Emission Measurement System Research Articles

Measurements of the Emissions of a “Golden” Vehicle at Seven Laboratories with Portable Emission Measurement Systems (PEMS)

In the last years, the in-use emissions of vehicles are measured on the road with portable emissions measurement systems (PEMS). PEMS cannot measure as accurately as the laboratory grade equipment, and studies on their measurement uncertainty have continued since their appearance in the market. In this study we compared PEMS to laboratory grade equipment in Italian laboratories testing a diesel “Golden” (i.e., reference) vehicle for two consecutive years. The results showed equal means of PEMS and laboratory grade equipment for carbon dioxide (CO2), nitrogen oxides (NOx), and particle number (PN), with a variability of ±5 g/km for CO2, ±10 mg/km for NOx, and ±1 × 1011 p/km for PN, which further decreased in the second year. For carbon monoxide (CO), the PEMS were on average 5–20 mg/km higher than the bags (variability ±40 mg/km). The main conclusion of this study is that PEMS are accurate under controlled laboratory ambient conditions, without any indications of significant bias.

Real-world emission characteristics of black carbon emitted by on-road China IV and China V diesel trucks

Diesel vehicle is an important source of black carbon (BC). A portable emission measurement system including a photo-acoustic extinctiometer and SEMTECH-LDV was used to measure the real-world emissions of 14 light-duty and heavy-duty diesel trucks (LDDTs and HDDTs, meeting the China IV and China V standards) in Beijing. BC emission factors and the BC/PM2.5 ratio were obtained, and the effects of the vehicle type, emission standard and driving cycle on emissions were analyzed. The tightening of emission standards and the advancement of vehicle technology have reduced BC emissions from the China II standard to the China V standard. The emission reductions of BC are lower than those of other components of PM2.5 from the China II standard to the China IV standard but higher from the China IV standard to the China V standard. The BC and PM2.5 had the same main sources for the HDDTs and China IV LDDTs but had different sources for the China V LDDTs having diesel particulate filters. The BC/PM2.5 ratios of LDDTs, and HDDTs decreased from the China IV standard to the China V standard by 97.2% and 38.2%, respectively. The BC/PM2.5 ratio for China V LDDTs was 10 to 20 times lower than that for other diesel vehicles. The BC emissions tested under the highway driving cycle were 39.4% ± 16.7% lower than those under the no-highway driving cycle, but the BC/PM2.5 ratios had the opposite tendency. More China V and China VI heavy-duty diesel vehicles equipped with diesel particulate filters need to be tested to obtain more accurate BC/PM2.5 data and to improve the readiness of emission inventory calculations. The findings of this study help clarify the BC emission characteristics of diesel vehicles on actual roads and provide scientific basis for the formulation of emission control strategies for diesel vehicles in China.

Study on real-world power-based emission factors from typical construction machinery

Construction machinery accounts for a large share of the non-road machinery market and is an important pollutant source. In this study, real-world emission tests were undertaken on 16 excavators and 19 wheel loaders by using a portable emission measurement system (PEMS) to obtain their real-world engine performance and emission factors. The typical operating modes were categorized as idling, moving and working modes. The results show that in the working mode, the engine continuously operated at a high speed, high torque and high load factor, which led to sharp up and down CO, HC, NOx and particle number (PN) emissions. As the emission standards were strengthened, the CO, HC and NOx emissions clearly decreased, and the excavators and wheel loaders showed a higher emission level in the moving mode. A comparison of the excavator and wheel loader in China III displayed that the CO, HC, and NOx total emission factors of the wheel loader were 10.20, 2.70 and 1.79 times higher than those of the excavator, respectively, so the wheel loader contributed more seriously to environmental pollution. The CO and HC measured emission factors of the excavators and wheel loaders were 0.05-1.38 times and 0.13-0.58 times higher than the corresponding Limitation and the recommended values from the national emission inventory Guideline. However, the NOx emission factors were 1.20-3.25 times higher than the corresponding Limitation and the recommended value from the Guideline, which means that the recommended values overestimate CO and HC, and underestimate NOx. A comparison of the emission factors of the excavators and wheel loaders in this study with others demonstrate that the CO and HC power-based emission factors were generally lower, but the NOx emission factor was higher.

