Size and composition distributions of particulate matter emissions: part 1--light-duty gasoline vehicles

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 PM0.1 (0.056- to 0.1-microm aerodynamic diameter) and fine PM1.8 (< or =1.8-microm aerodynamic diameter) emission rates of 9.6 mg/km and 213 mg/km, respectively. The newest vehicles had PM0.1 and PM1.8 emissions of 51 microg/km and 371 microg/km, respectively. Light duty trucks and sport utility vehicles had PM0.1 and PM1.8 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-microm particle diameter for all vehicles except those emitting visible smoke, which peaked between 0.18 and 0.32 microm. 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.     

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).     

Theoretical versus observed gas-particle partitioning of carbonyl emissions from motor vehicles

A state-of-the-science thermodynamic model describing gas-particle absorption processes was used to predict the gas-particle partitioning of mixtures of approximately 60 carbonyl compounds emitted from low-emission gasoline-powered vehicles, three-way catalyst gasoline-powered vehicles, heavy-duty diesel vehicles under the idle-creep condition (HDDV idle), and heavy-duty diesel vehicles under the five-mode test (HDDV 5-mode). Exhaust was diluted by a factor of 120-580 with a residence time of approximately 43 sec. The predicted equilibrium absorption partitioning coefficients differed from the measured partitioning coefficients by several orders of magnitude. Time scales to reach equilibrium in the dilution sampling system were close to the actual residence time during the HDDV 5-mode test and much longer than the actual residence time during the other vehicle tests. It appears that insufficient residence time in the sampling system cannot uniformly explain the failure of the absorption mechanism to explain the measured partitioning. Other gas-particle partitioning mechanisms (e.g., heterogeneous reactions, capillary adsorption) beyond the simple absorption theory are needed to explain the discrepancy between calculated carbonyl partitioning coefficients and observed partitioning. Both of these alternative partitioning mechanisms imply great challenges for the measurement and modeling of semi-volatile primary organic aerosol (POA) species from motor vehicles. Furthermore, as emitted particle concentrations from newer vehicles approach atmospheric background levels, dilution sampling systems must fundamentally change their approach so that they use realistic particle concentrations in the dilution air to approximately represent real-world conditions. Samples collected with particle-free dilution air yielding total particulate matter concentrations below typical ambient concentrations will not provide a realistic picture of partitioning for semi-volatile compounds.     

Source apportionment of wintertime secondary organic aerosol during the California regional PM10/PM2.5 air quality study

The UCD/CIT air quality model with the Caltech Atmospheric Chemistry Mechanism (CACM) was used to predict source contributions to secondary organic aerosol (SOA) formation in the San Joaquin Valley (SJV) from December 15, 2000 to January 7, 2001. The predicted 24-day average SOA concentration had a maximum value of 4.26 μg m^?3 50 km southwest of Fresno. Predicted SOA concentrations at Fresno, Angiola, and Bakersfield were 2.46 μg m^?3, 1.68 μg m^?3, and 2.28 μg m^?3, respectively, accounting for 6%, 37%, and 4% of the total predicted organic aerosol. The average SOA concentration across the entire SJV was 1.35 μg m^?3, which accounts for approximately 20% of the total predicted organic aerosol. Averaged over the entire SJV, the major SOA sources were solvent use (28% of SOA), catalyst gasoline engines (25% of SOA), wood smoke (16% of SOA), non-catalyst gasoline engines (13% of SOA), and other anthropogenic sources (11% of SOA). Diesel engines were predicted to only account for approximately 2% of the total SOA formation in the SJV because they emit a small amount of volatile organic compounds relative to other sources. In terms of SOA precursors within the SJV, long-chain alkanes were predicted to be the largest SOA contributor, followed by aromatic compounds. The current study identifies the major known contributors to the SOA burden during a winter pollution episode in the SJV, with further enhancements possible as additional formation pathways are discovered.     

