Particle Number Emission Rates Research Articles

Temperature-dependent particle number emission rates and emission characteristics during heating processes of edible oils

The goal of this research is to investigate the temperature-dependent emission rates of particle numbers and emission characteristics during oil heating. Seven regularly used edible oils were studied in a variety of tests to attain this objective. First, total particle number emission rates ranging from 10 nm to 1 μm were measured, followed by an examination within six size intervals from 0.3 μm to 10 μm. Following that, the impacts of oil volume and oil surface area on the emission rate were investigated, and multiple regression models were developed based on the results. The results showed that corn, sunflower and soybean oils had higher emission rates than other oils above 200 °C, with peak values of 8.22 × 109#/s, 8.19 × 109#/s and 8.17 × 109#/s, respectively. Additionally, peanut and rice oils were observed to emit the most particles larger than 0.3 μm, followed by medium-emission (rapeseed and olive oils) and low-emission oils (corn, sunflower and soybean oils). In most cases, oil temperature (T) has the most significant influence on the emission rate during the smoking stage, but its influence was not as pronounced in the moderate smoking stage. The models obtained are all statistically significant (P < 0.001), with R2 values greater than 0.9, and the classical assumption test concluded that regressions were in accordance with the classical assumptions regarding normality, multicollinearity, and heteroscedasticity. In general, low oil volume and large oil surface area were more recommended for cooking to mitigate UFPs emission.

Comparison of the time-dependent characteristics between particle mass and particle number emissions during oil heating and emission mitigation strategies

It is important to understand the cooking particles emitted over time to mitigate cooking pollution, but current control strategies fail to consider both particle mass and number emissions. Therefore, this study was designed to compare the differences in time-dependent characteristics of particle mass and number emissions and to propose comprehensive mitigation strategies that consider both characteristics. For this purpose, the effects of various factors on both emissions were analyzed, and time-dependent emission rate models were developed. The time-dependent models obtained were statistically significant (P < 0.001), with most R2 values greater than 0.90. The masses and numbers of particles emitted often varied in the opposite direction. During the smoking stage, corn oil exhibited low particle mass emissions while its particle number emission rate (TERn) reached 109#/s. However, at higher temperatures (T > TDM), the percentage difference in TERn with increasing oil volume decreased from 7.1% to 3.5%, while that in PM2.5 emission rate with decreasing oil volume was almost more than 25%. This indicated that the increased oil volumes were more effective in reducing the particle masses emitted from corn oil than in increasing the numbers of particles emitted, and similar conclusions were also drawn for decreasing oil surface area. Overall, oils exhibiting lower particle mass emissions and lower cooking temperatures were recommended for cooking. Lower oil volumes and larger pans should be used at relatively lower temperatures (T < TDM) primarily to mitigate particle number emissions, while higher oil volumes and smaller pans should be used at higher temperatures to control particle mass emissions.

Human exposure to aerosol from indoor gas stove cooking and the resulting nervous system responses.

Our knowledge of the effects of exposure to indoor ultrafine particles (sub-100nm, #/cm3 ) on human brain activity is very limited. The effects of cooking ultrafine particles (UFP) on healthy adults were assessed using an electroencephalograph (EEGs) for brain response. Peak ultrafine particle concentrations were approximately 3×105 particle/cm3, and the average level was 1.64×105 particle/cm3 . The average particle number emission rate (S) and the average number decay rate (a+k) for chicken frying in brain experiments were calculated to be 2.82×1012 (SD=1.83×1012 , R2 =0.91, p=0.0013) particles/min, 0.47 (SD=0.30, R2 =0.90, p<0.0001) min-1 , respectively. EEGs were recorded before and during cooking (14min) and 30min after the cooking sessions. The brain fast-wave band (beta) decreased during exposure, similar to people with neurodegenerative diseases. It subsequently increased to its pre-exposure condition for 70% of the study participants after 30min. The brain slow-wave band to fast-wave band ratio (theta/beta ratio) increased during and after exposure, similar to observed behavior in early-stage Alzheimer's disease (AD) patients. The brain then tended to return to its normal condition within 30min following the exposure. This study suggests that chronically exposed people to high concentrations of cooking aerosol might progress toward AD.

