Evaluation of the Street Canyon Level Air Pollution Distribution Pattern in a Typical City Block in Baoding, China

2021 ◽  
Author(s):  
Jingcheng Zhou ◽  
Songlin Xiang ◽  
Yizhou Zhang ◽  
Yuqing Wang ◽  
Wendong Ge ◽  
...  
Keyword(s):  
Air Pollution ◽  
Distribution Pattern ◽  
Street Canyon ◽  
City Block ◽  
Pollution Distribution

scholarly journals A numerical simulation of vehicle pollution distribution in a street canyon

2021 ◽  
Author(s):  
Александр Старченко ◽  
Евгений Данилкин ◽  
Дмитрий Лещинский
Keyword(s):  
Numerical Simulation ◽  
Street Canyon ◽  
Vehicle Pollution ◽  
Pollution Distribution

Comprehensive evaluation of an advanced street canyon air pollution model

2020 ◽  
Author(s):  
Christina Hood ◽  
Jenny Stocker ◽  
Martin Seaton ◽  
Kate Johnson ◽  
James O’Neill ◽  
...  
Keyword(s):  
Air Pollution ◽  
Street Canyon ◽  
Comprehensive Evaluation ◽  
Air Pollution Model

From Google Maps to Air Quality: a big data approach to modelling real-time NO2 concentrations in an urban street canyon from road traffic data

2020 ◽  
Author(s):  
Helen Pearce ◽  
Zhaoya Gong ◽  
Xiaoming Cai ◽  
William Bloss
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Real Time ◽  
Street Canyon ◽  
Box Model ◽  
Traffic Data ◽  
Flow Data ◽  
Pollutant Concentrations ◽  
Background Air ◽  
Model Chain

<p>In most European cities, the key air pollutants driving adverse health outcomes are nitrogen dioxide (NO2) and fine particulate matter (PM2.5), with 64% of new paediatric asthma cases in urban centres attributed to elevated NO2 levels (Achakulwisut et al., 2019). In the complex landscape of a city, a synthesis of techniques to quantify air pollution is required to account for variations in traffic, meteorology, and urban geometry.</p><p>Here, we present the results from a comparison study between measured air pollutant data collected at Marylebone Road, London and the output from a three-stage modelling chain. This site was chosen due to the availability of road-side air quality data collected within a street canyon (aspect ratio approximately equal to 1) and daily traffic flow in excess of 70,000 motor vehicles. The modelling chain consists of: 1) real-time traffic information of vehicle journey times, 2) speed-related emission calculations, and 3) air quality box-model to simulate the interaction of pollutants within the environment.</p><p>While the transport sector accounts for much of the outdoor air pollution in UK cities, a limiting factor of current techniques is that traffic is approximated at coarse temporal and spatial resolutions. In this study, we present a novel technique that helps to ‘fill in’ the gaps in our traffic data by harnessing the power of real-time queries to Google Maps to obtain travel times between fixed locations, enabling the derivation of average vehicle speeds. This dataset can then be used to determine more accurate emission factors for NOx. Total emissions are then calculated with the aid of traffic flow data and vehicle fleet characteristics. The air quality box model simulates photochemical reactions that form NO2, the exchange of pollutants with the background air aloft, and advection of pollutants along the street.</p><p>Hourly travel times and total vehicle flow data were collected between July and October 2019, totalling 905 observations and calculated emissions values. Meteorological data from Heathrow airport and background air quality from the Kensington AURN site were used as supporting inputs to the air quality box model. Each observation was treated as a starting point of the box model, and the simulation was run for 1 hour, with mixing due to advection occurring every 60 seconds. Results are promising; when using the full model chain modelled and measured NO2 concentrations are significantly correlated (r = 0.467, p < 0.000). In comparison, when a constant speed of 30 mph is used to calculate total emissions, therefore excluding the impact of congestion, the strength of the correlation decreases (r = 0.362, p < 0.000) and the model underestimates pollutant concentrations.</p><p>The applications of this model chain are vast. For any street that is covered by a suitable mapping platform and has available data on vehicle numbers, it would be possible to provide a real-time estimation of pollutant concentrations at a high temporal resolution. This could be utilised in several ways, such as: assessing policy implementation, and providing a high resolution input for air quality modelling and health exposure studies.</p>

Finding the right tree for future urban planning – Meso- to microscale model coupling in urban areas

2020 ◽  
Author(s):  
Joachim Fallmann ◽  
Helge Simon ◽  
Tim Sinsel ◽  
Marc Barra ◽  
Holger Tost
Keyword(s):  
Air Pollution ◽  
Urban Planning ◽  
Urban Area ◽  
Ozone Concentration ◽  
Tree Species ◽  
Urban Areas ◽  
Street Canyon ◽  
Model Systems ◽  
Traffic Load ◽  
Microscale Model

<p><span>It has been long understood that green infrastructure helps to mitigate urban heat island formation and therefore should be a key strategy in future urban planning practices. Due to its high level of heat resilience, the sycamore tree (Platanus) dominates the appearance of urban landscapes in central Europe. Under extreme climate conditions however, these species tend to emit high levels of biogenic volatile organic compounds (BVOCs) which in turn can act as precursors for tropospheric ozone, especially in highly NOx polluted environments such as urban areas. </span></p><p><span>Assessing the ozone air quality of a large urban area in Germany we use the state-of-the art regional chemical transport model MECO(n), with chemistry coming from the Modular Earth Submodel System (MESSy) and meteorology being calculated by COSMO. Including the latest version of TERRA_URB, the model is configured for the Rhine-Main urban area. In a second step, we implement parts of the regional atmospheric chemistry mechanism in the ENVI-met model framework in order to investigate the impact of isoprene emissions on ozone concentration at street level for the urban area of Mainz, Germany. </span></p><p><span>Whereas mesoscale model results only show moderate mean ozone pollution over the model area, at micro-scale level on selected hot spots we find a clear relationship between urban layout, proximity to NOx emitters, tree-species-dependent isoprene emission capacity and increase in ozone concentration. The ENVI-met study reveals, that next to tree species, its location is a key factor for its micro-climatic UHI and air pollution mitigation potential. We could show, that isoprene related ozone concentration is highly sensitive to leaf temperature, photosynthetic active radiation as well as to the proximity to NO2 pollution sources. In a street canyon with high traffic load we find significant correlations between diurnal boundary layer dynamics, morning and evening rush hour and ambient ozone levels. For a hot summer day in particular, we simulate ozone concentrations rising up to 500% within a weakly ventilated street canyon with a high amount of strong isoprene emitters being present.</span></p><p><span>We summarize that combining findings from meso- and microscale model systems can be an important asset for science tools for cities in the framework of climate change adaption and mitigation </span><span>and air pollution abatement</span><span> strategies.</span></p>

NO2 Vertical Gradient Monitoring Along a Street Canyon by LP-DOAS in the Framework of the Escape Air Pollution and Health Study

Epidemiology ◽  
2011 ◽  
Vol 22 ◽  
pp. S216 ◽  
Author(s):  
Ming-Yi Tsai ◽  
Sebastian Landwehr ◽  
Denis Pöhler ◽  
Alex Ineichen ◽  
Gerard Hoek ◽  
...  
Keyword(s):  
Air Pollution ◽  
Street Canyon ◽  
Vertical Gradient ◽  
Health Study
Sign in / Sign up

Export Citation Format

Share Document