Influence of regional development policies and clean technology adoption on future air pollution exposure

Future air pollution emissions in the year 2030 were estimated for the San Joaquin Valley (SJV) in central California using a combined system of land use, mobile, off-road, stationary, area, and biogenic emissions models. Four scenarios were developed that use different assumptions about the density of development and level of investment in transportation infrastructure to accommodate the expected doubling of the SJV population in the next 20 years. Scenario 1 reflects current land-use patterns and infrastructure while scenario 2 encouraged compact urban footprints including redevelopment of existing urban centers and investments in transit. Scenario 3 allowed sprawling development in the SJV with reduced population density in existing urban centers and construction of all planned freeways. Scenario 4 followed currently adopted land use and transportation plans for the SJV. The air quality resulting from these urban development scenarios was evaluated using meteorology from a winter stagnation event that occurred on December 15th, 2000 to January 7th 2001. Predicted base-case PM2.5 mass concentrations within the region exceeded 35 μg m^?3 over the 22-day episode. Compact growth reduced the PM2.5 concentrations by ～1 μg m^?3 relative to the base-case over most of the SJV with the exception of increases (～1 μg m^?3) in urban centers driven by increased concentrations of elemental carbon (EC) and organic carbon (OC). Low-density development increased the PM2.5 concentrations by 1–4 μg m^?3 over most of the region, with decreases (0.5–2 μg m^?3) around urban areas. Population-weighted average PM2.5 concentrations were very similar for all development scenarios ranging between 16 and 17.4 μg m^?3. Exposure to primary PM components such as EC and OC increased 10–15% for high density development scenarios and decreased by 11–19% for low-density scenarios. Patterns for secondary PM components such as nitrate and ammonium ion were almost exactly reversed, with a 10% increase under low-density development and a 5% decrease under high density development. The increased human exposure to primary pollutants such as EC and OC could be predicted using a simplified analysis of population-weighted primary emissions. Regional planning agencies should develop thresholds of population-weighted primary emissions exposure to guide the development of growth plans. This metric will allow them to actively reduce the potential negative impacts of compact growth while preserving the benefits.     

Particulate air quality model predictions using prognostic vs. diagnostic meteorology in central California

Comparisons were made between three sets of meteorological fields used to support air quality predictions for the California Regional Particulate Air Quality Study (CRPAQS) winter episode from December 15, 2000 to January 6, 2001. The first set of fields was interpolated from observations using an objective analysis method. The second set of fields was generated using the WRF prognostic model without data assimilation. The third set of fields was generated using the WRF prognostic model with the four-dimensional data assimilation (FDDA) technique. The UCD/CIT air quality model was applied with each set of meteorological fields to predict the concentrations of airborne particulate matter and gaseous species in central California. The results show that the WRF model without data assimilation over-predicts surface wind speed by ～30% on average and consequently yields under-predictions for all PM and gaseous species except sulfate (S(VI)) and ozone(O₃). The WRF model with FDDA improves the agreement between predicted and observed wind and temperature values and consequently yields improved predictions for all PM and gaseous species. Overall, diagnostic meteorological fields produced more accurate air quality predictions than either version of the WRF prognostic fields during this episode. Population-weighted average PM_2.5 exposure is 40% higher using diagnostic meteorological fields compared to prognostic meteorological fields created without data assimilation. These results suggest diagnostic meteorological fields based on a dense measurement network are the preferred choice for air quality model studies during stagnant periods in locations with complex topography.     

Simulating PM concentration during a winter episode in a subtropical valley: Sensitivity simulations and evaluation methods

We investigated a two-week episode with high PM concentrations in California Central Valley during the Christmas–New Year of 2000–2001 using a modeling system that consists of a computationally efficient, 3-D photochemical–microphysical transport model, a mesoscale meteorological model, emission models, and an evaluation package. One hundred simulations were conducted with fine resolutions and observational constraints, to reproduce spatial and temporal features of observed PM concentrations and to understand the formation mechanism of the episode. Simulated PM concentrations consist of secondary inorganic components, mainly ammonium nitrate, and total carbon in areas with elevated concentrations in the accumulation mode, and consist of mainly dust and sea salt in the coarse mode. Simulated oxidants and nitrate were significantly elevated over the valley, and the latter showed much less amplitude than the former. Simulated PM concentrations were evaluated with observations systematically with spatially and temporally paired method, a more restrictive multivariate method (NMFROC), and a more flexible “gradient evaluation” method. The paired evaluation shows that high correlation coefficient (R = ～0.8) and low fractional error (FE = ～0.1) could be achieved at stations with elevated 24-h concentration of PM in the accumulation mode in some simulations. The NMFROC method was used to extract useful information from seemingly failed simulations. A “gradient evaluation” method is introduced here to extract additional information from simulations. We found that emission reductions of NO_x and AVOC showed similar effects on percentage basis in different areas, and both are more effective than reducing NH₃ for abating elevated concentrations of accumulation mode PM in California Central Valley during the winter episode.     

