Traffic-induced Air Pollution Research Articles

Traffic Density and Measurement of Traffic-Induced Air Pollution in Apapa Seaport’s Environment

Traffic Density and Measurement of Traffic-Induced Air Pollution in Apapa Seaport’s Environment

Perception of Risks from Wood Combustion and Traffic Induced Air Pollution: Evidence from Northern Europe

The health effects of particulate matter, increasing emissions from transportation and requisites for making use of biofuels brings up the need to understand how individuals interpret air-pollution-related risks from wood burning and traffic. We aim to clarify the extent to which perceived risks from road-traffic and wood-smoke can be explained by the individual psychological, social status-related and socio-institutional factors in the case of two Northern European countries, Finland and Estonia. This approach elucidates which of the closely intertwined factors shape the perception of risks from air pollution in different socio-institutional contexts and for different air pollution sources. The study uses data from cross-sectional population surveys conducted among 1112 Finnish and 1000 Estonian residents about environmental health risk perception and coping. Binary logistic regression analysis demonstrated that in both countries’ cases, the perceived personal and general risk from traffic exhaust and wood-smoke can be explained by the perception of exposure to pollution and, also, by the level of knowledge of, the worry about and the possible symptoms from environmental health factors. The perceived vulnerability due to poor health further sensitises individuals towards risks from air pollution. Higher trust towards state institutions in guaranteeing a healthy living environment and greater perceived openness about the risks may attenuate the feelings of vulnerability to air pollution risks in Finland compared to Estonia. The ingrained appeal for wood burning may explain the higher acceptance of exhausts from wood-burning compared to traffic. This may lead to scant support for measures to reduce emissions from wood combustion.

A Mathematical and Numerical Framework for Traffic-Induced Air Pollution Simulation in Bamako

We present a mathematical and numerical framework for the simulation of traffic-induced air pollution in Bamako. We consider a deterministic modeling approach where the spatio-temporal dynamics of the concentrations of air pollutants are governed by a so-called chemical transport model. The time integration and spatial discretization of the model are achieved using the forward Euler algorithm and the finite-element method, respectively. The traffic emissions are estimated using a road traffic simulation package called SUMO. The numerical results for two road traffic-induced air pollutants, namely the carbon monoxide (CO) and the fine particulate matter (PM2.5), support that the proposed framework is suited for reproducing the dynamics of the pollutants specified.

Three-dimensional spatial modelling of traffic-induced urban air pollution using the Graz Lagrangian model and GIS

Air pollution is a significant global problem that affects climate, human, and ecosystem health. Traffic emissions are a major source of atmospheric pollution in large cities. The aim of this research was to support air quality analysis by spatially modelling traffic-induced air pollution dispersion in urban areas at the street level. The dispersion model called the Graz Lagrangian model (GRAL model) was adapted to determine the NOx concentration level based on traffic, meteorology, buildings, and street configuration data in one of Tehran’s high traffic routes. In this case, meteorological parameters such as wind speed and direction were considered significant factors. Later, using local and general auto-correlation analyses, temporal and spatial variations in the concentration of NOx were measured at different altitudes. The results showed that the average output concentration of NOx pollutants at different altitudes ranges from 64.5 to 426.6 ppb. The resulting Moran index equals to 0.7–0.9 which indicates a high level of positive spatial auto-correlation. The analysis of the local Moran index represents the overcame pollution clusters with high levels of concentration at low to medium heights and the rise in clusters with low pollution at higher heights, while there is no clear clustering in the middle sections. In addition, the study of pollutant concentration variations over time has shown that pollution peaks occur at 07:00–08:00 and 21:00–22:00.

