Time-series analysis of above-road particulate matter at the Caldecott Tunnel exit

On November 18, 1997, above-road particulate matter (PM) lidar (light detection and ranging) signals and heavy-duty (HD) and light-duty (LD) vehicle counts were simultaneously collected for 894 10-sec sampling periods at the Caldecott Tunnel in Orinda, CA, for the purpose of measuring the relative contributions of LD and HD vehicles to the PM lidar signal under real-world driving conditions. The relationship between the PM lidar signal and traffic activity (i.e., LD and HD traffic volumes) was examined using a time-series analysis technique, multilagged regression. The time-series model results indicate that the PM lidar signal in the current sampling period (PMt) depended on the level recorded in the previous three sampling periods (i.e., PMt-1, PMt-2, and PMt-3), the number of LD vehicles in the seventh past sampling period (LDt-7), and the number of HD vehicles measured 80 sec previous to the current sampling period (HDt-8). On a 10-sec period basis, the model results indicate that HD vehicles contributed, on average, 3 times more to above-road PM lidar signals than did LD vehicles. The observed lag in the relationship between vehicle types and the lidar signal 20 m above the road suggests that resuspended road dust, rather than tailpipe exhaust emissions, was the main source of the detected PM. Detection of road dust at such heights above the road suggests the need for investigating the processes governing the vertical transport and recycling of PM over the road as a function of vehicle dynamics under a range of meteorological conditions.     

Evaluation of particulate matter emissions from non-passenger diesel vehicles in Qatar

ABSTRACT

Road traffic is one of the main sources of particulate matter (PM) in the atmosphere. Despite its importance, there are significant challenges in the quantitative evaluation of its contribution to airborne concentrations. In order to propose effective mitigation scenarios, the proportions of PM traffic emissions, whether they are exhaust or non-exhaust emissions, should be evaluated for any given geographical location. In this work, we report on the first study to evaluate particulate matter emissions from all registered heavy duty diesel vehicles in Qatar. The study was applied to an active traffic zone in urban Doha. Dust samples were collected and characterized for their shape and size distribution. It was found that the particle size ranged from few to 600 μm with the dominance of small size fraction (less than 100 μm). In-situ elemental composition analysis was conducted for side and main roads traffic dust, and compared with non-traffic PM. The results were used for the evaluation of the enrichment factor and preliminary source apportionment. The enrichment factor of anthropogenic elements amounted to 350. The traffic source based on sulfur elemental fingerprint was almost 5 times higher in main roads compared with the samples from non-traffic locations. Moreover, PM exhaust and non-exhaust emissions (tyre wear, brake wear and road dust resuspension) were evaluated. It was found that the majority of the dust was generated from tyre wear with 33% followed by road dust resuspension (31%), brake wear (19%) and then exhaust emissions with 17%. The low contribution of exhaust PM₁₀ emissions was due to the fact that the majority of the registered vehicle models were recently made and equipped with efficient exhaust PM reduction technologies.

Implication: This study reports on the first results related to the evaluation of PM emission from all registered diesel heavy duty vehicles in Qatar. In-situ XRF elemental analysis from main, side roads as well as non-traffic dust samples was conducted. Several characterization techniques were implemented and the results show that the majority of the dust was generated from tyre wear, followed by road dust resuspension and then brake wear; whereas exhaust emissions were tremendously reduced since the majority of the registered vehicle models were recently made and equipped with efficient exhaust PM reduction technologies. This implies that policy makers should place stringent measures on old vehicle license renewals and encourage the use of metro and public transportation.     

