Evaluating mobile monitoring of on-road emission factors by comparing concurrent PEMS measurements

Characterization of on-road nitrogen oxides and black carbon emissions from high emitters of heavy-duty diesel vehicles in China

Heavy-duty diesel vehicles (HDDVs) significantly contribute to atmospheric nitrogen oxides (NOX) and black carbon (BC), with high emitters within the HDDV fleet impacting the total emissions. However, emission patterns and contributions of high emitters are rarely explored from a fleet-perspective. We investigated NOX and BC emission factors (EFs) from 1925 HDDVs in Shenzhen by the plume-chasing method, and found that the fleet-average EFs decreased with stricter emission standards. Unexpectedly, the average NOX EF for the China IV fleet was comparable with that for the China III fleet due to possible ineffective aftertreatment in high-emitter sectors of China IV HDDVs. Decreasing trend in average NOX EF since 2017 reflected the effective emission controls by the implementation of China V standard. Besides, semi-trailer tractors exhibited a higher incidence of NOX over-emissions, whereas BC high emitters were more pronounced in box trucks. Total NOX and BC emissions from HDDVs in Shenzhen were revisited, reaching 54.0 and 1.1 Gg·yr-1, with updated NOX EF correcting a 26.2 % underestimation in national guidelines. Notably, eliminating high emitters yields greater emission reduction benefits than merely retiring old HDDVs, with BC reduction outpacing NOX. This study provides new insights into the implementation of targeted emission reduction measures for HDDVs.

Regulatory Insights for On-Board Monitoring of Vehicular NOx Emission Compliance

Nitrogen oxide (NOx) emissions from heavy-duty diesel vehicles (HDDVs) have adverse effects on human health and the environment. On-board monitoring (OBM), which can continuously collect vehicle performance and NOx emissions throughout the operation lifespan, is recognized as the core technology for future vehicle in-use compliance, but its large-scale application has not been reported. Here, we utilized OBM data from 22,520 HDDVs in China to evaluate their real-world NOx emissions. Our findings showed that China VI HDDVs had a 73% NOx emission reduction compared with China V vehicles, but a considerable proportion still faced a significant risk of higher NOx emissions than the corresponding limits. The unsatisfactory efficiency of the emission treatment system under disadvantageous driving conditions (e.g., low speed or ambient temperature) resulted in the incompliance of NOx emissions, especially for utility vehicles (sanitation/garbage trucks). Furthermore, the observed intertrip and seasonal variability of NOx emissions demonstrated the need for a long-term continuous monitoring protocol instead of instantaneous evaluation for the OBM. With both functions of emission monitoring and malfunction diagnostics, OBM has the potential to accurately verify the in-use compliance status of large-scale HDDVs and discern the responsibility of high-emitting activities from manufacturers, vehicle operators, and driving conditions.

Characteristics of NOX and NH3 emissions from in-use heavy-duty diesel vehicles with various aftertreatment technologies in China

Some in-use China IV and China V heavy-duty diesel vehicles (HDDVs) with selective catalytic reduction (SCR) systems probably fail to mitigate nitrogen oxide (NOX) emissions as expected. Meanwhile, these SCR-equipped HDDVs might emit excessive ammonia (NH3). To better understand the NOX and NH3 emissions from typical HDDVs in China, seventeen in-use vehicles with various emission-control technologies were tested by using laboratory chassis dynamometers. The results indicated that individual NOX and NH3 emissions from HDDV fleets widely varied owing to differences in aftertreatment performance. China V and VI HDDVs with effectively functioning SCRs could substantially control their NOX emissions to be below the corresponding emission limits (i.e., 4.0 and 0.69 g/kWh for China V and China VI vehicles, respectively) but with a potential risk of high NH3 emissions caused by diesel exhaust fluid (DEF) overdosing. Furthermore, higher vehicle speed and payload resulted in lower NOX emissions and possibly higher NH3 emissions from HDDVs with effectively functioning SCRs, while higher NOX emissions from tampered- and non-SCR HDDVs. NOX emissions from China VI HDDVs were more sensitive to cold starts compared to China V and earlier vehicles, but there was no significant discrepancy in NH3 emissions between cold- and hot-start tests.

