Characterization of on-road vehicle emission factors and microenvironmental air quality in Beijing,China

In this paper, we report the results and analysis of a recent field campaign in August 2007 investigating the impacts of emissions from transportation on air quality and community concentrations in Beijing, China. We conducted measurements in three different environments, on-road, roadside and ambient. The carbon monoxide, black carbon and ultrafine particle number emission factors for on-road light-duty vehicles are derived to be 95 g kg^?1-fuel, 0.3 g kg^?1-fuel and 1.8 × 10¹⁵ particles kg^?1-fuel, respectively. The emission factors for on-road heavy-duty vehicles are 50 g kg^?1-fuel, 1.3 g kg^?1-fuel and 1.1 × 10¹⁶ particles kg^?1-fuel, respectively. The carbon monoxide emission factors from this study agree with those derived from remote sensing and on-board vehicle emission testing systems in China. The on-road black carbon and particle number emission factors for Chinese vehicles are reported for the first time in the literature. Strong traffic impacts can be observed from the concentrations measured in these different environments. Most clear is a reflection of diesel truck traffic activity in black carbon concentrations. The comparison of the particle size distributions measured at the three environments suggests that the traffic is a major source of ultrafine particles. A four-day traffic control experiment conducted by the Beijing Government as a pilot to test the effectiveness of proposed controls was found to be effective in reducing extreme concentrations that occurred at both on-road and ambient environments.     

Nanoparticle emissions on Minnesota highways

The objective of this project was to characterize on-road aerosol on highways surrounding the Minneapolis area. Data were collected under varying on-road traffic conditions and in residential areas to determine the impact of highway traffic on air quality. The study was focused on determining on-road nanoparticle concentrations, and estimating fuel-specific and particle emissions km⁻¹.On-road aerosol number concentrations ranged from 10⁴ to 10⁶ particles cm⁻³. The highest nanoparticle concentrations were associated with high-speed traffic. At high vehicular speeds engine load, exhaust temperature, and exhaust flow all increase resulting in higher emissions. Less variation was observed in particle volume, a surrogate measure of particle mass. Most of the particles added by the on-road fleet were below 50 nm in diameter. Particles in this size range may dominate particle number, but contribute little to particle volume or mass. Furthermore, particle number is strongly influenced by nucleation and coagulation, which have little or no effect on particle volume. Measurements made in heavy traffic, speeds<32 km h⁻¹, produced lower number concentrations and larger particles.Number concentrations measured in residential areas, 10–20 m from the highway, were considerably lower than on-road concentrations, but the size distributions were similar to on-road aerosol with high concentrations of very small (<20 nm) particles. Much lower number concentrations and larger particles were observed in residential areas located 500–700 m from the highway.Estimated emissions of total particle number larger than 3 nm ranged from 1.9 to 9.9×10¹⁴ particles km⁻¹ and 2.2–11×10¹⁵ particles (kg fuel)⁻¹ for a gasoline-dominated vehicle fleet.     

Pre- and post-catalyst-, fuel-, velocity- and acceleration-dependent benzene emission data of gasoline-driven EURO-2 passenger cars and light duty vehicles

