Developing CBRN Situational Understanding for Decision Support
By Dr. Alan C. Samuels
Article published on:
in the 2026 e-Edition
of the Army Chemical Review
Read Time:
< 7 mins
Explosive Ordnance Disposal Technicians with Explosive Ordnance
Disposal Mobile Unit ELEVEN (EODMU-11) dispose of hazardous material
during a chemical, biological, radiological, and nuclear (CBRN) drill
on Naval Air Weapons Station China Lake, Dec. 18, 2025. EODMU-11, a
subordinate command of Explosive Ordnance Disposal Group ONE
(EODGRU-1), operates as part of the Navy Expeditionary Combat Force,
providing skilled, capable, and deployable maritime EOD and Navy Diver
forces around the globe to support a range of operations.
(U.S. Navy Photo by Mass Communication Specialist 2nd Class August
Clawson)
Confronting an adversary able and willing to employ chemical or
biological weapons requires due diligence and an integrated early
warning system-of-systems approach. Emerging technologies play a key
role in the development of early warning throughout the continuum of
conflict, as seen in Figure 1. Understanding the capabilities and
limitations of each contributing source of data is crucial to the
chemical, biological, radiological, and nuclear (CBRN) subject matter
expert so that they can adequately inform commanders and their staffs of
contamination risks when possible.
Figure 1. Application and benefits accrued by a
system-of-systems approach to achieve integrated early warning across
the continuum of conflict. The appropriate technology shifts in utility
from a deter function in competition to a defend function in conflict,
preserving combat power. Multi-INT=multiple intelligence sources of
data, IAMD=Integrated Air and Missile Defense, HSI=hyperspectral
imaging, and LIDAR=light detection and ranging.
The most effective application of advanced integrated early warning
systems can be achieved with a deliberate understanding of their
employment and analytical outcomes. At the heart of any integrated early
warning system is the data management and integration environment, which
consumes information from a given situation and processes the data to
reliably develop a concise and cogent understanding of the operational
environment.
Figure 2. Hyperspectral images with false color (red) pixel
demarcation indicating the presence of a chemical simulant’s signature
in the image as discerned by the sensor and its library spectrum of
the chemical. Top: polyethylene glycol (PEG) detected after a
64-meter-high airburst at 2.5 km. Bottom: PEG detected after a
499-meter-high airburst at 5.1 km. (Imagery courtesy Spectrum
Photonics, Inc.)[iFOV: instantaneous field of view]
An adversary may employ chemical or biological threat agents to achieve
their perceived advantage at early stages in the transition to conflict.
The agents may be surreptitiously deployed under plausible deniability
circumstances by special operations or even by a proxy, such as
sympathetic actors. A covert attack aimed at contaminating air, food, or
water sources supporting a concentration of troops may be attempted to
disrupt and degrade the force before open hostilities begin. Emerging
technologies that continuously monitor the environment and population
can provide a deterrent effect while also enabling earlier responses
that mitigate the adverse outcomes of such operations. Untargeted
sequencing of complex samples, including air and wastewater, can reveal
the causative pathogen much earlier in the evolution of an outbreak than
would normally be realized through regular clinical presentation. In
addition, systematic physiological monitoring can reveal indications of
the potential onset of illness or infection sooner in the onset of an
outbreak, affording opportunities for early treatment and prophylaxis
options.
Once the situation escalates into open conflict, emerging intelligence,
surveillance, and reconnaissance tools can provide awareness and
understanding of an adversary’s decision to employ chemical or
biological agents well before an attack is carried out (as shown by
Multi-INT and Publicly Available Information in Figure 1). The
deployment chain necessary to support a successful CBRN attack presents
opportunities for observing the handling, transport, and preattack
positioning of such agents. This is due to the perpetrator’s need for
protective equipment and specialized facilities and resources to handle
and store the agents. Properly applied, these chemical and biological
observables can be identified before an adversary executes a planned
offensive action, creating opportunities for interdiction and
potentially deterring further hostile decisions.
Attacks involving chemical or biological weapons during open conflict do
not require waiting for weapon effects or detection by specialized
systems, as their delivery typically relies on overt means such as
artillery, mortars, rockets, missiles, or drone-based dissemination.
