Dive Physiology & Decompression Research

Henry's Law Underwater: The Gas-Physics Foundation

The core problem of decompression is thermodynamic. Henry's Law states that the amount of gas dissolved in a liquid is proportional to the partial pressure of that gas above the liquid. Descend to 30 m (4 bar absolute on air) and roughly four times more nitrogen dissolves into arterial blood than at the surface. Tissues with high lipid content—fat, myelin sheaths—absorb more than lean muscle or bone. As the diver ascends, partial pressures fall and dissolved nitrogen must leave solution. If it leaves slowly and diffusively, it exhales harmlessly through the lungs. If the ascent is too rapid, nitrogen comes out of solution explosively, forming autochthonous bubbles within tissues and the venous circulation [1]. Those bubbles cause DCS through a cascade of mechanisms: mechanical distortion of cells, activation of complement and platelet pathways, endothelial dysfunction, and ischemia [1].

The Bühlmann ZH-L16 Model: Compartments and Coefficients

The dominant framework for recreational and technical decompression planning is the Bühlmann ZH-L16 algorithm, developed over decades by Swiss physician Albert Bühlmann at the University of Zürich and first published in book form in 1983 (Decompression–Decompression Sickness, Springer). The model posits 16 parallel theoretical tissue compartments with nitrogen half-times ranging from approximately 4 minutes (fast tissues: cerebral grey matter, coronary tissue) to 635 minutes (slow tissues: tendons, avascular cartilage). Each compartment has empirically derived *a* and *b* coefficients that define a maximum tolerable supersaturation—the M-value—at each ambient pressure [1]. During a dive, the algorithm tracks nitrogen loading in each compartment in real time. Ascent is permitted only when no compartment's inert-gas pressure exceeds its M-value, forcing stops when necessary.

The three published variants—ZH-L16A (theoretical), ZH-L16B (printed tables), and ZH-L16C (dive computers)—differ in their coefficient sets. ZH-L16C is slightly more conservative for some compartments, and is the version embedded in most modern dive computers from Shearwater, Suunto, Mares, and others. A critical point often overlooked by recreational divers: two computers both labelled 'Bühlmann' can produce meaningfully different ascent schedules because manufacturers apply different internal rounding, surfacing assumptions, and start conditions [1]. This is not a malfunction—it reflects legitimate implementation choices within an algorithm framework, not a single deterministic model.

Gradient Factors: Conservatism as a Dial

The ZH-L16 M-values represent theoretical maximums, not safety targets. Many divers and dive agencies apply gradient factors (GF)—a mechanism introduced by Eric Baker in the late 1990s—to artificially constrain allowed supersaturation to a chosen fraction of the M-value. Gradient factors are expressed as two percentages: GF-Low (the maximum supersaturation allowed at the deepest stop) and GF-High (the maximum allowed at the surface). A setting of GF 30/85, for example, means the diver stops much deeper than pure ZH-L16 would require and surfaces at 85% of the theoretical M-value rather than 100%. Conservative settings like 30/70 are popular among technical divers; recreational divers using default computer settings often dive at effective GF values around 80/95 without realising it [2].

The optimal GF setting is contextual, not universal. A 2023 study on Belgian military divers found that lower GF-Low settings significantly reduced post-dive bubble grades measured by transthoracic Doppler echocardiography, confirming that deeper stops do reduce venous gas emboli (VGE) counts—though not necessarily DCS incidence in the short exposure durations studied [2]. Meanwhile, research from the US Navy and commercial diving communities has questioned whether deep stops provide meaningful benefit for bounce dives, with some evidence suggesting they actually load fast compartments and could increase risk in certain profiles. The debate over 'deep stops versus shallow stops' has been one of the liveliest in technical diving physiology for a decade.

The Varying Permeability Model: Thinking in Bubbles

Parallel to the Bühlmann paradigm is the Varying Permeability Model (VPM), developed by David Yount at the University of Hawaii and extended by Eric Maiken and others. Where Bühlmann tracks dissolved gas relative to empirical M-values, VPM explicitly models microscopic gas micronuclei—pre-existing bubble seeds in hydrophobic crevices of tissues—and calculates how supersaturation drives their growth. The model posits that exposure history matters: repeated dives progressively crush micronuclei into smaller sizes, which is why VPM-B schedules can be more conservative on repetitive dives than equivalent ZH-L16-GF plans. In practice, VPM-B with moderate conservatism settings generates deeper, shorter stops compared to ZH-L16-GF with conservative GF-Lows [1]. Neither model has been validated by a prospective randomised controlled trial large enough to definitively establish superiority; both reduce DCS risk relative to omitting decompression altogether.

DAN's Epidemiological Window: What Real Dives Tell Us

Decompression models are built on controlled chamber experiments and limited field data. The Divers Alert Network's Project Dive Exploration (PDE), running from 1995 to 2008, was the most ambitious attempt to ground-truth models against real recreational diving. Researchers collected detailed dive profiles from thousands of volunteer recreational divers across multiple sites, cross-referencing outcomes with DCS reports [3]. The headline finding: the absolute incidence of DCS in recreational diving is very low—approximately 1–3 cases per 10,000 dives—but the distribution of risk is not uniform. Repetitive dives, cold-water dives, older divers, heavier divers, and dives that violated no-stop limits all showed elevated relative risk. Crucially, a meaningful fraction of DCS cases occurred in divers whose computers showed no limit violations, confirming that algorithms describe average populations, not individual thresholds.

