Modeling Impacts of Urbanization and Urban Heat Island Mitigation on Boundary Layer Meteorology and Air Quality in Beijing Under Different Weather Conditions

2018 ◽  
Vol 123 (8) ◽  
pp. 4323-4344 ◽  
Author(s):  
Lei Chen ◽  
Meigen Zhang ◽  
Jia Zhu ◽  
Yongwei Wang ◽  
Andrei Skorokhod
Keyword(s):  
Boundary Layer ◽  
Air Quality ◽  
Urban Heat Island ◽  
Weather Conditions ◽  
Heat Island ◽  
Boundary Layer Meteorology ◽  
Urban Heat

The impact of COVID-19 lockdowns on surface urban heat island changes and air-quality improvements across 21 major cities in the Middle East

2021 ◽  
pp. 117802
Author(s):  
Ahmed M. El Kenawy ◽  
Juan I. Lopez-Moreno ◽  
Matthew F. McCabe ◽  
Fernando Domínguez-Castro ◽  
Dhais Peña-Angulo ◽  
...  
Keyword(s):  
Air Quality ◽  
Middle East ◽  
Urban Heat Island ◽  
Heat Island ◽  
Quality Improvements ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
The Impact

Trade-off between urban heat island mitigation and air quality in urban valleys

Urban Climate ◽  
2020 ◽  
Vol 31 ◽  
pp. 100542 ◽  
Author(s):  
Juan J. Henao ◽  
Angela M. Rendón ◽  
Juan F. Salazar
Keyword(s):  
Air Quality ◽  
Urban Heat Island ◽  
Heat Island ◽  
Trade Off ◽  
Urban Heat

An Observational Case Study of Synergies between an Intense Heat Wave and the Urban Heat Island in Beijing

2020 ◽  
Vol 59 (4) ◽  
pp. 605-620 ◽  
Author(s):  
Ning An ◽  
Jingjing Dou ◽  
Jorge E. González-Cruz ◽  
Robert D. Bornstein ◽  
Shiguang Miao ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Urban Heat Island ◽  
Heat Wave ◽  
Apparent Temperature ◽  
Heat Index ◽  
Heat Island ◽  
Canopy Layer ◽  
Urban Heat ◽  
Peak Pattern ◽  
Intense Heat

AbstractThe focus of this study is an intense heat episode that occurred on 9–13 July 2017 in Beijing, China, that resulted in severe impacts on natural and human variables, including record-setting daily electricity consumption levels. This event was observed and analyzed with a suite of local and mesoscale instruments, including a high-density automated weather station network, soil moisture sensors, and ground-based vertical instruments (e.g., a wind profiler, a ceilometer, and three radiometers) situated in and around the city, as well as electric power consumption data and analysis data from the U.S. National Centers for Environmental Prediction. The results show that the heat wave originated from dry adiabatic warming induced by the dynamic downslope and synoptic subsidence. The conditions were aggravated by the increased air humidity during subsequent days, which resulted in historically high records of the heat index (i.e., an index representing the apparent temperature that incorporates both air temperature and moisture). The increased thermal energy and decreased boundary layer height resulted in a highly energized urban boundary layer. The differences between urban and rural thermal conditions throughout almost the entire boundary layer were enhanced during the heat wave, and the canopy-layer urban heat island intensity (UHII) reached up to 8°C at a central urban station at 2300 local standard time 10 July. A double-peak pattern in the diurnal cycle of UHIIs occurred during the heat wave and differed from the single-peak pattern of the decadal average UHII cycles. Different spatial distributions of UHII values occurred during the day and night.

scholarly journals Secondary effects of urban heat island mitigation measures on air quality

2016 ◽  
Vol 125 ◽  
pp. 199-211 ◽  
Author(s):  
Joachim Fallmann ◽  
Renate Forkel ◽  
Stefan Emeis
Keyword(s):  
Air Quality ◽  
Urban Heat Island ◽  
Mitigation Measures ◽  
Heat Island ◽  
Secondary Effects ◽  
Urban Heat

scholarly journals Earth Observations Informing Cities’ Operations and Planning

Eos ◽  
2020 ◽  
Vol 101 ◽  
Author(s):  
Margaret Hurwitz ◽  
Christian Braneon ◽  
Dalia Kirschbaum ◽  
Felipe Mandarino ◽  
Raed Mansour
Keyword(s):  
Air Quality ◽  
Urban Heat Island ◽  
Rio De Janeiro ◽  
Heat Island ◽  
Earth Observations ◽  
Urban Heat

Rio de Janeiro, Brazil, and Chicago, Ill., are using NASA Earth observations to map, monitor, and forecast water and air quality, urban heat island effects, landslide risks, and more.

