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.     

A fuel-based approach for emission factor development for highway paving construction equipment in China

The objective of this paper is to develop and demonstrate a fuel-based approach for emissions factor estimation for highway paving construction equipment in China for better accuracy. A highway construction site in Chengdu was selected for this study with NO emissions being characterized and demonstrated. Four commonly used paving equipment, i.e., three rollers and one paver were selected in this study. A portable emission measurement system (PEMS) was developed and used for emission measurements of selected equipment during real–world highway construction duties. Three duty modes were defined to characterize the NO emissions, i.e., idling, moving, and working. In order to develop a representative emission factor for these highway construction equipment, composite emission factors were estimated using modal emission rates and the corresponding modal durations in the process of typical construction duties. Depending on duty mode and equipment type, NO emission rate ranged from 2.6–63.7mg/s and 6.0–55.6g/kg–fuel with the fuel consumption ranging from 0.31–4.52 g/s correspondingly. The NO composite emission factor was estimated to be 9–41mg/s with the single-drum roller being the highest and double-drum roller being the lowest and 6–30g/kg-fuel with the pneumatic tire roller being the highest while the double-drum roller being the lowest. For the paver, both time-based and fuel consumption-based NO composite emission rates are higher than all of the rollers with 56mg/s and 30g/kg-fuel, respectively. In terms of time–based quantity, the working mode contributes more than the other modes with idling being the least for both emissions and fuel consumption. In contrast, the fuel-based emission rate appears to have less variability in emissions. Thus, in order to estimate emission factors for emission inventory development, the fuel-based emission factor may be selected for better accuracy.

Implications: The fuel-based composite emissions factors will be less variable and more accurate than time-based emission factors. As a consequence, emissions inventory developed using this approach will be more accurate and practical.     

On-road comparison of a portable emission measurement system with a mobile reference laboratory for a heavy-duty diesel vehicle

On-road comparisons were made between a mobile emissions laboratory (MEL) meeting federal standards and a portable emissions measurement system (PEMS). These comparisons were made over different conditions; including road grade, vibration, altitude, electric fields, and humidity with the PEMS mounted inside and outside of the tractor's cab. Brake-specific emissions were calculated to explore error differences between the MEL and PEMS during the Not-To-Exceed (NTE) engine operating zone. The PEMS brake-specific NOx (bsNOx) NTE emissions were biased high relative to the MEL and, in general, were about 8% of the 2007 in-use NTE NO_x standard of 2.68 g kW^?1 h^?1 (2.0 g hp^?1 h^?1). The bsCO₂ emissions for the PEMS were also consistently biased high relative to the MEL, with an average deviation of +4% ± 2%. NMHC and CO emissions were very low and typically less than 1% of the NTE threshold. This research was part of a comprehensive program to determine the “allowance” when PEMS are used for in-use compliance testing of heavy-duty diesel vehicles (HDDVs).     

Research on a China 6b heavy-duty diesel vehicle real-world engine out NOx emission deterioration and ambient correction using big data approach

Environmental Science and Pollution Research - China VI standard proposed higher requirements for durability of heavy-duty diesel vehicles emissions. Previous research which took advantages of both...     

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.     

Open burning and open detonation PM10 mass emission factor measurements with optical remote sensing

Emission factors (EFs) of particulate matter with aerodynamic diameter ≤10 µm (PM₁₀) from the open burning/open detonation (OB/OD) of energetic materials were measured using a hybrid-optical remote sensing (hybrid-ORS) method. This method is based on the measurement of range-resolved PM backscattering values with a micropulse light detection and ranging (LIDAR; MPL) device. Field measurements were completed during March 2010 at Tooele Army Depot, Utah, which is an arid continental site. PM₁₀ EFs were quantified for OB of M1 propellant and OD of 2,4,6-trinitrotoluene (TNT). EFs from this study are compared with previous OB/OD measurements reported in the literature that have been determined with point measurements either in enclosed or ambient environments, and with concurrent airborne point measurements. PM₁₀ mass EFs, determined with the hybrid-ORS method, were 7.8?×?10^?3 kg PM₁₀/kg M1 from OB of M1 propellant, and 0.20 kg PM₁₀/kg TNT from OD of TNT. Compared with previous results reported in the literature, the hybrid-ORS method EFs were 13% larger for OB and 174% larger for OD. Compared with the concurrent airborne measurements, EF values from the hybrid-ORS method were 37% larger for OB and 54% larger for OD. For TNT, no statistically significant differences were observed for the EFs measured during the detonation of 22.7 and 45.4 kg of TNT, supporting that the total amount of detonated mass in this mass range does not have an effect on the EFs for OD of TNT.

