Real-Time Black Carbon Emissions from Light-Duty Passenger Vehicles Using a Portable Emissions Measurement System

Black carbon(BC)is considered the second largest anthropogenic climate forcer,but the radiative effects of BC are highly correlated with its combustion sources.On-road vehicles are an important source of anthropogenic BC.However,there are major uncertainties in the estimates of the BC emissions from on-road light-duty passenger vehicles(LDPVs),and results obtained with the portable emissions measurement system(PEMS)method are particularly lacking.We developed a PEMS platform and evaluated the on-road BC emissions from ten in-use LDPVs.We demonstrated that the BC emission factors(EFs)of gasoline direction injection(GDI)engine vehicles range from 1.10 to 1.56 mg.km^(-1),which are higher than the EFs of port fuel injection(PFI)engine vehicles(0.10–0.17 mg.km^(-1))by a factor of 11.The BC emissions during the cold-start phase contributed 2%–33%to the total emissions.A strong correlation(R^(2)=0.70)was observed between the relative BC EFs and average vehicle speed,indicating that traffic congestion alleviation could effectively mitigate BC emissions.Moreover,BC and particle number(PN)emissions were linearly correlated(R^(2)=0.90),and compared to PFI engine vehicles,the instantaneous PN-to-BC emission rates of GDI engine vehicles were less sensitive to vehicle specific power-to-velocity(VSPV)increase in all speed ranges.

Tailpipe emission characterizations of diesel-fueled forklifts under real-world operations using a portable emission measurement system

Non-road equipment is one of the key contributing sources to air pollution.Thus,an accurate development of emission inventory from non-road equipment is imperative for air quality management,especially for equipment with a large population such as diesel-fueled forklifts.The objective of this paper is to characterize duty-cycle based emissions from diesel-fueled forklifts using a portable emission measurement system(PEMS).Three dutycycles were defined in this study,including idling,moving,and working(active duty operation)and used to characterize in-use emissions for diesel-fueled forklifts.A total of twelve diesel-fueled forklifts were selected for real-world emission measurements.Results showed that fuel-based emission factors appear to have smaller variability compared to time-based ones.For example,the time-based emission factors for CO,HC,NO,and PM 2.5 for forklifts were estimated to be 16.6-43.9,5.3-15.1,26.2-49.9,5.5-11.1 g/hr with the fuel-based emission factors being 12.1-20.3,4.1-8.3,19.1-32.4,3.5-6.5 g/kg-fuel,respectively.NO emissions appear to be the biggest concern for emissions control.Furthermore,most of the emissions factors estimated from this study are significantly different from those in both National Guideline for Emission Inventory Development for Non-Road Equipment in China and welldeveloped emission factor models such as NONROAD by US EPA.This implies that localized,preferably fuel-based emission factors should be adjusted based on real-world emission measurements in order to develop a representative emission inventory for non-road equipment.

Numerical model of on-road emission rates of diesel buses in Beijing

A total of 14 in-use diesel buses were selected to conduct emission measurement using a portable emissions measurement system （PEMS） in Beijing. Their instantaneous gaseous emission rates, particular matter （PM） emission rates and driving parameters were obtained. The influences of speed, acceleration and vehicle specific power （VSP） on emissions were analyzed. Based on the relationships between these driving parameters and emissions, 24 driving bins defined by speed, ac- celeration and VSP were constructed with cluster analysis to group emission rates for Euro Ⅲ and IV buses, respectively. Then the emissions reductions from Euro Ⅲ to Euro Ⅳ diesel buses were ana- lyzed. Lastly, on-road hot-stabilized emission rate model for diesel buses in Beijing was developed. Through the comparison of the model simulation emission rates with the measured emission rates, the modeled emission results were in good agreement with the measured emission results. In most of the cases, the differences were less than 12 %.

Real-world fuel efficiency and exhaust emissions of light-duty diesel vehicles and their correlation with road conditions

