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Characterisation of nanoparticle emissions and exposure at traffic intersections through fast-response mobile and sequential measurements

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... Concentrations of traffic-related air pollutants are generally higher in TMEs than other areas because the direct emissions from mobile sources have not been widely dispersed (Berghmans et al., 2009;Colvile et al., 2001;Goel and Kumar, 2014;Patton et al., 2016). In high-traffic areas, congested traffic flow can have higher emissions due to frequent acceleration and deceleration of vehicles (Goel and Kumar, 2015). ...
... Air pollution exposures during cycling also depend on the route and traffic conditions, with higher exposures usually occurring in and near busy traffic and lower exposures in dedicated lanes farther from the main roads (CAFEH, 2015;Karanasiou et al., 2014;MacNaughton et al., 2014). Other factors that are common for most TMEs include traffic volume (Goel and Kumar, 2015;Rakowska et al., 2014) and the number of traffic signals (Karanasiou et al., 2014). For example, pedestrian and cyclist exposures to UFP and BC on high-traffic routes have been reported to be up to 60% higher compared with low-traffic routes (Kaur et al., 2005b;Strak et al., 2010). ...
... Personal exposure while driving in a car depends on the (front/ back) seat position (Chan and Chung, 2003) and personal behavior (Kaur et al., 2007;Weijers et al., 2004), such as whether the air conditioner is on or air vents and/or windows are open (Fruin et al., 2008;Hudda et al., 2012;Jiao and Frey, 2013;Kumar and Goel, 2016;Patton et al., 2016), the speed of the vehicle (Hudda et al., 2012;Karanasiou et al., 2014) and the distance maintained from preceding vehicles Sabin et al., 2004). In-cabin exposures in a vehicle when windows are closed also depend on whether fresh intake air or recirculated cabin air are used with the heating, ventilating, and air conditioning (HVAC) system (Goel and Kumar, 2015;Jiao and Frey, 2013;Joodatnia et al., 2013a). ...
Article
The World Health Organization estimates 3.7 million deaths in 2012 in low- and middle-income Asian countries due to outdoor air pollution. However, these estimates do not account for the higher exposures of specific particulate matter (PM) components – including fine particles (PM⁠2.5), ultrafine particles (UFP) and black carbon (BC) – typical of transport microenvironments (TMEs). With the rapidly growing number of on-road vehicles in Asia, human exposure to PM is an increasing concern. The aim of this review article is to comprehensively assess the PM⁠2.5, UFP, and BC related studies in Asian TMEs to understand the extent of exposure, the underlying factors leading to such exposure, and how Asian exposures compare to those found in Europe and the United States of America (USA). Pollutants considered and their health impacts are identified, along with the key factors that influence personal exposure in TMEs. We also characterised the human exposure to PM⁠2.5, UFP, and BC in TMEs (walk, cycle, car, and bus) in cities of Asia, Europe, and the USA. Instrumentation and measurement methods, exposure modeling techniques, and regulation are reviewed for PM⁠2.5, UFP, and BC. Relatively few studies have been carried out in urban Asian TMEs (i.e., walk, cycle, car, and bus) where PM⁠2.5, UFP, and BC had generally higher concentrations compared to Europe and USA. Based on available data, PM⁠2.5 concentrations while walking were 1.6 and 1.2 times higher in Asia (average 42μgm⁠−3) compared to Europe (26μgm⁠−3) and the USA (35μgm⁠−3), respectively. Likewise, average PM⁠2.5 concentrations in car (74μgm⁠−3) and bus (76μgm⁠−3) modes in Asia were approximately two to three times higher than in Europe and the USA. UFP exposures in Asia were twice as high for pedestrians and up to ∼9-times as high in cars than in Europe or the USA. Asian pedestrians were exposed to ∼7-times higher BC concentrations compared with pedestrians in the USA. Stochastic population-based models have yet to be applied widely in Asia but can be used to quantify inter-individual and inter-regional variability in exposures and to assess the contribution of TMEs to total exposures for multiple pollutants. The review also highlights specific gaps in the data set that need to be filled by future research as UFP and BC studies were rare as were studies of pedestrian and cyclist exposure in Asian TMEs.
... 6,[25][26][27][28] For instance, as little as 2% of commuting time spent in the car at traffic intersections can contribute as high as~25% of total commuting exposure in certain situations. 10 Active transport (cycling and walking) is beneficial to health due to increased physical activity. However, it is also associated with increased inhalation rate due to physical activity, which increases RDD. ...
... 33,34 Nonetheless, contemporary studies have found that the health benefits of walking and cycling outweigh the negative consequences and, hence, should be encouraged. 35 A number of studies have assessed the air pollution exposure of urban dwellers under different transport microenvironments (TMEs) such as cars, 10,36,37 buses, 38,39 trains 40-42 and cycles. 43,44 Particles of different sizes originate from different sources. ...
... The ratio of in-cabin to ambient particles is a function of whether windows are open, and, if windows are closed, whether air is recirculated or there is fresh air intake from the heating, ventilation, and air conditioning (HVAC) system. 10,46 The lowest concentrations in the car with respect to the rest of modes could be explained by the hindered entrance of outdoor sourced pollutants to the cabin owing to the closed windows. Therefore, infiltration of outdoor particles was expected to be low. ...
Article
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Commuting exposure: consider respiratory deposition doses, not just concentrations People using environmental-friendly commuting methods such as bicycle and walk are more at risk of pollution than those in cars. Researchers from the University of Surrey, UK, and North Carolina State University, USA, measured personal exposure levels of particulate matter (PM) in four transport modes (bus, car, cycle and walk) during peak and off-peak hours in a typical UK town, Guildford. Submicron (PM1) and fine particle (PM2.5) concentrations were usually high in the car while lowest for cyclists. The respiratory deposition doses for fine particles were comparable for walk and cycle, followed by bus and car. The management of commuting exposures should consider potential dose and not just exposure concentration. Opportunities such an increased distance between the heavily trafficked roadways and pedestrians/cyclists should be considered in urban planning to reduce potential doses.
... Chapter 4 presents the results from mobile measurements for PNCs inside the car cabin in five different ventilation settings. The work performed in this chapter is covered in Goel and Kumar (2015a). ...
... Chapter 8 presents the exposure estimation of nanoparticles and particulate matter at TIs. RDD rate is estimated for on-road, incabin and pedestrian exposure at TIs using the data collected during mobile and fixed-site measurements. The work performed in this chapter is covered in Goel and Kumar (2015a) and Goel and Kumar (2016a,b). Chapter 9 presents other results of dispersion modeling exercise using freely available models of air quality at TIs. ...
... The RDD rate can be estimated by using algebraic and semi-empirical deposition models. The deposition fraction model of the International Commission on Radiological Protection (ICRP, 1994) is a commonly accepted approach, which is applied here and also adopted by Goel and Kumar (2015a) and Azarmi and Kumar (2016). ...
Thesis
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Road vehicles are a major source of airborne nanoparticles (<100 nm) and particulate matter (PM), including PM10 (≤10 μm), PM2.5 (≤2.5 μm) and PM1 (≤1 μm) emissions. Over 99% of particles, by number, are reprsented by particles below 300 nm in diameter in polluted urban environments. The small size of particles in the nano-size range enables them to enter deeper into the lungs, causing both acute and chronic adverse health effects such as asthma, cardiovascular and ischemic heart diseases. The issue of air pollution becomes more prominent at urban traffic hot-spots such as traffic intersections (TIs), where pollution pockets are created due to frequently changing driving conditions. Recent trends suggest an exponential increase in travel demand and travelling time in the UK and elsewhere over the years, which indicate a growing need for the accurate characterisation of exposure at TIs since exposure at these hot-spots can contribute disproportionately high to overall commuting exposure. Based on field observations, this thesis aims (i) to investigate the traffic driving conditions in which TIs become a hotspot for nanoparticles and PM, (ii) to estimate the extent of road that is affected by high particle number concentrations (PNCs) and PM due to presence of a signal, (iii) to assess the vertical and horizontal variations in PNC and PMC at different TIs, (iv) to estimate the associated in-cabin and pedestrian exposure at TIs, and finally (v) to predict PNCs by using freely available models of air pollution at TIs. For this thesis, two sets of experiments (i.e. mobile- and fixed-sites) were carried out to measure airborne nanoparticles and PM in the size range of (0.005-10 μm) using a fast response differential mobility spectrometer (DMS50) and a GRIMM particle spectrometer (1.107 E). Mobile measurements were made on a circle passing through 10 TIs and fixed-site measurements were carried out at two different types of TIs (i.e. 3- and 4-way). Dispersion modelling was then performed by using California Line Source (CALINE4) and California Line Source for Queueing and Hotspot Calculations (CAL3QHC) at TIs. Several important findings were then extrapolated during the analysis. These findings indicated that congested TIs were found to become hot-spots when vehicle accelerate from idling conditions. The average length of road in longitudinal direction that is affected by high PNCs and PM was found to be highest (148 m; 89 to –59 m from the center of a TI) at a 3-way TI with built up area and lowest at 4-way TI with built-up area (79 m; 46 to –33 m). Vertical PNCs, horizontal PNCs and PM profiles followed an exponential decay. Exponential decay of PNCs in the vertical direction was much sharper at the 4-way TI than at the 3-way TI. Based on tracer gas method, particle number emission factors (PNEFs) during congested and free flow driving conditions were also estimated. The results showed that the PNEF during congested conditions can be up to 9 times higher than those during free flow conditions at a TI. In-cabin and pedestrian exposure during delay conditions was up to 7 and 7.3 times higher than exposure during free flow conditions at TIs. The modelling exercise showed that model choice to predict PNCs depends on the type of TI, size range of particles, receptor height and distance from the TI. Key findings of the proposed study could assist in validating and refining the capabilities of existing models for exposure assessment to PNCs at TIs. The proposed study will assist to enhance the scientific understanding of the problem as well as develop a database, showing the contribution of exposure at TIs towards the overall daily exposure during commuting in diverse city environments.
... Traditionally, exposure to air pollutants has been assessed through fixed-site air quality monitoring stations measuring at the background or traffic hotspots (Goel and Kumar 2014), but these stations might not be representative of the actual air pollution exposure Steinle et al., 2013). This is particularly true during commuting since this activity results in an increased exposure when compared to other daily activities and is characterised by a high exposure to time ratio (Buonanno et al., 2013a;Dons et al., 2011;Rivas et al., 2016Rivas et al., , 2017, especially in high vehicle density areas (Goel and Kumar 2015a). The reasons for this intense exposure is the proximity to the source (with levels of most air pollutants being particularly high along the busy roads) and the peak concentrations being usually observed during the peak traffic hours (Al-Dabbous and Kumar 2014; Kaur et al., 2005;Morawska et al., 2008;Rivas et al., 2016;Zhu et al., 2002). ...
... The DF varies according to the particle diameter and hence is usually not directly proportional to the mass concentration. The RDD is estimated according to Eq. (1), which is adapted from ICRP (1994) and has been used extensively in the literature (Azarmi and Kumar 2016;Goel and Kumar 2015a). ...
... Therefore, concentrations of both coarse and fine particles were slightly higher at the TIs compared with the rest of the route (Fig. 4). These higher concentrations can be explained due to abrupt changes in driving conditions (e.g., braking, acceleration/deceleration), temporary accumulation of vehicles (Kim et al., 2013;Kumar and Goel, 2016) and an increase in fuel consumption due to the acceleration of vehicles (Goel and Kumar 2015a). ...