Research on Actual Road Emission Prediction Model of Heavy-Duty Diesel Vehicles Based on OBD Remote Method and Artificial Neural Network

In order to establish a prediction model of PM and NOx emission factors for heavy-duty diesel vehicles under actual road conditions based on OBD remote monitoring and big data, this paper carried out actual road tests on two China V heavy-duty diesel vehicles to obtain transient OBD and emission data by a Portable Emission Measurement System (PEMS) and self-developed On-board Remote Emission Measurement System (OREMS). According to the degree of influence of different parameters in the engine OBD on PM and NOx emissions, the principal component analysis method is used to extract the principal component parameters used to predict the model input, and the construction of a "Heavy-duty Diesel Vehicle Predictive Model based on Remote Monitoring Data and Neural Network Technology". Finally, the predictive model is trained and verified by PEMS test data. The prediction model provides new means and methods for the future development of large-scale heavy-duty diesel vehicle NOx and PM emission predictions under actual road operation.

Research on the characteristics of real-world vehicle particle number and mass emissions

Plug-in hybrid electric vehicles (PHEVs) have been greatly promoted due to their advantages in both performance and energy saving. However, real-world particle emission measurements for PHEV are generally conducted by dilution system but rarely through the directly hot-sampling method. This study firstly employs a hot-sampling HT-ELPI+, the main component of a portable emission measurement system, to investigate the real-world emissions of particle matter (PM) and particle number (PN) from a Euro V PHEV. Obvious higher emission factors (EFs) of PN and PM occurred on the highway compared to those on other road types. However, the lowest EFs occurred on the urban road for PN, while on the rural road for PM. The average speed-bin EFs of PN and PM both exhibited increasing trends with the speed increase, especially when the speed exceeds 100 km/h. And the peak PN and PM emission rates in different speed ranges exhibit the highest in the high-speed range, while the lowest in the low-speed range. Furthermore, the particle number size distribution exhibited an obvious unimodal distribution (mode size: 9 nm) for the whole speed and the medium- and high-speed ranges, while a bimodal distribution (mode size: 9 nm and 30 nm) for the low-speed range.

A systematic review on real time exhaust gas sensing system for on board sensing of harmful gases in IC engine

Air pollution causes detrimental effects on human health and the atmosphere. The emissions associated with transport represent a major component of aerial pollution. In recent years, air pollution is becoming a very important issue in India and around the World. Conventionally, the most popular dynamometer testing has been widely used to measure vehicle exhaust emission and these measured emissions have been used as primary data for modeling transport related air quality impact. However, during such conventional emission testing, real driving conditions are not strictly considered. Nowadays, real-time vehicle emission measurement is mainly focused by the most of the researchers for analysis purposes. In the present paper, the various real-time vehicle emission measuring technologies such as vehicle emission measurement by using RFID technology, emission measurement using gas sensor technology, emission measurement using gas sensor technology with the use of IoT and emission measurement using portable emission measurement system (PEMS) is discussed.Article I.

Impact of drivers on real-driving fuel consumption and emissions performance

Eco-driving has attracted great attention as a cost-effective and immediate measure to reduce fuel consumption significantly. Understanding the impact of driver behaviour on real driving emissions (RDE) is of great importance for developing effective eco-driving devices and training programs. Therefore, this study was conducted to investigate the performance of different drivers using a portable emission measurement system. In total, 30 drivers, including 15 novice and 15 experienced drivers, were recruited to drive the same diesel vehicle on the same route, to minimise the effect of uncontrollable real-world factors on the performance evaluation. The results show that novice drivers are less skilled or more aggressive than experienced drivers in using the accelerator pedal, leading to higher vehicle and engine speeds. As a result, fuel consumption rates of novice drivers vary in a slightly greater range than those of experienced drivers, with a marginally higher (2%) mean fuel consumption. Regarding pollutant emissions, CO and THC emissions of all drivers are well below the standard limits, while NOx and PM emissions of some drivers significantly exceed the limits. Compared with experienced drivers, novice drivers produce 17% and 29% higher mean NOx and PM emissions, respectively. Overall, the experimental results reject the hypothesis that driver experience has significant impacts on fuel consumption performance. The real differences lie in the individual drivers, as the worst performing drivers have significantly higher fuel consumption rates than other drivers, for both novice and experienced drivers. The findings suggest that adopting eco-driving skills could deliver significant reductions in fuel consumption and emissions simultaneously for the worst performing drivers, regardless of driving experience.

