Supplementary workbook and plotting code for: High volume, low retention: the circularity trap in Pakistan's building materials
Description
This dataset supports the article "High volume, low retention: the circularity trap in Pakistan's building materials", submitted to Resources, Conservation & Recycling. The study combines published material intensities for three pacca house archetypes in Sindh, Pakistan (Karachi, Hyderabad and Deh 294) with product stage carbon factors for fired clay brick, cement and steel, national production data and an exploratory rubric for value retention at the end of service life. It tests whether the materials that carry most of the embodied carbon of Pakistani houses can also retain value through reuse or recycling. The Excel workbook contains every input, assumption and result of the study as live formulas. The Inputs sheet lists material intensities, carbon factors, production volumes and scenario settings, each with its source. The Retention rubric sheet scores steel, stone, concrete, fired clay brick and concrete block on recyclability, value preservation and market continuity, and includes dominance checks and market scenarios. The Carbon by Archetype sheet calculates the carbon contribution per m² of floor area under nine cement scenarios. The levers, throughput and brick decomposition sheets quantify the effect of LC3-type cement, zigzag kilns and secondary material markets, national material throughput, and the difference between two brick plants. The Outputs sheet links every number reported in the article to the cell that calculates it, and the References sheet lists all sources with their DOIs. Two Python scripts reproduce Fig. 1, Fig. 2 and the graphical abstract of the article directly from the Outputs sheet. A README file describes all files and sheets. All input data come from published sources, and no primary data were collected. The plotting code was prepared with the assistance of Claude (Anthropic), and the figures are drawn directly from the workbook values by that code.
Files
Steps to reproduce
1. Download all four files into one folder. 2. Open MCCM_supplementary_workbook.xlsx in Microsoft Excel or LibreOffice Calc. c. Input values are shown in blue on the Inputs and Retention rubric sheets. Changing an input recalculates every dependent result, and the 'Outputs' sheet shows the values reported in the article. 3. To reproduce the figures, install Python 3.9 or later with the matplotlib and openpyxl packages, for example, with pip install matplotlib openpyxl. 4. Run "python plot_figures.py" to create Fig. 1 and Fig. 2, and "python plot_graphical_abstract.py" to create the graphical abstract. Each script reads the workbook in the same folder and writes PDF, PNG and TIFF files there. A workbook stored elsewhere can be given as the first argument. 5. If you change an input, save the workbook in Excel or LibreOffice before running the scripts so that they read the recalculated values. The published figures use the Arial typeface, or Liberation Sans on Linux.