The real-world fuel efficiency and exhaust emission profiles of CO, HC and NOx for light-duty diesel vehicles were investigated. Using a portable emissions measurement system, 16 diesel taxies were tested on different roads in Macao and the data were normalized with the vehicle specific power bin method. The 11 Toyota Corolla diesel taxies have very good fuel economy of （5.9 ± 0.6） L/100 km, while other five diesel taxies showed relatively high values at （8.5 ± 1.7） L/100 km due to the variation in transmission systems and emission control strategies. Compared to similar Corolla gasoline models, the diesel cars confirmed an advantage of ca. 20% higher fuel efficiency. HC and CO emissions of all the 16 taxies are quite low, with the average at （0.05 ± 0.02） g/km and （0.38 ± 0.15） g/km, respectively. The average NOx emission factor of the 11 Corolla taxies is （0.56 ± 0.17） g/km, about three times higher than their gasoline counterparts. Two of the three Hyundai Sonata taxies, configured with exhaust gas recirculation （EGR） ＋ diesel oxidation catalyst （DOC） emission control strategies, indicated significantly higher NO2 emissions and NO2/NOx ratios than other diesel taxies and consequently trigger a concern of possibly adverse impacts on ozone pollution in urban areas with this technology combination. A clear and similar pattern for fuel consumption and for each of the three gaseous pollutant emissions with various road conditions was identified. To save energy and mitigate CO2 emissions as well as other gaseous pollutant emissions in urban area, traffic planning also needs improvement.

Quantification of emission variability for off-road equipment in China based on real-world measurements

The objective of this paper is to quantify the variability in emissions of off-road equipment using a portable emission measurement system.A total of 53 commonly used equipment for agriculture,base construction,paving construction,and material handling were selected.Time-based and fuel-based emissions were quantified by different duty and engine modes.Three duty modes(idling,moving,and working)were used.Ten engine modes were defined based on normalized engine revolutions-per-minute and manifold absolute pressure,respectively.Composite emission factors taking into account both duty modes and its corresponding time percentage during a typical duty cycle were estimated.Results showed that there existed a large off-road equipment variability in emissions.Depending on duty and engine modes,time-based NO emissions ranged from 3.1 to 237.9,29.1‒1475.6,83.2‒681.6,and 3.2‒385.2 g/h for agriculture,base construction,paving construction and material handling equipment,respectively while for fuel-based NO emissions these ranges were 5.3‒52.0,11.7‒69.0,4.8‒30.8,and 11.0‒54.6 g/kg,respectively.Furthermore,emission factors derived from this study exhibited a much larger variability compared to those used in NONROAD by US EPA and National Guideline for Off-road Equipment of China.This implied that localized measurements of emissions are needed for improvement of accuracy of emission inventory.Furthermore,both equipment types and operations should be considered for development of emission inventory and control strategy.

Real-world emission factors for Caterpillar 797B heavy haulers during mining operations

Real-world fuel-based emission factors （EFs） from Caterpillar 797B diesel heavy haulers when used for oil sands mining operations were measured using an on-hoard portable emissions monitoring system. Average EFs （in g/kg fuel） for 16 separate tests on four trucks were 3150 ± 4 for CO2, 2.51 ± 1.30 for CH4, 10.28 ± 3.21 for CO, 0.61 ± 0.32 for non-methane hydrocarbons, 55.49 ± 9,75 for NOx （reported as NO2）, 0.70 ± 0.17 for PM2.s （mass of particles with aerodynamic diameter 〈2.5 μm）, and 0.34 ± 0.05 for black carbon （BC）. Ultrafine particle numbers averaged （4.7 ± 4.1 ） × 10^15 particleslkg fuel. Fuel-based EFs of NO, NO2, and particle numbers were higher during idling, whereas PM2.5 and BC EFs were higher during traveling without a load. A comparison of emissions with those reported by oil sands facilities showed large variations, both among the facilities and between the reported emissions and the real-world measurements.

Development of database of real-world diesel vehicle emission factors for China

A database of real-world diesel vehicle emission factors, based on type and technology, has been developed following tests on more than 300 diesel vehicles in China using a portable emission measurement system. The database provides better understanding of diesel vehicle emissions under actual driving conditions. We found that although new regulations have reduced real-world emission levels of diesel trucks and buses significantly for most pollutants in China, NOx emissions have been inadequately controlled by the current standards, especially for diesel buses, because of bad driving conditions in the real world. We also compared the emission factors in the database with those calculated by emission factor models and used in inventory studies. The emission factors derived from COPERT（Computer Programmer to calculate Emissions from Road Transport） and MOBILE may both underestimate real emission factors, whereas the updated COPERT and PART5（Highway Vehicle Particulate Emission Modeling Software） models may overestimate emission factors in China. Real-world measurement results and emission factors used in recent emission inventory studies are inconsistent,which has led to inaccurate estimates of emissions from diesel trucks and buses over recent years. This suggests that emission factors derived from European or US-based models will not truly represent real-world emissions in China. Therefore, it is useful and necessary to conduct systematic real-world measurements of vehicle emissions in China in order to obtain the optimum inputs for emission inventory models.