scholarly journals Introducing the Green Infrastructure for Roadside Air Quality (GI4RAQ) Platform: Estimating Site-Specific Changes in the Dispersion of Vehicular Pollution Close to Source

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 769
Author(s):  
Helen Pearce ◽  
James G. Levine ◽  
Xiaoming Cai ◽  
A. Rob MacKenzie
Keyword(s):  
Air Quality ◽  
Green Infrastructure ◽  
Street Canyon ◽  
Urban Air Pollution ◽  
Cost Benefit ◽  
Pollutant Dispersion ◽  
Vehicular Pollution ◽  
Site Specific ◽  
Pollutant Concentrations ◽  
Prototype Software

The benefits of ‘green infrastructure’ are multi-faceted and well-documented, but estimating those of individual street-scale planting schemes at planning can be challenging. This is crucial to avoid undervaluing proposed schemes in cost–benefit analyses, and ensure they are resilient to ‘value engineering’ between planning and implementation. Here, we introduce prototype software enabling urban practitioners to estimate the site-specific air quality impacts of roadside vegetation barriers: highly localised changes in pollutant concentrations due to changes in the dispersion of vehicular emissions close to source. We summarise the recent shift in understanding regarding the impacts of vegetation on urban air pollution towards changes in pollutant dispersion (cf. deposition) and describe our prototype software, offering rapid estimates thereof. First tests of the underlying model’s performance are promising, reproducing: annual mean NO2 and PM2.5 concentrations in a street canyon (Marylebone Road, London, UK) to within 10% and 25%, respectively; and changes in pollutant concentrations of the right order of magnitude behind roadside barriers in a wind tunnel simulation of a street canyon and a real open-road environment. However, the model underestimates the benefits of a barrier in a simulated street canyon under perpendicular wind conditions. The prototype software is a first step towards informing practitioners of the site-specific impacts of vegetation barriers, which should always be additional to (i.e., no substitute for) essential emission reductions. The code is open-source to engage further researchers in its continued development.

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>

A Comparative Study of Various Turbulence Models for Simulating Pollutant Dispersion within an Isolated Street Canyon

2011 ◽  
Vol 356-360 ◽  
pp. 766-770
Author(s):  
Yuan Dong Huang ◽  
Yue Jiao Peng ◽  
Jian Wei Jiang ◽  
Zhong Hua Zhou ◽  
Jing Gu
Keyword(s):  
Wind Tunnel ◽  
Street Canyon ◽  
Vector Fields ◽  
Turbulence Models ◽  
Pollutant Dispersion ◽  
Pollutant Concentration ◽  
Leeward Side ◽  
Perfect Agreement ◽  
Pollutant Concentrations ◽  
Wind Tunnel Data

CFD calculations are carried out using the standard, RNG and realizable κ-ε turbulence models to simulate the airflow and pollutant dispersion inside an isolated street canyon. The computed air velocity vector fields and pollutant concentration contours show that all the three studied κ-ε models produce a very similar clockwise vortex structure that carries the pollutants released from the line source on the street floor towards the leeward side of the canyon. The calculated non-dimensional pollutant concentration distributions on both the leeward and windward walls of the canyon are compared with the wind tunnel measured data. It is revealed that (1) on the windward wall of the canyon, the calculated pollutant concentrations using the standard, RNG and realizable κ-ε models are all in perfect agreement with the experimental observations, (2) the RNG and realizable κ-ε models provide almost the same results for pollutant concentration distributions on the leeward wall of the canyon, (3) the RNG and realizable κ-ε models overestimate greatly the pollutant concentration values on the leeward wall of the canyon, whereas the concentration distributions predicted by the standard κ-ε model on the leeward wall are in reasonable agreement with the wind tunnel data.

scholarly journals APFoam 1.0: integrated computational fluid dynamics simulation of O<sub>3</sub>–NO<sub><i>x</i></sub>–volatile organic compound chemistry and pollutant dispersion in a typical street canyon

