Recent advances and perspectives towards emission inventories of mobile sources: Compilation approaches, data acquisition methods, and case studies.

In recent years, great efforts have been devoted to reducing emissions from mobile sources with the dramatic growth of motor vehicle and nonroad mobile source populations. Compilation of a mobile source emission inventory is conducive to the analysis of pollution emission characteristics and the formulation of emission reduction policies. This study summarizes the latest compilation approaches and data acquisition methods for mobile source emission inventories. For motor vehicles, a high-resolution emission inventory can be developed based on a bottom-up approach with a refined traffic flow model and real-world speed-coupled emission factors. The top-down approach has advantages when dealing with macroscale vehicle emission estimation without substantial traffic flow infrastructure. For nonroad mobile sources, nonroad machinery, inland river ships, locomotives, and civil aviation aircraft, a top-down approach based on fuel consumption or power is adopted. For ocean-going ships, a bottom-up approach based on automatic identification system (AIS) data is adopted. Three typical cases are studied, including emission reduction potential, a cost-benefit model, and marine shipping emission control. Outlooks and suggestions are given on future research directions for emission inventories for mobile sources: building localized emission models and factor databases, improving the dynamic updating capability of emission inventories, establishing a database of emission factors of unconventional pollutants and greenhouse gas from mobile sources, and establishing an urban high temporal-spatial resolution volatile organic compound (VOC) evaporation emission inventory.

Source-Receptor Relationship Revealed by the Halted Traffic and Aggravated Haze in Beijing during the COVID-19 Lockdown.

The COVID-19 outbreak greatly limited human activities and reduced primary emissions particularly from urban on-road vehicles but coincided with Beijing experiencing "pandemic haze," raising the public concerns about the effectiveness of imposed traffic policies to improve the air quality. This paper explores the relationship between local vehicle emissions and the winter haze in Beijing before and during the COVID-19 lockdown based on an integrated analysis framework, which combines a real-time on-road emission inventory, in situ air quality observations, and a localized numerical modeling system. We found that traffic emissions decreased substantially during the COVID-19 pandemic, but its imbalanced emission abatement of NOx (76%, 125.3 Mg/day) and volatile organic compounds (VOCs, 53%, 52.9 Mg/day) led to a significant rise of atmospheric oxidants in urban areas, resulting in a modest increase in secondary aerosols due to inadequate precursors, which still offset reduced primary emissions. Moreover, the enhanced oxidizing capacity in the surrounding regions greatly increased the secondary particles with relatively abundant precursors, which was transported into Beijing and mainly responsible for the aggravated haze pollution. We recommend that mitigation policies should focus on accelerating VOC emission reduction and synchronously controlling regional sources to release the benefits of local traffic emission control.

Intermediate-Volatility Organic Compound Emissions from Nonroad Construction Machinery under Different Operation Modes.

Intermediate-volatility organic compounds (IVOCs) have been found as important sources for secondary organic aerosol (SOA) formation. IVOC emissions from nonroad construction machineries (NRCMs), including two road rollers and three motor graders, were characterized under three operation modes using an improved portable emission measurement system. The fuel-based IVOC emission factors (EFs) of NRCMs varied from 245.85 to 1802.19 mg/kg·fuel, which were comparable at magnitudes to the reported results of an ocean-going ship and on-road diesel vehicles without filters. The discrepancy of IVOC EFs is significant within different operation modes. IVOC EFs under the idling mode were 1.24-3.28 times higher than those under moving/working modes. Unspeciated b-alkanes and cyclic compounds, which were the unresolved components in IVOCs at the molecular level, accounted for approximately 91% of total IVOCs from NRCMs. The SOA production potential analysis shows that IVOCs dominated SOA formation of NRCMs. Our results demonstrate that IVOC emissions from NRCMs are non-negligible. Thus, an accurate estimation of their IVOC emissions would benefit the understanding of SOA formation in the urban atmosphere.

DeepHMap++: Combined Projection Grouping and Correspondence Learning for Full DoF Pose Estimation.