... Because traffic-related pollutants are highly spatially heterogeneous in urban areas, individual exposures can depend strongly on relatively short stays in highly polluted micro-environments. For example, Goel and Kumar (2015a) estimated that drivers spend only 2% of their commuting time around intersections, but this short term exposure contributed~25% of the total respiratory doses during their commutes by car due to elevated UFP concentrations around the intersections. Here, we focus on exposures of transit users (people who commute by public or private bus or light rail), waiting at stops on streets used by cars, trucks and busses. ...
... The mean peak [UFP] around the intersections ranged 2.0 Â 10 4 to 3.9 Â 10 4 cm À3 and 1.4 Â 10 4 to 5.2 Â 10 4 cm À3 for six sites, in the morning and afternoon, respectively (Table 3). These values are comparable with the results of the previous intersection studies in the U.S. (3.4 Â 10 4 cm À3 in North Carolina (Holder et al., 2014) and 6.6 Â 10 4 cm À3 in Texas (Wang et al., 2008)) but somewhat lower compared to those in the U.K. (2.3 Â 10 5 cm À3 ) (Goel and Kumar, 2015a). However, because the measurements were conducted in different built-, traffic-, and meteorological environments and used different study designs, the direct comparison is less useful. ...
... However, because the measurements were conducted in different built-, traffic-, and meteorological environments and used different study designs, the direct comparison is less useful. For example, Goel and Kumar (2015a) drove in the busiest lane of the roads, whereas we drove in the outermost lanes adjacent to the sidewalks. ...
Article
Epidemiological studies have shown that exposure to traffic-related pollutants increases incidence of adverse health outcomes. Transit users in cities across the globe commonly spend 15-45 min or more waiting at transit stops each day, often at locations with high levels of pollution from traffic. Here, we investigate the characteristics of concentration profiles of ultrafine particles (UFP) with 5 m spatial resolution across intersections, to determine the best place to site transit stops to minimize exposures. Cross-intersection UFP profiles were derived from 1744 profiles covering 90 m before and after each intersection center with a mobile monitoring platform. Measurements were made at 10 signalized intersections located at six urban sites, each with a distinct built environment, during both mornings and afternoons. Measurements were made within 1.5 m of the sidewalk and approximately at breathing height (1.5 m above ground level) to approximate sidewalk exposures. UFP profiles were strongly influenced by high emissions from vehicle stops and accelerations, and peaked within 30 m of intersection centers; from there concentrations decreased sharply with distance. Peak concentrations averaged about 90% higher than the minima along the block. They were accompanied by more frequent and larger transient concentration spikes, increasing the chance of people near the intersection being exposed to both short-term extremely high concentration spikes and higher average concentrations. The decays are somewhat larger before the intersection than after the intersection, however as siting transit stops after intersections is preferred for smooth traffic flow, we focus on after the intersection. Simple time-duration exposure calculations combined with breathing rates suggest moving a bus stop from 20 to 40-50 m after the intersection can reduce transit-users' exposure levels to total UFP substantially, in proportion to the reciprocal of the magnitude of elevation at the intersection.
... Literature on the determinants of exposure to invehicle particle concentrations has been growing (Garramone 2013; Goel and Kumar 2015;Joodatnia, Kumar, and Robins 2013a;Kaur and Nieuwenhuijsen 2009;Qiu et al. 2017a;Rivas et al. 2017). These studies have shown that switching on the internal recirculation can reduce exposure concentrations in the passenger cabin. ...
... But under delay conditionsi.e., elevated road 1on-road PNC changed significantly, decreasing gradually during the queuing process and increasing rapidly at the time of acceleration. This result was consistent with the conclusion in Goel and Kumar (2015): that sudden acceleration in the speed of vehicles could result in the sudden emission of a large amount of particles. Within the dashed circles, the on-road PN concentration rapidly increased, coinciding with an event in the experimental record: the test vehicle was passed by a dieselfueled car. ...
Article
Full-text available
Road environments significantly affect in cabin concentration of particulate matter (PM). This study conducted measurements of in-vehicle and on-road concentrations of PM10, PM2.5, PM1, and particle number (PN) in size of 0.02-1 µm, under six ventilation settings in different urban road environments (tunnels, surface roads and elevated roads). Linear regression was then used to analyze the contributions of multiple predictor variables (including on-road concentrations, temperature, relative humidity, time of day, and ventilation settings) to measured variations. On-road measurements of PM2.5, PM1, and PN concentrations from the open surface roads were 5.5%, 3.7%, and 16% lower, respectively, than those measured in tunnels, but 7.6%, 7.1% and 24% higher, respectively, than those on elevated roads. The highest on-road PM10 concentration was observed on surface roads. The time series pattern of in-vehicle particle concentrations closely tracked the on-road concentrations outside of the car and exhibited a smoother profile. Irrespective of road environment, the average I/O ratio of particles was found to be the lowest when air conditioning was on with internal recirculation, the highest purification efficiency via ventilation was obtained by switching on external air recirculation and air conditioning. Statistical models showed that on-road concentration, temperature, and ventilation setting are common factors of significance that explained 58%-80%, 64%-97%, and 87%-98% of the variations in in-vehicle PM concentrations on surface roads, on elevated roads, and in tunnels, respectively.
... Most of the official institutions and government bodies use traditional environmental monitoring equipment. Although they are accurate and precise, the number of such monitoring units is sparse (Kumar et al., 2015). To get more fine-grained environmental information, a citizen science approach is being followed, which involves using low-cost sensors for community engaged environmental monitoring. ...
... The air quality quiz questions were designed in a way so that it can engage people irrespective of their digital literacy or technical knowledge about air pollution ( Table 2). The questions were primarily based on both the generic understanding of air pollution and the outcome of our research focusing on local study area, covering topics such as exposure at intersection (Goel and Kumar, 2015), exposure mitigation via green infrastructure along roadsides (Abhijith and Kumar, 2019;Abhijith et al., 2017), exposure to air pollutants during commuting (Rivas et al., 2017;Kumar et al., 2018) and pedestrian exposure to airborne particles and effect of roadside vegetation (Al-Dabbous and Abhijith and Kumar, 2019). They were simplified to the level where people could easily read and understand. ...
... Traffi c intersections (TIs) are usually characterized by higher particle concentrations. Such locations are generally considered as pollution hotspots (Goel and Kumar 2015). ...
... The percentage fractions of such particles were also higher during the morning and afternoon rush hours than at night. As already presented in the literature (Joodatnia et al. 2013, Goel andKumar 2015) this is obviously due to a greater number of vehicles and the related higher concentration of freshly emitted nucleation mode particles (size range 5-30 nm). Table 4 presents the estimated doses of the considered particles deposited in the respiratory tract of commuters and pedestrians after spending one hour on the considered route in peak and off-peak traffi c times. ...
Article
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Extensive aerosol particle concentrations are one of the factors contributing to poor air quality in cities. The aim of this study is to assess particle number and mass concentrations on a road in Lublin, Poland, in peak and off-peak traffic hours and its impact on the particle exposure for commuters and pedestrians. Mobile monitoring and fixed-site measurements on the sidewalk along the established 2.1 km long route were conducted with the use of Mobile Air Pollution Analytic Laboratory equipped, among other things, with instruments measuring the real-time number and mass concentrations of particles with size range from 10 nm to 32 μm. The highest average concentrations of ultrafine particle number PN0.1 (25.4 ±11×10³ pt/cm³; mean ± standard deviation), total particle number PN (29.2 ±12×10³ pt/cm³) as well as mass concentrations of PM2.5 (29.1 ±7.6 μg/m³) and PM10 (45.4 ±10.3 μg/m³) were obtained in peak traffic hours for the part of the route with the most intensive traffic. The average particle number concentrations for the entire route and the part of route with the most intensive traffic in peak times were found to be about 3 to 4 times higher than in off-peak times. The average particle mass concentrations were about twice as high. Furthermore, the average values of the examined particle number and mass concentrations were higher for the on-road measurements than for fixed-site measurements. Moreover, a greater percentage of ultrafine particles was observed during mobile monitoring than in the fixed-site measurement points. It was established that a greater number and mass of particles, irrespectively of their size range, is deposited in the respiratory tract of commuters and pedestrians in peak hours than in off-peak hours. In peak times the average particle doses received by commuters and pedestrians equaled 4.8 ±2.4×10⁹ pt/h or 29.6 ±10.7 μg/h (PM10) and 4.2 ±2.3×10⁹ pt/h or 29.6 ±8.6 μg/h (PM10), respectively. Additionally, in both peak and off-peak hours greater particle doses were determined in the considered part of the route with the most intensive traffic; however, in off-peak traffic times pedestrians are more exposed to traffic-related pollutants than commuters. Overall, the obtained results reflect the importance of traffic-related particle emission measurements for exposure evaluations and the need of taking the actions aimed at decreasing it.
... Although both transport modes circulate in close proximity to the exhaust of other vehicles, the buses run on dedicated lanes being less prone to traffic jam impacts. Additionally, traffic congestions have been shown to rise driver's exposure to airborne pollutants up to 29 times, compared to fluid traffic flow ( Goel and Kumar, 2015 ). ...
... Considering that braking events have a significant impact on the amount of material lost, the highest concentrations of brake and tyre wear particles should be observed near busy intersec-tions, traffic lights, pedestrian crossings, corners and bus stops (e.g. Goel and Kumar, 2015 ;Limo et al., 2018 ). Several key factors need to be assessed when investigating wear particles toxicity and their potential harmful health effects, namely their size distribution, agglomeration state, chemical composition, surface area, chemistry and surface charge ( Grigoratos and Martini, 2015 and references therein). ...
Article
Traffic is a main source of air pollutants in urban areas and consequently daily peak exposures tend to occur during commuting. Personal exposure to particulate matter (PM) was monitored while cycling and travelling by bus, car and metro along an assigned route in Lisbon (Portugal), focusing on PM2.5 and PM10 (PM with aerodynamic diameter <2.5 and 10 µm, respectively) mass concentrations and their chemical composition. In vehicles, the indoor-outdoor interplay was also evaluated. The PM2.5 mean concentrations were 28 ± 5, 31 ± 9, 34 ± 9 and 38 ± 21 µg/m³ for bus, bicycle, car and metro modes, respectively. Black carbon concentrations when travelling by car were 1.4 to 2.0 times higher than in the other transport modes due to the closer proximity to exhaust emissions. There are marked differences in PM chemical composition depending on transport mode. In particular, Fe was the most abundant component of metro PM, derived from abrasion of rail-wheel-brake interfaces. Enhanced concentrations of Zn and Cu in cars and buses were related with brake and tyre wear particles, which can penetrate into the vehicles. In the motorised transport modes, Fe, Zn, Cu, Ni and K were correlated, evidencing their common traffic-related source. On average, the highest inhaled dose of PM2.5 was observed while cycling (55 µg), and the lowest in car travels (17 µg). Cyclists inhaled higher doses of PM2.5 due to both higher inhalation rates and longer journey times, with a clear enrichment in mineral elements. The presented results evidence the importance of considering the transport mode in exposure assessment studies.
