Manjunath Rao elaborates on the critical shift from reactive to predictive emissions management in the oil and gas industry.

The oil and gas industry lies at the centre of global energy production, but its environmental footprint is impossible to ignore. It's estimated that greenhouse gas emissions from this sector account for about 15% of the planet’s energy-related emissions. With growing international pressure to decarbonise, the time for the industry to act decisively has never been greater.

What makes this challenge particularly daunting is the breadth of the industry’s emissions profile. Virtually every stage of the value chain contributes to the problem, from the combustion in boilers, heaters, and flares to indirect emissions produced by compressors and pumps. These operational necessities result in a hefty carbon footprint. On top of that, fugitive emissions—unintentional leaks from pipelines, scrubbers, and valves—make managing emissions not only a complex but urgent task.

Despite the global push to decarbonise, a recent Accenture report showed that only 18% of companies are on track to meet their net-zero goals by 2050. Rooted in traditional practices and facing growing pressure from regulators and investors, the path forward demands a fundamental shift in how emissions are managed. And this shift is crucial not only for maintaining credibility and compliance but also for ensuring long-term viability.

Why traditional emissions management is no longer enough

For decades, Continuous Emissions Monitoring Systems (CEMS) have been the backbone of emissions management in oil and gas facilities. Using physical sensors, these systems measure pollutants like carbon dioxide, methane, and sulfur oxides. While they were once viewed as innovative, their shortcomings have become more obvious as the industry faces more stringent regulatory standards and pushes toward decarbonisation.

One major issue is the cost and complexity of maintaining CEMS infrastructure. Refineries and gas plants operate in harsh environments where high temperatures, corrosive chemicals, and physical wear often lead to malfunctions or inaccuracies. Breakdowns are relatively common, and repairs or recalibrations can result in expensive downtime. Plus,the data these systems provide is reactive; by the time emissions are measured, they have already occurred, leaving operators with no way to make timely adjustments or prevent inefficiencies.

On top of that, traditional monitoring systems are struggling to align with stricter environmental regulations. With standards like the EPA’s 40 CFR Part 60 and the EU’s Large Combustion Plant Directive calling for more frequent reporting and tighter compliance, many facilities relying on older technologies face growing challenges,creating a widening gap between what’s required and what these legacy solutions can actually deliver.

How Industry 4.0 is transforming emissions monitoring

Advanced Emissions Monitoring systems with predictive capabilities offer an entirely different approach to emissions management—one that aligns with the needs of a rapidly changing industry. Unlike CEMS, which depend heavily on physical hardware, these systems use advanced process modeling and data analytics to analyse various operational parameters—like combustion efficiency, temperature profiles, and feedstock quality—to estimate emissions in real time.

This difference makes it a game-changer, especially for facilities in remote or hazardous locations where installing physical sensors is impractical. These systems also align well with the broader digital transformation and Industry 4.0 trends sweeping across industries, seamlessly integrating with IoT devices, digital twins, and other Industry 4.0 technologies, enabling operators to track and analyse emissions data in real time, identifying inefficiencies and opportunities for timely optimisation.

The predictive power of these systems is what truly sets them apart. By combining historical data with live operational insights, Advanced Emission Monitoring systems can identify trends and anomalies that signal potential emissions spikes. This gives operators the chance to take preemptive actions—whether by tweaking combustion settings or adjusting operational parameters—before they risk breaching regulatory limits.This proactive strategy not only enhances compliance but also helps minimise the financial and environmental repercussions of unexpected outages or penalties.

The challenges of adopting predictive technologies

While predictive emissions management has the potential to revolutionise emissions management, adopting this technology isn't without its hurdles. One of the biggest challenges is integrating advanced, predictive systems with the legacy systems of oil and gas facilities. Many of these operations still rely on outdated Distributed Control Systems (DCS) and Supervisory Control and Data Acquisition (SCADA) systems, which were never designed to work with modern software-driven solutions. This lack of compatibility can lead to delays in implementation, driving up costs and complicating the adoption process.