Characterization of the Fugitive Particulate Emissions from Construction Mud/Dirt Carryout

Abstract

Although the fugitive dust associated with construction mud/dirt carryout can represent a substantial portion of the particulate matter (PM) emissions inventory in non-attainment areas, it has not been well characterized by direct sampling methods. In this paper, a research program is described that directly determined both PM₁₀ and PM_2.5 (particles ≤10 and 2.5 μm in classical aerodynamic diameter, respectively) emission factors for mud/dirt carryout from a major construction project located in metropolitan Kansas City, MO. The program also assessed the contribution of automotive emissions to the total PM_2.5 burden and determined the baseline emissions from the test road. As part of the study, both time-integrated and continuous exposure-profiling methods were used to assess the PM emissions, including particle size and elemental composition. This research resulted in overall PM₁₀ and PM_2.5 emission factors of 6 and 0.2 g/vehicle, respectively. Although PM₁₀ is within the range of prior U.S. Environmental Protection Agency (EPA) guidance, the PM_2.5 emission factor is far lower than previous estimates published by EPA. In addition, based on both the particle size and chemical data obtained in the study, a major portion of the PM_2.5 emissions appears to be attributable to automotive exhaust from light-duty, gasoline-powered vehicles and not to the fugitive dust associated with re-entrained mud/dirt carryout.     

Seasonal ambient particulate matter and population health outcomes among communities impacted by road dust in British Columbia,Canada

In recent years, many air quality monitoring programs have favored measurement of particles less than 2.5 µm (PM_2.5) over particles less than 10 µm (PM₁₀) in light of evidence that health impacts are mostly from the fine fraction. However, the coarse fraction (PM_10-2.5) may have independent health impacts that support continued measurement of PM₁₀ in some areas, such as those affected by road dust. The objective of this study was to evaluate the associations between different measures of daily PM exposure and two daily indicators of population health in seven communities in British Columbia, Canada, where road dust is an ongoing concern. The measures of exposure were PM₁₀, PM_2.5, PM_10-2.5, PM_2.5 adjusted for PM_10-2.5, and PM_10-2.5 adjusted for PM_2.5. The indicators of population health were dispensations of the respiratory reliever medication salbutamol sulfate and nonaccidental mortality. This study followed a time-series design using Poisson regression over a 2003–2015 study period, with analyses stratified by three seasons: residential woodsmoke in winter; road dust in spring; and wildfire smoke in summer. A random-effects meta-analysis was conducted to establish a pooled estimate. Overall, an interquartile range increase in daily PM_10-2.5 was associated with a 3.6% [1.6, 5.6] increase in nonaccidental mortality during the road dust season, which was reduced to 3.1% [0.8, 5.4] after adjustment for PM_2.5. The adjusted coarse fraction had no effect on salbutamol dispensations in any season. However, an interquartile range increase in PM_2.5 was associated with a 2.7% [2.0, 3.4] increase in dispensations during the wildfire season. These analyses suggest different impacts of different PM fractions by season, with a robust association between the coarse fraction and nonaccidental mortality in communities and periods affected by road dust. We recommend that PM₁₀ monitoring networks be maintained in these communities to provide feedback for future dust mitigation programs.

Implications: There was a significant association between daily concentrations of the coarse fraction and nonaccidental mortality during the road dust season, even after adjustment for the fine fraction. The acute and chronic health effects associated with exposure to the coarse fraction remain unclear, which supports the maintenance of PM₁₀ monitoring networks to allow for further research in communities affected by sources such as road dust.     

Application of Infrared Spectroscopy to Exhaust Gas Analysis

Abstract

The Mohave Valley region of southern Nevada/southwestern Arizona has experienced elevated particulate concentrations and is classified as a PM₁₀ nonattainment area. Anthropogenic aerosol sources in the area include the Mohave Power Project (MPP), a 1,580-MW coal-fired power plant; motor vehicles; construction activities; and paved and unpaved road dust and disturbed desert soil. Aerosols may also be transported long distances from other areas, such as the Los Angeles Basin. Based on the infrequency of plume contact at sites in the valley (as determined by SO₂ measurements), it was believed that the contribution of the MPP to primary PM₁₀ was minimal and that fugitive dust was the primary source of ambient particulate matter.

