scholarly journals Estimation of Air Quality Criterion-based Building Setback Distance From Urban Roads and Freeway Using Microscopic Simulation of Traffic, Emissions, and Pollution Dispersion

2017 ◽  
Author(s):  
Sujit Das
Keyword(s):  
Air Quality ◽  
Quality Criterion ◽  
Traffic Emissions ◽  
Microscopic Simulation ◽  
Pollution Dispersion ◽  
Setback Distance

scholarly journals Regional Scale Impact of the COVID-19 Lockdown on Air Quality: Gaseous Pollutants in the Po Valley, Northern Italy

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 264 ◽  
Author(s):  
Giovanni Lonati ◽  
Federico Riva
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Regional Scale ◽  
High Volume ◽  
Ambient Air ◽  
Northern Italy ◽  
Traffic Emissions ◽  
Gaseous Pollutants ◽  
Po Valley ◽  
Concentration Levels

The impact of the reduced atmospheric emissions due to the COVID-19 lockdown on ambient air quality in the Po Valley of Northern Italy was assessed for gaseous pollutants (NO2, benzene, ammonia) based on data collected at the monitoring stations distributed all over the area. Concentration data for each month of the first semester of 2020 were compared with those of the previous six years, on monthly, daily, and hourly bases, so that pre, during, and post-lockdown conditions of air quality could be separately analyzed. The results show that, as in many other areas worldwide, the Po Valley experienced better air quality during 2020 spring months for NO2 and benzene. In agreement with the reductions of nitrogen oxides and benzene emissions from road traffic, estimated to be −35% compared to the regional average, the monthly mean concentration levels for 2020 showed reductions in the −40% to −35% range compared with the previous years, but with higher reductions, close to −50%, at high-volume-traffic sites in urban areas. Conversely, NH3 ambient concentration levels, almost entirely due the emissions of the agricultural sector, did not show any relevant change, even at high-volume-traffic sites in urban areas. These results point out the important role of traffic emissions in NO2 and benzene ambient levels in the Po Valley, and confirm that this region is a rather homogeneous air basin with urban area hot-spots, the contributions of which add up to a relatively high regional background concentration level. Additionally, the relatively slow response of the air quality levels to the sudden decrease of the emissions due to the lockdown shows that this region is characterized by a weak exchange of the air masses that favors both the build-up of atmospheric pollutants and the development of secondary formation processes. Thus, air quality control strategies should aim for structural interventions intended to reduce traffic emissions at the regional scale and not only in the largest urban areas.

scholarly journals Mobile monitoring of urban air quality at high spatial resolution by low-cost sensors: Impacts of COVID-19 pandemic lockdown

2020 ◽  
Author(s):  
Shibao Wang ◽  
Yun Ma ◽  
Zhongrui Wang ◽  
Lei Wang ◽  
Xuguang Chi ◽  
...  
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Low Cost ◽  
Air Pollutant ◽  
Mitigation Strategies ◽  
Traffic Emissions ◽  
Urban Air ◽  
Industrial Emissions ◽  
Gis Technology ◽  
Mobile Monitoring

Abstract. The development of low-cost sensors and novel calibration algorithms provides new hints to complement conventional ground-based observation sites to evaluate the spatial and temporal distribution of pollutants on hyper-local scales (tens of meters). Here we use sensors deployed on a taxi fleet to explore the air quality in the road network of Nanjing over the course of a year (Oct. 2019–Sep. 2020). Based on GIS technology, we develop a grid analysis method to obtain 50 m resolution maps of major air pollutants (CO, NO2, and O3). Through hotspots identification analysis, we find three main sources of air pollutants including traffic, industrial emissions, and cooking fumes. We find that CO and NO2 concentrations show a pattern: highways > arterial roads > secondary roads > branch roads > residential streets, reflecting traffic volume. While the O3 concentrations in these five road types are in opposite order due to the titration effect of NOx. Combined the mobile measurements and the stationary station data, we diagnose that the contribution of traffic-related emissions to CO and NO2 are 42.6 % and 26.3 %, respectively. Compared to the pre-COVID period, the concentrations of CO and NO2 during COVID-lockdown period decreased for 44.9 % and 47.1 %, respectively, and the contribution of traffic-related emissions to them both decreased by more than 50 %. With the end of the COVID-lockdown period, traffic emissions and air pollutant concentrations rebounded substantially, indicating that traffic emissions have a crucial impact on the variation of air pollutants levels in urban regions. This research demonstrates the sense power of mobile monitoring for urban air pollution, which provides detailed information for source attribution, accurate traceability, and potential mitigation strategies at urban micro-scale.