Empirical Assessment and Modeling of Traffic-induced Air Pollution

Congestion and traffic-induced air pollution are associated with population growth and economic development. Compared with congestion, there are relatively few studies on modeling and assessment of traffic-induced pollution. This paper presents an empirical assessment and analysis of traffic-induced air pollution with real-world data collected from the Hong Kong Strategic Road Network. The study employed historical data of traffic flows, speeds, and emission of air pollutants collated by the Hong Kong Transport Department and Environmental Protection Department. This paper first reveals the correlation between traffic flows, speeds, and corresponding induced pollutants including nitrogen oxides (NO2, NOX) and carbon monoxide (CO). To gain further statistical insight, a regression analysis was conducted on the flow–speed–emission relationship at three air quality monitoring stations, which revealed the significance of various factors on this relationship. This study contributes to green transport management and urban sustainability.

Traffic-induced atmospheric pollution during the COVID-19 lockdown: Dispersion modeling based on traffic flow monitoring in Turin, Italy

The COVID-19 pandemic, as a worldwide threat to public health, has led many governments to impose mobility restrictions and adopt partial or full lockdown strategies in many regions to control the disease outbreak. Although these lockdowns are imposed to save public health by reducing the transmission of the virus, rather significant improvements of the air quality in this period have been reported in different areas, mainly as a result of the reduction in vehicular trips. In this research, the city of Turin in the northern part of Italy has been considered as the study area, because of its special meteorology and geographic location in one of the most polluted regions in Europe, and also its high density of vehicular emissions. A Lagrangian approach is applied to illustrate and analyze the effect of imposing full lockdown restrictions on the reduction of traffic-induced air pollution in the city. To do this, the real-time traffic flow during the lockdown period is recorded, and by utilizing CALPUFF version 7, the dispersion of PM2.5, Total Suspended Particulate (TSP), Benzo(a)pyrene (BaP), NOx, and Black Carbon (BC) emitted from all circulating vehicles during and before the lockdown period are compared. Results indicate that the concentration of pollutants generated by road traffic sources (including passenger cars, busses, heavy-duty vehicles, light-duty vehicles, mopeds, and motorcycles) reduced at least 70% (for PM2.5) up to 88.1% (for BaP) during the studied period. Concentration maps show that the concentration reduction varied in different areas of the town, mainly due to the characteristics and strength of the emission sources and the geophysical features of the area.

A two-stage residential location and transport mode choice model with exposure to traffic-induced air pollution

Air pollution is an increasing concern to urban residents. In response, residents are beginning to adapt their travel behaviour and to consider local air quality when choosing a home. We study implications of such behaviour for the morphology of cities and population exposure to traffic-induced air pollution. To do so, we propose a spatially explicit and integrated residential location and transport mode choice model for a city with traffic-induced air pollution. Intra-urban spatial patterns of population densities, transport mode choices, and resulting population exposure are analysed for urban settings of varying levels of health concern and air pollution information available to residents. Numerical analysis of the feedback between residential location choice and transport mode choice, and between residents' choices and the subsequent potential impact on their own health suggests that increased availability of information on spatially variable traffic-induced health concerns shifts population towards suburban areas with availability of public transport. Thus, health benefits result from reduced population densities close to urban centres in this context. To mitigate population exposure, our work highlights the need for spatially explicit information on peoples' air pollution concerns and, on this basis, spatially differentiated integrated land use and transport measures.

Measuring Traffic Induced Air Pollution in Onne Port’s Environment

Maritime shipping has been a major facilitator of economic prosperity throughout the world and it is likely to grow to meet continued and growing transport needs in both developed and developing countries. However, global emissions from maritime shipping have increased considerably, causing depletion of the ozone layer and most importantly posing threat to lives and coastal environment through air pollution. This study investigated the constituents of ambient air in Onne port’s environment in Rivers State of Nigeria. Six air pollutants (O3 CO, NO2, PM2.5, PM10, and SO2) were critically monitored with hand-held mobile Aeroqual gas monitors, series 500, at strategic locations within the port’s environment and Eleme Junction (the control). We found that mean concentrations (μg·m3) of the following pollutants: O3 (71.776 ± 0.726), CO, (19.145 ± 0.275) NO2 (28.145 ± 0.965) and SO2 (36.913 ± 0.378) were significantly high. The particulates (PM10, PM2.5) also showed higher mean concentrations of 48.400 ± 0.197 and 29.676 ± 0.352 respectively. The observed values were found to be significantly higher than those observed in the control group and also exceeded the safe permissible limits for gaseous pollutants when compared to the World Health Organization’s (WHO) standards. This exceedance raises questions on Nigeria’s commitments to implementations of (Annex VI) International Maritime Organization’s (IMO) Convention for the Prevention of Marine Pollution (MARPOL 73/78) from Ships. Again, the findings portend ecological hazards to residents, flora and fauna as elevated levels of these gaseous pollutants have been associated with chronic respiratory diseases. The policy implications of the findings were discussed.