To evaluate the magnitude of source contributors, PM₁₀ measurements were made using a medium-volume sampler along with ancillary meteorological and air quality measurements in the Mohave Valley at Bullhead City, Arizona, for a period of longer than one year (September 1988 through mid-October 1989). The aerosol filter samples were analyzed for mass, elements, ions, and carbon. Source apportionment using the Chemical Mass Balance (CMB) receptor model was performed. On average, geological dust was the major contributor to PM10 (79.5%), followed by primary motor vehicle sources (16.7%), secondary ammonium sulfate (3.5%), secondary ammonium nitrate (0.1%), and primary coal-fired power plant emissions (0.1%).     

Development and Preliminary Evaluation of a Particulate Matter Emission Factor Model for European Motor Vehicles

ABSTRACT

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 um, either from published data or from user-defined size distributions.

A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM₁₀, PM₅, PM₂₅, and PM₁] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway).

A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM₁₀ was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

Monitoring of dust emission on gravel roads: Development of a mobile methodology and examination of horizontal diffusion

Traffic-generated fugitive dust on gravel roads impairs visibility and deposits on the adjacent environment. Particulate matter smaller than 10 μm in diameter (PM₁₀) is also associated with human health problems. Dust emission strength depends on the composition of granular material, road moisture, relative humidity, local climate (precipitation, wind velocity, etc.), and vehicle characteristics.The objectives of this study were to develop a reliable and rapid mobile methodology to measure dust concentrations on gravel roads, evaluate the precision and repeatability of the methodology and correspondence with the currently used visual assessment technique. Downwind horizontal diffusion was studied to evaluate the risk of exceeding the maximum allowed particulate matter concentration in ambient air near gravel roads according to European Council Directive [European Council Directive 1999/30/EC of 22 April 1999 relating to limit values for sulphur dioxide, nitrogen dioxide and oxides of nitrogen, particulate matter and lead in ambient air. Official Journal of the European Communities. L163/41.].A TSI DustTrak Aerosol Monitor was mounted on an estate car travelling along test sections treated with various dust suppressants. Measured PM₁₀ concentrations were compared to visual assessments performed at the same time. Airborne particles were collected in filters mounted behind the vehicle to compare the whole dust fraction with the PM₁₀ concentration. For measuring the horizontal diffusion, DustTraks were placed at various distances downwind of a dusty road section.The mobile methodology was vehicle and speed dependent but not driver dependent with pre-specified driving behaviours. A high linear correlation between PM₁₀ of different vehicles makes relative measurements of dust concentrations possible. The methodology gives continuous data series, mobility, and easy handling and provides fast, reliable and inexpensive measurements for estimating road conditions to make road maintenance more efficient.Good correlations between measured PM₁₀-values, visually assessed dust generation and dust collected in filters were obtained. PM₁₀ seems to be correlated to the whole dust fraction that impairs visibility on gravel roads.A decay in PM₁₀ concentration as a function of distance from the road was observed. Measured particles principally did not travel further than 45 m from the road. The risk of exceeding the PM₁₀ concentration stated in the EC-directive seems small.     

PM Emissions Emanating from Limited-Access Highways

ABSTRACT

Motor vehicle contributions to primary particulate matter (PM) emissions include exhaust, tire wear, brake and clutch wear, and resuspended road dust. Relatively few field studies have been conducted to quantify fleetaverage exhaust emissions for actual on-road conditions. Therefore, direct measurements of motor vehicle-related PM emissions are warranted. In this study, PM₁₀ and PM_2.5 mass concentrations were measured near two major highways in the St. Louis area over the period from February–April 1997. Samplers were deployed both upwind and downwind of the roadways to capture the transport and dispersion of PM with distance from the roadway. The observed microscale concentration fields were compared to estimates using the PART5 emission factor model together with the CALINE4 highway dispersion model. Traffic- induced PM mass concentrations observed downwind of the roadway were always less than PART5/CALINE4 predictions; average percent differences for observed traffic-induced mass concentrations compared to predicted values were ?34% for PM_2.5 and -70% for PM₁₀. In most cases, the observed PM concentration decay with increasing distance from the roadway was steeper than predicted by dispersion modeling. Motor vehicle-induced emission factors were reconstructed by fitting CALINE4 to the observed concentration data with the emission factor as the sole adjustable parameter. Reconstructed fleet-average motor vehicle emission factors for the urban interstate highway were 0.03–0.04 g/VMT for both PM_2.5 and PM₁₀, while the fleet-average emission factors for the rural interstate highway were 0.2 and 0.3 g/VMT for PM_2.5 and PM₁₀, respectively.     