The benzene emission characteristics of six gasoline-driven EURO-2 vehicles, three passenger cars and three light duty vehicles, have been determined by time-resolved chemical ionization mass spectrometry. Aliquots of the exhaust gas were monitored pre- and post-catalyst with two independently operating mass spectrometers. Each vehicle was driven with two different fuels having benzene contents of 1 and 2 vol%. Seven driving cycles—including the European (EDC) and the US (FTP-75) driving cycle—with a total driving time of about 8800 s were studied. Herein, we discuss the average emission characteristics of the entire fleet at transient driving in the velocity range of 0–150 km h⁻¹. The conversion efficiencies of the involved catalytic systems were deduced from the pre- and post-catalyst data. On average, the vehicles showed optimal benzene conversion efficiencies (>95%) in the velocity range of 30–90 km h⁻¹. When driving below 20 or above 100 km h⁻¹ reduced benzene conversion was found (80–82%). No benzene conversion was observed when driving above 130 km h⁻¹. In contrast, the post-catalyst benzene emissions exceeded those of the untreated exhaust gas by 19–49%. Thus on an average, benzene was formed across the catalysts under these conditions. In addition, the influence of the benzene content of the gasoline on the tail-pipe emissions was also studied. The use of the gasoline with 1 vol% benzene instead of 2 vol% induced a 20–30% reduction of the post-catalyst emissions when driving below 50 km h⁻¹. The fuel effect became smaller above 100 km h⁻¹ and was even negative at high engine load (>130 km h⁻¹). Thus under these conditions, when benzene is formed across the catalyst, the amount of the emitted benzene was independent of the benzene level of the fuel.     

On-road remote sensing measurements and fuel-based motor vehicle emission inventory in Hangzhou,China

Motor vehicles are one of the largest sources of air pollutants worldwide. Despite their importance, motor vehicle emissions are inadequately understood and quantified, esp. in developing countries. In this study, the real-world emissions of carbon monoxide (CO), hydrocarbons (HC) and nitrogen oxide (NO) were measured using an on-road remote sensing system at five sites in Hangzhou, China in 2004 and 2005. Average emission factors of CO, HC and NO_x for petrol vehicles of different model year, technology class and vehicle type were calculated in grams of pollutant per unit of fuel use (g l⁻¹) from approximately 32,260 petrol vehicles. Because the availability of data used in traditional on-road mobile source estimation methodologies is limited in China, fuel-based approach was implemented to estimate motor vehicle emissions using fuel sales as a measure of vehicle activity, and exhaust emissions factors from remote sensing measurements. The fuel-based exhaust emission inventories were also compared with the results from the recent international vehicle emission (IVE) model. Results show that petrol vehicle fleet in Hangzhou has significantly high CO emissions, relatively high HC and low NO_x, with the average emission factors of 193.07±15.63, 9.51±2.40 and 5.53±0.48 g l⁻¹, respectively. For year 2005 petrol vehicles exhaust emissions contributed with 182,013±16,936, 9107±2255 and 5050±480 metric ton yr⁻¹ of CO, HC and NO_x, respectively. The inventories are 45.5% higher, 6.6% higher and 53.7% lower for CO, HC and NO_x, respectively, than the estimates using IVE travel-based model. In addition, a number of insights about the emission distributions and formation mechanisms have been obtained from an in-depth analysis of these results.     

Roadside measurements of fine and ultrafine particles at a major road north of Gothenburg

Particle measurements were conducted at a road site 15 km north of the city of Gothenburg for 3 weeks in June 2000. The size distribution between 10 and 368 nm was measured continuously by using a differential mobility particle sizer (DMPS) system. PM_2.5 was sampled on a daily basis with subsequent elemental analysis using EDXRF-spectroscopy. The road is a straight four-lane road with a speed limit of 90 kph. The road passing the site is flat with no elevations where the vehicles run on a steady workload and with constant speed. The traffic intensity is about 20,000 cars per workday and 13,000 vehicles per day during weekends. The diesel fuel used in Sweden is low in sulphur content (<10 ppm) and therefore the diesel vehicles passing the site contribute less to particle emissions in comparison with other studies. A correlation between PM_2.5 and accumulation mode particles (100–368 nm) was observed. However, no significant correlation was found between number concentrations of ultrafine particles (10–100 nm) and PM_2.5 or the accumulation mode number concentration. The particle distribution between 10 and 368 nm showed great dependency on wind speed and wind direction, where the wind speed was the dominant factor for ultrafine (10–100 nm) particle concentrations. The difference in traffic intensity between workday and weekend together with wind data made it possible to single out the traffic contribution to particle emissions and measure the size distribution. The results presented in combination with previous studies show that both PM_2.5 and the mass of accumulation mode particles are bad estimates for ultrafine particles.     