2021 ◽  
Vol 14 (7) ◽  
pp. 4655-4681
Author(s):  
Luolin Wu ◽  
Jian Hang ◽  
Xuemei Wang ◽  
Min Shao ◽  
Cheng Gong
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Air Quality ◽  
Organic Compound ◽  
Volatile Organic Compound ◽  
Street Canyon ◽  
Vehicle Emissions ◽  
Pollutant Dispersion ◽  
Volatile Organic ◽  
Reactive Pollutant

Abstract. Urban air quality issues are closely related to human health and economic development. In order to investigate street-scale flow and air quality, this study developed the atmospheric photolysis calculation framework (APFoam 1.0), an open-source computational fluid dynamics (CFD) code based on OpenFOAM, which can be used to examine microscale reactive pollutant formation and dispersion in an urban area. The chemistry module of APFoam has been modified by adding five new types of reactions, which can implement the atmospheric photochemical mechanism (full O3–NOx–volatile organic compound chemistry) coupled with a CFD model. Additionally, the model, including the photochemical mechanism (CS07A), air flow, and pollutant dispersion, has been validated and shows good agreement with SAPRC modeling and wind tunnel experimental data, indicating that APFoam has sufficient ability to study urban turbulence and pollutant dispersion characteristics. By applying APFoam, O3–NOx–volatile organic compound (VOC) formation processes and dispersion of the reactive pollutants were analyzed in an example of a typical street canyon (aspect ratio H/W=1). The comparison of chemistry mechanisms shows that O3 and NO2 are underestimated, while NO is overestimated if the VOC reactions are not considered in the simulation. Moreover, model sensitivity cases reveal that 82 %–98 % and 75 %–90 % of NO and NO2, respectively, are related to the local vehicle emissions, which is verified as the dominant contributor to local reactive pollutant concentration in contrast to background conditions. In addition, a large amount of NOx emissions, especially NO, is beneficial to the reduction of O3 concentrations since NO consumes O3. Background precursors (NOx/VOCs) from boundary conditions only contribute 2 %–16 % and 12 %–24 % of NO and NO2 concentrations and raise O3 concentrations by 5 %–9 %. Weaker ventilation conditions could lead to the accumulation of NOx and consequently a higher NOx concentration but lower O3 concentration due to the stronger NO titration effect, which would consume O3. Furthermore, in order to reduce the reactive pollutant concentrations under the odd–even license plate policy (reduce 50 % of the total vehicle emissions), vehicle VOC emissions should be reduced by at least another 30 % to effectively lower O3, NO, and NO2 concentrations at the same time. These results indicate that the examination of the precursors (NOx and VOCs) from both traffic emissions and background boundaries is the key point for understanding O3–NOx–VOCs chemistry mechanisms better in street canyons and providing effective guidelines for the control of local street air pollution.

scholarly journals Assessing the Impact of Vehicle Speed Limits and Fleet Composition on Air Quality Near a School

2019 ◽  
Vol 16 (1) ◽  
pp. 149 ◽  
Author(s):  
Jiayi Tang ◽  
Aonghus McNabola ◽  
Bruce Misstear ◽  
Francesco Pilla ◽  
Md Saniul Alam
Keyword(s):  
Air Quality ◽  
Urban Air Pollution ◽  
Vehicle Speed ◽  
Traffic Emission ◽  
Speed Limits ◽  
School Based ◽  
Pollutant Concentrations ◽  
Fleet Composition ◽  
The Impact ◽  
Background Air

Traffic is a major source of urban air pollution that affects health, especially among children. As lower speed limits are commonly applied near schools in many cities, and different governments have different policies on vehicle fleet composition, this research estimated how different speed limits and fleet emissions affect air quality near a primary school. Based on data of traffic, weather, and background air quality records in Dublin from 2013, traffic, emission, and dispersion models were developed to assess the impact of different speed limits and fleet composition changes against current conditions. Outside the school, hypothetical speed limit changes from 30 km/h to 50 km/h could reduce the concentration of NO2 and PM10 by 3% and 2%; shifts in the fleet from diesel to petrol vehicles could reduce these pollutants by 4% and 3% but would increase the traffic-induced concentrations of CO and Benzene by 63% and 35%. These changes had significantly larger impacts on air quality on streets with higher pollutant concentrations. Findings suggest that both road safety and air quality should be considered when determining speed limits. Furthermore, fleet composition has different impacts on different pollutants and there are no clear benefits associated with incentivising either diesel or petrol engine vehicles.

