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Microorganisms – a) virus; b) bacteria; c) archaea; d) yeast; d) mold.

Each year, on the first morning of STLE’s Metalworking Fluid Management Certificate Training Course, I ask attendees about their backgrounds. Invariably, the majority have at least undergraduate degrees in chemistry, engineering, or chemical engineering. However, of the more than 600 people who have taken the course since 2004, fewer than 50 have had a microbiology course.

Globally, biodeterioration – damage that organisms cause – has been estimated to range between $100 billion and $500 billion annually. Of this, 70 % to 80 % of biodeterioration damage is caused by microorganisms. Add to this an estimated $1 trillion cost due to infectious disease. On the flipside, biotechnology is a $500 billion industry that is based on microbiology. Just considering the economic impact microbe have on our lives, one might reasonably ask why so few people have received the most rudimentary education about microbes. Perhaps it’s the six syllables in microorganism (mic-ro-org-an-is-m) and microbiology that make the topic so intimidating. Still, given the role of microbes in disease, nature’s primary cycles, and biotechnology, one might think that every high school graduate would have learned something about microbiology. In this post and the next several to follow, I will do my best to demystify microbiology.

In this month’s article and those that follow, I’ll offer a very superficial overview of microbiology from an ecological and industrial perspective. There are numerous, excellent introductory microbiology textbooks. I don’t intend to provide any level of detail approaching that of a microbiology textbook. My intention is to help non-technical readers gain a fundamental appreciation for how microbes can affect their lives and their businesses.


Microorganisms (micro – meaning: small + organism – meaning: something having many related parts that function together as a whole) are living things that are too small to be seen by the naked eye. Microbiologists agree that bacteria, archaea, and some fungi (yeasts and molds) are microorganisms.

The status of virus is still a matter of debate. Viruses are essentially genetic material packaged in a protein coat. They don’t perform most of the functions that are used to define living beings. Thus most microbiologists do not consider viruses to be life forms. However, viruses reproduce by infecting cells and hijacking their victim’s (host’s) metabolic machinery to reproduce. Consequently, some microbiologists believe viruses should be classified as living things. Image (a) in the title figure shows a tobacco mosaic virus (TMV). The TMV virus is structurally complex, regardless of how we classify it. I included a virus in the in the figure because there are research groups investigating the use of viruses to control microbial contamination in industrial systems. I’ll return to this topic in a future post.


One recent study, illustrated in Figure 1, estimated that microorganisms represent ~17% of Earth’s total biomass (estimated total biomass 550 gigatons of carbon – Gt C; 1Gt = 109 tons – and bacterial biomass ≈70 Gt)1. The contribution of bacteria to the Earth’s biomass is second only to that of plants. Microorganism biomass – including that of archaea, bacteria, fungi, protists, and viruses – account for ~93Gt.

A microbiome is the population of all microbes living in a specific ecosystem (fuel tank, cooling tower, human gut, etc.). Researchers investigating the human microbiome have estimated that the average human body has between 1x to 10x as many microbial cells as human cells. Moreover, it has been discovered that tissues, long thought to be microbe-free, have specific microbiomes that are likely to be essential for healthy tissue function (we have known about skin and gut microbes for nearly 170 years, but finding microbiomes specific to nearly every human tissue type (organs, muscle, etc.) was a surprise. Investigators have only scratched the surface of human microbiome research. We have little idea of how microbes interact with human cells and what roles they play in maintaining good health.

Fig 1. Relative abundance of Earth’s lifeforms, in Gt.


As I will explain in future articles, the microbial world is remarkably diverse. The number of different types of bacteria has been estimated to range from hundreds of thousands to tens of millions, of which only a fraction of a percent has been identified.

I’ll discuss why below. Despite their central importance to life as we know it, even the most rudimentary discussion of microorganisms or microbiology (i.e., the study of microorganisms) is rarely included in high school or university curricula.

A Brief History

Tree of Life

Microbes were the first organisms to exist on earth. Our current understanding is that Earth formed 4.6 billion (4,600,000,000) years ago. There is evidence that the first microbes came into existence approximately 3.5 to 3.8 billion years ago (the fossil record indicates that mammals appeared 65 million years ago, and humans showed up a mere 315,000 years ago). Figure 3 illustrates the life on Earth timeline. The bar illustrating Earth’s age is 5 inches (in) long and the one for microorganisms is 4.1 in long. By comparison, the one for plants is 0.2 in and the one for humans is 0.000003 in – too thin to see! Thus, for more than 3 billion years, microbes were the only life forms on Earth.

If we visualize life as a tree, the organisms began to diversify genetically approximately 3.2 to 3.5 billion years ago (Figure 3). This was the time of the last universal common ancestor – LUCA – of all cellular organisms, starting with the bacteria and (thus far) culminating in humans. Before the microbes now classified as members of the kingdom Archaea were discovered near ocean floor, thermal vents in the Marianas Trench, in 1960, the tree of life was thought to have three Kingdoms: Monera (Prokaryota – all single cell organisms that do not have a nucleus or other membrane-bound internal bodies, Protista – all single cell organisms with a nucleus and other membrane-bound bodies, and Eukaryota – all multicellular organisms). As depicted in Figure 3a, in the 1960s through 1990s, Archaea were classified as Archaebacteria. When viewed through a microscope, they appeared to be bacteria. Believing that conditions around Marianas Trench thermal vents was similar to those of primordial Earth, microbiologists initially assumed that Archaea were more ancient than true bacteria – Eubacteriales. As genetic tools became available in the early 1990s, it became apparent that a) Eubacteriales are more ancient than Archaea (Figure 3b), and b) the Archaea are sufficiently distinct genetically to be its own phylogenic Kingdom (phylogenics – the study of evolutionary development and diversification of a species or group of organisms). When Figure 3a was created, fungi were thought to be much more ancient than plants or animals. As Figure 3b illustrates, the phylogenetic tree of life branched off to fungi, plants, and animals a mere half-billion years ago. Thus, fungi are more closely related to us than they are to bacteria.

Fig 2. Timelines – microorganisms appeared approximately 1 billion years after Earth was formed and more than 3 billion years before the first plants appeared. Brown bar – Earth’s age; blue bar microorganisms’ age; green bar – time since plants first appeared; yellow bar – time since first animals appeared; purple bar (invisibly narrow line) – time since humans appeared.

Fig 3. Phylogenic trees – a) Tree from mid-1960s depicting Archaebacteria as being more ancient than Eubacteria; b) Woese et al. (19902) phylogenic tree showing three Kingdoms – Bacteria, Archaea, and Eucarya. Line segment lengths are based on genetic differences (longer lines indicate greater differences). The initial split at bottom center is LUCA.

Genomic testing has been a cottage industry since the late 1990s. A recent diagram (Figure 4) is based on the genomics of 2.3 million different species, from bacteria to humans, illustrates how complex the Tree has become (or as some authors note, the Tree now looks more like a Bush).

Fig 4. 2015 Tree of Life based on genetic data from 2.3 species.3

Human Awareness

Humans have been using microbes from time immemorial. We have been fermenting grains and grapes, and making cheeses, for as long as we have been cultivating plants or maintaining livestock. Modern microbiology dates from 1665, when Roert Hooke published Micrographia: or some Physiological Descriptions of Minute Bodies made by Magnifying Glasses with Observations and Inquiries Thereupon. A decade later, Antonie van Leeuwenhoek published his observations. Hooke and van Leeuwenhoek had each constructed microscopes through which they observed and created sketches of microorganisms (Figures 5a and 5b). However, it took another 200 years before Louis Pasteur and Robert Koch demonstrated that microbes were living beings and were responsible for fermentation, disease, and spoilage.

Fig 5. First microscopes – a) replica of Robert Hook’s microscope; b) replica of Antonie van Leeuwenhoek’s microscope.

Louis Pasteur conducted experiments to disprove the theory of spontaneous generation (belief that microbes developed from inanimate components of the materials which they caused to rot) and prove the germ theory of disease (i.e., that microorganisms did not form spontaneously and that they caused disease, biodeterioration, and were the agents responsible for fermentation). Pasture used goosenecked flasks (Figure 6) to demonstrate that microbes did not proliferate (multiply) in broth boiled in the flasks but did in identical flasks that contained unboiled broth. Proliferation also occurred when Pasteur intentionally permitted boiled broth to be exposed to microbially contaminated air (i.e., either by breaking off the gooseneck or tipping the flask). The gooseneck shape allowed air but not microbes to enter the flasks. These experiments led to Pasteur’s development of the pasteurization – the process of heating substances at temperatures sufficient to disinfect but not degrade them.

Fig 6. Drawing of Louis Pasteur’s gooseneck flask used to disprove spontaneous generation theory.

While Pasteur was focusing on fermentation microbiology, Robert Koch demonstrated the unequivocal relationship between microbes and disease. Koch demonstrated that the disease, anthrax was caused by the spore forming bacterium, Bacillus anthracis. He also developed the first solid growth media so that he could isolate pure cultures from colonies (Figure 7, zone 5). Pasteur’s and Koch’s research launched the modern age of microbiological research.

Fig 7. Obtaining a pure (single type of bacterium) culture by the streak plate method – a) specimen is collected using a sterilized inoculating loop; b) successively, initial specimen is deposited onto solid nutrient medium using a back-and forth motion (1), inoculating loop is heat sterilized, cooled, and oved across initial inoculation zone (2). This dilutes the sample. The final iteration (5) typically produces individual colonies after the inoculated plate has been incubated.

As now, much of the research performed during the late 19th century was focused on the relationship between microbes and disease. However, Sergei Winogradsky became the father of microbial ecology. Based on his pioneering research on sulfur metabolism in the late 1880s, Winogradsky developed the theory of biogeochemical cycles. This theory states that elements like sulfur, carbon, nitrogen, and phosphorous cycle through nature (Figure 8). These cycles are primarily mediated by microbial activity. The first paper describing gasoline deterioration by microbes was published in 1895. Starting in the 1920s, considerable effort was focused on oilfield damage caused by microorganisms. This research included the first studies on what was originally called microbially induced corrosion (MIC – now microbiologically influenced corrosion – see MICROBIOLOGICALLY INFLUENCED CORROSION – Biodeterioration Control Associations, Inc. ( However, the term biodeterioration was not coined until 1965, when H. J. Hueck offered the definition: “any undesirable change in the properties of a material caused by the vital activities of organisms.”4

Fig 8. Biogeochemical cycles – this illustration provided a simplified depiction of how carbon (C), nitrogen (N), phosphorous (P), and sulfur (S) cycle through nature.

In my seminars on the topic I explain that biodeterioration and bioremediation are two sides of the same biodegradation coin (Figure 9). As Winogradsky observed, microbes drive biogeochemical cycles. These cycles occur regardless of human intent. When we want biodegradation to occur, we call it bioremediation. When microbial activity causes changes, we’d prefer to prevent, we call it biodeterioration (see

Fig 9. Like the obverse (front) and reverse (back) sides of this 2000 Sacagawea U.S. dollar coin, bioremediation and biodeterioration are flips sides of biodegradation.


Microbes play invaluable roles in our lives. Our bodies would not function without the microbes that make up he human microbiome. Fewer than 2,000 pathogenic microbes have been identified among the tens of thousands that have been identified and the millions of different types of microbes that exist in nature. Microbes mediate nutrient cycles. This cycling conserves essential nutrients and prevents wastes from accumulating. Biodegradation includes all processes that breakdown organic substances. On one hand, biodegradation is the foundational element of a $0.5 trillion biotechnology industry. On the other, biodeterioration and infectious disease cost $1.5 trillion per year. We are part of the microbial world. To me, that seems like an excellent reason why everyone should have a basic understanding of microbiology.

For more information about fuel system condition monitoring and predictive maintenance, contact me at

1 Bar-On, Y.M, Phillips, R., Milo, R., 2018. The biomass distribution on Earth. Proc Natl Acad Sci U S A., 115(25):6506-6511.
2 Woese, C. R., Kandler, O., Wheelis M.L., 1990. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya. Proceedings of the National Academy of Sciences of the United States of America. 87 (12): 4576–9.
3 Hinchliff, C. et al., 2015. Synthesis of Phylogeny and Taxonomy Into a Comprehensive Tree of Life. Proceedings of the National Academy of Sciences
4 Hueck, H.J., 1965. The Biodeterioration of Materials as a Part of Hylobiology. Material und Organismen, 1, 5-34.


Leaking underground storage tank. Microbiologically influenced corrosion (MIC) created numerous holes in this home heating oil fuel tank.


AMPP (formerly NACE) and ASTM define corrosion as “the deterioration of a material, usually a metal, that results from a chemical or electrochemical reaction with its environment” (ASTM Terminology G193). AMPP defines microbiologically influenced corrosion (MIC) as “corrosion affected by the presence or activity, or both, of microorganisms.” The AMPP definition of MIC adds: “The microorganisms that are responsible for MIC are typically found in biofilms on the surface of the corroding material.”


