BR21882258 “Development of a complex of intelligent information and communication systems for environmental monitoring of emissions into the environment for making management decisions in the concept of carbon neutrality”

Project manager: Doctor of Sciences in IT, Biloshchytskyi Andrii Aleksandrovich

Source of funding: THE PAF KS MSHE OF RK

Years of implementation: 2023 – 2025

Amount of funding: 576,412,171.88 tenge

Project objective:

Development of a set of intelligent information and communication systems for monitoring emissions into the environment, which will eliminate uncontrolled emissions into the atmosphere and “releases to the terrain” by increasing the efficiency of measurement systems at emission sources in the concept of carbon neutrality, which will achieve near-zero greenhouse gas emissions by 2060.

Program summary:

Limiting global warming requires unprecedented action by all countries and all sectors of industry. To achieve net zero emissions by 2050, we must reduce greenhouse gas emissions rapidly, deeply, and sustainably, while increasing the planet’s capacity to absorb carbon through environmental solutions and carbon removal technologies. The findings of the UN Intergovernmental Panel on Climate Change define the regulations necessary to achieve climate neutrality by 2050.

The main idea of ​​the scientific project is to apply a scientific approach to solve the urgent problem of monitoring emissions into the environment and achieving carbon neutrality.

Partners:

Program objectives:

      1. Analysis of existing methods and models for monitoring emissions into the environment, as well as the                best world experience in implementing environmental monitoring systems.

  1. Analysis of existing methods (techniques) for measuring emissions (discharges) of pollutants: determining the speed and flow rate of gas and dust flows emanating from stationary sources of pollution; determining the pressure and temperature of gas and dust flows emanating from stationary sources of pollution; determining the humidity of gas and dust flows emanating from stationary sources of pollution.
  2. Development of methods for determining emissions subject to transfer from the main stationary sources of pollution with optimal characteristics in terms of time parameters and units of measurement. 4. Development of models for forecasting pollutants into the environment from the main stationary emission sources for different groups of enterprises
  3. Creation of methods for calculating the forecast of emissions subject to continuous monitoring
  4. Creation of methods for calculating the predicted discharges of wastewater discharged into a water body or onto the terrain, which are subject to equipping with an automated monitoring system
  5. Creation of a database of the main stationary sources of pollutants with regulation of emission quotas.
  6. Creation of models of the cloud architecture of a software package implemented using microservices technology, which will ensure: monitoring of emissions into the environment by quantity, quality of emissions and their change; control over compliance with standards for permissible emissions, discharges of pollutants and mass concentration of pollutants; assessment of the effectiveness of measures to reduce the harmful effects of pollutants on the state of the environment; accounting of emissions, discharges of pollutants based on the results of continuous measurements, preparation of reports on industrial environmental control; automated collection of data from emission sources.
  7. Development of methods for transmitting data from primary measuring devices at the main stationary emission sources to those responsible for environmental protection using cloud technologies or the Industrial Internet of Things
  8. Development of an intelligent information system: collection and processing of unstructured data from various sources, visualization services and data access level, interfaces (API) for interaction with external information systems.
  9. Testing of the developed experimental software package.

Stages of program implementation

  1. Analysis of existing methods and models for monitoring emissions into the environment, which will allow assessing the world experience of implementing environmental monitoring systems, as well as identifying existing methods for measuring indicators of pollutant emissions into the atmosphere.
  2. Development of a method for determining emissions and forecasting pollutants into the environment in the context of various groups of enterprises, which will allow calculating the forecast for emissions and wastewater discharges subject to continuous monitoring.
  3. Creation of a database of stationary sources of pollutants and development of a model of cloud architecture for the developed software package, implemented using blockchain technologies, microservices, Big Data and web solutions, which will certainly ensure: monitoring of emissions into the environment by quantity, by quality of emissions and their change, as well as verification and automated collection of data from emission sources.

Project results:

  • A method has been developed to determine emissions subject to transfer from the main stationary sources of pollution with optimal characteristics in terms of time parameter and units of measurement.
  • Models have been developed to predict CO₂ emissions based on the group method of data processing (GMDH) and multilayer perceptron (MLP ANN) for various energy sources: coal, natural gas, hydropower, biofuels and waste, renewable energy sources (wind, sun, etc.) and oil.
  • A method has been developed to predict emissions of pollutants subject to continuous monitoring, based on a comprehensive time series forecasting model that takes into account statistical fractal analysis.
  • A method has been developed to calculate predicted wastewater discharges into a water body or onto the terrain, which are subject to equipping an automated monitoring system, which is based on the results of applying fractal analysis of time series of emission indicators.
  • A database of the main stationary sources of pollutants with emission quotas has been created.
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