A flexible tool for the mitigation of CO₂ in various sectors

In recent decades, climate change has become a pressing issue that demands urgent attention from society. One of the primary contributors to this issue is increased greenhouse gas emissions from human activities. Carbon dioxide, the most prevalent greenhouse gas, accounts for approximately 65% of total greenhouse gas emissions. Since 1970, carbon dioxide emissions have risen by around 90%, primarily due to the combustion of fossil fuels and industrial processes. Therefore, it is crucial to monitor the amount of carbon dioxide that is being released into the atmosphere through the industrial, agricultural, and transport sectors.

Further, a deeper understanding of these processes would facilitate identifying critical parameters in each sub-sector responsible for CO₂ emissions. Identifying such parameters would pave the way for modifying existing technologies or implementing new technologies that would reduce CO₂ emissions. A comprehensive analysis on a pan-country/pan-sector, considering several interconnected sectors and sub-sectors could aid in identifying critical sectors and sub-sectors contributing to CO₂ emissions, and articulate the right way forward for meeting various country or sector-wide targets including net-zero carbon emissions.

To address this problem, a comprehensive tool that models sectors/sub-sectors using first principles (later validated with relevant data) accounting for emissions holistically is being developed. Implementing this tool can provide valuable insights into the carbon footprint of various sectors and help strategize efforts to reduce emissions. By comprehensively accounting for emissions, policymakers and industry stakeholders can identify the most significant sources of emissions and propose the most relevant and effective action plans to mitigate their impact.

Description of the tool and proposed methodology

The tool includes a fundamental primitive module that can model the emissions of any sector based on its input and output data. Further, the module can be enhanced with any phenomenological/data-driven model, whenever it is instantiated. Upstream and downstream processes involved in a particular sector, accounting for appropriate emissions from all associated sectors, can be incorporated using these fundamental modules. The first version of this tool will be validated using sector-wise data from India. This tool can be modified or extended to any country, provided necessary data is available.

The tool is proposed to be primarily a first-principles-based model, which would later be validated/improved using available data. Any sector, sub-sector or entity of a particular subsector could be considered the control volume on which the mass and energy conservation equations could be applied. For instance, the agrochemical sector, ammonia production industry and the reactor inside a particular ammonia production industry will all obey the mass and energy balance equations. Since CO₂ is a material stream leaving the process (in most cases), it can be quantified with respect to several factors such as feed quality, source of electricity and the efficiency of the process. This proposed tool development project aims to identify a set of parameters for each significant CO₂-emitting sector and sub-sector, with a clear definition of the dependency of CO₂ emissions on these parameters. These parameters can serve as baselines for policymakers to create new achievable policies and act as levers for sectorial users to decrease CO₂ emissions.

Uniqueness of the tool

Recently, several other tools that aid policymakers and the stakeholders have been proposed in the literature. Wang et al. [1] presented a spatial and temporal model for several decarbonization possibilities in China's power industries. Li et al. [2] modelled several scenarios where the emission footprint of China's light-duty trucks could be reduced by electrification. Tan et al. [3] proposed a leader-follower model for government and industry to decarbonize maritime emissions. Using this, the government could propose CO₂ mitigation techniques for emission reduction, and the industry could adopt some techniques with minimal investment and less penalty. The subsidy-penalty play between these two bodies would result in an optimal solution for decarbonization. Matamala et al. [4] studied the possibility of incorporating carbon capture and storage (CCS) in the power sector with the aid of negative carbon emission techniques such as biomass for the Latin American region. Hebada et al. [5] analyzed four different scenarios for decarbonizing Brazil's iron and steel industries towards net-zero emissions goal for 2050. Vernay et al. [6] reported a model for analyzing the impact on energy community businesses during an energy transition.

Despite the depth of study in all the above models, the proposed tool is unique in several ways. The reported models in the literature are restricted to a particular sector/sub-sector, whereas the proposed tool offers a generalized framework to integrate and model all sectors. Likewise, the reported models in the literature are confined to a particular geographic location relevant to a particular industry (for instance, Brazil was chosen for the decarbonization of Iron and Steel in ref [5]). However, in the proposed tool, this is expected as an outcome. In other words, if the proposed tool is used for the analysis of the iron and steel industry using Indian data, the results of the model would suggest CO₂ emissions corresponding to which region of India is more of a significant concern. This, in turn, can be used to take a closer look at that region and make some process/policy recommendations. Also, the proposed framework is rooted in first principles supported by data, whereas the reported models are purely data-driven with fundamental constraints. This feature makes the tool user-friendly, where the user can easily input the variables, parameters and the associated relations between them, in addition to providing significant flexibility and promoting wide-spread usage.

Features of the tool and the expected outcomes

1. The tool will have in-built "boxes" that the user can consider as the system boundary/control volume.
2. The user can provide the variables and parameters associated with the box in a standard format.
3. By default, basic balance equations will be assembled.
4. The user can provide additional equations that capture various known phenomenology.
5. The tool would provide relevant parameters for some common CO₂ emission processes such as cement, iron and steel, and power plant. However, the user can customize/modify it as required.
6. The tool can be interrogated to generate policy decisions and their impact on decarbonization.

In general, the proposed tool is expected to be practical and easy to use for managing multiple CO₂-emitting systems of interest. By accurately identifying relevant parameters and defining system boundaries, this tool has the potential to offer valuable insights into identifying, reducing, and mitigating CO₂ emissions on a global scale.

References

[1] Y. Wang, Z. Zhao, W. Wang, D. Streimikiene, T. Balezentis, Interplay of multiple factors behind decarbonization of thermal electricity generation: A novel decomposition model, Technological Forecasting and Social Change. 189 (2023). https://doi.org/10.1016/j.techfore.2023.122368.

[2] J. Li, L. Wang, C. Ji, H. Liu, L. Lu, T. Zhang, M. Zhao, S. Xu, Assessing the decarbonization potential of China's light-duty truck fleet by electrification, Energy Reports. 9 (2023) 212–225. https://doi.org/10.1016/j.egyr.2023.03.018.

[3] R.R. Tan, I.H. V. Gue, J.F.D. Tapia, K.B. Aviso, Bilevel optimization model for maritime emissions reduction, Journal of Cleaner Production. 398 (2023). https://doi.org/10.1016/j.jclepro.2023.136589.

[4] Y. Matamala, F. Flores, A. Arriet, Z. Khan, F. Feijoo, Probabilistic feasibility assessment of sequestration reliance for climate targets, energy. 272 (2023) 127160. https://doi.org/10.1016/j.energy.2023.127160.

[5] O. Hebeda, B.S. Guimarães, G. Cretton-Souza, E.L. La Rovere, A.O. Pereira, Pathways for deep decarbonization of the Brazilian iron and steel industry, Journal of Cleaner Production. 401 (2023) 136675. https://doi.org/10.1016/j.jclepro.2023.136675.

[6] A.L. Vernay, C. Sebi, F. Arroyo, Energy community business models and their impact on the energy transition: Lessons learnt from France, Energy Policy. 175 (2023). https://doi.org/10.1016/j.enpol.2023.113473.