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 ◽  
...  

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.

2019 ◽  
Author(s):  
Michael Biggart ◽  
Jenny Stocker ◽  
Ruth M. Doherty ◽  
Oliver Wild ◽  
Michael Hollaway ◽  
...  

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 μgm−3) is much lower than the measured range (~ 40 μgm−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.


2021 ◽  
pp. 117802
Author(s):  
Ahmed M. El Kenawy ◽  
Juan I. Lopez-Moreno ◽  
Matthew F. McCabe ◽  
Fernando Domínguez-Castro ◽  
Dhais Peña-Angulo ◽  
...  

Urban Climate ◽  
2020 ◽  
Vol 31 ◽  
pp. 100542 ◽  
Author(s):  
Juan J. Henao ◽  
Angela M. Rendón ◽  
Juan F. Salazar

2015 ◽  
Vol 22 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Hashem Akbari ◽  
Constantinos Cartalis ◽  
Denia Kolokotsa ◽  
Alberto Muscio ◽  
Anna Laura Pisello ◽  
...  

Increase of the ambient air temperature in cities caused by the urban heat island phenomenon has a seri- ous impact on the economic and social system of cities. to counterbalance the consequences of the increased urban temperatures important research has been carried out resulting in the development of efficient mitigation technologies. the present paper aims to present the state of the art in terms of local climate change and urban heat island mitigation techniques. In particular, developments in the field on highly reflective materials, cool and green roofs, cool pavements, urban green and of other mitigation technologies are presented in detail, while examples of implemented projects are given.


2016 ◽  
Vol 125 ◽  
pp. 199-211 ◽  
Author(s):  
Joachim Fallmann ◽  
Renate Forkel ◽  
Stefan Emeis

Author(s):  
D. Gerçek ◽  
İ. T. Güven ◽  
İ. Ç. Oktay

Along with urbanization, sealing of vegetated land and evaporation surfaces by impermeable materials, lead to changes in urban climate. This phenomenon is observed as temperatures several degrees higher in densely urbanized areas compared to the rural land at the urban fringe particularly at nights, so-called Urban Heat Island. Urban Heat Island (UHI) effect is related with urban form, pattern and building materials so far as it is associated with meteorological conditions, air pollution, excess heat from cooling. UHI effect has negative influences on human health, as well as other environmental problems such as higher energy demand, air pollution, and water shortage. <br><br> Urban Heat Island (UHI) effect has long been studied by observations of air temperature from thermometers. However, with the advent and proliferation of remote sensing technology, synoptic coverage and better representations of spatial variation of surface temperature became possible. This has opened new avenues for the observation capabilities and research of UHIs. <br><br> In this study, "UHI effect and its relation to factors that cause it" is explored for İzmit city which has been subject to excess urbanization and industrialization during the past decades. Spatial distribution and variation of UHI effect in İzmit is analysed using Landsat 8 and ASTER day & night images of 2015 summer. Surface temperature data derived from thermal bands of the images were analysed for UHI effect. Higher temperatures were classified into 4 grades of UHIs and mapped both for day and night. <br><br> Inadequate urban form, pattern, density, high buildings and paved surfaces at the expanse of soil ground and vegetation cover are the main factors that cause microclimates giving rise to spatial variations in temperatures across cities. These factors quantified as land surface/cover parameters for the study include vegetation index (NDVI), imperviousness (NDISI), albedo, solar insolation, Sky View Factor (SVF), building envelope, distance to sea, and traffic space density. These parameters that cause variation in intra-city temperatures were evaluated for their relationship with different grades of UHIs. Zonal statistics of UHI classes and variations in average value of parameters were interpreted. The outcomes that highlight local temperature peaks are proposed to the attention of the decision makers for mitigation of Urban Heat Island effect in the city at local and neighbourhood scale.


Eos ◽  
2020 ◽  
Vol 101 ◽  
Author(s):  
Margaret Hurwitz ◽  
Christian Braneon ◽  
Dalia Kirschbaum ◽  
Felipe Mandarino ◽  
Raed Mansour

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.


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