Investigation of Emission Inventory for Non-Road Mobile Machinery in Shandong Province: An Analysis Grounded in Real-World Activity Levels

Abstract

In tandem with the advancement of urban intelligent technology, the construction of remote monitoring platforms and databases for non-road mobile machinery is gradually improving in various provinces and cities. Employing the remote monitoring platform for non-road mobile machinery enables a detailed big data analysis of the actual operational state of the machinery. This method yields precise data on the activity levels of various machinery types. Importantly, it addresses the issue of reduced accuracy in emission inventories, which often arises from the conventional practice of using standard recommended values from the Guide to determine machinery activity levels during the compilation of non-road mobile machinery emission inventories. Based on the remote monitoring and management system of non-road mobile machinery, the actual value of the activity level of non-road mobile machinery was obtained, and the emission inventory of non-road mobile machinery in Shandong Province was established. The emission levels of PM, HC, NOx, and CO from main non-road mobile machinery, including forklifts, excavators, loaders, off-road trucks, and road rollers, were measured. The findings indicate that the operational activity levels of non-road mobile machinery in Shandong Province typically exceeded the guideline’s recommended values. Among them, the annual use time of port terminal ground handling equipment was the longest, with an average annual working time of 4321.5 h per equipment, more than six times the recommended value. Among all types of non-road mobile machinery, loader emissions accounted for the highest proportion, reaching 43.13% of the total emissions of various pollutants. With the tightening of the national standard for non-road mobile machinery from Stage II to Stage III, a significant reduction in actual mechanical emissions was observed, primarily manifested as a 91% decrease in NOx emissions. Based on the data from the remote monitoring platform, a new method for compiling the emission inventory of non-road mobile machinery is proposed in this paper. The calculated emission inventory can reflect more real emission situations and provide a reference and basis for emission control and sustainable emission reduction policy measures for non-road mobile machinery.