... Furthermore, a considerably high mass fraction of fine particles (PM 2.5 /PM 10 ≈ 0.90) was reported for windows-closed cars, with air conditioning and air intake from outside, when compared with bus, cycling and walking (Kumar et al., 2018b). Traffic intersections expose car commuters tõ 25% of the total commuting exposure despite spending only 2% of commuting time at signalised traffic intersections (Goel and Kumar, 2015). There are several factors that affect variability in commuters' pollutant exposure, including travel times and days (i.e. ...
... It may also allow car commuters to avoid hotspots during trips by choosing alternative route sections or turning on the recirculation to decrease incar exposure. Previous work has reported that time spent at hotspots around traffic intersections can represent as little as 2% of total commuting time and yet account for up to one-fourth of total exposure doses (Goel and Kumar, 2015). The above observations reinforce these findings (i.e. ...
Article
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Cars are a commuting lifeline worldwide, despite contributing significantly to air pollution. This is the first global assessment on air pollution exposure in cars across ten cities: Dhaka (Bangladesh); Chennai (India); Guangzhou (China); Medellín (Colombia); São Paulo (Brazil); Cairo (Egypt); Sulaymaniyah (Iraq); Addis Ababa (Ethiopia); Blantyre (Malawi); and Dar-es-Salaam (Tanzania). Portable laser particle counters were used to develop a proxy of car-user exposure profiles and analyse the factors affecting particulate matter ≤2.5 μm (PM2.5; fine fraction) and ≤10 μm (PM2.5–10; coarse fraction). Measurements were carried out during morning, off- and evening-peak hours under windows-open and windows-closed (fan-on and recirculation) conditions on predefined routes. For all cities, PM2.5 and PM10 concentrations were highest during windows-open, followed by fan-on and recirculation. Compared with recirculation, PM2.5 and PM10 were higher by up to 589% (Blantyre) and 1020% (São Paulo), during windows-open and higher by up to 385% (São Paulo) and 390% (São Paulo) during fan-on, respectively. Coarse particles dominated the PM fraction during windows-open while fine particles dominated during fan-on and recirculation, indicating filter effectiveness in removing coarse particles and a need for filters that limit the ingress of fine particles. Spatial variation analysis during windows-open showed that pollution hotspots make up to a third of the total route-length. PM2.5 exposure for windows-open during off-peak hours was 91% and 40% less than morning and evening peak hours, respectively. Across cities, determinants of relatively high personal exposure doses included lower car speeds, temporally longer journeys, and higher in-car concentrations. It was also concluded that car-users in the least affluent cities experienced disproportionately higher in-car PM2.5 exposures. Cities were classified into three groups according to low, intermediate and high levels of PM exposure to car commuters, allowing to draw similarities and highlight best practices.
... One further aim is to produce results for further analyses as for example the prediction of traffic situations or the estimation of caused exposures by the vehicles. The latter might be connected with the impact on health effects caused by traffic congestion 5 (Goel and Kumar 2015). ...
... Understanding traffic, traffic congestion appearance, and propagation in time and space is a task that has high importance for future generations. Besides tremendous emissions caused by traffic (Goel and Kumar 2015) in air 7 , land and water, there is a gigantic loss of time and money every day in the world, due to vehicle traffic congestion (Rao and Rao 2012). In general, traffic data acquisition is feasible with static and mobile sensors. ...
Thesis
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Vehicle traffic in urban environments consists of a variation of traffic phenomena. Defining and measuring these traffic phenomena is challenging, since traffic sensors can still not observe the traffic situation of one city entirely over a period of time. One possibility to get general overviews is analyzing data coming from tracked vehicle movements. In the best cases, tracked vehicles are numerous and part of vehicle fleets that represent a big proportion of traffic participants in the investigation area. Traffic data in the form of movement trajectories is producible via the Floating Car Data (FCD) technology, which uses mobile devices that allow positioning and recording on-board information in every tracked vehicle. In case of operating taxis, these devices are part of already installed dispatcher systems and are able to produce Floating Taxi Data (FTD). One type of applications with FCD and FTD consists of inferring traffic situations with numerous different computational techniques. This thesis introduces a traffic pattern analysis framework for FCD with the emphasis on detecting specific vehicle traffic patterns. The extracted patterns should define urban traffic congestion as the detectable traffic phenomenon, which is the focus of this work. In general, tracking numerous moving entities participating in traffic is part of a large body of ongoing research. By reviewing traditional traffic data acquisition techniques from different domains, this work aims to provide a connection to various research disciplines connected with research on moving objects. Those fields are coming from physics, computer science, GIScience and geography to mention a few. In contrast to traffic phenomena on highways, which are well studied, this work focus on urban traffic in highly populated cities with dense transportation infrastructure. By selecting, modifying, and applying various methodological aspects, this work shows the establishment of a traffic pattern analysis framework that allows extracting typical periodical and unusual traffic patterns for each day of the week. Traffic congestion can be seen as a daily event, since it has starting and end points, that occurs on specific rush hours of the day, but as well as traffic anomalies that are caused by different events in the urban environment. The distinguishing between different types of traffic congestion events is challenging, especially when relying on classified movement patterns from FCD, which is only a fraction of all traffic participants. The first step is to clarify the various terminologies and to associate them with respective formalizations of each appearance, as the terms road capacity and traffic bottlenecks. Additionally, there are different aspects of traffic congestion detection, which includes reasoning on FCD representations, preprocessing and analytical possibilities. The last mentioned include map matching on road segments and density-based clustering of vehicle movement. Preceding steps of the framework consist of adjusted preprocessing of the data. The following six framework techniques aim to reveal specific traffic patterns from the preprocessed FCD by different forms of representing urban traffic congestion events. The underlying computational methods of the framework enable the possibility to apply various computations as a sequence that reveal an increasing number of details on urban traffic congestion events. The results of the framework computations include mainly three different products that are subsequently inferable: congestion polygons, congestion propagation polylines (CPP) and bundles of associated road segments. The affected road segments result from previous matching between road segments and congestion polygons, or congestion propagation polylines. The evaluation of the framework outcomes consists of visual analysis methods. A test FTD set from taxis in Shanghai from 2007 serves for the framework evaluation. The results show selected parts of the urban investigation area influenced by recurrent and non-recurrent traffic congestion, which conclude to expected travel time variations during rush hours. Afterwards, the test results serve for extensive discussions on the usefulness and reasonability of the framework methods. A concluding outlook outlines ideas on future work, which mainly consists of proposed methodical extensions and finding suitable applications for the traffic pattern analysis framework.
... Recent studies have shown that UFP concentrations may be larger inside the cabin than outside (Goel and Kumar [1]). Decreasing the infiltration rates and thus exposure of car passenger during commuting time is then a major goal. ...
... Characterizing the interactions between particles and the surrounding flow (wake flow) would be an asset to improve our knowledge on the particle dynamics and their ability to infiltrate the car cabin. Although numerical studies and on road measurements are quite numerous (Goel and Kumar [1], Kumar et al. [2]), our interest is focused on experimental investigations of UFP distribution in the wake of a reduced scale model in wind tunnel. To achieve this goal, a first step is to provide an accurate description of the flow dynamics downstream of a car. ...
Conference Paper
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Wind tunnel investigations have been conducted in the wake of three simplified car models, commonly called Ahmed body, with 0 • , 25 • and 35 • rear slant angle respectively. The upstream velocity is 14.3m/s, leading to a Reynolds number based on the model height of 4.95 × 10 4. Velocity measurements have been recorded with a Laser Doppler Velocimetry system. An innovative data treatment method has been developed to obtain accurate and reliable flow statistics regardless the seeding conditions. Wake flow properties such as the recirculation length, turbulence intensity or turbulent kinetic energy are similar to results found in the literature. Further works will consist in measuring the nanoparticle concentration fields in the wake of the same models, in order to better understand the particle dynamics and especially the interaction between turbulent vortical structures and particles. The final goal of the project is to identify key parameters that influence particle path and possible infiltration in the following vehicle through air entrances.
... Ordinary Least Squares estimates in the odd-numbered columns, with standard errors calculated by bootstrapping (200 samples each): (i) the consumer-level fuel choice data, to account for sampling variation in the predicted gasoline share in a first-step consumer demand model, and (ii) the pollutant-meterology-traffic data in the second-step particle regression, clustering by date. Two-Stage Least Squares estimates in the even-numbered columns, with the median ethanol-to-gasoline price ratio across pumping stations instrumenting for the predicted gasoline share in the particle regression equation roadside or on-road location, suggesting that the absolute changes in particle number concentrations that coincide with the fuel shifts may be different if they were to be measured near road traffic or at the vehicle exhaust 51,52 . The site has been described as "ideal for tracking ambient aerosols" and "representative of the ambient pollution burden of the city," due to the well-mixed air masses arriving at the location and limited influence of local sources 50 . ...
Article
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Despite ethanol’s penetration into urban transportation, observational evidence quantifying the consequence for the atmospheric particulate burden during actual, not hypothetical, fuel-fleet shifts, has been lacking. Here we analyze aerosol, meteorological, traffic, and consumer behavior data and find, empirically, that ambient number concentrations of 7–100-nm diameter particles rise by one-third during the morning commute when higher ethanol prices induce 2 million drivers in the real-world megacity of São Paulo to substitute to gasoline use (95% confidence intervals: +4,154 to +13,272 cm⁻³). Similarly, concentrations fall when consumers return to ethanol. Changes in larger particle concentrations, including US-regulated PM2.5, are statistically indistinguishable from zero. The prospect of increased biofuel use and mounting evidence on ultrafines’ health effects make our result acutely policy relevant, to be weighed against possible ozone increases. The finding motivates further studies in real-world environments. We innovate in using econometrics to quantify a key source of urban ultrafine particles.
... In contrast, the levels at S3 and S6 were significantly lower than at the other four sites (p b 0.01). The highest outdoor concentrations at S1 could be explained by a strong influence of vehicle emissions from a busy street with traffic light intersection; it has been reported that under such stop and start conditions PN concentrations are the highest, and several times exceed the concentrations under traffic free-flowing conditions (Goel and Kumar, 2015). While S2 is next to S1, it is positioned at leeward side of the building with regard to the street (Fig. S1a) and therefore is less affected by emissions from the traffic. ...
Article
No studies have been conducted in Vietnam to understand the levels of atmospheric ultrafine particles, despite having adverse health effects. Information about indoor air quality in Vietnam is also limited. Hence we aimed to conduct the first assessment of ultrafine particle concentrations in terms of particle number (PN) in Hanoi, by simultaneously measuring indoor and outdoor PN concentrations from six households at different locations across the city in January 2016. We also acquired PM2.5 data for this monitoring period from an air quality monitoring station located at the US Embassy in Hanoi, to compare the general trends between PN and PM2.5 concentrations. The mean daily indoor and outdoor PN concentrations for the monitoring period were 1.9 × 10⁴ p/cm³ and 3.3 × 10⁴ p/cm³, respectively, with an increase during rush hour traffic. It was concluded that traffic was the main contributor to outdoor PN concentrations, with agricultural burning having a small influence at one study location. The mean ratio of indoor to outdoor PN concentrations for all six sites was 0.66 ± 0.26, which points to outdoor air as the main driver of indoor PN concentrations, rather than indoor sources. These PN concentrations and I/O ratios are similar to those reported for a number of cities in developed countries. However, in contrast to PN, ambient mean PM2.5 concentrations in Hanoi (60–70 μg/m³) were significantly higher than those typically recorded in developed countries. These findings demonstrate that urban particle mass (PM2.5) concentrations are not indicative of the PN concentrations, which can be explained by different sources contributing to PN and PM, and that direct measurements of PN are necessary to provide information about population exposure to ultrafine particles and for management of air quality.