scholarly journals APFoam-1.0: integrated CFD simulation of O<sub>3</sub>–NO<sub>x</sub>–VOCs chemistry and pollutant dispersion in typical street canyon

2020 ◽  
Author(s):  
Luolin Wu ◽  
Jian Hang ◽  
Xuemei Wang ◽  
Min Shao ◽  
Cheng Gong
Keyword(s):  
Air Quality ◽  
Street Canyon ◽  
Vehicle Emissions ◽  
Cfd Simulation ◽  
Pollutant Dispersion ◽  
Urban Air Quality ◽  
Urban Air ◽  
License Plate ◽  
Health And Economic Development ◽  
Reactive Pollutant

Abstract. Urban air quality issues are closely related to the human health and economic development. In order to improve the resolution and numerical accuracy of urban air quality simulation, this study has developed the Atmospheric Photolysis calculation framework (APFoam-1.0), an open-source CFD code based on OpenFOAM, which can be used to examine the micro-scale reactive pollutant formation and dispersion in the urban area. The chemistry module of the newly APFoam has been modified by adding five new types of reaction, which implements the coupling with atmospheric photochemical mechanism (full O3–NOx–VOCs chemistry) and CFD model. Additionally, numerical model has been validated and shows the good agreement with wind tunnel experimental data, indicating that the APFoam has sufficient ability to study urban turbulence and pollutant dispersion characteristics. By applying the APFoam, O3–NOx–VOCs formation processes and dispersion of the reactive pollutants are analyzed in an example of typical street canyon (aspect ratio H / W = 1). Chemistry mechanism comparison shows that O3 and NO2 are underestimated while NO is overestimated if the VOCs reactions are not considered in the simulation. Moreover, model sensitivity cases reveal that 82 %–98 % and 75 %–90 % of NO and NO2 are related to the local vehicle emissions which are verified as the dominated contributors to local reactive pollutant concentration in contrast to their background conditions. Besides, a large amount of NOx emission, especially NO emission, is beneficial to reduce the O3 concentrations since NO consumes O3. Background precursors (NOx/VOCs) from boundary conditions only contribute 2 %–16 % and 12 %–24 % of NO and NO2 concentrations and raise O3 concentration by 5 %–9 %. Weaker ventilation conditions lead to accumulation of NOx and higher NOx concentration, but a lower O3 concentrations due to the stronger NO titration effect consuming O3. Furthermore, in order to reduce the reactive pollutant concentrations under the odd-even license plate policy (reduce 50 % of the total vehicle emissions), vehicle VOCs emissions should be reduced by at least another 30 % to effectively lower O3, NO and NO2 concentrations at the same time. These results indicate that the examination of the precursors (NOx/VOCs) from both traffic emissions and background boundaries is the key point for better understanding O3–NOx–VOCs chemistry mechanisms in street canyons and providing effective guidelines for the joint prevention and control of local street air pollution.

Pollutant Effect on the Pedestrians and Bicyclists for the Different Setting of Bus Lanes in Urban Street Canyons

2012 ◽  
Vol 518-523 ◽  
pp. 3038-3044
Author(s):  
Li Lei ◽  
Jian Zhang Wang ◽  
Heng Zhang
Keyword(s):  
Emission Intensity ◽  
Street Canyon ◽  
Pollutant Dispersion ◽  
Pollutant Concentration ◽  
Windward Side ◽  
Leeward Side ◽  
Urban Street ◽  
Pollutant Concentrations ◽  
Bus Lane ◽  
Bicycle Lane