Impact of ironing on indoor particle levels and composition

Domestic chores are an important part of the household's daily routine and can contribute significantly to personal exposure. In this study, the particulate mass and number concentrations were assessed when using two irons (steam iron and steam iron with boiler) under distinct conditions (minimum ventilation and indoor doors open) and in the background air. The detailed PM10 chemical characterisation included organic and elemental carbon, elements and organic speciation. Particle number emission rates ranged from 8.1 ± 0.09 × 1011 to 15 ± 3.5 × 1011 particles min−1. Ratios of peak to background levels indicate that ironing can elevate the ultrafine particle number concentrations by a factor ranging from 35 to 194. PM10 emission rates from steam iron, under minimum ventilation conditions (6.6 ± 1.4 μg s−1), were higher than those from steam iron with the doors open (1.9 ± 1.6 μg s−1). The highest particle number and mass emission rates were recorded when the steam iron with boiler was used. Regarding the chemical composition of particles, elemental carbon and strontium were only detected during ironing. Bromide concentrations increased noticeably over background levels (9–51 times) during ironing. PM10 samples encompassed a wide range of organic compounds, part of which can be attributed to the handling of textiles and the use of detergents, fabric softeners, cosmetics and personal care products. Substances emitted by volatilisation or shedding of textile fibres, or due to handling, can contribute to human exposure through inhalation. The cancer risks associated with inhalation of metals and PAH were found to be negligible.

Application of a Diffusion Charger to Quantify Real-Time Particle Emissions from Light-Duty Vehicles: a Comparison Study with a Particle Size Spectrometer

Measurement methods for vehicle-emitted particulate matter (PM) have evolved as vehicle emission standards have become more stringent. For example, the filter-based gravimetric method has been demonstrated feasible to measure emissions at levels below 1 mg/mi from light-duty vehicles. However, while regulatory methods and instruments for measuring PM emissions are rigorous and accurate, there is a need to continue evaluating alternatives for use in the laboratory, as well as simple and robust instruments for screening that can be used for detecting high emissions on the roadside and evaluating the effectiveness of repairs in support of inspection and maintenance (I/M) programs. This study investigated the performance of an aerosol diffusion charger (TSI Electrical Aerosol Detector) by comparing its raw signal (aerosol active surface area) and its conversion to particle number and mass emission rates with those reported or calculated from a multi-channel electrometer-based particle size spectrometer (TSI Engine Exhaust Particle Sizer) and various condensation particle counters (CPCs). Four light-duty vehicles were tested, including gasoline port fuel injection (PFI), gasoline direct injection (GDI), and a diesel vehicle equipped with a diesel particulate filter (DPF). Results show that the diffusion charger was responsive over a wide particle size and concentration range, exhibiting sufficient signal-to-noise ratio during transient measurements of the gasoline PFI vehicle and light-duty diesel vehicle with a DPF (both certified below 1 mg/mi). High sensitivity at low concentrations suggests that the diffusion charger may have potential for identifying failures of emission control systems at lower concentrations than methods designed to report real-time suspended particle number or mass metrics directly. Systematic and fundamental data from our study underscore the challenge with “black box” equipment calibrated to calculate total particle number and mass from surface area measurements based on constant unimodal fit parameters. Future work could focus on the applications from deploying active surface area monitors at the roadside or for using surface area measurements to evaluate repair effective in support of I/M programs.

Particle number emission rates of aerosol sources in 40 German households and their contributions to ultrafine and fine particle exposure.

More representative data on source-specific particle number emission rates and associated exposure in European households are needed. In this study, indoor and outdoor particle number size distributions (10-800nm) were measured in 40 German households under real-use conditions in over 500days. Particle number emission rates were derived for around 800 reported indoor source events. The highest emission rate was caused by burning candles (5.3×1013 h-1 ). Data were analyzed by the single-parameter approach (SPA) and the indoor aerosol dynamics model approach (IAM). Due to the consideration of particle deposition, coagulation, and time-dependent ventilation rates, the emission rates of the IAM approach were about twice as high as those of the SPA. Correction factors are proposed to convert the emission rates obtained from the SPA approach into more realistic values. Overall, indoor sources contributed~56% of the daily-integrated particle number exposure in households under study. Burning candles and opening the window leads to seasonal differences in the contributions of indoor sources to residential exposure (70% and 40% in the cold and warm season, respectively). Application of the IAM approach allowed to attribute the contributions of outdoor particles to the penetration through building shell and entry through open windows (26% and 15%, respectively).

Determination of the emission indices for NO, NO2 , HONO, HCHO, CO, and particles emitted from candles.

