Nitrated aromatic compounds (NACs) are critical toxic components of PM2.5, and accurately identifying their sources is vital for effective urban air quality improvement. However, the lack of real-world emission data for construction machinery has introduced significant uncertainties into NACs source apportionment and emission inventories, particularly in urban areas where such machinery is widely used. Here, we characterized NACs, including nitrated polycyclic aromatic hydrocarbons (NPAHs) and nitrophenols (NPs), emissions from forklifts and excavators at construction sites in China. It is found that construction machinery emitted significantly higher NACs levels compared to on-road vehicles, with average NPAHs and NPs emission factors of 340.1 and 562.0 μg kg−1 fuel for forklifts and 459.0 and 1381.1 μg kg−1 fuel for excavators. Emissions during working modes were 1.1–1.6 times higher than during idling for forklifts and excavators. A key finding was the dominance of 5-nitroacenaphthene and 1-nitropyrene, which contrasts sharply with the observed emissions in other sources. We believed that combining the 5-nitroacenaphthene and 1-nitropyrene during the source apportionment using the receptor model would make it possible to separate the contributions of construction machinery. Notably, the light absorption of 45 NACs from both forklifts and excavators collectively accounted for approximately 30% of the total methanol-soluble brown carbon—a significantly higher contribution ratio compared to other emission sources. Furthermore, while construction machinery accounted for less than 5% of urban vehicle numbers, its toxic equivalent quotients can reach 4 to 6 times that of on-road vehicles with the nonnegligible potential toxicity. These results highlight the urgent need for stricter emission controls on construction machinery to reduce NACs-related adverse environmental effects in urban environments. Our findings provide valuable insights for constructing NACs emission inventories and refining NACs source apportionment methods in urban atmospheric studies.
Zhang et al. (Sun,) studied this question.