高光谱成像
化学
化学成像
遥感
高分辨率
图像分辨率
时间分辨率
光谱成像
全光谱成像
模式识别(心理学)
人工智能
计算机科学
量子力学
物理
地质学
作者
Yikai Li,Chengzhi Xing,Jian Chen,Peiyuan Jiao,Chao Liu,Jiale Fang,Cheng Liu
标识
DOI:10.1021/acs.analchem.5c00837
摘要
Volatile organic compounds (VOCs) and their secondary pollutants pose significant risks to both the environment and human health. In response to air pollution control policies, the emissions of conventional pollutants, such as NO2 and SO2, have been preliminarily controlled. As a result, the reduction of VOC emissions has become a key measure for further improving air quality. Industrial activities are the primary anthropogenic source of VOCs, highlighting the urgent need for effective methods to detect VOC plume concentrations and monitor their dispersion and transport. This study proposes a hyperspectral rapid imaging system (HRIS), which achieves innovative advancements in noise removal, signal enhancement, and chromatic aberration correction. These breakthroughs enable, for the first time, high spatiotemporal resolution and synchronous observation of multiple VOC components, with final imaging results available within minutes. In two experimental setups, the system successfully measured the concentrations and emission fluxes of formaldehyde (HCHO), nitrobenzene (C6H5NO2), benzoic acid (CH3C6H3O2), nitrogen dioxide (NO2), and sulfur dioxide (SO2), with the highest emission flux recorded at 0.45 ± 0.13 kg/h. The application of HRIS facilitates the development of dynamic VOC emission inventories, providing critical data to support the design of future emission reduction strategies.
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