Road Dust Resuspension in the Vicinity of Limestone Quarries in Jordan

Abstract

Many areas in Jordan suffer from elevated levels of coarse particulate matter (PM₁₀). One potentially significant source of the observed PM is the resuspension of road dust in the vicinity of limestone quarries. To obtain data to assess the impact from this source, PM₁₀ road dust resus-pension factors near Abusiiah, a town to the north east of Amman surrounded by many quarries and brick factories, were measured. Measurements included PM₁₀ mass, particle size distributions, wind speed, and wind direction.The results showed that PM₁₀ concentrations could be as high as 600 µg/m³, and most of the airborne PM is in the coarse fraction. Loading trucks play a major role in resus-pending road dust, with an observed PM₁₀ emission rate of >6000 mg/km.     

PM composition and source reconciliation in Mexico City

PM_2.5 and PM₁₀ were collected during 24-h sampling intervals from March 1st to 31st, 2006 during the MILAGRO campaign carried out in Mexico City's northern region, in order to determine their chemical composition, oxidative activity and the estimation of the source contributions during the sampling period by means of the chemical mass balance (CMB) receptor model. PM_2.5 concentrations ranged from 32 to 70 μg m⁻³ while that of PM10 did so from 51 to 132 μg m⁻³. The most abundant chemical species for both PM fractions were: OC, EC, SO₄²⁻, NO₃⁻, NH₄⁺, Si, Fe and Ca. The majority of the PM mass was comprised of carbon, up to about 52% and 30% of the PM2.5 and PM10, respectively. PM2.5 constituted more than 50% of PM10. The redox activity, assessed by the dithiothreitol (DTT) assay, was greater for PM_2.5 than for PM₁₀, and did not display significant differences during the sampling period. The PM_2.5 source reconciliation showed that in average, vehicle exhaust emissions were its most important source in an urban site with a 42% contribution, followed by re-suspended dust with 26%, secondary inorganic aerosols with 11%, and industrial emissions and food cooking with 10% each. These results had a good agreement with the Emission Inventory. In average, the greater mass concentration occurred during O₃S that corresponds to a wind shift initially with transport to the South but moving back to the North. Taken together these results show that PM chemical composition, oxidative potential, and source contribution is influenced by the meteorological conditions.     

Temporal variations of fine and coarse particulate matter sources in Jeddah,Saudi Arabia

This study provides the first comprehensive analysis of the seasonal variations and weekday/weekend differences in fine (aerodynamic diameter <2.5 μm; PM_2.5) and coarse (aerodynamic diameter 2.5–10 μm; PM_2.5–10) particulate matter mass concentrations, elemental constituents, and potential source origins in Jeddah, Saudi Arabia. Air quality samples were collected over 1 yr, from June 2011 to May 2012 at a frequency of three times per week, and analyzed. The average mass concentrations of PM_2.5 (21.9 μg/m³) and PM₁₀ (107.8 μg/m³) during the sampling period exceeded the recommended annual average levels by the World Health Organization (WHO) for PM_2.5 (10 μg/m³) and PM₁₀ (20 μg/m³), respectively. Similar to other Middle Eastern locales, PM_2.5–10 is the prevailing mass component of atmospheric particulate matter at Jeddah, accounting for approximately 80% of the PM₁₀ mass. Considerations of enrichment factors, absolute principal component analysis (APCA), concentration roses, and backward trajectories identified the following source categories for both PM_2.5 and PM_2.5–10: (1) soil/road dust, (2) incineration, and (3) traffic; and for PM_2.5 only, (4) residual oil burning. Soil/road dust accounted for a major portion of both the PM_2.5 (27%) and PM_2.5–10 (77%) mass, and the largest source contributor for PM_2.5 was from residual oil burning (63%). Temporal variations of PM_2.5–10 and PM_2.5 were observed, with the elevated concentration levels observed for mass during the spring (due to increased dust storm frequency) and on weekdays (due to increased traffic). The predominant role of windblown soil and road dust in both the PM_2.5 and PM_2.5–10 masses in this city may have implications regarding the toxicity of these particles versus those in the Western world where most PM health assessments have been made in the past. These results support the need for region-specific epidemiological investigations to be conducted and considered in future PM standard setting.

