scholarly journals A Study of Traffic Emissions Based on Floating Car Data for Urban Scale Air Quality Applications

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1064
Author(s):  
Felicita Russo ◽  
Maria Gabriella Villani ◽  
Ilaria D’Elia ◽  
Massimo D’Isidoro ◽  
Carlo Liberto ◽  
...  
Keyword(s):  
Air Quality ◽  
Road Traffic ◽  
Urban Traffic ◽  
Traffic Emissions ◽  
Floating Car Data ◽  
Road Traffic Emissions ◽  
Pollutant Concentrations ◽  
Modeling Systems ◽  
Hourly Data ◽  
Microscale Modeling

Urban air quality in cities is strongly influenced by road traffic emissions. Micro-scale models have often been used to evaluate the pollutant concentrations at the scale of the order of meters for estimating citizen exposure. Nonetheless, retrieving emissions information with the required spatial and temporal details is still not an easy task. In this work, we use our modelling system PMSS (Parallel Micro Swift Spray) with an emission dataset based on Floating Car Data (FCD), containing hourly data for a large number of road links within a 1 × 1 km2 domain in the city of Rome for the month of May 2013. The procedures to obtain both the emission database and the PMSS simulations are hosted on CRESCO (Computational Centre for Research on Complex Systems)/ENEAGRID HPC facilities managed by ENEA. The possibility of using such detailed emissions, coupled with HPC performance, represents a desirable goal for microscale modeling that can allow such modeling systems to be employed in quasi-real time and nowcasting applications. We compute NOx concentrations obtained by: (i) emissions coming from prescribed hourly modulations of three types of roads, based on vehicle flux data in the FCD dataset, and (ii) emissions from the FCD dataset integrated into our modelling chain. The results of the simulations are then compared to concentrations measured at an urban traffic station.

scholarly journals Automated Planning for Urban Traffic Management

2017 ◽  
Author(s):  
Thomas L. McCluskey ◽  
Mauro Vallati ◽  
Santiago Franco
Keyword(s):  
Air Quality ◽  
Traffic Management ◽  
Road Traffic ◽  
Automated Planning ◽  
Road Transport ◽  
Urban Traffic ◽  
Traffic Emissions ◽  
Transport Infrastructure ◽  
Large Cities ◽  
Road Traffic Emissions

The global growth in urbanisation increases the demand for services including road transport infrastructure, presenting challenges in terms of mobility. Optimising the exploitation of urban road network, while attempting to minimise the effects of traffic emissions, is a great challenge. SimplyfAI was a UK research council grant funded project which was aimed towards solving air quality problems caused by road traffic emissions. Large cities such as Manchester struggle to meet air quality limits as the range of available traffic management devices is limited. In the study, we investigated the application of linked data to enrich environmental and traffic data feeds, and we used this with automated planning tools to enable traffic to be managed at a region level. The management will have the aim of avoiding air pollution problems before they occur. This demo focuses on the planning component, and in particular the engineering and validation aspects, that were pivotal for the success of the project.

scholarly journals Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO2 and PM2.5 Pollution in Urban Areas

2020 ◽  
Vol 17 (6) ◽  
pp. 2099 ◽  
Author(s):  
Martin Otto Paul Ramacher ◽  
Matthias Karl
Keyword(s):  
Air Pollution ◽  
Population Dynamics ◽  
Urban Areas ◽  
Road Traffic ◽  
Ambient Air ◽  
Traffic Emissions ◽  
Exposure Model ◽  
Population Exposure ◽  
Road Traffic Emissions ◽  
Pollutant Concentrations

To evaluate the effectiveness of alternative policies and measures to reduce air pollution effects on urban citizen’s health, population exposure assessments are needed. Due to road traffic emissions being a major source of emissions and exposure in European cities, it is necessary to account for differentiated transport environments in population dynamics for exposure studies. In this study, we applied a modelling system to evaluate population exposure in the urban area of Hamburg in 2016. The modeling system consists of an urban-scale chemistry transport model to account for ambient air pollutant concentrations and a dynamic time-microenvironment-activity (TMA) approach, which accounts for population dynamics in different environments as well as for infiltration of outdoor to indoor air pollution. We integrated different modes of transport in the TMA approach to improve population exposure assessments in transport environments. The newly developed approach reports 12% more total exposure to NO2 and 19% more to PM2.5 compared with exposure estimates based on residential addresses. During the time people spend in different transport environments, the in-car environment contributes with 40% and 33% to the annual sum of exposure to NO2 and PM2.5, in the walking environment with 26% and 30%, in the cycling environment with 15% and 17% and other environments (buses, subway, suburban, and regional trains) with less than 10% respectively. The relative contribution of road traffic emissions to population exposure is highest in the in-car environment (57% for NO2 and 15% for PM2.5). Results for population-weighted exposure revealed exposure to PM2.5 concentrations above the WHO AQG limit value in the cycling environment. Uncertainties for the exposure contributions arising from emissions and infiltration from outdoor to indoor pollutant concentrations range from −12% to +7% for NO2 and PM2.5. The developed “dynamic transport approach” is integrated in a computationally efficient exposure model, which is generally applicable in European urban areas. The presented methodology is promoted for use in urban mobility planning, e.g., to investigate on policy-driven changes in modal split and their combined effect on emissions, population activity and population exposure.