scholarly journals Organic Air Quality Markers of Indoor and Outdoor PM2.5 Aerosols in Primary Schools from Barcelona

2020 ◽  
Vol 17 (10) ◽  
pp. 3685 ◽  
Author(s):  
Barend L. van Drooge ◽  
Ioar Rivas ◽  
Xavier Querol ◽  
Jordi Sunyer ◽  
Joan O. Grimalt
Keyword(s):  
Air Quality ◽  
Indoor Air ◽  
Primary Schools ◽  
Airborne Particulate Matter ◽  
Traffic Emissions ◽  
Quality Markers ◽  
Polycyclic Aromatic ◽  
Motorized Vehicles ◽  
Carbon Concentrations ◽  
Indoor And Outdoor

Airborne particulate matter with an aerodynamic diameter smaller than 2.5 µg, PM2.5 was regularly sampled in classrooms (indoor) and playgrounds (outdoor) of primary schools from Barcelona. Three of these schools were located downtown and three in the periphery, representing areas with high and low traffic intensities. These aerosols were analyzed for organic molecular tracers and polycyclic aromatic hydrocarbons (PAHs) to identify the main sources of these airborne particles and evaluate the air quality in the urban location of the schools. Traffic emissions were the main contributors of PAHs to the atmospheres in all schools, with higher average concentrations in those located downtown (1800–2700 pg/m3) than in the periphery (760–1000 pg/m3). The similarity of the indoor and outdoor concentrations of the PAH is consistent with a transfer of outdoor traffic emissions to the indoor classrooms. This observation was supported by the hopane and elemental carbon concentrations in PM2.5, markers of motorized vehicles, that were correlated with PAHs. The concentrations of food-related markers, such as glucoses, sucrose, malic, azelaic and fatty acids, were correlated and were higher in the indoor atmospheres. These compounds were also correlated with plastic additives, such as phthalic acid and diisobutyl, dibutyl and dicyclohexyl phthalates. Clothing constituents, e.g., adipic acid, and fragrances, galaxolide and methyl dihydrojasmonate were also correlated with these indoor air compounds. All these organic tracers were correlated with the organic carbon of PM2.5, which was present in higher concentrations in the indoor than in the outdoor atmospheres.

scholarly journals Impact of Ventilation Strategy on the Transmission of Outdoor Pollutants into Indoor Environment Using CFD

2021 ◽  
Vol 13 (18) ◽  
pp. 10343
Author(s):  
Murtaza Mohammadi ◽  
John Calautit
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Indoor Environment ◽  
Dispersion Model ◽  
Personal Exposure ◽  
Health Impact ◽  
Concentration Data ◽  
Pollution Dispersion ◽  
Indoor Spaces

The transition to remote working due to the pandemic has accentuated the importance of clean indoor air, as people spend a significant portion of their time indoors. Amongst the various determinants of indoor air quality, outdoor pollution is a significant source. While conventional studies have certainly helped to quantify the long-term personal exposure to pollutants and assess their health impact, they have not paid special attention to the mechanism of transmission of pollutants between the two environments. Nevertheless, the quantification of infiltration is essential to determine the contribution of ambient pollutants in indoor air quality and its determinants. This study evaluates the transmission of outdoor pollutants into the indoor environment using 3D computational fluid dynamics modelling with a pollution dispersion model. Naturally ventilated buildings next to an urban canyon were modelled and simulated using Ansys Fluent and validated against wind tunnel results from the Concentration Data of Street Canyons database. The model consisted of two buildings of three storeys each, located on either side of a road. Two line-source pollutants were placed in the street, representing traffic emissions. Three internal rooms were selected and modelled on each floor and implemented with various ventilation strategies. Results indicate that for a canyon with an aspect ratio of 1, indoor spaces in upstream buildings are usually less polluted than downstream ones. Although within the canyon, pollution is 2–3 times higher near the upstream building. Cross ventilation can minimise or prevent infiltration of road-side pollutants into indoor spaces, while also assisting in the dispersion of ambient pollutants. The critical configuration, in terms of air quality, is single-sided ventilation from the canyon. This significantly increases indoor pollutant concentration regardless of the building location. The study reveals that multiple factors determine the indoor–outdoor links, and thorough indexing and understanding of the processes can help designers and urban planners in regulating urban configuration and geometries for improved indoor air quality. Future works should look at investigating the influence of indoor emissions and the effects of different seasons.