... There was a need for improvements in after-treatment technologies to reduce pollutant emissions, as could be the case for LDVs and HDVs in the MASP (the vehicles are currently newer and the situation has changed, even after increases in the use of ethanol and biodiesel in the fuel blends). Goel and Kumar (2015), evaluated the influence of nanoparticle emissions due to traffic conditions and the population exposure at traffic intersections. ...
Article
We present a comprehensive review of published results from the last 30 years regarding the sources and atmospheric characteristics of particles and ozone in the Metropolitan Area of São Paulo (MASP). During the last 30 years, many efforts have been made to describe the emissions sources and to analyse the primary and secondary formation of pollutants under a process of increasing urbanisation in the metropolitan area. From the occurrence of frequent violations of air quality standards in the 1970s and 1980s (due to the uncontrolled air pollution sources) to a substantial decrease in the concentrations of the primary pollutants, many regulations have been imposed and enforced, although those concentrations do not yet conform to the World Health Organization guidelines. The greatest challenge currently faced by the São Paulo State Environmental Protection Agency and the local community is controlling secondary pollutants such as ozone and fine particles. Understanding the formation of these secondary pollutants, by experimental or modelling approaches, requires the description of the atmospheric chemical processes driven by biofuel, ethanol and biodiesel emissions. Exposure to air pollution is the cause of many injuries to human health, according to many studies performed not only in the region but also worldwide, and affects susceptible populations such as children and the elderly. The MASP is the biggest megacity in the Southern Hemisphere, and its specifics are important for other urban areas that are facing the challenge of intensive growth that puts pressure on natural resources and worsens the living conditions in urban areas. This text discusses how imposing regulations on air quality and emission sources, mainly related to the transportation sector, has affected the evolution of pollutant concentrations in the MASP.
... Further, the exposure during commuting is highly affected by individual mode of transport. Comparison among studies is challenging owing to variability in the methods used for sampling and different conditions in each transport mode (such as ventilation rates and fuel type; Goel and Kumar, 2015a;Karanasiou et al., 2014;Kaur et al., 2007). Moreno et al. (2015aMoreno et al. ( , 2015b reported the following hierarchy for PNC in different transport microenvironments with data from various studies: urban background b underground b tram b walking in a suburban main road b walking and cycling in the city centre b bus. ...
Article
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People with low-income often experience higher exposures to air pollutants. We compared the exposure to particulate matter (PM1, PM2.5 and PM10), Black Carbon (BC) and ultrafine particles (PNC; 0.02-1 µm) for typical commutes by car, bus and underground from 4 London areas with different levels of income deprivation (G1 to G4, from most to least deprived). The highest BC and PM concentrations were found in G1 while the highest PNC in G3. Lowest concentrations for all pollutants were observed in G2. We found no systematic relationship between income deprivation and pollutant concentrations, suggesting that differences between transport modes are a stronger influence. The underground showed the highest PM concentrations, followed by buses and a much lower concentrations in cars. BC concentrations in the underground were overestimated due to Fe interference. BC concentrations were also higher in buses than cars because of a lower infiltration of outside pollutants into the car cabin. PNCs were highest in buses, closely followed by cars, but lowest in underground due to the absence of combustion sources. Concentration in the road modes (car and bus) were governed by the traffic conditions (such as traffic flow interruptions) at the specific road section. Exposures were reduced in trains with non-openable windows compared to those with openable windows. People from lower income deprivation areas have a predominant use of car, receiving the lowest doses (RDD<1 µg h-1) during commute but generating the largest emissions per commuter. Conversely, commuters from higher income deprivation areas have a major reliance on the bus, receiving higher exposures (RDD between 1.52-3.49 µg h-1) while generating less emissions per person. These findings suggest an aspect of environmental injustice and a need to incorporate the socioeconomic dimension in life-course exposure assessments.
... It is challenging to represent the effects of actual driving situations on on-road emissions because driving mode (i.e., idling, accelerating, cruising, and decelerating) and road configuration (i.e., intersection, upslope, and downslope) spatio-temporally vary at small scale, particularly in urban areas [11,12]. Among various driving situations, congestion with frequent accelerations at low vehicle speeds [13][14][15], signalized traffic intersection [16,17], and upslope [7,18] are found to aggravate on-road air quality. ...
Article
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Mobile monitoring and computational fluid dynamics (CFD) modeling are complementary methods to examine spatio-temporal variations of air pollutant concentrations at high resolutions in urban areas. We measured nitrogen oxides (NOx), black carbon (BC), particle-bound polycyclic aromatic hydrocarbons (pPAH), and particle number (PN) concentrations in a central business district using a mobile laboratory. The analysis of correlations between the measured concentrations and traffic volumes demonstrate that high emitting vehicles (HEVs) are deterministically responsible for poor air quality in the street canyon. The determination coefficient (R²) with the HEV traffic volume is the largest for the pPAH concentration (0.79). The measured NOx and pPAH concentrations at a signalized intersection are higher than those on a road between two intersections by 24% and 25%, respectively. The CFD modeling results reveal that the signalized intersection plays a role in increasing on-road concentrations due to accelerating and idling vehicles (i.e., emission process), but also plays a countervailing role in decreasing on-road concentrations due to lateral ventilation of emitted pollutants (i.e., dispersion process). It is suggested that the number of HEVs and street-canyon ventilation, especially near a signalized intersection, need to be controlled to mitigate poor air quality in a central business district of a megacity.
... Among all, road traffic is considered to be the main anthropogenic source that can produce up to 90% of total PNCs in polluted urban environments (Kumar et al. 2010c). Numerous studies have shown a strong direct correlation of nanoparticles measured along the roadsides with the traffic volume (Kumar et al. 2009a;Mishra et al. 2012;Goel and Kumar 2015). Source apportionment techniques such as positive matrix factorization Al-Dabbous and Kumar 2015) or principal component analysis (Pey et al. 2009) have been applied on PNCs measured at the roadside and urban background locations. ...
Chapter
This chapter discusses the emission, transformation, and fate of incidental airborne nanoparticles. It starts with the up-to-date summary of recent review articles covering various aspects of both the incidental nanoparticles and ENPs. Transformation processes play an important role in influencing the characteristics of nanoparticles both spatially and temporally. A common method to represent the atmospheric size distributions of atmospheric particles is through various modes. A typical size distribution in atmospheric environments shows the presence of the following modes:nucleation, Aitken, accumulation, and coarse. Nucleation mode particles are those generally formed by the gas-to-particle conversion after rapid cooling and dilution of exhaust emissions. Understanding the different transformation processes (i.e., nucleation, coagulation, condensation, evaporation, and dry deposition) is important in order to study the temporal and spatial changes occurring to nanoparticles in the atmospheric environment. The detection of ENP concentrations is necessary for determining human exposure in both the indoor factory environment and ambient non-workplace atmosphere.
... Colwill and Hickman, 1980;Clifford et al., 1997;Chan et al., 2002), and particulate matter (e.g. Knibbs et al., 2010;Hudda et al., 2012;Goel and Kumar 2015). ...
Article
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There is a lack of knowledge regarding in-vehicle concentrations of nitrogen dioxide (NO2) during transit through road tunnels in urban environments. Furthermore, previous studies have tended to involve a single vehicle and the range of in-vehicle NO2 concentrations that vehicle occupants may be exposed to is not well defined. This study describes simultaneous measurements of in-vehicle and outside-vehicle NO2 concentrations on a route through Sydney, Australia that included several major tunnels, minor tunnels and busy surface roads. Tests were conducted on nine passenger vehicles to assess how vehicle characteristics and ventilation settings affected in-vehicle NO2 concentrations and the in-vehicle-to-outside vehicle (I/O) concentration ratio. NO2 was measured directly using a cavity attenuated phase shift (CAPS) technique that gave a high temporal and spatial resolution. In the major tunnels, transit-average in-vehicle NO2 concentrations were lower than outside-vehicle concentrations for all vehicles with cabin air recirculation either on or off. However, markedly lower I/O ratios were obtained with recirculation on (0.08–0.36), suggesting that vehicle occupants can significantly lower their exposure to NO2 in tunnels by switching recirculation on. The highest mean I/O ratios for NO2 were measured in older vehicles (0.35–0.36), which is attributed to older vehicles having higher air exchange rates. The results from this study can be used to inform the design and operation of future road tunnels and modelling of personal exposure to NO2.
... Beneficial effects may be observed also in reduced rerouting through nearby neighborhoods, fewer accidents, improved emergency service, and pollution. In [1], experiments showed that the concentration of fine particles in the air at traffic lights during stops is 29-times higher as compared to free-flow conditions. Also, though the delay time at intersections represents only a minor portion of the entire commuting time, it may contribute up to about 25% of the total trip emissions. ...
Article
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The problem of maximizing bandwidth along anarterial is addressed here by use of two combined control actions:traffic light offsets and recommended speeds. The optimizationproblem has been enriched in order to account for traffic energyconsumption and network travel time, thus avoiding impracticalor undesirable solutions. A traffic microscopic simulator has beenused to assess the performance of the proposed technique in termsof energy consumption, travel time, idling time, and number ofstops. The correlation of theoretical bandwidth with known trafficperformance metrics is studied, and an analysis of the Paretooptimum has been carried out to help the designer choose atradeoff in the multiobjective optimization. Finally, an evaluationof the traffic performance at different levels of traffic demandaims at showing the best operation conditions of the proposedstrategy. A demand-dependent optimization is proposed.
... In ac car, the direct infiltration of on-road emissions was prohibited due to the closure of the windows. Recirculation mode of air-conditioning prevented the entry of fresh air into vehicle cabin, as highlighted by earlier studies (Goel and Kumar, 2015;Kumar and Goel, 2016;Rivas et al., 2017a). Ac car exhibited the highest and bus resulted in the lowest CO exposure concentrations. ...
Article
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National Highways (NH) are the major road networks linking cities but exposure studies during long commutes on highways are limited. We assessed exposure concentrations of fine particles ≤2.5 μm in diameter (PM2.5) and carbon monoxide (CO) inside bus, ac (air-conditioned) and non-ac car and on an Indian NH over 200 km length. A total of nine round journeys were made in three modes. Analysis of variance (ANOVA) and generalized linear model (GLM) were applied to quantify the contribution of determinants that may explain the variability of exposure concentrations and their association with in-vehicle temperature and relative humidity (RH). The highest and lowest exposures concentrations to PM2.5 were observed in non-ac car (89 ± 32 μg m−3) and the ac car (55 ± 19 μg m−3). Exposures concentrations in non-ac car were higher during in-city travel (113 ± 36 μg m−3). The average CO exposure concentrations were highest in ac car (2.0 ± 0.9 ppm). Results of GLM analysis suggested that travel mode, highway segments (in/out-city) and the journey times are key determinants of personal exposure concentrations. Travel mode for PM2.5 (15%) and NH segments for CO (21%) explained maximum variability. Altogether, these explained 33% and 57% of the variability in PM2.5 and CO exposure concentrations, respectively. PM2.5 consists of soot, mineral and fly ash that are a proxy of fresh exhaust emissions, re-suspended road dust and industrial emissions, respectively. Additionally, EDX analyses revealed an abundance of Si, Al, Ca and Pb, confirming re-suspension, brake/tire wear and construction dust as important sources.
