Industrial processes often emit pollutants and toxins into the environment that can harm humans and the environment. Hazardous gas emissions from industries typically result from combustion processes, such as those used in power plants, factories, and other industrial sites. Industrial gas emissions can contribute to ground-level ozone, smog, and haze, leading to poor air quality, respiratory and cardiovascular diseases, and global climate change.
In many power plants, the biggest challenge is constantly monitoring emissions to ensure that they don’t exceed certain limits, and these monitoring systems are hardware-based. This can be a daunting task as there are multiple points where emissions can be released and monitoring them all simultaneously can be exceedingly difficult. Traditional gas emission monitoring methods involve labor-intensive processes to collect and analyze samples, and to measure the levels of contaminants and pollutants, resulting in limited readings and delayed access to data. AI uses deep learning algorithms to analyze large sets of data and provide insights into how these datasets relate to each other.
Prognostic Emission Monitor (PEM) is NURBS Labs’ AI software-based predictive emission monitoring system that can provide in-depth insights into parameters that affect emission variables and monitor hazardous emissions from power plants, thermal power plants, effluent treatment plants, and other manufacturing facilities. It offers an alternative to the shortcomings of a Continuous Emission Monitoring System (CEMS) such as high Capex, high maintenance, and operator training costs. PEM is used to determine the emission concentrations of a pollutant based on their relationship with several continuously monitored process parameters (e.g., fuel/gas consumption, air/fuel ratio, pressure, temperature, turbine and boiler settings, environmental conditions) and fuel or feed quality data (e.g., the Sulfur content) of an emission source.
Industrial plants use sensors to measure and monitor emissions from industrial processes. These sensors measure various parameters such as temperature, pressure, flow rate, and composition of the emissions. The data from these sensors is then sent through the software-based Prognostic Emission Monitors (PEM) where it is analyzed using software and algorithms. This analysis allows the system to predict any potential issues that may arise and identify possibilities to reduce emissions. Plant operators can use this data to optimize their processes for maximum efficiency by adjusting their operations.
Benefits of using Prognostic Emission Monitor
PEM provides satisfactory results in environmental compliance, as they provide enhanced, accurate data to meet regulatory requirements. Additionally, the plant data system can help detect potential issues swiftly, allowing corrective actions to be taken. The installation is seamless as no plant shutdown is required, low maintenance costs, and no hardware/spare parts are needed; it consumes little to no power and works with minimum manpower. As a result, PEM can improve process efficiency and cost savings, as they can reduce hazardous gas emissions released from processes. The environmental aspect of the ESG principle directly relates to the emission monitoring system of a power plant. This is because it evaluates the power plant’s impact on the natural world and the environment. Investing in PEM is important for any business that wants to ensure its processes are as efficient and environmentally friendly as possible.
It provides more accurate measurements than traditional methods do because it uses algorithms instead of humans to calculate gas levels based on plant data from multiple sources within a facility’s location. The data is processed to determine the concentration of pollutant emissions by revealing the hidden relationship between data and thus understanding the trends and patterns. This means there are fewer errors associated with human error in manual calculations or inaccurate measurements taken at different times in the production process. PEM enables plant owners and operators to better control costs, by avoiding unexpected costs due to unforeseen issues with hardware analyzers.
PEM shows great promise as a more efficient and accurate way to monitor emissions. With frequent monitoring of emissions, the industry can act quickly on problems before they become major sources of pollution. Analyzing emission data can recommend optimal operating parameters that reduce emissions and help organizations achieve their environmental goals.
NURBS Labs is committed to helping our clients achieve their sustainability goals. We are proud to be a part of the solution for a cleaner and healthier environment. Taking measures to protect the environment can be accomplished by contacting NURBS Labs and we will help you analyze your plant data to find ways to improve without additional Capex.
For more information visit https://www.nurbslabs.com/prognostic-emission-monitor/