Evaluation of Regenerative-air Vacuum Street Sweeping on Geological Contributions to PM10

Street sweeping is often proposed as a means of reducing the emissions from paved roads. The objective of this study was to evaluate the effectiveness of street sweeping on ambient particulate matter concentrations and to determine the difference In source contributions to PM10 concentrations between street sweeping and non-street sweeping periods.

Chemically-speciated measurements of PM10 and PM2.5 were taken in the commercial section of Reno, Nevada, for a one-month sampling period. The Chemical Mass Balance (CMB) model was applied to these data and an average of approximately 50 percent of the PM10 was apportioned to resuspended geological material. During half of the sampling period, streets In the vicinity of the sampling site were completely swept with a regenerative-air vacuum sweeper, while no sweeping was performed during the remainder of the experiment. Ratios of primary geological contributions divided by primary motor vehicle contributions to PM10 were compared between sweeping and non-sweeping periods using analysis of variance. This ratio of source contributions minimizes the effects of variations in traffic volume and meteorological dispersion. No significant differences in geological contributions to PM10 were detected as a result of regenerative-air vacuum street sweeping.     

Determination of PM10 emission rates from street sweepers

The use of street sweepers to clean paved roads, particularly after high-wind events, has been proposed as a PM10 control method. Using an artificial tunnel, the emission rates for several street sweepers were quantified under actual operating conditions. The tunnel was a tent enclosure, 6.1 x 4.3 x 73 m, open on both ends. PM10 concentrations were measured at the inlet and outlet while a sweeper removed sand deposited along the length. Measurements were made using a specialized low-volume filter sampler and an integrating nephelometer. The volume of air passing through the tunnel was measured by releasing an inert tracer, sulfur hexafluoride, at the inlet and measuring its concentration at the outlet. A large difference in emission rates between vacuum-type sweepers was observed, with rates varying from 5 to 100 mg m-1 swept. For the cleanest sweepers, the background rates (collected by sweeping clean pavement) were about half of the total PM10 emission rate. These background emission rates likely were from diesel exhaust; background rates for the single gasoline-powered sweeper were below detection. Particle light scattering data confirmed the filter collection results. The artificial tunnel approach would be useful in measuring total emissions from other mobile and stationary sources.     

Trends in primary particulate matter emissions from Canadian agriculture

Particulate matter (PM) has long been recognized as an air pollutant due to its adverse health and environmental impacts. As emission of PM from agricultural operations is an emerging air quality issue, the Agricultural Particulate Matter Emissions Indicator (APMEI) has been developed to estimate the primary PM contribution to the atmosphere from agricultural operations on Census years and to assess the impact of practices adopted to mitigate these emissions at the soil landscape polygon scale as part of the agri-environmental indicator report series produced by Agriculture and Agri-Food Canada. In the APMEI, PM emissions from animal feeding operations, wind erosion, land preparation, crop harvest, fertilizer and chemical application, grain handling, and pollen were calculated and compared for the Census years of 1981-2006. In this study, we present the results for PM10 and PM2.5, which exclude chemical application and pollen sources as they only contribute to total suspended particles. In 2006, PM emissions from agricultural operations were estimated to be 652.6 kt for PM10 and 158.1 kt for PM2.5. PM emissions from wind erosion and land preparation account for most of PM emissions from agricultural operations in Canada, contributing 82% of PM10 and 76% of PM2.5 in 2006. Results from the APMEI show a strong reduction in PM emissions from agricultural operations between 1981 and 2006, with a decrease of 40% (442.8 kt) for PM10 and 47% (137.7 kt) for PM2.5. This emission reduction is mainly attributed to the adoption of conservation tillage and no-till practices and the reduction in the area of summer fallow land.     