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.

scholarly journals Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52)

2017 ◽  
Vol 10 (7) ◽  
pp. 2615-2633 ◽  
Author(s):  
Volker Grewe ◽  
Eleni Tsati ◽  
Mariano Mertens ◽  
Christine Frömming ◽  
Patrick Jöckel
Keyword(s):  
Air Quality ◽  
Tropospheric Ozone ◽  
Radiative Forcing ◽  
Road Traffic ◽  
Computing Time ◽  
Reaction Rates ◽  
Traffic Emissions ◽  
Time Step ◽  
Road Traffic Emissions ◽  
The Impact

Abstract. Questions such as what is the contribution of road traffic emissions to climate change? or what is the impact of shipping emissions on local air quality? require a quantification of the contribution of specific emissions sectors to the concentration of radiatively active species and air-quality-related species, respectively. Here, we present a diagnostics package, implemented in the Modular Earth Submodel System (MESSy), which keeps track of the contribution of source categories (mainly emission sectors) to various concentrations. The diagnostics package is implemented as a submodel (TAGGING) of EMAC (European Centre for Medium-Range Weather Forecasts – Hamburg (ECHAM)/MESSy Atmospheric Chemistry). It determines the contributions of 10 different source categories to the concentration of ozone, nitrogen oxides, peroxyacytyl nitrate, carbon monoxide, non-methane hydrocarbons, hydroxyl, and hydroperoxyl radicals ( =  tagged tracers). The source categories are mainly emission sectors and some other sources for completeness. As emission sectors, road traffic, shipping, air traffic, anthropogenic non-traffic, biogenic, biomass burning, and lightning are considered. The submodel obtains information on the chemical reaction rates, online emissions, such as lightning, and wash-out rates. It then solves differential equations for the contribution of a source category to each of the seven tracers. This diagnostics package does not feed back to any other part of the model. For the first time, it takes into account chemically competing effects: for example, the competition between NOx, CO, and non-methane hydrocarbons (NMHCs) in the production and destruction of ozone. We show that the results are in-line with results from other tagging schemes and provide plausibility checks for concentrations of trace gases, such as OH and HO2, which have not previously been tagged. The budgets of the tagged tracers, i.e. the contribution from individual source categories (mainly emission sectors) to, e.g., ozone, are only marginally sensitive to changes in model resolution, though the level of detail increases. A reduction in road traffic emissions by 5 % shows that road traffic global tropospheric ozone is reduced by 4 % only, because the net ozone productivity increases. This 4 % reduction in road traffic tropospheric ozone corresponds to a reduction in total tropospheric ozone by  ≈  0.3 %, which is compensated by an increase in tropospheric ozone from other sources by 0.1 %, resulting in a reduction in total tropospheric ozone of  ≈  0.2 %. This compensating effect compares well with previous findings. The computational costs of the TAGGING submodel are low with respect to computing time, but a large number of additional tracers are required. The advantage of the tagging scheme is that in one simulation and at every time step and grid point, information is available on the contribution of different emission sectors to the ozone budget, which then can be further used in upcoming studies to calculate the respective radiative forcing simultaneously.

scholarly journals Functionality of openair package in air pollution assessment and modeling — a case study of Krakow

2017 ◽  
Vol 28 (2) ◽  
pp. 22-27 ◽  
Author(s):  
Adriana Szulecka ◽  
Robert Oleniacz ◽  
Mateusz Rzeszutek
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Quality Management System ◽  
Measurement Data ◽  
Pollution Assessment ◽  
Software Modeling ◽  
Pollution Dispersion ◽  
Back Trajectories ◽  
Air Pollution Dispersion ◽  
Air Pollution Assessment

Abstract The paper presents the possibilities of selected functions from openair package for R programming environment in urban air pollution assessment. Examples of data analysis were based on the measurements from continuous air quality monitoring stations in Krakow (Poland). In order to present additional functionality of this software, modeling results of back trajectories and air pollution dispersion were used. Functions and visualization methods included in openair package make scrutiny of large data sets easier and less time consuming. They allow for analysis of measurement data with the determination of general relationships between parameters, additional complex spatial analyses for back trajectories, and validation of air pollution dispersion models. Openair package is, therefore, a valuable and functional tool that can be successfully used as a support in the air quality management system.

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