石油化工安全环保技术 ›› 2024, Vol. 40 ›› Issue (4): 63-66.

• 工业污染防治与生态保护 • 上一篇    

石油化工生产过程中污染物排放自行监测技术

慕典伟   

  1. 中国石油天然气股份有限公司长庆油田分公司,甘肃 庆阳 745700
  • 收稿日期:2023-02-15 接受日期:2024-07-15 出版日期:2024-08-20 发布日期:2024-08-28
  • 作者简介:慕典伟,男,2011 年毕业于西安石油大学工商管理专业,主要从事油田化验室分析与环境保护管理工作, 工程师。电话:0874-78454121,E-mail:ggffddaa123456789@yeah.net

Self-Monitoring Technology of Pollutant Discharge in Petrochemical Production Process

Mu Dianwei   

  1. PetroChina Changqing Oilfield Company, Qingyang, Gansu, 745700
  • Received:2023-02-15 Accepted:2024-07-15 Online:2024-08-20 Published:2024-08-28

摘要: 监测石油化工生产过程中污染物排放情况的过程中,由于需要监测的污染物种类较多,导致监测结果的准确性较低。为此提出石油化工生产过程中污染物排放自行监测技术研究。设计了包含HT6501 中央控制器和ATT7022E 计量芯片的智能数据采集装置,利用对相邻时间窗内石油化工生产设备的状态参数差值进行计算,获取对应的生产状态。再结合石油化工生产的产品产出量与能耗之间的关系计算产品产出情况,利用产物与污染物产出量以及企业对污染物的处理能力,计算得到不同产物最终的排放情况。在测试结果中,设计方法对于大气污染物和水污染物的排放量监测结果与实际值的误差稳定在0.3 mg/h 以内。

关键词: 石油化工生产, 污染物排放, 自行监测, 智能数据采集, 状态参数差值, 产品产出量

Abstract: In the process of monitoring the pollutant discharge in the petrochemical production process, the accuracy of the monitoring results is low due to the large number of pollutants to be monitored. Therefore, the self-monitoring technology of pollutant discharge in the petrochemical production process is proposed. An intelligent data acquisition device including HT6501 central controller and ATT7022E metering chip is designed to calculate the difference of the status parameters of petrochemical production equipment in the adjacent time window to obtain the corresponding production status. Then the product output is calculated by combining the relationship between the output of petrochemical products and energy consumption. And the final emissions of different products are calculated by using the output of products and pollutants and the enterprise's capacity to treat pollutants. In the test results, the error between the monitoring results of the design method for the emission of air pollutants and water pollutants and the actual value is stable within 0.3mg/h.

Key words: petrochemical production, pollutant emission, self-monitoring, intelligent data acquisition, status parameter difference, product output