (LULC) change under urbanization in Wuhan, China, from 2000 to 2019, based on continuous time series mapping using Landsat observations with a support vector machine. The results indicated rapid urbanization, with large LULC changes triggered. The built-up area increased by 982.66 km2 (228%) at the expense of a reduction of 717.14 km2 (12%) for cropland, which threatens food security to some degree. In addition, the natural habitat shrank to some extent, with reductions of 182.52 km2, 23.92 km2 and 64.95 km2 for water, forest and grassland, respectively. Generally, Wuhan experienced a typical urbanization course that first sped up, then slowed down and then accelerated again, with an obvious internal imbalance between the 13 administrative districts. Hanyang, Hongshan and Dongxihu specifically presented more significant land dynamicity, with Hanyang being the active center. Over the past 19 years, Wuhan mainly developed toward the east and south, with the urban gravity center transferred from the northwest to the southeast of Jiang’an district. Lastly, based on the predicted land allocation of Wuhan in 2029 by the patch-generating land use simulation (PLUS) model, the future landscape dynamic pattern was further explored, and the result shows a rise in the northern suburbs, which provides meaningful guidance for urban planners and managers to promote urban sustainability.

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“…Xu et al (2013) Percentage of adults age 20+ diagnosed with diabetes Semenza et al (1999), Semenza et al (1996), Schwartz (2005), and Knowlton et al (2009) Percentage of land covered in high density development Uejio et al (2011), Jones et al (1982), Harlan et al (2006), Clarke (1972), and Buechley et al (1972) Percentage of land covered in non-green space Gronlund et al (2015), Zanobetti et al (2013), Kilbourne et al (1982), Y. Xu et al (2013), Harlan et al (2006), and Harlan et al (2013) Average summertime enhanced vegetation index (EVI) score Gronlund et al (2015), Harlan et al (2006), and Harlan et al (2013) Average summertime 2m air temperature anomaly (°F) Harlan et al (2006), Johnson and Wilson (2009), Avashia et al (2021), Basu et al (2008), Medina-Ramón and Schwartz (2007), and Zanobetti and Schwartz (2008) a Supporting literature identifies research studies that support a relationship between the given variables and adverse heat-related health outcomes.…”

Section: Heat Vulnerability Index (Hvi) Datamentioning

confidence: 99%

Residential and Race/Ethnicity Disparities in Heat Vulnerability in the United States

Manware

Dubrow²,

Carrión³

et al. 2022

GeoHealth

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Adverse health outcomes caused by extreme heat represent the most direct human health threat associated with the warming of the Earth's climate. Socioeconomic, demographic, health, land cover, and temperature determinants contribute to heat vulnerability; however, nationwide patterns of residential and race/ethnicity disparities in heat vulnerability in the United States are poorly understood. This study aimed to develop a Heat Vulnerability Index (HVI) for the United States; to assess differences in heat vulnerability across geographies that have experienced historical and/or contemporary forms of marginalization; and to quantify HVI by race/ethnicity. Principal component analysis was used to calculate census tract level HVI scores based on the 2019 population characteristics of the United States. Differences in HVI scores were analyzed across the Home Owners' Loan Corporation (HOLC) “redlining” grades, the Climate and Economic Justice Screening Tool (CEJST) disadvantaged versus non‐disadvantaged communities, and race/ethnicity groups. HVI scores were calculated for 55,267 U.S. census tracts. Mean HVI scores were 17.56, 18.61, 19.45, and 19.93 for HOLC grades “A”–“D,” respectively. CEJST‐defined disadvantaged census tracts had a significantly higher mean HVI score (19.13) than non‐disadvantaged tracts (16.68). The non‐Hispanic African American or Black race/ethnicity group had the highest HVI score (18.51), followed by Hispanic or Latino (18.19). Historically redlined and contemporary CEJST disadvantaged census tracts and communities of color were found to be associated with increased vulnerability to heat. These findings can help promote equitable climate change adaptation policies by informing policymakers about the national distribution of place‐ and race/ethnicity‐based disparities in heat vulnerability.

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Understanding temperature related health risk in context of urban land use changes

Cited by 28 publications

References 49 publications

Elevation gradient dependence of extreme climate indices on Yunnan Plateau, China

Elevation gradient dependence of extreme climate indices on Yunnan Plateau, China

Understanding Spatio-Temporal Patterns of Land Use/Land Cover Change under Urbanization in Wuhan, China, 2000–2019

Residential and Race/Ethnicity Disparities in Heat Vulnerability in the United States

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