**1. Introduction**

Arsenic is an element that is toxic for the environment and people's health [1–4], especially As2O3. In the smelting process for copper sulfide ores, arsenic is dispersed into the fly ash, smelting slag and copper matte [5–7]. Due to the increasing complexity of copper concentrate, arsenic control has been listed as an important issue in copper smelters [8]. The SKS (Shuikoushan) copper smelting process is very adaptable to complex concentrates and it has high arsenic removal efficiency [9–13]. In recent years, the SKS copper smelting process has become a popular research topic [14–20]. Arsenic removal in the SKS smelting process is affected by several factors, such as the composition of concentrate, matte grade, oxygen concentration in air blown into the furnace, oxygen/ore ratio, smelting temperature, the Fe/SiO2 ratio in slag, and so on. In our previous study, the effects of matte grade, oxygen/ore ratio, oxygen concentration in air blown into the furnace, smelting temperature and ratio of Fe/SiO2 in slag were investigated [21].

However, the composition of concentrate, especially the major elements (Cu, Fe and S), could affect the oxygen/sulfur potential of the smelting system, and further affect the removal of arsenic. Therefore, in this work, the content of the major elements (Cu, Fe and S) in sulfide concentrate was adjusted, and the removal of arsenic from the matte to gas phase in the SKS copper smelting process was

investigated through the commercial simulation software SKSSIM [22]. This work will help us to better understand the SKS copper smelting process.

#### **2. Research Methodology**

The study was carried out by SKSSIM simulation software, combined with actual production in the Fangyuan 1# smelter in Dongying, China.

SKSSIM is an efficient simulation software for the SKS process, and it is based on the SKS smelting mechanism model [22] and the theory of Gibbs free energy minimization [23]. In the mechanism model, the SKS furnace is divided into seven functional layers from top to bottom and three functional regions along the length direction [21–24]. The particle swarm optimization algorithm, C# computer programming language, and Microsoft Visual Studio were used to develop the SKSSIM software. The development process (including activity coefficient, Gibbs free energy including activity coefficient, Gibbs free energy, phase entrainment coefficient, model verification and modification) has been presented in detail in our previous work [23]. SKSSIM has been successfully validated by the actual production process in Fangyuan 1# smelter [21,23,24]. Therefore, SKSSIM is a convenient method to carry out this study.
