高级检索

    基于无人机多参数监测的湿垃圾处理厂污染气体分布及环境因子研究

    Pollutant Gas Distribution and Environmental Factors in a Wet Waste Treatment Plant Based on Multi-Parameter UAV Monitoring

    • 摘要: 湿垃圾处理厂在运行过程中释放的甲烷(CH4)、硫化氢(H2S)、氨气(NH3)及挥发性有机物(VOCs)等污染物,对周边环境与人体健康构成威胁。为了解决传统监测方法空间覆盖、时效性及安全性不足的问题,基于无人机搭载多参数传感器,构建了一套气体监测系统,并在上海某湿垃圾处理厂开展了实地监测。本研究分析了不同功能区污染气体的水平分布异质性、垂直浓度梯度及与环境因子的相关性。结果显示,在全厂范围内CH4浓度整体显著高于其他气体,达到1 860 μg/m3,是主要的环境污染压力来源;H2S与NH3浓度高值区与餐余车间、厨余车间、干化车间和卸料大厅等处理工艺环节密切相关,呈现出明显的区域差异和点源性排放特征;尽管VOCs浓度相对较低,但其成分复杂,具有潜在环境风险。垂直剖面监测表明,CH4在各高度均维持高浓度(1 800~1 900 μg/m3),而NH3主要在设施的上层空间聚集,H2S浓度随高度缓慢上升,VOCs则在垂直方向上分布相对均匀。污染物的扩散趋势可能导致NH3加剧恶臭污染,影响空气质量并危害居民健康;VOCs可能增强臭氧生成和二次有机气溶胶形成,加剧光化学烟雾问题。相关性分析结果表明,湿度与气压是影响气体释放与扩散的关键因子,特别是湿度对NH3与VOCs的调节作用最为显著。本研究验证了无人机多参数监测在复杂场景下对污染气体监测方面的有效性,为湿垃圾处理厂污染气体的精准监测、环境风险评估及差异化管控策略的制定提供科学依据。

       

      Abstract: Emissions of atmospheric pollutants such as methane (CH4), hydrogen sulfide (H2S), ammonia (NH3), and volatile organic compounds (VOCs) from wet waste treatment plants pose serious environmental and health risks. Conventional monitoring methods, which rely on fixed stations or manual sampling, often face challenges such as limited spatial coverage, delayed data collection, and operational safety hazards. To address these limitations, this study developed a gas monitoring system utilizing a multi-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, the catering waste workshop, the drying workshop, and the 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); 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 intensify 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 these factors, 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. Overall, 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.

       

    /

    返回文章
    返回