Fast response sequential measurements and modelling of nanoparticles inside and outside a car cabin

Commuters are regularly exposed to short-term peak concentration of traffic produced nanoparticles (i.e. particles <300 nm in size). Studies indicate that these exposures pose adverse health effects (i.e. cardiovascular). This study aims to obtain particle number concentrations (PNCs) and distributions (PNDs) inside and outside a car cabin whilst driving on a road in Guildford, a typical UK town. Other objectives are to: (i) investigate the influences of particle transformation processes on particle number and size distributions in the cabin, (ii) correlate PNCs inside the cabin to those measured outside, and (iii) predict PNCs in the cabin based on those outside the cabin using a semi-empirical model. A fast response differential mobility spectrometer (DMS50) was employed in conjunction with an automatic switching system to measure PNCs and PNDs in the 5–560 nm range at multiple locations inside and outside the cabin at 10 Hz sampling rate over 10 s sequential intervals. Two separate sets of measurements were made at: (i) four seats in the car cabin during ∼700 min of driving, and (ii) two points, one the driver seat and the other near the ventilation air intake outside the cabin, during ∼500 min of driving. Results of the four-point measurements indicated that average PNCs at all for locations were nearly identical (i.e. 3.96, 3.85, 3.82 and 4.00 × 104 cm−3). The modest difference (∼0.1%) revealed a well-mixed distribution of nanoparticles in the car cabin. Similar magnitude and shapes of PNDs at all four sampling locations suggested that transformation processes (e.g. nucleation, coagulation, condensation) have minimal effect on particles in the cabin. Two-point measurements indicated that on average, PNCs inside the cabin were about 72% of those measured outside. Time scale analysis indicated that dilution was the fastest and dominant process in the cabin, governing the variations of PNCs in time. A semi-empirical model was proposed to predict PNCs inside the cabin as a function of those measured outside. Performance evaluation of the model against multiple statistical measures was within the recommended guidelines for atmospheric dispersion modelling. Trip average PNCs obtained using the model demonstrate a reasonably good correlation (i.e. R2 = 0.97) with measured values

H15-3: Number concentration, distribution and transformation of nanoparticles in and outside a car cabin

City dwellers are regularly exposed to nanoparticle (i.e. particles < 300 nm in diameter), emitted by fossil fuelled vehicles, whilst commuting by transport modes such as taxis and buses. Exposure to these nanoparticles can lead to significant adverse effects on human health. This study aims to investigate spatial distribution of particle number concentrations (PNCs) and distributions (PNDs) in and outside a car cabin during driving. Possible influences of particle transformation processes on PNC and PNDs in the car cabin are also investigated. Another objective is to predict the PNCs in the car cabin using those measured outside. Measurements of particles in the 5-560 nm size range were conducted using a fast response differential mobility spectrometer (DMS50) in conjunction with an automated switching system. The DMS50 was used to measure size-resolved sequential distributions at: (i) four seats in the car cabin during about 700 minutes of driving, and (ii) two points at the driver's seat, inside and the front bonnet outside the cabin, during about 500 minutes of driving. The emission penetration and spatial distribution in the car cabin through (i) the ventilation system (Vent), and (ii) door/window sealing (CG) was simulated by means of three-dimensional computational fluid dynamics (CFD) using the Fluent code. Standard k-ε turbulence model was employed to simulate turbulence flow in the cabin. Vent/CG emission ratio was altered for the two different scenarios (0.9/0.1 and 0.7/0.3), indicating; (i) no filter fitted Vent and high vehicle sealing efficiency, (ii) filter fitted Vent and reduced sealing efficiency. Four-point measurements indicated that the average PNCs at the front seats (3.96 and 3.85 × 104 cm-3) were almost identical to those found at the rear seats (3.82 and 4.00 × 104 cm-3). The very small differences (∼0.1%) suggest that the car cabin is very close to a well-mixed microenvironment. Two-point measurements revealed that the ratio of average PNCs in (2.72 ± 1.03 × 104 cm-3) and outside the car cabin (3.75 ± 1.62 × 104 cm-3) was about 0.72. A semi-empirical box mode model was introduced to predict PNCs in the car cabin as a function of those measured outside and cabin air exchange rate. Performance evaluation of the box model against statistical measures was within the recommended guidelines for urban air quality modelling. Overall, PNCs calculated by the model demonstrate a satisfactory correlation with the measured values. CFD simulations indicate that away from the Vent, emission is dispersed almost uniformly in the car cabin. Vent / CG ratios indicated that despite changes of emission filtering into the cabin, the dispersion characteristics remained almost identical at passengers' breathing height (i.e. 1.2 m from the floor)

