Development of a microscale emission factor model for particulate matter for predicting real-time motor vehicle emissions

The U.S. Environmental Protection Agency's National Exposure Research Laboratory is pursuing a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source through the air pathway to human exposure in significant exposure microenvironments. Current particulate matter (PM) emission models, particle emission factor model (used in the United States, except California) and motor vehicle emission factor model (used in California only), are suitable only for county-scale modeling and emission inventories. There is a need to develop a site-specific real-time emission factor model for PM emissions to support human exposure studies near roadways. A microscale emission factor model for predicting site-specific real-time motor vehicle PM (MicroFacPM) emissions for total suspended PM, PM less than 10 microm aerodynamic diameter, and PM less than 2.5 microm aerodynamic diameter has been developed. The algorithm used to calculate emission factors in MicroFacPM is disaggregated, and emission factors are calculated from a real-time fleet, rather than from a fleet-wide average estimated by a vehicle-miles-traveled weighting of the emission factors for different vehicle classes. MicroFacPM requires input information necessary to characterize the site-specific real-time fleet being modeled. Other variables required include average vehicle speed, time and day of the year, ambient temperature, and relative humidity.     

Developing a high-resolution vehicular emission inventory by integrating an emission model and a traffic model: Part 1--Modeling fuel consumption and emissions based on speed and vehicle-specific power

To improve the accuracy and applicability of vehicular emission models, this study proposes a speed and vehicle-specific power (VSP) modeling method to estimate vehicular emissions and fuel consumption using data gathered by a portable emissions monitoring system (PEMS). The PEMS data were categorized into discrete speed-VSP bins on the basis of the characteristics of vehicle driving conditions and emissions in Chinese cities. Speed-VSP modal average rates of emissions (or fuel consumption) and the time spent in the corresponding speed-VSP bins were then used to calculate the total trip emissions (or fuel consumption) and emission factors (or fuel economy) under specific average link speeds. The model approach was validated by comparing it against measured data with prediction errors within 20% for trip emissions and link-speed-based emission factors. This analysis is based on the data of light-duty gasoline vehicles in China; however, this research approach could be generalized to other vehicle fleets in other countries. This modeling method could also be coupled with traffic demand models to establish high-resolution emissions inventories and evaluate the impacts of traffic-related emission control measures.     

Numerical model for static chamber measurement of multi-component landfill gas emissions and its application

The quantitative assessment of landfill gas emissions is essential to assess the performance of the landfill cover and gas collection system. The relative error of the measured surface emission of landfill gas may be induced by the static flux chamber technique. This study aims to quantify effects of the size of the chamber, the insertion depth, pressure differential on the relative errors by using an integrated approach of in situ tests, and numerical modeling. A field experiment study of landfill gas emission is conducted by using a static chamber at one landfill site in Xi’an, Northwest China. Additionally, a two-dimensional axisymmetric numerical model for multi-component gas transport in the soil and the static chamber is developed based on the dusty-gas model (DGM). The proposed model is validated by the field data obtained in this study and a set of experimental data in the literature. The results show that DGM model has a better capacity to predict gas transport under a wider range of permeability compared to Blanc’s method. This is due to the fact that DGM model can explain the interaction among gases (e.g., CH₄, CO₂, O₂, and N₂) and the Knudsen diffusion process while these mechanisms are not included in Blanc’s model. Increasing the size and the insertion depth of static chambers can reduce the relative error for the flux of CH₄ and CO₂. For example, increasing the height of chambers from 0.55 to 1.1 m can decrease relative errors of CH₄ and CO₂ flux by 17% and 18%, respectively. Moreover, we find that gas emission fluxes for the case with positive pressure differential (?P_in-out) are greater than that of the case without considering pressure fluctuations. The Monte Carlo method was adopted to carry out the statistical analysis for quantifying the range of relative errors. The agreement of the measured field data and predicted results demonstrated that the proposed model has the capacity to quantify the emission of landfill gas from the landfill cover systems.

     

Grey optimization Verhulst model and its application in forecasting coal-related CO2 emissions

Environmental Science and Pollution Research - Energy saving and emission reduction are the most concerned issues in the world. Objective and accurate prediction of carbon emissions can provide...     

