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.     

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.     

Predictive NOx emission monitoring on board a passenger ferry

NO_x emissions from a medium speed diesel engine on board a servicing passenger ferry have been indirectly measured using a predictive emission monitoring system (PEMS) over a 1-yr period. Conventional NO_x measurements were carried out with a continuous emission monitoring system (CEMS) at the start of the study to provide historical data for the empirical PEMS function. On three other occasions during the year the CEMS was also used to verify the PEMS and follow any changes in emission signature of the engine. The PEMS consisted of monitoring exhaust O₂ concentrations (in situ electrochemical probe), engine load, combustion air temperature and humidity, and barometric pressure. Practical experiences with the PEMS equipment were positive and measurement data were transferred to a land-based office by using a modem data communication system. The initial PEMS function (PEMS1) gave systematic differences of 1.1–6.9% of the calibration domain (0–1725 ppm) and a relative accuracy of 6.7% when compared with CEMS for whole journeys and varying load situations. Further improvements on the performance could be obtained by updating this function. The calculated yearly emission for a total engine running time of 4618 h was 316 t NO_x±38 t and the average NO_x emission corrected for ambient conditions 14.3 g kWh_corr⁻¹. The exhaust profile of the engine in terms of NO_x, CO and CO₂ emissions as determined by CEMS was similar for most of the year. Towards the end of the study period, a significantly lower NO_x emission was detected which was probably caused by replacement of fuel injector nozzles. The study suggests that PEMS can be a viable option for continuous, long-term NO_x measurements on board ships.     

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.     

Hydrocarbon emission fingerprints from contemporary vehicle/engine technologies with conventional and new fuels

The present paper presents results from the analysis of 29 individual C₂–C₉ hydrocarbons (HCs) specified in the European Commission Ozone Directive. The 29 HCs are measured in exhaust from common, contemporary vehicle/engine/fuel technologies for which very little or no data is available in the literature. The obtained HC emission fingerprints are compared with fingerprints deriving from technologies that are being phased out in Europe. Based on the total of 138 emission tests, thirteen type-specific fingerprints are extracted (Mean ± SD percentage contributions from individual HCs to the total mass of the 29 HCs), essential for receptor modelling source apportionment. The different types represent exhaust from Euro3 and Euro4 light-duty (LD) diesel and petrol-vehicles, Euro3 heavy-duty (HD) diesel exhaust, and exhaust from 2-stroke preEuro, Euro1 and Euro2 mopeds. The fuels comprise liquefied petroleum gas, petrol/ethanol blends (0–85% ethanol), and mineral diesel in various blends (0–100%) with fatty acid methyl esters, rapeseed methyl esters palm oil methyl esters, soybean oil methyl or sunflower oil methyl esters. Type-specific tracer compounds (markers) are identified for the various vehicle/engine/fuel technologies.An important finding is an insignificant effect on the HC fingerprints of varying the test driving cycle, indicating that combining HC fingerprints from different emission studies for receptor modelling purposes would be a robust approach.The obtained results are discussed in the context of atmospheric ozone formation and health implications from emissions (mg km^?1 for LD and mopeds and mg kW h^?1 for HD, all normalised to fuel consumption: mg dm^?3 fuel) of the harmful HCs, benzene and 1,3-butadiene.Another important finding is a strong linear correlation of the regulated “total” hydrocarbon emissions (tot-HC) with the ozone formation potential of the 29 HCs (ΣPO₃ = (1.66 ± 0.04) × tot-RH; r² = 0.93). Tot-HC is routinely monitored in emission control laboratories, whereas C₂–C₉ are not. The revealed strong correlations broadens the usability of data from vehicle emission control laboratories and facilitates the comparison of the ozone formation potential of HCs in exhaust from of old and new vehicle/engine/fuel technologies.     