In the present study, emission indices for NO, NO2 , HONO, HCHO, CO, particle mass, and particle numbers including particle size distributions for three different offering candles were determined. The candles investigated showed similar emission characteristics with emission indices (g/kg) in good agreement with former candle emission studies. An average HONO/NOx emission ratio of 6.6±1.1% was obtained, which is much higher compared to most other combustion sources, indicating that candles may be a significant indoor source of this important trace gas. The particle size distributions indicate that the majority of the emitted particles are in the size range 7-15nm. Three modes were observed during burning the candles with very different emission profiles: a "normal burning" mode characterized by low particle number emission rates and small particles; an initial "sooting" behavior after ignition, and a final "smoldering" phase upon candle extinction with higher particle number emission rates and larger particles. The particle emission upon extinction is dependent on the extinction method. The NOx emission indices were applied in a simple box model to calculate typical indoor NOx concentration levels from candle emissions, which were in excellent agreement with direct measurements in a typical indoor environment.

Impact of vacuum cleaning on indoor air quality

Vacuum cleaning can be a household source of particulate matter (PM) both from the vacuum motor and from settled dust resuspension. Despite the evidence of this contribution to PM levels indoors, the effect of this source on PM composition is still unknown. In this study, four vacuum cleaners (washable filter bag less, wet, bagged and HEPA filter equipped robot) were tested for the emission rate of particulate mass and number. The detailed PM chemical characterisation included organic and elemental carbon, metals and organic speciation. PM10 emission rates from bagged vacuum operation were much higher (207 ± 99.0 μg min−1) compared with the ones obtained from wet (86.1 ± 16.9 μg min−1) and washable filter bag less vacuums (75.4 ± 7.89 μg min−1). Particle (8–322 nm) number emission rates ranged from 5.29 × 1011 (washable filter bag less vacuum) to 21.2 × 1011 (wet vacuum) particles min−1. Ratios of peak to background levels indicate that vacuuming can elevate the ultrafine particle number concentrations by a factor ranging from 4 to 61. No increase in PM mass or number concentrations was observed during the HEPA filter equipped vacuum operation. The increase in copper and elemental carbon PM10 contents during vacuuming suggested motor emissions. Organic compounds in PM10 included alkanes, PAHs, saccharides, phenolics, alcohols, acids, among others. However, it was not possible to establish a relationship between these compounds and vacuuming due to the vast array of possible household sources. The cancer risks associated with metals and PAH inhalation were negligible.

Particle and volatile organic compound emissions from a 3D printer filament extruder

Fused Deposition Modeling (FDM®), also known as Fused Filament Fabrication (FFF), 3D printers have been shown in numerous studies to emit ultrafine particles and volatile organic compounds (VOCs). Filament extruders, designed to create feedstocks for 3D printers, have recently come onto the consumer market for at-home hobbyists as an alternative to buying 3D printer filaments. These instruments allow for the creation of 3D printer filaments from raw plastic pellets. Given the similarity in processes and materials used by 3D printers and filament extruders, we hypothesized that filament extruders may also release ultrafine particle emissions and VOCs. An off-the-shelf filament extruder was operated in a 2 m3 chamber using three separate feedstocks: acrylonitrile butadiene styrene (ABS) pellets, pulverized poly-lactic acid (PLA), and PLA pellets. Ultrafine particle emissions were measured in real-time using a scanning mobility particle sizer and thermal desorption tubes were used for both non-targeted and targeted analysis of VOCs present in emissions. Ultrafine particle number emission rates were comparable to those found in 3D printer studies with the greatest to least emission rates from ABS pellets, pulverized PLA, and PLA pellets, respectively. In addition, the majority of particles released were found to be ultrafine (1–100 nm), similar to 3D printer studies. A variety of VOCs were identified using the ABS feedstock, including styrene and ethylbenzene, and PLA feedstock. Styrene average mass concentration amounts were found to be near the EPA Integrated Risk Information System Reference Concentration for Inhalation Exposure for 3 min and 5 min samples. Further studies will be needed to determine the impact on emissions of environmental volume, air exchange rate, and extruder settings such as extrusion speed and temperature. The results support the hypothesis that use of a filament extruder may present an additional exposure risk to 3D printer hobbyists.