Data-driven method for estimating emission factors of multiple pollutants from excavators based on portable emission measurement system and online driving characteristic identification

This study aims to explore the factors that influence the emission characteristics of multiple pollutants from non-road mobile machinery (NRMM) under real-world conditions and to establish a data-driven method for calculating accurate emission factors. This research focused on NRMM excavators meeting the third-stage emission standards and identified the actual work characteristics of 108 excavators in different scenarios based on a self-developed testing system for 368,000 h. Additionally, a portable emission testing system (PEMS) was used to study the instantaneous emission characteristics under different driving styles and modes for 10 EC210 excavators with the largest engineering construction inventory. The results showed that the average time proportions of idling, working, and moving modes for excavators were 21 %, 66 %, and 13 %, respectively. The results also revealed that the instantaneous emission rates of multiple pollutants varied significantly under different driving styles and modes. Driving style affected the hydraulic pump power change rate through hydraulic pilot pressure, and engine load surge caused turbocharger response delay and in-cylinder combustion deterioration, which affected pollutant emissions. Driving mode affected the emission characteristics of idling, high-speed idling, moving, and working modes of excavators through the external characteristics corresponding to the engine speed gear set. The data-driven method for calculating emission factors differed from the traditional method for most indicators to varying degrees. In terms of fuel-based emission factors (EFfs), except for the EFfNOx indicator, which was 7.859 % higher than the traditional method, the other three indicators were significantly lower than the traditional method. In terms of power-based emission factors (EFps), except for EFpPM and EFpPN, the other two indicators were much higher than the traditional method. EFpCO and EFpNOx were 7.93 % and 20.332 % higher than the traditional method, respectively. It is recommended to use the data-driven method based on the actual driving data distribution to provide scientific support for accurately establishing the emission inventory.

Emission Measurements on a Large Sample of Heavy-Duty Diesel Trucks in China by Using Mobile Plume Chasing

Real-world heavy-duty diesel trucks (HDTs) were found to emit far more excess nitrogen oxides (NOX) and black carbon (BC) pollutants than regulation limits. It is essential to systematically evaluate on-road NOX and BC emission levels for mitigating HDT emissions. This study launched 2109 plume chasing campaigns for NOX and BC emissions of HDTs across several regions in China from 2017 to 2020. It was found that NOX emissions had limited reductions from China III to China V, while BC emissions of HDTs exhibited high reductions with stricter emission standard implementation. This paper showed that previous studies underestimated 18% of NOX emissions in China in 2019 and nearly half of the real-world NOX emissions from HDTs (determined by updating the emission trends of HDTs) exceeded the regulation limits. Furthermore, the ambient temperature was identified as a primary driver of NOX emissions for HDTs, and the low-temperature penalty has caused a 9-29% increase in NOX emissions in winter in major regions of China. These results would provide important data support for the precise control of the NOX and BC emissions from HDTs.

Updating On-Road Vehicle Emissions for China: Spatial Patterns, Temporal Trends, and Mitigation Drivers

