Corresponding Author: Jerry Song; jerrysong0128@gmail.com
This project serves as an interactive guide to the practical implementation of dynamic material flow analysis (DMFA). Specifically, it leverages historical data on cement production in China to develop predictive models for future production trends at the provincial level. By harnessing DMFA techniques, we aim to offer insights into the potential trajectories of cement production, a critical element within China's industrial landscape.
This collaborative initiative is the brainchild of a partnership between Song Jingyang (Jerry) and Zhu Yanlei, a Ph.D. candidate at Peking University. Together, we have combined our expertise and passion for data analysis and environmental studies to delve into the complex dynamics of cement production in China. Our collaboration aims not only to forecast future trends but also to contribute to the broader discourse on sustainable industrial practices.
Within this repository, you'll find a comprehensive exploration of our methodologies, data sources, modeling techniques, and findings. Our hope is that this project will not only showcase the application of DMFA but also serve as a valuable resource for researchers, practitioners, and enthusiasts interested in the intersection of data science, environmental studies, and industrial forecasting.
The dynamic stock model is based on the ODYM model developed by Stefan Pauliuk, Uni Freiburg, Germany. For the original code & latest updates, see: https://github.com/IndEcol/ODYM