A 2016 NACE study estimated that globally the cost of corrosion was $2.5 trillion U.S. ($2,500,000,000,000).

A 2022 Ohio University study suggested that damage attributed to MIC represented 20 % of the total, or $500 billion U.S.

Historically, MIC was the acronym for microbially induced corrosion, and later, microbiologically induced corrosion. Well into the 1990s, the prevailing theory was that MIC was primarily caused by a process called cathodic depolarization (more on that below). By the end of the 1990s, most investigators recognized that MIC was more complicated and that is was more common for microbes to influence rather than cause MIC. Conveniently, the MIC acronym worked as well for microbiologically influenced corrosion as it did for microbially induced corrosion and microbiologically induced corrosion.

AMPP TM0166 Detection, Testing, and Evaluation of Microbiologically Influenced Corrosion (MIC) on External Surfaces of Buried Pipelines provides an excellent overview of MIC. Although the document’s focus is pipeline corrosion, the general principles it describes are generally applicable. TM0166 is a consensus standard. There are also several excellent books that cover MIC in detail. A few of my favorites include:

  • Manual of Biocorrosion, H. A. Videla, CRC Press, Boca Raton, 273 pp, 1996, ISBN 0-87371-726-0
  • Microbiologically Influenced Corrosion, B. J. Little and J. S. Lee, John Wiley & Sons, Inc. Hoboken, 279 pp, 2007, ISBN 978-0-471-77276-7
  • CorrCompilations: Introduction to Corrosion Management of Microbiologically Influenced Corrosion, R. Eckert, AMPP, Houston, 489 pp, 2015, ISBN 978-1-575-90285-2

Additionally, a substantial body of MIC literature has been published in the past decade. In January 2023 alone, 180 peer-reviewed papers were published. A citation service (ScienceDirect) search of papers published since 2010 listed more than 8,000 publications. Consequently, in today’s article, I’ll share only a bit of history and a offer superficial overview of MIC.

Cathodic Depolarization Theory

A relationship between microbial contamination and corrosion has been recognized since the late 19th century. By the mid-20th century, researchers were in general consensus about the relationship between biofilms and MIC (for a refresher on biofilms, see my May and August 2022 What’s New articles). However, the mechanisms are still being investigated. One the earliest models – cathodic depolarization – was proposed in the 1930s. According to this model, when a metal surface is exposed to water, metal dissolution can occur. At the anode, positively charged metal ions (Me2+) form (in the case of iron – Fe – ferrous – Fe2+ – ions form), releasing two electrons (e) per metal ion (Table 1, Reaction 1). The electrons migrate to the cathode where they bond with hydrogen (H+) ions (Table 1, Reaction 3) dissociated from water (Table 1, Reaction 2) to passivate the cathode. Sulfate reducing bacteria enzymes utilize the hydrogen ions from the cathodic surface and catalyze sulfate reduction to sulfide (Table 1, reaction 4). The dissolved Fe2+ ions react with sulfide (S2-) and hydroxide (OH-1) to form ferrous sulfide (FeS) and ferrous hydroxide (Fe(OH)2) deposits (Table 1, Reactions 5 and 6, respectively). The mechanism is illustrated schematically in Figure 1.

Table 1. MIC SRB-mediated cathodic depolarization.

Fig 1. Cathodic depolarization. Numbers in circles refer to reaction numbers listed in Table 1. Hydrogen coating at cathode passivates surface – inhibiting electron flow. SRB-mediated hydrogen utilization depassivates the cathode and promotes electron flow.

The early discovery of the relationship between SRB and MIC continues to influence how investigators think about MIC to this day. However, it is now recognized that SRB-mediated cathodic depolarization is only one MIC mechanism.

Common Denominator

The definition I quoted in the second sentence of this article is quite broad. Microbiologists and corrosion engineers now recognized that microbes influence corrosion through a variety of mechanisms in addition to cathodic depolarization. However, MIC is invariably associated with biofilms. The presence of biofilm creates an electropotential gradient between biofilm-free surfaces and those beneath biofilm polymer – extracellular polymeric substances (EPS). Figure 2 is from one of my fuel microbiology course modules. It illustrates the oxygen concentration ([O2]) as a function of distance from the bulk fluid to deep within a biofilm matrix. Aerobic (bacteria that require O2) and facultatively anaerobic bacteria (bacteria that use O2 for respiration when it is available then switch to fermentation when the [O2] is insufficient to support aerobic respiration) that are part of the biofilm microbiome scavenge and thereby deplete O2 (a microbiome is all the microorganisms present in a specific environment) from the biofilm matrix. Near the biofilm surface that is in contact with the bulk fluid (e.g., water, fuel, water-miscible metalworking fluids, etc.), diffusion is sufficient to keep the [O2] close to saturation (O2 saturation concentrations are temperature dependent). At 20&deg C 100 % saturation in water = 8.77 mg L-1 . Deep within a biofilm, [O2] can be <0.4 mg L-1anoxic.

Fig 2. Oxygen gradient between bulk fluid and depths of biofilm matrix.

Although biofilms can develop from a single microbe, more commonly, biofilm microbiomes include a variety of microbes. As I discussed in May 2022, both the types of microbes and their respective physiologies vary depending on their location within a biofilm community. Consequently, although MIC encompasses several different types of corrosion processes, biofilm presence is the common denominator.

MIC Mechanisms

Sulfate reduction

As discussed under Cathodic depolarization, sulfate reducing bacteria (SRB) and archaea (SRA) – collectively referred to as sulfate reducing prokaryotes (SRP) utilize SO42- instead of O2 for respiration. The process – called dissimilatory sulfate reduction – generates H2S (Table 1, Reaction 4). When ferrous iron (Fe2+) is present, the H2S react with Fe2+ to produce ferrous sulfide (FeS – Table 1, Reaction 5). Deposition of FeS one ferrous metal surfaces stimulate the galvanic cell’s (Figure 1) cathodic reaction – accelerating the corrosion rate.

Acid production

Nominally, acid producing bacteria (APB) defines a category of bacteria that produce organic or inorganic acids. Classifying microbes as APB is arbitrary. The metabolic pathways by which all organisms generate energy produce low molecular weight (C1 to C6) organic acids (LMWOA) – mono-, di-, and tricarboxylic acids (Table 2). Thus, all microorganisms are acid producers. However, there are some classes of bacteria that generate greater yields (i.e., mg acid excreted per cell) than others. For example, bacteria in the Family Acetobacteraceae ferment sugars and ethanol to acetic acid (the metabolic processes the convert wine into vinegar).

Table 2. Low molecular weight organic acids produced as energy metabolism metabolites.

These LMWOA can attack metals directly. When chloride, sulfate, nitrate, or nitrite salts are present, they can react with LMWOA to form strong inorganic acids (hydrochloric, sulfuric, nitric, and nitrous, respectively) and weak organic bases. The strong inorganic acids are aggressively corrosive.

Metal deposition

Iron oxidizing bacteria and manganese oxidizing bacteria form metal oxides and hydroxides that typically take the form of tubercles (Figure 3). Oxygen becomes depleted under the deposits. This creates the anode terminal of a galvanic corrosion cell.

Fig. 3. Iron oxide corrosion tubercles on interior surface of a firemain line. Source: Scott McNamara, Liberty Corrosion Solutions

Metal reduction

Respiration is the process by which organisms obtain energy. The last step in respiration is the release of an electron which transfers to a terminal electron acceptor. For all aerobic organisms O2 is the terminal electron acceptor. In anaerobic respiration a different molecule serves this role. SRP use SO42- as a terminal electron acceptor. Other microbes can use nitrate (NO3), nitrite (NO2), ferric iron (Fe3+), or manganese (Mn) as terminal electron acceptors. Microbes that use either iron o manganese for respiration are called metal reducing bacteria (MRB). Ferric iron is reduced to ferrous (Fe2+) and Mn4+ is reduced to Mn2+ both of which are water soluble. Thus, MRB dissolve metal oxides, thereby accelerating localized corrosion.

Hydrogen embrittlement

Hydrogen embrittlement occurs when hydrogen atoms permeate metals. Figure 4 shows an intergranular crack cause by hydrogen embrittlement in steel. Hydrogen accumulates at the cathodic end of galvanic reaction cells. For example, it is a biproduct of dissimilatory sulfate reduction and other metabolic processes. Thus, the hydrogen that accumulates around the cathode can infiltrate steel’s intergranular spaces. This most commonly occurs in systems using cathodic protection too aggressively.

Fig 4. Hydrogen embrittlement stress cracks formed between metal grains of a steel specimen. Source:

MIC Morphology:

Historically, it was a believed that pitting corrosion was diagnostic for MIC. However, we now know that abiotic mechanisms can cause MIC and that MIC can cause both localized (e.g., pitting) and more general corrosion. This means that visual (with or without microscopy) observation of corrosion patterns is insufficient to diagnose. Correct diagnosis is made even more challenging when the corrosion is inside tanks. Health and safety-focused regulations typically require that tanks been cleaned and rendered gas-free before inspectors can enter them. The processes that render the space safe for entry also disrupts or destroys much of the evidence. As illustrated in Figure 5, regions of heavy biofilm accumulation are apparent in this UST. In the 1980s, when this photo was taken, an inspector could enter the tank (wearing appropriate personal protective equipment) and collect surface swab, scrape, and fluid samples. Those samples could then be tested microbiologically and chemically (for organic chemical composition and minerology) to facilitate diagnosis. Confined space entry practices used today, remove most of the residue visible in Figure 5 before an inspector is permitted to enter the tank. Thus, although we know considerably more about MIC today than we did half a century ago, there are still considerable challenges to timely and accurate diagnoses in systems likely to be affected by MIC.

Fig 5. UST interior view, after product removal but before tank cleaning. Note bands of heavy slime accumulation 15° either side of bottom dead center. Numerous corrosion pits were observed under these slime-covered regions.


Our understanding of MIC continues to evolve. Analytical tools that are currently available did not exist in the 1930s when the seminal papers describing MIC were published. There are several well documented MIC mechanisms. All are associated with the presence of biofilms. Moreover, observing pitting corrosion is no longer recognized as a sufficient basis for diagnosing MIC.

For more information about fuel system condition monitoring and predictive maintenance, contact me at


Bottom sample from ultra-low-sulfur diesel tank showing hazy fuel over bottoms-water loaded with suspended solids.

Opportunity Cost

In two previous articles, I’ve discussed the opportunity costs associated with premature filter plugging (see November 2016 and February 2019). My November 2016 article focused on the disconnect between operator awareness and the actual incidence of substantial contamination in underground storage tanks (UST) and fuel transfer equipment between UST and dispensers. In February 2019, I presented an opportunity cost calculation model that I had first suggested to fuel retailers in 1992. My 2019 calculations were based on unleaded gasoline sold at $2.30 U.S. per gal. Today, as I passed several forecourts gasoline prices ranged from $2.60 to $2.80 per gal and ultra-low-sulfur diesel (ULSD) prices were more than $6.00 U.S. per gal. In my February 2019 article I defined opportunity cost as follows (note: the maximum permitted flow rate at commercial dispensers is 40 gpm):

Opportunity cost is the difference between the economic value of the theoretically optimal use of an assist and the value realized by its actual use. At fuel retail sites that experience rush hour peaks, where the dispenser flowrate is the primary factor controlling fuel sales revenues, the opportunity cost is the difference between sales generated while dispensing at 10 gpm (U.S. EPA’s maximum permissible flowrate at retail dispensers) and sales generated while dispensing at slower flowrates.

If you assume that dispensers can operate for a maximum of 30 min per hour – allowing 30 min per hour for payment and vehicle movement), a commercial dispenser can deliver 1,200 gph. At $6.00 gal-1 , that generates $7,200 gross revenue. For each 1 % of flow rate reduction, the opportunity cost is $72 h-1 . That doesn’t seem like much but, if flow rate is the limiting factor for 4h day-1 , the opportunity cost per dispenser per year is $105,000 for each 1 % of flow rate below the 40 gpm maximum.

Case Study

Since I first started providing fuel retailers with my opportunity cost model in 1992, few have been willing to check their flow rates and test my calculations. However, my cost model was validated in an article the that appeared in the 3rd quarter issue of PEI Journal (Vol 16, Issue 3). The title of the article was Preventing Fuel Contamination Issues by Bill Jones and Jessica Montgomery of Warren Rogers and Clean Fuels National, respectively. The article is a case study that illustrated the impact of maintaining clean fuel systems on opportunity cost.

Predictive Maintenance

In their PEI article, Jones and Montgomery advocated for a predictive maintenance approach (see What’s New December 2016, and January 2017), using flow rate testing as a fast and easily performed routine check. As shown in Figure 1a, five-weeks after new filters were installed, flow rates began to decrease. Jones and Montgomery noted that it is important to run flow rate tests during quiet periods. At sites with submerged turbine pumps (STP) that were under-capacity, flow rates were affected by the number of dispensers operating simultaneously (Figure 1b). At this site, flow rate testing at each dispenser needed to be performed when no other dispensers were operating.