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 Variability of levels of PM, black carbon and particle number concentration in selected European cities

2011 ◽  
Vol 11 (3) ◽  
pp. 8665-8717 ◽  
Author(s):  
C. Reche ◽  
X. Querol ◽  
A. Alastuey ◽  
M. Viana ◽  
J. Pey ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Road Traffic ◽  
Traffic Emissions ◽  
Northern Europe ◽  
Gaseous Pollutants ◽  
Emission Sources ◽  
Urban Background ◽  
Road Traffic Emissions ◽  
The Impact

Abstract. In many large cities of Europe standard air quality limit values of particulate matter (PM) are exceeded. Emissions from road traffic and biomass burning are frequently reported to be the major causes. As a consequence of these exceedances a large number of air quality plans, most of them focusing on traffic emissions reductions, have been implemented in the last decade. In spite of this implementation, a number of cities did not record a decrease of PM levels. Thus, is the efficiency of air quality plans overestimated? Or do we need a more specific metric to evaluate the impact of the above emissions on the levels of urban aerosols? This study shows the results of the interpretation of the 2009 variability of levels of PM, black carbon (BC), aerosol number concentration (N) and a number of gaseous pollutants in seven selected urban areas covering road traffic, urban background, urban-industrial, and urban-shipping environments from southern, central and northern Europe. The results showed that variations of PM and N levels do not always reflect the variation of the impact of road traffic emissions on urban aerosols. However, BC levels vary proportionally with those of traffic related gaseous pollutants, such as CO, NO2 and NO. Due to this high correlation, one may suppose that monitoring the levels of these gaseous pollutants would be enough to extrapolate exposure to traffic-derived BC levels. However, the BC/CO, BC/NO2 and BC/NO ratios vary widely among the cities studied, as a function of distance to traffic emissions, vehicle fleet composition and the influence of other emission sources such as biomass burning. Thus, levels of BC should be measured at air quality monitoring sites. During traffic rush hours, a narrow variation in the N/BC ratio was evidenced, but a wide variation of this ratio was determined for the noon period. Although in central and northern Europe N and BC levels tend to vary simultaneously, not only during the traffic rush hours but also during the whole day, in urban background stations in southern Europe maximum N levels coinciding with minimum BC levels are recorded at midday in all seasons. These N maxima recorded in southern European urban background environments are attributed to midday nucleation episodes occurring when gaseous pollutants are diluted and maximum insolation and O3 levels occur. The occurrence of SO2 peaks may also contribute to the occurrence of midday nucleation bursts in specific industrial or shipping-influenced areas, although at several central European sites similar levels of SO2 are recorded without yielding nucleation episodes. Accordingly, it is clearly evidenced that N variability in different European urban environments is not equally influenced by the same emission sources and atmospheric processes. We conclude that N variability does not always reflect the impact of road traffic on air quality, whereas BC is a more consistent tracer of such an influence. The combination of PM10 and BC monitoring in urban areas potentially constitutes a useful approach to evaluate the impact of road traffic emissions on air quality.

INTEGRATED MODELING OF ROAD TRAFFIC EMISSIONS: APPLICATION TO LISBON AIR QUALITY MANAGEMENT

2004 ◽  
Vol 35 (5-6) ◽  
pp. 535-548 ◽  
Author(s):  
C. BORREGO ◽  
O. TCHEPEL ◽  
L. SALMIM ◽  
J. H. AMORIM ◽  
A. M. COSTA ◽  
...  
Keyword(s):  
Air Quality ◽  
Quality Management ◽  
Road Traffic ◽  
Integrated Modeling ◽  
Traffic Emissions ◽  
Air Quality Management ◽  
Road Traffic Emissions

scholarly journals New considerations for PM, Black Carbon and particle number concentration for air quality monitoring across different European cities

2011 ◽  
Vol 11 (13) ◽  
pp. 6207-6227 ◽  
Author(s):  
C. Reche ◽  
X. Querol ◽  
A. Alastuey ◽  
M. Viana ◽  
J. Pey ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Road Traffic ◽  
Traffic Emissions ◽  
Quality Monitoring ◽  
Gaseous Pollutants ◽  
Air Quality Monitoring ◽  
Urban Background ◽  
Road Traffic Emissions ◽  
The Impact