Vehicle emissions in China have been decoupled from rapid motorization owing to comprehensive control strategies. China's increasingly ambitious goals for better air quality are calling for deep emission mitigation, posing a need to develop an up-to-date emission inventory that can reflect the fast-developing policies on vehicle emission control. Herein, large-sample vehicle emission measurements were collected to update the vehicle emission inventory. For instance, ambient temperature correction modules were developed to depict the remarkable regional and seasonal emission variations, showing that the monthly emission disparities for total hydrocarbon (THC) and nitrogen oxide (NOX) in January and July could be up to 1.7 times in northern China. Thus, the emission ratios of THC and NOX can vary dramatically among various seasons and provinces, which have not been considered well by previous simulations regarding the nonlinear atmospheric chemistry of ozone (O3) and fine particulate matter (PM2.5) formation. The new emission results indicate that vehicular carbon monoxide (CO), THC, and PM2.5 emissions decreased by 69, 51, and 61%, respectively, during 2010-2019. However, the controls of NOX and ammonia (NH3) emissions were not as efficient as other pollutants. Under the most likely future scenario (PC [1]), CO, THC, NOX, PM2.5, and NH3 emissions were anticipated to reduce by 35, 36, 35, 45, and 4%, respectively, from 2019 to 2025. These reductions will be expedited with expected decreases of 56, 58, 74, 53, and 51% from 2025 to 2035, which are substantially promoted by the massive deployment of new energy vehicles and more stringent emission standards. The updated vehicle emission inventory can serve as an important tool to develop season- and location-specific mitigation strategies of vehicular emission precursors to alleviate haze and O3 problems.

Quantifying traffic-related carbon emissions on elevated roads through on-road measurements

Vehicles generally move smoothly and with high speeds on elevated roads, thereby producing specific traffic-related carbon emissions in contrast to ground roads. Hence, a portable emission measurement system was adopted to determine traffic-related carbon emissions. The on-road measurement results revealed that the instantaneous emissions of CO2 and CO from elevated vehicles were 17.8% and 21.9% higher than those from ground vehicles, respectively. Based on it, the vehicle specific power was confirmed to exhibit a positive exponential relationship with instantaneous CO2 and CO emissions. In addition to carbon emissions, carbon concentrations on roads were simultaneously measured. The average CO2 and CO emissions on elevated roads in urban areas were 1.2% and 6.9% higher than those on ground roads, individually. Finally, a numerical simulation was performed, and the results verified that elevated roads could deteriorate the air quality on ground roads but improve the air quality above them. What ought to be paid attention to is that the elevated roads present varied traffic behaviour and cause particular carbon emissions, indicating that comprehensive consideration and further balance among the traffic-related carbon emissions are necessary when building elevated roads to alleviate the traffic congestion in urban areas.

Assessing heavy-duty vehicles (HDVs) on-road NOx emission in China from on-board diagnostics (OBD) remote report data

Mobile source emissions are some of the major causes of air pollution across the world and are associated with numerous adverse health impacts. China has implemented increasingly stringent emission standards over the past few decades, the most recent one being the sixth emission standard (China VI) first rolled out in 2019. The China VI standard places special emphasis on tightening limits for NO_x emission and introduces remote monitoring of vehicles' On-board diagnostics (OBD) data to reduce emissions from diesel and gas-powered heavy-duty vehicles (HDV). This paper aims to establish a methodology to calculate HDV NO_x emissions on an extended timescale, and under real-world operations. OBD data was collected and examined from 53 China VI diesel HDVs and 14 China V diesel HDVs, which found that the average NO_x emission factors are 1.420 g/km and 3.894 g/km for the two samples respectively; this indicates that the implementation of China VI standard helps to significantly reduce NO_x emission from HDVs. Combining the emission factors and calculated travel distances collected by OBD and vehicle sales data, the China VI emission standard is estimated to have resulted in 43,969 tons of NO_x emission reduction by the end of 2020. With China announcing country-wide enforcement of the new standard in 2021, >1.7 million tons of NO_x emission could be avoided by 2023 annually.

