基于电力大数据的VOCs企业污染防治综合预警管控分析方法

VOCs Enterprise Pollution Prevention and Control Comprehensive Early Warning Analysis Method Based on Power Big Data

挥发性有机物是大气污染物重要组成部分,严重威胁环境和人类健康。随着VOCs问题的日趋突出,如何快速、低成本地检测企业VOCs排放情况已成为大家关注的重点。本文基于用电大数据,构建企业污染排放用电异常判断模型和企业停减产计划执行监测模型,对企业生产过程中的产污、治污用电全过程进行监测和预警,实现VOCs排放快速精准监测、预警和管控。经现场检验,判断准确率为100%,目前该模型已在VOCs排放检测领域进行部署应用。对助力政府部门快速精准管控企业VOCs排放,提升城市空气质量具有很大的意义,还可免除企业购置VOCs在线检测装置成本,具有巨大的应用前景和广阔的市场空间。

Volatile organic compounds(VOCs),an important component of air pollutants,pose a serious threat to the environment and human health.With the increasingly prominent VOCs problems,how to quickly and cheaply detect enterprise VOCs emissions has become the focus of attention.Based on the big data of electricity consumption,this paper constructs the judgment model of abnormal power consumption of enterprise pollution emission and the implementation monitoring model of enterprise shutdown and production reduction plan,monitors and warns the whole process of pollution production,pollution control and electricity consumption in the production process of enterprise,and realizes the rapid and accurate monitoring,warning and control of VOCs emission.After field inspection,the judgment accuracy is 100%.At present,the model has been deployed and applied in the field of VOCs emission detection.It has great significance to help government departments quickly and accurately control enterprise VOCs emissions and improve urban air quality.It can also exempt enterprises from the cost of purchasing VOCs online detection devices,which has huge application prospects and broad market space.