Environmental Monitoring Reinvented: How Russia Is Building an Emission Control System Based on Calculation Methods

Introduction: From Smokestacks and Measurements to Digital Twins

Russian industry stands on the threshold of a genuine revolution in environmental control. Whereas just a few decades ago emission monitoring amounted to periodic measurements at smokestacks and the compilation of paper reports, today complex software suites harnessing the power of artificial intelligence and big data are taking their place. This transition is driven not only by a drive for technological progress but also by stringent requirements of environmental legislation.

Modern realities demand that large enterprises monitor in real time what is released into the atmosphere. However, traditional instrumental methods — installing gas analyzers on every stack — prove either technically challenging or economically impractical. This is precisely why the calculation method is coming to the forefront, and its pinnacle is predictive automatic emission control systems (PAECS) — "digital twins" of production facilities that do not merely record but predict environmental impact.

The Legislative Foundation: Why Enterprises Are Forced to Change

The transformation of Russia's environmental monitoring system is not an initiative of individual companies but a direct state mandate. In 2014, Federal Law No. 219-FZ was adopted, marking the starting point for large-scale changes. This document obligated all facilities exerting significant negative environmental impact (Category I facilities) to implement continuous monitoring and emission accounting systems.

The practical implementation mechanisms for these requirements were enshrined in Russian Government Resolution No. 262 of March 13, 2019, which approved the Rules for the Creation and Operation of Automatic Systems for Monitoring Emissions and Discharges of Pollutants. According to these rules, the program for creating an automatic monitoring system must define the list of stationary sources subject to control, the locations and timelines for installing measurement instruments, as well as the composition and format of transmitted information.

The legislator set strict timeframes: an automatic monitoring system must be created within a period not exceeding four years from the date of obtaining an integrated environmental permit (IEP). It is important to understand that failure to comply with these requirements entails administrative liability: legal entities face fines ranging from 100,000 to 200,000 rubles under Part 1 of Article 8.51 of the Code of Administrative Offenses of the Russian Federation.

Two Paths of Control: Instrumental vs. Calculation

Automatic monitoring systems can be implemented in two fundamentally different ways. The first is the instrumental method, which involves installing physical gas analyzers at emission sources that measure pollutant concentrations in real time. The second is the calculation method, whereby emission data is not measured directly but computed based on mathematical models using information about technological processes, raw material composition, and equipment operating modes.

The instrumental method was long considered the "gold standard," but practice has revealed its substantial limitations. Direct measurements using gas analyzers are far from always possible: difficulties arise with high temperatures and pressures of exhaust gases, lack of technical access to measurement points, high gas flow velocities, and fugitive emission sources such as open storage areas, quarries, and spoil heaps.

The calculation method, by contrast, is free from most of these limitations. Instead of attempting to "catch" every pollutant molecule at the stack outlet, the system builds a mathematical model of the entire technological process and computes with high accuracy how much and which substances should be formed given the specified operating parameters. As Alexey Parasyuna, a representative of Norsoft, aptly put it: "We do not physically measure but compute the amount of harmful emissions."

Predictive Systems: The "Digital Twin" of Production

The pinnacle of the calculation approach is predictive automatic emission control systems (PAECS). In official Rosstandart documents, they are defined as systems based on hardware and software tools installed at facilities with negative environmental impact and utilizing artificial intelligence methods and mathematical modeling.

How does such a system work? Imagine an exact digital copy of the entire production cycle that lives and breathes synchronously with the real equipment. Here are the main components of this complex mechanism.

Source Data Collection. A predictive system continuously receives information from multiple sources: the automated process control system (APCS), data on the chemical composition of raw materials and fuels, equipment load indicators, temperature and pressure at key points.

Mathematical Modeling. The acquired data is processed by complex algorithms based on the physicochemical laws of combustion, melting, or chemical reactions. The system "understands" what is happening inside a furnace, reactor, or boiler and calculates which substances and in what quantities should be formed as a result.

Artificial Intelligence. Modern predictive systems actively employ machine learning methods. By comparing calculated data with occasional instrumental measurements (which are still conducted for model verification), the algorithms continuously self-learn and improve forecast accuracy.

Dispersion Forecasting. Unlike a simple gas analyzer that only records the fact of emission "here and now," a predictive system is capable of modeling the dispersion of pollutants in the atmosphere considering current and forecast meteorological conditions — wind speed and direction at various altitudes, air temperature, and terrain.

Scenario Modeling. One of the most powerful capabilities of predictive systems is the ability to run various scenarios. An enterprise can assess in advance how emissions will change with increased production load, switching to different raw materials, or altering process regimes. This allows for environmentally informed management decisions even before changes occur in reality.

Russian Developments: From Idea to Industrial Implementation

Russia is not merely copying foreign experience but is creating its own, in many respects unique, solutions in the field of predictive environmental monitoring. The flagship project here is the Axioma system developed by Nornickel's subsidiary Norsoft in collaboration with Digital Corporate Technologies.

The system was conceived as a full-fledged alternative to traditional automatic emission control. Its key feature is the ability not only to calculate current emissions but also to forecast their dispersion considering weather conditions up to a day ahead. The system can predict in which direction, at what altitude, and with what speed and intensity emissions will spread depending on specific meteorological conditions.

If the risk of pollution reaching residential areas is assessed as high, Axioma issues recommendations for adjusting the production regime — for example, temporarily reducing the load on certain units. This approach allows preventing incidents rather than merely recording them after the fact.