China 6 moving average window method for real driving emission evaluation: Challenges, causes, and impacts

The light-duty moving average window (MAW) method, used for China 6 real driving emission (RDE) calculation, is quite complex with various boundaries. Previous research noticed that the MAW might underestimate the calculation results, while the reasons for this underestimation haven't been studied systematically. With 29 vehicles tested in 10 cities and different boundaries applied for calculation, this study quantitively analyzed the problem, causes, and impacts of the light-duty MAW method. The instantaneous utilization factor (IUF) is proposed for reason analysis. The current MAW method could weaken the supervision of real driving tests as more than 75% of the tests underestimated MAW results, with the largest underestimation being around 100%. The data exclusion could lead to biased MAW results. But without the exclusion, the MAW result couldn't always get an increase due to the IUF and window weighting factor variation. With the extended factors removed, the MAW result bias is significantly reduced. The MAW will lead to a lower IUF of the data at the start/end of the tests, and when the cold-start data is considered, this low utilization must be noticed. The effect from the data exclusion, extended factors, and the window characteristics are closely coupled and they should be taken into consideration simultaneously to consummate the calculation method. The current drift-check progress couldn't effectively monitor the portable emission measurement system (PEMS), especially during the tests. The MAW result might lead to unreasonable emission limits and the emission inventory. Relevant policy based on these results might be implausible.

Effect of sampling duration on the estimate of pollutant concentration behind a heavy-duty vehicle: A large-eddy simulation

Plume chasing is cost-effective, measuring individual, on-road vehicular emissions. Whereas, wake-flow-generated turbulence results in intermittent, rapid pollutant dilution and substantial fluctuating concentrations right behind the vehicle being chased. The sampling duration is therefore one of the important factors for acquiring representative (average) concentrations, which, however, has been seldom addressed. This paper, which is based on the detailed spatio-temporal dispersion data after a heavy-duty truck calculated by large-eddy simulation (LES), examines how sampling duration affects the uncertainty of the measured concentrations in plume chasing. The tailpipe dispersion is largely driven by the jet-like flows through the vehicle underbody with approximate Gaussian concentration distribution for x ≤ 0.6h, where x is the distance after the vehicle and h the characteristic vehicle size. Thereafter for x ≥ 0.6h, the major recirculation plays an important role in near-wake pollutant transport whose concentrations are highly fluctuating and positively shewed. Plume chasing for a longer sampling duration is more favourable but is logistically impractical in busy traffic. Sampling duration, also known as averaging time in the statistical analysis, thus has a crucial role in sampling accuracy. With a longer sampling (averaging) duration, the sample mean concentration converges to the population mean, improving the sample reliability. However, this effect is less pronounced in long sampling duration. The sampling accuracy is also influenced by the locations of sampling points. For the region x > 0.6h, the sampling accuracy is degraded to a large extent. As a result, acceptable sample mean is hardly achievable. Finally, frequency analysis unveils the mechanism leading to the variance in concentration measurements which is attributed to sampling duration. Those data with frequency higher than the sampling frequency are filtered out by moving average in the statistical analyses.

Evaluation of a cost-effective roadside sensor platform for identifying high emitters

High-emission vehicles (high emitters) likely have significantly higher nitrogen oxide and particle number (PN) emission factors compared to other vehicles. Effective identification of these vehicles in road traffic requires efficient and cost-effective instruments. In this study, a compact, cost-effective sensor platform was developed and evaluated in a field experiment. The platform was deployed on a roadside, and we measured pollutant concentrations in the exhaust plumes of four diesel trucks with various aftertreatment systems, cargo loads, and driving speeds. The sensor platform successfully measured carbon dioxide, PN, and nitric oxide (NO) concentrations, and the data were used to derive the plume-based emission factors of these pollutants. By considering both NO and PN emission factors, three diesel trucks with failed or outdated aftertreatment systems were successfully identified as potential high emitters. The NO emission factor obtained by the sensor platform was consistent with that of the benchmark portable emission measurement system. The sensor platform also effectively elucidated the differential influences of aftertreatment systems and driving conditions on emission factors. This pilot test demonstrates the feasibility of a sensor-based system for high emitter identification. Owing to its cost-effective and compact design, the proposed sensor platform has greater potential for mass networked deployment than regular-size instruments, thereby effectively supporting regulatory protocols for screening high emitters on public roads.