In recent years, estimating the 6D pose of object instances with convolutional neural network (CNN) has received considerable attention. Depending on whether intermediate cues are used, the relevant literature can be roughly divided into two broad categories: direct methods and two-stage pipelines. For the latter, intermediate cues, such as 3D object coordinates, semantic keypoints, or virtual control points instead of pose parameters are regressed by CNN in the first stage. Object pose can then be solved by correspondence constraints constructed with these intermediate cues. In this paper, we focus on the postprocessing of a two-stage pipeline and propose to combine two learning concepts for estimating object pose under challenging scenes: projection grouping on one side, and correspondence learning on the other. We firstly employ a local-patch based method to predict projection heatmaps which denote the confidence distribution of projection of 3D bounding box's corners. A projection grouping module is then proposed to remove redundant local maxima from each layer of heatmaps. Instead of directly feeding 2D⁻3D correspondences to the perspective-n-point (PnP) algorithm, multiple correspondence hypotheses are sampled from local maxima and its corresponding neighborhood and ranked by a correspondence⁻evaluation network. Finally, correspondences with higher confidence are selected to determine object pose. Extensive experiments on three public datasets demonstrate that the proposed framework outperforms several state of the art methods.

An Occlusion-Aware Framework for Real-Time 3D Pose Tracking.

Random forest-based methods for 3D temporal tracking over an image sequence have gained increasing prominence in recent years. They do not require object's texture and only use the raw depth images and previous pose as input, which makes them especially suitable for textureless objects. These methods learn a built-in occlusion handling from predetermined occlusion patterns, which are not always able to model the real case. Besides, the input of random forest is mixed with more and more outliers as the occlusion deepens. In this paper, we propose an occlusion-aware framework capable of real-time and robust 3D pose tracking from RGB-D images. To this end, the proposed framework is anchored in the random forest-based learning strategy, referred to as RFtracker. We aim to enhance its performance from two aspects: integrated local refinement of random forest on one side, and online rendering based occlusion handling on the other. In order to eliminate the inconsistency between learning and prediction of RFtracker, a local refinement step is embedded to guide random forest towards the optimal regression. Furthermore, we present an online rendering-based occlusion handling to improve the robustness against dynamic occlusion. Meanwhile, a lightweight convolutional neural network-based motion-compensated (CMC) module is designed to cope with fast motion and inevitable physical delay caused by imaging frequency and data transmission. Finally, experiments show that our proposed framework can cope better with heavily-occluded scenes than RFtracker and preserve the real-time performance.

Emission characteristics of offshore fishing ships in the Yellow Bo Sea, China.

Maritime transport has been playing a decisive role in global trade. Its contribution to the air pollution of the sea and coastal areas has been widely recognized. The air pollutant emission inventories of several harbors in China have already been established. However, the emission factors of local ships have not been addressed comprehensively, and thus are lacking from the emission inventories. In this study, on-board emission tests of eight diesel-powered offshore fishing ships were conducted near the coastal region of the northern Yellow Bo Sea fishing ground of Dalian, China. Results show that large amounts of fine particles (<0.5µm, 90%) were found in maneuvering mode, which were about five times higher than those during cruise mode. Emission rates as well as emission factors based on both distance and fuel were determined during the cruise and maneuvering modes (including departure and arrival). Average emission rates and distance-based emission factors of CO, HC and PM were much higher during the maneuvering mode as compared with the cruise mode. However, the average emission rate of Nitrous Oxide (NOx) was higher during the cruise mode as compared with the maneuvering modes. On the contrary, the average distance-based emission factors of NOx were lower during the cruise mode relative to the maneuvering mode due to the low sailing speed of the latter.

Chlorogenic acid protects against cholestatic liver injury in rats.

The aim of this study was to investigate the protective effect of chlorogenic acid (CA) on liver injury caused by bile duct ligation (BDL), as well as the potential mechanism. Permanent bile duct ligation induced liver injury was evaluated by liver index, liver function and pathological observation. Oral administration of CA for 3 weeks markedly attenuated liver swelling and fibrosis. Blood biochemistry results revealed that CA decreased alanine transaminase, aspartate aminotransferase, alkaline phosphatase, total bilirubin, direct bilirubin and total bile acid. PCR analysis indicated that collagen I, collagen III, transforming growth factor and vascular endothelial growth factor mRNA were increased markedly by BDL treatment but these increases were suppressed by CA. Additionally, CA effectively alleviated the expression of α-smooth muscle actin induced by BDL. Taken together, our data indicate that CA can efficiently inhibit BDL-induced liver injury in rats, which is a candidate drug for preventing liver injury against cholestasis.