Trends in primary particulate matter emissions from Canadian agriculture

Particulate matter (PM) has long been recognized as an air pollutant due to its adverse health and environmental impacts. As emission of PM from agricultural operations is an emerging air quality issue, the Agricultural Particulate Matter Emissions Indicator (APMEI) has been developed to estimate the primary PM contribution to the atmosphere from agricultural operations on Census years and to assess the impact of practices adopted to mitigate these emissions at the soil landscape polygon scale as part of the agri-environmental indicator report series produced by Agriculture and Agri-Food Canada. In the APMEI, PM emissions from animal feeding operations, wind erosion, land preparation, crop harvest, fertilizer and chemical application, grain handling, and pollen were calculated and compared for the Census years of 1981–2006. In this study, we present the results for PM₁₀ and PM_2.5, which exclude chemical application and pollen sources as they only contribute to total suspended particles. In 2006, PM emissions from agricultural operations were estimated to be 652.6 kt for PM₁₀ and 158.1 kt for PM_2.5. PM emissions from wind erosion and land preparation account for most of PM emissions from agricultural operations in Canada, contributing 82% of PM₁₀ and 76% of PM_2.5 in 2006. Results from the APMEI show a strong reduction in PM emissions from agricultural operations between 1981 and 2006, with a decrease of 40% (442.8 kt) for PM₁₀ and 47% (137.7 kt) for PM_2.5. This emission reduction is mainly attributed to the adoption of conservation tillage and no-till practices and the reduction in the area of summerfallow land.

Implications: Increasing sustainability in agriculture often means adapting management practices to have a beneficial impact on the environment while maintaining or increasing production and economic benefits. We developed an inventory of primary PM emissions from agriculture in Canada to better quantify the apportionment, spatial distribution, and trends for Census years 1981–2006. We found major reductions of 40% in PM₁₀ and 47% in PM_2.5 emissions over the 25-yr period as a co-benefit of increasing carbon sequestration in agricultural soils. Indeed, farmers adopted conservation tillage/no-till practices, increased usage of cover crops, and reduced summerfallow, in order to increase soil organic matter and reduce carbon dioxide emissions, which also reduced primary PM emissions, although the agricultural production increased over the period.     

Deriving fuel-based emission factor thresholds to interpret heavy-duty vehicle roadside plume measurements

Remote sensing devices have been used for decades to measure gaseous emissions from individual vehicles at the roadside. Systems have also been developed that entrain diluted exhaust and can also measure particulate matter (PM) emissions. In 2015, the California Air Resources Board (CARB) reported that 8% of in-field diesel particulate filters (DPF) on heavy-duty (HD) vehicles were malfunctioning and emitted about 70% of total diesel PM emissions from the DPF-equipped fleet. A new high-emitter problem in the heavy-duty vehicle fleet had emerged. Roadside exhaust plume measurements reflect a snapshot of real-world operation, typically lasting several seconds. In order to relate roadside plume measurements to laboratory emission tests, we analyzed carbon dioxide (CO₂), oxides of nitrogen (NO_X), and PM emissions collected from four HD vehicles during several driving cycles on a chassis dynamometer. We examined the fuel-based emission factors corresponding to possible exceedances of emission standards as a function of vehicle power. Our analysis suggests that a typical HD vehicle will exceed the model year (MY) 2010 emission standards (of 0.2 g NO_X/bhp-hr and 0.01 g PM/bhp-hr) by three times when fuel-based emission factors are 9.3 g NO_X/kg fuel and 0.11 g PM/kg using the roadside plume measurement approach. Reported limits correspond to 99% confidence levels, which were calculated using the detection uncertainty of emissions analyzers, accuracy of vehicle power calculations, and actual emissions variability of fixed operational parameters. The PM threshold was determined for acceleration events between 0.47 and 1.4 mph/sec only, and the NO_X threshold was derived from measurements where after-treatment temperature was above 200°C. Anticipating a growing interest in real-world driving emissions, widespread implementation of roadside exhaust plume measurements as a compliment to in-use vehicle programs may benefit from expanding this analysis to a larger sample of in-use HD vehicles.

Implications: Regulatory agencies, civil society, and the public at large have a growing interest in vehicle emission compliance in the real world. Leveraging roadside plume measurements to identify vehicles with malfunctioning emission control systems is emerging as a viable new and useful method to assess in-use performance. This work proposes fuel-based emission factor thresholds for PM and NOx that signify exceedances of emission standards on a work-specific basis by analyzing real-time emissions in the laboratory. These thresholds could be used to prescreen vehicles before roadside enforcement inspection or other inquiry, enhance and further develop emission inventories, and potentially develop new requirements for heavy-duty inspection and maintenance (I/M) programs, including but not limited to identifying vehicles for further testing.     