In order to study the pollutant effect on the pedestrians and bicyclists for the different setting of bus lanes, the numerical simulation of pollutant dispersion for isolated street canyon was conducted based on a two dimensional k-ε turbulence model and species transport equation. The simulation results fit well with the corresponding wind tunnel tests. The analysis result shows that the pollutant concentration at the leeward side is evidently higher than that of the windward side in the isolated street canyon. The pollutant concentration for the bicycle lane is obviously higher than that of the sidewalk near the ground at the leeward side. As the height increases, the pollutant concentration for the sidewalk is higher than that of the bicycle lane instead. The pollutant concentrations for the sidewalk and the bicycle lane are nearly the same, and almost no change with the height increases at the windward side. When the density of bus lane is low, the emission intensity of the bus lanes is lower than that of the vehicle lanes, and setting of outside bus lanes will have less pollution to the pedestrians and bicyclists. And when the density of bus lane is high, the emission intensity of the bus lanes is higher than that of the vehicle lanes, and setting of inside bus lanes will have less pollution to the pedestrians and bicyclists.

Investigating the Impact of Meteorological Conditions on Near-Road Pollutant Dispersion between Daytime and Nighttime Periods

2018 ◽  
Vol 2672 (25) ◽  
pp. 99-110 ◽  
Author(s):  
Mohammad Hashem Askariyeh ◽  
Suriya Vallamsundar ◽  
Reza Farzaneh
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Pollutant Dispersion ◽  
The United States ◽  
Meteorological Conditions ◽  
Traffic Emissions ◽  
Mobile Source ◽  
Pollutant Concentrations ◽  
The Impact ◽  
Nighttime Construction

In urban areas in Texas and the rest of the United States, roadway work zone and construction activities are often conducted at night to reduce disruption to traffic and to prevent congestion caused by lane closures during peak hours. The reduced traffic delays due to nighttime construction have the potential to reduce traffic emissions. However, the air quality impacts associated with moving these activities from daytime to nighttime have not been studied in detail. Air quality impacts depend on two major factors: the traffic emissions and meteorological conditions. While the impact of traffic emissions between time periods has been studied in the literature, there is limited knowledge on understanding the impact of meteorological conditions on the dispersion of mobile source pollutants. This study specifically addresses this gap by evaluating the impact of the meteorological conditions on pollutant concentrations under different input settings related to the region, land use, distance from roadways, and averaging periods. The assessment of the impact of metrological conditions indicated that for the same amount of emissions, the nighttime period could result in higher pollutant concentration levels. However, given that traffic congestion and overall traffic volumes are generally substantially lower in the nighttime period, the findings do not imply that nighttime construction activities result in worse air quality in terms of pollutant concentrations. Thus, the relative difference in pollutant concentrations obtained from shifting construction activities from daytime to nighttime periods should be assessed based on a combination of meteorological and traffic conditions.

scholarly journals The impact of measures to reduce ambient air PM<sub>10</sub> concentrations originating from road dust, evaluated for a street canyon in Helsinki

2019 ◽  
Vol 19 (17) ◽  
pp. 11199-11212 ◽  
Author(s):  
Ana Stojiljkovic ◽  
Mari Kauhaniemi ◽  
Jaakko Kukkonen ◽  
Kaarle Kupiainen ◽  
Ari Karppinen ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Street Canyon ◽  
Dust Emission ◽  
Road Dust ◽  
Ambient Air ◽  
Air Quality Measurements ◽  
Emission Models ◽  
The Impact ◽  
Quality Measurements

Abstract. We have numerically evaluated how effective selected potential measures would be for reducing the impact of road dust on ambient air particulate matter (PM10). The selected measures included a reduction of the use of studded tyres on light-duty vehicles and a reduction of the use of salt or sand for traction control. We have evaluated these measures for a street canyon located in central Helsinki for four years (2007–2009 and 2014). Air quality measurements were conducted in the street canyon for two years, 2009 and 2014. Two road dust emission models, NORTRIP (NOn-exhaust Road TRaffic Induced Particle emissions) and FORE (Forecasting Of Road dust Emissions), were applied in combination with the Operational Street Pollution Model (OSPM), a street canyon dispersion model, to compute the street increments of PM10 (i.e. the fraction of PM10 concentration originating from traffic emissions at the street level) within the street canyon. The predicted concentrations were compared with the air quality measurements. Both road dust emission models reproduced the seasonal variability of the PM10 concentrations fairly well but under-predicted the annual mean values. It was found that the largest reductions of concentrations could potentially be achieved by reducing the fraction of vehicles that use studded tyres. For instance, a 30 % decrease in the number of vehicles using studded tyres would result in an average decrease in the non-exhaust street increment of PM10 from 10 % to 22 %, depending on the model used and the year considered. Modelled contributions of traction sand and salt to the annual mean non-exhaust street increment of PM10 ranged from 4 % to 20 % for the traction sand and from 0.1 % to 4 % for the traction salt. The results presented here can be used to support the development of optimal strategies for reducing high springtime particulate matter concentrations originating from road dust.