Fig 1. Retail gasoline dispenser flow rate testing – a) flow rate as a function of time in service since last filter change; b) flow rate as a function of the number of dispensers operating simultaneously (from Jones and Montgomery, PEI Journal, 16(3): pp 26-32).

Corrective Action Impact

Jones and Montgomery reported the impact of contaminant removal (UST system cleaning) on daily fuel sales volumes (Figure 2 – Figure 1-4 in the PEI article). The figure did not identify which dispensers handled unleaded gasoline and which handled ULSD. Nor did Jones and Montgomery report the impact of tank cleaning on the time lapse between new filter replacement and flow rate degradation. I always recommend recording dispenser totalizer readings when changing filters. Premature filter plugging (e.g., flow-rate reduction) relates to how many gallons have been filtered before flow rate (or pressure differential) is affected. When the fuel is clean, a 10 µm dispenser filter should be able to process at least 500,000 gal before the flow rate decreases by 10 %. In the case of dispensers H18 and H19 – each delivering approximately 4,000 GPD – that translates to approximately 4 months (125 days) of at least 90 % maximum flow rate. For the lower volume dispensers (H9, H10, H11, H12, and H17) that handled approximately 200 GPD, filter performance life should be years. Here, I’ll focus on the impact of tank cleaning on dispenser H18T to illustrate the opportunity cost associated with premature filter plugging. After tank cleaning and fuel polishing:

  • Average daily sales increased by approximately 2,400 gallons.
  • If the product was ULSD @ $6 gal-1 , after cleaning, H18 generated an additional $14,400 gross revenue per day, or $5.3 million per year.
  • If the product was regular unleaded gasoline @ $4 gal-1 , after cleaning, H18 generated an additional $9,600 gross revenue per day, or $3.5 million per year.

Table 1 summarizes the net additional revenue for all the dispensers at which substantial fuel sales volumes were observed. Although sales at several dispensers decreased (the article made no mention of other contributing factors), the net increase was 1,200 GPD (438,000 gal per year). I used current fuel pricing here in the Princeton New Jersey area to compute the sales $s impact.

Fig 2. Effect of tank cleaning on fuel sales volumes (from Jones and Montgomery, PEI Journal, 16(3): pp 26-32).

Table 1. Effect of tank cleaning on revenues (data taken from Figure 2).

Bottom Line

In 1992, when I founded BCA, I shared an opportunity cost calculation tool with prospective fuel retailer clients. Thirty years later, a case study reported in PEI Journal validated the opportunity costs estimated in my model.

There are factors other than filter plugging that affect dispenser flow rates. The most common is pump power insufficient to deliver maximum permissible flow to all dispensers when customers are fueling at multiple dispensers. In my March 2021 What’s New post, I summarized other common causes of fuel system flow rate reduction.

There are factors other than uncontrolled microbial contamination that contribute to premature (i.e., >10 % flow rate reduction before 500,000 gal have been filtered) filter failure. However, uncontrolled microbial contamination is one of the most common causes.

Cost effective condition monitoring relies on tiered testing (see What’s New, February 2017) in which a fast, easily performed test is run most frequently and more diagnostic tests are run when the results from the frequently run test are at or above their control limit (see What’s New, October 2020). The Jones and Montgomery case study article published in PEI Journal (Volume 16, Issue 3, 2022) demonstrates the value of both tiered condition monitoring and linking test results to appropriate actions.

For more information about fuel system condition monitoring and predictive maintenance, contact me at


International Association for Stability, Handling and Use of Liquid Fuels (IASH)

IASH was founded in 1983 when Nahum Por, a chemist at Oil Refineries Ltd., Haifa, Israel, obtained support from the Israel Institute of Petroleum & Research to sponsor a conference to discuss issues related to the stability and handling of liquid fuels. The focus was on fuels and crude oil stored as strategic reserves. Between 1983 and 2003, IASH met triennially – venues alternating between Western Europe and North America. Since 2005, the society has been meeting biennially. The association is intimate (approximately 200 members) but include an international group of subject matter experts and people responsible for intermediate to long-term fuel storage. Invariably topics addressed during IASH Conferences range from practical fuel storage and condition monitoring considerations to esoteric explorations of fuel deterioration physicochemical processes. Each conference has included a half-day fuel microbiology session.

I have been attending the IASH conferences since the 1991 Orlando, FL meeting. I have yet to be disappointed by the quality of the presentations and the number of new insights I gain from the speakers. September’s conference in Dresden was no exception.

IASH 2022

The 17th International Conference on the Stability & Handling of Liquid Fuels (IASH 2022) was held in Dresden from 11 through 15 September. In keeping with the precedents set at the previous 16 conferences, the program included excellent papers covering the gamut of fuel quality and stability issues (visit Dresden Agenda ( to see the conference program). This year’s conference included many papers addressing sustainable fuels – particularly sustainable aviation fuels (SAF) – and fuel quality modelling. I was particularly encouraged to see many younger participants presenting their research. Typically, the conference proceedings are available form the IASH website (Home ( three to five months after the meeting. If you are particularly interested in any of the presentations, you can contact the authors directly for copies of their papers or presentations. I won’t attempt to provide a synopsis of every session or paper presented in Dresden. Instead, I’ll focus on the fuel microbiology papers.

IASH 2022 Fuel Microbiology Presentations

Detection Technologies

Dr. Jiri Snaidr of Vermicon AG (Hallbergmoos, Germany) reported on the development of a gene probe system for detecting specific microbes in fuel systems. The prototype flow cytometry system relied on fluorescent dye linked, ribonucleic acid (RNA) to label target microbes. After specimens are stained, they are drawn through a flow cytometer. Each target microbe is stained with a dye that fluoresces at a different wavelength so that the abundance of each organism can be quantified. Over the past decade, a new generation of flow cytometer has been developed that has made the technology an increasingly useful tool for quantifying microbial contamination in liquids. There are several challenges related to the use of flow cytometry for microbial contamination in fuels. As I’ll discuss below, the variety of microbes and types that exist in different fuel systems is considerable. Probes designed to detect specific microbes are likely to miss others that might be present. Additionally, microbial population densities in fuel samples is likely to be <1 cells mL-1 . This means that in order to reliably detect fuel contaminant microbes, specimens will need to be ≥1 L.

Dr. Osman Radwan of University of Dayton Research Institute (Dayton, OH, USA) discussed the use of an electrochemical biosensor to detect biofilm development on fuel system surfaces. Dr. Radwan’s multi-phase, fluidic device is comprised of an array that is pretreated with a protein molecule believed to be universally present among fuel degrading fungi (i.e., a biorecognition element – BRE). When microbes are bound to the protein, they generate an electrochemical signal. To date, Dr. Radwan and his colleagues have performed in-lab tests demonstrating their ability to detect filamentous fungi and single-cell yeasts. One challenge common among devices such as the one that Dr., Radwan described is that the sensor quickly becomes saturated. The sensors detect initial biofilm formation but cannot differentiate between a 10 µm or 1,000 µm thick film. It is generally recognized that fuel and fuel system biodeterioration are primarily due to the activities of biofilm communities. Thus, being able to assess three-dimensional biofilm growth is an important requirement for surface sensor arrays. Both Dr. Snadir and Dr. Radwan presented cutting edge technologies that are likely to take years of further development before they will be ready for commercial deployment, but their work is exciting and points towards the future.

Biodeterioration Mitigation and Contamination Control

Graham Hill, of ECHA Microbiology, Ltd. (Cardiff, Wales, UK) discussed the relationship between salinity and sulfate reducing bacterial (SRB) activity in marine, seawater ballasted, fuel tanks. Microbiologically influenced corrosion (MIC) has been a problem in ships’ fuel tanks since the early 20th century transition from coal to liquid fuels. In order to maintain stability, ships take on seawater as they consume fuel. One of the most serious, unintended consequences of sea water ballasting is that the combination of seawater and fuel create an excellent environment for the proliferation of microbes. Aerobic and facultatively anaerobic microbes scavenge oxygen and produce low molecular weight organic acids on which SRB can thrive. Mr. Hill reported the results of lab-scale tests run at ECHA. His team found that by using freshwater, rather than seawater – i.e., keeping the salinity at <9 g L-1 (the typical salinity of ocean water is 35 g L-1) – reduces SRB activity (sulfate production) substantially.

Dr. Oscar Ruiz, U.S. Air Force research Lab (AFRL, Dayton, OH, USA) reported on successful laboratory tests that demonstrated the efficacy of a graphene oxide (GO), nanoparticle, depth filter to scrub microbes from fuel. Dr. Ruiz report the results of a 227 m3 (60,000 gal) trial. At flow rates ≤ 40 L min-1 (≤10 gpm) the device removed >90 % of the bioburden. At the end of the test the pressure differential across the filter was < 28 kPa (4 psi). Given the increased regulatory pressure against the use of fuel-treatment, antimicrobial pesticides (biocides), filtration is a promising alternative. Traditional filter media develop a cake that improves filtration efficacy to a point. Once the filter has accumulated too much material, pressure differentials increase, and flowrates decrease. If GO media can overcome this limitation, they might change the nature of fuel filtration. Filtration’s primary limitation is that the microbes that pass through the medium can colonize downstream surfaces and form biofilm communities. Filtration does not address biofilm control.

Microbial Ecology

Dr. Gareth Wiliams of ECHA Microbiology, Ltd. (Cardiff, Wales, UK) reported the results of an investigation into the factors contributing to hydrogen sulfide generation in salt caverns in which butane was stored. The ECHA team used quantitative polymerase chain reaction (qPCR) and next generation sequencing (NGS) to identify microbes in salt dome samples. Dr. Williams reported that of three caverns tested, hydrogen sulfide accumulated only in one. However, the microbial population profiles were similar among all three caverns. All three had SRB and Halobacterium species (Halobacterium is a genus within the domain of Archaea). The primary difference among the three caverns was the suction line installation. The cavern in which substantial concentrations of hydrogen sulfide had developed had an irregular floor. The uptake line was above the bottom; allowing brine to accumulate. The uptake lines in the other two caverns were at the bottom. In these caverns there was no bottom brine layer.

I presented NGS genomic data from the CRC-sponsored diesel fuel microcosm study from which I had reported adenosine triphosphate (ATP and adenylate energy charge (AEC) results at ICSHLF 16 in 2019 (The Relationship Between Planktonic and Sessile Mirobial Population Adenosine Triphosphate Bioburdens in Diesel Fuel Microcosms | IASH Online Library of Conference Proceedings and Newsletters ( and The Relationship Microbial Community Vitality and ATP Bioburden in Bottoms Waters Under Fuel Microcosms | IASH Online Library of Conference Proceedings and Newsletters ( – both are accessible to IASH members only. If you cannot access the papers, contact me for copies). Although during the original study (DP-07-16-01-FINAL-REPORT-REV-30JUL21-COMPLETE.pdf ( only a few aqueous phase samples were subjected to NGS testing. We were able to obtain the microcosms after 18-months. Marathon Petroleum, LuminUltra Technologies Ltd., and BCA collaborated to collect samples from the fuel-water interface and aqueous phases f 32 microcosms. LuminUltra Technologies Ltd. Performed the 18-month NGS tests and a different lab had performed the 3-month tests. Among the eight microcosms for which there were data from 3 and 18 months, the genomic profiles of four microcosms had remained stable and those of the other four changed substantially. Duplicate samples from several 18-month microcosms demonstrated that variability among duplicate aqueous samples was excellent but that variability among duplicate interface samples was substantial. Genomic test methods continue to evolve rapidly. As the protocols are refined, it will be essential to understand the sources of variation related to sampling and testing. Without this understanding, results from environmental samples will be difficult to interpret. I’ll devote a future What’s new post to genomics, transcriptomics, and metabolomics.

Lifetime Achievement Award

During the conference banquet I was taken totally by surprise when I was called to the stage to receive IASH’s Lifetime Achievement Award. I confess that when 1 st Vice-Chair, Matt DeWitt announced that it was time to present awards, I commented to my tablemates that these awards have never been given to microbiologists we are such a small minority within the Association. As I was making the comment, I heard my name. Did I mention that I was taken totally by surprise?

The award citation reads:

“By the members of IASH in recognition of his significant technical contributions and leadership related to testing, control and mitigation of microbiological contamination in fuels and oils. His notable technical contributions include over 70 technical publications on fuel, lubricant and metalworking fluid microbiology and biodeterioration. He has had numerous Chair and leadership positions in ASTM, IBBS, and IATA, and contributed significantly to the development of best industry practice documents and guidelines for the prevention and control of microbiological contamination in fuels.”