Implications: Particulate matter (PM) in the atmosphere affects the health of humans and ecosystems, visibility, and climate. Fugitive PM emissions are not well characterized because of spatial and temporal ubiquity and heterogeneity. The hybrid-ORS method is appropriate for quantifying fugitive PM emission factors (EFs) because it captures the spatial and temporal dispersion of ground level and elevated plumes in real time, without requiring numerous point measurement devices. The method can be applied to provide an opportunity to reduce the uncertainty of fugitive PM EFs and readily update PM emissions in National Emission Inventories for a range of fugitive PM sources.     

A new approach to in-situ determination of roadside particle emission factors of individual vehicles under conventional driving conditions

A method for continuous on-road measurements of particle number emissions for both diesel- and petrol-fuelled vehicles is presented. The setup allows the determination of particle number emission factors on an individual vehicle basis by the simultaneous measurement of CO₂ and particle concentrations. As an alternative to previous measurements on the kerbside, the sample is taken directly in the street, with the advantage of sampling in-situ within the exhaust plumes of passing vehicles, allowing the separation of the individual high-concentration plumes. The method was tested in two experiments that were conducted in the Gothenburg area. In the first study, which was performed at an urban roadside, we were able to determine particle emission factors from individual vehicles in a common car fleet passing the measurement site. The obtained emission factors were of the same order of magnitude (between 1.4 × 10¹² and 1.8 × 10¹⁴ particles km^?1) as values published in the recent literature for light duty vehicles. An additional on-road experiment was conducted at a rural road with four light duty reference vehicles (three of them petrol-powered and one diesel-powered) at driving speeds of 50 and 70 km h^?1, realised with different engine speeds. The results of the traffic emission studies show that the method is applicable provided that instruments with an adequate dynamic range are used and that the traffic is not too dense. In addition, the variability in particle emissions for a specified driving condition was estimated.     

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.     

Definition of yearly emission factor of dust and greenhouse gases through continuous measurements in swine husbandry

