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Emissions of agricultural machines during tillage processes played an important role in severe seasonal pollution events in agricultural areas in China and cannot be ignored. In this study, the CO, NOX, HC and PM2.5 emissions of agricultural machines during real-world tillage processes were tested using a portable emission measurement system (PEMS), and their fuel-based and tillage area-based emission factors were calculated. The CO, NOX, HC and PM2.5 emissions were influenced by emission standards, engine rated power, tillage processes and crops. Only the CO, HC and PM2.5 fuel-based emission factors were reduced from China 0 to China II. For China III agricultural machines, the fuel-based emission factors were higher during plowing and tilling than during harvesting. The tillage area-based CO, NOX, HC and PM2.5 emission factors of corn tillage process were 11.85 ± 8.30, 53.21 ± 48.80, 3.46 ± 3.14 and 1.64 ± 1.33 kg/km2, respectively. The tillage area-based CO, NOX, HC and PM2.5 emission factors of wheat tillage process were 19.69 ± 21.50, 79.98 ± 63.22, 3.90 ± 2.96 and 1.61 ± 2.43 kg/km2, respectively. The tillage area-based emission factors of China III agricultural machines during plowing and tilling were higher than those during harvesting. The fuel consumption per unit tillage area can be used to provide a reference for the interconversion of the two emission factors in future studies. By comparing the fuel-based emission factors in this study with those in the Guidelines and other studies, we observed that the CO, HC and PM2.5 emissions of agricultural machines with corresponding emission standards may be overestimated and the NOX emissions may be underestimated in areas where wheat and corn are mainly grown. Moreover, the pollutant emissions of agricultural machines were regionally different. These results could help elucidate the pollution contribution of agricultural machines in China.

A series of lockdown measures in response to the Corona Virus Disease 2019 (COVID-19) outbreak resulted in a drop in anthropogenic emissions and changes in concentrations of PM2.5 and O3. Backward trajectories analysis, cluster analysis, potential source contribution function (PSCF) and concentration weighted trajectory (CWT) technologies were conducted to reveal the characteristics and potential source areas of pollutants in Beijing before the COVID-19 outbreak (BCO period), during the outbreak (COB period) and after the outbreak (ACO period), as well as the contemporaneous period in 2019 (CCO period), which is critical for exploring the efficient control measures and making policy. The results indicated that despite the significant reduction in anthropogenic emissions during the epidemic, the PM2.5 concentrations increased by 1.0% caused by unfavorable meteorological conditions. O3 concentrations increased by 174.8% compared to that during the BCO period due to the increased temperature and inappropriate precursor reduction ratios. A considerable decrease of NO3- in PM2.5 was observed under the influence of significant reductions in vehicle emissions during the lockdown. The cluster analysis revealed that short-range transport played a significant role in the accumulation of local PM2.5 pollution, while long-range northwest airflows contributed more to O3 accumulation, and weakened as the season changed. The PSCF and CWT analysis demonstrated that potential source areas of PM2.5 were mostly located in the central and southern Hebei, the southwestern Shandong in the CCO period, and expanded to central Inner Mongolia and northern Shanxi in the COB period. These areas were highly compatible with the high emission areas of the emission inventory statistics. After the outbreak, the source areas of O3 were centered in the Beijing-Tianjin-Hebei region and Shandong province, with a radial dispersion in all directions, while they were distributed in the central Mongolia and Inner Mongolia during the other periods.

The C4.5 algorithm has three shortcomings: the wide range of candidate segmentation threshold sequences for continuous attributes, the comprehensive influence of different attributes and local subsets under the same attribute, and the inter-attribute redundancy. When dealing with continuous attributes, sampling and threshold supplement processing near the transition boundary of the attribute interval corresponding to the adjacent different categories are performed for narrowing the range of candate segmentation threshold sequences. By adding standardizing Euclidean distance of the attribute global and local factors to represent attribute weight, the calculation of C4.5 information gain is otpimized. And averaging Gini index of other attributes and adding correction factor, the influence of redundancy between attributes is greatly decreased. The overall average improvement range of the base classifier and the bagging integration classifier is 0.6%~2.1% and 0.7% ~ 2.7%, respectively, which shows that this integration model can improve the classification accuracy and also validate its feasibility and reliability.

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. [ABSTRACT FROM AUTHOR]

To alleviate air pollution and lessen the petroleum demand from the motor vehicle sector in China, natural gas vehicles (NGVs) have been rapidly developed over the last several years. However, the understanding of the real-world emissions of NGVs is very limited. In this study, the emissions from 20 compressed-natural-gas-fueled bi-fuel taxis were measured using a portable emission measurement system (PEMS) under actual driving conditions in Yichang, China. The emission characteristics of the tested vehicles were analyzed, revealing that the average CO2, CO, HC and NOx emissions from the tested compressed-natural-gas (CNG) taxis under urban driving conditions were 1.6, 4.0, 2.0 and 0.98 times those under highway road conditions, respectively. The CO, HC and NOx emissions from Euro 3 CNG vehicles were approximately 40%, 55% and 44% lower than those from Euro 2 vehicles, respectively. Compared with the values for light-duty gasoline vehicles reported in the literature, the CO2 and CO emissions from the tested CNG taxis were clearly lower; however, significant increases in the HC and NOx emissions were observed. Finally, we normalized the emissions under the actual driving cycles of the entire test route to the New European Driving Cycle (NEDC)-based emissions using a VSP modes method developed by North Carolina State University. The simulated NEDC-based CO emissions from the tested CNG taxis were better than the corresponding emissions standards, whereas the simulated NEDC-based HC and NOx emissions greatly exceeded the standards. Thus, more attention should be paid to the emissions from CNG vehicles. As for the CNG-fueled bi-fuel taxis currently in use, the department of environmental protection should strengthen their inspection and supervision to reduce the emissions from these vehicles. The results of this study will be helpful in understanding and controlling emissions from CNG-fueled bi-fuel vehicles in China. [ABSTRACT FROM AUTHOR]