Trends in on-road vehicle emissions of ammonia

Motor vehicle emissions of ammonia have been measured at a California highway tunnel in the San Francisco Bay area. Between 1999 and 2006, light-duty vehicle ammonia emissions decreased by 38 ± 6%, from 640 ± 40 to 400 ± 20 mg kg^?1. High time resolution measurements of ammonia made in summer 2001 at the same location indicate a minimum in ammonia emissions correlated with slower-speed driving conditions. Variations in ammonia emission rates track changes in carbon monoxide more closely than changes in nitrogen oxides, especially during later evening hours when traffic speeds are highest. Analysis of remote sensing data of Burgard et al. (Environmental Science Technology 2006, 40, 7018–22) indicates relationships between ammonia and vehicle model year, nitrogen oxides, and carbon monoxide. Ammonia emission rates from diesel trucks were difficult to measure in the tunnel setting due to the large contribution to ammonia concentrations in a mixed-traffic bore that were assigned to light-duty vehicle emissions. Nevertheless, it is clear that heavy-duty diesel trucks are a minor source of ammonia emissions compared to light-duty gasoline vehicles.     

Comparison of measured and model-calculated real-world traffic emissions

The quality of an emission calculation model based on emission factors measured on roller test stands and statistical traffic data was evaluated using source strengths and emission factors calculated from real-world exhaust gas concentration differences measured upwind and downwind of a motorway in southwest Germany. Gaseous and particulate emissions were taken into account. Detailed traffic census data were taken during the measurements. The results were compared with findings of similar studies.The main conclusion is the underestimation of CO and NO_x source strengths by the model. On the average, it amounts to 23% in case of CO and 17% for NO_x. The latter underestimation results from an undervaluation by 22% of NO_x emission factors of heavy-duty vehicles (HDVs). There are significant differences between source strengths on working days and weekends because of the different traffic split between light-duty vehicles (LDVs) and HDVs. The mean emission factors of all vehicles from measurements are 1.08 g km⁻¹ veh⁻¹ for NO_x and 2.62 g km⁻¹ veh⁻¹ for CO. The model calculations give 0.92 g km⁻¹ veh⁻¹ for NO_x and 2.14 g km⁻¹ veh⁻¹ for CO.The source strengths of 21 non-methane hydrocarbon (NMHC) compounds quantified are underestimated by the model. The ratio between the measured and model-calculated emissions ranges from 1.3 to 2.1 for BTX and up to 21 for 16 other NMHCs. The reason for the differences is the insufficient knowledge of NMHC emissions of road traffic.Particulate matter emissions are dominated by ultra-fine particles in the 10–40 nm range. As far as aerosols larger than 29 nm are concerned, 1.80×10¹⁴ particles km⁻¹ veh⁻¹ are determined for all vehicles, 1.22×10¹⁴ particles km⁻¹ veh⁻¹ and an aerosol volume of 0.03 cm³ km⁻¹ veh⁻¹ are measured for LDVs, and for HDVs 7.79×10¹⁴ particles km⁻¹ veh⁻¹ and 0.41 cm³ km⁻¹ veh⁻¹ are calculated. Traffic-induced turbulence has been identified to have a decisive influence on exhaust gas dispersion near the source.     

Emissions of PCDD/Fs,PCBs, and PAHs from legacy on-road heavy-duty diesel engines