Characterizations of chemical oxidants in Mexico City: A regional chemical dynamical model (WRF-Chem) study

The formation of chemical oxidants, particularly ozone, in Mexico City were studied using a newly developed regional chemical/dynamical model (WRF-Chem). The magnitude and timing of simulated diurnal cycles of ozone (O₃), carbon monoxide (CO) and nitrogen oxides (NO_x)_, and the maximum and minimum O₃ concentrations are generally consistent with surface measurements. Our analysis shows that the strong diurnal cycle in O₃ is mainly attributable to photochemical variations, while diurnal cycles of CO and NO_x mainly result from variations of emissions and boundary layer height. In a sensitivity study, oxidation reactions of aromatic hydrocarbons (HCs) and alkenes yield highest peak O₃ production rates (20 and 18 ppbv h⁻¹, respectively). Alkene oxidations, which are generally faster, dominate in early morning. By late morning, alkene concentrations drop, and oxidations of aromatics dominate, with lesser contributions from alkanes and CO. The sensitivity of O₃ concentrations to NO_x and HC emissions was assessed. Our results show that daytime O₃ production is HC-limited in the Mexico City metropolitan area, so that increases in HC emissions increase O₃ chemical production, while increases in NO_x emissions decrease O₃ concentrations. However, increases in both NO_x and HC emissions yield even greater O₃ increases than increases in HCs alone. Uncertainties in HC emissions estimates give large uncertainties in calculated daytime O₃, while NO_x emissions uncertainties are less influential. However, NO_x emissions are important in controlling O₃ at night.     

Influence of passenger car auxiliaries on pollutant emission factors within the Artemis model

The impact of the auxiliaries and particularly air conditioning on emissions (CO₂, CO, HC, NO_x and particles) is investigated. To this aim, various data from European laboratories are used and analysed. Parameters linked to technology and to climatic conditions are investigated. The main distinction is made between gasoline and diesel vehicles. A physical model is proposed to extrapolate the excess emissions at low temperature (below 28 °C) and with solar radiation, together with a statistical model.     

A Fuel-Based Motor Vehicle Emission Inventory

Abstract

A fuel-based methodology for calculating motor vehicle emission inventories is presented. In the fuel-based method, emission factors are normalized to fuel consumption and expressed as grams of pollutant emitted per gallon of gasoline burned. Fleet-average emission factors are calculated from the measured on-road emissions of a large, random sample of vehicles. Gasoline use is known at the state level from sales tax data, and may be disaggregated to individual air basins. A fuel-based motor vehicle CO inventory was calculated for the South Coast Air Basin in California for summer 1991. Emission factors were calculated from remote sensing measurements of more than 70,000 in-use vehicles. Stabilized exhaust emissions of CO were estimated to be 4400 tons/day for cars and 1500 tons/day for light-duty and medium- duty trucks, with an estimated uncertainty of ±20% for cars and ±30% for trucks. Total motor vehicle CO emissions, including incremental start emissions and emissions from heavy-duty vehicles were estimated to be 7900 tons/day. Fuelbased inventory estimates were greater than those of California's MVEI 7F model by factors of 2.2 for cars and 2.6 for trucks. A draft version of California's MVEI 7G model, which includes increased contributions from high-emitting vehicles and off-cycle emissions, predicted CO emissions which closely matched the fuel-based inventory. An analysis of CO mass emissions as a function of vehicle age revealed that cars and trucks which were ten or more years old were responsible for 58% of stabilized exhaust CO emissions from all cars and trucks.     

Using NOx and CO monitoring data to indicate fine aerosol number concentrations and emission factors in three UK conurbations

