The environmental problem of volatile organic compounds (VOCs) pollution in industrial parks is becoming increasingly serious. Rapid and large-scale monitoring of the overall pollution in the area and identification of pollution sources are keys to efficient pollution control. However, traditional detection methods cannot achieve rapid detection, let alone accurately pinpoint the source of pollution. In this study, an online VOC mobile monitoring system based on time-of-flight mass spectrometry was used to monitor an industrial park and successfully obtain the VOC distribution image of the industrial park. Two polluted areas (A and B) were pinpointed by examining the image, and the ΣVOCs concentration ranges were 74–421 μg/m³ and 51–577 μg/m³. Eight abnormal sites with concentration peaks exceeding the standard were found, and the pollution source of one abnormal site was analyzed. The correlation between the pollution source factor of the abnormal site and the emission enterprise was as high as 0.91, and the pollution source of the abnormal site was identified. To explore whether it was affected by other surrounding enterprises, a positive matrix factorization model was further used to analyze the receptor data of abnormal site. Three pollution sources were analyzed and compared with enterprise emission sources. Combined with the location of the abnormal site and emission sources, we found that the abnormal sites were not only affected by the emission sources of surrounding enterprises but also by the emission sources of enterprises in the northeast. This approach offers rapid and large-scale monitoring of the overall pollution in an area and quickly pinpointed the location of the pollution sources. This method solves the shortcomings of traditional methods that cannot identify the location of pollution source and provides an effective technical means for the rapid detection of the pollution distribution in industrial parks for efficient screening of pollution sources.

中文翻译：

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使用在线质谱法对挥发性有机化合物进行车载移动监测：在工业园区的应用

工业园区挥发性有机化合物（VOCs）污染的环境问题日益严重。对区域内的整体污染情况进行快速、大规模的监测和查明污染源是有效控制污染的关键。然而，传统的检测方法无法实现快速检测，更不能准确定位污染源。本研究采用基于飞行时间质谱的在线VOC移动监测系统对某工业园区进行监测，成功获取了工业园区VOC分布图像。通过检查图像确定了两个污染区域（A和B），ΣVOCs浓度范围为74-421 μg/m ³和51-577 μg/m ³. 共发现8个浓度峰值超标的异常点，并对1个异常点的污染源进行了分析。异常场地污染源因子与排放企业的相关系数高达0.91，确定了异常场地的污染源。为探究是否受到周边其他企业的影响，进一步采用正矩阵分解模型对异常部位的受体数据进行分析。对三种污染源进行了分析，并与企业排放源进行了比较。结合异常站点的位置和排放源，我们发现异常站点不仅受到周边企业排放源的影响，还受到东北地区企业排放源的影响。这种方法可以快速、大规模地监测一个地区的整体污染情况，并快速确定污染源的位置。该方法解决了传统方法无法识别污染源位置的缺点，为工业园区污染分布的快速检测、高效筛查污染源提供了有效的技术手段。