Exhaust emissions of seventeen 2,3,7,8-substituted polychlorinated dibenzo-p-dioxin/furan (PCDD/F) congeners, tetra–octa PCDD/F homologues, 12 WHO 2005 polychlorinated biphenyl (PCB) congeners, mono–nona chlorinated biphenyl homologues, and 19 polycyclic aromatic hydrocarbons (PAHs) from three legacy diesel engines were investigated. The three engines tested were a 1985 model year GM 6.2 J-series engine, a 1987 model year Detroit Diesel Corporation 6V92 engine, and a 1993 model year Cummins L10 engine. Results were compared to United States’ mobile source inventory for on-road diesel engines, as well as historic and modern diesel engine emission values. The test fuel contained chlorine at 9.8 ppm which is 1.5 orders of magnitude above what is found in current diesel fuel and 3900 ppm sulfur to simulate fuels that would have been available when these engines were produced. Results indicate PCDD/F emissions of 13.1, 7.1, and 13.6 pg International Toxic Equivalency (I-TEQ) L⁻¹ fuel consumed for the three engines respectively, where non-detects are equal to zero. This compares with a United States’ mobile source on-road diesel engine inventory value of 946 pg I-TEQ L⁻¹ fuel consumed and 1.28 pg I-TEQ L⁻¹ fuel consumed for modern engines equipped with a catalyzed diesel particle filter and urea selective catalytic reduction. PCB emissions are 2 orders of magnitude greater than modern diesel engines. PAH results are representative of engines from this era based on historical values and are 3–4 orders of magnitude greater than modern diesel engines.     

Mercury emissions from automobiles using gasoline,diesel, and LPG

Mercury (Hg) emissions from gasoline, diesel, and liquefied petroleum gas (LPG) vehicles were measured and speciated (particulate, oxidized, and elemental mercury). First, three different fuel types were analyzed for their original Hg contents; 571.1±4.5 ng L⁻¹ for gasoline, 185.7±2.6 ng L⁻¹ for diesel, and 1230.3±23.5 ng L⁻¹ for LPG. All three vehicles were then tested at idling and driving modes. Hg in the exhaust gas was mostly in elemental form (Hg⁰), and no detectable levels of particulate (Hg^p) or oxidized (Hg²⁺) mercury were measured. At idling modes, Hg concentrations in the exhaust gas of gasoline, diesel, and LPG vehicles were 1.5–9.1, 1.6–3.5, and 10.2–18.6 ng m⁻³, respectively. At driving modes, Hg concentrations were 3.8–16.8 ng m⁻³ (gasoline), 2.8–8.5 ng m⁻³ (diesel), and 20.0–26.9 ng m⁻³ (LPG). For all three vehicles, Hg concentrations at driving modes were higher than at idling modes. Furthermore, Hg emissions from LPG vehicle was highest of all three vehicle types tested, both at idling and driving modes, as expected from the fact that it had the highest original fuel Hg content.     

A mobile pollutant measurement laboratory—measuring gas phase and aerosol ambient concentrations with high spatial and temporal resolution

A mobile pollutant measurement laboratory was designed and built at the Paul Scherrer Institute (Switzerland) for the measurement of on-road ambient concentrations of a large set of trace gases and aerosol parameters with high time resolution (<15 s for most instruments), along with geographical and meteorological information. This approach allowed for pollutant level measurements both near traffic (e.g. in urban areas or on freeways/main roads) and at rural locations far away from traffic, within short periods of time and at different times of day and year. Such measurements were performed on a regular base during the project year of gas phase and aerosol measurements (YOGAM). This paper presents data measured in the Zürich (Switzerland) area on a late autumn day (6 November) in 2001. The local urban particle background easily reached 50 000 cm⁻³, with additional peak particle number concentrations of up to 400 000 cm⁻³. The regional background of the total particle number concentration was not found to significantly correlate with the distance to traffic and anthropogenic emissions of carbon monoxide and nitrogen oxides. On the other hand, this correlation was significant for the number concentration of particles in the size range 50–150 nm, indicating that the particle number concentration in this size range is a better traffic indicator than the total number concentration. Particle number size distribution measurements showed that daytime urban ambient air is dominated by high number concentrations of ultrafine particles (nanoparticles) with diameters <50 nm, which are immediately formed by traffic exhaust and thus belong to the primary emissions. However, significant variation of the nanoparticle mode was also observed in number size distributions measured in rural areas both at daytime and nighttime, suggesting that nanoparticles are not exclusively formed by primary traffic emissions. While urban daytime total number concentrations were increased by a factor of 10 compared to the nighttime background, corresponding factors for total surface area and total volume concentrations were 2 and 1.5, respectively.     

