基于智能电网大数据的工业企业大气污染排放特征研究

本文尝试构建基于智能电网大数据的工业企业污染排放预测方法。通过分析上海大中型工业企业用电量与工业总产出、工业总产出与主要污染物直接排放量之间的关联关系,本文建立了工业企业基于用电量的直接污染排放清单估算方法。利用此估算方法,可在实时的智能电网大数据基础上估算工业企业直接污染排放量,服务于大气污染的实时预警和预测。本文研究表明,这种清单估算方法可直接应用于工业企业污染的实时防控,既可服务于政府大气污染监测、应急机制启动时防控对象的选择,也可服务于未来的污染物排放权实时交易市场的供需分析等,是大数据在污染防治领域应用的可行路径。

Emission Characteristics of Industrial Air Pollution by Using Smart-Grid Big Data

This paper tries to develop a new method to forecast the industrial pollutant emission based on smart-grid big data. By analyzing the correlation between electricity use, industrial output and main environmental pollutants, this paper built up an accounting method for estimating the direct pollutants emission. This method can support the estimation of industrial direct pollutant emission basd on real-time smart-grid big data and serve the precautionary management and pollution forecast. The study indicates that such method can be applied to manage the real-time industrial pollution by filtering the regulated targets in extremely polluted days. It can also support the real-time trading of pollution rights in future cap and trading markets. This method proved that energy big data can be utilized in air pollution control effectively.