| 摘要: |
| 工业企业废气排放是恶臭污染的主要来源,为推动异味监测从人工监测到仪器监测的转变,提高自动化、智能化水平,本研究在典型工业园区搭建异味在线监测系统,同时在重点企业周边综合开展走航、手工监测、人工嗅辨等监测工作,并开展臭气浓度(OU值)算法优化试点工作。结果表明,该系统检出限小于0.1 nmol/mol,线性系数大于0.99,重复性相对标准偏差小于1.5%,具有良好的准确性、稳定性,在工业园区在线试点监测和走航监测中均取得较好的应用效果,满足环境空气异味在线监测要求；引入未知因子计算公式后,软件计算的OU值与人工嗅辨结果接近,张家港、镇江人工嗅辨与软件算法相关性分别为0.91、0.93,能保证较高的准确率。 |
| 关键词: 异味监测 工业园区 在线监测 臭气浓度 算法优化 |
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| 基金项目:江苏省生态环境监测科研基金项目 |
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| Research and pilot application of online monitoring technology of ambient air odor in industrial parks |
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| Abstract: |
| In order to promote the transformation of odor monitoring from manual monitoring to instrument monitoring, and improve the level of automation and intelligence, this study built an online odor monitoring system in typical industrial parks, and comprehensively carried out monitoring work such as navigation, manual monitoring, and manual sniffing around key enterprises, and carried out pilot work on odor concentration (OU value) algorithm optimization. The results show that the detection limit of the system is less than 0.1 nmol/mol, the linear coefficient is greater than 0.99, and the relative standard deviation of repeatability is less than 1.5%, which has good accuracy and stability, and has achieved good application results in online pilot monitoring and navigation monitoring in industrial parks, and meets the requirements of online monitoring of ambient air odor. After the introduction of the unknown factor calculation formula, the OU value calculated by the software is close to the manual sniffing results, and the correlation between the artificial sniffing algorithm in Zhangjiagang and Zhenjiang is 0.91 and 0.93, respectively, which can ensure a high accuracy rate. |
| Key words: Odor monitoring industrial park Onlinemonitoring odor concentration Algorithm optimization |