Implications: Temporal variations of fine and coarse PM mass, elemental constituents, and sources were examined in Jeddah, Saudi Arabia, for the first time. The main source of PM_2.5–10 is natural windblown soil and road dust, whereas the predominant source of PM_2.5 is residual oil burning, generated from the port and oil refinery located west of the air sampler, suggesting that targeted emission controls could significantly improve the air quality in the city. The compositional differences point to a need for health effect studies to be conducted in this region, so as to directly assess the applicability of the existing guidelines to the Middle East air pollution.     

Lidar-assisted measurement of PM10 emissions from agricultural tilling in California's San Joaquin Valley – Part I: lidar

Vertical profiling with point samplers is an accepted method for quantifying the fluxes of PM₁₀ from non-point fugitive dust sources, but is limited by uncertainty in estimates of the actual height of the dust plume, especially for plumes that exceed the highest sampling height. Agricultural land preparation operations in the San Joaquin Valley were monitored using upwind–downwind vertical PM₁₀ profiles and data collected during the first successful experiment to include light detection and ranging (lidar), in 1998, were analyzed to provide modeling criteria for the 1996 and 1997 data. A series of six comprehensive PM₁₀ tests with concurrent lidar data was examined to: (a) develop a framework for analyzing upwind–downwind point PM₁₀ concentration profiles of land preparation operations (disking, listing, root cutting, and ripping) and (b) identify conditions under which the field sampling strategies affect the reproducibility of PM₁₀ concentration measurements. Lidar data were used to verify that the plume heights and shapes extrapolated from the point sampler vertical profiles adequately described the plumes. The shortcomings of the vertical profiling technique and lidar methods are discussed in the light of developing efficient robust methods for accurate PM₁₀ emissions quantification from complex non-point sources.     

Quantifying road dust resuspension in urban environment by Multilinear Engine: A comparison with PMF2

Atmospheric PM pollution from traffic comprises not only direct emissions but also non-exhaust emissions because resuspension of road dust that can produce high human exposure to heavy metals, metalloids, and mineral matter. A key task for establishing mitigation or preventive measures is estimating the contribution of road dust resuspension to the atmospheric PM mixture. Several source apportionment studies, applying receptor modeling at urban background sites, have shown the difficulty in identifying a road dust source separately from other mineral sources or vehicular exhausts. The Multilinear Engine (ME-2) is a computer program that can solve the Positive Matrix Factorization (PMF) problem. ME-2 uses a programming language permitting the solution to be guided toward some possible targets that can be derived from a priori knowledge of sources (chemical profile, ratios, etc.). This feature makes it especially suitable for source apportionment studies where partial knowledge of the sources is available.In the present study ME-2 was applied to data from an urban background site of Barcelona (Spain) to quantify the contribution of road dust resuspension to PM₁₀ and PM_2.5 concentrations. Given that recently the emission profile of local resuspended road dust was obtained (Amato, F., Pandolfi, M., Viana, M., Querol, X., Alastuey, A., Moreno, T., 2009. Spatial and chemical patterns of PM₁₀ in road dust deposited in urban environment. Atmospheric Environment 43 (9), 1650–1659), such a priori information was introduced in the model as auxiliary terms of the object function to be minimized by the implementation of the so-called “pulling equations”.ME-2 permitted to enhance the basic PMF solution (obtained by PMF2) identifying, beside the seven sources of PMF2, the road dust source which accounted for 6.9 μg m^?3 (17%) in PM₁₀, 2.2 μg m^?3 (8%) of PM_2.5 and 0.3 μg m^?3 (2%) of PM₁. This reveals that resuspension was responsible of the 37%, 15% and 3% of total traffic emissions respectively in PM₁₀, PM_2.5 and PM₁. Therefore the overall traffic contribution resulted in 18 μg m^?3 (46%) in PM₁₀, 14 μg m^?3 (51%) in PM_2.5 and 8 μg m^?3 (48%) in PM₁. In PMF2 this mass explained by road dust resuspension was redistributed among the rest of sources, increasing mostly the mineral, secondary nitrate and aged sea salt contributions.     