1st Vice-Chair Matt DeWitt presenting IASH Lifetime Achievement Award to Fred Passman


In summary, the conference was an exceptional opportunity to learn about various aspects of fuel degradability and its control. I most strongly recommend that individuals who are responsible for fuel quality join IASH and make plans to attend future IASH conferences. Again, for more information about IASH, visit Home (

To contact me, please send an email to


Biofilm at Metalworking Fluid Surface – Sump Wall Interface.

Biofilms Part 1 Recap

In my last What’s New article I wrote:

Biofilms can form on any surface that is in contact with water. In aqueous systems such as heat exchanger, potable water, firemain, containing water-miscible metalworking fluid, biofilms can coat >90 % of surfaces in contact with the fluid. In systems containing fuels, lubricants, or other fluids in which water is not normally miscible, biofilms typically develop in zones where condensate water accumulates.

Biofilms are complex structures comprised primarily of EPS. Microbes living in biofilm consortia resemble the cells of multicellular organisms. Physiologically, they can be quite distinct from genetically identical planktonic cells. Additionally, genetically identical microbes can differ physiologically based on their location within the EPS matrix. Due to the combined effects of microbial metabolic activity and EPS chemistry, the physicochemical environment within biofilms can be very different from that of the fluid with which it is in contact. Chemical gradients within biofilms contribute to microbiologically influenced corrosion (MIC).

In this article, I’ll review the types of biodeterioration damage that can be associated with biofilms. In particular, I’ll discuss:

  • Biofouling
  • Heat exchanger, heat transfer reduction
  • Microbiologically influenced corrosion (MIC)


Biofouling is the unwanted accumulation of organisms, their excreted polymers (see EPS discussion in the May 2022 What’s New article), and entrained substances on surfaces. Although multicellular organisms, such as barnacles, can be part of biofouling communities, in this article I’ll focus on microbial biofouling. Figure 1 shows four examples of biofouling. Figure 1a is a fermentation unit’s transfer line. Biofouling contributes to finished product contamination and inhibits flow from the fermenter to the drying unit. Figure 1b is a fouled fuel dispenser filter element. This is the most common cause of reduced fuel flowrates at retail fuel dispensers (in the U.S., fuel should be dispensed at 10 gpm – 40 L min-1; filter fouling can reduce the flowrate to <1 gpm – 4 L min-1). In Figure 1c, biofouling has glued small metal particles (swarf) together in a metalworking fluid (MWF) return line. Swarf is generated during metal removal by grinding. In this pipe, EPS has glued the swarf particles into a solid mass, causing what I call industrial atherosclerosis (atherosclerosis is condition where the arteries become narrowed and hardened due to buildup of fats in the artery wall; industrial atherosclerosis occurs when biofouling narrows the internal diameter of a pipe).

Figure 1d shows biofouling on the surface of an automatic tank gauge’s (ATG’s) water float. In fuel storage tanks, ATGs are used to record both product and bottoms-water volumes. An ATG has two floats that move along a metal shaft. One float (not shown) is designed to rest on top of the fuel’s surface – signaling the total fluid volume in the tank. The water float’s specific gravity (SG) is greater than that of the fuel product, but less than that of water. Consequently, it rests at the fuel-water interface. Biofouling on the water float’s surface can either decrease or increase the float’s SG. If the biofilm has numerous gas pockets, it will decrease the float’s SG and cause it to register the presence of water even when none is present. If the biofilm is loaded with rust particles, it will increase the float’s SG. The float will fail to lift off the tank’s floor when bottom-water is present.

Fig 1. Biofouling – a) Fermenter transfer line; b) fuel dispenser filter; c) MWF used fluid transfer line; d) underground storage tank ATG water float.

In general terms, these four photographs illustrate how biofouling can affect industrial systems. Biofilm microbes on pipe surfaces can contaminate fluids as they flow through the line. Biomass accumulations on filter media can block fluid flow. Biofilm accumulation and the interaction between biofilm polymers and metal fines can restrict fluid flow by reducing the pipe’s functional inner diameter. Biofouling on sensor surfaces can cause sensors to generate inaccurate signals.

Although the next two biofilm-related problems depend on the presence of biofouling, the mere physical presence of biofilms can degrade industrial system operations. Think of this as passive biodeterioration – microbes are not attacking surfaces.

Heat exchanger, heat exchange inhibition

Biofilms are excellent insulators. One report (Biofilm effects on heat transfer of heat exchangers) estimated that a 5 µm thick biofilm can reduce heat exchange across copper tubes, in tube-in-shell heat exchangers, by 67 %. Tube-in-shell heat exchangers are fabricated by placing a tube bundle (Figure 2a) into an outer shell (Figure 2b). The water to be cooled either flows through the outer shell and the cooling water flows through the tubes or the cooling water flows through the outer shell and the water to be cooled flows through the tubes. Either way, the tremendous surface area to volume ratio facilitates heat transfer from the warmer fluid to the cooler fluid. The tubes are commonly made of aluminum, brass, copper, carbon steel, or stainless steel, although other metals are also used. Figures 3a and 3b respectively show heat exchanger biofouling on the exterior and interior tube surfaces. The heavy biofilms depicted in these photographs can reduce heat transfer by > 90 %.

Fig 2. A tube-in-shell heat exchanger – a) tube bundle; b) outer shell.

Thermal conductivity (λ) – expressed as W (m . K)-1, where W is watts, m is meters, and K is temperature in degrees Kelvin – is a measure of the ease with which heat is transmitted through a material. Table 1 provides a list the λ-values for common heat exchanger tube and insulating materials. Although λ is important, other factors such as corrosion and scaling resistance, and durability are considered when selecting heat exchanger materials. Note that λbiofilm is comparable to λdry soil and λwater. All are excellent insulators.

A case study, reporting the impact of a 1 mm of biofilm in a 200-ton centrifugal chiller operating at 50% load, stated that heat exchange was reduced by 35 %.

Fig 3. A tube-in-shell heat exchanger – a) biofouling coating tube exterior surfaces; b) biofouling coating tube interior surfaces.

Table 1. Selected thermal conductivity values.

As with biofouling as a general category, biofilm functionality as an insulator is a physical phenomenon – independent of microbial metabolism within the biofilm matrix.

Microbiologically influenced corrosion

Microbiologically influenced corrosion (MIC) is the biologically mediated deterioration of a material. I’ll provide a more detailed discussion of MIC in a future What’s New article. For now, I will note that MIC occurs under biofilms. Globally, MIC causes an estimated $40 billion and $100 billion U.S. damage annually. As I explained in my May 2022 article, the biofilm creates electropotential gradients including zones in which oxygen (O2) is relatively depleted. A Galvanic cell is an electrochemical cell in which an electric current is generated from oxidation-reduction reactions. The oxygen gradients within biofilms drive Galvanic oxidation-reduction reactions. As illustrated in Figure 4, an anodic cell forms under the oxygen depleted zone. Metallic iron (Fe) dissolves as ferrous iron (Fe2+) and electrons (e) flow towards the cathodic cell (metal under more oxygen rich zones within the biofilm). Although the cathode attracts hydrogen ions (H+), dissolve oxygen (O2) can react with the hydrogen to produce water (H2O). Hydrogen removal from the cathode propagates continued electron flow and metal dissolution.

Fig 4. Galvanic corrosion under biofilm.

Galvanic corrosion can occur without direct microbial involvement, although EPS production and aerobic respiration both contribute to creating the oxygen concentration differentials illustrated in Figure 4. In fuel over water systems, biofilm accumulation is typically heaviest at the fuel-water interface (Figure 5a). The corrosion coupon shown in Figures 5a (before biofilm removal) and 5b (after coupon was cleaned for corrosion analysis) was suspended in a jar that contained diesel fuel over an aqueous salts- solution. Note that the amount of damage to the coupon was also at the interface. Although MIC tubercles can be seen on the coupon’s surface in both the interface (Figure 5c) and aqueous (Figure 5d) contact zones, the number of tubercles per cm2 is considerably greater in the interface zone. Similarly, as shown in the title photo, heaviest biofilm accumulation in MWF sumps tends to be found at the MWF-air-tank wall interface. MIC can also occur one surfaces exposed to water vapor or mist. In ships tanks, the heaviest corrosion is commonly observed on the tank overhead surfaces where water vapor condenses – providing an ideal habitat for fungal growth.

In metalworking facilities with central MWF systems, MWF returning from machines to filtration units flows through sluices. Historically, these sluices were covered with open grates. In the late 1990s grates were replaced by solid steel plates to reduce mist concentrations in facilities’ breathing zones (i.e., 1m to 2 m above the floor). This change effectively prevented mists generated in the sluice from escaping but provides a surface on which biofilms and MIC could develop (Figure 6).

Fig 5. Corrosion coupon from fuel over water microcosm – a) biofilm-coated coupon; b) coupon after cleaning; c) scanning electron microscope (SEM) image of coupon surface at fuel-water interface (inset circle is the area analyzed by energy dispersive x-ray analysis; d) SEM image of coupon surface in zone exposed to aqueous phase.

Fig 6. MWF return sluice deck plate (cover); underside.

Although biofilms and MIC develop only develop when sufficient water is present, Figure 7 illustrates how undetectable trace concentrations of water are sufficient to support MIC. Figures 7a and &b, respectively, show the exterior and interior surfaces of an UST’s submerged turbine pump’s riser. Nominally, these surfaces are in contact only with fuel. However, the exterior corrosion and innumerable tubercles on the interior surface would not have formed had they not been exposed to sufficient free water to support microbial growth.

Fig 7. UST submerged turbine pump riser pipe – a) exterior surface; b) interior surface after pipe was cut in half, longitudinally.

Galvanic corrosion is only one of several MIC mechanisms. Surface depassivation (H+ ion removal) was the first MIC mechanism described. Passivation – the arrest of electron flow in a galvanic cell – occurs when the H+ ions accumulating on the cathode for a film. As part of the sulfate reduction pathway, sulfate reducing bacteria (SRB) scavenge hydrogen from a galvanic cell’s cathode. This depassivates the surface – accelerating electron flow and metal dissolution. This mechanism was reported in the 1940s before microbiologists recognized the significance of biofilms. Although SRBs are still considered to play a significant MIC role, since the 1970s it has become apparent that low molecular weight (primarily C1 – formic, C2 – acetic, and C3 – lactic acids) organic acids (LMWOA) produced by all microbes contribute to MIC. These LMWOA can react directly with metal surfaces or can react with dissolve inorganic salts such as sodium or calcium chloride to form a strong inorganic acid (hydrochloric acid – HCl) and a weak organic base (the sodium C1, C2, or C3 salt – sodium formate, sodium acetate, or sodium lactate). Strong acids such as HCl can dissolve metals aggressively. Because biofilms act as barriers, the concentration of acids at the biofilm-metal surface can quite high (e.g., 1N hydrochloric acid, 2N sulfuric acid, etc.). The pH in this high acid zone can be <2. Aggressive MIC under a biofilm can drill a hole in 1 cm think mild steel pipe or tank walls in less than six months.


Biofilms primarily contribute to three types of biodeterioration: biofouling, insulation, and corrosion. When a biofilm is present, all three types of biodeterioration can be occurring simultaneously. By creating a barrier between sensors and fluids, biofilms can cause sensor failures. Heavy biofilm accumulations can restrict fluid flow through pipes. Even thin (<5 µm) biofilms can substantially reduce heat transfer in heat exchangers. Ineffective heat exchange causes process fluid overheating and consequent fluid, system or both types of failure. MIC occurs under biofilms. Combined, these biodeterioration mechanisms cause more than $100 billion U.S. annual damage globally.

In my next What’s New article I’ll discuss general approaches for biofilm control. In the meantime, if you have any questions about the information in this post, don’t hesitate to contact me at


Metalworking fluid return sluice cover plate; underside, showing biofilm build-up.

What are biofilms?

ASTM1 defines biofilm as a noun: “microorganisms living in a self-organized community attached to surfaces, interfaces, or each other, embedded in a matrix of extracellular polymeric substances of microbial origin, while exhibiting altered phenotypes with respect to growth rate and gene transcription.” The ASTM definition adds: “Biofilms may be comprised of bacteria, fungi, algae, protozoa, viruses, or infinite combinations of these microorganisms. The qualitative characteristics of a biofilm, including, but not limited to, population density, taxonomic diversity, thickness, chemical gradients, chemical composition, consistency, and other materials in the matrix that are not produced by the biofilm microorganisms, are controlled by the physiochemical environment in which it exists.”

There are quite a few complex terms used in this definition. In today’s article, I’ll unpack the definition and explain why people involved with industrial fluid or system management should pay attention to biofilms.