... Gao et al. [22] assessed the health damage caused by vehicle exhaust. Goel and Kumar [23] studied the exposure to vehicle exhaust under different traffic conditions, and their findings show that PM 2.5 pollution caused by vehicle exhaust when traffic jams is more serious than when traffic flow is smooth. ...
Article
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This paper investigates the meteorological factors and human activities that influence PM2.5 pollution by employing the data envelopment analysis (DEA) approach to a chance constrained stochastic optimization problem. This approach has the two advantages of admitting random input and output, and allowing the evaluation unit to exceed the front edge under the given probability constraint. Furthermore, by utilizing the meteorological observation data incorporated with the economic and social data for Jiangsu Province, the chance constrained stochastic DEA model was solved to explore the relationship between the meteorological elements and human activities and PM2.5 pollution. The results are summarized by the following: (1) Among all five primary indexes, social progress, energy use and transportation are the most significant for PM2.5 pollution. (2) Among our selected 14 secondary indexes, coal consumption, population density and civil car ownership account for a major portion of PM2.5 pollution. (3) Human activities are the main factor producing PM2.5 pollution. While some meteorological elements generate PM2.5 pollution, some act as influencing factors on the migration of PM2.5 pollution. These findings can provide a reference for the government to formulate appropriate policies to reduce PM2.5 emissions and for the communities to develop effective strategies to eliminate PM2.5 pollution.
... It is important to stress that even for a given route exposure-related factors such as traffic characteristics and weather conditions are subject to frequent changes. Traffic intersections (TIs) are considered to be pollution hotspots [Goel and Kumar 2015]. Data for exposure assessments can be provided through mobile and fixed-site measurements. ...
Article
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Traffic-related emissions, apart from emissions from fuel combustion for heating purposes, significantly deteriorate air quality in cities. The above mainly concerns areas located close to busy traffic routes. According to epidemiological studies, traffic-related emissions have an adverse health effect. This specifically affects commuters (drivers and car passengers) as well as pedestrians. The aim of this study was to determine the variations of particle number and mass concentrations along a busy road in Lublin, Poland and their impact on the particle exposure for commuters and pedestrians. On-route and fixed-site measurements were performed in the summer (June) with a focus on peak and off-peak traffic hours and road sections with low and high traffic intensity. During peak hours, the average number concentration of ultrafine particles (PN0.1) in the road section near 4-way traffic intersections (TIs) was about 2 times higher than during off-peak hours. The average mass concentration of fine particles (PM2.5) was also approximately twice as high than in off-peak hours. Similar relations were found for other measured aerosol particles as well as with respect to particle exposure. The obtained results indicate the need for further extended research on traffic-related emissions and exposure and the ways of limiting them.
... Regarding active modes, pedestrians and cyclists are exposed to lower particle concentrations when selecting routes separated from motorized traffic [19]. Regarding motorized modes, factors affecting the levels of exposure primarily relate to ventilation settings (e.g., windows open or closed and air conditioning on/off), vehicle mode (e.g., year, design, and fuel type), breathing zones with respect to the positions of passengers, doors opening at bus stops, seat positions, passenger density inside a cabin, urban air quality, and urban meteorological conditions [2,3,12,[21][22][23][24]. ...
Article
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Exposure to inhalable particulate matter pollution is a hazard to human health. Many studies have examined the in-transit particulate matter pollution across multiple travel modes. However, limited information is available on the comparison of in-transit exposure among cities that experience different climates and weather patterns. This study aimed to examine the variations in in-cabin particle concentrations during taxi, bus, and metro commutes among four megacities located in the inland and coastal areas of China. To this end, we employed a portable monitoring approach to measure in-transit particle concentrations and the corresponding transit conditions using spatiotemporal information. The results highlighted significant differences in in-cabin particle concentrations among the four cities, indicating that PM concentrations varied in an ascending order of, and the ratios of different-sized particle concentrations varied in a descending order of CS, SZ, GZ, and WH. Variations in in-cabin particle concentrations during bus and metro transits between cities were mainly positively associated with urban background particle concentrations. Unlike those in bus and metro transit, in-cabin PM concentrations in taxi transit were negatively associated with urban precipitation and wind speed. The variations in particle concentrations during the trip were significantly associated with passenger density, posture, the in-cabin location of investigators, and window condition, some of which showed interactive effects. Our findings suggest that improving the urban background environment is essential for reducing particulate pollution in public transport microenvironments. Moreover, optimizing the scheduling of buses and the distribution of bus stops might contribute to mitigating the in-cabin exposure levels in transit. With reference to our methods and insights, policymakers and other researchers may further explore in-transit exposure to particle pollution in different cities.
... Aerosols are multi-component mixtures that originate from different sources and evolve through several microphysical processes like nucleation, coagulation, and condensation, before being removed through dry or wet deposition . Aerosols are important constituents of the earth's atmosphere, which either directly or indirectly influence climate, air quality, visibility, and human health (Lelieveld et al. 2015;Kumar et al. 2015;Goel and Kumar 2015). Additionally, aerosols are also linked with modification in cloud microphysical properties (Gettelman et al. 2013), hydrological cycle (Ramanathan et al. 2001), radiative forcing (Kumar et al. 2017a, b), and with food security (Burney and Ramanathan 2014). ...
Article
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Evolution of submicron particles in terms of particle number concentration and mobility-equivalent diameter were measured during Diwali festival specific intensive pyrotechnic displays in Varanasi over central Indo-Gangetic Plain (IGP). A scanning mobility particle sizer coupled with an optical particle sizer was used to fit in an overlapping size range, and particle number concentration were analyzed to have an insight into the new particle formation, and subsequent evolution of particles from nucleation to accumulation mode. Further, variation in black carbon (BC) concentration and aerosol ionic composition were measured simultaneously. Frequent fluctuation in particle number concentration in and around Diwali festival was evidenced, primarily influenced by local emission sources and meteorology; with three distinct peaks in number concentrations (dN/dlogDp: 3.1-4.5x104 cm3) coinciding well with peak firework emission period (18:00-23:00h). Submicron particle size distribution revealed a single peak covering a size-range of 80-130nm, and for all instances, number concentration maximum coincided with geometric mean minimum, indicating the emission primarily in the ultrafine range (<0.1µm). Interestingly, during peak firework emissions, beside rise in accumulation mode, an event of new particle formation was identified with increase in nucleation and small Aitken mode, before being dispersed to background aerosols. On an integral scale, a clear distinction was noted between a normal and an episodic event, with a definite shift in the generation of ultrafine particles compared to the accumulation mode. The BC diurnal profile was typical, with a prominent nocturnal peak (12.0±3.9µgm-3) corresponding to a decrease in the boundary layer height. A slight shift in maximum BC (16.8µgm-3) was noted on the night of the event coinciding well with firework emissions. An increase in some specific ionic species was also noted in combination to increase in the overall cation to anion ratio, which was explained in terms of heterogeneous transformation of NOx, and catalytic conversion of SO2.
... The highest particle number concentrations are found at the most congested and highly built-up parts of a route such as at traffic intersections [59], with levels 29 times higher than those found during free-flowing traffic conditions [60]. Pedestrian and cyclist exposure at traffic intersections was higher than on roads with free-flowing traffic [56,61,62]. ...
Article
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As global awareness of air pollution rises, so does the imperative to provide evidence-based recommendations for strategies to mitigate its impact. While public policy has a central role in reducing air pollution, exposure can also be reduced by personal choices. Qualified evidence supports limiting physical exertion outdoors on high air pollution days and near air pollution sources, reducing near-roadway exposure while commuting, utilising air quality alert systems to plan activities, and wearing facemasks in prescribed circumstances. Other strategies include avoiding cooking with solid fuels, ventilating and isolating cooking areas, and using portable air cleaners fitted with high efficiency particulate air filters. We detail recommendations to assist providers and public health officials when advising patients and the public regarding personal-level strategies to mitigate risk imposed by air pollution, while recognising that well-designed prospective studies are urgently needed to better establish and validate interventions that benefit respiratory health in this context.
... In the US alone, urban congestion costs 8.8 billion hours of travel delay, and 3.3 billion gallons of wasted fuel per year (Schrank et al., 2019). In addition, pollution due to petrol and diesel cars at stand still at major traffic intersections can rise to more than 20 times than in normal free flow traffic conditions (Goel and Kumar, 2015). ...
Thesis
Autonomous vehicles are predicted to number several millions by 2025. Crucially, these vehicles will be able to communicate and coordinate with vehicles in range, opening up opportunities to mitigate congestion and the risk of accidents. This ability to communicate and coordinate underpins the notion of Connected Autonomous Vehicles (CAVs). This thesis presents a decentralised mechanism for traffic control of CAVs in settings where road intersections have to be managed and optimised. Against this background, we propose a solution based on the distributed constraint optimisation approach (DCOP). We first model the intersection and formulate the regulation problem as a DCOP. Following this, we evaluate the performance of different DCOP algorithms. Thereafter, we opt for an algorithm and adapt it to the traffic regulation problem, in order to improve performance and enhance security. In a multi-intersection setup, we propose an individual priority mechanism allowing road intersections to distribute vehicles while avoiding computational expensive global optimisation
... We believe that this difference between the PM2.5 and PM10 pollution roses is attributed to the different driving conditions at the road intersection compared to the free flow, also reported in similar studies (Goel and Kumar (2015)), and the sea salt and shipping emissions coming from the coastline (see Section 5.3.2 on the source apportionment results) Typical Days 23 58 123 125 38 218 26 166 172 119 195 Minor Event 23 325 279 181 106 753 322 363 278 218 602 Major Event 1 -1569 1569 1569 1569 -1781 1781 1781 1781 Total 46 241 201 144 59 409 249 267 214 123 402 * minor dust events with PM 10 >200 μg.m -3 and major dust storms with PM 10 >1000 μg.m -3 (Al-Dabbous and Draxler, 2001;Saraga et al., 2017) A more detailed analysis of the diurnal and weekday patterns is shown in Figure 5.6, using a threshold of PM10 <200 μg m -3 (the suggested daily mean for non-dusty days). On average, PM10 ...
