The rapid detection of petroleum hydrocarbons and organic pesticides is an important prerequisite for precise soil management. It is also a guarantee for soil quality, environmental safety, and human health. However, the current rapid detection methods are prone to sample matrix interference, complex development processes, short lifespan, and low detection accuracy. Moreover, they face difficulties in achieving simultaneous detection of petroleum hydrocarbons and organic pesticides. In this paper, we developed an electronic nose system for the simultaneous detection of petroleum hydrocarbons and organic pesticides in soil based on gas technology, which includes a sampling module and recognition model. The developed sampling module can simultaneously acquire the odor signals of petroleum hydrocarbons and organic pesticides in soil. The established recognition model can quickly distinguish between healthy soil, soil contaminated by petroleum hydrocarbons, and soil contaminated by organic pesticides. It can also achieve specific recognition of pesticide types and petroleum types. The performance of the developed electronic nose system was verified for real soil, petroleum products, and organic pesticides. The experiment shows that the developed electronic nose system has an accuracy of 100% for three tasks: soil conditions identification, pesticide types identification, and petroleum types identification.

This study examines the stability of the Huangyukou landslide in Yanqing District, Beijing, under varying rainfall conditions, focusing on the effects of rainfall infiltration and surface runoff on slope stability. Using a combination of field surveys, geophysical methods, drone photogrammetry, and laboratory testing, a high-precision 2D and 3D numerical model was developed. A hydrological-soil-structure coupling model was employed to simulate rainfall-induced infiltration and runoff processes, revealing that increased saturation and pore water pressure significantly reduce shear strength, enhancing the risk of slope failure. Stability analysis, using a reduction factor method, yielded stability coefficients of 1.06 and 1.04 for 20-year and 100-year return period rainfall scenarios, respectively. The results highlight the critical role of rainfall in destabilizing the upper layers of dolomite and shale, with significant deformation observed in the middle and rear slope sections. This research provides a comprehensive framework for assessing landslide risk under extreme rainfall events, offering practical implications for risk mitigation in similar geological contexts.