Vehicular volatile organic compounds losses due to refueling and diurnal process in China: 2010-2050.

Volatile organic compounds (VOCs) are crucial to control air pollution in major Chinese cities since VOCs are the dominant factor influencing ambient ozone level, and also an important precursor of secondary organic aerosols. Vehicular evaporative emissions have become a major and growing source of VOC emissions in China. This study consists of lab tests, technology evaluation, emissions modeling, policy projections and cost-benefit analysis to draw a roadmap for China for controlling vehicular evaporative emissions. The analysis suggests that evaporative VOC emissions from China's light-duty gasoline vehicles were approximately 185,000 ton in 2010 and would peak at 1,200,000 ton in 2040 without control. The current control strategy implemented in China, as shown in business as usual (BAU) scenario, will barely reduce the long-term growth in emissions. Even if Stage II gasoline station vapor control policies were extended national wide (BAU+extended Stage II), there would still be over 400,000 ton fuel loss in 2050. In contrast, the implementation of on-board refueling vapor recovery (ORVR) on new cars could reduce 97.5% of evaporative VOCs by 2050 (BAU+ORVR/BAU+delayed ORVR). According to the results, a combined Stage II and ORVR program is a comprehensive solution that provides both short-term and long-term benefits. The net cost to achieve the optimal total evaporative VOC control is approximately 62 billion CNY in 2025 and 149 billion CNY in 2050.

Characterizing ammonia emission from light-duty gasoline vehicles under the influence of multiple factors and its correlation with conventional pollutants.

Ammonia (NH3), which is a precursor of secondary particulate matter (PM), can be produced through three-way catalyst (TWC) side reactions in light-duty gasoline vehicles (LDGVs), posing a threat to human health and air quality. To explore ammonia emission characteristics, 8 LDGVs and 1 hybrid electric light-duty vehicle (HEV) with various mileages traveled were analyzed with a chassis dynamometer system during regulation driving cycles. The emission factors of the adopted China VI in-use LDGVs were 7.04 ± 2.61 mg/km under cold-start conditions and 4.94 ± 1.69 mg/km under hot-start conditions. With increasing mileage traveled, the total ammonia emissions increased, and the difference between the cold/hot-start results decreased. The emissions of in-use LDGVs with bi-fuel engines were analyzed, and more ammonia was generated in the compressed natural gas (CNG) mode through the hydrocarbon (HC) reforming reaction. The relationship between the emissions of ammonia and conventional pollutants was established. During the initial cold-start phase, a delay in ammonia formation was observed, and the ammonia emissions conformed with the CO and HC emissions after exhaust heating. Vehicle specific power (VSP) analysis revealed that the interval of highest ammonia emissions corresponded to acceleration events at high speeds. For the HEV, the transition from motor to engine drive conditions contributed to ammonia emission occurrence because of the more pronounced cold-start events. The use of HEV technology could introduce additional uncertainties in controlling urban ammonia emissions. Detailed analysis of emission characteristics could provide data support for future research on ammonia emission standards and control strategies for LDGVs.

Assessment of identification performance for high emission heavy-duty diesel vehicles by means of remote sensing.

To improve the accuracy of detecting high NO (nitric oxide) emissions from heavy-duty diesel vehicles (HDDV) by remote sensing (RS), the emissions of one HDDV complied with China V regulation and one HDDV complied with China VI regulation at constant speeds, with and without after-treatment devices, are tested by a portable emission measurement system (PEMS) and RS. The optimized measurement procedures for detecting high NO emissions from China V and China VI HDDVs by RS are summarized. The correlation of RS and PEMS data shows that the ratio of NO to CO2 (carbon dioxide) is a more appropriate RS measurement than NO concentration alone for identifying high emitters, although NO concentrations of 600 ppm and 100 ppm can be used as a basis for distinguishing between China V and China VI HDDVs, respectively. When the NO/CO2 ratio is >200 × 10-4 and 25 × 10-4, identifying China V and China VI HDDV high emitters, respectively, is possible. Additionally considering the vehicle speed can reduce the high emitter identification error rate, and excluding data where vehicle acceleration is less than -0.1 m/s2 can further improve identification accuracy. Four new high-emitter identification methods based on different combinations of measurements are shown to improve identification efficiency with only small increases in identification error. This study provides evidence to support the future development of high-precision RS methodologies for identifying high-emission vehicles.