Radar and integrated air and missile defense systems provide awareness
of incoming threats and enable remote-sensing systems, including
hyperspectral imaging (HSI) and backscatter light detection and ranging
(LIDAR). Properly cued, these systems can quickly assess and track the
plumes that
result from a chemical or biological attack. In the case of
hyperspectral sensing, gas-phase threat agents can be detected and
identified almost instantaneously, provided the system observes the
initial release. A 2018 test at Dugway Proving Ground involving an
airburst release of a chemical simulant demonstrated the effectiveness
of an HSI system in detecting and identifying chemical agents, as shown
in Figure 2. To ensure that the initial release was observed, the HSI
system was cued by radar to the point of arrival of the incoming
artillery shells.
Figure 3. Backscatter LIDAR scan overlaid on aerial imagery,
with the LIDAR positioned at the upper-right corner (0,0). The color
scale represents the logarithmic change in signal relative to ambient
background aerosol levels. (Imagery courtesy of Spectral Sensor
Solutions, LLC.)
Not all threat agents present in the gas phase. Some are intentionally
deployed as low volatility hazards that disperse to yield a persistent
area effect on equipment or to deny access to affected terrain. A
properly cued backscatter LIDAR system fills the awareness gap caused by
the lack of a gas phase signature that can be observed by an HSI system.
The LIDAR affords an understanding of the plume location and dispersion
pattern being disseminated and/or the deposition of persistent hazards
onto terrain, enabling the further investigation of the effects of such
an attack by properly equipped CBRN response elements. Figure 3 shows a
sample backscatter LIDAR scan that has developed a geospatial plume
dispersion and dispersion pattern. Two aerosol plumes are detected: a
narrow, low-density plume from a stationary burning tire to the left and
a broader, more intense plume created by a mobile release of a biothreat
aerosol simulant from a vehicle-mounted disseminator to the right. This
aerosol threat simulant plume is at a 45-degree angle to the wind due to
the disseminator vehicle moving perpendicular to the wind. The color
scale indicates relative backscattered intensity, with higher values
corresponding to denser aerosol concentrations. This scan provides
real-time situational awareness by showing the location, shape, and
intensity of airborne hazards. This information can be used to cue
sensors mounted on uncrewed aerial systems (UAS) into specific locations
within airborne plumes for further interrogation or sample collection.
This expansive real estate coverage afforded by the LIDAR, with short
mission life but precise sortie management of the UAS, accentuates the
advantage of integrating the wide area.
The advent of low-cost autonomous systems has enabled the execution of a
sampling mission cued by the LIDAR so that the area impacted by the
plume, or even the plume itself, can be intercepted and either
identified by an onboard sensor or have the sample brought back for
analysis by trained CBRN operators equipped with far-forward analytic
sensors and instruments.
Another emerging technology and chemical defense capability that
enhances situational understanding in the integrated early warning
system-of-systems is the CBRN microsensor (C-MS). These low-cost
deployable arrays of microelectronic devices can be deposited along
routes, zones, and areas that are beyond the line of sight of an optical
sensor such as the hyperspectral or LIDAR sensors, affording an early
warning and cross-cueing capability even when the optical systems are
unable to continuously observe or track the event. The sequence of
events contributing to integrated early warning as described are
depicted in Figure 4.
Figure 4. Conceptual rendition of integrated early warning.
CBRN Microsensors are depicted as red/yellow circles. Optical system
fields of view (FOV) are depicted as blue fans.[ISR: Intelligence,
Surveillance, and Reconnaissance. WMD: Weapons of Mass Destruction.
NLOS: Non-Line-Of-Sight]
The CBRN Support to Command and Control (CSC2) program is delivering a
modernized CBRN data management computational environment that consumes
the disparate data from both CBRN and non-CBRN data sources. It then
fuses and analyzes the data and projects the likely source terms and
downwind hazards to provide immediate decision support benefit. The
program is continuously updating the deployed computational systems,
analytic algorithms, and command and control interfaces to effectively
deliver CBRN threat awareness and understanding to operational
commanders and staffs at the tactical edge. CBRN professionals are
responsible for the effective application of the full complement of
situational awareness and understanding systems and analytic tools at
their disposal to continuously inform the Observe-Orient-Decide-Act
(OODA) cycle so that commanders preserve freedom of maneuver and
decision space inside the adversary’s OODA loop.
Author
Dr. Samuels is a research chemist at the U.S. Army
Combat Capabilities Development Command. He holds a doctorate degree
in physical chemistry from New Mexico State University, Las Cruces,
New Mexico.