Thesis
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This thesis and the work to which it refers are the results of my own efforts. Any ideas, data, images or text resulting from the work of others (whether published or unpublished) are fully identified as such within the work and attributed to their originator in the text, bibliography or in footnotes. This thesis has not been submitted in whole or in part for any other academic degree or professional qualification. I agree that the University has the right to submit my work to the plagiarism detection service Turnitin UK for originality checks. Whether or not drafts have been so-assessed, the University reserves the right to require an electronic version of the final document (as submitted) for assessment as above. Abstract There is substantial evidence that airborne particulate matter (PM) contributes to haze, acid rain, global climate change, and decreased life expectancy. Many recent studies have reported that a large fraction of airborne PM could be attributed to fugitive PM (fPM). The developing arid and semi-arid regions, in particular, are facing the biggest brunt of fPM usually ascribed to the regionally transported dust. On the other hand, the rapid expansion of their metropolitan cities is contributing a considerable amount of locally induced fPM which makes it a prominent environmental and health stressor in these areas. Based on field measurements and dispersion modelling, this thesis aims to: (i) measure fPM from two common sources (loose soils and non-exhaust traffic) in areas with arid desert climates, (ii) derive representative emission models, and (iii) assess their overall environmental and health impacts. For this thesis, on site measurements and samples of PM (<10 µm diameter) were collected. Source apportionment was performed to determine the contributions of individual sources. Dispersion modelling and regression analysis were used to derive emission models for loose Calcisols (a prominent soil in the subject areas) and vehicle-induced fPM (VfPM). Finally, our derived models were used along with the state-of-the-art practices (i.e., regional emission models and the World Health Organization's (WHO) Environmental Burden of Disease (EBD) method) to determine the environmental and health impacts of local fPM. Several important findings were extracted from the above analysis: (i) fPM from different origins contribute more than 60% of the urban PM in arid areas, (ii) power law emission models with wind speed dependence were derived for loose Calcisols soil, (iii) emission factors were derived for VfPM using linear regression and were close to values reported in USA, (iv) EBD estimates found that fPM may lead to ~ 11.0 times higher short-term excess mortalities compared to constant database measurements. 4
... agricultural burning, forest fires and waste disposal), vehicular traffic (Abramesko and Tartakovsky, 2017) and industrial emissions (Keuken et al., 2015). Other sources are tire wear and tear from car brakes, air traffic (Keuken et al., 2015;Kecorius et al., 2016;Habre et al., 2018;Stacey, 2019;Møller et al., 2020), seaport, maritime transportation (Agudelo-Castañeda et al., 2019), construction, demolition, restoration and concrete processing Kumar et al., 2016), domestic wood stoves (Marabini et al., 2017), outdoor burning, kitchen (Chen et al., 2017), and cigarette smoke (Goel and Kumar, 2015). ...
Article
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Air pollution by particulate matter (PM) is one of the main threats to human health, particularly in large cities where pollution levels are continually exceeded. According to their source of emission, geography, and local meteorology, the pollutant particles vary in size and composition. These particles are conditioned to the aerodynamic diameter and thus classified as coarse (2.5–10 μm), fine (0.1–2.5 μm), and ultrafine (<0.1 μm), where the degree of toxicity becomes greater for smaller particles. These particles can get into the lungs and translocate into vital organs due to their size, causing significant human health consequences. Besides, PM pollutants have been linked to respiratory conditions, genotoxic, mutagenic, and carcinogenic activity in human beings. This document presents an overview of emission sources, physicochemical characteristics, collection and measurement methodologies, toxicity, and existing control mechanisms for ultrafine particles (UFPs) in the last fifteen years.
... Although there is a wealth of studies that have tackled air pollution from diverse sources such as road vehicles Goel and Kumar, 2015), road works (Fuller and Green, 2004;Tian et al., 2007), non-vehicular activities (Saliba et al., 2010;, and industrial works (Rodríguez et al., 2004;Toledo et al., 2008;Diapouli et al., 2013;, there is a lack of studies that address PM emanating from demolition sites. Consequently, the focus of this paper is related to (1) quantifying particulate matter with aerodynamic diameter less than or equal to 10 µm (PM 10 ) emissions during the implosion of concrete grain silos located at the old seaport in Aqaba off the Gulf of Aqaba that took place on 13 January 2019 and (2) estimating particle mass emission rate of PM 10 produced by the collapse Aerosol and Air Quality Research,20: x: 1-9, xxxx 2 of imploded silos. ...
Article
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This study quantified the effect of imploding old concrete grain silos in Aqaba, Jordan, on the eastern side of the Gulf of Aqaba, an arid region, on air quality by measuring the PM10 concentrations before and after the implosion at four monitoring locations. The implosion of the silos forms part of a comprehensive plan to relocate and upgrade the Port of Aqaba, which is situated on the coast of the Red Sea, with the goal of freeing space for development and improving the infrastructure in the heart of the city. The demolition, which occurred at 11:00 a.m. (local time) on 13 January 2019, generated a massive cloud of dust that was transported to nearby areas. To characterize these emissions, descriptive statistics, graphical methods, inverse distance weighting interpolation, decision trees constructed with recursive partitioning, the Gaussian dispersion model, the modified box model, and regression analysis were applied. The PM10 concentrations were in compliance with the Jordanian 24-h standard of 120 µg m–3 prior to the implosion but substantially increased (although still varied by distance from the demolition site) at all four stations afterward, with the maximum values (259–587 µg m–3) exceeding the pre-implosion ones by as much as 26 times. However, these high concentrations were short-lived, and the majority of the stations returned to background levels within 30–33 hours. According to our calculations on the implosion, the PM10 emission rate was 17 ± 2 mg m–2 s–1, which is equivalent to 215 ± 22 kg silo–1, and the air mixing height was 613 ± 72 m, or approximately eight times the height of the silos.
... The difficulty of working with mobile air quality monitoring data arises from the combination of complex spatiotemporal sampling and temporal air quality variability in different locations, related to traffic dynamics, street topology, meteorology, background source strength, etc. (Goel & Kumar, 2015;Van den Bossche et al., 2015). As mobile sensors capture only a snapshot of air pollution at a given location and time, this temporal variability makes it difficult to characterize the air pollution at a given location based on these measurements alone. ...
... A relatively rare and expensive network of stationary 88 measurement sensors does not provide sufficient spatial resolution to observe emission episodes 89 related to traffic disturbances. As a consequence, the effects of exposure to pollution hot-spots 90 remain poorly investigated (Kumar et al., 2015). However, it can be expected that low-cost 91 sensors will be widely used in the near future. ...
Article
The paper presents the application of a low-cost system for monitoring the current level of road traffic participants' exposure to PM10 air pollution. The research was carried out from the end of August 2017 to the beginning of October 2017 on the central section of one of the main roads in Bielsko-Biała, Poland. In the analysed period, significant changes in the daily distribution of road traffic both into and out of the city centre were observed. The average travel time depended on the direction of traffic, and the difference between directions being almost 50%. The PM10 urban background concentration was also subject to daily changes, and in the fifth week of observation, it reached a value more than twice as high as in the first week of observation. The maximum level of road traffic participants' exposure was observed at a relatively low urban background PM10 concentration. It was observed that a significant slowdown in traffic in conditions of acceptable urban air quality led to a comparable level of exposure to that of standard traffic conditions and poor urban air quality. It was also found that the slowdown in traffic increased the exposure time of traffic participants travelling towards the city centre by an average of 24% and, for those travelling in the opposite direction, by as much as 50%. In an extreme case of traffic delay, exposure to PM10 concentration in the vicinity of the road was two and a half times as long.
... The adverse effects of vehicular exhaust can be more serious in megacities because of excessive vehicular density and traffic conditions. The frequent acceleration and deceleration of vehicles in high-traffic areas, particularly in congested traffic flows, produces greater emissions (Goel and Kumar, 2015); toll plazas are especially susceptible to the build-up of vehicular pollutants because vehicles spend prolonged durations in both idling and accelerating/decelerating at low gears. In this regard, a previous study conducted at a highway toll station in Malaysia (Niza and Jamal, 2007) estimated that the peak CO exposure level of toll workers is 18 ppm. ...
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... One may note that the relative importance of these sources varies significantly with location where, for example, open fire cooking sources are used extensively in many developing countries while residential wood burning is an increasing issue also in developed regions as a way to reduce consumption of fossil fuel. For mobile sources like vehicles the contribution to traffic emissions (eg, road and sea traffic), the specific engine and abatement technology in each individual source together with operating (especially engine load) and ambient conditions make the emission pattern complex and highly variable [14]. This calls for detailed descriptions on the individual level as well as continuous updates of the average fleet emission over time to capture the rapid embracement of new technology and fuels [31]. ...
Chapter
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... Similar relations in terms of increasing particle concentrations in the vicinity of traffic intersections were reported in many previous studies, e.g. elevated concentrations of trafficrelated particles in close proximity of intersections were observed, among others, by Goel and Kumar (2015). Data obtained by Ćwiklak et al. (2009) in Zabrze (Upper Silesia, Poland) near a busy street intersection indicated that the average increase of PM 2.5 and PM 10 concentrations as compared to the urban background amounted to 46.9% and 44.9%, respectively. ...
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We designed a novel experimental set-up to pseudo-simultaneous measure size-segregated filtration efficiency (ηF), breathing resistance (ηP) and potential usage time (tB) for 11 types of face protective equipment (FPE; four respirators; three medical; and four handmade) in the submicron range. As expected, the highest ηF was exhibited by respirators (97±3%), followed by medical (81±7%) and handmade (47±13%). Similarly, the breathing resistance was highest for respirators, followed by medical and handmade FPE. Combined analysis of efficiency and breathing resistance highlighted trade-offs, i.e. respirators showing the best overall performance across these two indicators, followed by medical and handmade FPE. This hierarchy was also confirmed by quality factor, which is a performance indicator of filters. Detailed assessment of size-segregated aerosols, combined with the scanning electron microscope imaging, revealed material characteristics such as pore density, fiber thickness, filter material and number of layers influence their performance. ηF and ηP showed an inverse exponential decay with time. Using their cross-over point, in combination with acceptable breathability, allowed to estimate tB as 3.2-9.5 hours (respirators), 2.6-7.3 hours (medical masks) and 4.0-8.8 hours (handmade). While relatively longer tB of handmade FPE indicate breathing comfort, they are far less efficient in filtering virus-laden submicron aerosols compared with respirators.
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Scientific literature has overlooked how PM2.5 concentrations vary with varying pedestrian heights near a roadway. Understanding this is important because walking is an essential commuting element of a sustainable transportation system, and pedestrians’ height varies widely. Therefore, the focus of the current study is to bridge this gap using results from CALINE 4 model and mobile PM2.5 measurements. In CALINE 4, a simple pedestrian pathway depicting the selected study site located near the Sardar Patel Road, Chennai, India, was simulated. The PM2.5 concentrations were estimated on this pathway at varying heights (0.1–1.8 m) in 135 simulated runs. Subsequently, the sensitivity of the PM2.5 exposure difference across heights was explored with varying ambient PM2.5 concentrations, wind speed, traffic volume, and traffic compositions. Results indicated that the PM2.5 concentrations reduced with increasing heights of pedestrians in all the modelled runs. When this PM2.5 exposure difference was investigated with varying surrounding conditions, it was found that the difference in PM2.5 exposure across heights was influenced by the wind speed, traffic volume, and traffic composition. Ambient PM2.5 concentrations had no discernible effect on it. Car-dominated traffic with a higher mode share of heavy commercial vehicles was marked with the highest PM2.5 exposure difference across heights. For traffic volume, it was observed that for every 100 vehicles hr–1 increase in traffic volume, the PM2.5 exposure difference increased by 0.13 µg m–3 m–1 in the range of pedestrian’s height. For wind speed, calculations suggested that for every 1 m s–1 increase in wind speed, the PM2.5 exposure difference was reduced by 0.095 µg m–3 m–1 in the range of pedestrian’s height. Finally, to bolster the modelling results, mobile PM2.5 measurements (using portable, low-cost optical particle sensors) were conducted near a busy urban roadway at two different heights, 80 cm and 150 cm, during peak and off-peak hours. The results of mobile measurements were found to be consistent with CALINE 4 modelled results.