Particle emissions from fused deposition modeling 3D printers: Evaluation and meta-analysis

Fused deposition modeling (FDM) 3D printers, the most popular choice among home hobbyists, have been shown to release volatile organic chemicals (VOCs) and billions of airborne particles per minute, indicating the potential for consumer inhalation exposure and consequent health risks. Publications on FDM 3D printer emissions however, contain large heterogeneity of testing methods and analytical procedures making it difficult to reach overall conclusions for particle characteristics or particle number emission rates across the field. In this publication, data were collected over the printing time from 3D printer emission studies including particle count diameters (PCDs) (nanometers), particle number concentrations (PNCs) (particles/cm3), and particle number emission rates (PNERs) (particles min−1). Despite heterogeneity in methods, the majority of particles released were reported as ultrafine in size (i.e., <100 nm) indicating that using both acrylonitrile butadiene styrene (ABS) and poly-lactic acid (PLA) may present a risk of exposure to respirable particles. Mean PNC emitted in 3D printing tests ranged over several orders of magnitude across publications with overall means of 300,980 particles/cm3 for ABS and 65,482 particles/cm3 for PLA. Although mean PNC data were available from only 7 of the 16 papers reviewed, ABS resulted in greater particle numbers than PLA suggesting increased exposure to ultrafine particles. A linear mixed model was fitted for mean PNCs to further explore the impact of nozzle temperature and filament material. Finally, the PNER calculation method especially regarding losses, varied widely across studies, and directly impacted the PNERs reported. To strengthen direct comparability of results going forward, it is recommended that standard emissions testing protocols be developed for FDM 3D printers and particle influxes and losses be more uniformly calculated.

Contributions of burner, pan, meat and salt to PM emission during grilling

Grilling ground beef meat was conducted in two locations at Nazarbayev University, Kazakhstan. The experiments were designed such that only particles from beef meat were isolated. A similar experimental protocol was applied at both locations. The average particle number and mass emission rates for grilling pure meat itself (excluding particles from pan and burner) were found to be 9.4 × 1012(SD = 7.2 × 1012 particle min−1 and 7.6 × 10 (SD = 6.3 × 10) mg.min−1, respectively. The PM emissions (number and mass) from the burner were found to be negligible compared to the pan and meat emissions. Ultrafine particle (UFP) concentrations from the heated pan itself were comparable to those of grilled meat. However, the particle mass concentrations from the pan itself were negligible. Approximately an hour of continuous heating resulted in zero emissions from the pan.

Characterization and Control of Nanoparticle Emission during 3D Printing.

This study aimed to evaluate particle emission characteristics and to evaluate several control methods used to reduce particle emissions during three-dimensional (3D) printing. Experiments for particle characterization were conducted to measure particle number concentrations, emission rates, morphology, and chemical compositions under manufacturer-recommended and consistent-temperature conditions with seven different thermoplastic materials in an exposure chamber. Eight different combinations of the different control methods were tested, including an enclosure, an extruder suction fan, an enclosure ventilation fan, and several types of filter media. We classified the thermoplastic materials as high emitter (>1011 #/min), medium emitters (109 #/min -1011 #/min), and low emitters (<109 #/min) based on nanoparticle emissions. The nanoparticle emission rate was at least 1 order of magnitude higher for all seven filaments at the higher consistent extruder temperature than at the lower manufacturer-recommended temperature. Among the eight control methods tested, the enclosure with a high-efficiency particulate air (HEPA) filter had the highest removal effectiveness (99.95%) of nanoparticles. Our recommendations for reducing particle emissions include applying a low temperature, using low-emitting materials, and instituting control measures like using an enclosure around the printer in conjunction with an appropriate filter (e.g., HEPA filter) during 3D printing.

Particle emission rates during electrostatic spray deposition of TiO2 nanoparticle-based photoactive coating

Here, we studied the particle release rate during Electrostatic spray deposition of anatase-(TiO2)-based photoactive coating onto tiles and wallpaper using a commercially available electrostatic spray device. Spraying was performed in a 20.3m3 test chamber while measuring concentrations of 5.6nm to 31μm-size particles and volatile organic compounds (VOC), as well as particle deposition onto room surfaces and on the spray gun user hand. The particle emission and deposition rates were quantified using aerosol mass balance modelling. The geometric mean particle number emission rate was 1.9×1010s−1 and the mean mass emission rate was 381μgs−1. The respirable mass emission-rate was 65% lower than observed for the entire measured size-range. The mass emission rates were linearly scalable (±ca. 20%) to the process duration. The particle deposition rates were up to 15h−1 for <1μm-size and the deposited particles consisted of mainly TiO2, TiO2 mixed with Cl and/or Ag, TiO2 particles coated with carbon, and Ag particles with size ranging from 60nm to ca. 5μm. As expected, no significant VOC emissions were observed as a result of spraying. Finally, we provide recommendations for exposure model parameterization.

