A comparative multidimensional evaluation of parameters and alternatives for transformation of sustainable cement production in Pakistan

Abstract

The United Nations has declared its latest climate report a ‘code red,’ sounding the alarm and prompting a global call for scientists and policymakers to adopt comprehensive, systems-wide integrated strategies for promoting sustainable life on Earth. The need for collaborative and holistic approaches for the transformation of cement production into a socio-ecologically sustainable industrial segment had never been more imperative. This paper rigorously evaluates the parameters and alternatives for the sustainable transformation of Pakistan's cement industry. Economic, environmental, and social parameters are explored and screened using multiple methodologies. Real-world data collected from the operating cement plants in Pakistan are analyzed using Principal Component Analysis (PCA) and Grey Relational Analysis (GRA). The consolidated list of sustainability criteria and alternatives is evaluated using the Multi Actor Multi Criteria Analysis (MAMCA) framework, which incorporates the involvement of both local and international stakeholders for prioritization of the transformation goals. Data analytic results reveal that carbon emissions have a strong degree of statistical association with production ingredients such as SiO2, Insoluble Residue (IR), Al2O3, and Fe2O3. Although there are a few interesting variations in the priorities computed from the recorded perspectives of different stakeholders, the consensus on giving top priority to environmental parameters and the alternatives like ‘Waste-heat Recovery Plants’ and ‘Vertical Rolling Mills’ is novel and promising. By taking all the main sustainability domains into account, employing multidimensional techniques, and involving multiple stakeholder perspectives under the context of a developing country, the research outcomes of this study become highly attractive for researchers, investors, and policymakers all over the world.