Modeling wintertime particulate matter formation in central California

A wintertime episode during the 2000 California Regional PM Air Quality Study (CRPAQS) was simulated with the air quality model CMAQ–MADRID. Model performance was evaluated with 24-h average measurements available from CRPAQS. Modeled organic matter (OM) was dominated by emissions, which were probably significantly under-represented, especially in urban areas. In one urban area, modeled daytime nitrate concentrations were low and evening concentrations were high. This diurnal profile was not explained by the partition of nitrate between the gas and particle phases, because gaseous nitric acid concentrations were low compared to PM nitrate. Both measured and simulated nitrate concentrations aloft were lower than at the surface at two tower locations during this episode. Heterogeneous reactions involving NO₃ and N₂O₅ accounted for significant nitrate production in the model, resulting in a nighttime peak. The sensitivity of PM nitrate to precursor emissions varied with time and space. Nitrate formation was on average sensitive to NO_x emissions. However, for some periods at urban locations, reductions in NO_x caused the contrary response of nitrate increases. Nitrate was only weakly sensitive to reductions in anthropogenic VOC emissions. Nitrate formation tended to be insensitive to the availability of ammonia at locations with high nitrate, although the spatial extent of the nitrate plume was reduced when ammonia was reduced. Reductions in PM emissions caused OM to decrease, but had no effect on nitrate despite the role of heterogeneous reactions. A control strategy that focuses on NO_x and PM emissions would be effective on average, but reductions in VOC and NH₃ emissions would also be beneficial for certain times and locations.     

Theoretical study of the impact of particulate matter gravitational settling on ambient coarse particulate matter monitoring for agricultural emissions

The particle size distributions (PSDs) of particulate matter (PM) in the downwind plume from simulated sources of a cotton gin were analyzed to determine the impact of PM settling on PM monitoring. The PSD of PM in a plume varies as a function of gravitational settling. Gravitational settling has a greater impact on the downwind PSD from sources with PSDs having larger mass median diameters (MMDs). The change in PSD is a function of the source PSD of emitted PM, wind speed, and downwind distance. Both MMD and geometric standard deviation (GSD) in the downwind plume decrease with an increase in downwind distance and source MMD. The larger the source MMD, the greater the change in the downwind MMD and GSD. Also, the greater the distance from the source to the sampler, the greater the change in the downwind MMD and GSD. Variations of the PSD in the downwind plume significantly impact PM10 sampling errors associated with the U.S. Environmental Protection Agency (EPA) PM10 samplers. For the emission sources with MMD > 10 microm, the PM10 oversampling rate increases with an increase in downwind distance caused by the decrease of GSD of the PSD in the downwind plume. Gravitational settling of particles does not help reduce the oversampling problems associated with the EPA PM10 sampler. Furthermore, oversampling rates decrease with an increase of the wind speed.     

Measurement, analysis, and modeling of fine particulate matter in eastern North Carolina

An analysis of fine particulate data in eastern North Carolina was conducted to investigate the impact of the hog industry and its emissions of ammonia into the atmosphere. The fine particulate data are simulated using ISORROPIA, an equilibrium thermodynamic model that simulates the gas and aerosol equilibrium of inorganic atmospheric species. The observational data analyses show that the major constituents of fine particulate matter (PM2.5) are organic carbon, elemental carbon, sulfate, nitrate, and ammonium. The observed PM2.5 concentration is positively correlated with temperature but anticorrelated with wind speed. The correlation between PM2.5 and wind direction at some locations suggests an impact of ammonia emissions from hog facilities on PM2.5 formation. The modeled results are in good agreement with observations, with slightly better agreement at urban sites than at rural sites. The predicted total inorganic particulate matter (PM) concentrations are within 5% of the observed values under conditions with median initial total PM species concentrations, median relative humidity (RH), and median temperature. Ambient conditions with high PM precursor concentrations, low temperature, and high RH appear to favor the formation of secondary PM.     