Effect of traffic-induced air pollution on seed germination of Arizona Cypress (Cupressus arizonica Green) and Black Pine (Pinus nigra Arnold)

In this study, the effect of air pollution due to different traffic congestion of intersections and distance from intersection center on seed germination characteristics of Cupressus arizonica and Pinus nigra were studied in Urmia, Iran. At first, all intersections were classified into three classes of low, moderate and high traffic congestion using Urmia Traffic and Transport Organization report, and then 3 intersections were randomly selected from each class. Seed cones of C. arizonica and P. nigra that commonly planted in the boulevards leading to these intersections were collected at distances 0, 20, 40, 60, 80 and 100 m from the intersection center. The results showed that 1000 seed weight, germination rate (%), mean time to germination, Kotowski velocity coefficient, and maximum mean daily germination (peak value) of P. nigra seeds and only 1000 seed weight and seed germination rate (%) of C. arizonica significantly decreased with increasing traffic congestion. With increasing distance from intersection center, 1000 seed weight, seed germination rate (%) and mean time to germination of P. nigra in moderate traffic areas increased significantly. While, 1000 seed weight and seed germination rate (%) of C. arizonica in high and moderate traffic areas respectively followed the same circumstance. In general, both species were able to show the effect of air pollution as a bio-indicator, although, it seems that C. arizonica probably is more resistant to contaminants than P. nigra.

Mapping spatial distribution of traffic induced criteria pollutants and associated health risks using kriging interpolation tool in Delhi

The present study undertakes to understand the spatial influence of traffic-induced criteria air pollutants and associated health risks assessment at major transport corridors in Delhi. The study includes the classification of vehicular pollutants parameters into five different distribution categories, i.e., low, moderately low, moderate, moderately high, and high. Spatial distribution maps were developed using Geographic Information System (GIS) environment for eleven districts covering 36 transport corridors of the city. The study demonstrated the concentration of three out of the five ambient air pollutants, namely, NOx, PM10 and PM2.5, with highest values in the range of 294.10–362.57, 203.99–422.42 and 333.71–541.72 μg/m3, respectively. Corresponding National Ambient Air Quality Standards (NAAQS) values were found to be grossly violated as reflected by NOx, PM2.5 and PM10 concentrations with 2–5 times higher values. Remaining two (CO and SOx) were found to be under permissible limits, and most of them exhibited low levels of observed concentrations. The ambient air quality in south, central, east, and New Delhi areas were found to be in high and moderately high categories and necessitating adequate control measures. The study reported a total of 281107, 20791, 31636 expected cases of human exposure to respiratory mortality, cardiovascular mortality and total mortality, respectively whereas, 281107 and 71608 number of cases were reported in relation to respiratory morbidity in terms of COPD hospital admission and cardiovascular morbidity along the transport corridors. The outcome of the study may provide a basis for decision makers to formulate the policy as per the scale of impact of traffic induced air pollution in critical areas around the major transport corridors.

