## 1 Introduction  
Steel has become an indispensable material in modern industry because of its high strength, excellent toughness, and wide applicability. In recent decades, accelerated urbanization and industrialization in China have significantly increased steel consumption across various sectors [1]. To meet the growing demand, China has become the world's leading producer and consumer of steel, accounting for 54% of global crude steel production in 2023 [2]. This increasing consumption has resulted in a large accumulation of steel-containing products in downstream sectors such as buildings, machinery, and others, known as steel in-use stocks (SIUS). SIUS can be recycled, processed, and reused after reaching the end of their lifetime, making them a key source of secondary resource recycling and utilization in the future. This can help reduce the demand for crude steel and lower the carbon footprint of steel products [3, 4]. _The 14 th Fire-Year Plan for the Development of Circular Economy_[5] and _Rexycling of Waste Materials_[6] both emphasize that it is important to increase the recycling rate of steel scrap. Scrap steel accounted for 65% of the major recycling recoveries in 2022 [7], making SIUSone of the key resources in the future. Therefore, accounting for SIUS can help to clarify the amount of scrap steel, and the spatial characteristics of SIUS can aid in the rational layout of the renewable resource processing industry. Thus, investigating the characteristics and quantity of SIUS is essential. In general, two research approaches are commonly used to quantify steel flows and SIUS. The first is the top-down approach, which is mainly suitable for calculating SIUS at the national level. In this approach, SIUS is obtained by calculating the difference between the inflow and outflow steel. This approach is typically applied to estimate SIUS at the national level [3,8,9]. The second approach is the bottom-up approach, which involves collecting the quantity of steel products and the steel content per unit of products from the five sub-sectors [10,11]. Compared to the top-down approach, the bottom-up approach provides more detailed information about the distribution of SIUS in different sectors. Therefore, in this study, the bottom-up approach is used to calculate SIUS and forecast the future steel stocks, demand, and available scrap resources. At present, most studies on SIUS primarily focus on the national level, such as the United States [8], China [12], and Japan [3]. [PERSON] (2023) [13] found that SIUS in developed countries is significantly higher than in China. Additionally, some studies have examined the differences in SIUS among provinces and cities. [PERSON] et al. (2020) and [PERSON] et al. (2020) used the bottom-up method to explore the heterogeneity of SIUS in 31 provinces [10,14]. [PERSON] et al. (2019) studied the metal stocks of 10 megacities in China [15]. However, fewer studies provide in-depth analyses of the characteristics of the provinces with large SIUS and forecast steel demand based on stocks, which does not provide sufficient support for local policies. Currently, research on the spatial characteristics of SIUS focuses primarily on the distribution characteristics. [PERSON] et al. (2020) found that the eastern zone has the largest share of SIUS by analyzing the total SIUS [14]. [PERSON] et al. (2020) analyzed per capita SIUS and found that its distribution is highly uneven, with higher values in the eastern and coastal regions [10]. By systematically analyzing the spatial characteristics of SIUS, it is possible to identify the distribution patterns of iron and steel resources within different prefecture-level cities. The current analysis of SIUS's spatial characteristics is relatively shallow. Incorporating a spatial autocorrelation model can better identify the clustering patterns of SIUS across different cities, which is crucial for optimizing the location and capacity planning of resource recovery bases [16].