Numerical Simulation of Secondary Impacts of Designed Urban Thermal Island Control on Summer Air Quality in Tehran Metropolitan Area

The Urban Heat Island (UHI) describes the temperature difference between urban and rural temperatures. Finding urban heat island mitigation strategies is of great importance, given expected influences on human health and air quality. This study presents numerical simulations over a summer period to investigate the impact of urban heat island control measures on Tehran urban air quality. The WRF-Chem Chemical Mesoscale Model is used to investigate the effect of increasing urban vegetation and highly reflective surfaces on the concentration of primary pollutants (CO, NO) as well as secondary pollutants (O3) in urban canyons. In order to account for the heterogeneity of urban areas, a multi-layered urban canopy model is coupled with WRF-Chem. Using this canopy model at its broad range requires introducing several urban user classes in WRF-Chem. Tehran metropolis is considered to simulate designed experiments in the summer of 2016. The selected reduction measures in the simulations are able to reduce the urban temperature by about 1-3 degrees Celsius and average daily ozone concentration by 5 to 10 percent. The modeling results also presented secondary negative effects on urban air quality, which is strongly related to the reduction of vertical mixing in the urban boundary layer. The simulation results show a 1 to 20% increase in the primary pollutants (NO and CO). Despite the daily average decrease in ozone concentration, highly reflective surfaces due to severe short-wavelength radiation that accelerates photochemical reactions can lead to an increase in the peak ozone concentration by up to 9% at noon hours.
Extended Abstract
1-Introduction
Significant emission of heat from human activities and overheating of synthetic surfaces over natural surfaces leads to urban heat island formation. The average annual temperature in central areas of a large city is at least about 1-3 ° C above the surrounding area. On calm nights, city centers can experience temperatures as high as 12 ° C. In addition to the health problems caused by rising temperatures, the effect of increasing rates of photochemical reactions, which in turn worsens indoor air quality, is also of particular importance (Oke, 1982). Specific measures such as the use of green roofs or facades and materials with high reflectivity are able to reduce the intensity of the urban heat island. The purpose of this study is to use the WRF-Chem model, coupled with urban parameterization schemes, to investigate the dynamical and chemical processes when applying conventional reduction strategies. The study area is the urban area of ​​Tehran as one of the most polluted cities in Iran.
2-Materials and Methods    
To show the three-dimensional structure of urban areas, the urban parameterization plan was used along with the Noha land surface model. In order to show the heterogeneity of urban land levels and to use urban modeling with its full expansion, the main urban class (1) in the WRF / Chem model was divided into 3 subclasses (31-33). The range of the model for the internal nest was 103 by 79 network cells with a horizontal resolution of 1.33 km. In order to identify morphological features for each class of Tehran urban area, the characteristics of roads and buildings (building height, street width, albedo level, vegetation, etc.) as well as thermodynamic properties and roughness characteristics within the model were updated. The simulation period was July 17 to July 23, 2016, a period of thermal stress in Tehran that could be considered as a special period for future weather conditions in Tehran. The basic mode (control) was simulated along with urban planning strategies such as increasing urban vegetation (park), increasing building surface whiteness (albedo), and changing building density (density) for further study.
3-Results and Discussion     
During the study of simulation sensitivity, different meteorological and pollution parameters of the simulated air in the default mode were compared with the average observations of the three urban metering stations. The correlation between simulations and observations, except for CO, was greater than 0.5, and the model performed well in reproducing various parameters. Comparing the results of simulations with observational data, it can be stated that the model generally simulates the hourly changes of meteorological variables well, but more or less estimates the concentration of air pollutants during the simulation period (Grossman and Sobert and Clark, 2013). One reason for the comparison method is that simulation outputs are extracted at the beginning of each hour, while measurements are reported as average or average daily (Akbari et al., 2001). To investigate the effect of different reduction strategies, the effect of each strategy on the concentration of different pollutants was simulated. On average, the air temperature decreases by 3.37 degrees Celsius and 1.7 degrees Celsius, respectively, for the albedo and park scenario. In relation to the primary pollutants CO, SO2 or NOx, the positive effect of reduced temperature is reversed. This was particularly the case for a scenario in which the whiteness of the roof and walls of buildings increased (the relative increase in primary contaminants by up to 20%). An increase in ozone concentration of up to 9% for the Albido scenario was found around 1300 hours, which could be due to a further increase in ceiling and wall surface whitening from 0.2 to 0.7 (Takabayashi and Moriyama, 2007), which is 67% higher than the increase in use. It was done by two other studies (Taha, 2008 and 1997-A) and on the other hand, the maximum decrease in air temperature in Tehran urban area was 2.17⁰ C, which is about 0.83 33 2.83 33 C lower than the decrease. The temperature was reported by Taha (2008).
4-Conclusion
Simulation experiments were designed and studied to evaluate urban thermal island control strategies that could have an adverse effect on urban air quality. The selected measures showed positive and negative effects on the concentration and dispersion of pollutants. Albido's strategies and urban vegetation are able to improve air quality, followed by a daily decrease in the average concentration of ozone. Also, lowering the temperature has a significant effect on the dynamic structure of the urban boundary layer. Reduction of turbulent kinetic energy (TKE) due to lower temperatures leads to a decrease in turbulence mixing rate and a decrease in the height of the mixing layer, which leads to higher surface concentrations of primary contaminants.
This case study provides simulation for a city in certain climatic conditions, because for cities with different sizes, locations, population densities, emission conditions, or different meteorological conditions, similar actions may have different effects on air quality. In urban planning, the social effects of parks on increasing the well-being of citizens should also be considered