Investigation of nitrogen oxides, particle number, and size distribution on a light-duty diesel car with B10 and G10 fuels

Nitrogen oxides (NOx) and particle emissions from a light-duty diesel car with B10 (10% biodiesel from cooking oil +90% diesel, v/v) and G10 (10% GTL fuel +90% diesel, v/v) were investigated under the New European Driving Cycle (NEDC). The car was equipped with a high-pressure common rail system, cooled exhaust gas recirculation (EGR), and diesel oxidation catalyst (DOC). Results show that G10 has the lowest fuel consumption and B10 has the highest fuel consumption among the three fuels. B10 can increase the NOx emissions, and the G10 NOx emission is lower than diesel. The number-weighted particle size distribution shows that B10 and G10 can decrease the particle number at almost a full size range. In the four urban driving cycles (UDC), the geometric mean diameter (GMD) of B10 and G10 are both smaller than diesel. For the extra urban driving cycle (EUDC), the particle number concentration and emission rate are far higher than UDC cycle. The acceleration phase has a higher particle number emission rate and nucleation particle number than deceleration for the three fuels. Particle number emission is reduced when using B10 and G10 regardless of acceleration or deceleration. Number-weighted particle size distribution in acceleration and deceleration shows that the nucleation particle number in deceleration is far higher than acceleration, whereas accumulation particle shows the opposite tendency.

Effective Coagulation Coefficient Approach for Estimating Particle Number Emission Rates for Strong Emission Sources

Particle number emission rate is one of the important parameters that characterizes the emission source and it is an essential input to the aerosol dynamics models. Estimation of this quantity at the source is rather complicated due to the combined action of ventilation and coagulation on the depletion of particle number concentrations. Techniques to estimate number emission rate are still at preliminary stage and hence there is a definite need to develop a methodology for this purpose. In the present study, an effective coagulation coefficient (Keff) approach is provided to correct for coagulation losses encountered during experiments for the determination of number emission rate. Keff is expressed as a function of single parameter (β) namely the ratio of the prescribed ventilation rate and measured number concentration in the experiments. The utility of the approach is demonstrated by applying it to few practical cases reported in the literature. The results are further discussed.

Characterization of Real-World Particle Number Emissions during Reignition Events from a 2010 Light-Duty Hybrid Electric Vehicle

Despite the increasing popularity of hybrid electric vehicles (HEVs), few studies have compared the real-world particle emissions of HEVs from internal combustion engine (ICE) reignition events with that of a conventional vehicle (CV) during real-world driving. Reignition events occur under unstable combustion conditions and frequently result in particle number (PN) emission rates (PNERs) that exceed those for stabilized engine operation. Tailpipe PNERs from a CV and an HEV 2010 Toyota Camry were quantified on a 32-mi route over rural, urban, and freeway roadways in Chittenden County, Vermont, with the total onboard tailpipe emissions measurement system. This study directly compared the CV and HEV PNERs and characterized the operation of the HEV in a new HEV ICE operating mode framework. Mean PNER for reignition events (7.19 pM 11.8 × 1010 particles/s) were on average four times greater than for stabilized HEV operation (1.79 ± 3.99 × 1010 particles/s). Under urban, rural, and freeway driving, HEV reignition event operation accounted for 58.7%, 44.6%, and 5.0%, respectively, of the total PN inventory. Mean HEV PNER was 1.8 times greater than that of the CV in urban driving, while under freeway driving, where the two vehicles operated similarly, average CV PNER was 2.4 times greater than that of the HEV. The data show that the typical fuel consumption benefits of HEVs in urban driving are associated with a trade-off in PN emissions. The HEV ICE operating behavior has implications for the spatial distribution of PN hot spots as well as the associated microscale modeling of alternative vehicle technology emissions.

Comparison of particle mass and number emissions from a diesel transit bus across temporal and spatial scales

This study analyzes particle number and mass emission rates measured from the exhaust of a 2002 diesel transit bus in real-world driving conditions. The dynamics of the particle number and mass emission rates are examined at resolved temporal and spatial scales across an urban arterial, a rural arterial and a divided freeway. Time-based particle number and mass emission rates were highest on the freeway, but the distance-based particle emission rates of emission/km at “hot-spots” for exposure assessment for selected 50-m road segments occurred at intersections when the bus accelerated from a stop or traveled up high grades. Comparisons of particle mass and number emission rates between idling and acceleration indicate that unless the bus is extending idling for several minutes, public exposure to bus particle emissions near bus stops can be mainly attributed to accelerations. Generally, particle number and mass emissions rates are highly correlated both temporally and spatially. Some deviations occur because particle mass emissions are highly elevated during sustained fueling events such as traveling on high grades and during sustained accelerations, while particle number emissions are more sensitive to fuel and engine speed fluctuations.