Characterizing Fuel Use and Emission Hotspots for a Diesel-Operated Passenger Rail Service.

Spatially varying diesel locomotive fuel use and emission rates (FUERs) are needed to accurately quantify local emission hotspots and their health impacts. However, existing locomotive FUER data are typically not spatially resolved or representative of real-world locomotive operation. Therefore, existing data are of limited use in quantifying the spatial variability in real-world FUERs. The objectives of this work are to quantify spatial variability in locomotive FUERs and identify factors differentiating hotspots from non-hotspots. FUERs were measured based on real-world measurements conducted for the Piedmont passenger rail service using a portable emission measurement system. FUERs were quantified based on 0.25 mile track segments on the Piedmont route. Hotspots were defined as segments in the top quintile of segment-average FUERs. On average, hotspots contributed 40-50% to trip fuel use and emissions. Hotspots were typically associated with low-to-medium speed, and high acceleration and grade. In contrast, non-hotspots were associated with high speed, and low acceleration and grade. Hotspots were typically located near populated areas and, thus, may exacerbate air pollutant exposure. The method demonstrated here can be applied to other passenger train services to assess key trends in hotspot locations and factors that explain the occurrence of hotspots.

NOx Emission from Diesel Vehicle with SCR System Failure Characterized Using Portable Emissions Measurement Systems

Nitrogen oxides (NOx) emissions from diesel vehicles are major contributors to increasing fine particulate matter and ozone levels in China. The selective catalytic reduction (SCR) system can effectively reduce NOx emissions from diesel vehicles and is widely used in China IV and V heavy-duty diesel vehicles (HDDVs). In this study, two China IV HDDVs, one with SCR system failure and the other with a normal SCR system, were tested by using a portable emissions measurement system (PEMS). Results showed that the NOx emission factors of the test vehicle with SCR system failure were 8.42 g/kW∙h, 6.15 g/kW∙h, and 6.26 g/kW∙h at loads of 0%, 50%, and 75%, respectively, which were 2.14, 2.10, and 2.47 times higher than those of normal SCR vehicles. Emission factors, in terms of g/km and g/kW∙h, from two tested vehicles were higher on urban roads than those on suburban and motorways. The NOx emission factor of the vehicle with failed SCR system did not meet the China IV emission standard. The time-weighted results for normal SCR vehicle over the three road types show that, except for NOx emission factor 12.17% higher than the China IV limit at 0% load, the emission values are 16.21% and 27.54% below the China IV standard limit at 50% load and 75% load, respectively. In general, with higher load, NOx emissions (in terms of g/kW∙h) from the tested vehicle decreased. Furthermore, NO/NOx concentrations of both vehicles with normal and failed SCR systems showed a decreasing trend with the increase in load.

Research on the real-world gaseous emission characteristics of a plug-in hybrid electric vehicle under different initial battery state-of-charge

Plug-in hybrid electric vehicles (PHEVs) have been greatly promoted due to their advantage in both vehicle performance and energy conversion efficiency. However, real-world emission measurements are rarely conducted for PHEV under different initial battery state-of-charge (SoC). In this study, a portable emission measurement system (PEMS) was employed to investigate the real-world emissions of carbon monoxide (CO), nitrogen oxides (NOx), and carbon dioxide (CO2) from a Euro V PHEV under fully and uncharged initial battery SoC. Compared to the emissions under the uncharged state, the average emission factors (EFs) of CO, NOx, and CO2 under the fully charged state are reduced by 72.2%, 27.8%, and 29.0%, respectively. And the reduction effect on the urban road is much more significantly prominent compared to that on the rural road and highway. In addition, obvious reduction effectiveness can be found for CO EFs in different average speed bins, especially those with speeds above 100 km/h. For NOx and CO2, however, the average speed-bin EFs are reduced only when the speed is below 70 km/h, while no obvious differences can be found when the speed is above 70 km/h. Furthermore, for the average vehicle specific power (VSP)-bin emission rates, obvious reduction effectiveness is observed for CO in different speed ranges, and for NOx and CO2 in the low- and medium-speed ranges except the high-speed range.

