A comprehensive review on integrative approach for sustainable management of plastic waste and its associated externalities.

Concrete is the most highly used construction material globally. This is largely due to its durability, versatility and manufacture from inexpensive and readily available materials. Although concrete has become an essential and ubiquitous construction material for modern society, its use has significant environmental impacts. The full cement and concrete lifecycle, from production to final disposal, accounts for nearly 10% of global energy-related CO2 emissions with the majority of these emissions produced from cement, which is the binding material that holds concrete together. The cement and concrete industry (CCI), which is integral to global infrastructure development, is therefore confronted with a growing need to decarbonize its operations and products, as well as to support the decarbonization of associated end-user sectors. This paper provides a systematic and critical review of more than 800 studies to highlight ways in which the CCI can decarbonize. A socio-technical perspective is used to understand the full range of industrial and economic activities where a decarbonized paradigm for cement and concrete production is relevant. This perspective is further used to assess key technical, economic, social and political factors that will drive a net-zero transition in the CCI over the long term. 

Decarbonizing the cement and concrete industry: A systematic review of socio-technical systems, technological innovations, and policy options

Pulp and paper industry in energy transition: Towards energy-efficient and low carbon operation in Finland and Sweden

A data-driven model for sustainable and resilient supplier selection and order allocation problem in a responsive supply chain: A case study of healthcare system

Deployng of the carbon capture technologies for co2 emission mitigation in the industrial sectors

An overview of Asian cement industry: Environmental impacts, research methodologies and mitigation measures

ABSTRACT The purpose of this research paper is to implement a machine learning model with the integration of the supply chain occupational reference (SCOR) model to develop an artificial intelligence-based system for resilient and sustainable supplier selection for a pharmaceutical company. Initially, the SCOR 4.0 model with the integration of Best Worst Method (BWM) has been used to develop the framework of customer satisfaction and to identify the critical elements of the suppliers. Later, the gradient boosting machine learning model has been implemented to classify the supplier as well as rank the suppliers from best to worst based on the acceptability score. The result shows that the gradient boosting algorithm performs well as a classifier, where the supplier with the most acceptability score represents the best supplier and the supplier with the least acceptability score represents the worst supplier. This study contributes to our understanding of how and when integrated SCOR and machine learning models can help improve supplier selection.

https://doi.org/10.1080/23789689.2023.2165782

Resilient and sustainable supplier selection: an integration of SCOR 4.0 and machine learning approach

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An overview of Asian cement industry: Environmental impacts, research methodologies and mitigation measures

Resilient and sustainable supplier selection: an integration of SCOR 4.0 and machine learning approach