Chemodiversity of organic nitrogen emissions from light-duty gasoline vehicles is governed by engine displacements and driving speed.

Organic nitrogen emissions from light-duty gasoline vehicles (LDGVs) is believed to play a pivotal role in atmospheric particulate matter (PM) in urban environments. Here, the characterization of organic nitrogen emitted by LDGVs with varying engine displacements at different speed phases was analyzed using a Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) at molecular level. For the LDGV with small engine displacements, the nitrogen-containing organic (CHON) compounds exhibit higher abundance, molecular weight, oxygen content and aromaticity in the extra-high-speed phase. Conversely, for the LDGV with big engine displacements, more CHON compounds with elevated abundance, molecular weight, oxygen content and aromaticity were observed in the low-speed phase. Our study assumed that the formation of CHON compounds emitted from LDGVs is mainly the oxidation reaction during fuel combustion, so the potential precursor-product pairs related to oxidation process were used to study the degree of combustion reaction. The results show that the highest proportion of oxidation occurs during extra-high-speed phase for LDGV with small engine displacements, and during low-speed phase for LDGV with big engine displacements. These results offer a novel perspective for comprehending the mechanism behind vehicle emissions formation and contribute valuable insights for crafting effective air pollution regulations.

Characterizing NOx emissions from diesel trucks with tampered aftertreatment systems and its implications for identifying high emitters.

Reducing the differences between real-world and certificated NOx emission levels is an important element of in-use emission surveillance programs. Therefore, investigating the characteristics of the vehicles which have much higher NOx emissions (i.e., high-emitters) and determining a reasonable cut-off point to identify high-emitters with a low false detection rate is important. In this study, six diesel trucks were tested under different aftertreatment conditions. The results showed that the discrepancies of fuel-specific NOx emissions between vehicles with functioning and tampered selective catalytic reduction (SCR) systems occur mainly from medium- to high-speed modes. This is because the SCR systems were at low conversion efficiencies when the exhaust temperature was low, including cold-start and urban creep conditions. By using binary classification, we selected fuel-specific NOx cut-off points for high-emitters from China V and China VI diesel trucks. The false detection rate of high-emitters can decrease by 33 % and 95 %, if only NOx emissions from medium- to high-speed modes were used for the chosen cut-off points, respectively. This work highlights the importance of in-use emission compliance programs. It also suggests that high-emitters can be more accurately identified at medium- to high-speed modes if using instantaneous emission data.

Impacts on real-world extra cold start emissions: Fuel injection, powertrain, aftertreatment and ambient temperature.

Vehicles emit substantial amounts of pollutants during start periods. Engine starts mainly occur in urban areas, causing serious harm to humans. To investigate the impacts on extra cold start emissions (ECSEs), eleven China 6 vehicles with various control technologies (fuel injection, powertrain, and aftertreatment) were monitored with a portable emission measurement system (PEMS) at different temperatures. For conventional internal combustion engine vehicles (ICEVs), the average ECSEs of CO2 increased by 24%, while the average ECSEs of NOx and particle number (PN) decreased by 38% and 39%, respectively, with air conditioning (AC) on. Gasoline direct injection (GDI) vehicles had 5% lower CO2 ECSEs, but 261% higher NOx ECSEs and 318% higher PN ECSEs than port fuel injection (PFI) vehicles at 23 °C. The average PN ECSEs were significantly reduced by gasoline particle filters (GPFs). The GPF filtration efficiency was higher in GDI than PFI vehicles due to particle size distribution. Hybrid electric vehicles (HEVs) generated excessive PN extra start emissions (ESEs), resulting in a 518% increase compared to ICEVs. The start times of the GDI-engine HEV accounted for 11% of the whole test time, but the proportion of PN ESEs relative to total emissions were 23%. Linear simulation based on the decrease in ECSEs with increasing temperature underestimated the PN ECSEs from PFI and GDI vehicles by 39% and 21%, respectively. For ICEVs, CO ECSEs varied with temperature in a U shape with a minimum at 27 °C; NOx ECSEs decreased as ambient temperature increased; PFI vehicles generated more PN ECSEs at 32 °C than GDI vehicles, stressing the significance of ECSEs at high temperature. These results are useful for improving emission models and assessing air pollution exposure in urban aeras.

