电子企业水质特征因子与雨污混接诊断研究

针对雨水管网旱天混接排放来源中,工业企业接入雨水管网可能造成的严重水环境污染问题,以城区内存在的电子类工业企业为研究对象,开展了电子类企业混接水质特征因子识别与混接诊断研究.研究表明,在22项水质监测指标中,显著表征电子类企业废水混接的水质特征因子指标包括氟化物、氯化物、硫酸盐;其中氟化物的显著性最高,且浓度变化范围相对最低,约为(10.5±1.76) mg/L(均值±标准差).针对上海市中心城区某排水系统,以氟化物作为特征因子,结合化学质量平衡模型和随机算法对半导体废水混接进行了解析,与调查结果相比,混接水量解析误差在15%以内.进一步针对各种典型工业行业类型,建立混接水质特征因子数据库,可将水质特征因子推广应用于雨水管网混接成因识别.

Tracer parameters to identify and quantify electronic industrial flow entries into storm drains

The non-storm water sources with inappropriate entries into storm drains, especially industrial sources, could have a severe detriment to the quality of receiving water body. This study assessed tracer parameters to identify electronic enterprises with inadvertent connections to storm drains and therefore quantified the industrial source flow using the identified tracer parameters. Among the 22 monitored water quality indicators, fluoride, chloride and sulphate are identified as the markers, which can be used to distinguish electronic industry wastewater from sanitary wastewater. Particularly, fluoride is the priority marker, showing most significant difference among the source types and less concentration range within the electronic industry source type, with a concentration level of (10.5±1.76) mg/L (i.e., standard± deviation). A case study at a catchment in the Shanghai downtown area was conducted based on fluoride mass balance within the storm pipes and Monte Carlo simulation. For the dry-weather discharge from the storm pipe network, the estimated electronic industrial flow ratio matches the data from field observations, with a relative error less than 15%. Moreover, from a wider perspective, the use of multi marker species is desired to provide clear evidence for the presence of a variety of industry trades with unexpected entry into storm drains.