A PEMS study of the emissions of gaseous pollutants and ultrafine particles from gasoline- and diesel-fueled vehicles

On-road emission measurements of gasoline- and diesel-fueled vehicles were conducted by a portable emission measurement system (PEMS) in Shanghai, China. Horiba OBS 2200 and TSI EEPS 3090 were employed to detect gaseous and ultrafine particle emissions during the tests. The driving-based emission factors of gaseous pollutants and particle mass and number were obtained on various road types. The average NOx emission factors of the diesel bus, diesel car, and gasoline car were 8.86, 0.68, and 0.17 g km−1, all of which were in excess of their emission limits. The particle number emission factors were 7.06 × 1014, 6.08 × 1014, and 1.57 × 1014 km−1, generally higher than the results for similar vehicle types reported in the previous studies. The size distributions of the particles emitted from the diesel vehicles were mainly concentrated in the accumulation mode, while those emitted from the gasoline car were mainly distributed in the nucleation mode. Both gaseous and particle emission rates exhibit significant correlations with the change in vehicle speed and power demand. The lowest emission rates for each vehicle type were produced during idling. The highest emission rates for each vehicle type were generally found in high-VSP bins. The particle number emission rates of the gasoline car show the strongest growth trend with increasing VSP and speed. The particle number emission for the gasoline car increased by 3 orders of magnitude from idling to the highest VSP and driving speed conditions. High engine power caused by aggressive driving or heavy loads is the main contributor to high emissions for these vehicles in real-world situations.

Particulate pollution in different housing types in a UK suburban location

To investigate the levels of particulate pollution in residential built environments measurements of PM10, PM2.5, and PM1 and concentrations were made between 2004 and 2008 in various residencies in a UK suburban location. Measurements were carried out in three different residential settings (Types I, II and III). In type I non-smoking living rooms, the highest 24-hour mean concentrations were found in summer. When smoking took place in type I residences, the concentrations of PM10, PM2.5 and PM1, during the winter were almost double those in summer. In type II houses the concentrations were higher in the houses with open plan kitchens than in those with separate kitchens. In type III houses, mean concentrations were significantly higher in wood heated living rooms than those using central heating. In kitchens, cooking resulted in substantially higher concentrations of particulate matter with levels above those in smoking living rooms in winter. The hourly maximum values of number concentration were considerably higher in smoking rooms than non-smoking ones. Cooking resulted in increased number concentrations, with the average hourly maximum concentration of 179,110 #/cm3. Particle mass and number emission rates were determined for a number of activities. In kitchens grilling had the highest average number emission rate, followed by boiling and frying. The results clearly highlight the impact of different forms of dwelling and their use and management by occupants on the levels of particulate matter in naturally ventilated residential built environments.

Onboard, Real-World Second-by-Second Particle Number Emissions from 2010 Hybrid and Comparable Conventional Vehicles

Despite hybrid-electric vehicles becoming more prominent in the on-road light-duty vehicle fleet, few studies have evaluated their real-world particle emissions. Hot-stabilized tailpipe particle number concentrations, emission rates, and number distributions emitted from two 2010 Toyota Camry vehicles—one hybrid and one conventional—were quantified during city driving in Burlington, Vermont, at ambient temperatures between −5°C and 9°C with the University of Vermont total onboard tailpipe emissions measurement system. Across replicate real-world runs, the average total cumulative particle number (3- to 3,000-nm particle diameter) emission rates measured for the hybrid vehicle were two times higher than that of the conventional vehicle, despite the hybrid vehicle's internal combustion engine being off 16% to 57% of the run duration. Average second-by-second number distributions for the conventional vehicle had three particle modes (10, 50, and 400 nm), whereas the broader hybrid vehicle distributions had two distinct modes (50 and 400 nm) with shoulders at 10 and 20 nm. These distributions changed little over the route for a given vehicle type. The unexpected higher particle number emission rates from the hybrid, and possibly the differences in number distributions, may be explained by an observed pattern of internal combustion engine restarts under stop-and-go driving that resulted in extreme particle emission rates up to 3.5 × 1010 (number per second) at every engine restart. The hybrid restart behavior resulted in high particle number emissions localized primarily at intersections. More detailed study is needed on different hybrid vehicle designs to determine the broader significance of the observed particle emission patterns.