VL Energy has developed a first-of-its-kind artificial intelligence (AI) powered Predictive Emissions Monitoring Systems (PEMS). Harnessing the power of cloud computing and AI methods, the PEMS reviews the operating parameters of combustion equipment to power predictive models for emission monitoring. Compared to the incumbent Continuous Emissions Monitoring Systems (CEMS), PEMS significantly reduces capital and operating costs, while improving safety and mitigating environmental impacts.

The PEMS units are critical in many ways. Nitrogen oxides (NOx) have adverse environmental and health effects, contributing to smog and acid rain, as well as forming fine particles (PM) and ozone in the ambient air (tropospheric ozone or ground-level ozone). To ensure compliance with regulatory emission limits, industrial facilities with large stationary sources are typically required to equip one or more continuous emissions monitoring systems (CEMS) to monitor NOx and other air emissions. However, CEMS are quite expensive and require frequent maintenance. In addition, frequent cylinder gas audits (CGA) and spare parts stocking add extra costs to operators. Despite these measures, analyzer malfunction can still cause non-compliance on availability requirements. Moreover, CEMSs are cost prohibitive for small combustion sources, so industry relies on general emission factors for emission monitoring and reporting.

Once commercialized, VL Energy’s PEMS will be critical in monitoring and reducing emissions economically across emission sources of all sizes and in various industries.