Reducing vehicle fuel consumption and exhaust emissions from the application of a green-safety device under real driving

Vehicle emissions have a significantly negative impact on climate change, air quality and human health. Drivers of vehicles are the last major and often overlooked factor that determines vehicle performance. Eco-driving is a relatively low-cost and immediate measure to reduce fuel consumption and emissions significantly. This paper reports investigation of the effects of an on-board green-safety device on fuel consumption and emissions for both experienced and inexperienced drivers. A portable emissions measurement system (PEMS) was installed on a diesel light goods vehicle (LGV) to measure real-driving emissions (RDE), including total hydrocarbons (THC), CO CO2, NO, NO2 and particulate matter (PM). In addition, driving parameters (e.g. vehicle speed and acceleration) and environmental parameters (e.g. ambient temperature, humidity and pressure) were recorded in the experiments. The experimental results were evaluated using the Vehicle Specific Power (VSP) methodology to understand the effects of driving behavior on fuel consumption and emissions. The results indicated that driving behavior was improved for both experienced and inexperienced drivers after activation of the on-board green-safety device. In addition, the average time spent was shifted from higher to lower VSP modes by avoiding excessive speed, and aggressive accelerations and decelerations. For experienced drivers, the average fuel consumption and NO, NO2 and soot emissions were reduced by 5%, 56%, 39% and 35%, respectively, with the on-board green-safety device. For inexperienced drivers, the average reductions were 6%, 65%, 50% and 19%, respectively. Moreover, the long-term formed habits of experienced drivers are harder to be changed to accept the assistance of the green-safety device, whereas inexperienced drivers are likely to be more receptive to change and improve their driving behaviors.

Modeling the emissions of rural vehicles based on real-world driving cycles

Characterized by a high frequency of use, harsh working environments, poor maintenance, and low levels of emission controls, rural vehicles (RVs) are becoming an important source of air pollution. Our study used a portable emission measurement system (PEMS) to test the real-world emissions of 35 RVs on provincial, rural, and farm roads. The results show that high emission rates of carbon monoxide (CO) and hydrocarbons (HC) mainly occurred when accelerating at low speeds. However, high levels of nitrogen oxides (NOx) were emitted during high-speed acceleration. The particulate number (PN) of emissions was higher when the RVs were accelerating. According to the overall test results, the vehicle specific power (VSP) on the provincial road mostly ranged within (0, 3], accounting for 68.80% of the total. The VSP on rural and farm roads was concentrated within (0, 2] kW·ton−1, accounting for 67.09% and 76.64% of the total, respectively. We defined 14 bins based on the distribution of the VSP values and calculated the average emission rate of each bin. By comparing the average emission rate among the bins, we found that within Bins 1–7 (VSP < 0 kW·ton−1), CO, HC, and NOx emissions slowly increased as the VSP increased. In Bins 8–13 (VSP ≥ 0 kW·ton−1), the average emission rates of four pollutants increased as the VSP increased. However, all pollutants decreased in Bin 14 (VSP ≥ 6 kW·ton−1). We built a microscopic emission model according to the VSP distribution characteristics of RVs on different road types. We compared the measured and simulated emission factors and found that our emission model can greatly simulate the HC, NOx and PN emission factors of RVs.

Real Driving Emission Calibration—Review of Current Validation Methods against the Background of Future Emission Legislation