Evaluation of a simplified top-down model for the spatial assessment of hot traffic emissions in mid-sized cities

Traffic emission estimation in developing countries is a key-issue for air pollution management. In most cases, comprehensive bottom-up methodologies cannot be applied in mid-sized cities because of the resource cost related to their application. In this paper, a simplified emission estimation model (SEEM) is evaluated. The model is based on a top-down approach and gives annual global hot emission. Particular attention is paid to the quality of the input traffic data. The quality of results is assessed by application of the SEEM model in the Chilean Gran Concepción urban area and by comparison with a bottom-up approach that has been led for the year 2000. The SEEM model estimates emissions with an accuracy of about $20\%$ and is related to important resource savings. The results of the SEEM model are then distributed in space with a disaggregation approach and using GIS techniques. The relevancy of the disaggregation approach is evaluated among several possibilities through statistical methods. A spatial disaggregation using principal roads density gives the best results in terms of emissions repartition and gives a globally accurate image of the distribution of hot emissions in a mid-sized city.     

Developing a high-resolution vehicular emission inventory by integrating an emission model and a traffic model: Part 2--A case study in Beijing

A grid-based, bottom-up method has been proposed by combining a vehicle emission model and a travel demand model to develop a high-resolution vehicular emission inventory for Chinese cities. Beijing is used as a case study in which the focus is on fuel consumption and emissions from hot-stabilized activities of light-duty gasoline vehicles (LGVs) in 2005. The total quantity of emissions, emission intensity, and spatial distribution of emissions at 1- by 1-km resolution are presented and compared with results from other inventory methods commonly used in China. The results show that the total daily fuel consumption and vehicular emissions of carbon dioxide, carbon monoxide, hydrocarbons, and oxides of nitrogen from LGVs in the Beijing urban area in 2005 were 1.95 x 10(7) L, 4.28 x 10(4) t, 1.97 x 10(3) t, 0.28 x 10(3) t, and 0.14 x 10(3) t, respectively. Vehicular fuel consumption and emissions show spatial variations that are consistent with the traffic characteristics. The grid-based inventory developed in this study reflects the influence of traffic conditions on vehicle emissions at the microscale and may be applied to evaluate the effectiveness of traffic-related measures on emission control in China.     

Sensitivity analysis and evaluation of microFacCO: a microscale motor vehicle emission factor model for CO emissions

This paper presents a sensitivity analysis of a microscale emission factor model (MicroFacCO) for predicting real-time site-specific motor vehicle CO emissions to input variables, as well as a limited field study evaluation of the model. The sensitivity analysis has shown that MicroFacCO emission estimates are very sensitive to vehicle fleet composition, speed, and ambient temperature. For the present U.S. traffic fleet, the CO emission rate (g/mi) is increased by more than 500% at 5 mph in comparison with a speed greater than 40 mph and by approximately 67% at ambient temperatures of 45 degrees F and > or = 95 degrees F in comparison with an ambient temperature of 75 degrees F. The input variable "emission failure standard rate" is more sensitive to estimating emission rates in the 1990s than in the 2000s. The estimation of emission rates is not very sensitive to relative humidity. MicroFacCO can also be applied to examine the contribution of emission rates per vehicle class and model year. The model evaluation is presented for tunnel studies at five locations. In general, this evaluation study found good agreement between the measured and the modeled emissions. These analyses and evaluations have identified the need for additional studies to update the high-speed (>35 mph) air conditioning (A/C) correction factor and to add effects due to road grades. MicroFacCO emission estimates are very sensitive to the emission standard failure rate. Therefore, the model performance can be greatly improved by using a local emission standard failure rate.     

Derivation of motor vehicle tailpipe particle emission factors suitable for modelling urban fleet emissions and air quality assessments

Background, aim and scope  

Urban motor vehicle fleets are a major source of particulate matter pollution, especially of ultrafine particles (diameters < 0.1 μm), and exposure to particulate matter has known serious health effects. A considerable body of literature is available on vehicle particle emission factors derived using a wide range of different measurement methods for different particle sizes, conducted in different parts of the world. Therefore, the choice as to which are the most suitable particle emission factors to use in transport modelling and health impact assessments presented as a very difficult task. The aim of this study was to derive a comprehensive set of tailpipe particle emission factors for different vehicle and road type combinations, covering the full size range of particles emitted, which are suitable for modelling urban fleet emissions.     

