Environmental $\gamma$-Ray Flux in Hall C at LNGS and Its Correlation with Radon Activity

This paper presents the first high-precision, efficiency-corrected spatial mapping of the environmental $\gamma$-ray flux in Hall C at the Gran Sasso National Laboratory, revealing a clear correlation with ambient radon levels and providing essential radiological data for future rare-event experiments.

The Gist

Imagine you are trying to listen to a very faint whisper in a giant, noisy cave. To hear that whisper clearly, you need to know exactly how loud the background noise is, where it's coming from, and what makes it change.

This paper is about scientists going into Hall C, a massive underground laboratory deep beneath a mountain in Italy (Gran Sasso), to map out that "background noise." Specifically, they are measuring gamma rays—invisible, high-energy particles that act like a constant, low-level hum of radiation coming from the rocks and air around them.

Here is the story of what they did, explained simply:

1. The Mission: Mapping the Invisible Fog

Scientists are building incredibly sensitive experiments (like DarkSide-20k and CUPID) in this hall to hunt for rare cosmic events. These experiments are so sensitive that even a tiny bit of background radiation can drown out the signal they are looking for.

Until now, the "noise map" for Hall C was very blurry. Scientists knew the noise existed, but they didn't know exactly how loud it was in different corners of the room or how it changed over time. This team decided to create a high-definition map.

2. The Tool: A "Radiation Camera" on Wheels

Instead of setting up a fixed sensor, they built a mobile laboratory on a cart.

• The Camera: At the heart of the cart is a High-Purity Germanium (HPGe) detector. Think of this as a super-precise camera that doesn't take pictures of light, but of energy. It can identify exactly which "notes" (energies) the gamma rays are playing.
• The Radon Sensor: They also strapped a radon monitor to the cart. Radon is a radioactive gas that seeps out of the ground. It's like a ghost that drifts through the air, and when it decays, it creates its own burst of gamma rays.
• The Journey: They rolled this cart to eight different spots in the hall. Some spots were near huge metal tanks (the experiments), and others were near the walls. They took measurements at each spot, like a photographer taking photos of a room from every angle to see how the light hits different surfaces.

3. The Calibration: Teaching the Computer to "See"

Before they could trust the data, they had to teach their computer simulation (a digital twin of their detector) how to behave.

• They used calibrated radioactive sources (like tiny, known lightbulbs of radiation) and placed them in specific spots around the detector.
• They compared what the real detector saw with what the computer simulation predicted.
• The "Dead Layer" Mystery: Old detectors often develop a "dead layer" on the outside—a thin skin where the detector stops working perfectly. The team had to figure out exactly how thick this skin was (about 1.7 mm) to make sure their computer model was accurate. Once they fixed this, the computer and the real detector agreed perfectly.

4. The Findings: The Hum of the Hall

After crunching the numbers, they found the average "volume" of the gamma-ray noise in the hall:

• The Result: The average flux is 0.46 gamma rays per square centimeter every second.
• The Variation: The noise wasn't the same everywhere. In some spots (near the big experiments and scaffolding), the noise was about 20–28% louder than in other spots. This is likely because the massive metal structures block some radiation but also trap air, changing how the gas moves.

5. The Big Discovery: The Gas Connection

The most interesting part of the story is the relationship between the gamma rays and the radon gas.

• The Correlation: The team watched the data over a month. They noticed that whenever the level of radon gas in the air went up, the gamma-ray "noise" went up with it.
• The Day/Night Cycle: They found a pattern similar to a city's traffic. During the day, people open doors and the ventilation fans run, flushing the radon gas out. At night, the hall is quiet, the doors are closed, and the radon gas builds up like fog in a valley. Consequently, the gamma-ray noise gets louder at night.
• The Math: They calculated that for every bit of extra radon gas, the gamma-ray rate increased slightly. However, the radon is only responsible for about 6–7% of the total noise. The rest (93%+) comes from the rocks and concrete walls themselves, which are always "humming" regardless of the air quality.

6. Why This Matters

This paper provides the first precise, corrected, and detailed map of the radiation environment in Hall C.

• It tells future scientists exactly what "background noise" to expect when they design their shields.
• It proves that the environment isn't static; it breathes. The radiation levels change with the ventilation and the radon gas.
• By understanding that the "noise" has two parts (the constant rock hum and the variable radon fog), scientists can better predict and subtract the background to hear the faint whispers of the universe they are trying to detect.

