Dataset Information

Strong contributions of local background climate to the cooling effect of urban green vegetation.

ABSTRACT: Utilization of urban green vegetation (UGV) has been recognized as a promising option to mitigate urban heat island (UHI) effect. While we still lack understanding of the contributions of local background climate to the cooling effect of UGV. Here we proposed and employed a cooling effect framework and selected eight typical cities located in Temperate Monsoon Climate (TMC) and Mediterranean Climate (MC) demonstrate that local climate condition largely affects the cooling effect of UGV. Specifically, we found increasing (artificial) rainfall and irrigation contribute to improving the cooling intensity of grassland in both climates, particularly in the hot-dry environment. The cities with high relative humidity would restrict the cooling effect of UGV. Increasing wind speed would significantly enhance the tree-covered while weakening the grass-covered UGVs' cooling effect in MC cities. We also identified that, in order to achieve the most effective cooling with the smallest sized tree-covered UGV, the area of trees in both climate zones' cities should generally be planned around 0.5?ha. The method and results enhance understanding of the cooling effect of UGVs on larger (climate) scales and provide important insights for UGV planning and management.

SUBMITTER: Yu Z

PROVIDER: S-EPMC5931616 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Strong contributions of local background climate to the cooling effect of urban green vegetation.

Yu Zhaowu Z Xu Shaobin S Zhang Yuhan Y Jørgensen Gertrud G Vejre Henrik H

Scientific reports 20180501 1

Utilization of urban green vegetation (UGV) has been recognized as a promising option to mitigate urban heat island (UHI) effect. While we still lack understanding of the contributions of local background climate to the cooling effect of UGV. Here we proposed and employed a cooling effect framework and selected eight typical cities located in Temperate Monsoon Climate (TMC) and Mediterranean Climate (MC) demonstrate that local climate condition largely affects the cooling effect of UGV. Specific ...[more]

PMID: 29717184

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Project description:BackgroundVegetation dynamics is defined as a significant indictor in regulating terrestrial carbon balance and climate change, and this issue is important for the evaluation of climate change. Though much work has been done concerning the correlations among vegetation dynamics, precipitation and temperature, the related questions about relationships between vegetation dynamics and other climatic factors (e.g., specific humidity, net radiation, soil moisture) have not been thoroughly considered. Understanding these questions is of primary importance in developing policies to address climate change.MethodsIn this study, the least squares regression analysis method was used to simulate the trend of vegetation dynamics based on the normalized difference vegetation index (NDVI) from 1981 to 2018. A partial correlation analysis method was used to explore the relationship between vegetation dynamics and climate change; and further,the revised greyscale model was applied to predict the future growth trend of natural vegetation.ResultsThe Mann-Kendall test results showed that th e air temperature rose sharply in 1997 and had been in a state of high fluctuations since then. Strong changes in hydrothermal conditions had major impact on vegetation dynamics in the area. Specifically, the NDVI value of natural vegetation showed an increasing trend from 1981 to 2018, and the same changes occurred in the precipitation. From 1981 to 1997, the values of natural vegetation increased at a rate of 0.0016 per year. From 1999 to 2009, the NDVI value decreased by an average rate of 0.0025 per year. From 2010 to 2018, the values began an increasing trend and reached a peak in 2017, with an average annual rate of 0.0033. The high vegetation dynamics areas were mainly concentrated in the north and south slopes of the Tianshan Mountains, the Ili River Valley and the Altay area. The greyscale prediction results showed that the annual average NDVI values of natural vegetation may present a fluctuating increasing trend. The NDVI value in 2030 is 0.0196 higher than that in 2018, with an increase of 6.18%.ConclusionsOur results indicate that: (i) the variations of climatic factors have caused a huge change in the hydrothermal conditions in Xinjiang; (ii) the vegetation dynamics in Xinjiang showed obvious volatility, and then in the end stage of the study were higher than the initial stage the vegetation dynamics in Xinjiang showed a staged increasing trend; (iii) the vegetation dynamics were affected by many factors,of which precipitation was the main reason; (iv) in the next decade, the vegetation dynamics in Xinjiang will show an increasing trend.

Project description:Urban populations are highly vulnerable to the adverse effects of heat, with heat-related mortality showing intra-urban variations that are likely due to differences in urban characteristics and socioeconomic status.We investigated the influence of urban green and urban blue, that is, urban vegetation and water bodies, on heat-related excess mortality in the elderly > 65 years old in Lisbon, Portugal, between 1998 and 2008.We used remotely sensed data and geographic information to determine the amount of urban vegetation and the distance to bodies of water (the Atlantic Ocean and the Tagus Estuary). Poisson generalized additive models were fitted, allowing for the interaction between equivalent temperature [universal thermal climate index (UTCI)] and quartiles of urban greenness [classified using the Normalized Difference Vegetation Index (NDVI)] and proximity to water (? 4 km vs. > 4 km), while adjusting for potential confounders.The association between mortality and a 1°C increase in UTCI above the 99th percentile (24.8°C) was stronger for areas in the lowest NDVI quartile (14.7% higher; 95% CI: 1.9, 17.5%) than for areas in the highest quartile (3.0%; 95% CI: 2.0, 4.0%). In areas > 4 km from water, a 1°C increase in UTCI above the 99th percentile was associated with a 7.1% increase in mortality (95% CI: 6.2, 8.1%), whereas in areas ? 4 km from water, the estimated increase in mortality was only 2.1% (95% CI: 1.2, 3.0%).Urban green and blue appeared to have a mitigating effect on heat-related mortality in the elderly population in Lisbon. Increasing the amount of vegetation may be a good strategy to counteract the adverse effects of heat in urban areas. Our findings also suggest potential benefits of urban blue that may be present several kilometers from a body of water.Burkart K, Meier F, Schneider A, Breitner S, Canário P, Alcoforado MJ, Scherer D, Endlicher W. 2016. Modification of heat-related mortality in an elderly urban population by vegetation (urban green) and proximity to water (urban blue): evidence from Lisbon, Portugal. Environ Health Perspect 124:927-934;?http://dx.doi.org/10.1289/ehp.1409529.

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Dataset Information

Strong contributions of local background climate to the cooling effect of urban green vegetation.

Publications

Strong contributions of local background climate to the cooling effect of urban green vegetation.

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