# Calculation Methods for Construction Material Stocks: A Systematic Review
## 3 Results
### Content Analysis
#### 3.2.2 Material Stock Calculation Methods
[43] modeled the stocks and flows of non-metallic minerals in residential buildings, roads, and railways in the European Union from 2004 to 2009. The study employed the typology of 72 buildings, four roads, and two railway types aiming to estimate the total material stock in the European Union. The results showed that the per capita non-metallic minerals stocks for roads were 128 tons, while it was 72 tons for residential buildings and 3 tons for railways in 2009. Demand Driven  
The demand-driven methodology estimates the material stock by using socio-economic indicators to model the demand for construction material. The methodology is used in the research where the material stock is estimated based upon the assumption that the demand of construction material is dependent upon economic, population, and social reasons in the society. Demand-driven has been a less commonly used method compared to others. The summary of the demand-driven methodology is shown in Table 4.  
In a comprehensive study, [PERSON] [44] endeavored to identify the material stock accumulation and the speed of material stock accumulation around the world historically. The study reviewed the literature and found material stock accumulation, speed, and acceleration throughout 1950 to 2010 for forty different countries. The results suggest that the growth of material stock follows four archetypal patterns. Almost 600 Gigatons were accumulated from 1970 to 2010, of which more than half were added in the last 13 years. In another study, however, [PERSON] [48], modeled the national material stock of Japan and the US. The model used the historical data of average floor area and material intensity; then, analyzed the reasons for the differences in the material stock. Results showed that there exist different patterns of material stock accumulation around the world. Similarly, between 1930 and 2005, the material stock per capita was higher for the US. However, both countries almost reached a similar material stock per capita in 2005, i.e., 310 tons for Japan and 375 tons for the US. [PERSON] et al. [47] investigated stock dynamics in Japan in relation to population and economic drivers using panel regression and IPAT (Impact = Population*Affluence*Technology) analyses from the past five decades. The key characteristic changes in different regions with the potential influence on material stock growth were critically reviewed to carry out the research. The results suggested that economic growth, population growth, and migrations caused material stock growth. [PERSON] et al. [45] also presented a demand-driven stock modeling approach that considered demographic aspects, lifestyle-related issues, and building-specific characteristics for energy reduction strategies in buildings. The study was conducted on dwelling stocks in Germany and the Czech Republic. The results showed that the current regulations were [PERSON] to achieve the 20% energy efficiency goal by 2020 but not to reach the 2050 energy and GHG-emission goals. In contrast, Yoshida et al. [34] proposed an automatic detection of the anthropogenic disturbance of soil and earth from excavation and mining sites. They used GIS and digital elevation modeling to pinpoint the location and amount of excavation in Japan as a case study. The results indicated that