Sensitivity analysis and evaluation of MicroFacPM: a microscale motor vehicle emission factor model for particulate matter emissions

A microscale emission factor model (MicroFacPM) for predicting real-time site-specific motor vehicle particulate matter emissions was presented in the companion paper titled "Development of a Microscale Emission Factor Model for Particulate Matter (MicroFacPM) for Predicting Real-Time Motor Vehicle Emissions". The emission rates discussed are in mass per unit distance with the model providing estimates of fine particulate matter (PM2.5) and coarse particulate matter. This paper complements the companion paper by presenting a sensitivity analysis of the model to input variables and evaluation model outputs using data from limited field studies. The sensitivity analysis has shown that MicroFacPM emission estimates are very sensitive to vehicle fleet composition, speed, and the percentage of high-emitting vehicles. The vehicle fleet composition can affect fleet emission rates from 8 mg/mi to 1215 mg/mi; an increase of 5% in the smoking (high-emitting) current average U.S. light-duty vehicle fleet (compared with 0%) increased PM2.5 emission rates by -272% for 2000; and for the current U.S. fleet, PM2.5 emission rates are reduced by a factor of -0.64 for speeds >50 miles per hour (mph) relative to a speed of 10 mph. MicroFacPM can also be applied to examine the contribution of emission rates per vehicle class, model year, and sources of PM. The model evaluation is presented for the Tuscarora Mountain Tunnel, Pennsylvania Turnpike, PA, and some limited evaluations at two locations: Sepulveda Tunnel, Los Angeles, CA, and Van Nuys Tunnel, Van Nuys, CA. In general, the performance of MicroFacPM has shown very encouraging results.     

Estimates of black carbon and size-resolved particle number emission factors from residential wood burning based on ambient monitoring and model simulations

In this paper we derive typical emission factors for coarse particulate matter (PM(10)), oxides of nitrogen (NO(x)), black carbon (BC), and number particle size distributions based on a combination of measurements and air quality dispersion modeling. The advantage of this approach is that the emission factors represent integrated emissions from several vehicle types and different types of wood stoves. Normally it is very difficult to estimate the total emissions in cities on the basis of laboratory measurements on single vehicles or stoves because of the large variability in conditions. The measurements were made in Temuco, Chile, between April 18 and June 15, 2005 at two sites. The first one was located in a residential area relatively far from major roads. The second site was located in a busy street in downtown Temuco where wood consumption is low. The measurements support the assumption that the monitoring sites represent the impact of different emission sources, namely traffic and residential wood combustion (RWC). Fitting model results to the available measurements, emission factors were obtained for PM(10) (RWC = 2160 +/- 100 mg/kg; traffic = 610 +/- 51 mg/veh-km), NO(x) (RWC = 800 +/- 100 mg/kg; traffic = 4400 +/- 100 mg/veh-km), BC (RWC = 74 +/- 6 mg/kg; traffic = 60 +/- 3 mg/veh-km) and particle number (N) with size distribution between 25 and 600 nm (N(25-600)) (RWC = 8.9 +/- 1 x 10(14) pt/kg; traffic = 6.7 +/- 0.5 x 10(14) pt/veh-km). The obtained emission factors are comparable to results reported in the literature. The size distribution of the N emission factors for traffic was shown to be different than for RWC. The main difference is that although traffic emissions show a bimodal size distribution with a main mode below 30 nm and a secondary one around 100 nm, RWC emissions show the main mode slightly below 100 nm and a smaller nucleation mode below 50 nm.     

A composite receptor and dispersion model approach for estimation of effective emission factors for vehicles

It is difficult to estimate vehicular emission factors at traffic junctions for use in dispersion modelling studies. Firstly, because the vehicles are in various modes of operation and secondly, it is difficult to delineate the effects of other contributing sources, mainly the effects of road dust and deposited constituents, which are very prominent at traffic junctions in India. Factor analysis-multiple regression (FA-MR), a receptor modelling technique has been used in this study for apportioning the contributing sources. The measurement data consist of one year's temporal variation of suspended particulate matter (SPM), analysed for its trace metal constituents, and two gaseous components NO₂ and SO₂ at two traffic junctions in Mumbai (India). FA-MR apportioned 40% of the observed SPM to road dust and 15% to vehicular sources. Of the total Pb observed in the SPM, FA-MR apportioned 60% to vehicular sources and 20% to road dust. The field-observed vehicular counts, meteorological parameters and road geometry were used in California line source dispersion model to estimate the effective vehicular emission factor for Pb at one traffic junction. This derived emission factor was used to predict the Pb concentration at second (independent observation) traffic junction. The result was found to be more satisfactory than using default emission factors obtained from literature. Similarly, effective vehicular emission factor for NO₂ was also evaluated for one site and tested for predicting concentrations at the other site.     