Traffic induced air pollution modeling: scenario analysis for air quality management in street canyon

Mathematical models are intensively used in environmental science for various reasons – status quo assessment, statistical modeling, forecasting, and planning, scenario analysis. Traffic flow and related atmospheric pollution modeling is one of the most complex challenges because of various aspects, - wide versa of affecting factors, daily, diurnal, weekly, monthly and yearly variability and non-stability of them. In the present study atmospheric model OSPM (Operational Street Pollution Model) is used to calculate NOx and PM10 concentration levels in the historical center (street canyon) of the city of Riga (Latvia) in order to make further assumptions (e.g., for the traffic load) for minimizing traffic induced air pollution in street canyons. In total five different scenarios were analyzed involving prioritizations of public transport, restrictions for old private cars or flow limitations in traffic jam situations during working days.

AHP-based Spatial Air Quality Impact Assessment Model of vehicular traffic change due to highway broadening in Sikkim Himalaya

ABSTRACTHighway traffic-induced air pollution is a major concern for health and ecosystem. The SAQIAM was developed to facilitate visualization and interpretation of geographic distribution of air pollution impacts due to highway broadening in East Sikkim. An analytic hierarchy process-based Spatial Air Quality Index (SAQI) was constructed for this purpose. The individual air pollutant maps of CO, NO2, SO2 and suspended particulate matter were prepared using IITLS dispersal model. Model validation and spatial crossvalidation criteria suggested that SAQIAM is a reliable spatial model. Statistical analysis of SAQI showed that it is a reliable index. SAQI maps under various time horizons showed that the pre-project and project-implementation scenarios will have mostly good air quality while post-project implementation scenario will have poor air quality close to the highway. Spatially explicit sensitivity analysis indicates that SAQIAM is robust. SAQIAM has the potential to serve as decision support tool for geovisualization of transport-related project impacts on air quality. Moreover, it can facilitate environmental managers to prioritize mitigation measures by capturing the perception of stakeholders using SAQI.Abbreviations: SAQIAM: Spatial Air Quality Impact Assessment Model; SAQI: Spatial Air Quality Index; EBK: Empirical Bayesian Kriging; IND-AQI: Indian Air Quality Index; AHP: Analytic Hierarchy Process; SESA: Spatially Explicit Sensitivity Analysis; OAT: One-At-a-Time; MACR: Mean Absolute Change Rate; ICCR: Impact Category Change Rate

Impacts of wind fields on the distribution patterns of traffic emitted particles in urban residential areas

Traffic emissions are a major contributor to urban atmospheric pollution. The wind fields also play an important role in the dispersion of air pollutants from the traffic emissions. However, the effects of different regional wind fields on the diffusion patterns of traffic-emitted fine particulate matter (PM2.5) in urban areas are still unclear and lack quantified measurements. To provide guidance to urban planning and design, as well as urban governance and management, it is especially important to identify the extent to which wind fields affect the diffusion of traffic-emitted particles. To understand the effect, field measurements and numerical simulations were conducted in this study. The field measurements mainly focused on collecting three-dimensional (3D) distributions of concentrations of traffic-emitted particles in a student dormitory zone at a university using instrumented unmanned aerial vehicles (UAVs). The collected PM2.5 measurements were used to verify and calibrate numerical models. Then, computational fluid dynamics (CFD) simulations were used to track the progress of pollutant dispersion and evaluate its relationship to urban forms. The effects of different wind directions (northwest and southeast) on the distribution and deposition of the traffic-emitted particles in the residential area were studied under different wind velocity conditions (1 m s−1, 5 m s−1 and 20 m s−1). As efficient observation platforms, the UAVs employed in the study allowed the capture of the 3D variations in the distributions of atmospheric pollutants in urban areas. The result provides a better understanding of the dispersion of atmospheric pollutants in a specific urban built environment under different wind fields, which can support urban governance and planning and design practice leading to effective mitigation of traffic-induced air pollution in urban areas.

Equilibrium and first-best city with endogenous exposure to local air pollution from traffic

Exposure to urban traffic-induced air pollution is a major health concern of cities. This paper analyzes the urban structure when localized pollution exposure arises from commuting traffic and investigates the feedback effect of endogenous pollution on residential choices. The presence of stronger traffic-induced air pollution exposure reduces the geographical extent and the population of cities. Land rents fall with distance from the city center while population densities may be non-monotonic. Cleaner vehicle technologies reduce pollution exposure everywhere, increase population and density everywhere and do not affect the spatial extent of the city. The paper compares the urban equilibrium with the first-best. The first-best structure is a less expanded city with higher densities at the center and lower densities at the fringe.

