Objective With the acceleration of industrialization,heavy metal pollution in industrial wastewater and waste gas has increasingly become a major challenge for environmental protection.The aim of this study was to accurately determine the heavy metal content in industrial wastewater and waste gas by Inductively Coupled Plasma Optical Emission Spectrometry(ICP-OES).To evaluate the degree of pollution and provide scientific basis for pollution control.Methods In this study,wastewater and exhaust gas samples from different industrial zones were collected,and the samples were treated appropriately,including filtration,acidification,or the use of absorption solution,to adapt to the analytical requirements of ICP-OES.In this study,the inductively coupled plasma emission spectrometer Avio 200 was used for analysis.According to the HJ 776-2015 standard,the method optimization was carried out for the detection of four heavy metals including copper,zinc,nickel and chromium,including the adjustment of analysis parameters such as power,argon flow rate and sample introduction rate to ensure the sensitivity and accuracy of the detection.Results Through this study,we optimized the inter laboratory comparison sample testing process using single factor analysis of variance.The results indicate that the optimized testing process significantly improved the sensitivity and accuracy of detecting heavy metals(copper,zinc,nickel,and chromium)in industrial wastewater and exhaust gases.The treatment technology under Condition B,compared to Condition A,proved to be more effective in reducing the content of heavy metals in samples,especially for copper and zinc.Conclusion This study successfully utilized single factor analysis of variance to optimize the inter laboratory comparison sample testing process,providing a scientific basis for improving the accuracy and efficiency of heavy metal detection in environmental monitoring.
single factor analysis of varianceinterlaboratory comparisonsample testingtest flow optimization
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