| Summary: | Dense air quality monitoring network (AQMN) is one of main ways to surveil industrial air pollution. This paper is concerned with the design of a dense AQMN for H<sub>2</sub>S for a chemical industrial park in Shanghai, China. An indicator (Surveillance Efficiency, <i>SE</i>) for the long-term performance of AQMN was constructed by averaging pollution detection efficiency (<i>r<sub>d</sub></i>) and source identification efficiency (<i>r<sub>b</sub></i>). A ranking method was developed by combing Gaussian puff model and Source area analysis for improving calculation efficiency. Candidate combinations with highest score were given priority in the selection of next site. Two existing monitors were suggested to relocate to the west and southwest of this park. <i>SE</i> of optimized AQMN increased quickly with monitor number, and then the growth trend started to flatten when the number reached about 60. The highest <i>SE</i> occurred when the number reached 110. Optimal schemes of AQMNs were suggested which can achieve about 98% of the highest <i>SE</i>, while using only about 60 monitors. Finally, the reason why the highest <i>SE</i> is less than 1 and the variation characteristics of <i>r<sub>d</sub></i> and <i>r<sub>b</sub></i> were discussed. Overall, the proposed method is an effective tool for designing AQMN with optimal <i>SE</i> in industrial parks.
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