Autism Linked to Air Pollution In Preschool Children

Back to table of contents Previous article Next article Clinical & Research NewsFull AccessAutism Linked to Air Pollution In Preschool ChildrenJoan Arehart-TreichelJoan Arehart-TreichelSearch for more papers by this authorPublished Online:18 Jan 2013https://doi.org/10.1176/appi.pn.2013.1a3AbstractA pollution-based case-control study suggests that being exposed to high levels of traffic-induced air pollution, such as that emitted on freeways, might be a risk factor for autism.Could exposure to traffic-related air pollution contribute to autism? A study published online November 26, 2012, in Archives of General Psychiatry and funded by the National Institute of Environmental Health Sciences suggests so.Traffic-related air pollution has been shown to induce inflammation. Inflammation may be involved in some forms of autism, according to emerging evidence.Tyler Olson/ShutterstockTwo years ago, Heather Volk, Ph.D., an assistant professor of research at the University of Southern California, and her colleagues found a provocative association between living near a freeway and autism. This association implied that traffic air pollution might be a culprit in autism.They decided to conduct another study to test the hypothesis. The cohort included 279 preschool children with autism and 145 preschool children with typical development (controls). In addition to vehicle-emission rates, the researchers used local meteorological data, traffic volume, and road geometry to construct mathematical models of traffic-related air pollution in the areas where the subjects lived. The researchers then used the models as well as the addresses of the subjects to see whether they could find any links between traffic air pollution and autism.They could. The children residing in areas with the highest levels of traffic air pollution were three times more likely to have autism than were the children residing in areas with the lowest levels. Moreover, the children with autism were twice as likely as controls to have been exposed to high levels of traffic air pollution during their mothers’ pregnancy and three times as likely as controls to have been exposed to high levels of traffic air pollution during the first year of life. Some specific traffic air pollutants—nitrogen dioxide and particulate matter—were likewise associated with autism during pregnancy and the first year of life. Finally, the findings remained solid even when demographic and socioeconomic factors as well as maternal smoking during pregnancy were considered.“This study is a major contribution to the literature regarding factors potentially involved in the cause of autism,” Christopher McDougle, M.D., a professor of autism at Harvard Medical School, said during an interview. “While we know that genetic contributions exist, it is also clear that environmental factors are also important. To date, few environmental factors related to the cause of autism have been identified by rigorous scientific investigation.”There are also some possible routes whereby traffic air pollution could lead to autism, McDougle pointed out. “Previous research has shown that concentrations of particulate air pollutants, such as polycyclic aromatic hydrocarbons, can reduce the expression of genes, including the MET receptor tyrosine kinase gene, which is important in early life neurodevelopment and is markedly reduced in the brains of people with autism. Traffic-related air pollution has also been shown to induce inflammation after both short- and long-term exposure. Emerging evidence demonstrates that inflammation may also be involved in some forms of autism.”“We are currently studying whether genes involved in brain development and genes that help the body metabolize toxins interact with air pollution exposure to alter autism risk,” Volk told Psychiatric News. “We are also working to study whether there are particular time points when exposure may be important.” ■An abstract of “Traffic-Related Air Pollution, Particulate Matter, and Autism” is posted at http://archpsyc.jamanetwork.com/article.aspx?articleid=1393589#qundefined. ISSUES NewArchived

3D Visualization of Traffic-Induced Air Pollution Impacts of Urban Transport Schemes

AbstractThe negative impacts of urban traffic growth are well known, e.g., congestion, increased air pollution, and more traffic noise. Humans can readily see traffic congestion, and can hear traffic noise, but inevitably they are much less aware of odorless, invisible, silent air pollution. Therefore, quite naturally people, whether the general public or transport professionals, struggle to visualize air pollution from traffic, and will find it particularly difficult to visualize changes in air pollution levels resulting from changes in traffic conditions because of the implementation of various urban transport schemes. Hence, there is always a risk of the air quality impacts of potential urban transport schemes being underappreciated. Therefore, this paper contributes to the knowledge by devising a new three-dimensional (3D) visualization approach for modeled air quality before and after the implementation of potential urban transport schemes. Using the Dunkirk area of the City of Nottingham in the Unit...