Reducing air pollution caused by emissions from road traffic, especially in urban areas, is an important goal of legislators and the automotive industry. The introduction of so-called “Real Driving Emission” (RDE) tests for the homologation of vehicles with internal combustion engines according to the EU6d legislation was a fundamental milestone for vehicle and powertrain development. Due to the introduction of non-reproducible on-road emission tests with “Portable Emission Measurement Systems” (PEMS) in addition to the standardized emission tests on chassis dynamometers, emission aftertreatment development and validation has become significantly more complex. For explicit proof of compliance with the emission and fuel consumption regulations, the legislators continue to require the “Worldwide Harmonized Light Duty Vehicle Test Cycle” (WLTC) on a chassis dynamometer. For calibration purposes, also various RDE profiles are conducted on the chassis dynamometer. However, the combination of precisely defined driving profiles on the chassis dynamometer and the dynamics-limiting boundary conditions in PEMS tests on the road still lead to discrepancies between the certified test results and the real vehicle behavior. The expected future emissions standards to replace EU6d will therefore force even more realistic RDE tests. This is to be achieved by significantly extending the permissible RDE test boundary conditions, such as giving more weight to the urban section of an RDE test. In addition, the introduction of limit values for previously unregulated pollutants such as nitrogen dioxide (NO2), nitrous oxide (N2O), ammonia (NH3) and formaldehyde (CH2O) is being considered. Furthermore, the particle number (for diameters of solid particles &gt; 10 nm: PN10), the methane (CH4) emissions and emissions of non-methane organic gases (NMOG) shall be limited and must be tested. To simplify the test procedure in the long term, the abandonment of predefined chassis dyno emission tests to determine the pollutant emission behavior is under discussion. Against this background, current testing, validation, and development methods are reviewed in this paper. New challenges and necessary adaptations of current approaches are discussed and presented to illustrate the need to consider future regulatory requirements in today’s approaches. Conclusions are drawn and suggestions for a robust RDE validation procedure are formulated.

Alternative Exhaust Emission Factors from Vehicles in On-Road Driving Tests

On-road driving tests are performed to determine the emission of harmful exhaust compounds from vehicles. These primarily include carbon dioxide, nitrogen oxides, and particle number. However, there is a lack of indicators that combine the first three substances that are the most important in assessing the environmental aspects of vehicles. The purpose of this article is to indicate the possibility of assessing emissions in real driving conditions from light-duty and heavy-duty vehicles of different categories. In order to do so, a portable emissions measurement system (PEMS) and an instrument for measuring the particle number were used. The tests were carried out on routes designed to comply with the requirements and regulations laid down in the European Union legislation. On-road emissions of carbon dioxide, nitrogen oxides and particle number have been determined. Factors have been determined as the multiplication of these compounds for each vehicle category in three phases of the test: urban, rural, and motorway. A new way of assessing emissions from vehicles using new factors has been proposed.

Experimental Investigation on Emissions Characteristics from Urban Bus Fueled with Diesel, Biodiesel and an Oxygenated Additive from Residual Glycerin from Biodiesel Production

The aim of the study was to assess the influence of the addition of an oxygenated additive (a mixture of mono-, di- and triacetylglycerol obtained from residual glycerin within the biodiesel production scheme) on the specific fuel consumption and exhaust emissions of a EURO 3 diesel bus during its daily route through the city. To do this, the urban bus was fuelled with five fuel blends of diesel (D), biodiesel (B), additive (A) and heptanol as co-surfactant (H). A portable emissions measurement system was used to measure the exhaust gases while an engine exhaust particle system with a dilution system, both installed on the urban bus, was used for nanoparticles measurement in actual operating conditions through the city of Seville. Results showed that B95A5 (95%v/v biodiesel, 5%v/v additive) and B90A10 were the blends that most increased NOx emissions (by 24.12% and 9.85%, respectively) compared to D100. On the other hand, B47.5D47.5A2.5H2.5 was the blend that most reduced total particle number (by 31.6%) and NOx emissions (by 12%). All in all, the oxygenated additive can be efficiently blended with biodiesel to reduce particle emissions from engines without diesel particle filter, such as those in urban buses in many European cities.