scholarly journals Evolution of Gaseous and Particulate Pollutants in the Air: What Changed after Five Lockdown Weeks at a Southwest Atlantic European Region (Northwest of Spain) Due to the SARS-CoV-2 Pandemic?

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 562
Author(s):  
Jorge Moreda-Piñeiro ◽  
Joel Sánchez-Piñero ◽  
María Fernández-Amado ◽  
Paula Costa-Tomé ◽  
Nuria Gallego-Fernández ◽  
...  
Keyword(s):  
Air Quality ◽  
Road Traffic ◽  
Statistical Significance ◽  
Temporal Trends ◽  
Air Pollutant ◽  
Concentration Data ◽  
Southwest Atlantic ◽  
Pollutant Concentrations ◽  
Air Quality Monitoring Stations ◽  
Almost All

Due to the exponential growth of the SARS-CoV-2 pandemic in Spain (2020), the Spanish Government adopted lockdown measures as mitigating strategies to reduce the spread of the pandemic from 14 March. In this paper, we report the results of the change in air quality at two Atlantic Coastal European cities (Northwest Spain) during five lockdown weeks. The temporal evolution of gaseous (nitrogen oxides, comprising NOx, NO, and NO2; sulfur dioxide, SO2; carbon monoxide, CO; and ozone, O3) and particulate matter (PM10; PM2.5; and equivalent black carbon, eBC) pollutants were recorded before (7 February to 13 March 2020) and during the first five lockdown weeks (14 March to 20 April 2020) at seven air quality monitoring stations (urban background, traffic, and industrial) in the cities of A Coruña and Vigo. The influences of the backward trajectories and meteorological parameters on air pollutant concentrations were considered during the studied period. The temporal trends indicate that the concentrations of almost all species steadily decreased during the lockdown period with statistical significance, with respect to the pre-lockdown period. In this context, great reductions were observed for pollutants related mainly to fossil fuel combustion, road traffic, and shipping emissions (−38 to −78% for NO, −22 to −69% for NO2, −26 to −75% for NOx, −3 to −77% for SO2, −21% for CO, −25 to −49% for PM10, −10 to −38% for PM2.5, and −29 to −51% for eBC). Conversely, O3 concentrations increased from +5 to +16%. Finally, pollutant concentration data for 14 March to 20 April of 2020 were compared with those of the previous two years. The results show that the overall air pollutants levels were higher during 2018–2019 than during the lockdown period.

scholarly journals Feature and Language Selection in Temporal Symbolic Regression for Interpretable Air Quality Modelling

Algorithms ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 76
Author(s):  
Estrella Lucena-Sánchez ◽  
Guido Sciavicco ◽  
Ionel Eduard Stan
Keyword(s):  
Air Quality ◽  
Fundamental Problem ◽  
Multivariate Time Series ◽  
Quality Data ◽  
Data Sets ◽  
Air Quality Modelling ◽  
Regression Problem ◽  
Car Traffic ◽  
Pollutant Concentrations ◽  
Language Selection

Air quality modelling that relates meteorological, car traffic, and pollution data is a fundamental problem, approached in several different ways in the recent literature. In particular, a set of such data sampled at a specific location and during a specific period of time can be seen as a multivariate time series, and modelling the values of the pollutant concentrations can be seen as a multivariate temporal regression problem. In this paper, we propose a new method for symbolic multivariate temporal regression, and we apply it to several data sets that contain real air quality data from the city of Wrocław (Poland). Our experiments show that our approach is superior to classical, especially symbolic, ones, both in statistical performances and the interpretability of the results.

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