We present a new mobile environmental reaction chamber for the simulation of the atmospheric aging of different emission sources without limitation from the instruments or facilities available at any single site. Photochemistry is simulated using a set of 40 UV lights (total power 4 KW). Characterisation of the emission spectrum of these lights shows that atmospheric aging of emissions may be simulated over a range of temperatures (−7 to 25 °C). A photolysis rate of NO₂, J_NO2, of (8.0 ± 0.7) × 10⁻³ s⁻¹ was determined at 25 °C. We demonstrate the utility of this new system by presenting results on the aging (OH = 12 × 10⁶ cm⁻³ h) of emissions from a modern (Euro 5) gasoline car operated during a driving cycle (New European Driving Cycle, NEDC) on a chassis dynamometer in a vehicle test cell. Emissions from the entire NEDC were sampled and aged in the chamber. Total organic aerosol (OA; primary organic aerosol (POA) emission + secondary organic aerosol (SOA) formation) was (369.8–397.5)10⁻³ g kg⁻¹ fuel, or (13.2–15.4) × 10⁻³ g km⁻¹, after aging, with aged OA/POA in the range 9–15. A thorough investigation of the composition of the gas phase emissions suggests that the observed SOA is from previously unconsidered precursors and processes. This large enhancement in particulate matter mass from gasoline vehicle aerosol emissions due to SOA formation, if it occurs across a wider range of gasoline vehicles, would have significant implications for our understanding of the contribution of on-road gasoline vehicles to ambient aerosols

Abstract. Inhaled aerosolized particulate matter (PM) induces cellular oxidative stress in vivo, leading to adverse health outcomes. The oxidative potential (OP) of PM appears to be a more relevant proxy of the health impact of the aerosol rather than the total mass concentration. However, the relative contributions of the aerosol sources to the OP are still poorly known. In order to better quantify the impact of different PM sources, we sampled aerosols in a French city for one year (2014, 115 samples). A coupled analysis with detailed chemical speciation (more than 100 species, including organic and carbonaceous compounds, ions, metals and aethalometer measurements) and two OP assays (ascorbic acid, AA, and dithiothreitiol, DTT) in a simulated lung fluid (SLF) were performed in these samples. We present in this study a statistical framework using a coupled approach with positive matrix factorization (PMF) and multiple linear regression to attribute a redox-activity to PM sources. Our results highlight the importance of the biomass burning and vehicular sources to explain the observed OP for both assays. In general, we see a different contribution of the sources when considering the OP AA, OP DTT or the mass of the PM10. Moreover, significant differences are observed between the DTT and AA tests which emphasized chemical specificities of the two tests and the need of a standardized approach for the future studies on epidemiology or toxicology of the PM.

Abstract. Traffic-related pollution is a major concern in urban areas due to its deleterious effects on human health. The characteristics of the traffic emissions on four highway environments in the Helsinki metropolitan area were measured with a mobile laboratory, equipped with state-of-the-art instrumentation. Concentration gradients were observed for all traffic-related pollutants, particle number (CN), particulate mass (PM 1 ), black carbon (BC), organics, and nitrogen oxides (NO and NO 2 ). Flow dynamics in different environments appeared to be an important factor for the dilution of the pollutants. For example, the half-decay distances for the traffic-related CN concentrations varied from 8 to 83 m at different sites. The PM 1 emissions from traffic mostly consisted of organics and BC. At the most open site, the ratio of organics to BC increased with distance to the highway, indicating condensation of volatile and semi-volatile organics on BC particles. These condensed organics were shown to be hydrocarbons as the fraction of hydrocarbon fragments in organics increased. Regarding the CN size distributions, particle growth during the dilution was not observed; however the mass size distributions measured with a soot particle aerosol mass spectrometer (SP-AMS), showed a visible shift of the mode, detected at ∼ 100 nm at the roadside, to a larger size when the distance to the roadside increased. The fleet average emission factors appeared to be lower for the CN and higher for the NO 2 than ten years ago. The reason is likely to be the increased fraction of light-duty (LD) diesel vehicles in the past ten years. The fraction of heavy-duty (HD) traffic, although constituting less than 10 % of the total traffic flow, was found to have a large impact on the emissions.

Abstract. We have used two methods for measuring emission factors (EFs) in real driving conditions on five cars in a controlled environment: the stationary method, where the investigated vehicle drives by the stationary measurement platform and the composition of the plume is measured, and the chasing method, where a mobile measurement platform drives behind the investigated vehicle. We measured EFs of black carbon and particle number concentration. The stationary method was tested for repeatability at different speeds and on a slope. The chasing method was tested on a test track and compared to the portable emission measurement system. We further developed the data processing algorithm for both methods, trying to improve consistency, determine the plume duration, limit the background influence and facilitate automatic processing of measurements. The comparison of emission factors determined by the two methods showed good agreement. EFs of a single car measured with either method have a specific distribution with a characteristic value and a long tail of super emissions. Measuring EFs at different speeds or slopes did not significantly influence the EFs of different cars; hence, we propose a new description of vehicle emissions that is not related to kinematic or engine parameters, and we rather describe the vehicle EF with a characteristic value and a super emission tail.

Abstract. The chasing method was used in an on-road measurement campaign, and emission factors (EF) of black carbon (BC), particle number (PN) and nitrogen oxides (NOx) were determined for 139 individual vehicles of different types encountered on the roads. The aggregated results provide EFs for BC, NOx and PN for three vehicle categories: goods vehicles, gasoline and diesel passenger cars. This is the first on-road measurement study where BC EFs of numerous individual diesel cars were determined in real-world driving conditions. We found good agreement between EFs of goods vehicles determined in this campaign and the results of previous studies that used either chasing or remote-sensing measurement techniques. The composition of the sampled car fleet determined from the national vehicle registry information is reflective of Eurostat statistical data on the Slovenian and European vehicle fleet. The median BC EF of diesel and gasoline cars that were in use for less than 5 years decreased by 60 and 47 % from those in use for 5–10 years, respectively; the median NOx and PN EFs of goods vehicles that were in use for less than 5 years decreased from those in use for 5–10 years by 52 and 67 %, respectively. Surprisingly, we found an increase of BC EFs in the newer goods vehicle fleet compared to the 5–10-year old one. The influence of engine maximum power of the measured EFs showed an increase in NOx EF from least to more powerful vehicles with diesel engines. Finally, a disproportionate contribution of high emitters to the total emissions of the measured fleet was found; the top 25 % of emitting diesel cars contributed 63, 47 and 61 % of BC, NOx and PN emissions respectively. With the combination of relatively simple on-road measurements and sophisticated post processing, individual vehicle EF can be determined and useful information about the fleet emissions can be obtained by exactly representing vehicles which contribute disproportionally to vehicle fleet emissions; and monitor how the numerous emission reduction approaches are reflected in on-road driving conditions.