If you have been reading my What’s New articles, you already know what microorganisms are. They are organisms that are too small to be seen without the use of a magnifying device such as a microscope (Figure 1). Here’s a quick refresher (all definitions are for plural terms and are quotes from ASTM terminology standards):

  • Algae – major group of lower plants, generally aquatic, photosynthetic of extremely varied morphology and physiology, monocellular plants with chlorophyll often masked by a brown or red pigment.
  • Archaea – (domain Archaea), any of a group of single-celled prokaryotic organisms (that is, organisms whose cells lack a defined nucleus) that have distinct molecular characteristics separating them from bacteria (the other, more prominent group of prokaryotes) as well as from eukaryotes (organisms, including plants and animals, whose cells contain a defined nucleus).
  • Bacteria – any of a class of microscopic single-celled organisms reproducing by fission or by spores. Characterized by round, rod-like, spiral, or filamentous bodies, often aggregated into colonies or mobile by means of flagella. Widely dispersed in soil, water, organic matter, and the bodies of plants and animals. Either autotrophic (self-sustaining, self-generative), saprophytic (derives nutrition from nonliving organic material already present in the environment), or parasitic (deriving nutrition from another living organism). Often symbiotic (advantageous) in man, but sometimes pathogenic.
  • Fungi – single cell (yeasts) or filamentous (molds) microorganisms that share the property of having the true intracellular membranes (organelles) that characterize all higher life forms (Eukaryotes).
  • Protozoa – a phylum or group of phyla that comprises the single-celled microscopic animals, which include amoebas, flagellates, ciliates, sporozoans, and many other forms.
  • Virus – an infective agent that typically consists of a nucleic acid molecule in a protein coat, is too small to be seen by light microscopy, and is able to multiply only within the living cells of a host.

Fig 1. Microorganisms – a) archaea; b) algae; c) bacteria; d) fungi – molds; e) fungi – yeasts; f) protozoa; g) virus. Note size ranges from viruses (150 to 200 nm dia) to algae (100 µm dia).

Self-organized community

A self-organized community is one that forms due to the activities of its members. As I’ll explain in more detail below, biofilms are complex creations that are quite similar to multi-cellular organisms such as sponges and all higher organisms. The shape and function of each cell within the biofilm matrix is affected by chemical signals it receives from other cells.

Matrix of extracellular polymeric substances of microbial origin

A matrix is the set of conditions that provides a system in which something grows or develops. A biofilm matrix is a complex mixture of biomolecules, including genetic material (deoxyribonucleic acid – DNA – and ribonucleic acid – RNA), peptides, lipids, carbohydrates, and other large molecular weight molecules. This mixture is called extracellular polymeric substance (EPS). Originally (when I was an undergraduate investigating biofilm development on cave steam surfaces) biofilms were thought to be homogeneous surface coatings – not unlike a uniform layer of slimy paint. Now we understand that the EPS matrix is structurally complex. As Figure 2 illustrates, within the biofilm’s EPS matrix there are cell-dense and cell-free zones. Additionally, channels provide for nutrient and metabolite flow within the biofilm. Biofilms release cells into the bulk fluid by two mechanisms. Passive release occurs due to the erosive effects of fluid flowing over the biofilm. However, biofilm communities can also release cells actively. Planktonic microbes released from biofilms can settle on downstream surfaces and pioneer the creation of new biofilm communities. Some zones within the biofilm are tightly packed with microbial cells and others are cell deserts – with no cells visibly present.

Fig 2. Biofilm schematic. Red shapes of microbial cells. Light blue area is the EPS. Dark blue areas are channels, and yellow area is the bulk fluid flowing over he biofilm.

The process of biofilm development has been well studied. Bacteria with specialized external structures called attachment pili are attracted to substrate surfaces (for example, metal or concrete surfaces) by electrostatic and other forces (Figure 3a). This is called the attachment phase, or Stage I, of biofilm development. During Stage II (the growth phase), these pioneering bacteria replicate and start producing EPS (Figure 3b). In many environments, a mature biofilm (Stage III; Figures 2 and 3c) can develop within 24 h to 72 h. The population in a mature biofilm can consist of a single type of microbe (operational taxonomic unit – OTU – or genotype), when the microbes in the EPS matrix are genetically identical (i.e., monoclonal), or diverse OTUs.

Fig 3. Biofilm development – a) pioneer bacteria with attachment pili are attracted to surfaces by various electrochemical forces; b) after attaching to surfaces, pioneer bacteria reproduce, and excrete adhesive polymers and EPS; c) with a few days, the mature biofilm has formed.

Microbes within the biofilm form a consortium. They signal to one another by secreting and sensing various types of biomolecules. This molecular communication among cells is quite sophisticated and resembles the kind of intercellular communication that takes place among cells in multicellular organisms ranging from sponges to humans.


A phenotype is a set of an organism’s observable characteristics resulting from its interaction of its genotype with the environment. Just as the appearance and function of human cells depend on their location (e.g., skin cells, liver cells, muscle cells, etc. – all of which vary based on the organ of which they are part and their location within the organ – think of the many different cell phenotypes in an eyeball!), the appearance and function of microbial cells can vary with their immediate environment. Nearly 20 years ago, researchers at the Montana State University’s Center for Biofilm Engineering (Center for Biofilm Engineering – Center for Biofilm Engineering | Montana State University) placed a single bacterial cell onto a glass surface and watched as it reproduced and created a biofilm consortium. The researchers found that both the shape (morphology) and physiological characteristics (nutrients the cell can consume and waste products it excretes) of a single genotype depended on cells’ locations within the biofilm matrix. Reiterating my earlier comment: think of biofilm consortia as being among the earliest multicellular organisms. It is likely that early reports of biofilm microbial diversity included incorrect assessments based on phenotypic differentiation among cells. The biofilm literature now includes descriptions of both monoclonal and genetically diverse biofilm consortia.

Genetic Transfers

Confused yet? Microbes living in close proximity are exceptionally promiscuous. They can exchange both chromosomal and extrachromosomal DNA. Chromosomal DNA is the DNA contained in the threadlike structure that contains the organism’s genes which, in turn, define its genotype. Plasmids are strands of DNA that are not part of a cell’s chromosome. Plasmids can replicate independently of the chromosome. They can be present inside cells or in the EPS matrix. When plasmids from the environment enter cells, the process is called transfection.

Bacterial can transfer both chromosomal DNA and plasmids through conjugation pili. This process is called conjugation. Figure 4 illustrates the conjugation process. After the plasmid replicates inside one cell (Figures 1a and 1b), it can be transferred via a conjugation pilus (singular form of pili) to another cell (Figures 1c, through 1e). At the end of the process, both sells have the plasmid (Figure 1f). Plasmids are an essential tool for genetic engineering. In nature, they are the primary means by which properties such as microbicide resistance are transferred among cells.

Fig 4. Plasmid gene transfer by conjugation – a) two bacterial cells – one with and one without the plasmid; b) plasmid replicates; c) conjugation pilus connects two cells; d) plasmid DNA enters conjugation pilus for transfer to recipient cell; e) plasmid transfer has completed; f) both cells can now transfer plasmid to other cells.

Bacterial and fungal viruses can also act as vectors for gene transfers. When a DNA virus infects a host cell, its DNA is typically integrated into the host cell’s chromosome. As new viruses are produced within the host cell, some of the virions can pick up one or more genes from the host’s chromosome. After the host cell lyses, the released virions attach to new host cells. Those carrying genes from the previous host cell can transfer those genes to their new hosts. This process is call transduction.

Gene transfer among biofilm consortium cells is one of several communications mechanisms. Additionally, it is a process that spreads adventitious genes (such as microbicide resistance) among members of the biofilm community.


Biofilms can form on any surface that is in contact with water. In aqueous systems such as heat exchanger, potable water, firemain, containing water-miscible metalworking fluid, biofilms can coat >90 % of surfaces in contact with the fluid. In systems containing fuels, lubricants, or other fluids in which water is not normally miscible, biofilms typically develop in zones where condensate water accumulates.

Biofilms are complex structures comprised primarily of EPS. Microbes living in biofilm consortia resemble the cells of multicellular organisms. Physiologically, they can be quite distinct from genetically identical planktonic cells. Additionally, genetically identical microbes can differ physiologically based on their location within the EPS matrix. Due to the combined effects of microbial metabolic activity and EPS chemistry, the physicochemical environment within biofilms can be very different from that of the fluid with which it is in contact. Chemical gradients within biofilms contribute to microbiologically influenced corrosion (MIC).

My next What’s New article will expand on how biofilms contribute to biodeterioration problems. In the meantime, if you have any questions about the information in this post, don’t hesitate to contact me at

1 ASTM E2196 Standard Test Method for Quantification of Pseudomonas aeruginosa Biofilm Grown with Medium Shear and Continuous Flow Using Rotating Disk Reactor,


Microbes do not care whether operators accept the science.

Can microbes degrade turbine oil and cause damage to turbine oil systems?

The short answer is yes.

In 2018, as part of an Energy Institute sponsored project, I invited more than 100 turbine system operators to complete a survey designed to assess biodeterioration risk awareness and operational measures (for example, condition monitoring practices) for reducing the risk. Concurrently, I sent a similar invitation to power generation facility operators responsible for emergency standby diesel generator fuel systems. In contrast to the 23 % response from the folks responsible for fuel systems, I received no complete responses from folks responsible for turbine oil systems. Clearly, personnel responsible for fuel systems were more aware of the risk of biodeterioration than were their colleagues responsible for turbine oil systems.

Turbine oil and turbine oil system biodeterioration is not a common occurrence, but it does happen. A major challenge is that the people who need to connect the dots, are typically unaware of the potential for microbes to grow in these systems.

In this What’s New article I will summarize thet types of damage microbes can cause to turbine oil systems when sufficient water is present.


Although microbes require free water (water that has coalesced into droplets or a continuous phase) the volume they require can be vanishingly small. In my education courses, I compare a 1 µm (0.000039 in) bacterium on a surface under a 1 mm (0.039 in) film of water (Figure 1a) to a 2 m (6ft) tall person standing on the floor of a lake that is as deep as Mt. Kilimanjaro is tall (6,000m – 20,000 ft – Figures 1b and 1c). Moreover, a one mL (0.034 oz) drop of water can be a habitat for more than a billion bacterial cells. Thus, undetectably small traces of water can support substantial microbial communities and those communities can degrade the oil and damage the turbine oil system. Note: this phenomenon applies equally traces of water found in fuel and hydraulic fluid systems.

Fig 1. Relativity – the environment provided by a 1 mm thick film of water – a) relative dimensions of a 1 µm -long bacterium in 1 mm of water in graduated cylinder; b) a 2 m tall person standing at the base of Mt. Kilimanjaro; c) the same person standing on the floor of a lake that is as deep as Mt. Kilimanjaro is tall.

The most common symptom of uncontrolled microbial contamination in turbine oils is increased entrained water as determined by the Karl Fischer test (ASTM Test Methods D1533 or D6304). Water’s solubility in turbine oils can range from 20 µg kg-1 (i.e., ppt) to 60 µg kg-1. Optimally, it is maintained at <50 µg kg-1. Figure 2, copied from an article in Machinery Lubrication, shows that petroleum based turbine oils typically become visibly hazy once the water concentration reaches approximately 100 µg kg-1 (0.1 %). The water solubility in phosphate ester (PE) based oils is approximately 10x greater (i.e., 1,000 µg g-1). Haze (cloudiness) indicates that the concentration of water in the oil has exceeded its solubility and that the water has coalesced into micelles (droplets). Figure 3a shows oil in which the water concentration is below the saturation concentration. Figures 3b and 3c show how increased volumes of dispersed water increase the oil’s haziness; ultimately forming an invert emulsion.

Fig 2. Relationship between water concentration and haze (and bearing life).
Source: Water In Oil Contamination (

Fig 3. Relationship between water concentration and haze – a) water concentration is below the saturation level – the oil is clear and bright; b) water concentration is greater than saturation level – the oil has become hazy; c) sufficient water is present to form an invert emulsion.

What does this have to do with microbes? Microbes can produce detergent-like molecules called biosurfactants. As illustrated in Figure 4, biosurfactant molecules create stable, invert (water-in-oil) emulsions. Invert emulsion micelles provide oil-water surface area that facilitates microbes’ ability to use base-stock and additives as food.

Fig 4. Biosurfactant-based, invert emulsion – a) oil over water that is infected with biosurfactant—producing microbes; b) sample show in (a), 30 min after vigorous shaking – note formation of a stable, invert-emulsion; c) invert emulsion – water droplet encased by biosurfactant molecules; d) biosurfactant molecule showing polar (charged) head and non-polar (chargeless, hydrocarbon) tail.

Thus, water provides an environment in microbes can thrive. Thriving microbes produce biosurfactants that degrade the oils water separability properties (ASTM Test Method D1401) and thereby make nutrients from oil more readily available to the infecting microbes. Now I’ll summarize the primary consequences of providing microbes with the water they need to thrive.

What damage can microbes cause to turbine oils?

