Water Reduction roadmap
In 2022, BMS established the first phase of our Water Reduction Roadmap to baseline our current water usage while mobilizing site leaders to drive water efficiency projects. Through efforts like smart water metering systems, rainwater collection and treatment, and prioritizing and updating water balances, in 2022, we realized a 4.1% decrease year-over-year in total water withdrawal. In addition to continuous learning from these projects, BMS is evaluating multiple water conservation technologies for application across our operations.
Smart meters and audits
We implemented smart meters within building automation systems and cloud-based platforms that track water usage across buildings and campuses, allowing for quick response to significant water-use deviation. We have already realized benefits including:
- Reclamation of dewatered groundwater for use in cooling towers at Princeton Pike, NJ
- Reclamation of clean in Place and other recoverable Water for injection (WFI) uses for reuse as cooling Tower makeup at Phoenix, AZ
Wastewater management
BMS follows stringent corporate standards and guidelines that meet or exceed local requirements regarding the treatment and management of wastewater effluents. We design clean and efficient pharmaceutical manufacturing processes that minimize the impact on the environment.
Wastewater from our facilities undergoes a high degree of treatment before being discharged. Treatment is provided by company-owned and operated on-site infrastructure or off-site municipal wastewater treatment systems, or a combination of both. We continue to allocate additional resources to assess and better understand the wastewater characteristics at our largest sites, enabling us to identify potential reuse opportunities.
BMS Global Engineering & Facilities (GEF) Energy & Water Council
Our GEF teams across the globe meet monthly to discuss energy and water reduction initiatives across our global sites and new technological opportunities. These regular meetings have improved transparency and shared learnings across the globe and allowed for greater optimization.