DAN's annual diving reports continue to capture injury data from their emergency medical hotline. The most recent editions document that neurological DCS—affecting the spinal cord, vestibular system, or brain—accounts for roughly half of all treated cases, reflecting both its clinical severity and the tendency for divers experiencing neurological symptoms to seek help more reliably than those with joint pain alone [3]. The data also reveal a persistent pattern: a significant proportion of serious DCS cases occur in divers using enriched air nitrox (EANx) who mistake higher O₂ fractions for unconditional protection—nitrox reduces nitrogen loading at a given depth but does not eliminate risk, and incorrect maximum operating depth (MOD) calculations introduce oxygen toxicity as an additional hazard.

Patent Foramen Ovale: A Hole in the Heart, a Gap in the Model

Perhaps the most significant individual anatomical risk factor for DCS is patent foramen ovale (PFO), a remnant of fetal circulation present in 25–30% of adults. In utero, the foramen ovale allows oxygenated blood to bypass the non-functional fetal lungs; it normally seals at birth under the pressure reversal of the first breath. When it remains patent, a right-to-left shunt (RLS) can open intermittently under conditions of elevated right-heart pressure—including exertion, Valsalva manoeuvres, and the increased venous gas emboli load of ascent [4].

The mechanism is dangerous and direct: venous gas bubbles that would otherwise be filtered by the pulmonary capillary bed pass into the arterial circulation, where they can lodge in cerebral, spinal, or coronary vessels. A landmark prospective observational study by Germonpré and colleagues (2021) followed 304 active divers for over two years, screening for RLS by carotid Doppler ultrasound [4]. Divers with large RLS had a five-fold higher incidence of DCS episodes compared with those without, with the excess concentrated in neurological presentations. A 2019 case-control study in the Journal of Cardiology similarly found high-grade PFO in 70% of divers with unprovoked (within-limits) neurological DCS, versus approximately 27% of controls [5].

The clinical management question—should divers with PFO undergo catheter closure?—has been substantially clarified by the DIVE-PFO Registry, reported in JACC in 2020 [6]. In 180 divers with PFO who had experienced at least one DCS episode, catheter-based percutaneous closure led to complete elimination of right-to-left shunting and a significant reduction in recurrent DCS over a follow-up period averaging four years. A large 2023 cohort study published in the Annals of Internal Medicine, following over 5,000 divers, confirmed that PFO-positive individuals had a three-fold elevated DCS incidence and that the relative risk was substantially attenuated in those who adopted conservative diving profiles following PFO diagnosis [7]. DAN and UHMS jointly published guidelines recommending that divers with a PFO history and neurological DCS be referred for cardiology evaluation and counselled on the risks of continued diving versus closure [8].

Immersion Pulmonary Edema: The Condition Divers Often Miss

While DCS dominates decompression medicine discourse, immersion pulmonary edema (IPE)—also called swimming-induced pulmonary edema (SIPE)—has emerged as a distinct and clinically significant hazard that may be more common than previously recognised. IPE involves non-cardiogenic fluid flooding of the pulmonary alveoli during or immediately after immersion, typically manifesting as acute dyspnea, cough, blood-tinged froth, and hypoxia during or after a dive [9]. Unlike DCS, it is not caused by bubble formation; rather, it arises from a cascade of haemodynamic stresses specific to immersion: increased central blood volume (blood redistributes from peripheral vessels), elevated pulmonary capillary wedge pressure, cold-water-driven peripheral vasoconstriction, and elevated inspiratory resistance against the hydrostatic pressure gradient of water around the chest [10].

A 2023 comparative study in Sports Medicine – Open examined IPE presentation across military and recreational divers, finding that cold water (<20°C), exertion, and pre-existing hypertension or cardiac disease were independent risk factors [11]. The 2024 joint position statement from the South Pacific Underwater Medicine Society (SPUMS) and the UK Diving Medical Committee formalised management guidelines: IPE should be treated emergently with oxygen and affected divers should undergo full cardiovascular workup before returning to the water [9]. The key clinical challenge is distinguishing IPE from pulmonary DCS in the field; both present with dyspnea post-dive, but IPE typically onsets during ascent or immediately at the surface—often before significant bubble formation could theoretically occur—and lacks the neurological or musculoskeletal features of decompression sickness.

The Limits of Algorithms: Individual Biology in a Population Model

All decompression models share a fundamental epistemological limitation: they are population-level statistical constructs applied to individuals who vary enormously in physiology, fitness, anatomy, and behaviour. Hydration status, physical exertion during the dive, water temperature, residual bubble load from previous dives, age-related changes in tissue perfusion, body composition, and genetic variation in nitrogen-metabolising enzyme systems all modulate true DCS risk in ways no algorithm fully captures. This is not a criticism of the models—it is the nature of the problem. The practical implication is that algorithm compliance is necessary but not sufficient: safety requires conservative ascent rates, safety stops beyond those mandated, awareness of individual factors (PFO screening, cardiovascular fitness, age), and honest self-assessment of diving conditions.

The frontier of decompression research involves real-time physiological monitoring—wearable Doppler bubble detectors, heart-rate-adjusted decompression, and machine-learning models trained on individual dive profiles—but none of these has yet been validated for clinical use. In the meantime, divers who understand the science behind their computers, who respect the biological individuality the algorithm cannot see, and who recognise the symptoms of DCS and IPE without delay, are the ones most likely to reach the surface safely, dive after dive.