Study of Air Pollutions Caused by Exhaust Gases Emitted from Gasoline Vehicles in Erbil City

The environmental pollution caused by exhaust gas during parking in Erbil City’s Periodic Vehicle Inspection (PVI) was studied. The purpose of this research is to measure vehicle exhaust emissions from Erbil (PVI) gasoline vehicles. Tested the carbon monoxide (CO), carbon dioxide (CO2), oxygen (O2) and hydrocarbon (HC) emissions of gasoline vehicles. The statistical results show that there are significant differences between emission rates based on vehicle characteristics (such as fuel type, model year, engine fuel supply system, and regular maintenance). In addition, these factors will also affect the emission level test results based on the Iraqi vehicle emission standards. In addition, the emissions of these exhaust gases also depend on factors such as engine combustion design and operating conditions, fuel grade, lubricants, local road conditions and other factors, and continue to affect the concentration of pollutants emitted by vehicles (such as carbon dioxide and unburned hydrocarbons) These pollutants are very toxic to the human body and cause environmental pollution. Accurate estimates of pollutant emissions are needed to ensure proper design and implementation of air quality plans. Emission factors (EFs) are empirical functions between pollutant emissions and their activities. In this review article, in connection with the development of EFs found in emission models used to generate emission inventories, techniques for measuring emissions from road vehicles are studied. The emission measurement technologies covered include those most widely used for road vehicle emission data collection, namely chassis and engine dynamometer measurements, remote sensing, road tunnel research, and portable emission measurement systems (PEMS). The main advantages and disadvantages of each method with regard to emission modeling are presented. It also reviews ways in which EF can be derived from test data, with a clear distinction between data obtained under controlled conditions (engine and chassis dynamometer measurements using standard driving cycles) and measurements under real conditions.

Simulation and assessment of traffic pollutant dispersion at an urban signalized intersection using multiple platforms

Evaluating the performance of air quality models for roadside traffic exhaust dispersion is critical to sustainable environmental development and urban pollution management. This study introduces three models, namely CAL3QHC, ENVI-met and ANSYS Fluent, to model the pollutant dispersion at an isolated busy urban signalized intersection, by taking fine particulate matter (PM2.5) as the subject matter. A dynamic emission factor model was established based on Cell Transmission Model (CTM) and Portable Emission Measurement System (PEMS) experiment, which was further implemented with the User Defined Function (UDF) of ANSYS Fluent. Results from an empirical study based on the Jianchuan and Humin Road intersection, in suburb Shanghai, demonstrate that ANSYS Fluent performs better for PM2.5 concentration prediction with carefully calibrated parameter settings. Simulation results from both CAL3QHC and ANSYS Fluent are within an acceptable scale, while ENVI-met performs better in assessing the correlation relationships between PM concentrations and the intersectional and meteorological factors. The concentration of PM2.5 was found to increase significantly during the idle phase, which tends to be accumulated in front of the intersection buildings simultaneously. With the increasing of the altitude, the overall average PM2.5 concentration of the intersection decreases gradually. Street canyons with high buildings were found with comparable lower wind speeds, hindering the pollutant diffusion. Finds of this study may assist urban intersection design from a variety of perspectives, e.g., lane channelization, signal timing, and even architecture styles of the surrounding buildings.

Characterization of Pollutant Emissions from Typical Material Handling Equipment Using a Portable Emission Measurement System

Non-road equipment has been an important source of pollutants that negatively affect air quality in China. An accurate emission inventory for non-road equipment is therefore required to improve air quality. The objective of this paper was to characterize emissions from typical diesel-fueled material handling equipment (loaders and cranes) using a portable emission measurement system. Instantaneous, modal, and composite emissions were quantified in this study. Three duty modes (idling, moving, and working) were used. Composite emission factors were estimated using modal emissions and time-fractions for typical duty cycles. Results showed that emissions from loaders and cranes were higher and more variable for the moving and working modes than the idling mode. The estimated fuel-based CO, HC, NO, and PM2.5 composite emission factors were 21.7, 2.7, 38.2, and 3.6 g/(kg-fuel), respectively, for loaders, and 8.7, 2.4, 28.3, and 0.3 g/(kg-fuel), respectively, for cranes. NO emissions were highest and should be the main focus for emission controls. CO, HC, NO, and PM2.5 emissions measured were different from emission factors in the US Environmental Protection Agency NONROAD model and the Chinese National Guideline for Emission Inventory Development for Non-Road Equipment. This indicates that improving emission inventory accuracy for non-road equipment requires more real-world emission measurements.

