Error Propagation Approach in Assessment of Boiler Emissions Uncertainties for Tea Factories in Kenya

Many tea factories in Kenya still heavily rely on fuelwood for energy, leading to the release of carbon dioxide (CO2) and other pollutants, impacting the environment, and contributing to climate change.This study focuses on understanding how errors in boiler emission measurement tools, specifically flow meters, flue gas analyzers, and temperature sensors, propagate and affect the accuracy of emissions data, potentially complicating regulatory efforts and environmental assessments.In a bid to address the aforementioned issue, measurement data of the boilers under study were collected over six distinct periods from selected tea factories in Kenya, which captured a wide range of operational conditions.With the application of novel standard error propagation techniques, the uncertainties associated with each instrument in the measurements were considered.Results in this research revealed that significant variations in gas emissions readings, primarily due to errors from the instruments and general environmental fluctuations, such as temperature and humidity This paper centered on emissions of carbon dioxide, nitrogen oxides sulphur oxides and particulate matter and further explicated the effect of error propagation, showing how minor variations in sensor accuracy resulted in substantial change in under or overestimation of emissions levels.Findings in this study underscore the need for constant protocols in calibrations and the application of real-time correction methods within the equipment of boiler emissions monitoring.The analysis in this research showed that the current measurement systems might not adequately support compliance with the environmental regulations, which thereby threatens human life.Finally, concludes that the establishment of more robust methods of calibration practices in Kenya tea factories, the adoption of advanced monitoring equipment and technologies, and the adoption of real-time processes in data analysis work well to improve and mitigate errors emanating from measurement instruments.These recommendations aim to improve measurement accuracy, resulting in sustainable environmental practices in Kenya's tea industry and, by extension, contributing to climate mitigation.