CS8: Decarbonizing Industry and Transport

Industrial chemical synthesis is a primary driver of global energy consumption and carbon emissions, largely due to the century-long reliance on fossil-fuel-based thermal processing. Traditional synthesis methods, such as those used for ammonia, methanol, and light olefins, typically require high-temperature and high-pressure environments that are fundamentally difficult to decarbonize. As the industrial sector transitions toward electrification, electrified thermal methods which convert electrical energy into direct heating for sustainable chemicals production have attracted fast-rising interest. Despite emerging progress, this field remains relatively underdeveloped.
This study assesses the technical and operational viability of integrating electrified thermal routes into a modern, renewable-heavy industrial framework. We analyze the performance and physical principles of four primary electrothermal technologies: Joule-heating, induction-heating, microwave-assisted, and plasma-assisted synthesis. Unlike conventional studies, this work evaluates these methods through their ability to facilitate chemical activation at significantly lower pressures than the industrial standard.
The comparison focuses on parameters critical to industrial transition: thermal coupling efficiency, selectivity, and compatibility with intermittent renewable energy inputs. The results provide a strategic outlook on which electrothermal pathways offer the most realistic potential for scaled-up, decentralized production. This research will provide a holistic assessment of prior work in electrothermal synthesis, and most importantly, to highlight the critical outlook which will enable renewable-integrated, thermally assisted production of sustainable chemicals.

This paper presents a two stage statistical optimization framework for the optimal sizing of Battery Energy Storage Systems (BESS), aiming to reduce greenhouse gas (GHG) emissions, improve energy efficiency, and lower maintenance and fuel costs in offshore drilling operations, reducing capital expenditures and payback periods. The proposed approach ensures that these benefits are achieved without compromising the resilience requirements of Dynamic Positioning (DP) systems or safety standards in classified offshore environments, where failures in the Power Management System (PMS) may lead to severe safety and environmental consequences.
To evaluate the viability of hybrid battery–diesel generation in this context, a two stage optimization methodology was developed to minimize Marginal Abatement Costs (MAC) across multiple BESS configurations for three split group drillships. A stochastic programming approach was incorporated using historical power demand data from a best-class drillship operating for Petrobras, capturing operational uncertainties and transient effects that deterministic models disregard. The methodology is implemented in a modular modeling platform that supports diverse power system topologies and integration schemes. It enables comparison not only of load profile smoothing from peak shaving, but also of the reduction in online diesel generator groups resulting from reliable backup power provided by spinning reserve.
Preliminary results indicate that the optimized solution for both MAC and GHG emission‑reduction criteria is the spinning‑reserve strategy with closed bus ties, leading to a 17.37% GHG emission reduction and a 67.51% running‑hour reduction. Alternatively, dismissing spinning reserve and keeping split bus ties can achieve similar MAC results while maintaining current operational standards, leading to a 5.32% GHG emission reduction and a 4.06% running‑hour reduction. BESS systems designed solely for peak‑shaving purposes can be downgraded by 84–87%, reducing capital investments by 94.73% with comparable economic performance.

The decarbonization of the chemical sector in India is necessarily path dependent and is important to achieve national mitigation targets, as the industry's electrification can provide strong mitigation potential only if the power sector is low carbon. However, in 2019, coal based generation accounted for about 72% of electricity production in India. Sectors that are hard to abate, including chemical, account for about a quarter of the country's CO₂ emissions, and the chemical sector needs a diverse set of mitigation measures, including biofuel, hydrogen, CCS, and efficiency measures.
We have used KiNESYS, an economywide energy system modelling framework, to assess India's long-term energy transition under alternative policy and technology pathways by developing two scenarios: a Base Scenario and a Net Zero Scenario.
In the Base scenario, the energy demand continues to grow through 2050, with a gas dominated fuel mix as shown in Fig. 1. Although coal and grid electricity remain important, oil products are cut but not eliminated. This means that the sector essentially transitions from one fossil fuel to another (gas), with very limited electrification; thus, overall emissions reductions occur through efficiency and fossil fuel switching, rather than a low-carbon transition.




Fig. 1. Base Scenario Energy Mix Chemical Sector.
In the Net-Zero scenario, there is a change in the energy mix of the chemical industry. By 2050, electricity emerges as the largest energy source, indicating extensive electrification. Biofuels gas follows after 2040 for non electrifiable applications, and hydrogen enters as a significant carrier for clean materials and high temperature requirements. Coal and oil are almost phased out, as shown in Fig. 2. 

Fig. 2. Net Zero Scenario Energy Mix Chemical Sector.

Decarbonising heavy industries such as alumina, iron, and steel involves complex technical, economic, environmental, social, and political considerations. There are multiple technologies that a company might introduce to reduce emissions, and traditionally, choices have been made predominantly, or exclusively, on financial metrics. As the scope of stakeholders in heavy industry expands and expectations for businesses to achieve economic growth while promoting social and environmental benefits grow, a new way of assessing project viability needs to be embedded. We propose a tool based on a Multi-Criteria Decision Analysis (MCDA) approach. We present a case study for selecting decarbonisation pathways for iron, steel and alumina operators in Australian industrial hubs. Through a literature review and stakeholder engagement, we establish a holistic set of comparison criteria, along with plausible point estimates and value ranges for the pathways. Using min-max normalisation and simple additive weighting, we generate a comparison score for each pathway. To account for uncertainty in the criteria values, we adopt a probabilistic Monte Carlo sensitivity analysis, sampling across plausible ranges of criteria and weights to generate distributions of comparison scores for each pathway. This approach allows us to identify tipping points, to assess the robustness of scenario rankings under uncertainty, and to evaluate the impact of policy changes that may incentivise alternative preferences. Our findings have important policy implications for investment decision-making in decarbonisation pathways for both corporations and the government, and the tool could act as a model for selecting the most appropriate option for decarbonisation in other sectors or jurisdictions.

Globally as energy transition evolves, energy efficiency positions as an enabler for industrial competitiveness, climate mitigation and sustainable development. Nevertheless, most empirical evidence on energy Environmental Social and Governance (ESG) nexus is focused on advanced economies but a departure and critical gap remain in understanding how energy efficiency shapes sustainability readiness in low-income, industrializing economies. This study informs bridging continents and fuelling progress in a global context by sharing evidence from Uganda a developing manufacturing economy at the intersection of African industrialization and global sustainability strategies. The study examines whether energy efficiency constitutes a substantial enabler of ESG readiness in Uganda's manufacturing sector. A quantitative time-series design is employed using World Bank data of Uganda for 35 years (1990–2024) and multiple linear regression models are estimated with diagnostic tests done to ensure model reliability. The results reveal a statistically significant inverse relationship between energy efficiency and environmental readiness. Also, there is a positive significant relationship between energy efficiency and social readiness. In contrast, governance readiness shows no significant relationship with energy efficiency emphasizing the institutional boundaries that underlie energy transitions in developing economies. The findings demonstrate energy efficiency as a dimension-specific enabler of ESG readiness. It substantially strengthens environmental and social outcomes of firms but does not inevitably render improved governance structures. The study contributes to empirical evidence from Sub-Saharan Africa and emphasizes the rationale of integrated policy frameworks that link energy transitions with institutional reforms. It concludes and recommends that energy efficiency should be recognized not just as an operational enabler but a deliberate path towards sustainable and inclusive industrial development in Uganda and beyond.