Abstract. In many large cities of Europe standard air quality limit values of particulate matter (PM) are exceeded. Emissions from road traffic and biomass burning are frequently reported to be the major causes. As a consequence of these exceedances a large number of air quality plans, most of them focusing on traffic emissions reductions, have been implemented in the last decade. In spite of this implementation, a number of cities did not record a decrease of PM levels. Thus, is the efficiency of air quality plans overestimated? Do the road traffic emissions contribute less than expected to ambient air PM levels in urban areas? Or do we need a more specific metric to evaluate the impact of the above emissions on the levels of urban aerosols? This study shows the results of the interpretation of the 2009 variability of levels of PM, Black Carbon (BC), aerosol number concentration (N) and a number of gaseous pollutants in seven selected urban areas covering road traffic, urban background, urban-industrial, and urban-shipping environments from southern, central and northern Europe. The results showed that variations of PM and N levels do not always reflect the variation of the impact of road traffic emissions on urban aerosols. However, BC levels vary proportionally with those of traffic related gaseous pollutants, such as CO, NO2 and NO. Due to this high correlation, one may suppose that monitoring the levels of these gaseous pollutants would be enough to extrapolate exposure to traffic-derived BC levels. However, the BC/CO, BC/NO2 and BC/NO ratios vary widely among the cities studied, as a function of distance to traffic emissions, vehicle fleet composition and the influence of other emission sources such as biomass burning. Thus, levels of BC should be measured at air quality monitoring sites. During morning traffic rush hours, a narrow variation in the N/BC ratio was evidenced, but a wide variation of this ratio was determined for the noon period. Although in central and northern Europe N and BC levels tend to vary simultaneously, not only during the traffic rush hours but also during the whole day, in urban background stations in southern Europe maximum N levels coinciding with minimum BC levels are recorded at midday in all seasons. These N maxima recorded in southern European urban background environments are attributed to midday nucleation episodes occurring when gaseous pollutants are diluted and maximum insolation and O3 levels occur. The occurrence of SO2 peaks may also contribute to the occurrence of midday nucleation bursts in specific industrial or shipping-influenced areas, although at several central European sites similar levels of SO2 are recorded without yielding nucleation episodes. Accordingly, it is clearly evidenced that N variability in different European urban environments is not equally influenced by the same emission sources and atmospheric processes. We conclude that N variability does not always reflect the impact of road traffic on air quality, whereas BC is a more consistent tracer of such an influence. However, N should be measured since ultrafine particles (<100 nm) may have large impacts on human health. The combination of PM10 and BC monitoring in urban areas potentially constitutes a useful approach for air quality monitoring. BC is mostly governed by vehicle exhaust emissions, while PM10 concentrations at these sites are also governed by non-exhaust particulate emissions resuspended by traffic, by midday atmospheric dilution and by other non-traffic emissions.

scholarly journals Ambient Air Quality Assessment in the Grand Casablanca Area (Morocco): Impact of Road Traffic Emissions for the 2013-2016 Period

2018 ◽  
Vol 1 (1) ◽  
pp. 1 ◽  
Author(s):  
Manal Inchaouh ◽  
Kenza Khomsi ◽  
Pr. Mohamed Tahiri
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Areas ◽  
Road Traffic ◽  
Ambient Air ◽  
Traffic Emissions ◽  
Road Traffic Emissions ◽  
Critical Areas ◽  
Air Quality Assessment ◽  
Road Traffic Pollution

<p><em>Air Pollution is a serious hazard worldwide especially in urban areas. Road traffic is the main cause of pollution in agglomerations that are confronted to an excess of pollutants due to traffic intensity and the dominance of diesel cars. This paper presents the assessment of road traffic pollution in the Grand Casablanca</em><em> </em><em>area. Data used are the result of simultaneous measurements at thirteen sites located in the Grand Casablanca. Available data cover 4 years period (2013</em><em>-</em><em>2016). Traffic-related air pollutants are reviewed in order to assess their impact on the local air quality. It include nitrogen dioxide (NO<sub>2</sub>), particulate matter (PM<sub>10</sub>), carbon monoxide (CO) and Benzene (C<sub>6</sub>H<sub>6</sub>). Annual evolutions are presented and compared to national air quality standards;</em><em> </em><em>NO<sub>2</sub> annual trends are also evaluated. The [NO]/[NO<sub>2</sub>] emissions ratio calculation allows then to characterize the measurement sites against road traffic. The paper focuses on determining the contribution of road traffic emissions on air quality modifying; we found spatial variability in traffic</em><em> </em><em>pollutants. The results pointed out that road traffic and conditions are the main causes of air pollution in the area and the analysis provide a quick view of the relatively critical areas that need more action to reduce this pollution.</em></p>

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

2017 ◽  
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?" requires 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, implemented in the Modular Earth-System Model MESSy, which keeps track of the contribution of source categories (mainly emission sectors) to various concentrations. The diagnostics is implemented as a submodel (TAGGING) of EMAC (European Centre for Medium-Range Weather Forecasts – Hamburg (ECHAM)/Modular Earth Submodel System (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 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 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 &amp;approx; 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 &amp;approv; 0.2 %. This compensating effect compares well 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.

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