Size and composition distributions of particulate matter emissions: part 2--heavy-duty diesel vehicles

Particulate matter (PM) emissions from heavy-duty diesel vehicles (HDDVs) were collected using a chassis dynamometer/dilution sampling system that employed filter-based samplers, cascade impactors, and scanning mobility particle size (SMPS) measurements. Four diesel vehicles with different engine and emission control technologies were tested using the California Air Resources Board Heavy Heavy-Duty Diesel Truck (HHDDT) 5 mode driving cycle. Vehicles were tested using a simulated inertial weight of either 56,000 or 66,000 lb. Exhaust particles were then analyzed for total carbon, elemental carbon (EC), organic matter (OM), and water-soluble ions. HDDV fine (< or =1.8 microm aerodynamic diameter; PM1.8) and ultrafine (0.056-0.1 microm aerodynamic diameter; PM0.1) PM emission rates ranged from 181-581 mg/km and 25-72 mg/km, respectively, with the highest emission rates in both size fractions associated with the oldest vehicle tested. Older diesel vehicles produced fine and ultrafine exhaust particles with higher EC/OM ratios than newer vehicles. Transient modes produced very high EC/OM ratios whereas idle and creep modes produced very low EC/OM ratios. Calcium was the most abundant water-soluble ion with smaller amounts of magnesium, sodium, ammonium ion, and sulfate also detected. Particle mass distributions emitted during the full 5-mode HDDV tests peaked between 100-180 nm and their shapes were not a function of vehicle age. In contrast, particle mass distributions emitted during the idle and creep driving modes from the newest diesel vehicle had a peak diameter of approximately 70 nm, whereas mass distributions emitted from older vehicles had a peak diameter larger than 100 nm for both the idle and creep modes. Increasing inertial loads reduced the OM emissions, causing the residual EC emissions to shift to smaller sizes. The same HDDV tested at 56,000 and 66,000 lb had higher PM0.1 EC emissions (+22%) and lower PM0.1 OM emissions (-38%) at the higher load condition.     

Determination of volatile organic compound emissions and ozone formation from spraying solvent-based pesticides

Large-scale agricultural activities have come under scrutiny for possible contributions to the emission of ozone precursors. The San Joaquin Valley (SJV) of California is an area with intense agricultural activity that exceeds the federal ozone standards for more than 30 to 40 d yr(-1) and the more stringent state standards for more than 100 d yr(-1). Pesticides are used widely in both agricultural and residential subregions of the SJV, but the largest use, by weight of "active ingredient," is in agriculture. The objective of the study was to determine the role of pesticide application on airborne volatile organic compounds (VOC) concentrations and ozone formation in the SJV. The ozone formation from the pesticide formulation sprayed on commercial orchards was studied using two transportable smog chambers at four application sites during the summers of 2007 and 2008. In addition to the direct measurements of ozone formation, airborne VOC concentrations were measured before and after pesticide spraying using canister and sorbent tube sampling techniques. Soil VOC concentrations were also measured to understand the distribution of VOCs between different environmental compartments. Numerous VOCs were detected in the air and soil samples throughout the experiment but higher molecular weight aromatic hydrocarbons were the primary compounds observed in elevated concentrations immediately after pesticide spraying. Measurements indicate that the ozone concentration formed by VOC downwind of the orchard may increase up to 15 ppb after pesticide application, with a return back to prespray levels after 1 to 2 d.