A detailed investigation of ambient aerosol composition and size distribution in an urban atmosphere

This research was executed between March 2009 and March 2010 to monitor particulate matter size distribution and its composition in Istanbul. Particulate matter composition was determined using ion chromatography and inductively coupled plasma optical emission spectrometry. The sampling point is adjacent to a crowded road and the Bosporus Strait. Two prevailing particulate modes are found throughout PM₁₀ by sampling with a nine-stage low-volume cascade impactor. First mode in the fine mode is found to be between 0.43 and 0.65 μm, whereas the other peak was observed between 3.3 and 4.7 μm, referring to the coarse mode. The mean PM₁₀ concentration was determined as 41.2 μg/m³, with a standard deviation of 16.92 μg/m³. PM_0.43 had the highest mean concentration value of 10.67 μg/m³, making up nearly one fourth of the total PM₁₀ mass. For determining the effect of traffic on particulate matter (PM) composition and distribution, four different sampling cycles were applied: entire day, nighttime, rush hour, and rush hour at weekdays. SO ₄ ^?2 and organic carbon/elemental carbon proportions are found to be lower in night samples, representing a decrease in traffic. The long-range transports of dust storms were observed during the sampling periods. Their effects were determined analytically and their route models were run by the HYSPLIT model and validated through satellite photographs taken by the NASA Earth Observatory.     

Wintertime PM2.5 and PM10 Source Apportionment at Sacramento,California

ABSTRACT

The chemical mass balance (CMB) model was applied to winter (November through January) 1991–1996 PM2.5 and PM10 data from the Sacramento 13th and T Streets site in order to identify the contributions from major source categories to peak 24-hr ambient PM_2.5 and PM₁₀ levels. The average monthly PM₁₀ monitoring data for the nine-year period in Sacramento County indicate that elevated concentrations are typical in the winter months. Concentrations on days of highest PM₁₀ are dominated by the PM2.5 fraction. One factor contributing to increased PM_2.5 concentrations in the winter is meteorology (cool temperatures, low wind speeds, low inversion layers, and more humid conditions) that favors the formation of secondary nitrate and sulfate aerosols. Residential wood burning also elevates fine particulate concentrations in the Sacramento area.

The results of the CMB analysis highlight three key points. First, the source apportionment results indicate that primary motor vehicle exhaust and wood smoke are significant sources of both PM_2.5 and PM₁₀ in winter. Second, nitrates, secondarily formed as a result of motor-vehicle and other sources of nitrogen oxide (NO_x), are another principal cause of the high PM_2.5 and PM₁₀ levels during the winter months. Third, fugitive dust, whether it is resuspended soil and dust or agricultural tillage, is not the major contributor to peak winter PM_2.5 and PM10 levels in the Sacramento area.     