[Emission Factors of Carbonaceous Aerosol and Stable Carbon Isotope for In-use Vehicles].

Vehicle exhaust is an important anthropogenic source of atmospheric carbonaceous aerosols; of which, the emission factors and stable carbon isotope composition are important basic data. In-use motor vehicles of different types were selected to conduct dynamometer tests using different test cycles and under cold/hot start conditions. The exhaust of each test stage was collected to analyze the carbonaceous components and stable carbon isotopes and to discuss the influencing factors. The total carbon emission factors follow the order:heavy-duty diesel vehicles>light-duty diesel vehicles>light-duty gasoline vehicles. Although the emission factors of light-duty natural gas vehicles were very low at the low- and medium-speed stages, they were similar to those of heavy-duty diesel vehicles at the high-speed stage. The emission factors of cold start were higher than those of hot start, and the emission factors of the NEDC test cycle were lower than those of WLTC (which should be related to the driving speed). The emission factors of organic carbon (OC) of gasoline and natural gas vehicles were much higher than those of elemental carbon (EC) in every test stage. The emission factors of OC and EC of diesel vehicles were similar. The OC/EC of all types of vehicles increased with the increase in driving speed. Stable carbon isotopes in EC were higher than those in OC. The stable carbon isotope in different vehicles follow the order:light-duty gasoline vehicles

Exhaust aftertreatment device-derived ammonia emissions from conventional and hybrid light-duty gasoline vehicles over different driving cycles.

Ammonia emissions from motor vehicles have great effect on air pollution and human health in urban areas. Recently, many countries have focus on ammonia emission measurement and control technologies for light-duty gasoline vehicles (LDGVs). To analyze ammonia emission characteristics, three conventional LDGVs and one hybrid electric light-duty vehicle (HEV) were evaluated over different driving cycles. The average ammonia emission factor at 23℃ was 4.5 ± 1.6 mg/km over Worldwide harmonized light vehicles test cycle (WLTC). Most ammonia emissions mainly concentrated in low and medium speed sections at cold-start stage, which were related to rich burn conditions. The increasing ambient temperatures led to the decrease of ammonia emissions, but high load caused by extremely elevated ambient temperature led to obvious ammonia emissions. The ammonia formation is also related to three-way catalytic converter (TWC) temperatures, and underfloor TWC catalyst could eliminate ammonia partly. The ammonia emission from HEV, which are significant less than LDGV, corresponded to the engine working state. The large temperature difference in the catalysts caused by power source shifts were the main reason. Exploring the effects of various factors on the ammonia emission is beneficial for revealing the instinct formation conditions, providing theoretical support for the future regulations.

The synergistic effect on production of lignin-modifying enzymes through submerged co-cultivation of Phlebia radiata, Dichomitus squalens and Ceriporiopsis subvermispora using agricultural residues.

The lignin-modifying enzymes (LMEs) play an important role in decomposition of agricultural residues, which contain a certain amount of lignin. In this study, the production of LMEs by three co-cultivated combinations of Phlebia radiata, Dichomitus squalens and Ceriporiopsis subvermispora and the respective monocultures was comparatively investigated. Laccase and manganese peroxidases (MnP) were significantly promoted in the co-culture of P. radiata and D. squalens, and corncob was verified to be beneficial for laccase and MnP production. Moreover, laccase production by co-culture of P. radiata and D. squalens with high ratio of glucose to nitrogen was higher than low ratio under carbon- and nitrogen-meager conditions. New laccase isoenzymes measured by Native-PAGE were stimulated by co-cultured P. radiata with D. squalens or C. subvermispora, respectively, growing in the defined medium containing corncob, but the expression of laccase was greatly restrained by the co-culturing of D. squalens with C. subvermispora. This study showed that the synergistic and depressing effects of co-cultivation of P. radiata, D. squalens and C. subvermispora on LMEs were species specific.

Evaluation of real-world emissions of China V heavy-duty vehicles fueled by diesel, CNG and LNG on various road types.