The project has received the status of a unique digital IT project within the work of the Industrial Competence Center "Ecology." Moreover, according to Nornickel representatives, the Axioma system has proven that it "is more effective than simply hanging sensors straight on." The product has successfully passed trials at the company's facilities and is ready for replication in other industries.

Another significant player is Rosatom State Corporation, which through its subsidiary Rusatom Infrastructure Solutions has developed its own IT solution for automating the collection and analysis of data from gas analyzer sensors. The system also allows for automatic generation of reports for government agencies, significantly reducing the administrative burden on enterprises.

The market also features other software products addressing related tasks: "INFOPRO: Ecology" for automating calculations and reporting, and "ASMO-ecology" for comprehensive waste and emission accounting. Thus, a full-fledged ecosystem of digital environmental control tools is taking shape in Russia.

Standardization: The Rules of the Game for Digital Ecology

Such a large-scale transition to new technologies required the creation of a regulatory framework defining uniform requirements for predictive systems. And here Russia has taken the path of proactive standardization.

Since March 1, 2025, 16 national standards (GOST R) for classical automatic emission and discharge monitoring systems have been introduced and are in effect, developed by the D.I. Mendeleev Institute for Metrology (VNIIM) with the participation of the Research Institute "CEPP" and industrial enterprises. This in itself was an important step toward streamlining requirements.

However, the most significant event was the development of specialized standards specifically for predictive systems. In September 2025, Rosstandart approved a package of six national standards regulating the application of predictive systems at all stages of their lifecycle:

• GOST R 71979-2025 "Automatic emission and discharge monitoring systems. Automatic emission monitoring systems. Predictive systems. General provisions";

• GOST R 71980-2025 "Automatic emission and discharge monitoring systems. Automatic emission monitoring systems. Predictive systems. Requirements for software";

• GOST R 71982-2025 "Automatic emission and discharge monitoring systems. Automatic emission monitoring systems. Metrological assurance of predictive systems. General provisions."

These documents, for the first time in Russian practice, clearly define what a predictive system is, what requirements it must meet, and how its metrological assurance should be carried out. The emergence of such standards is a crucial signal to the market: the calculation method is recognized by the state as a legitimate and fully-fledged instrument of environmental control.

The Economics of the Calculation Method: Why It Is Profitable

In addition to technical advantages, the transition to predictive systems has a strong economic rationale. According to expert estimates, the use of predictive systems allows for a 2–5 fold reduction in capital investments for creating a monitoring system compared to equipping all emission sources with gas analyzers. Operating costs are reduced by dozens of times — after all, software does not require regular verification, replacement of sensitive elements, or calibration gases.

For a large industrial enterprise with tens or hundreds of emission sources, the savings can amount to hundreds of millions of rubles. At the same time, the enterprise gains not just "cheap" monitoring but qualitatively new capabilities — forecasting, scenario modeling, integration with production management systems.

Problems and Challenges: What Hinders Widespread Adoption

Despite the obvious advantages, the path of the calculation method to universal recognition has not been and will not be smooth. Several fundamental problems remain to be solved.

The Issue of Accuracy. Calculation methods objectively have a larger margin of error compared to instrumental methods. Research shows that relative errors in determining emissions by calculation methods can be quite significant. For example, errors in determining emissions during metal smelting exceed 25%, reach 20% for painting operations, and can be as high as 100% for electroplating processes. For other technological processes, the error can reach 30% or more.

This creates a risk of distorting the true picture of pollution and raises legitimate questions from regulatory authorities. A solution may be combining calculation and instrumental methods, where periodic direct measurements are used to verify and calibrate mathematical models.

Lack of Approved Methodologies. For a long time, one of the key problems was the absence of emission calculation methodologies approved by the Ministry of Natural Resources for many technological processes. Out of approximately 160 methodologies actually used at enterprises, only about 20 were listed in the official register. This created legal uncertainty and risks for business.

Trust in Data. Perhaps the most difficult challenge is building trust in calculated data among all stakeholders: regulatory authorities, the public, and business itself. A digital twin can be arbitrarily accurate, but if its readings are not accepted as evidence during inspections, the system's value drops sharply. This is why the work on standardization and metrological assurance of predictive systems being conducted by Rosstandart and VNIIM is so important.

Prospects: Where the System Is Headed

Despite the existing difficulties, the vector of environmental monitoring development in Russia is quite clearly defined. The state continues its course toward digitalization of environmental control, and the calculation method plays a key role in this process.

In the coming years, we can expect an expansion of the list of approved calculation methodologies, improvement of the regulatory framework, and accumulation of practical experience in applying predictive systems across various industries. It is already clear that predictive systems are not a temporary solution but a new paradigm of environmental control that will eventually become dominant.

Integration of predictive systems with the state register of negative impact facilities will create a unified information space where emission data will be accumulated in real time. This will enable not only monitoring of individual enterprises but also managing the environmental situation on the scale of entire regions, forecasting unfavorable periods, and taking proactive measures.

Conclusion

Russia is in an active phase of building a new, high-tech environmental monitoring system. The calculation method and predictive systems represent not just a technological novelty but a fundamental shift in the approach to controlling industrial impact on the environment. We are moving from simply recording violations to intelligent management based on forecasting and prevention.

This path is not easy: issues of calculation accuracy must be resolved, missing methodologies must be developed, and trust must be built between business and government. But the first steps have already been taken: a legislative framework has been created, national standards have been approved, and functioning domestic software products have emerged. All this allows us to look to the future with cautious optimism, where the "digital twin" of a production facility will become as common a tool as a physical sensor on a smokestack.