Physical characterization of the fine particle emissions from commercial aircraft engines during the Aircraft Particle Emissions eXperiment (APEX) 1–3

The fine particulate matter (PM) emissions from nine commercial aircraft engine models were determined by plume sampling during the three field campaigns of the Aircraft Particle Emissions Experiment (APEX). Ground-based measurements were made primarily at 30 m behind the engine for PM mass and number concentration, particle size distribution, and total volatile matter using both time-integrated and continuous sampling techniques. The experimental results showed a PM mass emission index (EI) ranging from 10 to 550 mg kg^?1 fuel depending on engine type and test parameters as well as a characteristic U-shaped curve of the mass EI with increasing fuel flow for the turbofan engines tested. Also, the Teflon filter sampling indicated that ～40–80% of the total PM mass on a test-average basis was comprised of volatile matter (sulfur and organics) for most engines sampled. The number EIs, on the other hand, varied from ～10¹⁵ to 10¹⁷ particles kg^?1 fuel with the turbofan engines exhibiting a logarithmic decay with increasing fuel flow. Finally, the particle size distributions of the emissions exhibited a single primary mode that were lognormally distributed with a minor accumulation mode also observed at higher powers for all engines tested. The geometric (number) mean particle diameter ranged from 9.4 to 37 nm and the geometric standard deviation ranged from 1.3 to 2.3 depending on engine type, fuel flow, and test conditions.     

Application of a combined measurement and modeling method to quantify windblown dust emissions from the exposed playa at Mono Lake, California

Particulate matter < or =10 microm (PM10) emissions due to wind erosion can vary dramatically with changing surface conditions. Crust formation, mechanical disturbance, soil texture, moisture, and chemical content of the soil can affect the amount of dust emitted during a wind event. A refined method of quantifying windblown dust emissions was applied at Mono Lake, CA, to account for changing surface conditions. This method used a combination of real-time sand flux monitoring, ambient PM10 monitoring, and dispersion modeling to estimate dust emissions and their downwind impact. The method identified periods with high emissions and periods when the surface was stable (no sand flux), even though winds may have been high. A network of 25 Cox sand catchers (CSCs) was used to measure the mass of saltating particles to estimate sand flux rates across a 2-km2 area. Two electronic sensors (Sensits) were used to time-resolve the CSC sand mass to estimate hourly sand flux rates, and a perimeter tapered element oscillating microbalance (TEOM) monitor measured hourly PM10 concentrations. Hourly sand flux rates were related by dispersion modeling to hourly PM10 concentrations to back-calculate the ratio of vertical PM10 flux to horizontal sand flux (K-factors). Geometric mean K-factor values (K(f)) were found to change seasonally, ranging from 1.3 x 10(-5) to 5.1 x 10(-5) for sand flux measured at 15 cm above the surface (q15). Hourly PM10 emissions, F, were calculated by applying seasonal K-factors to sand flux measurements (F = K(f) x q15). The maximum hourly PM10 emission rate from the study area was 76 g/m2 x hr (10-m wind speed = 23.5 m/sec). Maximum daily PM10 emissions were estimated at 450 g/m2 x day, and annual emissions at 1095 g/m2 x yr. Hourly PM10 emissions were used by the U.S. Environmental Protection Agency (EPA) guideline AERMOD dispersion model to estimate downwind ambient impacts. Model predictions compared well with monitor concentrations, with hourly PM10 ranging from 16 to over 60,000 microg/m3 (slope = 0.89, R2 = 0.77).     

Simulation of the evolution of particle size distributions in a vehicle exhaust plume with unconfined dilution by ambient air

Over the past several years, numerous studies have linked ambient concentrations of particulate matter (PM) to adverse health effects, and more recent studies have identified PM size and surface area as important factors in determining the health effects of PM. This study contributes to a better understanding of the evolution of particle size distributions in exhaust plumes with unconfined dilution by ambient air. It combines computational fluid dynamics (CFD) with an aerosol dynamics model to examine the effects of different streamlines in an exhaust plume, ambient particle size distributions, and vehicle and wind speed on the particle size distribution in an exhaust plume. CFD was used to calculate the flow field and gas mixing for unconfined dilution of a vehicle exhaust plume, and the calculated dilution ratios were then used as input to the aerosol dynamics simulation. The results of the study show that vehicle speed affected the particle size distribution of an exhaust plume because increasing vehicle speed caused more rapid dilution and inhibited coagulation. Ambient particle size distributions had an effect on the smaller sized particles (approximately 10 nm range under some conditions) and larger sized particles (>2 microm) of the particle size distribution. The ambient air particle size distribution affects the larger sizes of the exhaust plume because vehicle exhaust typically contains few particles larger than 2 microm. Finally, the location of a streamline in the exhaust plume had little effect on the particle size distribution; the particle size distribution along any streamline at a distance x differed by less than 5% from the particle size distributions along any other streamline at distance x.     