On-road emission characteristics of heavy-duty diesel vehicles in Shanghai

On-road vehicle tests of nine heavy-duty diesel trucks were conducted using SEMTECH-D, an emissions measuring instrument provided by Sensors, Inc. The total length of roads for the tests was 186 km. Data were obtained for 37,255 effective driving cycles, including 17,216 on arterial roads, 15,444 on residential roads, and 4595 on highways. The impacts of speed and acceleration on fuel consumption and emissions were analyzed. Results show that trucks spend an average of 16.5% of the time in idling mode, 25.5% in acceleration mode, 27.9% in deceleration mode, and only 30.0% at cruise speed. The average emission factors of CO, total hydrocarbons (THC), and NO_x for the selected vehicles are (4.96±2.90), (1.88±1.03) and (6.54±1.90) g km⁻¹, respectively. The vehicle emission rates vary significantly with factors like speed and acceleration. The test results reflect the actual traffic situation and the current emission status of diesel trucks in Shanghai. The measurements show that low-speed conditions with frequent acceleration and deceleration, particularly in congestion conditions, are the main factors that aggravate vehicle emissions and cause high emissions of CO and THC. Alleviating congestion would significantly improve vehicle fuel economy and reduce CO and THC emissions.     

Decadal reductions of traffic emissions on a transit route in Austria – results of the Tauerntunnel experiment 1997

Real-world emissions of a traffic fleet on a transit route in Austria were determined in the Tauerntunnel experiment in October 1997. The total number of vehicles and the average speed was nearly the same on both measuring days (465 vehicles 30 min⁻¹ and 76 km h⁻¹ on the workday, 477 and 78 km h⁻¹ on Sunday). The average workday fleet contained 17.6% heavy-duty vehicles (HDV) and the average Sunday fleet 2.8% HDV resulting in up to four times higher emission rates per vehicle per km on the workday than on Sunday for most of the regulated components (CO₂, CO, NO_x, SO₂, and particulate matter-PM10). Emission rates of NMVOC accounted for 200 mg vehicle⁻¹ km⁻¹ on both days. The relative contributions of light-duty vehicles (LDV) and HDV to the total emissions indicated that aldehydes, BTEX (benzene, toluene, ethylbenzene, xylenes), and alkanes are mainly produced by LDV, while HDV dominated emissions of CO, NO_x, SO₂, and PM10. Emissions of NO_x caused by HDV were 16,100 mg vehicle⁻¹ km⁻¹ (as NO₂). Produced by LDV they were much lower at 360 mg vehicle⁻¹ km⁻¹. Comparing the emission rates to the results that were obtained by the 1988 experiment at the same place significant changes in the emission levels of hydrocarbons and CO, which accounted 1997 to only 10% of the levels in 1988, were noticed. However, the decrease of PM has been modest leading to values of 80 and 60% of the levels in 1988 on the workday and on Sunday, respectively. Emission rates of NO_x determined on the workday in 1997 were 3130 mg vehicle⁻¹ km⁻¹ and even higher than in 1988 (2630 mg vehicle⁻¹ km⁻¹), presumable due to the increase of the HD-traffic.     