The process by which microbes (and all other living things) consume nutrients and convert them into food, energy, and waster is called metabolism. Microbes can directly consume oil additives, including corrosion inhibitors, antioxidants, and lubricity additives. They can also consume base oils. The net effect of this metabolic activity includes:

  • Decreased base number
  • Decreased oxidative stability
  • Decreased water separability (as noted above)
  • Decreased corrosion inhibition
  • Increased acid number
  • Increased particle load
  • Increased water content (as noted above)
  • Degraded viscosity and viscosity index properties

You’ll probably notice that each of these symptoms of turbine oil degradation can also be caused by non-microbiological (abiotic) processes. That creates a significant challenge when attempting to distinguish between biodeterioration and abiotic deterioration. More on that below.

What damage can microbes cause to turbine oil systems?

Premature filter plugging

In Figure 5, the oil is flowing from left to right. Unlike organic and inorganic particles, when microbes are trapped onto filter surfaces (Figure 5a) they can reproduce (proliferate) and excrete extracellular polymeric substance (EPS – a blend of various macromolecules that includes lipids, carbohydrates, proteins, nucleic acids, and others). Consequently, filter media are coated with both an increasing mass of cells and EPS (Figure 5b). Microbes trapped within the filter’s matrix can also proliferate and produce EPS. The combination effect is premature filter plugging as indicated by an increased pressure differential across the filter (Figure 5c). Figures 5d and 5e are photomicrographs of a filter’s surface and cross-section – illustrating how the weaved fibers achieve the medium’s designated porosity and filtration efficiency.

Fig 5. Microbes causing premature filter plugging- a) microbes (bacteria) trapped on upstream side of filter; b) trapped microbes proliferate and produce EPS; c) microbial colonization and EPS production no and within matrix restricts oil flow – causing high pressure differential across filter; d) inset showing surface view of filter’s fibers; e) inset showing cross-section view of filter’s fibers.


Microbiologically influenced corrosion (MIC) is an umbrella term that includes direct and indirect mechanisms by which microbes contribute to corrosion. I’ll devote a future What’s New article to explaining MIC. For now, I’ll simply note that MIC most commonly contributes to failures of pressurized lines and that (have you read this before?) MIC shares symptoms with abiotic corrosion mechanisms.

Reservoir fouling

Figures 3 and 4 illustrate mild forms of invert emulsion. Figure 6 is a sample from the bottom of a turbine oil reservoir. The invert emulsion residue that was produced by microbes in the system was nearly solid. To remove it from the reservoir, operators had to drain the tank, shovel out the semi-sold mass from the bottom 5 cm (2 in), then use high pressure, hot water and detergent to clean the reservoir before retuning it to service. Lines in which this mass had congealed had to be replaced.

Fig 6. Turbine oil reservoir bottom sample showing 5 cm layer of semi-solid, invert emulsion associated with uncontrolled microbial contamination.


When sufficient water to present, microbes can proliferate and be metabolically active in turbine oil systems. When this happens, microbial populations can degrade both the oil and the system. For a full treatment of the problem and its mitigation, read Energy Institute’s Guidelines on detecting, controlling, and mitigating microbial growth in oils and fuels used at power generation facilities, 1 st Ed., June 2020, ISBN 978 1 78725 188 5 (Figure 7).

Fig 7. Cover – EI Guidelines on detecting, controlling, and mitigating microbial growth in oils and fuels used at power generation facilities, 2020.

As always, I look forward to receiving your questions and comments at


One of the more famous quotes from William Shakespeare’s play, Romeo and Juliet.

Language Matters

In this month’s article I’ll address the use of what I call unregistered microbicides.

Over the course of the past several decades, industry and regulators have taken increasingly jaundiced views of chemical substances variously known as antimicrobial pesticides, biocidal substances, biocides, biocidal products, and microbicides. What are these substances? The EU’s Biocidal Products Regulation (BPR – Regulation (EU) No 528/2012 of the European Parliament and of the Council of 22 May 2012) Article 3, 1 (a) offers this definition:

any substance or mixture, in the form in which it is supplied to the user, consisting of, containing or generating one or more active substances, with the intention of destroying, deterring, rendering harmless, preventing the action of, or otherwise exerting a controlling effect on, any harmful organism by any means other than mere physical or mechanical action,

any substance or mixture, generated from substances or mixtures which do not themselves fall under the first indent, to be used with the intention of destroying, deterring, rendering harmless, preventing the action of, or otherwise exerting a controlling effect on, any harmful organism by any means other than mere physical or mechanical action.

A treated article that has a primary biocidal function shall be considered a biocidal product.

I’ve highlighted key words in the BPR definition because one response from industry has been to replace products that are registered as microbicides with alternative chemistries that do are not registered. They then promote their finish goods as being “biocide free.”

I pose this question:
Is it legitimate to make a biocide-free claim if a substance is used to control microbial contamination in a formulated product although it does not have an antimicrobial pesticide registration?

Non-biocidal additives in water-miscible metalwork fluids (MWF)

There are three groups of products related to MWF biodeterioration resistance – bioresistant, biostatic, and adjuvant additives.

Bioresistant additives

Bioresistant (recalcitrant) additives are chemistries that are difficult for microbes to use as food. As illustrated in Figure 1, their concentration in a fluid is unaffected by the fluid’s bioburden.

Fig 1. Bioresistant MWF additive – additive concentration is unaffected by microbial load (bioburden).1

Biostatic additives

In contrast to bioresistant additives, for which there appears to be no interaction between microbes and the additive, biostatic additives contribute to the MWF formulation’s ability to resist microbial growth. Figure 2a shows that when a biostatic MWF is inoculated with microbes, they do not proliferate (i.e., the biobuden does not increase). However (Figure 2b), if a biostatic additive is added to a heavily contaminated MWF, it has no effect on the biobuden.

Fig 2. Biostatic MWF additive – a) When microbes are added to biostatic MWF formulation, they do not proliferate; b) when a biostatic additive is added to a heavily contaminated MWF, it has no impact on the bioburden.


Additives that have no direct impact on microbial contamination in MWF (Figure 3a), but which improve the performance of microbicides are called adjuvants. Figure 3 illustrates this concept. Microbicides can kill off microbes (Figures 3b and 3c, red line), prevent microbes from proliferating (Figure 3d), or do both.

Fig 3. Adjuvant MWF additive impact on biomass – a) adjuvant without microbicide; b) microbicide speed of kill without adjuvant; c) microbicide speed of kill with adjuvant; d) microbial proliferation in MWF formulated with microbicide (red line) and microbicide plus adjuvant (purple line).

Similarly, an adjuvant can increase a microbicide’s speed of kill (Figure 3c, purple line), prolong the duration of its effectiveness against repeated challenges (Figure 3d, purple line) or both. The red arrows in Figure 3d indicate weekly inoculation of the test MWF with a microbial challenge population per ASTM Practice E2275.

Unregistered, microbicidal additives in water-miscible MWF

A key word in BPR’s biocide definition is intention. With this word, BPR’s definition shifts from an objective perspective – if a substance has a controlling effect on microbes, it is a microbicide – to a subjective perspective – only if it was intended for a substance to have a controlling effect on microbes is that substance subject to BPR registration. The U.S. Federal Insecticide, Rodenticide and Pesticide Act (FIFRA) has similar language (Sec. 2 [17 U.S.C. 136 (u)). The challenge is in reaching consensus on the meaning intention regarding the use of MWF functional additives.

Functional additives

In the MWF sector, a functional additive is a chemical substance that provides one or more performance properties to the fished formulation. Typical functional additive performance properties include:

  • Corrosion inhibition
  • Coupling – additives that provide chemical bonds between dissimilar substances (e.g., base oils and polar molecules)
  • Emulsion stabilization
  • Foam inhibition
  • Lubricity
  • Microbicidal activity
  • pH control (buffering)

Products used in several of these functional categories also impact microbial contamination. All chemicals sold for use in technical applications Europe must be registered in accordance with Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH – Regulation (EC) No 1907/2006 of the European Parliament and of the Council of 18 December 2006). In the early and mid-1990s, I was hopeful that REACH would the toxicity data required for all industrial chemicals would be similar. This would have closed the cost gap associated with obtaining the toxicity data needed for microbicide registration versus that needed for non-microbicidal substances. However, requiring a full toxicological test package for each of the millions of industrial chemicals was determined to be prohibitively expensive. Additionally, the time and laboratory facilities required to test all industrial chemicals rendered the concept untenable. Consequently, although some toxicological data are required to support product registrations under REACH, substantially more is needed for product registration under BPR. This creates a grey zone.

What is the difference between a registered and an unregistered microbicide?

Per the definition I quoted in the opening paragraph, a registered microbicide is an active substance (ingredient) or formulated product intentionally used to control microbial contamination and approved for such use by the cognizant regulatory agency (e.g., the European Chemical Agency’s – ECHA’s – Biocidal Products Committee, and the U.S. EPA’s Office of Pesticide Programs).

There is no consensus on definition of an unregistered microbicide. Nor is there consensus about the concept of intention. There is no universally agreed upon demarcation between a non-biocidal additive that also affects microbial contamination and one that has some level of non-biocidal activity (e.g., corrosion inhibition) but primarily inhibits microbial growth. To further complicate matters, there are numerous technical grade substances that are substantially more toxic than biocidal products. Moreover, there are registered microbicides that have non-biocidal applications. For example, hexahydro-1,3,5-tris(hydroxyethyl)-s-triazine (HTHT – CAS 4719-04-4) is registered as a MWF microbicide under the BPR, FIFRA and other nations’ pesticide regulations. However, it is also an effective sulfide scavenger used to scrub sulfide from gas generate during petroleum refining. When the product is sold for antimicrobial purposes, it has a pesticide label. When it is sold as a sulfide scavenger it has a technical chemical, it has a substantially less informative label – there is no intention of antimicrobial activity when HTHT is used as a sulfide scavenger.

For decades, I have argued the following:

  • If an additive demonstrates one or more, better than average, non-biocidal functional properties – regardless of its antimicrobial properties – it need not be registered as a biocidal substance unless biocidal claims are made.
  • If an additive does not demonstrate one or more, better than average, non-biocidal functional properties, and demonstrates antimicrobial performance, it should be registered as a biocidal substance.

Case study – Dicyclohexylamine

Dicyclohexylamine (DCHA, CAS 101-83-7) is a secondary amine that has been used in MWF formulations for more than two decades. As a chemical group, amines have several performance properties, the most common of which are:

  • Corrosion inhibition
  • Emulsion stabilization
  • pH control (buffering)

However, performance in each category varies substantially among amines. When DCHA has been tested for its corrosion inhibition, emulsion stabilization, or pH control performance, it has not compared favorably relative to other amines. Figure 4 is a plot of DCHA’s antimicrobial performance in a MWF. Testing was performed per ASTM Practice E2275. As Figure 4 illustrates, in a MWF that contained DCHA at 3,000 mg kg-1 (ppm), the challenge population fell to below detection levels (BDL) and remained BDL for the duration of the eight-week study.

DCHA is an example of a chemical that has demonstrated antimicrobial performance properties, is represented as having typical amine performance properties (although with no supporting data) and is used in MWF formulations. It is a prime example of an additive that does not demonstrate one or more, better than average, non-biocidal functional properties, and demonstrates antimicrobial performance – i.e., an unregistered microbicide.

Fig 4. ASTM Practice E2275 test results – MWF formulated with DCHA at 3,000 mg kg-1.

Now compare DCHA’s toxicity profile with that of HTHT. The data in Table 1 are taken from the products’ respective Safety Data Sheets (SDS). Per the SDS data, DCHA’s acute oral toxicity is >5x that of HTHT and its acute dermal toxicity is 10x that of HTHT. Moreover, DCHA’s ecotoxicity is greater than that of HTHT and its biodegradability is less than that of HTHT. Consequently, although MWF formulated with HTHT can claim to be biocide-free (they do not contain appropriately registered microbicides), they are potentially more toxic and less environmentally acceptable.

Table 1. Product SDS toxicity profile comparison – DCHA and HTHT.

Are there regulatory or liability issues?

This is an issue for regulators and lawyers. I am neither. However, there are precedents that suggest MWF compounders who use putative performance additives that do not actually demonstrate one or more, better than average, non-biocidal functional properties, but do demonstrate antimicrobial performance have exposure on both counts. There have been class-action lawsuits in which the plaintiffs have claimed adverse health effects caused by MWF exposure and in which MWF compounders have been listed as defendants. One can only speculate on the impact of formulations with unregistered microbicides on the ability of formulators to create a credible defense against adverse health complaints.