It is increasingly accepted that although exposure to elevated concentrations of PM₁₀ is associated with an increased risk of mortality and morbidity, the relationship may not be causal. Rather, there is evidence that number concentrations may be a more appropriate metric than mass concentrations in evaluating health risk. Number concentrations are not routinely monitored and spatial and temporal patterns are poorly quantified. CO and NO_x are co-pollutants with their major urban source in common with fine particles, i.e. road vehicle emissions; are routinely monitored in many cities and are also related to ill health. Datasets of particle number concentration measurements from approximately month-long field campaigns in Manchester, Edinburgh and Birmingham (UK) are compared with simultaneous concentrations of CO and NO_x from nearby fixed monitors. It was found that it might be possible to reliably predict particle number concentrations (diameters>100 nm) on an hourly basis in Manchester city centre from knowledge of NO_x or CO concentrations alone. The influences of meteorology, spatial variability in emissions and lack of co-location upon the correlations are investigated using cluster analysis. The cluster analysis revealed that these relationships may vary between cities and are dependent upon monitor location but in ways that can be ascribed. For two out of three sites there existed a linear relationship between average cluster aerosol and gas concentrations. This indicates that although airmass aging disrupts the short-term linear relationship, the relationship in the average survives. An emission ratio of particles (approx. 100–500 nm diameter) to NO_x of approximately 50 cm⁻³ ppb⁻¹ was estimated in Manchester and Birmingham. Particle mass spectrometry measurements indicated that organic compounds dominated these particles and an emission rate of 0.58 ton km⁻² a⁻¹ of organic particulate matter from road transport has been estimated for the Greater Manchester conurbation.     

Application of CALINE4 to roadside NO/NO2 transformations

The CALINE4 roadway dispersion model has been applied to concentrations of NO_x and NO₂ measured near Gandy Boulevard in Tampa, FL (USA) during May 2002. A NO_x emission factor of 0.86 gr mi⁻¹ was estimated by treating NO+NO₂ (NO_x) as a conserved species and minimizing the differences between measured and calculated NO_x concentrations. This emission factor was then used to calculate NO₂ concentrations using the NO/NO₂ transformation reactions built into CALINE4. A comparison of measured and calculated NO₂ concentrations indicates that for ambient O₃ concentrations less than 40 ppb the model under-predicts the chemical transformation of NO. The enhanced transformation of NO may be due to reactions of NO with oxidants such as peroxy radicals that are present either in the atmosphere or in vehicle exhaust.     

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.     

Analysis and modelling of the pollutant emissions from European cars regarding the driving characteristics and test cycles

Within the European research project ARTEMIS, significant works have been conducted to analyse the hot emissions of pollutant from the passenger cars regarding the driving cycles and to propose modelling approaches taking into account large but heterogeneous datasets recorded in Europe. The review and analysis of a large range of test cycles enabled first the building-up of a set of contrasted cycles specifically designed for characterizing the influence of the driving conditions. These cycles were used for the measurement of the pollutants emission rates from nine passenger cars on a chassis dynamometer.Emissions measured on 30 vehicles tested on cycles adapted to their motorization (i.e., cycles for high- or low-powered cars, inducing thus a significant difference in the dynamic) were also considered for analysing the influence of the cycles and of the kinematic parameters on the hot emission rates of the regulated pollutants (CO, HC, NO_x, CO₂, PM). An analyses of variance demonstrated the preponderance of the driving type (urban, rural road, motorway), of the vehicle category (fuel, emission standard) and emitting status (high/normal emitter) and thus the pertinence of analysing and modelling separately the corresponding emissions. It also demonstrated that Urban driving led systematically to high diesel emission rates and to high CO₂, HC and NO_x emissions from petrol cars. Congested driving implied high CO₂ (diesel and petrol) and high diesel NO_x emission. On motorway, the very high speeds generated high CO₂, while unsteady speeds induced diesel NO_x and petrol CO over-emissions. A search for pertinent kinematic parameters showed that urban diesel emissions were mostly sensitive to stops and speed parameters, while petrol emissions were rather sensitive to acceleration parameters. On the motorway, diesel NO_x and CO₂ emissions rates increased with the speed variability and occurrence of high speeds, while CO₂ and CO over-emission from petrol cars were linked to the occurrence of strong acceleration at high speeds.A modelling approach based on partial least square regression was tested, which demonstrates its ability to discriminate satisfactorily the emissions according to dynamic related parameters and in particular when considering the two-dimensionnal distribution of instantaneous speed and acceleration.Finally, a strategy was proposed to analyse the large but heterogeneous set of hot emission data collected within the ARTEMIS project. The approach consisted in analysing the similarity of the numerous cycles as regards their kinematic, grouping them into reference test patterns through an automatic clustering, and then computing reference emissions for these patterns. These principles enabled the development of a method to compute the emissions at a low spatial scale, i.e. the so-called traffic situation approach, which was implemented in the European Artemis model for estimating the cars’ pollutant emissions.     