On-road remote sensing of liquefied petroleum gas (LPG) vehicle emissions measurement and emission factors estimation

In the present study, the real-world on-road liquefied petroleum gas (LPG) vehicle/taxi emissions of carbon monoxide (CO), hydrocarbon (HC) and nitric oxide (NO) were investigated. A regression analysis approach based on the measured LPG vehicle emission data was also used to estimate the on-road LPG vehicle emission factors of CO, HC and NO with respect to the effects of instantaneous vehicle speed and acceleration/deceleration profiles for local urban driving patterns. The results show that the LPG vehicle model years and driving patterns have a strong correlation to their emission factors. A unique correlation of LPG vehicle emission factors (i.e., g km⁻¹ and g l⁻¹) on different model years for urban driving patterns has been established. Finally, a comparison was made between the average LPG, and petrol [Chan, T.L., Ning, Z., Leung, C.W., Cheung, C.S., Hung, W.T., Dong, G., 2004. On-road remote sensing of petrol vehicle emissions measurement and emission factors estimation in Hong Kong. Atmospheric Environment 38, 2055–2066 and 3541] and diesel [Chan, T.L., Ning, Z., 2005. On-road remote sensing of diesel vehicle emissions measurement and emission factors estimation in Hong Kong. Atmospheric Environment 39, 6843–6856] vehicle emission factors. It has shown that the introduction of the replacement of diesel taxis to LPG taxis has alleviated effectively the urban street air pollution. However, it has demonstrated that proper maintenance on the aged LPG taxis should also be taken into consideration.     

Road traffic emission factors for heavy metals

Quantifying the emissions and concentrations of heavy metals in urban air is a prerequisite for assessing their health effects. In this paper a combination of measurements and modelling is used to assess the contribution from road traffic emissions. Concentrations of particulate heavy metals in air were measured simultaneously during 1 year at a densely trafficked street and at an urban background site in Stockholm, Sweden. Annual mean concentrations of cadmium were 50 times lower than the EU directive and for nickel and arsenic concentrations were 10 and six times lower, respectively. More than a factor of two higher concentrations was in general observed at the street in comparison to roof levels indicating the strong influence from local road traffic emissions. The only compound with a significantly decreasing trend in the urban background was Pb with 9.1 ng m^?3 in 1995/96 compared to 3.4 ng m^?3 2003/04. This is likely due to decreased emissions from wear of brake linings and reduced emissions due to oil and coal combustion in central Europe.Total road traffic emission factors for heavy metals were estimated using parallel measurements of NOx concentrations and knowledge of NOx emission factors. In general, the emission factors for the street were higher than reported in road tunnel measurements. This could partly be due to different driving conditions, since especially for metals which are mainly emitted from brake wear, more stop and go driving in the street compared to in road tunnels is likely to increase emissions. Total emissions were compared with exhaust emissions, obtained from the COPERT model and brake wear emissions based on an earlier study in Stockholm. For Cu, Ni and Zn the sum of brake wear and exhaust emissions agreed very well with estimated total emission factors in this study. More than 90% of the road traffic emissions of Cu were due to brake wear. For Ni more than 80% is estimated to be due to exhaust emissions and for Zn around 40% of road traffic emissions are estimated to be due to exhaust emissions. Pb is also mainly due to exhaust emissions (90%); a fuel Pb content of only 0.5 mg L^?1 would give similar emission factor as that based on the concentration increment at the street. This is the first study using simultaneous measurements of heavy metals at street and roof enabling calculations of emission factors using a tracer technique.     

Aerosol number size distributions within the exhaust plume of a diesel and a gasoline passenger car under on-road conditions and determination of emission factors

A new setup has been developed and built to measure number size distributions of exhaust particles and thermodynamic parameters under real traffic conditions. Measurements have been performed using a diesel and a gasoline passenger car driving with different speeds and engine conditions. Significant number of nucleation mode particles was found only during high load conditions, i.e. high car and engine speeds behind the diesel car. The number concentration of soot mode particles varied within a factor of two for different engine conditions while the concentration of nucleation mode particles varied up to two orders of magnitude. The results show that roadside measurements are still quite different from those behind the tailpipe. Beside dilution transformation processes within the first meter behind the tailpipe also play an important role, such as nucleation and growth. Emission factors were calculated and compared with those obtained by other studies. Emission factors for particles larger than 25 nm (primary emissions) varied within 1.1 × 10¹⁴ km^?1 and 2.7 × 10¹⁴ km^?1 for the diesel car and between 0.6 × 10¹² km^?1 and 3.5 × 10¹² km^?1 for the gasoline car. The advantage of these measurements is the exhaust dilution under atmospheric conditions and the size-resolved measurement technique to divide into primary emitted and secondary formed particles.     