Effects of driving behavior on real-world emissions of particulate matter, gaseous pollutants and particle-bound PAHs for diesel trucks

This study employed a portable emissions measurement system to investigate the effects of vehicle attributes, driving behavior, and road grade on real-world emissions of particulate matter (PM), regulated gaseous pollutants, and particle-bound polycyclic aromatic hydrocarbons (PAHs) for old-model diesel trucks (model year 1995–2006, 6.7–35.0 metric ton) with little to no tailpipe emission control. The rated power of engines was a major determinant of the distance-specific emission factors of PM, particle-bound PAHs, and most gaseous pollutants. However, the engine size was unrelated to the total hydrocarbon emission factor and the benzo[a]pyrene equivalent (BaPeq) emission factor of PAHs. Aggressive (AG) and normal (NR) driving behaviors were quantitatively defined with a relative positive acceleration. The emission factors of PM, CO2, and THC were significantly different (p < 0.05) between the AG and NR driving modes. AG driving caused an average increase in emissions of PM, CO2, NOx, and particle-bound PAHs by 122%, 56%, 15%, and 128%, respectively, compared to the respective emissions under the NR mode. The BaPeq emission factor of PAHs in the AG mode was more than 10 times that in the NR mode. The road gradient (ranging from −9.3% to 9.0% over the test route) had significant impacts on the emissions of PM, CO2, and NOx. PM, CO2, and NOx emission factors increased by 109%, 168%, and 160%, respectively, in the >6% grade bin and decreased by 95%, 91%, and 90%, respectively, in the equivalent negative-grade bin, implying that the decrease in emissions on negative road slopes may not compensate for the increase in emissions on the equivalent positive road slopes despite the road slope being compensated. The findings of this study will be valuable for developing air quality management strategies and furthering scientific knowledge on the complex interplay of different variables that affect real-world emissions of on-road vehicles.

Sensitivity of light duty vehicle tailpipe emission rates from simplified portable emission measurement systems to variation in engine volumetric efficiency

ABSTRACT Light-duty gasoline vehicle (LDGV) tailpipe emission rates can be quantified based on pollutant concentrations measured using portable emission measurement systems (PEMS). Emission rates depend on exhaust flow. For simplified and micro-PEMS, exhaust flow is inferred from engine mass air flow (MAF) and air-to-fuel ratio. For many LDGVs, MAF is broadcast via the on-board diagnostic (OBD) interface. For some vehicles, only indirect indicators of MAF are broadcast. In such cases, MAF can be estimated using the speed-density method (SDM). The SDM requires an estimate of the engine volumetric efficiency (VE), which is the ratio of actual to theoretical MAF. VE is affected by intra-vehicle variability in the engine load and inter-vehicle variability in engine characteristics (e.g., the type of valvetrain). The suitability of SDM-based estimates of MAF in conjunction with simplified and micro-PEMS has not been adequately evaluated. Therefore, the objectives are to: (1) quantify VE accounting for intra- and inter-vehicle variability; and (2) evaluate the accuracy of SDM-based vehicle emission rate estimation approaches. Seventy-seven naturally-aspirated LDGVs were measured using PEMS. For each vehicle, VE was estimated using three approaches: (1) constant VE calibrated to actual fuel use; (2) average estimates of VE for Vehicle Specific Power modes imputed from OBD data; and (3) modeled VE using multilinear regression (MLR). The MLR models were developed based on engine load and engine characteristics. The best model was selected based on various statistical diagnostics. When engines were under load, variability in VE was most sensitive to variations in engine load. During idling, VE differed between engines depending on engine characteristics. The constant and modeled VE estimation approaches enable the accurate estimation of microscale and mesoscale emission rates, with errors typically within ±10% compared to values imputed from OBD data. Thus, accurate emission rates can be obtained from simplified and micro-PEMS. Implications: Simplified and micro portable emission measurement systems (PEMS) enable widespread measurement of vehicle exhaust emission. As a cost saving measure, they estimate exhaust flow indirectly rather than via measurement, typically based on engine mass air flow (MAF). For some vehicles, MAF is not reported by the on-board diagnostic (OBD) system but can be inferred from other reported variables and volumetric efficiency (VE). However, VE is typically proprietary. Methods demonstrated here for estimating VE enable accurate quantification of emission rates, thereby enabling use of these PEMS for policy-relevant applications such as technology assessments, trends analysis, and emissions inventories.