Size and Composition Distributions of Particulate Matter Emissions: Part 1—Light-Duty Gasoline Vehicles

Abstract

Size-resolved particulate matter (PM) emitted from light-duty gasoline vehicles (LDGVs) was characterized using filter-based samplers, cascade impactors, and scanning mobility particle size measurements in the summer 2002. Thirty LDGVs, with different engine and emissions control technologies (model years 1965–2003; odometer readings 1264–207,104 mi), were tested on a chassis dynamometer using the federal test procedure (FTP), the unified cycle (UC), and the correction cycle (CC). LDGV PM emissions were strongly correlated with vehicle age and emissions control technology. The oldest models had average ultrafine PM_0.1 (0.056- to 0.1-μm aerodynamic diameter) and fine PM_1.8 (≤1.8-μm aerodynamic diame ter) emission rates of 9.6 mg/km and 213 mg/km, respectively. The newest vehicles had PM_0.1 and PM_1.8 emis sions of 51 μg/km and 371 μg/km, respectively. Light duty trucks and sport utility vehicles had PM_0.1 and PM_1.8 emissions nearly double the corresponding emission rates from passenger cars. Higher PM emissions were associated with cold starts and hard accelerations. The FTP driving cycle produced the lowest emissions, followed by the UC and the CC. PM mass distributions peaked between 0.1-and 0.18-μm particle diameter for all vehicles except those emitting visible smoke, which peaked between 0.18 and 0.32 μm. The majority of the PM was composed of carbonaceous material, with only trace amounts of water-soluble ions. Elemental carbon (EC) and organic matter (OM) had similar size distributions, but the EC/OM ratio in LDGV exhaust particles was a strong function of the adopted emissions control technology and of vehicle maintenance. Exhaust from LDGV classes with lower PM emissions generally had higher EC/OM ratios. LDGVs adopting newer technologies were characterized by the highest EC/OM ratios, whereas OM dominated PM emissions from older vehicles. Driving cycles with cold starts and hard accelerations produced higher EC/OM ratios in ultrafine particles.     

Estimation of road vehicle exhaust emissions from 1992 to 2010 and comparison with air quality measurements in Genoa,Italy

An investigation into road transport exhaust emissions in the Genoa urban area was performed by comparing the quantities of carbon monoxide (CO), nitrogen oxides (NO_x), nitrogen dioxide (NO₂) and particulate matter (PM) emitted by different vehicle categories with air quality measurements referred to the same pollutants. Exhaust emissions were evaluated by applying the PROGRESS (computer PROGramme for Road vehicle EmiSSions evaluation) code, developed by the Internal Combustion Engines Group of the University of Genoa, to eight different years (from 1992 to 2010), considering spark ignition and Diesel passenger cars and light duty vehicles, heavy duty vehicles and buses, motorcycles and mopeds. Changes in terms of vehicles number, mileage and total emissions are presented together with relative distributions among the various vehicle categories. By comparing 1992 and 2010 data, calculated trends show a 7% increase in the number of vehicles, with total mileage growing at a faster rate (approx. 22%); total emissions decrease considerably, by approximately 50% for NO_x and PM, 70% for HC and 80% for CO, due to improvements in engines and fuels forced by the stricter European legislation and the fleet renewal, while primary NO₂ emission will be very close to 1992 level, after a decrease of about 18% in 2000.Air quality was analysed by selecting traffic and background measuring stations from the monitoring network managed by the Environmental Department of the Province of Genoa: average annual concentrations of considered pollutants from 1994 to 2007 were calculated in order to obtain the relative historical trends and compare them with European public health limits and with road vehicle emissions. Though an important reduction in pollutant concentrations has been achieved as a consequence of cleaner vehicles, some difficulties in complying with present and/or future NO₂ and PM₁₀ limits are also apparent, thus requiring suitable measures to be taken by the local authorities.     

