火电企业大气污染物排放量核算方法研究

Calculation Method and Application of Air Pollutant Emissions in Thermal Power Companies

大气污染物严重破坏生态环境及人类身心健康,但因其易扩散、难检测,导致难以快速核算企业真实排放量,妨碍了行政干预和市场手段的污染治理工作。针对位居工业大气污染物排放量之首的火电行业,从企业角度出发,打破对末端监测数据的依赖,构建基于神经网络修正灰色预测的大气污染物排放量核算模型,利用该模型对某火电企业2019-2021年二氧化硫、氮氧化物、烟尘排放量进行预测,预测误差均在1%以内,具有较高的预测精度,验证了模型的有效性和准确性,为火电企业大气污染物排放量快速核算提供了新方法。

Air pollutants seriously damage the ecological environment and human physical and mental health,however,due to their easy diffusion and difficult detection,it is difficult to quickly calculate the real emissions of companies,which hinders the pollution control work by administrative intervention and market means.Aiming at the thermal power industry,which ranks first in industrial air pollutant emissions,this paper breaks the dependence on terminal monitoring data,improving the whole process analysis from input to output,and to build an air pollutant emission accounting model based on neural network modified grey prediction.The model was used to predict the emissions of sulfur dioxide,nitrogen oxides and smoke of a thermal power company from 2019-2021.The prediction errors were all within 1%,which has a high prediction accuracy,verifies the validity and accuracy of the model,and provides a new method for rapid accounting of air pollutant emissions of thermal power enterprises.