Spatial and temporal characterization of PM2.5 mass concentrations in California, 1980-2007

Systematic measurement of fine particulate matter (aerodynamic diameter less than 2.5 microm [PM2.5]) mass concentrations began nationally with implementation of the Federal Reference Method (FRM) network in 1998 and 1999. In California, additional monitoring of fine particulate matter (PM) occurred via a dichotomous sampler network and several special studies carried out between 1982 and 2002. The authors evaluate the comparability of FRM and non-FRM measurements of PM2.5 mass concentrations and establish conversion factors to standardize fine mass measurements from different methods to FRM-equivalent concentrations. The authors also identify measurements of PM2.5 mass concentrations that do not agree with FRM or other independent PM2.5 mass measurements. The authors show that PM2.5 mass can be reconstructed to a high degree of accuracy (r2 > 0.9; mean absolute error approximately 2 microg m(-3)) from PM with an aerodynamic diameter < or =10 microm (PM10) mass and species concentrations when site-specific and season-specific conversion factors are used and a statewide record of fine PM mass concentrations by combining the FRM PM2.5 measurements, non-FRM PM2.5 measurements, and reconstructions of PM2.5 mass concentrations. Trends and spatial variations are evaluated using the integrated data. The rates of change of annual fine PM mass were negative (downward trends) at all 22 urban and 6 nonurban (Interagency Monitoring of Protected Visual Environments [IMPROVE]) monitoring locations having at least 15 yr of data during the period 1980-2007. The trends at the IMPROVE sites ranged from -0.05 to -0.25 microg m(-3) yr(-1) (median -0.11 microg m(-3) yr(-1)), whereas urban-site trends ranged from -0.13 to -1.29 microg m(-3) yr(-1) (median -0.59 microg m(-3) yr(-1)). The urban concentrations declined by a factor of 2 over the period of record, and these decreases were qualitatively consistent with changes in emissions of primary PM2.5 and gas-phase precursors of secondary PM. Mean PM2.5 mass concentrations ranged from 3.3 to 7.4 microg m(-3) at IMPROVE sites and from 9.3 to 37.1 microg m(-3) at urban sites.     

Effects of engine speed and accessory load on idling emissions from heavy-duty diesel truck engines

A nontrivial portion of heavy-duty vehicle emissions of NOx and particulate matter (PM) occurs during idling. Regulators and the environmental community are interested in curtailing truck idling emissions, but current emissions models do not characterize them accurately, and little quantitative data exist to evaluate the relative effectiveness of various policies. The objectives of this study were to quantify the effect of accessory loading and engine speed on idling emissions from a properly functioning, modern, heavy-duty diesel truck and to compare these results with data from earlier model year vehicles. It was found that emissions during idling varied greatly as a function of engine model year, engine speed, and accessory load conditions. For the 1999 model year Class 8 truck tested, raising the engine speed from 600 to 1050 rpm and turning on the air conditioning resulted in a 2.5-fold increase in NOx emissions in grams per hour, a 2-fold increase in CO2 emissions, and a 5-fold increase in CO emissions while idling. On a grams per gallon fuel basis, NOx emissions while idling were approximately twice as high as those at 55 mph. The CO2 emissions at the two conditions were closer. The NOx emissions from the 1999 truck while idling with air conditioning running were slightly more than those of two 1990 model year trucks under equivalent conditions, and the hydrocarbon (HC) and CO emissions were significantly lower. It was found that the NOx emissions used in the California Air Resources Board's (CARB) EMFAC2000 and the U.S. Environmental Protection Agency's (EPA) MOBILE5b emissions inventory models were lower than those measured in all of the idling conditions tested on the 1999 truck.     

Emission reductions from woody biomass waste for energy as an alternative to open burning

Woody biomass waste is generated throughout California from forest management, hazardous fuel reduction, and agricultural operations. Open pile burning in the vicinity of generation is frequently the only economic disposal option. A framework is developed to quantify air emissions reductions for projects that alternatively utilize biomass waste as fuel for energy production. A demonstration project was conducted involving the grinding and 97-km one-way transport of 6096 bone-dry metric tons (BDT) of mixed conifer forest slash in the Sierra Nevada foothills for use as fuel in a biomass power cogeneration facility. Compared with the traditional open pile burning method of disposal for the forest harvest slash, utilization of the slash for fuel reduced particulate matter (PM) emissions by 98% (6 kg PM/BDT biomass), nitrogen oxides (NOx) by 54% (1.6 kg NOx/BDT), nonmethane volatile organics (NMOCs) by 99% (4.7 kg NMOCs/BDT), carbon monoxide (CO) by 97% (58 kg CO/BDT), and carbon dioxide equivalents (CO2e) by 17% (0.38 t CO2e/BDT). Emission contributions from biomass processing and transport operations are negligible. CO2e benefits are dependent on the emission characteristics of the displaced marginal electricity supply. Monetization of emissions reductions will assist with fuel sourcing activities and the conduct of biomass energy projects.     