Global atmospheric emission inventory of polycyclic aromatic hydrocarbons (PAHs) for 2004

The global atmospheric emissions of the 16 polycyclic aromatic hydrocarbons (PAHs) listed as the US EPA priority pollutants were estimated using reported emission activity and emission factor data for the reference year 2004. A database for emission factors was compiled, and their geometric means and frequency distributions applied for emission calculation and uncertainty analysis, respectively. The results for 37 countries were compared with other PAH emission inventories. It was estimated that the total global atmospheric emission of these 16 PAHs in 2004 was 520 giga grams per year (Gg y^?1) with biofuel (56.7%), wildfire (17.0%) and consumer product usage (6.9%) as the major sources, and China (114 Gg y^?1), India (90 Gg y^?1) and United States (32 Gg y^?1) were the top three countries with the highest PAH emissions. The PAH sources in the individual countries varied remarkably. For example, biofuel burning was the dominant PAH source in India, wildfire emissions were the dominant PAH source in Brazil, while consumer products were the major PAH emission source in the United States. In China, in addition to biomass combustion, coke ovens were a significant source of PAHs. Globally, benzo(a)pyrene accounted for 0.05% to 2.08% of the total PAH emission, with developing countries accounting for the higher percentages. The PAH emission density varied dramatically from 0.0013 kg km^?2 y in the Falkland Islands to 360 kg km^?2 y in Singapore with a global mean value of 3.98 kg km^?2 y. The atmospheric emission of PAHs was positively correlated to the country's gross domestic product and negatively correlated with average income. Finally, a linear bivariate regression model was developed to explain the global PAH emission data.     

A novel field measurement method for determining fine particle and gas emissions from residential wood combustion

Emission data from residential wood combustion are usually obtained on test stands in the laboratory but these measurements do not correspond to the operational conditions in the field because of the technological boundary conditions (e.g. testing protocol, environmental and draught conditions). The field measurements take into account the habitual practice of the operators and provide the more reliable results needed for emission inventories. In this study, a workable and compact method for measuring emissions from residential wood combustion in winter conditions was developed. The emissions for fine particle, gaseous and PAH compounds as well as particle composition in real operational conditions were measured from seven different appliances. The measurement technique worked well and was evidently suitable for winter conditions. It was easy and fast to use, and no construction scaffold was needed. The dilution of the sample with the combination of a porous tube diluter and an ejector diluter was well suited to field measurement. The results indicate that the emissions of total volatile organic carbon (TVOC) (17 g kg⁻¹ (of dry wood burned)), carbon monoxide (CO) (120 g kg⁻¹) and fine particle mass (PM₁) (2.7 g kg⁻¹) from the sauna stove were higher than in the other measured appliances. In the masonry heaters, baking oven and stove, the emissions were 2.9–9 g kg⁻¹ TVOC, 28–68 g kg⁻¹ CO and 0.6–1.6 g kg⁻¹ PM₁. The emission of 12 PAHs (PAH₁₂) from the sauna stove was 164 mg kg⁻¹ and consisted mainly of PAHs with four benzene rings in their structure. PAH₁₂ emission from other appliances was, on average, 21 mg kg⁻¹ and was dominated by 2-ring PAHs. These results indicate that despite the non-optimal operational practices in the field, the emissions did not differ markedly from the laboratory measurements.     

