Air Pollution Control for Finishers

Tri-Mer manufactures and installs pollution control systems for plating, anodizing and powder coating. Chemical-free fan/separator scrubs corrosive fumes with 1/10th the water of traditional scrubbers. Crossflow, for inorganic compounds, maintains stack emissions to specific ppms. Odor control systems simultaneously handle particulate and inorganic compounds. The C/E-1 Chrome Scrubber is 99.5%+ efficient for all chrome regardless of inlet loading, and doesn’t consume chemicals or generate waste. Whirl/Wet self-cleaning wet dust collector uses minimal water, is 99%+ efficient for particulate 3+ microns. Stand-alone equipment or turnkey systems are available, including tanks, ducting, exhaust hoods and material handling.

Tri-Mer Corp. | 989-723-7838 | tri-mer.com

Related Content

Novel Wastewater Treatment Targets Micropollutants

Swiss wastewater treatment technology provider Oxyle specializes in advanced wastewater treatment for removal of highly persistent micropollutants such as PFAS.
NASF/AESF Foundation Research Project #122: Electrochemical Approaches to Treatment of PFAS in Plating Wastewater - 10th Quarterly Report

The NASF-AESF Foundation Research Board selected a project addressing the problem of PFAS and related chemicals in plating wastewater streams. This report covers the 10th quarter of work (April-June 2023). Here, we examine the effect of surface fluorination of Ti4O7 anodes on PFAS degradation performance in terms of energy performance as well as formation of chlorate and perchlorate when chloride is present in the solution. The full paper on this work can be accessed and printed at short.pfonline.com/NASF24Feb2.
NASF/AESF Foundation Research Project #121: Development of a Sustainability Metrics System and a Technical Solution Method for Sustainable Metal Finishing - 15th Quarterly Report

This NASF-AESF Foundation research project report covers the twelfth quarter of project work (October-December 2023) at Wayne State University in Detroit. In this period, our main effort focused on the development of a set of Digital Twins (DTs) using the Physics-Informed Neural Network (PINN) technology with application on parts rinsing simulation.