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This study investigates and proposes emission factors (EFs) and models for vehicle-induced exhaust (VEX) and fugitive (VfPM) particulate matter emissions representative of areas with arid climates. Particle number (PNC) and mass (PMC) concentrations and their integrated samples were collected for a period of three months for both PM10 and PM2.5 next to a trafficked road in the city of Doha, Qatar. Using Positive Matrix Factorization (PMF) on the elemental data of the samples, six distinct PM sources were identified: traffic exhaust, dust resuspension, fresh and aged sea salt, secondary aerosols, and fuel oil/shipping. Dispersion modelling and regression analysis were combined to derive EFs (linear analysis) and models (non-linear analysis) for the total traffic fleet (heavy and light duty). The estimated EFs were between 620 and 730 mg VKT⁻¹ (VKT; Vehicle Kilometer Travelled) (adj. R² ∼ 0.84) and 1080–1410 mg VKT⁻¹ (adj. R² ∼ 0.70) for VEX and VfPM, respectively. The integration of field measurements, chemical characterization, and dispersion modelling presented herein, is one of the first similar studies conducted in the wider region, identifies the importance of fugitive PM (fPM), and marks the need for further studies to improve emissions modelling of VfPM in arid desert climates.
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At the crosswalk of urban traffic intersections, vehicles frequently stop with their engines idling adjacent to it during the red-light period and accelerate with intensified emissions during the green-light period. As a result, pedestrians are inevitably at a higher risk of exposure to near-source traffic-related air pollution while walking on the crosswalk or waiting on the roadside. Therefore, this study focuses on pedestrian exposure to particulate matter on the crosswalk at urban intersections. Firstly, mobile measurements at varied locations of the crosswalk were carried out to reveal the spatial difference of particles on the whole crosswalk. The results show that the concentrations of submicron and coarse particles are higher on the parking crosswalk than that on the non-parking crosswalk. Secondly, mobile measurements at varied heights of crosswalk were carried out to discover the vertical difference of particles on the crosswalk. Particulate concentration is higher at the height of 1.5 m than that at 0.5 m. Thirdly, fixed-site measurements were conducted on the roadside to make a comparison with the crosswalk. Particulate concentration is found to be nearly 6% higher on the crosswalk than that on the roadside. Finally, pedestrian exposure to particulate matter in varied trips on the crosswalk is investigated and the exposure in trips with a 10s–20s delay after the onset of a walk signal is lower than in other situations. The results can help fully recognize the particulate pollution at intersections and better understand the particulate exposure of pedestrians on crosswalk at urban intersections.
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To evaluate the respiratory health risk of pedestrians at signalized intersections, it is crucial to accurately investigate their spatial distribution of particulate matter (PM) in the air and the respiratory exposure dose to the public. The particle number concentrations (PNCs) of different sizes (10–2500 nm) along the horizontal and vertical vibrations of the intersection were measured in Xi'an, China, and the respiratory deposition dose (RDD) rate of pedestrians was calculated to estimate the pedestrian exposure level. The mean PNC at the intersection's entrance (1.59 × 10⁴ # cm⁻³) was larger than at its exit (1.34 × 10⁴ # cm⁻³) irrespective of the particle mode. At the exit, moreover, the PNC values decreased exponentially with increasing distance from the parking baseline of the intersection, while no such damping characterized the entrance to it. Concerning the vertical vibration of the intersection, both nucleation and Aitken modes of PNC peaked at a 0.4-m height and the maximum PNC in the accumulation mode and coarse mode appeared at a height of 3.4–4.5 m. Average RDD rate at the signalized intersection's entrance and exit was respectively 8.103 μg h⁻¹ and 7.523 μg h⁻¹. For this same intersection, the highest PM exposure dose was 8.444 μg h⁻¹ for the elderly, followed by 8.061 μg h⁻¹ for adults, and 3.221 μg h⁻¹ for children.
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Motivated by public interest, the Clean Air and Urban Landscapes (CAUL) hub deployed instrumentation to measure air quality at a roadside location in Sydney. The main aim was to compare concentrations of fine particulate matter (PM2.5) measured along a busy road section with ambient regional urban background levels, as measured at nearby regulatory air quality stations. The study also explored spatial and temporal variations in the observed PM2.5 concentrations. The chosen area was Randwick in Sydney, because it was also the subject area for an agent-based traffic model. Over a four-day campaign in February 2017, continuous measurements of PM2.5 were made along and around the main road. In addition, a traffic counting application was used to gather data for evaluation of the agent-based traffic model. The average hourly PM2.5 concentration was 13 µg/m3, which is approximately twice the concentrations at the nearby regulatory air quality network sites measured over the same period. Roadside concentrations of PM2.5 were about 50% higher in the morning rush-hour than the afternoon rush hour, and slightly lower (reductions of <30%) 50 m away from the main road, on cross-roads. The traffic model under-estimated vehicle numbers by about 4 fold, and failed to replicate the temporal variations in traffic flow, which we assume was due to an influx of traffic from outside the study region dominating traffic patterns. Our findings suggest that those working for long hours outdoors at busy roadside locations are at greater risk of suffering detrimental health effects associated with higher levels of exposure to PM2.5. Furthermore, the worse air quality in the morning rush hour means that, where possible, joggers and cyclists should avoid busy roads around these times.
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A ação do homem tem provocado mudanças no meio ambiente, sendo a poluição urbana uma das consequências negativas aplicadas nesse ecossistema. Com o desenvolvimento tecnológico, novas perspectivas computacionais afloram para o monitoramento ambiental. Este artigo apresenta pontos chaves da fenomenologia ambiental que podem se beneficiar da evolução promovida pela computação aplicada nos estudos da poluição, assim como realiza um levantamento de pesquisas e tecnologias utilizadas nesse contexto.
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Considerable changes in particulate matter (PM) during COVID-19 lockdown in major cities around the World demand changes in exposure assessment studies of PM. The present study shows variations in respiratory deposition dose (RDD) of both fine (PM2.5) and coarse (PM10) particles before, during and after Covid-19 lockdown phases at three sites (with different pollution signatures) in Delhi—Alipur, Okhla and Pusa Road. Exposure assessment study showed mean PM2.5 RDD (± S.D.) (µg/min) for walk and sit mode during before lockdown (BL) as 2.41(± 1.20) and 0.84(± 0.42) for Alipur, 2.71(± 1.60) and 0.94(± 0.56) for Okhla, and 2.54(± 1.28) and 0.88(± 0.44) for Pusa road, which decreased drastically during Lockdown 1(L1) as 0.85(± 0.35) and 0.30(± 0.12) for Alipur, 0.83(± 0.33) and 0.29(± 0.11) for Okhla, and 0.68(± 0.28) and 0.23(± 0.10) for Pusa road, respectively. Mean PM10 RDD (± S.D.) (µg/min) for walk and sit mode during before lockdown (BL) as 3.90 (± 1.73) and 1.36 (± 0.60) for Alipur, 4.74 (± 2.04) and 1.65 (± 0.71) for Okhla, and 4.25 (± 1.69) and 1.48 (± 0.59) for Pusa Road, respectively which decreased drastically during Lockdown 1(L1) as 2.19 (± 0.95) and 0.76 (± 0.33) for Alipur, 1.73 (± 0.67) and 0.60 (± 0.23) for Okhla and, 1.45 (± 0.50) and 0.50 (± 0.17) for Pusa Road, respectively. Significant decrease in RDD concentrations (Both PM2.5 and PM10) than that of BL phase have been found during Lockdown 1(L1) phase and other successive lockdown and unlock phases—Lockdown 2(L2), Lockdown 3(L3), Lockdown 4(L4) and Unlock1 (UL1) phases. Changes in RDD values during lockdown phases were affected by lesser traffic emission, minimized industrial activities, biomass burning activities, precipitation activities, etc. Seasonal variations of RDD showed Delhites are found exposed to more fine and coarse particles’ RDD (walk and sit modes) before and after lockdown, i.e. during normal days than during lockdown phases showing potential health effects. People in sit condition found less exposed to fine and coarse RDD comparison to those in walk condition both during normal and lockdown days.
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Observation of air pollution at high spatio-temporal resolution has become easy with the emergence of low-cost sensors (LCS). LCS provide new opportunities to enhance existing air quality monitoring frameworks but there are always questions asked about the data accuracy and quality. In this study, we assess the performance of LCS against industry-grade instruments. We use linear regression (LR), arti[cial neural networks (ANN), support vector regression (SVR) and random forest (RF) regression for development of calibration models for LCS, which were Smart Citizen (SC) kits developed in iSCAPE project. Initially, outdoor colocation experiments are conducted where ten SC kits are collocated with GRIMM, which is an industry-grade instrument. Quality check on the LCS data is performed and the data is used to develop calibration models. Model evaluation is done by testing them on 9 SC kits. We observed that the SVR model outperformed other three models for PM2.5 with an average root mean square error of 3.39 and average R2 of 0.87. Model validation is performed by testing it for PM10 and SVR model shows similar results. The results indicate that SVR can be considered as a promising approach for LCS calibration.
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We investigated the determinants of personal exposure concentrations of commuters’ to black carbon (BC), ultrafine particle number concentrations (PNC), and particulate matter (PM1, PM2.5 and PM10) in different travel modes. We quantified the contribution of key factors that explain the variation of the previous pollutants in four commuting routes in London, each covered by four transport modes (car, bus, walk and underground). Models were performed for each pollutant, separately to assess the effect of meteorology (wind speed) or ambient concentrations (with either high spatial or temporal resolution). Concentration variations were mainly explained by wind speed or ambient concentrations and to a lesser extent by route and period of the day. In multivariate models with wind speed, the wind speed was the common significant predictor for all the pollutants in the above-ground modes (i.e., car, bus, walk); and the only predictor variable for the PM fractions. Wind speed had the strongest effect on PM during the bus trips, with an increase in 1 m s-1 leading to a decrease in 2.25, 2.90 and 4.98 µg m-3 of PM1, PM2.5 and PM10, respectively. PM2.5 and PM10 concentrations in car trips were better explained by ambient concentrations with high temporal resolution although from a single monitoring station. On the other hand, ambient concentrations with high spatial coverage although lower temporal resolution predicted better the concentrations in bus trips, due to bus routes passing through streets with a high variability of traffic intensity. In the underground models, wind speed was not significant and line and type of windows on the train explained 42% of the variation of PNC and 90% of all PM fractions. Trains in the district line with openable windows had an increase in concentrations of 1684 cm-3 for PNC and 40.69 µg m-3 for PM2.5 compared with trains that has non-openable windows. The results from this work can be used to target efforts to reduce personal exposures of London commuters.