Pollution attenuation by roadside greenbelt in and around urban areas

Greenbelts are effective tools for mitigation of traffic induced air and noise pollution. In this study, the potential role of greenbelts along the roadside for the reduction of air pollution and noise levels has been assessed by using seasonally monitored data in a megacity of Bangladesh. Correlation analysis was performed between the vegetation status, measured by canopy density and shelterbelt porosity, and the total suspended particles (TSP) removal percentage. Further, the reduction of noise level was also analyzed. The results showed that the greenbelts greatly contributed to reduce TSP pollution and it was as much as 65%. Noise level reduction was also achieved up to 17dB when compared to the open area. Moreover, TSP removal percentage was correlated to the crown density. Area having higher crown density demonstrated less air pollution and lower level of noise compared to the area having lower crown density. Greenbelt showed better performance in summer time than winter.

Green transportation planning and regional sustainable development within metropolitan regions: The role of traffic pollutant inventory in decision making

Increasingly, the Chinese metropolitan transportation organizations face many challenges ahead, as they try to meet the Nation's mobility requirements, decrease congestion impacts, and improve the level of air quality. However, the previous modeling tools (for example, land use, travel demand, and emission models) were not designed, nor do they generally provide visible feedback between adjacent procedures during the whole planning approach. Consequently, the preparation of a comprehensive database of traffic induced pollutant emissions in the form of an emission inventory is one of the basic tools for assessing the impact of regional development, population trends, and infrastructure improvements on air quality. The MOBILE 5 model is used to estimate emissions from both stationary and mobile motor vehicles, including: (1) identification of exhaust emission resource; (2) determination of emission index by vehicle type and size; (3) modeling the atmospheric pollutant diffuseness model across segment and intersection; (4) evaluation of traffic induced air pollution over network. The proposed approach is successfully applied to the Xi’an Metropolitan Area. The Base Case for the area generated emission estimators for hydrocarbons, particulate matter, carbon monoxide, and oxides of nitrogen. The modeled outputs provide a reasonable match for future strategies and policies in the study area, and successfully propose interventions to guide fuel consumption in planning schemes over the next five to ten years. Key words: Transportation planning, air quality, vehicle emission index, MOBILE 5, fuel consumption.

Evolution of Traffic Flows and Traffic-Induced Air Pollution Due to Structural Changes and Development during 1993-2006 in Tartu (Estonia)

Traffic is the main factor affecting air quality in most cities. After the Estonian re-independence in 1991, the increase of motorization has been fast and car usage has intensified. During the sam ...

CFD analysis on traffic-induced air pollutant dispersion under non-isothermal condition in a complex urban area in winter

There is a higher concentration of traffic-induced air pollution alongside roads in winter than in summer due to the relatively stable atmospheric conditions. In this study, a three-dimensional computational fluid dynamics (CFD) simulation coupled with radiation and conduction analysis was carried out to analyze the pollutant dispersion under non-isothermal conditions within an objective area in Kawasaki city, Japan, in winter. The temporal variations of wind speed and pollutant concentrations were analyzed at the pedestrian level (1.5 m above the ground level). The average wind velocity in the high-density building area is very low. The pollutant accumulates around the fencings on the road due to the weak winds and vortices around them. The surface and air temperature were also discussed. The results show a systematic variation of the differences from 9:00 to 17:00. Numerical predictions demonstrate reasonably good agreement with measurements. The concentration is a little lower under non-isothermal condition than under isothermal condition.