What have we learned from highly time-resolved measurements during EPA's Supersites Program and related studies?

A wide range of new and exciting highly time-resolved instruments were deployed during the U.S. Environmental Protection Agency (EPA) Supersite program and related studies that occurred during the same time period. These measurements elucidated the temporal variation of a suite of gas-phase species, particle physical properties, and size-resolved particulate chemical composition. Because the temporal resolution was so high, concentration and size distribution changes as short as 1 min or less were discerned. Often data from multiple instruments were correlated with each other and with meteorological measurements, and these correlations enabled conclusions to be drawn about the photochemical activity of the atmosphere, the location of point sources, and even the emissions characteristics of these sources. For instance, rapid changes in particulate matter (PM) concentration were due to meteorological conditions, emissions, and plume excursions that led to increases in nitrate, sulfate, and organic carbon concentrations. This paper summarizes the conclusions that have been reached, to date, using these new, highly time-resolved instruments, and demonstrates their promise for future studies.     

The Southeastern Aerosol Research and Characterization Study, part 3: continuous measurements of fine particulate matter mass and composition

Deployment of continuous analyzers in the Southeastern Aerosol Research and Characterization Study (SEARCH) network began in 1998 and continues today as new technologies are developed. Measurement of fine particulate matter (PM2.5) mass is performed using a dried, 30 degrees C tapered element oscillating microbalance (TEOM). TEOM measurements are complemented by observations of light scattering by nephelometry. Measurements of major constituents include: (1) SO4(2-) via reduction to SO2; (2) NH4+ and NO3- via respective catalytic oxidation and reduction to NO, (3) black carbon (BC) by optical absorption, (4) total carbon by combustion to CO2, and (5) organic carbon by difference between the latter two measurements. Several illustrative examples of continuous data from the SEARCH network are presented. A distinctive composite annual average diurnal pattern is observed for PM2.5 mass, nitrate, and BC, likely indicating the influence of traffic-related emissions, growth, and break up of the boundary layer and formation of ammonium nitrate. Examination of PM2.5 components indicates the need to better understand the continuous composition of the unmeasured "other" category, because it contributes a significant fraction to total mass during periods of high PM2.5 loading. Selected episodes are presented to illustrate applications of SEARCH data. An SO2 conversion rate of 0.2%/hr is derived from an observation of a plume from a coal-fired power plant during early spring, and the importance of local, rural sources of NH3 to the formation of ammonium nitrate in particulate matter (PM) is demonstrated.     

On-road and laboratory investigation of low-level PM emissions of a modern diesel particulate filter equipped diesel passenger car

Modern diesel particulate filter (DPF) systems are very effective in reducing particle emissions from diesel vehicles. In this work low-level particulate matter (PM) emissions from a DPF equipped EURO-4 diesel vehicle were studied in the emission test laboratory as well as during real-world chasing on a high-speed test track. Size and time resolved data obtained from an engine exhaust particle sizer (EEPS) and a condensation particle counter (CPC) are presented for both loaded and unloaded DPF condition. The corresponding time and size resolved emission factors were calculated for acceleration, deceleration, steady state driving and during DPF regeneration, and are compared with each other. In addition, the DPF efficiency of the tested vehicle was evaluated during the New European Driving Cycle (NEDC) by real time pre-/post-DPF measurements and was found to be 99.5% with respect to PM number concentration and 99.3% for PM mass, respectively. PM concentrations, which were measured at a distance of about 10 m behind the test car, ranged from 1 to 1.5 times background level when the vehicle was driven on the test track under normal acceleration conditions or at constant speeds below 100 kmh^?1. Only during higher speeds and full load accelerations concentrations above 3 times background level could be observed. The corresponding tests in the emission laboratory confirmed these results. During DPF regeneration the total PM number emission of nucleation mode particles was 3–4 orders of magnitude higher compared to those emitted at the same speed without regeneration, while the level of the accumulation mode particles remained about the same. The majority of the particles emitted during DPF regeneration was found to be volatile, and is suggested to originate from accumulated sulfur compounds.     