Estimation of vehicular emission inventories in China from 1980 to 2005

Multi-year inventories of vehicular emissions at a high spatial resolution of 40 km×40 km were established in China using the GIS methodology for the period 1980–2005, based on provincial statistical data from yearbooks regarding vehicles and roads, and on the emission factors for each vehicle category in each province calculated by COPERT III program. Results showed that the emissions of CH₄, CO, CO₂, NMVOC, NO_x, PM₁₀, and SO₂ increased from 5, 1066, 19 893, 169, 174, 26, and 16 thousand tons in 1980 to 377, 36 197, 674 629, 5911, 4539, 983, and 484 thousand tons in 2005 at an annual average rate of 19%, 15%, 15%, 15%, 14%, 16%, and 15%, respectively. Statistical analysis of vehicular emissions and GDP showed that they were well positively correlated, which revealed that increase of pollutant emissions has been accompanying the growth of GDP. Spatial distribution of pollutant emissions was rather unbalanced: over three-quarters of the total emissions concentrated in developed regions of China's southeastern, northern and central areas covering only 35.2% of China's territory, while the remaining emissions were distributed over the southwestern, northwestern and northeastern regions covering as much as 64.8% of the territory. In 2005, the Beijing–Tianjin–Hebei region, the Yangtze River Delta, and the Pearl River Delta covering only 2.3%, 2.2%, and 1.9%, respectively, of the territory, generated about 10%, 19%, and 12%, respectively, of the total emissions. Since 1990, motorcycles have been the major contributors to the CH₄, CO, NMVOC, and PM₁₀ emissions, due to the large population. Heavy-duty vans were the major contributors to the NO_x and SO₂ emissions because of high emission factors. Passenger cars contributed about one third of the emissions of each pollutant. Contributions of vehicle categories to emissions varied from province to province, due to the diversity of vehicle compositions among provinces.     

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.     

Differences in airborne particle and gaseous concentrations in urban air between weekdays and weekends

Airborne particle number concentrations and size distributions as well as CO and NO_x concentrations monitored at a site within the central business district of Brisbane, Australia were correlated with the traffic flow rate on a nearby freeway with the aim of investigating differences between weekday and weekend pollutant characteristics. Observations over a 5-year monitoring period showed that the mean number particle concentration on weekdays was (8.8±0.1)×10³ cm⁻³ and on weekends (5.9±0.2)×10³ cm⁻³—a difference of 47%. The corresponding mean particle number median diameters during weekdays and weekends were 44.2±0.3 and 50.2±0.2 nm, respectively. The differences in mean particle number concentration and size between weekdays and weekends were found to be statistically significant at confidence levels of over 99%. During a 1-year period of observation, the mean traffic flow rate on the freeway was 14.2×10⁴ and 9.6×10⁴ vehicles per weekday and weekend day, respectively—a difference of 48%. The mean diurnal variations of the particle number and the gaseous concentrations closely followed the traffic flow rate on both weekdays and weekends (correlation coefficient of 0.86 for particles). The overall conclusion, as to the effect of traffic on concentration levels of pollutant concentration in the vicinity of a major road (about 100 m) carrying traffic of the order of 10⁵ vehicles per day, is that about a 50% increase in traffic flow rate results in similar increases of CO and NO_x concentrations and a higher increase of about 70% in particle number concentration.     

On-Road Motor Vehicle Emissions and Fuel Consumption in Urban Driving Conditions

ABSTRACT

This paper reports on the analysis of on-road vehicle speed, emission, and fuel consumption data collected by four instrumented vehicles. Time-, distance-, and fuel-based average fuel consumption, as well as CO, HC, NO_x, and soot emission factors, were derived. The influences of instantaneous vehicle speed on emissions and fuel consumption were studied. It was found that the fuel-based emission factors varied much less than the time- and distance-based emission factors as instantaneous speed changed. The trends are similar to the results obtained from laboratory tests. The low driving speed contributed to a significant portion of the total emissions over a trip. Furthermore, the on-road data were analyzed using the modal approach. The four standard driving modes are acceleration, cruising, deceleration, and idling. It was found that the transient driving modes (i.e., acceleration and deceleration) were more polluting than the steady-speed driving modes (i.e., cruising and idling) in terms of g/km and g/ sec. These results indicated that the on-road emission measurement is feasible in deriving vehicle emissions and fuel consumption factors in urban driving conditions.     

