We have observed a wide area of air pollutant impact downwind of a freeway during pre-sunrise hours in both winter and summer seasons. In contrast, previous studies have shown much sharper air pollutant gradients downwind of freeways, with levels above background concentrations extending only 300 m downwind of roadways during the day and up to 500 m at night. In this study, real-time air pollutant concentrations were measured along a 3 600 m transect normal to an elevated freeway 1–2 hours before sunrise using an electric vehicle mobile platform equipped with fast-response instruments. In winter pre-sunrise hours, the peak ultrafine particle (UFP) concentration (~95 000 cm−3) occurred immediately downwind of the freeway. However, downwind UFP concentrations as high as ~ 40 000 cm−3 extended at least 1 200 m from the freeway, and did not reach background levels (~15 000 cm−3) until a distance of about 2 600 m. UFP concentrations were also elevated over background levels up to 600 m upwind of the freeway. Other pollutants, such as NO and particle-bound polycyclic aromatic hydrocarbons, exhibited similar long-distance downwind concentration gradients. In contrast, air pollutant concentrations measured on the same route after sunrise, in the morning and afternoon, exhibited the typical daytime downwind decrease to background levels within ~300 m as found in earlier studies. Although pre-sunrise traffic volumes on the freeway were much lower than daytime congestion peaks, downwind UFP concentrations were significantly higher during pre-sunrise hours than during the daytime; UFP and NO concentrations were also strongly correlated with traffic counts on the freeway. We associate these elevated pre-sunrise concentrations over a wide area with a nocturnal surface temperature inversion, low wind speeds, and high relative humidity. Observation of a wide air pollutant impact area downwind of a major roadway prior to sunrise has important exposure assessment implications since it demonstrates extensive roadway impacts on residential areas during pre-sunrise hours, when most people are at home.

Fuel-based emission factors for 143 light-duty gasoline vehicles (LDGVs) and 93 heavy-duty diesel trucks (HDDTs) were measured in Wilmington, CA using a zero-emission mobile measurement platform (MMP). The frequency distributions of emission factors of carbon monoxide (CO), nitrogen oxides (NO x ), and particle mass with aerodynamic diameter below 2.5 mm (PM 2.5 ) varied widely, whereas the average of the individual vehicle emission factors were comparable to those reported in previous tunnel and remote sensing studies as well as the predictions by Emission Factors (EMFAC) 2007 mobile source emission model for Los Angeles County. Variation in emissions due to different driving modes (idle, low-and high-speed acceleration, low-and high-speed cruise) was found to be relatively small in comparison to intervehicle variability and did not appear to interfere with the identification of high emitters, defined as the vehicles whose emissions were more than 5 times the fleet-average values. Using this definition, approximately 5% of the LDGVs and HDDTs measured were high emitters. Among the 143 LDGVs, the average emission factors of NO x , black carbon (BC), PM 2.5 , and ultrafine particle (UFP) would be reduced by 34%, 39%, 44%, and 31%, respectively, by removing the highest 5% of emitting vehicles, whereas CO emission factor would be reduced by 50%. The emission distributions of the 93 HDDTs measured were even more skewed: approximately half of the NO x and CO fleet-average emission factors and more than 60% of PM 2.5 , UFP, and BC fleet-average emission factors would be reduced by eliminating the highest-emitting 5% HDDTs. Furthermore, high emissions of BC, PM 2.5 , and NO x tended to cluster among the same vehicles.

Real time air pollutant concentrations were measured downwind of Santa Monica Airport (SMA), using an electric vehicle mobile platform equipped with fast response instruments in spring and summer of 2008. SMA is a general aviation airport operated for private aircraft and corporate jets in Los Angeles County, California. An impact area of elevated ultrafine particle (UFP) concentrations was observed extending beyond 660 m downwind and 250 m perpendicular to the wind on the downwind side of SMA. Aircraft operations resulted in average UFP concentrations elevated by factors of 10 and 2.5 at 100 and 660 m downwind, respectively, over background levels. The long downwind impact distance (i.e., compared to nearby freeways at the same time of day) is likely primarily due to the large volumes of aircraft emissions containing higher initial concentrations of UFP than on-road vehicles. Aircraft did not appreciably elevate average levels of black carbon (BC), particle-bound polycyclic aromatic hydrocarbons (PB-PAH), although spikes in concentration of these pollutants were observed associated with jet takeoffs. Jet departures resulted in peak 60-s average concentrations of up to 2.2 x 10(6) cm(-3), 440 ng m(-3), and 30 microg m(-3) for UFP, PB-PAH, and BC, respectively, 100 m downwind of the takeoff area. These peak levels were elevated by factors of 440, 90, and 100 compared to background concentrations. Peak UFP concentrations were reasonably correlated (r(2) = 0.62) with fuel consumption rates associated with aircraft departures, estimated from aircraft weights and acceleration rates. UFP concentrations remained elevated for extended periods associated particularly with jet departures, but also with jet taxi and idle, and operations of propeller aircraft. UFP measured downwind of SMA had a median mode of about 11 nm (electric mobility diameter), which was about half of the 22 nm median mode associated with UFP from heavy duty diesel trucks. The observation of highly elevated ultrafine particle concentrations in a large residential area downwind of this local airport has potential health implications for persons living near general aviation airports.

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We observed elevated air pollutant concentrations, especially of ultrafine particles (UFP), black carbon (BC) and NO, across the residential neighborhood of the Boyle Heights Community (BH) of Los Angeles, California. Using an electric vehicle mobile platform equipped with fast response instruments, real-time air pollutant concentrations were measured in BH in spring and summer of 2008. Pollutant concentrations varied significantly in the two seasons, on different days, and by time of day, with an overall average UFP concentration in the residential areas of ~33 000 cm−3. The averaged UFP, BC, and NO concentrations measured on Soto St, a major surface street in BH, were 57 000 cm−3, 5.1 µg m−3, and 67 ppb, respectively. Concentrations of UFP across the residential areas in BH were nearly uniform spatially, in contrast to other areas in the greater metropolitan area of Los Angeles where UFP concentrations exhibit strong gradients downwind of roadways. We attribute this “UFP cloud” to high traffic volumes, including heavy duty diesel trucks on the freeways which surround and traverse BH, and substantial numbers of high-emitting vehicles (HEVs) on the surface streets traversing BH. Additionally, the high density of stop signs and lights and short block lengths, requiring frequent accelerations of vehicles, may contribute. The data also support a role for photochemical production of UFP in the afternoon. UFP concentration peaks (5 s average) of up to 9 million particles cm−3 were also observed immediately behind HEVs when they accelerated from stop lights in the BH neighborhood and areas immediately adjacent. Although encounters with HEV during mornings accounted for only about 6% and 17% of time spent monitoring residential areas and major surface streets, HEV contributed to about 28% and 53% of total ultrafine particles measured on the route, respectively. The observation of elevated pollutant number concentrations across the Boyle Heights community highlights how multiple factors combine to create high pollutant levels, and has important human exposure assessment implications, including the potential utility of our data as inputs to epidemiological studies.