Abstract:The emission of atmospheric pollutants such as methane (CH4), hydrogen sulfide (H2S), ammonia (NH3), and volatile organic compounds (VOCs) from wet waste treatment plants poses serious environmental and health risks. Conventional monitoring methods, which rely on fixed stations or manual sampling, often face various challenges regarding limited spatial coverage, delayed data collection, and operational safety hazards. To address these limitations, this study developed a gas monitoring system utilizing a mutli-parameter sensor integrated with an unmanned aerial vehicle (UAV). Field monitoring was conducted at a wet waste treatment plant in Shanghai to assess pollutant distribution, vertical concentration gradients, and correlations with environmental factors across different functional areas. The results revealed that CH4 concentrations were significantly higher than those of other gases, reaching up to 1860 μg/m3 throughout the plant, making CH4 the primary contributor to the total emission load. In contrast, H2S and NH3 exhibited distinct point-source characteristics, with high concentrations closely associated with specific processing stages, including the kitchen waste workshop, catering waste workshop, drying workshop, and unloading hall. Although VOC concentrations were relatively low, their complex composition presented potential environmental risks. Vertical profile monitoring showed that CH4 maintained high concentrations at all heights (1800 – 1900 μg/m3) and NH3 tended to accumulate in the upper sections of the facility, while H2S concentrations gradually increased with height. Conversely, VOCs exhibited a relatively homogeneous vertical distribution across the plant. These diffusion trends suggest that NH3 could intensity odor pollution, while VOCs may enhance ozone formation and the generation of secondary organic aerosols. Correlation analysis indicated that humidity and air pressure were key environmental factors influencing the release and dispersion of these gases. Among them, humidity demonstrated the most significant influence on NH3 and VOC levels, suggesting its critical role in determining their atmospheric residence time and transport behavior. This study demonstrates the effectiveness of UAV-based sensing for detecting pollutant gases in complex industrial settings. By enabling precise monitoring and real-time data acquisition, this approach improves environmental risk assessment and supports the creation of targeted pollution control strategies for wet waste treatment plants. Our findings confirm that UAV-mounted systems provide significant advantages over conventional methods, specifically in terms of expanded spatial coverage and enhanced operational safety. Consequently, this study highlights the transformative potential of UAV technology in environmental monitoring, offering critical insights for air quality management and evidence-based policymaking in waste treatment sectors. Close-