Data integrity is another critical concern. Since predictive systems generate emission estimates based on various operational inputs, any errors or inconsistencies in these variables—whether from fluctuating feedstock quality or aging equipment—can skew the reliability of the predictions. In fact, regulatory bodies are also cautious about fully embracing these systems as a primary replacement for CEMS. Even though the technology has shown promise in numerous pilot projects, agencies are hesitant to step away from traditional systems like CEMS,largely due to their established history. As a result, many companies find themselves running both systems during the transition, which adds complexity and expense.

Lastly, there’s the human element. Shifting from traditional, hardware-focused monitoring systems to software-driven onesdemands a major cultural shift. Engineers and operators who have been trained in conventional methods need to learn to embrace and trust data-driven insights. Without proper training and buy-in from the workforce, the full potential of these systems cannot be realised.

Steps toward successful adoption of advanced emission monitoring

To tackle the challenges of adopting Advanced Emission Monitoring Systems, companies need a thoughtful plan in place. A key first step is developing a strong data ecosystem. By standardising and streamlining their data infrastructure, companies can ensure that these predictive systems getthe high-quality inputs they need. This, in turn, leads to accurate insights that can be put into action.

It's also vital for organisations to work closely with regulatory bodies. Engaging regulators in pilot programs allows companies to showcase the accuracy and reliability of Advanced Emission Monitoring systems in real-world situations. Being transparent during this process can significantly build trust and help pave the way for eventual approvals.

Another crucial piece of the puzzle is workforce training. By prioritising upskilling, companies can equip their teams to effectively work with advanced analytics tools and integrate predictive insights into their everyday tasks. This not only smooths the transition but also empowers employees to maximise the benefits of the technology.

Lastly, taking small, manageable steps can create a significant impact. By starting with non-critical areas for the implementation of predictive technologies, companies can test the waters, refine the system, and foster organisational support before moving into their core operations. Basically, this incremental approach ensures that any challenges encountered can be addressed before full-scale implementation.

A smarter, greener future for oil and gas

As the pressure to meet sustainability targets mounts, the oil and gas sector can no longer rely on traditional emissions management practices. With stricter regulations and heightened public scrutiny, simply reacting to emissions issues after they occur is no longer enough. To remain competitive, companies must embrace proactive solutions—like Advanced Emissions Monitoring systems—which go beyond compliance to become a critical strategic asset.

Adopting advanced monitoring systems with predictive capabilities not only helps companies stay ahead of regulatory requirements but also offers a significant competitive advantage. According to McKinsey, companies that integrate predictive technologies into their operations don’t just achieve environmental targets—they also reduce operational costs, improve asset performance, and realise long-term efficiencies. In a market increasingly driven by sustainability, businesses that lead in emissions management are better positioned to attract investor confidence and build stronger relationships with stakeholders.

The future belongs to those who embrace predictive technologies, aligning environmental goals with bottom-line performance, and leading the charge in the global energy transition.

Manjunath Rao is Director – Process Industries, Utthunga. With over 40 years of experience in the Oil & Gas and Petrochemical industries, Manjunath Rao is a distinguished leader and expert in process engineering, commissioning, and large-scale project management. As Director of Process Engineering at Utthunga, Manjunath has successfully led complex projects, from mechanical completion to startup, with a focus on cost control, risk mitigation, and compliance with quality and safety standards.

His deep domain expertise spans plant operations, technical services, and commissioning, with a proven track record in managing critical infrastructure projects such as New Build Rig and Cross-country Pipelines. Known for integrating cutting-edge technologies and optimising plant performance, he fosters cross-functional collaboration to drive innovation and operational excellence.

A recognised thought leader in the global Oil & Gas sector, Manjunath's strategic vision and hands-on experience make him a sought-after authority on advancing industry standards and delivering high-impact, sustainable solutions.