Natural gas has been widely considered as an alternative fuel to diesel on heavy-duty vehicles (HDVs). To evaluate the real-world emissions, 19 diesel HDVs, 3 CNG HDVs and 9 LNG HDVs were tested using portable emission measurement system on urban, suburban and freeway roads . The results show that average emission rates of CO, HC and NOx from diesel, CNG and LNG HDVs tend to rise with the increasing of VSP. Due to different emission control strategies and complicated driving cycle, NOx reduction rates of real-world emission factors are lower than those of the corresponding limits from China II to China V diesel HDVs. CO and NOx emission factors from all tested HDVs on urban road are generally higher than those on suburban road in the same velocity intervals, which means driving behaviors on different road types have great influence on emission factors in the same velocity intervals. NOx emission factors from LNG HDVs are higher than those from diesel HDVs, indicating that using China V LNG HDVs instead of China V diesel HDVs could not be an ideal alternative for freeway transportation. As CO and NOx comprehensive emission factors from China V CNG HDVs are higher than those from China V diesel, even higher than China IV diesel HDVs, China V CNG HDVs are unable to be considered as cleaner vehicles when compared to China V diesel HDVs in the study. It is noticeable that HC emission factors from CNG and LNG HDVs are extremely higher compare with diesel HDVS. NO2 emission factors from LNG HDVs are 2.14-9.19 and 4.74-8.53 times than those from diesel and CNG HDVs with various road types. Our study can provide development road map for different fuel types of HDVs and the reference for new emission legislation of HDVs.

On-road pollutant emission and fuel consumption characteristics of buses in Beijing.

On-road emission and fuel consumption (FC) levels for Euro III and IV buses fueled on diesel and compressed natural gas (CNG) were compared, and emission and FC characteristics of buses were analyzed based on approximately 28,700 groups of instantaneous data obtained in Beijing using a portable emissions measurement system (PEMS). The experimental results revealed that NOx and PM emissions from CNG buses were decreased by 72.0% and 82.3% respectively, compared with Euro IV diesel buses. Similarly, these emissions were reduced by 75.2% and 96.3% respectively, compared with Euro III diesel buses. In addition, CO2, CO, HC, NOx, PM emissions and FC of Euro IV diesel buses were reduced by 26.4%, 75.2%, 73.6%, 11.4%, 79.1%, and 26.0%, respectively, relative to Euro III diesel buses. The CO2, CO, HC, NOx, PM emissions and FC factors all decreased with bus speed increased, while increased as bus acceleration increased. At the same time, the emission/FC rates as well as the emission/FC factors exhibited a strong positive correlation with the vehicle specific power (VSP). They all were the lowest when VSP < 0, and then rapidly increased as VSP increased. Furthermore, both the emission/FC rates and emission/FC factors were the highest at accelerations, higher at cruise speeds, and the lowest at decelerations for non-idling buses. These results can provide a base reference to further estimate bus emission and FC inventories in Beijing.

Study on the real-world emissions of rural vehicles on different road types.

To better understand the real-world emissions of rural vehicles (RVs) in China, 8 China II RVs and 18 China III RVs were tested on a provincial road, rural road and farm road using a portable emissions measurement system. The results are illustrated in contour maps of the speed, acceleration and emission rates and show that CO, HC, NOx and PM emissions differ for the three road types; however, the peak emission points all occur on the provincial road. The average CO, HC, NOx and PM emission factors based on distance for the China II RVs are 9.21, 4.05, 1.68 and 2.58 times higher, respectively, than those of the China III RVs. However, the average NOx emission factors of the China II and III RVs are 2.21 and 1.65 times higher than the corresponding recommended values of national emission inventory guideline, resulting in underestimation of overall RVs' emissions. Distance-based emission factors of four pollutants ranked from high to low are farm road > rural road > provincial road. In contrast to the average emission factors of the China II RVs on the three road types, those of the China III RVs are significantly less in terms of distance and fuel consumption. The results of other researchers differ from those in this study: the CO emission factor of the China II RVs is 2.12 times higher than that of the China II light-duty diesel vehicles (LDDVs). The PM emission factor of the China III RVs is 2.67 times higher than that of the China III LDDVs. The NOx emission factors of the China II and III RVs are similar to those of the corresponding China II and III LDDVs. Our research increases the understanding of real-world emissions of RVs and can act as great references for policy makers developing RV emission baselines.

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.