The object of this study was to develop an accurate estimation method to evaluate the contribution of the various compartments of swine husbandry to dust and GHG (greenhouse gases, CO₂, CH₄ and N₂O) emission into the atmosphere during one year of observation.A weaning, a gestation, a farrowing and a fattening room in an intensive pig house were observed in three different periods (Autumn–Winter, Springtime and Summer, monitoring at least 60% of each period (20% at the beginning, in the middle and at the end) of each cycle).During monitoring, live weight, average live weight gain, number of animals and its variation, type of feed and feeding time were taken into account to evaluate their influence on PM₁₀, or the fraction of suspended particulate matter with an aerodynamic diameter less than or equal to 10 μm [Emission Inventory Guidebook, 2007. B1100 Particle Emissions from Animal Husbandry Activities. Available from: <http://reports.eea.europa.eu/EMEPCORINAIR5/en/B1100vs1.pdf> (accessed October 2008)] and to define GHG emission.The selected piggery had a ventilation control system using a free running impeller to monitor continuously real-time environmental and management parameters with an accuracy of 5%.PM₁₀ concentration was monitored by a sampler (Haz Dust EPAM 5000), either continuously or through traditional gravimetric technique, and the mean value of dust amount collected on the membranes was utilized as a correction factor to be applied to continuously collected data.PM₁₀ concentration amount incoming from inlets was removed from PM₁₀ emission calculation, to estimate the real contribution of pig house dust pollution into atmosphere.Mean yearly emission factor of PM₁₀ was measured in 2 g d^?1 LU^?1 for the weaning room, 0.09 g d^?1 LU^?1 for the farrowing room, 2.59 g d^?1 LU^?1 for the fattening room and 1.23 g d^?1 LU^?1 for the gestation room. The highest PM₁₀ concentration and emission per LU was recorded in the fattening compartment while the lowest value was recorded in the farrowing room.CO₂, CH₄ and N₂O concentrations were continuously measured in the exhaust ducts using an infrared photoacoustic detector IPD (Brüel & Kjaer, Multi-gas Monitor Type 1302, Multipoint Sampler and Doser Type 1303) sampling data every 15 min, for the 60% of the cycles.Yearly emission factor for CO₂ was measured in 5997 g d^?1 LU^?1 for the weaning room, 1278 g d^?1 LU^?1 for the farrowing room, 13,636 g d^?1 LU^?1 for the fattening room and 8851 g d^?1 LU^?1 for the gestation room.Yearly emission factor for CH₄ was measured in 24.57 g d^?1 LU^?1 for the weaning room, 4.68 g d^?1 LU^?1 for the farrowing room, 189.82 g d^?1 LU^?1 for the fattening room and 132.12 g d^?1 LU^?1 for the gestation room.Yearly emission factor for N₂O was measured in 3.62 g d^?1 LU^?1 for the weaning room, 0.66 g d^?1 LU^?1 for the farrowing room, 3.26 g d^?1 LU^?1 for the fattening room and 2.72 g d^?1 LU^?1 for the gestation room.     

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.     

隧道实验测定南京市机动车PM10排放因子

选取南京城市隧道进行机动车PM10平均排放因子的测试研究.采用质量平衡模型和多元线性回归方法计算了4种车型PM10的综合排放因子.结果表明:隧道内机动车PM10平均排放因子为0.347±0.100 g/(km·辆);大型车的PM10排放因子远高于其他车型的排放因子,其次是中型车和摩托车,小型车最小,其综合排放因子分别为1.440 g/(km·辆)、0.850 g/(km·辆)、0.790 g/(km·辆)和0.320 g/(km·辆);在车速相似的情况下,本隧道实验所测机动车的PM10排放因子与国内隧道实验结果相仿,却远大于国外隧道实验结果.     

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.     

Estimation of road vehicle exhaust emissions from 1992 to 2010 and comparison with air quality measurements in Genoa,Italy

An investigation into road transport exhaust emissions in the Genoa urban area was performed by comparing the quantities of carbon monoxide (CO), nitrogen oxides (NO_x), nitrogen dioxide (NO₂) and particulate matter (PM) emitted by different vehicle categories with air quality measurements referred to the same pollutants. Exhaust emissions were evaluated by applying the PROGRESS (computer PROGramme for Road vehicle EmiSSions evaluation) code, developed by the Internal Combustion Engines Group of the University of Genoa, to eight different years (from 1992 to 2010), considering spark ignition and Diesel passenger cars and light duty vehicles, heavy duty vehicles and buses, motorcycles and mopeds. Changes in terms of vehicles number, mileage and total emissions are presented together with relative distributions among the various vehicle categories. By comparing 1992 and 2010 data, calculated trends show a 7% increase in the number of vehicles, with total mileage growing at a faster rate (approx. 22%); total emissions decrease considerably, by approximately 50% for NO_x and PM, 70% for HC and 80% for CO, due to improvements in engines and fuels forced by the stricter European legislation and the fleet renewal, while primary NO₂ emission will be very close to 1992 level, after a decrease of about 18% in 2000.Air quality was analysed by selecting traffic and background measuring stations from the monitoring network managed by the Environmental Department of the Province of Genoa: average annual concentrations of considered pollutants from 1994 to 2007 were calculated in order to obtain the relative historical trends and compare them with European public health limits and with road vehicle emissions. Though an important reduction in pollutant concentrations has been achieved as a consequence of cleaner vehicles, some difficulties in complying with present and/or future NO₂ and PM₁₀ limits are also apparent, thus requiring suitable measures to be taken by the local authorities.     