From a regulatory perspective, the issue is what claims are made. Some years ago, a food grade lubricant compounder formulated some of their products with PARABENs (para-hydroxy benzoic acid esters). Although PARABENs are commonly used as food and cosmetic preservatives, they are not registered as industrial microbicides. The compounder promoted the antimicrobial activity of their food grade lubricant. In doing so, they violated two laws. They used unregistered biocidal products as microbicides in the lubricant. They made pesticidal claims for their lubricant, although the product did not have a U.S. EPA pesticide registration. The compounder was quite fortunate in that the US EPA OPP did not press criminal charges and the fine was a fraction of what it might have been, had the US EPA’s officials applied the standard $5,000 per incident (i.e., each customer site at which product was used) per day. It has been argued that if a compounder does not claim microbial contamination resistance or other antimicrobial performance properties in their written literature, they will not come under the US EPA’s OPP scrutiny. I wonder if the risk is worth the benefit.

In terms of antimicrobial pesticides, the MWF sector is an orphan the total MWF microbicide market is estimated to be <$200 million U.S.). With the continued consolidation of biocide manufactures, and increased cost of providing all of the toxicological test data needed to support new microbicide registrations, the only new microbicides likely to be made available for use in MWF are active ingredients that have been approved in non-MWF, large volume (i.e., >$50 million opportunity for a given product) markets.


What does the term “biocide-free” mean if MWF formulated with chemistries that are more toxic than the appropriately registered antimicrobial pesticides that they replace? I suggest that all stakeholders from compounders to end-users are safer if they use additives for which complete toxicological profiles are available rather than alternatives for which only limited data are available. The increased amount of information provided on microbicide labels doesn’t make them more hazardous than other industrial chemicals. Just as a rose by any other name is would smell as sweet, a microbicidal chemical – unregistered microbicide – by any other name is just as toxic – perhaps even more so.

As always, I look forward to receiving your questions and comments at

1 I originally created Figures 1, 2, and 3 for STLE’s MWF 240 Metalworking Fluid Formulation Concepts course, Module 3 Minimizing MWF Biodeterioration Risk.


Sources of Variation. Homogeneity – the non-uniform distribution of microbes in the sample source (VSOURCE, where V = variability), the sample (VSAMPLE) and the specimen (VSPECIMEN) – contributes substantially to test result variability.

It’s Not the Method

A few years ago, a single set of fuel and fuel-associated water samples were used for two ASTM interlaboratory studies (ILS). You can read the details in the paper published in International Biodeterioration & Biodegradation. The ILS were performed based on the guidance provided by ASTM Practice D6300 for Determination of Precision and Bias Data for Use in Test Methods for Petroleum Products, Liquid Fuels, and Lubricants. As we discovered, D6300 is only applicable to properties that are both homogeneous and stable. Microbial contamination is neither. The two ILS were for ASTM Methods D7687 for Measurement of Cellular Adenosine Triphosphate in Fuel and Fuel-associated Water With Sample Concentration by Filtration and D8070 for Screening of Fuels and Fuel Associated Aqueous Specimens for Microbial Contamination by Lateral Flow Immunoassay. A few hours before the first ILS, specimens were prepared from samples known to have high, intermediate, and low bioburdens. Per D6300 a specimen was 200 mL fluid in a container, with three replicate containers for each combination of samples type (fuel grade or bottoms-water) and bioburden. Each container received a randomized code so that ILS participants would not know its contents. Preliminary ILS indicated that repeatability (single analyst) variability was < 5 % for each of the methods. Shockingly, the data from the D6300-based ILS indicated that both repeatability and reproducibility variability for each method were astronomical. I use the word shocking because both methods had long histories of yielding precise test results. The results suggested that the bioburdens in supposedly identical, replicate samples were actually substantially different. To test this theory, my collaborators and I compared the D7687 and D8070 results for each specimen. We found result agreement for 108 of 128 specimens (84 % agreement between methods). These findings inspired the development of ASTM Guide D7847 for Interlaboratory Studies for Microbiological Test Methods. The Guide enables ILS planners to reduce the variability of bioburdens in specimens so that test method rather than bioburden variability is tested.

In today’s What’s New article, I’ll explain some of the factors that contribute to test result variability. Remember that it is essential to understand test method variability before attempting to set data-based control limits.

Microbiological Test Result Variability – Are Microbes Present?

Are samples collected from locations most likely to have microbes?

In July 2021’s What’s New article, I wrote that the variability of microbiological test data is substantially greater than for other of tests used to analyze fuels, hydraulic fluids, lubricants, metalworking fluids (MWF), and other fluid samples. The non-uniform (heterogeneous) distribution of microbes in these fluids is often the primary factor contributing to test result variability.

The title Figure in today’s illustrates how non-uniform distribution of microbes within the system being sampled and the sample are typically the primary sources of variation. Typically, VSOURCE (where V = variability) increases as the ratio of oil (or fuel) to water increases.

The source is the system from which samples are collected. The most appropriate samples for microbiological testing are collected from places where microbes are most likely to accumulate in the system. I discussed this in some detail in the February 2020 What’s New article, and ASTM Practice D7464 provides detailed instructions for collecting samples intended for microbiology testing. The most accurate and precise microbiological test method will only detect microbes present in the test specimen – the volume or mass of material actually tested.

In most systems, bioburdens are most likely to be found on surfaces and at interfaces. It is important to understand that biofilms do not cover surfaces like coatings. Biofilms – either on system surfaces or at interfaces (i.e., the fuel-water interface) – are localized. Figure 1a shows biofilm accumulation in a fuel underground storage tank (UST). Biofilm of different thicknesses accumulate in bands along the UST’s length. Even though the nominal biofilm thickness within each band is rated by its average thickness (thick – ≥ 10 mm; moderate – ≥ 5 mm to < 10 mm; and minimal – < 5 mm), within the thick and moderate bands, biofilm thickness ranges from <0.1 mm to 10 mm. Consequently, the bioburden in replicates samples from adjacent 25 cm2 surfaces can vary by more than an order of magnitude. Similarly, Figure 1b shows the surface of a MWF sump. The heaviest biofilm accumulation is at the MWF-sump wall interface. However, as in the UST example, bioburden among replicate samples can vary by more than an order of magnitude. Figure 1c is a photo of two standpipe covers on the roof of a 5,000 m3 (30,000 bbl) diesel fuel above ground storage tank (AST). The distance between their respective centerlines is 16 cm. The AST bottom samples from the two standpipes (Figure 1d) are quite different in appearance and in their respective bioburdens.

Fig 1. Bioburden heterogeneity – a) UST bottom showing biofilm thickness zones; b) MWF sump wall showing biofilm thickness zones; c) 5,000 m3 diesel AST standpipe covers; d) bottom samples from the two standpipes shown in 1c.

Figure 2 illustrates bioburden heterogeneity in MWF (Figure 2a) and fuels (Figure 2b) respectively. The MWF is approximately 95 % water. Moreover, in an active MWF the fluid is recirculating at velocities sufficient to keep chips in suspension. Consequently, bioburden distribution in the MWF tends to be relatively homogeneous. Microbiology test results from replicate MWF samples typically vary by less than 20 %. In contrast, in fuel or oil samples that are nominally water-free, microbes tend to from discrete masses (flocs), making bioburden distribution in these fluids quite heterogeneous. The results from replicate samples can vary by more than an order of magnitude.

Fig 2. Source variability – a) MWF sump; replicate samples have similar bioburdens; b) oil sump (or fuel tank); replicate samples have different bioburdens. Red dots are microbes, purple circles are samples.

Are samples sufficiently large?

The VSAMPLE derives from VSYSTEM. As illustrated in Figures 1d and 2, bioburden heterogeneity in the system from which samples are collected contributes directly to bioburden differences among replicate samples. The purple circles in Figure 2 illustrate how the amount of bioburden captured in a sample bottle depends on bioburden homogeneity in the sampled fluid. Consequently, the results from triplicate samples of MWF are typically less variable than those from triplicate turbine oil samples.

One approach for reducing VSAMPLE is to increase the sample volume. Figure 3 illustrates how increasing the sample volume can decrease VSAMPLE. When bioburden distribution is uniform – as in recirculating MWF (Figure 3a) the bioburden per mL is unlikely to be affected substantially. However, when bioburden distribution is heterogeneous – as in oils and fuels (Figure 3b) – then increasing sample volume decreases the risk of failing to detect microbes present but heterogeneously distributed in the fluid.

Fig 3. Sample size and microbe recovery – a) sample size does not affect bioburden capture in MWF; b) sample size substantially affects bioburden capture in fuels and oils.

Must the entire sample volume be tested?

The specimen is the portion of the sample that is tested. For example, for culture testing, the specimen size can range from <1 mL (ASTM Method D7978) to 500 mL (ASTM Practice D6974). The specimen size for adenosine triphosphate (ATP) testing by ASTM Method D7687 is either 20 mL of fuel or 5 mL of bottoms water, although, to increase test sensitivity, larger volumes are permitted. If 100 % of a sample is to be tested the specimen is equivalent to the sample and VSPECIMEN = VSAMPLE. Typically, however, the specimen volume is a small percentage of the sample volume. When this is the case, VSPECIMEN ≠ VSAMPLE. Figure 4 illustrates how VSPECIMEN is proportional to the bioburden’s heterogeneity in the sample.

For some fuel microbiological tests, the specimen is an extract from the sample. For example, ASTM Method D7463 uses 1 mL of a capture solution to extract polar molecules (e.g., whole cells, and polar organic – including ATP – and inorganic molecules) from the fuel phase. ASTM Method D8070 also includes an extraction step. For these methods, the efficiency with which the extractant transfers the analyte from the original sample contributes to VSPECIMEN.

As with the relationship between source and sample, the greater the sample’s water-content the more uniform the distribution of cells tends to be (Figure 4a). In nominally water-free fluids (Figure 4b) cell flocs tend to be distributed non-uniformly. Consequently, the bioburden in some samples is likely to differ from that in other samples. Vigorous shaking can reduce bioburden heterogeneity within a sample container. The amount of force used, and the duration of the shaking step will vary among sample types. Optimally, an adjustable, wrist-action shaker should be used (Figure 5). The wrist-action motion simulates hand shaking but eliminates the effects of fatigue – all samples are shaken with the same motion. The adjustment changes the amount of force imparted by each shake. Sample viscosity and the amount of flocing dictate the force needed to disperse microbes uniformly throughout the sample. If samples have multiple phases (e.g., fuel, invert emulsion, and free-water – Figure 6), the phases should be separated into different sample containers and then treated as separate samples for testing.

Fig 4. Specimen variability – a) MWF (aqueous fluid); b) turbine oil (viscous, non-aqueous fluid). The bioburdens in replicate specimens drawn from each of the MWF samples are less variable than those in replicate specimens from an oil or fuel sample. Red dots are microbes, purple circles are specimens.

Fig 5. A four sample, adjustable force, wrist-action shaker. Both the range of arc and force applied for each cycle can be adjusted.

Fig 6. Three-phase sample from diesel UST. Before testing, phases should be separated, with each phase being transferred to a separate sample container.

A surface-active agent such as Cetyl Trimethyl Ammonium Bromide (CTAB) or Polyethylene glycol sorbitan monooleate (Tween® 80 – Tween is a registered trademark of Sigma-Aldrich), may added to samples to improve floc dispersion and bioburden heterogeneity in samples. The chemistry of the extraction reagents used for ASTM Methods D7463 and D8070 are proprietary. They are likely to contain one or more surfactants.

Last month I discussed quantitative recovery. In the article, I indicated that the essential element of quantitative recovery was consistency – regardless of whether the specimen preparation step recovered 5 % or 100 % of the analyte. In 2011, Defense Canada evaluated D7463’s extraction step. The data presented in Table 1 are taken from that study. For each sample, the ATP extraction step was repeated two to four times. The data were reported in relative light units per sample (RLU). The RLU in the second extracts ranged from 39 % to 137 % of the RLU in the first extract. Similarly, the RLU in the third extract ranged from ≤ 8 % (the test’s maximum RLU is 50,000) to 132 %. As I noted above, if the extraction step was quantitative, then RLU in subsequent extracts should have been a consistent fraction of the original. The fact that in some samples RLU in subsequent extracts were greater than in in the original and in other samples RLU decreased with each extraction demonstrated that the Method’s extraction step was not quantitative. The also means that VSPECIMEN was a major source of the method’s total variability.

Table 1. ASTM Method D7463 ATP extraction efficiency – middle distillate fuels.


Microbiological Test Result Variability – Experimental Error

Experimental error includes the factors that contribute to protocol-related test result variability – VERROR.

Most commonly, VERROR reflects repeatability precision – the variability of replicate test results run on a single sample, by a single operator, using a single apparatus, over a short time period. The primary factors contributing to VERROR include:

  • Effects of lot-to-lot reagent differences
  • Testing conditions
  • Operator’s skill

Effects of lot-to-lot reagent differences

All microbiological test methods use reagents. Stains are used for microscopic direct counts and flow cytometry. Nutrient media are used for culture testing. Extraction and bioluminescence reagents are used for ATP luminometry. Lot-to-lot variations in reagent composition can contribute to test result variability. Using ATP testing as an example, the RLU generated by a given concentration of ATP depends on the concentrations of Luciferase enzyme and Luciferin substrate in the luminescence reagent. Both components degrade over time. Consequently, the ratio of RLU to ATP concentration ([ATP]) decreases as reagent ages. Similarly, minor changes in growth medium nutrients and water concentration can affect the recovery of culturable microbes. Best practice is to routinely evaluate the impact of using different reagent lots, by running replicate tests using both the old and new lot reagents. This is a common practice in clinical labs but a rarity in industrial labs or among field operators performing condition monitoring tests.