scholarly journals Opposite Effects of Aerosols on Daytime Urban Heat Island Intensity between Summer and Winter

2020 ◽  
Author(s):  
Wenchao Han ◽  
Zhanqing Li ◽  
Fang Wu ◽  
Yuwei Zhang ◽  
Jianping Guo ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Air Pollution ◽  
Urban Heat Island ◽  
Planetary Boundary Layer ◽  
Urban Areas ◽  
Urban Heat Island Intensity ◽  
Heat Island ◽  
Different Seasons ◽  
Urban Heat ◽  
The Impact

Abstract. The urban heat island intensity (UHII) is the temperature difference between urban areas and their rural surroundings. It is commonly attributed to changes in the underlying surface structure caused by urbanization. Air pollution caused by aerosol particles can affect the UHII by changing the surface energy balance and atmospheric thermodynamic structure. By analyzing satellite data and ground-based observations collected from 2001 to 2010 at 35 cities in China and using the WRF-Chem model, we found that aerosols have very different effects on daytime UHII in different seasons: reducing the UHII in summer, but increasing the UHII in winter. The seasonal contrast in the spatial distribution of aerosols between the urban centers and the suburbs lead to a spatial discrepancy in aerosol radiative effect (SD-ARE). Additionally, different stability of the planetary boundary layer induced by aerosol is closely associated with a dynamic effect (DE) on the UHII. SD-ARE reduces the amount of radiation reaching the ground and changes the vertical temperature gradient, whereas DE increases the stability of the planetary boundary layer and weakens heat release and exchange between the surface and the PBL. Both effects exist under polluted conditions, but their relative roles are opposite between the two seasons. It is the joint effects of the SD-ARE and the DE that drive the UHII to behave differently in different seasons, which is confirmed by model simulations. In summer, the UHII is mainly affected by the SD-ARE, and the DE is weak, and the opposite is the case in winter. This finding sheds a new light on the impact of the interaction between urbanization-induced surface changes and air pollution on urban climate.

scholarly journals Street-scale air quality modelling for Beijing during a winter 2016 measurement campaign

2020 ◽  
Vol 20 (5) ◽  
pp. 2755-2780 ◽  
Author(s):  
Michael Biggart ◽  
Jenny Stocker ◽  
Ruth M. Doherty ◽  
Oliver Wild ◽  
Michael Hollaway ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Heat Island ◽  
Monitoring Network ◽  
Ambient Air ◽  
Traffic Emissions ◽  
Heat Island ◽  
Emissions Inventory ◽  
Measurement Campaign ◽  
Urban Heat

Abstract. We examine the street-scale variation of NOx, NO2, O3 and PM2.5 concentrations in Beijing during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) winter measurement campaign in November–December 2016. Simulations are performed using the urban air pollution dispersion and chemistry model ADMS-Urban and an explicit network of road source emissions. Two versions of the gridded Multi-resolution Emission Inventory for China (MEIC v1.3) are used: the standard MEIC v1.3 emissions and an optimised version, both at 3 km resolution. We construct a new traffic emissions inventory by apportioning the transport sector onto a detailed spatial road map. Agreement between mean simulated and measured pollutant concentrations from Beijing's air quality monitoring network and the Institute of Atmospheric Physics (IAP) field site is improved when using the optimised emissions inventory. The inclusion of fast NOx–O3 chemistry and explicit traffic emissions enables the sharp concentration gradients adjacent to major roads to be resolved with the model. However, NO2 concentrations are overestimated close to roads, likely due to the assumption of uniform traffic activity across the study domain. Differences between measured and simulated diurnal NO2 cycles suggest that an additional evening NOx emission source, likely related to heavy-duty diesel trucks, is not fully accounted for in the emissions inventory. Overestimates in simulated early evening NO2 are reduced by delaying the formation of stable boundary layer conditions in the model to replicate Beijing's urban heat island. The simulated campaign period mean PM2.5 concentration range across the monitoring network (∼15 µg m−3) is much lower than the measured range (∼40 µg m−3). This is likely a consequence of insufficient PM2.5 emissions and spatial variability, neglect of explicit point sources, and assumption of a homogeneous background PM2.5 level. Sensitivity studies highlight that the use of explicit road source emissions, modified diurnal emission profiles, and inclusion of urban heat island effects permit closer agreement between simulated and measured NO2 concentrations. This work lays the foundations for future studies of human exposure to ambient air pollution across complex urban areas, with the APHH-China campaign measurements providing a valuable means of evaluating the impact of key processes on street-scale air quality.

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