High spatial resolution mapping of steel resources accumulated above ground in mainland China: Past trends and future prospects

摘要: Abstract High-resolution mapping of steel resources accumulated above ground (referred to as stocks) is critical for exploring urban mining and circular economy opportunities. Prior studies have attempted approximate stocks using nighttime light (NTL). Although proven be a fast estimation technique, the accuracy NTL-based approach may subject several limitations, it has not been used projecting future stocks. To fill these gaps, we developed an aggregative downscaling model that fuses multiple large-scale spatial datasets, including gridded population, gross domestic product (GDP), built-up area. We demonstrated utility this by map in mainland China at 1 × 1 km resolution. Our results found increased from 12,873 t/km2 33,027 t/km2 during 1995–2015, four clusters (i.e., Beijing-Tianjin-Hebei agglomeration, Yangtze River Delta, Guangdong-Hong Kong-Macao Greater Bay Area, Chengdu-Chongqing metropolitan) possessed over 40% national total 2015, revealing unbalanced distribution across China. Moving forward, with assumed population growth, GDP area expansion, accumulation expected climb up 64,636 t/km2 cencentrate larger cities 2030, such Beijing, Shanghai, Shenzhen, Guangzhou. analysis highlights magnitude pace which are ground. estimates capture spatiotemporal dynamics stocks, potentially allowing better policy-making business decision-making on resource efficiency, waste management, environmental sustainability regional or scales.