Testing Re-entrained Aerosol Kinetic Emissions from Roads : a new approach to infer silt loading on roadways

PM₁₀ and PM_2.5 emissions from roadways are currently estimated using the silt loading on the road surface as a surrogate for the emissions potential of road dust. While the United States Environmental Protection Agency prescribes this method in AP-42, there is considerable cost associated with silt loading measurements; it is feasible to sample only a small portion of a roadway network. A new approach for measuring the concentration of suspendable PM₁₀ above road surfaces has been developed to obtain a more spatially representative estimate of a road's potential to emit dust. The Testing Re-entrained Aerosols Kinetic Emissions from Roads (TRAKER) system uses real-time aerosol sensors mounted on a vehicle to measure the concentration of dust suspended from the road while the vehicle is in motion. When coupled with a Global Positioning System (GPS) instrument, TRAKER can be used to efficiently survey the changes in suspendable particles due to varying road conditions over a large spatial domain.In a recent study on paved roads in Las Vegas, the TRAKER system was compared with collocated silt loading measurements. The TRAKER system was also used to survey the relative amounts of suspendable road dust on approximately 300 miles of paved roads. The system provides a unique perspective on road dust sources and their spatial distribution.Results of this study indicated that the difference of the PM₁₀ concentrations measured behind the tire and on the hood is exponentially related to vehicle speed. This was an interesting finding because current AP-42 road dust emissions estimation methods do not include vehicle speed as a factor in the emissions calculations. The experiment also demonstrated that the distribution of suspendable material on roadways is highly variable and that a large number of samples are needed to represent road dust emissions potential on an urban scale for a variety of road and activity conditions.     

Near-road air pollutant concentrations of CO and PM2.5: A comparison of MOBILE6.2/CALINE4 and generalized additive models

The contribution of vehicular traffic to air pollutant concentrations is often difficult to establish. This paper utilizes both time-series and simulation models to estimate vehicle contributions to pollutant levels near roadways. The time-series model used generalized additive models (GAMs) and fitted pollutant observations to traffic counts and meteorological variables. A one year period (2004) was analyzed on a seasonal basis using hourly measurements of carbon monoxide (CO) and particulate matter less than 2.5 μm in diameter (PM_2.5) monitored near a major highway in Detroit, Michigan, along with hourly traffic counts and local meteorological data. Traffic counts showed statistically significant and approximately linear relationships with CO concentrations in fall, and piecewise linear relationships in spring, summer and winter. The same period was simulated using emission and dispersion models (Motor Vehicle Emissions Factor Model/MOBILE6.2; California Line Source Dispersion Model/CALINE4). CO emissions derived from the GAM were similar, on average, to those estimated by MOBILE6.2. The same analyses for PM_2.5 showed that GAM emission estimates were much higher (by 4–5 times) than the dispersion model results, and that the traffic-PM_2.5 relationship varied seasonally. This analysis suggests that the simulation model performed reasonably well for CO, but it significantly underestimated PM_2.5 concentrations, a likely result of underestimating PM_2.5 emission factors. Comparisons between statistical and simulation models can help identify model deficiencies and improve estimates of vehicle emissions and near-road air quality.     

Windblown Dust Contributes to High PM25 Concentrations

ABSTRACT

The revised National Ambient Air Quality Standards for PM include fine particulate standards based upon mass measurements of PM₂₅. It is possible in arid and semi-arid regions to observe significant coarse mode intrusion in the PM_2.5 measurement. In this work, continuous PM₁₀, PM_2.5, and PM_1.0 were measured during several windblown dust events in Spokane, WA. PM_{2 5} constituted ~30% of the PM₁₀ during the dust event days, compared with ~48% on the non-dusty days preceding the dust events. Both PM₁₀ and PM_2.5 were enhanced during the dust events. However, PM_1.0 was not enhanced during dust storms that originated within the state of Washington. During a dust storm that originated in Asia and impacted Spokane, PM_1.0 was also enhanced, although the Asian dust reached Washington during a period of stagnation and poor dispersion, so that local sources were also contributing to high particulate levels. The “intermodal” region of PM, defined as particles ranging in aerodynamic size from 1.0 to 2.5 um, was found to represent a significant fraction of PM₂₅ (~51%) during windblown dust events, compared with 28% during the non-dusty days before the dust events.