BY DR TIM SANDLE | PHARMACEUTICAL MICROBIOLOGY AND CONTAMINATION CONTROL EXPERT
27th MAY
Cleanrooms form the controlled environment in which pharmaceutical products are manufactured, making their performance critical to product quality, patient safety and regulatory compliance. To ensure a cleanroom is operating effectively, several key performance tests must be carried out - one of the most important being the assessment of Air Changes per Hour (ACH).
ACH is a fundamental parameter in cleanroom design and performance monitoring. It measures how many times the total volume of air within a room is replaced each hour with High-Efficiency Particulate Air (HEPA)-filtered air. This helps determine the cleanroom’s ability to dilute airborne contaminants, maintain pressure differentials, and consistently achieve the required International Organization for Standardization (ISO) classification 1.
While ACH is a critical component of contamination control, it should not be considered in isolation. Factors such as airflow direction, airflow visualisation and recovery rates also play an essential role in overall cleanroom performance.
This article explores the principles behind ACH, why it matters and how it is measured within cleanroom environments.
In a cleanroom ACH is measured by determining the volume of air supplied to the room and dividing it by the room volume. It is not measured directly as a single parameter but calculated from airflow measurements.
The core calculation is:

Regulatory guidance, including the European Pharmacopoeia (EU) and the Pharmaceutical Inspection Co-operation Scheme (PIC/S) Annex 1 (2022), do not prescribe fixed ACH values. However, the ACH is expected to be calculated to demonstrate that airflow is sufficient to maintain the required cleanroom classification. This needs to be established during initial cleanroom qualification and verified periodically.
Typical industry ranges are:
| Grade | Typical ACH |
| Grade B | 20-60 ACH |
| Grade C/D | 10-25 ACH |
Air change rates in a cleanroom are determined by measuring total supply airflow (via velocity or airflow hoods) and dividing by room volume. This calculates how many times the air is replaced per hour. The measurement of airflow can be performed in different ways 2:
1. Supply air velocity measurement
This requires measuring air velocity at HEPA filter face or supply diffusers using an anemometer (hot-wire or vane design). With the readings taken, the next step is to multiply:

Then, take the sum of all the supply points within the cleanroom.
2. Airflow hood
This method requires the placement of a balometer / airflow hood over each supply diffuser, which directly measures volumetric airflow (m³/hr).
3. Duct airflow measurement
This method requires measurements of the flow inside Heating, Ventilation and Air Conditioning (HVAC) ducts to be taken, using a Pitot tube and flow stations.
Of the three methods, the supply air velocity measurement is the most common. There are some indirect methods as well - these should not be used instead of the above methods, but they can support the assessment. These methods are:
Using data collected from either the supply air velocity measurement or from the air hood, an example ACH calculation is:

As well as periodic testing (e.g. every six months for higher grade cleanrooms or annually for lower grade cleanrooms), it is also important to reassess ACH values after any HVAC changes, especially room supply fans.
There is a strong interest in reducing ACH in cleanrooms because HVAC systems are one of the largest energy consumers in pharmaceutical manufacturing. ACH is a primary driver of that energy use 3.
Cleanrooms require:
This means the higher the ACH, the more air that must be moved, filtered, heated/cooled - hence the higher the fan power and conditioning load. In other words, energy demand increases roughly in proportion to airflow volume, but fan energy can increase exponentially with flow rate.
A major draw on energy is the fan. Fan power ∝ (airflow) (as an approximate relationship). Therefore, even a small reduction in ACH can deliver large energy savings. For example, reducing ACH by 20% can reduce fan energy by ~40–50%. Since cleanroom performance depends more on airflow design than ACH alone, many firms are seeking to optimise airflow. While this is laudable, the impact on contamination and other factors must be assessed 4.
A suggested approach is 5:
Check that environmental performance is maintained
Assess recovery capability
Examine airflow effectiveness
Perform a Quality Risk Assessment based on
An example risk assessment, for a Grade C room, can be used to assess whether a room is suitable for ACH reduction:
| Factor | Risk level | Rationale |
| Room grade (C) | Moderate | Less critical than Grade A/B |
| Process type | Low–moderate | Closed/semi-closed |
| Operator density | Moderate | Intermittent occupancy |
| Historical EM data | Low | Stable over 2+ years |
A risk-based approach would also reduce ACH rates gradually and assess each step. For instance ACH reduction in controlled phases:
| Phase | ACH | Duration | Controls |
| Baseline | 22 | - | - |
| Step 1 | 18 | 4 weeks | Enhanced EM |
| Step 2 | 15 | 4 weeks | Enhanced EM |
| Step 3 | 12 | 8 weeks | Full qualification |
Reducing ACH is pursued because cleanroom airflow is a major driver of energy consumption, and optimising (rather than maximising) airflow can deliver substantial cost and sustainability benefits without compromising GMP compliance when supported by robust performance data6.
This article has looked at Air Changes per Hour and how they can be measured within the cleanroom. As the article has pointed out, ACH values are an important part of contamination control within the cleanroom. However, ACH is not the most important measure (at least not alone). Contamination control experts need to be mindful of factors like:
Indeed, it can be a common pitfall to assume that ACH alone ensures compliance
1. Fernández M. Airflow reduction in cleanroom operations: HVAC optimisation strategies. Pharmaceutical HVAC. 2025
2. Xu T. Considerations for efficient airflow design in cleanrooms. Berkeley (CA): Lawrence Berkeley National Laboratory; 2004
3. Hart A. Airflow reduction in cleanrooms after closing hours: case study. ISPE; 2020
4. Chen Y, Li N, Zhao Y, Zhao W. Study on energy consumption influencing factors of HVAC systems for cleanrooms in semiconductor fabs. In: Proc Int Conf Civil Engineering and Architecture. Singapore: Springer; 2024
5. Loomans MGLC, Molenaar PCA, Kort HSM, Joosten PHJ. Energy demand reduction in pharmaceutical cleanrooms through optimisation of ventilation. Energy Build. 2019;202:109346
6. Zeng X, Li C, Li X, Mao C, Li Z, Li Z. Energy efficiency optimisation of air conditioning systems towards low-carbon cleanrooms: review and future perspectives. Energies. 2025;18(13):3538