Effectiveness of Different Urban Heat Island Mitigation Methods and Their Regional Impacts

Abstract

Cool roofs and green roofs are two popular methods to mitigate the urban heat island and improve urban climates. The effectiveness of different urban heat island mitigation strategies in the summer of 2013 in the Yangtze River delta, China, is investigated using the Weather Research and Forecasting (WRF) Model coupled with a physically based single-layer urban canopy model. The modifications to the roof surface changed the urban surface radiation balance and then modified the local surface energy budget. Both cool roofs and green roofs led to a lower surface skin temperature and near-surface air temperature. Increasing the roof albedo to 0.5 caused a similar effectiveness as covering 25% of urban roofs with vegetation; increasing the roof albedo to 0.7 caused a similar near-surface air temperature decrease as 50% green roof coverage. The near-surface relative humidity increased in both cool roof and green roof experiments because of the combination of the impacts of increases in specific humidity and decreases in air temperature. The regional impacts of cool roofs and green roofs were evaluated using a regional effect index. A regional impact was found for near-surface air temperature and specific/relative humidity when the percentage of roofs covered with high-albedo materials or green roofs reached a higher fraction (greater than 50%). The changes in the vertical profiles of temperature cause a more stable atmospheric boundary layer over the urban area; at the same time, the crossover phenomena occurred above the boundary layer due to the decrease in vertical wind speed.

Assessing the Impact of Urban Hydrological Processes on the Summertime Urban Climate in Nanjing Using the WRF Model

“…Moreover, the influence height and magnitude by ALH are slightly smaller than by GRO and OASIS. The thin warmer layer above the PBL is very weak in the early morning and becomes strong (~0.3 K) in the afternoon; this outcome is similar to results from previous studies of green roof impacts on UHI (Sharma et al, 2016; Sun et al, 2016; Zhang et al, 2017). The crossover effect of the specific humidity is also observed during daytime (not shown) but is relatively weak, with only a maximum of approximately 0.1-0.2 g kg -1 in the afternoon.…”

“…The overall model performance is quantified by five statistical measures: the correlation coefficient (R), mean error (ME), root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). For any given variable with (n) pairs of observed (O) and modeled (M) values, these statistics are defined as follows: Journal of Geophysical Research: Atmospheres previous WRF simulations of summer climatology over the Yangtze River Delta region Chen & Zhang, 2018;Zhang et al, 2017). The statistics for turbulent fluxes (H, LE, and R n ) are similar to WRF-SLUCM simulations over Beijing in summer (Miao & Chen, 2014) but are slightly worse than the annual results .…”

A Novel SUHI Referenced Estimation Method for Multicenters Urban Agglomeration using DMSP/OLS Nighttime Light Data

“…Previous studies used RLST at the suburban areas to reveal SUHII of a single-city research across global [3], national [31], and city scales [54]- [57]. Forest reference was proposed and applied to the urban agglomeration in the Yangtze River Delta due to the relatively stable in surface coverage and temperature [20].…”

Effectiveness of Urban Hydrological Processes in Mitigating Urban Heat Island and Human Thermal Stress During a Heat Wave Event in Nanjing, China

“…A number of mitigation strategies have been proposed to reduce the UHI effect by modifying the land surface, such as the use of green and cool roofs/walls (Imran et al, 2018;Ma et al, 2018;Sharma et al, 2016;Sun et al, 2016;Yang et al, 2016a;Zhang et al, 2017), deploying rooftop solar photovoltaic panels (Ma et al, 2017;Salamanca et al, 2016), and increasing urban vegetation fractions (Jacobs et al, 2018;X. X. Li & Norford, 2016).…”