Ions in motor vehicle exhaust and their dispersion near busy roads

Measurements in the exhaust plume of a petrol-driven motor car showed that molecular cluster ions of both signs were present in approximately equal amounts. The emission rate increased sharply with engine speed while the charge symmetry remained unchanged. Measurements at the kerbside of nine motorways and five city roads showed that the mean total cluster ion concentration near city roads (603 cm^?3) was about one-half of that near motorways (1211 cm^?3) and about twice as high as that in the urban background (269 cm^?3). Both positive and negative ion concentrations near a motorway showed a significant linear increase with traffic density (R² = 0.3 at p < 0.05) and correlated well with each other in real time (R² = 0.87 at p < 0.01). Heavy duty diesel vehicles comprised the main source of ions near busy roads. Measurements were conducted as a function of downwind distance from two motorways carrying around 120–150 vehicles per minute. Total traffic-related cluster ion concentrations decreased rapidly with distance, falling by one-half from the closest approach of 2 m to 5 m of the kerb. Measured concentrations decreased to background at about 15 m from the kerb when the wind speed was 1.3 m s^?1, this distance being greater at higher wind speed. The number and net charge concentrations of aerosol particles were also measured. Unlike particles that were carried downwind to distances of a few hundred metres, cluster ions emitted by motor vehicles were not present at more than a few tens of metres from the road.     

Particulate Emission Rates for Unpaved Shoulders along a Paved Road

ABSTRACT

This paper reports the first empirical estimate of particle emissions from unpaved shoulders along paved roads.¹ Its objectives are to develop and demonstrate an emission rate measurement methodology that can be applied in different areas; identify the mechanisms that suspend dust from unpaved shoulders and the observables related to this suspension process; and quantify PM₁₀ mass emissions in the form of an emission rate. To achieve these objectives, fast-response observations from nephelometers and a sonic anemometer were used to characterize shortlived dust plumes generated by passing vehicles. In addition, detailed soil surface measurements determined the mechanical properties of the shoulder surfaces.

Large traffic-induced turbulence events that led to significant dust entrainment were almost exclusively caused by “large” vehicles such as trucks, semis, and vehicles pulling trailers, all traveling 50-65 mph. PM₁₀ emission rates for these large, fast-traveling vehicles were determined to be 8 ± 4 grams per vehicle kilometer traveled under dry conditions. Emissions due to smaller vehicles such as cars, vans, and sport utility vehicles were negligible for normal on-road driving. These results indicate that the majority of PM₁₀ emissions from unpaved shoulders is caused by relatively few vehicles.     

Application of a Lagrangian particle model to assess the impact of harbour,industrial and urban activities on air quality in the Taranto area,Italy

This paper evaluates the relative impact on air quality of harbour emissions, with respect to other emission sources located in the same area. The impact assessment study was conducted in the city of Taranto, Italy. This area was considered as representative of a typical Mediterranean harbour region, where shipping, industries and urban activities co-exist at a short distance, producing an ideal case to study the interaction among these different sources. Chemical and meteorological field campaigns were carried out to provide data to this study. An emission inventory has been developed taking into account industrial sources, traffic, domestic heating, fugitive and harbour emissions. A 3D Lagrangian particle dispersion model (SPRAY) has then been applied to the study area using reconstructed meteorological fields calculated by the diagnostic meteorological model MINERVE. 3D short term hourly concentrations have been computed for both all and specific sources. Industrial activities are found to be the main contributor to SO₂. Industry and traffic emissions are mainly responsible for NO_x simulated concentrations. CO concentrations are found to be mainly related to traffic emissions, while primary PM₁₀ simulated concentrations tend to be linked to industrial and fugitive emissions. Contributions of harbour activities to the seasonal average concentrations of SO₂ and NO_x are predicted to be up to 5 and 30 μg m⁻³, respectively to be compared to a overall peak values of 60 μg m⁻³ for SO₂ and 70 μg m⁻³ for NO_x. At selected urban monitoring stations, SO₂ and NO_x average source contributions are predicted to be both of about 9% from harbour activities, while 87% and 41% respectively of total concentrations are predicted to be of industrial origin.