Resolving the interactions between population density and air pollution emissions controls in the San Joaquin Valley, USA

The effectiveness of emissions control programs designed to reduce concentrations of airborne particulate matter with an aerodynamic diameter < 2.5 microm (PM2.5) in California's San Joaquin Valley was studied in the year 2030 under three growth scenarios: low, medium, and high population density. Base-case inventories for each choice of population density were created using a coupled emissions modeling system that simultaneously considered interactions between land use and transportation, area source, and point source emissions. The ambient PM2.5 response to each combination of population density and emissions control was evaluated using a regional chemical transport model over a 3-week winter stagnation episode. Comparisons between scenarios were based on regional average and population-weighted PM2.5 concentrations. In the absence of any emissions control program, population-weighted concentrations of PM2.5 in the future San Joaquin Valley are lowest undergrowth scenarios that emphasize low population density. A complete ban on wood burning and a 90% reduction in emissions from food cooking operations and diesel engines must occur before medium- to high-density growth scenarios result in lower population-weighted concentrations of PM2.5. These trends partly reflect the fact that existing downtown urban cores that naturally act as anchor points for new high-density growth in the San Joaquin Valley are located close to major transportation corridors for goods movement. Adding growth buffers around transportation corridors had little impact in the current analysis, since the 8-km resolution of the chemical transport model already provided an artificial buffer around major emissions sources. Assuming that future emissions controls will greatly reduce or eliminate emissions from residential wood burning, food cooking, and diesel engines, the 2030 growth scenario using "as-planned" (medium) population density achieves the lowest population-weighted average PM2.5 concentration in the future San Joaquin Valley during a severe winter stagnation event. Implications: The San Joaquin Valley is one of the most heavily polluted air basins in the United States that are projected to experience strong population growth in the coming decades. The best plan to improve air quality in the region combines medium- or high-density population growth with rigorous emissions controls. In the absences of controls, high-density growth leads to increased population exposure to PM2.5 compared with low-density growth scenarios (urban sprawl).     

The need for ammonia abatement with respect to secondary PM reductions in Europe

In Europe, secondary particulate matter (PM) comprises 50% or more of PM 2.5. To reduce PM concentrations requires lowering precursor emissions. Since the 1980s, SO(2) emissions have decreased by more than 60%, while particle concentrations have decreased less. NO(x) and NH(3) emissions have decreased slightly. The role of ammonia in particle formation is addressed here. It is shown that secondary PM concentrations can only be effectively reduced if ammonia emissions are decreased in much the same way as those of SO(2) and NO(x).     

An assessment of air emissions from liquefied natural gas ships using different power systems and different fuels

The shipping industry has been an unrecognized source of criteria pollutants: nitrogen oxides (NOx), volatile organic compounds, coarse particulate matter (PM10), fine particulate matter (PM2.5), sulfur dioxide (SO2), and carbon monoxide (CO). Liquefied natural gas (LNG) has traditionally been transported via steam turbine (ST) ships. Recently, LNG shippers have begun using dual-fuel diesel engines (DFDEs) to propel and offload their cargoes. Both the conventional ST boilers and DFDE are capable of burning a range of fuels, from heavy fuel oil to boil-off-gas (BOG) from the LNG load. In this paper a method for estimating the emissions from ST boilers and DFDEs during LNG offloading operations at berth is presented, along with typical emissions from LNG ships during offloading operations under different scenarios ranging from worst-case fuel oil combustion to the use of shore power. The impact on air quality in nonattainment areas where LNG ships call is discussed. Current and future air pollution control regulations for ocean-going vessels (OGVs) such as LNG ships are also discussed. The objective of this study was to estimate and compare emissions of criteria pollutants from conventional ST and DFDE ships using different fuels. The results of this study suggest that newer DFDE ships have lower SO2 and PM2.5/PM10 emissions, conventional ST ships have lower NOx, volatile organic compound, and CO emissions; and DFDE ships utilizing shore power at berth produce no localized emissions because they draw their required power from the local electric grid.