The behaviour of traffic produced nanoparticles in a car cabin and resulting exposure rates

The aim of this study is to assess particle number concentrations (PNCs) and distributions (PNDs) in a car cabin while driving. Further objectives include the determination of the influence of particle transformation processes on PNCs, PNDs and estimation of PNC related exposure. On-board measurements of PNCs and PNDs were made in the 5–560 nm size range using a fast response differential mobility spectrometer (DMS50), which has a response time of 500 ms. Video records of the traffic ahead of the experimental car were also used to correlate emission events with measured PNCs and PNDs. A total of 30 return trips was made on a 2.7 km route during morning and evening rush hours, with journey times of 7 ± 2 and 10 ± 3 min, respectively. The average PNC for the set of morning journeys, 5.79 ± 3.52 × 104 cm−3, was found to be nearly identical to the average recorded during the afternoon, 5.95 ± 4.67 × 104 cm−3. Average PNCs for individual trips varied from 2.42 × 104 cm−3 to 2.18 × 105 cm−3, mainly due to changes in the emissions affecting the experimental car (e.g. when the experimental car was following another vehicle). The largest one second averaged PNC during a specific event, 1.85 × 106 cm−3, was found to be over 30-times greater than the overall average of 5.87 ± 4.06 × 104 cm−3. Correlation of video records and concentration data indicated that close proximity to a preceding vehicle led to a clear increase in PNCs of freshly emitted nucleation mode particles. The evolution of normalised PNDs demonstrated that dilution was the dominant transformation process in the car cabin. The deposition of inhaled particles in the lung was estimated on the basis of either the size-resolved distribution or the total PNC. In general, the two methods yielded similar results but differences up to 30% were noted in some cases, with the latter method giving the lower values. Overall, the results reflect the importance of size-resolved measurements for deriving accurate evaluations of exposure rates, as well as identifying emissions from nearby traffic as the cause of short-term elevations of PNCs and hence dose rates

The behaviour of traffic produced nanoparticles in a car cabin and resulting exposure rates

The aim of this study is to assess particle number concentrations (PNCs) and distributions (PNDs) in a car cabin while driving. Further objectives include the determination of the influence of particle transformation processes on PNCs, PNDs and estimation of PNC related exposure. On-board measurements of PNCs and PNDs were made in the 5–560 nm size range using a fast response differential mobility spectrometer (DMS50), which has a response time of 500 ms. Video records of the traffic ahead of the experimental car were also used to correlate emission events with measured PNCs and PNDs. A total of 30 return trips was made on a 2.7 km route during morning and evening rush hours, with journey times of 7 ± 2 and 10 ± 3 min, respectively. The average PNC for the set of morning journeys, 5.79 ± 3.52 × 104 cm−3, was found to be nearly identical to the average recorded during the afternoon, 5.95 ± 4.67 × 104 cm−3. Average PNCs for individual trips varied from 2.42 × 104 cm−3 to 2.18 × 105 cm−3, mainly due to changes in the emissions affecting the experimental car (e.g. when the experimental car was following another vehicle). The largest one second averaged PNC during a specific event, 1.85 × 106 cm−3, was found to be over 30-times greater than the overall average of 5.87 ± 4.06 × 104 cm−3. Correlation of video records and concentration data indicated that close proximity to a preceding vehicle led to a clear increase in PNCs of freshly emitted nucleation mode particles. The evolution of normalised PNDs demonstrated that dilution was the dominant transformation process in the car cabin. The deposition of inhaled particles in the lung was estimated on the basis of either the size-resolved distribution or the total PNC. In general, the two methods yielded similar results but differences up to 30% were noted in some cases, with the latter method giving the lower values. Overall, the results reflect the importance of size-resolved measurements for deriving accurate evaluations of exposure rates, as well as identifying emissions from nearby traffic as the cause of short-term elevations of PNCs and hence dose rates