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The fuel consumption of the vehicles is increasing day by day as a result of enhanced trip lengths, personal mode of transport and congested intersections. When the vehicles are waiting for their turn to cross the intersection at signals, the drivers normally keep their vehicle's engine on and a result of this extra fuel is consumed. This small amount of fuel wasted aggregated over a number of cycles per day, number of days per year and number of signalized intersections results in a huge quantity of fuel. Measuring delay is important in computing the level of service provided to road users at signalized intersection. Intersection delays may include queue delay and control delay. The signalized intersection capacity and LOS estimation procedures are built around the concept of average control delay per vehicle. Control delay is the portion of the total delay attributed to traffic signal operation for signalized intersections and this delay can be categorized into deceleration delay, stopped delay and acceleration delay. In India mainly two methods were using to estimate control delay those are field measurement and theoretical/analytical measurement. Field measurement of control delay includes the use of test-car observations, path tracing of individual vehicles, and the recording of arrival and departure volumes at Intersection but this expensive for long period. Analytical delay models of traffic systems are structured in a demand-supply framework and these models deals with the macroscopic method to estimate delay measurements. Whereas micro simulation based models are capable to estimate the individual delay of each vehicle at intersection and these models works on car following theory. The main objective of present study is to estimate delay and fuel loss during idling vehicles at signalized intersections in Ahmedabad city. For estimation of delay at intersections, typical corridor on drive in road in Ahmedabad city has been considered. Drive in road is one the busiest urban arterial corridor and this corridor connects the traffic coming from Thaltej intersection to Vijay Char Rasta Intersection.
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Spatial distributions of ultrafine particles (UFPs; 6 < Dp < 560 nm) and related gaseous and particulate pollutants were estimated from on-road measurements undertaken on busy roadways of Seoul, Korea, using a mobile laboratory (ML). The objectives of the study were to determine the spatial variations in UFP size distributions and concentrations of associated gaseous and particulate pollutants and to observe the relationships of UFP number concentrations with other pollutants on roadways in an urban area in Korea. The pollutants associated with diesel vehicles such as black carbon (BC) and particle-bound polycyclic aromatic hydrocarbons (PM-PAHs) exhibited a high determination coefficient (r2 = 0.65), indicating the influence of diesel vehicles on emissions in the study area. Further supporting evidence for the influence of diesel vehicles on emissions was given by the higher determination coefficients of PM-PAHs and BC concentrations with larger size-classified particles, ranging from 60 < Dp < 220 nm, than with total UFP number concentrations or smaller particles in the 6 < Dp < 60 nm size range. Peak concentrations of measured pollutants were observed mostly at intersections, reflecting the relationships of transient driving modes (i.e., deceleration and acceleration) with emissions of UFPs, associated pollutants, and concentrated traffic volumes at such locations.
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For the first time in Germany, we obtained high-resolution spatial distributions of particle numbers and nitrogen oxides in an urban agglomeration using a tram system. In comparison to particle numbers the NOx concentration decreased much faster with a significantly steeper gradient when going from the inner city to the surrounding area. In case of NOx the decrease was 70% while for particle number concentration it was only 50%. We found an area in the rural surrounding with a second increase of particle numbers without simultaneous enhanced NOx levels. The source of the high particle numbers could be ascribed to industry emissions about 5–10 km away. The mean spatial distribution of particle number concentration depended on wind direction, wind velocity and boundary layer stability. The dependency was particularly strong in the rural area affected by industrial emissions, where individual wind directions led to concentration differences of up to 25%. The particulate concentration was 40% higher during low wind velocities (1–5 m s−1) than during high wind velocities (>5 m s−1). We observed similar findings for the impact of boundary layer stability on particle numbers concentration. Particle pollution was 40% higher for stable stratification compared to neutral or unstable cases.
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Ultrafine particles (UFPs; diameter less than 100 nm) are ubiquitous in urban air, and an acknowledged risk to human health. Globally, the major source for urban outdoor UFP concentrations is motor traffic. Ongoing trends towards urbanisation and expansion of road traffic are anticipated to further increase population exposure to UFPs. Numerous experimental studies have characterised UFPs in individual cities, but an integrated evaluation of emissions and population exposure is still lacking. Our analysis suggests that the average exposure to outdoor UFPs in Asian cities is about four-times larger than that in European cities but impacts on human health are largely unknown. This article reviews some fundamental drivers of UFP emissions and dispersion, and highlights unresolved challenges, as well as recommendations to ensure sustainable urban development whilst minimising any possible adverse health impacts.
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Diesel engine particle emissions during transient operations, including emissions during FTP transient cycles and during active regenerations of a NOx adsorber, were studied using a fast Engine Exhaust Particle Sizer (EEPS). For both fuels tested, a No. 2 certification diesel and a low sulfur diesel (BP-15), high particle concentrations and emission rates were mainly associated with heavy engine acceleration, high speed, and high torque during transient cycles. Averaged over the FTP transient cycle, the particle number concentration during tests with the certification fuel was 1.2e8/cm, about four times the particle number concentration observed during tests using the BP-15 fuel. The effect of each engine parameter on particle emissions was studied. During tests using BP-15, the particle number emission rate was mainly controlled by the engine speed and torque, whereas for Certification fuel, the engine acceleration also had a strong effect on number emission rates. The effects of active regenerations of a diesel NOx adsorber on particle emissions were also characterized for two catalyst regeneration strategies: Delayed Extended Main (DEM) and Post 80 injection (Post80). Particle volume concentrations observed during DEM regenerations were much higher than those during Post80 regenerations, and the minimum air to fuel ratio achieved during the regenerations had little effect on particle emission for both strategies. This study provides valuable information for developing strategies that minimize the particle formation during active regenerations of NOx adsorbers.
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Accurate quantification of exposures to traffic-related air pollution in near-highway neighborhoods is challenging due to the high degree of spatial and temporal variation of pollutant levels. The objective of this study was to measure air pollutant levels in a near-highway urban area over a wide range of traffic and meteorological conditions using a mobile monitoring platform. The study was performed in a 2.3-km(2) area in Somerville, Massachusetts (USA), near Interstate I-93, a highway that carries 150,000 vehicles per day. The mobile platform was equipped with rapid-response instruments and was driven repeatedly along a 15.4-km route on 55 days between September 2009 and August 2010. Monitoring was performed in 4-6-hour shifts in the morning, afternoon and evening on both weekdays and weekends in winter, spring, summer and fall. Measurements were made of particle number concentration (PNC; 4-3,000 nm), particle size distribution, fine particle mass (PM(2.5)), particle-bound polycyclic aromatic hydrocarbons (pPAH), black carbon (BC), carbon monoxide (CO), and nitrogen oxides (NO and NO(x)). The highest pollutant concentrations were measured within 0-50 m of I-93 with distance-decay gradients varying depending on traffic and meteorology. The most pronounced variations were observed for PNC. Annual median PNC 0-50 m from I-93 was two-fold higher compared to the background area (>1 km from I-93). In general, PNC levels were highest in winter and lowest in summer and fall, higher on weekdays and Saturdays compared to Sundays, and higher during morning rush hour compared to later in the day. Similar spatial and temporal trends were observed for NO, CO and BC, but not for PM(2.5). Spatial variations in PNC distance-decay gradients were non-uniform largely due to contributions from local street traffic. Hour-to-hour, day-to-day and season-to-season variations in PNC were of the same magnitude as spatial variations. Datasets containing fine-scale temporal and spatial variation of air pollution levels near highways may help to inform exposure assessment efforts.
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A proposed revision of the dosimetric model of the respiratory tract used in ICRP Publication 30 (ICRP, 1979) provides for the inhalability of airborne materials and describes deposition in specific extrathoracic and thoracic regions. Clearance is competitive between particle transport processes and absorption into blood. Reference values for particle transport rates are provided. In the absence of observations on specific radionuclide compounds, default values for rate of absorption into blood are proposed for materials classified as being rapidly, moderately, or slowly absorbed. The calculation of doses follows the method of ICRP 30 (ICRP, 1979), in which the committed equivalent dose in a target tissue is determined by the energy absorbed per unit mass. However, instead of calculating an average dose to the total lungs, the new model provides for calculating doses to specific tissues of extrathoracic and thoracic airways, and then adjusting these doses to account for differences in radiation sensitivity. These detriment-adjusted doses can be summed separately for the extrathoracic and the thoracic regions yielding two values of equivalent dose for the entire respiratory tract which can be used in the ICRP dosimetric system (ICRP, 1991).
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This paper presents a new methodology to measure delay at signalized intersections using linearly referenced global positioning system data. The methodology can be used to evaluate new models that estimate control delay (which includes deceleration delay, stopped delay, and acceleration delay). The main components of delay were determined by analyzing the distance-rime, speed-time, and acceleration-time diagrams of a travel time run. The procedure used speeds and forward and backward acceleration algorithms to detect critical delay points. The stopped delay versus control delay relationship was found to be linear. In contrast to other studies, it was found that such a relationship did not pass through the origin and that a deceleration-acceleration delay value had to be added to the stopped delay term to obtain control delay. It was also found that deceleration and acceleration lengths were much longer than others reported in the literature and that the percentage of the control delay that takes place after the signalized intersection stop bar is not negligible.
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Commuters are regularly exposed to short-term peak concentration of traffic produced nanoparticles (i.e. particles <300 nm in size). Studies indicate that these exposures pose adverse health effects (i.e. cardiovascular). This study aims to obtain particle number concentrations (PNCs) and distributions (PNDs) inside and outside a car cabin whilst driving on a road in Guildford, a typical UK town. Other objectives are to: (i) investigate the influences of particle transformation processes on particle number and size distributions in the cabin, (ii) correlate PNCs inside the cabin to those measured outside, and (iii) predict PNCs in the cabin based on those outside the cabin using a semi-empirical model. A fast response differential mobility spectrometer (DMS50) was employed in conjunction with an automatic switching system to measure PNCs and PNDs in the 5–560 nm range at multiple locations inside and outside the cabin at 10 Hz sampling rate over 10 s sequential intervals. Two separate sets of
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The aim of this study is to assess particle number concentrations (PNCs) and distributions (PNDs) in a car cabin while driving. Further objectives include the determination of the influence of particle transformation processes on PNCs, PNDs and estimation of PNC related exposure. On-board measurements of PNCs and PNDs were made in the 5–560 nm size range using a fast response differential mobility spectrometer (DMS50), which has a response time of 500 ms. Video records of the traffic ahead of the experimental car were also used to correlate emission events with measured PNCs and PNDs. A total of 30 return trips was made on a 2.7 km route during morning and evening rush hours, with journey times of 7 ± 2 and 10 ± 3 min, respectively. The average PNC for the set of morning journeys, 5.79 ± 3.52 × 104 cm−3, was found to be nearly identical to the average recorded during the afternoon, 5.95 ± 4.67 × 104 cm−3. Average PNCs for individual trips varied from 2.42 × 104 cm−3
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We compared the effect of ambient temperature observed in two different seasons on the size distribution and particle number concentration (PNC) as a function of distance (up to ~ 250 m) from a major traffic road (25% of the vehicles are heavy-duty diesel vehicles). The modal particle diameter was found between 10 and 30 nm at the roadside in the winter. However, there was no peak for this size range in the summer, even at the roadside. Ambient temperature affects both the atmospheric dilution ratio (DR) and the evaporation rate of particles, thus it affects the decay rate of PNC. We corrected the DR effect in order to focus on the effect of particle evaporation on PNC decay. The decay rate of PNC with DR was found to depend on the season and particle diameter. During the winter, the decay rate for smaller particles (< 30 nm) was much higher (i.e., the concentration decreased significantly against DR), whereas it was low during the summer. In contrast, for particles > 30 nm in diameter, the decay