Investigations of emissions and heterogeneous formation of HONO in a road traffic tunnel

Simultaneous measurements of nitrous acid (HONO) and nitrogen dioxide (NO₂) using a differential optical absorption spectroscopy system, nitrogen oxide (NO) by an in situ chemiluminescence analyser and carbon dioxide (CO₂) by a gas chromatographic technique were carried out in the Wuppertal Kiesbergtunnel. At high traffic density HONO concentrations of up to 45 ppbV were observed. However, at low traffic density unexpectedly high HONO concentrations of up to 10 ppbV were measured caused by heterogeneous HONO formation on the tunnel walls. In addition to the tunnel campaigns, emission measurements of HONO, NO₂, NO and CO₂ from different single vehicles (a truck, a diesel and a gasoline passenger car) were also performed. For the correction of the HONO emission data, the heterogeneous HONO formation on the tunnel walls was quantified by two different approaches (a) in different NO₂ emission experiments in the tunnel without traffic and (b) on tunnel wall residue in the laboratory. The HONO concentration corrected for heterogeneous formation on the tunnel walls, in relation to the CO₂ concentration can be used to estimate the amount of HONO, which is directly emitted from the vehicle fleet. From the measured data, emission ratios (e.g. HONO/NO_x) and emission indices (e.g. mg HONO kg⁻¹ fuel) were calculated. The calculated emission index of 88±18 mg HONO kg⁻¹ fuel allows an estimation of the HONO emission rates from traffic into the atmosphere. Furthermore, the heterogeneous formation of HONO from NO₂ on freshly emitted exhaust particles is discussed.     

Nitrogen oxide fluxes between corn (Zea mays L.) leaves and the atmosphere

In the United States, fertilized corn fields, which make up approximately 5% of the total land area, account for approximately 45% of total soil NO_x emissions. Leaf chamber measurements were conducted of NO and NO₂ fluxes between individual corn leaves and the atmosphere in (1) field-grown plants near Champaign, IL (USA) in order to assess the potential role of corn canopies in mitigating soil–NO_x emissions to the atmosphere, and (2) greenhouse-grown plants in order to study the influence of various environmental variables and physiological factors on the dynamics of NO₂ flux. In field-grown plants, fluxes of NO were small and inconsistent from plant to plant. At ambient NO concentrations between 0.1 and 0.3 ppbv, average fluxes were zero. At ambient NO concentrations above 1 ppbv, NO uptake occurred, but fluxes were so small (14.3±0.0 pmol m⁻² s⁻¹) as to be insignificant in the NO_x inventory for this site. In field-grown plants, NO₂ was emitted to the atmosphere at ambient NO₂ concentrations below 0.9 ppbv (the NO₂ compensation point), with the highest rate of emission being 50 pmol m⁻² s⁻¹ at 0.2 ppbv. NO₂ was assimilated by corn leaves at ambient NO₂ concentrations above 0.9 ppbv, with the maximum observed uptake rate being 643 pmol m⁻² s⁻¹ at 6 ppbv. When fluxes above 0.9 ppbv are standardized for ambient NO₂ concentration, the resultant deposition velocity was 1.2±0.1 mm s⁻¹. When scaled to the entire corn canopy, NO₂ uptake rates can be estimated to be as much as 27% of the soil-emitted NO_x. In greenhouse-grown and field-grown leaves, NO₂ deposition velocity was dependent on incident photosynthetic photon flux density (PPFD; 400–700 nm), whether measured above or below the NO₂ compensation point. The shape of the PPFD dependence, and its response to ambient humidity in an experiment with greenhouse-grown plants, led to the conclusion that stomatal conductance is a primary determinant of the PPFD response. However, in field-grown leaves, measured NO₂ deposition velocities were always lower than those predicted by a model solely dependent on stomatal conductance. It is concluded that NO₂ uptake rate is highest when N availability is highest, not when the leaf deficit for N is highest. It is also concluded that the primary limitations to leaf-level NO₂ uptake concern both stomatal and mesophyll components.     