Separate determination of PM10 emission factors of road traffic for tailpipe emissions and emissions from abrasion and resuspension processes

Little is known about the relevance of mechanically produced particles of road traffic from abrasion and resuspension processes in relation to the exhaust pipe particles. In this paper, emission factors of PM₁₀ and PM₁ for light and heavy-duty vehicles were derived for different representative traffic regimes from concentration differences of particles and nitrogen oxides (NO_x) in ambient air upwind and downwind of busy roads, or alternatively of kerbsides and nearby background sites. Hereby, PM₁ was interpreted as direct exhaust emissions and PM₁₀-PM₁ as mechanically produced emissions from abrasion and resuspension processes. The results show that abrasion and resuspension processes represent a significant part of the total primary PM₁₀ emissions of road traffic. At sites with relatively undisturbed traffic flow they are in the same range as the exhaust pipe emissions. At sites with disturbed traffic flow due to traffic lights, emissions from abrasion/resuspension are even higher than those from the exhaust pipes.     

Application of a microscale emission factor model for particulate matter to calculate vehicle-generated contributions to fine particulate emissions

This paper discusses the evaluation and application of a new generation of particulate matter (PM) emission factor model (MicroFacPM). MicroFacPM that was evaluated in Tuscarora Mountain Tunnel, Pennsylvania Turnpike, PA shows good agreement between measured and modeled emissions. MicroFacPM application is presented to the vehicle traffic on the main approach road to the Ambassador Bridge, which is one of the most important international border entry points in North America, connecting Detroit, MI, with Windsor, Ontario, Canada. An increase in border security has forced heavy-duty diesel vehicles to line up for several kilometers through the city of Windsor causing concern about elevated concentrations of ambient PM. MicroFacPM has been developed to model vehicle-generated PM (fine [PM2.5] and coarse < or = 10 microm [PM10]) from the on-road vehicle fleet, which in this case includes traffic at very low speeds (10 km/h). The Windsor case study gives vehicle generated PM2.5 sources and their breakdown by vehicle age and class. It shows that the primary sources of vehicle-generated PM2.5 emissions are the late-model heavy-duty diesel vehicles. We also applied CALINE4 and AERMOD in conjunction with MicroFacPM, using Canadian traffic and climate conditions, to describe the vehicle-generated PM2.5 dispersion near this roadway during the month of May in 2003.     

Development of molecular marker source profiles for emissions from on-road gasoline and diesel vehicle fleets

As part of the Gasoline/Diesel PM Split Study, relatively large fleets of gasoline vehicles and diesel vehicles were tested on a chassis dynamometer to develop chemical source profiles for source attribution of atmospheric particulate matter in California's South Coast Air Basin. Gasoline vehicles were tested in cold-start and warm-start conditions, and diesel vehicles were tested through several driving cycles. Tailpipe emissions of particulate matter were analyzed for organic tracer compounds, including hopanes, steranes, and polycyclic aromatic hydrocarbons. Large intervehicle variation was seen in emission rate and composition, and results were averaged to examine the impacts of vehicle ages, weight classes, and driving cycles on the variation. Average profiles, weighted by mass emission rate, had much lower uncertainty than that associated with intervehicle variation. Mass emission rates and elemental carbon/organic carbon (EC/OC) ratios for gasoline vehicle age classes were influenced most by use of cold-start or warm-start driving cycle (factor of 2-7). Individual smoker vehicles had a large range of mass and EC/OC (factors of 40 and 625, respectively). Gasoline vehicle age averages, data on vehicle ages and miles traveled in the area, and several assumptions about smoker contributions were used to create emissions profiles representative of on-road vehicle fleets in the Los Angeles area in 2001. In the representative gasoline fleet profiles, variation was further reduced, with cold-start or warm-start and the representation of smoker vehicles making a difference of approximately a factor of two in mass emission rate and EC/OC. Diesel vehicle profiles were created on the basis of vehicle age, weight class, and driving cycle. Mass emission rate and EC/OC for diesel averages were influenced by vehicle age (factor of 2-5), weight class (factor of 2-7), and driving cycle (factor of 10-20). Absolute and relative emissions of molecular marker compounds showed levels of variation similar to those of mass and EC/OC.     