The contribution of traffic and solvent use to the total NMVOC emission in a German city derived from measurements and CMB modelling

In order to quantify the contribution of solvent use and road traffic to the total non-methane volatile organic compound (NMVOC) emissions in Germany, the composition of air in the city of Wuppertal was investigated during three campaigns at different locations. The measurements covered NMVOCs in the range of C₃–C₁₀ hydrocarbons and C₁–C₆ oxygenated compounds. An assessment of the contribution from different emission sources to the observed NMVOC concentrations was attempted with the chemical mass balance (CMB) modelling technique. Emission profiles for traffic were obtained from measurements performed in a traffic tunnel, at a downtown street intersection and during drives through the city and on motorways. Solvent emission profiles were investigated in the vicinity of different factories and workshops using solvents in Wuppertal. Apportionment analyses were performed for several receptor points located down-wind from the city centre, in residential, dense traffic and industrial areas.The results of the present work show that traffic emission rather than solvent use determines the ambient NMVOC composition. The maximum contribution of solvent use to the NMVOC emission estimated on the basis of experimentally obtained results amounts to about 23% in the whole area of Wuppertal. It can be concluded that the contribution of solvent use to the NMVOC concentrations also in other German cities falls in the range of few to about 20%, assuming that Wuppertal can be considered as a typical German urban area with certain proportions of domestic, traffic and various industrial activities. These results are in strong disagreement with the German Emission Inventory, which states, that in the reference year 2003 about 51% of the total NMVOC emissions originate from solvent use and only 14% from traffic.     

Understanding the emission impacts of high-occupancy vehicle (HOV) to high-occupancy toll (HOT) lane conversions: Experience from Atlanta,Georgia

Converting a congested high-occupancy vehicle (HOV) lane into a high-occupancy toll (HOT) lane is a viable option for improving travel time reliability for carpools and buses that use the managed lane. However, the emission impacts of HOV-to-HOT conversions are not well understood. The lack of emission impact quantification for HOT conversions creates a policy challenge for agencies making transportation funding choices. The goal of this paper is to evaluate the case study of before-and-after changes in vehicle emissions for the Atlanta, Georgia, I-85 HOV/HOT lane conversion project, implemented in October 2011. The analyses employed the Motor Vehicle Emission Simulator (MOVES) for project-level analysis with monitored changes in vehicle activity data collected by Georgia Tech researchers for the Georgia Department of Transportation (GDOT). During the quarterly field data collection from 2010 to 2012, more than 1.5 million license plates were observed and matched to vehicle class and age information using the vehicle registration database. The study also utilized the 20-sec, lane-specific traffic operations data from the Georgia NaviGAtor intelligent transportation system, as well as a direct feed of HOT lane usage data from the State Road and Tollway Authority (SRTA) managed lane system. As such, the analyses in this paper simultaneously assessed the impacts associated with changes in traffic volumes, on-road operating conditions, and fleet composition before and after the conversion. Both greenhouse gases and criteria pollutants were examined.

Implications: A straight before-after analysis showed about 5% decrease in air pollutants and carbon dioxide (CO₂). However, when the before-after calendar year of analysis was held constant (to account for the effect of 1 yr of fleet turnover), mass emissions at the analysis site during peak hours increased by as much as 17%, with little change in CO₂. Further investigation revealed that a large percentage decrease in criteria pollutants in the straight before-after analysis was associated with a single calendar year change in MOVES. Hence, the Atlanta, Georgia, results suggest that an HOV-to-HOT conversion project may have increased mass emissions on the corridor. The results also showcase the importance of obtaining on-road data for emission impact assessment of HOV-to-HOT conversion projects.