Real-world vehicle emissions and VOCs profile in the Taipei tunnel located at Taiwan Taipei area

An in situ field experiment was conducted in a highway road tunnel in the Taipei City to determine the motor vehicle emission factors (EF) of different kinds of air pollution species. These are carbon monoxide (CO), oxides of nitrogen (NO_x), non-methane hydrocarbons (NMHC) and VOCs species. About 56 species of VOCs were sampled by canister sampler and followed by the GC-MS analyzing. Furthermore, the tunnel-drafting rate was determined by SF₆ tracer method.The EF for the highway vehicles determined from this experiment are 3.64, 0.90, 0.44 and 0.24 gm km⁻¹ veh⁻¹ for CO, NO_x, NMHC and the totally measured VOCs, respectively. A comparison of the EFs from the road tunnel experiment to the estimates by the USEPA MOBILE5b (M5b) and the modified Taiwan EPA MOBILE-TAIWAN2.0 (MT2.0) provides a first-hand evaluation of the model characteristics. M5b and MT2.0 both tend to underpredict CO by 10% and 20%, respectively. While M5b overpredicts NO_x and NMHC by 40% and 20%, respectively; MT2.0 has fairly good predictions for these two species. From the GC-MS analysis of the canister samples, it was found that the most abundant species from the traffic-emitted VOCs in Taipei road tunnel are toluene, ethene and 1,2,4-trimethyl-benzene (1,2,4-TMB) by the weight basis. However, ethene, acetylene and toluene are the most abundant in VOCs based on volume. The VOCs’ weight composition in terms of the carbon bond classification is 28% by the paraffins, 33% by the olefins and 39% by the aromatics, respectively. In order to evaluate the ozone formation potential from the typical road emission in Taipei area, the maximum increment reactivity is calculated. It was found that about 1015 mg of O₃ is induced by per vehicle per kilometer traveled emission. Among them, ethene, 1,2,4-TMB and propene from the road vehicle's emission contribute most to the ozone-formation reactivity.     

Effects of biodiesel on emissions of regulated air pollutants and polycyclic aromatic hydrocarbons under engine durability testing

An 80,000-km durability test was performed on two engines using diesel and biodiesel (methyl ester of waste cooking oil) as fuel in order to examine emissions resulting from the use of biodiesel. The test biodiesel (B20) was blended with 80% diesel and 20% methyl ester derived from waste cooking oil. Emissions of regulated air pollutants, including CO, HC, NO_x, particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs) were measured at 20,000-km intervals. The identical-model engines were installed on a standard dynamometer equipped with a dilution tunnel used to measure the pollutants. To simulate real-world driving conditions, emission measurements were made in accordance with the United States Environmental Protection Agency (USEPA) FTP transient cycle guidelines. At 0 km of the durability test, HC, CO and PM emission levels were lower for the B20 engine than those for diesel. After running for 20,000 km and longer, they were higher. However, the deterioration coefficients for these regulated air pollutants were not statistically higher than 1.0, implying that the emission factors do not increase significantly after 80,000 km of driving. Total (gaseous+particulate phase) PAH emission levels for both B20 and diesel decreased as the driving mileage accumulated. However, for the engine using B20 fuel, particulate PAH emissions increased as engine mileage increased. The average total PAH emission factors were 1097 and 1437 μg bhp h⁻¹ for B20 and diesel, respectively. For B20, the benzo[a]pyrene equivalence emission factors were 0.77, 0.24, 0.20, 7.48, 5.43 and 14.1 μg bhp h⁻¹ for 2-, 3-, 4-, 5-, 6-ringed and total PAHs. Results show that B20 use can reduce both PAH emission and its corresponding carcinogenic potency.