Characteristics of carbonyls: Concentrations and source strengths for indoor and outdoor residential microenvironments in China

Indoor and outdoor carbonyl concentrations were measured simultaneously in 12 urban dwellings in Beijing, Shanghai, Guangzhou, and Xi’an, China in summer (from July to September in 2004) and winter (from December 2004 to February 2005). Formaldehyde was the most abundant indoor carbonyls species, while formaldehyde, acetaldehyde and acetone were found to be the most abundant outdoor carbonyls species. The average formaldehyde concentrations in summer indoor air varied widely between cities, ranging from a low of 19.3 μg m⁻³ in Xi’an to a high of 92.8 μg m⁻³ in Beijing. The results showed that the dwellings with tobacco smoke, incense burning or poor ventilation had significantly higher indoor concentrations of certain carbonyls. It was noticed that although one half of the dwellings in this study installed with low emission building materials or furniture, the carbonyls levels were still significantly high. It was also noted that in winter both the indoor and outdoor acetone concentrations in two dwellings in Guangzhou were significantly high, which were mainly caused by the usage of acetone as industrial solvent in many paint manufacturing and other industries located around Guangzhou and relatively longer lifetime of acetone for removal by photolysis and OH reaction than other carbonyls species. The indoor carbonyls levels in Chinese dwellings were higher than that in dwellings in the other countries. The levels of indoor and ambient carbonyls showed great seasonal differences. Six carbonyls species were carried out the estimation of indoor source strengths. Formaldehyde had the largest indoor source strength, with an average of 5.25 mg h⁻¹ in summer and 1.98 mg h⁻¹ in winter, respectively. However, propionaldehyde, crotonaldehyde and benzaldehyde had the weakest indoor sources.     

An urban emissions inventory for South America and its application in numerical modeling of atmospheric chemical composition at local and regional scales

This work describes the development of an urban vehicle emissions inventory for South America, based on the analysis and aggregation of available inventories for major cities, with emphasis on its application in regional atmospheric chemistry modeling. Due to the limited number of available local inventories, urban emissions were extrapolated based on the correlation between city vehicle density and mobile source emissions of carbon monoxide (CO) and nitrogen oxides (NOx). Emissions were geographically distributed using a methodology that delimits urban areas using high spatial resolution remote sensing products. This numerical algorithm enabled a more precise representation of urban centers. The derived regional inventory was evaluated by analyzing the performance of a chemical weather forecast model in relation to observations of CO, NOx and O₃ in two different urban areas, São Paulo and Belo Horizonte. The gas mixing ratios simulated using the proposed regional inventory show good agreement with observations, consistently representing their hourly and daily variability. These results show that the integration of municipal inventories in a regional emissions map and their precise distribution in fine scale resolutions are important tools in regional atmospheric chemistry modeling.     

Development and preliminary evaluation of a particulate matter emission factor model for European motor vehicles

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 microns, either from published data or from user-defined size distributions. A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM10, PM5, PM2.5, and PM1] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway). A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM10 was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

Monitoring method for airborne glymes and its application in fuel exhaust emission measurement.

A monitoring method based on solvent extraction of adsorbed target glymes followed by gas chromatograph-mass spectrometry GC-MS analysis was developed for seven glymes, namely ethylene glycol dimethyl ether, propylene glycol dimethyl ether, ethylene glycol diethyl ether, diethylene glycol dimethyl ether, diethylene glycol diethyl ether, triethylene glycol dimethyl ether, and tetraethylene glycol dimethyl ether. The best recoveries of target glymes were achieved when using a combination of sample collection medium of graphitised carbon black (GCB) with a solvent mixture of methylene chloride and methanol (95/5, v/v). Method detection limits ranged from 1.5 microg/m3 for diethylene glycol diethyl ether to 13.2 microg/m3 for ethylene glycol diethyl ether based on a sample volume of 3.4 1. Using this method, diethylene glycol dimethyl ether and diethylene glycol diethyl ether were detected and measured successfully in diluted vehicle exhausts in diesel fuel engine tests.