Testing conditions

Enzymatic reaction rates vary with temperature. In 1889, his relationship was described mathematically by Svante Arrhenius. Figure 7 illustrates the logarithmic relationship between enzymatic reactions (including microbial growth rates) and temperature. Note that the y-axis scale is logarithmic. At temperatures greater than the one at which the reaction rate is maximal (Vmax) enzymes denature. Consequently, the reaction rate typically plummets as temperature continues to increase. The front end of the graph is important for microbiological testing. For example, the time needed for a bacterial colony to be visible will be longer at 20 °C than at 30 °C. If test kit instructions indicate that samples incubated at 30 °C should be observed at 48 h, but the actual incubation temperature is 20 °C, the results are likely to underestimate the actual CFU mL-1 (see What’s New, July 2017). Similarly, ATP test results are temperature dependent.

Fig 7. Enzymatic reaction rate – at temperatures less than the Vmax temperature, the reaction rate is described by the Arrhenius equation. At temperatures greater than the Vmax temperature, the reaction rate plummets as enzymes are destroyed and become inactive.

All testing should be performed at a standard temperature (for example 17 ± 2 °C – typical room temperature), or minimally at a given temperature. Using a reference standard reduces temperature’s impact on VERROR. In Figures 8 and 9, ATP was tested at 5 °C and 17 °C. The RLU at 5 °C were approximately 20 % of RLU at 17 °C (Figure 8). However, after raw RLU data were converted to [ATP] (pg mL-1) per ASTM D7687, the computed [ATP]s were statistically indistinguishable (Figure 9).

Fig 8. Temperature effect on ASTM D7687 results – orange squares: RLU at 17 °C; grey triangles: RLU at 5 °C.

Fig 9. Temperature effect on ASTM D7687 results – orange squares: [ATP] at 17 °C; grey triangles: [ATP] at 5 °C.

Depending on the test method, other conditions such as gas composition (e.g., presence or absence of oxygen), relative humidity, and atmospheric pressure can affect results. However, these factors are rarely relevant for routine microbiological testing of industrial fluid samples.

Operator’s skill

Not long ago, an ILS (a different one form the one with which I opened today’s article) yielded surprisingly large reproducibility variation. Single-operator repeatability variation was negligible (< 5 %), but variability among labs was >2 orders of magnitude. The ILS coordinator performed a root cause analysis to help understand why the results varied so widely among participating labs. The investigation determined that none of the labs had actually followed the Test Method’s protocol steps. This experience highlighted the importance of operator training and quality assurance. Common operator factors that contribute to VERROR include:

  • Sample handling
  • Specimen collection and dispensing
  • Reagent preparation
  • Attention to protocol detail

Sample Handling – Operators must take precautions to avoid contaminating samples with microbes from their hands, the test facility environment, or devices used to handle samples. Earlier, I discussed the importance of agitating samples to homogenously disperse microbes. If the operator does not perform this step consistently (same amount of force for a standard time), the samples homogeneity will be affected. Homogeneity begins to degrade immediately sample agitation stops. The speed with which homogeneity degrades depends on the sample type. Best practice is to withdraw specimens within less than 1 min after agitating a specimen. If there will be more than a 1 min delay between specimens, the sample should be reagitated before the next specimen is drawn.

In multi-phase samples, bioburden tends to be much greater in the invert emulsion and aqueous phases. Failure to separate phases will cause higher bioburdens in those phases to bias (increase the apparent bioburden in) the fuel or oil phase test results.

Specimen collection and dispensing – the smaller the specimen volume the more critical it is to ensure that volumes are drawn and collected precisely. For example, for a 100 mL specimen, the impact of actually drawing 99 mL or 101 mL is 1 % to the total volume. In contrast, for a 10 mL sample the impact is 10 % and for a 1 mL sample it is 100 %. I have seen instances where a pipetting device was malfunctioning and an analyst – believing that they are transferring 1.0 mL of specimen – dispensed 0.0 mL. A high bioburden specimen was erroneously reported as having negligible bioburden. Pipetting devices vary on how they deliver fluid. Some are designed to deliver the designated volume although they retain some fluid. Others deliver the designated volume only when all fluid has been eliminated from the pipet. Operators must be sure that they are using pipets appropriately. They must also ensure that the entire specimen is delivered to the appropriate container. When specimens are being diluted, some methods prescribe that after dispensing the specimen into a solvent (or dilution blank) the pipet be rinses several times with the specimen-solvent mixture to maximized quantitative specimen transfer. Other methods do not prescribe this step. Operators must ensure that they perform this steps exactly as prescribed in each test method.

Reagent preparation – this step can be as simple as rehydrating freeze-dried reagents to following complex recipes. Any deviation from reagent preparation instructions can affect the test results substantially. During my undergraduate years, a visiting professor developed a nutrient medium with which he was able to cultivate a unique microbe that had never been recovered previously. After he published the research, others tried to reproduce his results. All were unsuccessful until the professor compared his lab notes with the published paper. The publisher had reversed the order in which they listed the growth medium’s ingredients. The switch made all the difference. Once other researchers started using the original recipe, they were able to reproduce the professor’s results. When preparing reagents, care must be taken to avoid infecting them with microbial contaminants. Operators must also be careful to follow reagent storage requirements (e.g., store in the dark, within a specified temperature range, for no longer than the specified period).

Attention to protocol detail – as I mentioned regarding the ILS with the excellent repeatability variation but horrible reproducibility variation, it is imperative that operators follow the protocol precisely as prescribed. Field tests are typically more forgiving than laboratory tests in this regard. Test kit manufacturers invariably invest substantial time and effort to understand the factors that affect their kit’s precision and accuracy. Similarly, researchers who publish peer-reviewed methodology papers understand the non-analyte factors that can affect test results. New operators often need training on how to perform manual tasks such as sample shaking, pipetting, calibrating instruments, etc. Performing protocol steps improperly can contribute to imprecision, in accuracy or both.


Microbial contamination in industrial systems can be localized. One consequence of this localization is that samples collected from heavily contaminated systems can be microbe-free. By extension, microbiological test methods will not detect microbes that are not captured in a sample. The heterogeneous distribution of microbes also means that VSYSTEM and VSAMPLE can be much greater than any test method’s VERROR. Notwithstanding the heterogeneity issue, improper sample handling contributes to VSPECIMEN and sloppy performance of microbiological tests contributes to VERROR. Following best practices for identifying appropriate diagnostic sample collection points and sampling protocols decreases the risk of failing to detect microbial contamination in infected systems. Proper sample handling and test method performance improve test result accuracy and precision.

As always, I look forward to receiving your questions and comments at


Most commonly, quantitative recovery applies when a method consistently detects a substantial percentage of the intended analyte in a specimen. Read on to learn more.

Analytes and Parameters

In chemistry, an analyte is a substance or material being measured by an analytical method. In microbiology, the analyte is either microbial cells or molecules. A parameter is a property used to quantify an analyte. Direct counting – using either a microscope or a flow cytometer – is the only microbiological test method for which the analyte and parameter are the same – cells. More commonly, the parameter measured is something that is proportional to the number of cells present. For example, with culture testing (see What’s New 06 July 2017) the analyte is culturable microbes and the test parameter is colony forming units (CFU – Figure 1a). For adenosine triphosphate (ATP) testing the analyte is the ATP molecule and the parameter is light emitted during the luciferase-luciferin mediated dephosphorylation of ATP to adenosine monophosphate (AMP – see What’s New, August 2017 and Figure 1b).

Fig 1. Two microbiological analytes – a) Colony counts – the analyte is the original, culturable bacterium. To be detectable, the microbe must reproduce through approximately 30 generations (doublings) to produce a visible colony. The number of colonies on a plate are reported as colony forming units (CFU). The CFU/plate are corrected the degree to which the original specimen was diluted (i.e., the dilution factor) to give a result in CFU mL-1, CFU cm-2, or CFU g-1. b) Adenosine triphosphate (ATP) concentration – the chemical interaction of ATP with the substrate-enzyme reagent luciferin-luciferase generates a photon of light – generally observed as an instrument-dependent relative light unit (RLU). Quantitative results are obtained by comparing observed test results with those obtained using one or more ATP reference standards.

Quantitative Recovery does not mean 100 % Recovery

Microbiological testing includes several steps between sample collection and result recovery. In my January 2022 What’s New article, I’ll provide a more complete discussion of how each of these steps contributes to test result variability. For now, it is sufficient to understand that recovery is a source of variation.

Figure 2 is similar to, but slightly different from Figure 7 in my March 2020 article. Each of the methods illustrated is quantitative. However, except for direct counts (possibly), none captures 100 % of the analyte.

Analyte recovery is affected by one or more factors. All methods are affected by analyte heterogeneity – non-uniform distribution of microbes (Figure 3). Regardless of the method used, if the number of microbes present (bioburden) in replicate samples varies substantially, then so will the results. Bioburdens tend to be distributed more homogeneously in low viscosity (<20 cSt) aqueous fluids (e.g., cooling tower water, water-miscible metalworking fluids, liquid household products, etc.) and more heterogeneously in viscous, water-based fluids or in non-aqueous fluids (e.g., fuels, lubricants, and oils).

Fig 2. The dark blue circle represents all microbes present in a sample – the microbiome. The percentages listed under each method are estimates of how much of the microbiome it detects.

Fig 3. Impact of heterogeneity on analyte in samples – a) sample misses widely dispersed microbial masses; b) sample missed uniformly distributed on system surfaces but not in fluid; c) sample captures representative biomass from uniformly distributed masses.

Similarly, all methods are affected by specimen handling. Recall that a specimen is the portion of a sample that is analyzed. Thus, one or more 20 mL specimens from a 500 mL sample might be tested by ASTM method D7687 for ATP in fuel. In ASTM method D7687 and practice D6974 a filtration step is used to physically separate microbial cells from the specimen (Figure 4). For ATP or genomic testing, the cells are then broken open (lysed) to release their contents (e.g., ATP, DNA, RNA). For culture testing the membrane is placed onto a nutrient medium.

Fig 4. Separating microbes from a specimen – filtration method.

The filters’ nominal pore sizes (NPS) are 0.45 µm for D6974 and 0.7 µm for D7687. Both are larger than the 0.22 µm NPS filters used for filter sterilization. However, each has proven adequate to quantitatively retain bacterial cells in specimens to be analyzed by the respective test method.

Put another way, the filters used for D6974 and D7687 meet the objective – to ensure that the percent recovery will always be within an acceptable range. Figure 5 illustrates this concept for D7687. When both the specimen and filtrate are tested for cellular ATP concentration ([cATP]), the [cATP]filtrate = 0 % to 10 % of the ATP-bioburden intentionally added to the specimen. This range was determined through a series of field tests that were run to determine the precent recovery of ATP from fuel samples. The average percent recovery ± standard deviation was 101 ± 10 % (where the samples were spiked with bacteria to give 2,000 pg mL-1).

Fig 5. Cellular ATP (cATP) recovery = 90 % to 110 % of the analyte in typical specimens. Note that the blue circle’s area that is not covered by the yellow circle and the orange circle’s area that is not covered by the blue circle are negligible.

What This Means in Practical Terms

I wrote this What’s New article because someone using ASTM D7687 performed a culture test of the filtrate and recover 105 CFU mL-1. They did not test the filtrate for [cATP]. Consequently, they were alarmed that the filter used for ASTM D7687 did not trap microbes quantitatively.

If the culturable bioburden before filtration was 1 x 106 CFU mL-1, and 10 % of the cells passed through the filter, the culturable bioburden in the filtrate would be 1 x 105 CFU mL-1. It would be naïve to conclude that the filter did not trap bacterial cells very efficiently. The percentage of cells that passed through the filter was a small fraction of the total number of cells in the specimen. Consequently, the loss would not affect how the test result was interpreted (see What’s New, August 2021). Keep in mind that for D7687 and D6974, respectively the typical test result standard deviations are Log10 X ± 0.1X and Log10 Y ± 0.5Y, where X is [cATP] in pg mL-1 and Y is CFU mL-1.

There is a common impulse to compare test results obtained from different test methods that measure different parameters. However, as explained in ASTM Guide E1326, it is essential to fully understand what is actually being compared. When testing quantitative recovery, it is imperative to use the same analyte before and after the microbe separation step illustrated in Figure 3.

As always, I look forward to receiving your questions and comments at


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