CO2 Emission Factors and Carbon Losses for Off-Road Mining Trucks

There are myriad questions that remain to be answered in greenhouse gas (GHG) emissions trading. This article addresses carbon dioxide (CO2) emission factors and carbon losses from heavy equipment that is used to transport ores. Differences occurred between the Intergovernmental Panel for Climate Change (IPCC) emission factor and those that were obtained by considering incomplete combustion and on-site exhaust concentration measurements. Emissions from four off-road vehicles were analyzed. They operated at idle (loading, unloading, and queuing) and in motion (front and rear, loaded and unloaded). The results show that the average CO2 emission factors can be as low as 64.8% of the IPCC standard value for diesel fuel. On the other hand, carbon losses can be up to 33.5% and energy losses up to 25.5%. To the best of the authors’ knowledge, the method that was developed here is innovative, simple, useful, and easily applicable in determining CO2 emission factors and fuel losses for heavy machinery.

Uncertainty investigation of plume-chasing method for measuring on-road NOx emission factors of heavy-duty diesel vehicles

The plume-chasing method has shown great advantages in measuring on-road emission factors (EFs) compared with regulatory methods like dynamometer and portable emission measurement systems (PEMS). In this study, a new on-board measurement system incorporating ultrasonic anemometers and solid-state Lidar was developed to investigate the uncertainties of on-road emission factors measured by plume-chasing method due to variables such as on-road wind velocity, chasing speed, chasing distance, and turbulent kinetic energy (TKE). A series of PEMS-chasing experiments for heavy-duty diesel vehicles (HDDVs) were conducted on both highways and local roadways in Beijing, China. Our analysis demonstrated that the differences in EF estimations between concurrent plume-chasing and PEMS measurement decreased with increasing chasing speed as a result of greater vehicle-induced TKE in the wake between HDDV and the mobile platform, whereas the effect of chasing distance on EF estimations appeared insignificant within the tested distance range (12-22 m). In the case of strong crosswinds, overprediction of chasing-based EFs was observed due to convective plume mixing from surrounding vehicular sources. The findings of this study contribute greatly to interpret emission factors measured by the plume-chasing method, and also calls for a future study to develop real-time EF correction algorithms for large-scale mobile chasing measurements.

State-of-the-Art of Establishing Test Procedures for Real Driving Gaseous Emissions from Light- and Heavy-Duty Vehicles

Air pollution caused by vehicle emissions has raised serious public health concerns. Vehicle emissions generally depend on many factors, such as the nature of the vehicle, driving style, traffic conditions, emission control technologies, and operational conditions. Concerns about the certification cycles used by various regulatory authorities are growing due to the difference in emission during certification procedure and Real Driving Emissions (RDE). Under laboratory conditions, certification tests are performed in a ‘chassis dynamometer’ for light-duty vehicles (LDVs) and an ‘engine dynamometer’ for heavy-duty vehicles (HDVs). As a result, the test drive cycles used to measure the automotive emissions do not correctly reflect the vehicle’s real-world driving pattern. Consequently, the RDE regulation is being phased in to reduce the disparity between type approval and vehicle’s real-world emissions. According to this review, different variables such as traffic signals, driving dynamics, congestions, altitude, ambient temperature, and so on have a major influence on actual driving pollution. Aside from that, cold-start and hot-start have been shown to have an effect on on-road pollution. Contrary to common opinion, new technology such as start-stop systems boost automotive emissions rather than decreasing them owing to unfavourable conditions from the point of view of exhaust emissions and exhaust after-treatment systems. In addition, the driving dynamics are not represented in the current laboratory-based test procedures. As a result, it is critical to establish an on-road testing protocol to obtain a true representation of vehicular emissions and reduce emissions to a standard level. The incorporation of RDE clauses into certification procedures would have a positive impact on global air quality.