In short, they didn't just count the noise; they figured out why the noise changes, ensuring that future experiments in this hall have the best possible chance of success.

Technical Summary

Problem Statement

Next-generation rare-event search experiments operating in underground laboratories require an exceptionally detailed understanding of all background contributions to define sensitivity goals and design effective shielding. While the Gran Sasso National Laboratory (LNGS) has documented environmental $\gamma$-ray fluxes for Halls A and B, information regarding Hall C is extremely limited. Hall C hosts large-scale detectors such as DarkSide-20k and CUPID, whose massive shielding and structural components can significantly attenuate or distort the environmental $\gamma$-ray flux, creating strong position-dependent variations. Furthermore, Hall C features non-uniform concrete and rock surfaces and specific ventilation conditions that affect the spatial and temporal distribution of airborne radon ($^{222}$Rn). Previous measurements in Hall C were approximate, lacked uncertainty quantification, and did not provide a systematic spatial mapping or efficiency-corrected flux determination.

Methodology

The authors conducted a comprehensive measurement campaign using a high-purity germanium (HPGe) detector mounted on a movable cart, allowing for deployment at eight distinct locations within Hall C under identical operating conditions.

• Experimental Setup: The detector was a p-type semi-coaxial HPGe crystal (10% relative efficiency) housed in a U-type cryostat with liquid nitrogen cooling. The system included an ORTEC Nomad Plus multichannel analyzer and a laptop for remote control and data storage. A portable AlphaGUARD D2000 radon monitor was mounted on the same cart to simultaneously measure ambient radon activity, temperature, pressure, and humidity.
• Detector Commissioning and Calibration: The energy scale was calibrated using environmental $\gamma$-ray peaks ($^{238}$U, $^{232}$Th, and $^{40}$K chains) without external sources. The detector's intrinsic background was measured using a lead and copper shield, confirming it was negligible (<1% of the unshielded rate).
• Monte Carlo Modeling: A detailed Geant4 simulation of the detector geometry was developed. To ensure accuracy, the model was validated using calibrated $\gamma$-ray sources ($^{133}$Ba, $^{137}$Cs, $^{60}$Co) placed at various positions. A critical aspect of the modeling was the determination of the "dead layer" thickness (inactive volume on the crystal surface), which was optimized by comparing measured and simulated full-energy-peak efficiencies (FEPEs). The best-fit dead layer thicknesses were determined to be 1.7 mm for both the top/side and bottom layers.
• Flux Calculation: The environmental $\gamma$-ray flux was calculated by correcting the measured count rates for the energy-dependent detection efficiency (derived from the validated MC model) and the geometrical acceptance. The analysis covered an energy range of 57–2800 keV.
• Radon Correlation Study: A dedicated long-term run (five weeks) was performed at Position 8 to investigate the temporal correlation between the $\gamma$-ray rate and ambient radon activity, analyzing data in 1-hour and 6-hour bins to distinguish short-term fluctuations from longer trends.

Key Results

• Spatial Mapping: The $\gamma$-ray flux was measured at eight locations. Positions 7 and 8 (near the CUPID experiment and a scaffolding platform) exhibited rates approximately 21–28% higher than positions 1–6 (surrounding the DarkSide-20k cryostat). This variation is attributed to massive structures modifying the flux from surrounding rock and affecting air recirculation.
• Average Flux: The average environmental $\gamma$-ray flux in Hall C, integrated over 57–2800 keV, was measured to be $(0.46 \pm 0.06_{stat} \pm 0.03_{syst}) \text{ cm}^{-2} \text{ s}^{-1}$. This represents the first precise, uncertainty-controlled determination for this hall.
• Radon Correlation: A clear temporal correlation was observed between the $\gamma$-ray rate and ambient radon activity. The data showed that $\gamma$-ray rates tend to increase during nighttime hours, coinciding with radon accumulation due to reduced ventilation.
• Quantitative Dependence: A linear fit of the binned data revealed that an increase of 1 Bq m$^{-3}$ in average radon activity corresponds to an increase of approximately 0.011 Hz in the measured $\gamma$-ray rate. For typical radon levels in Hall C (~100 Bq m$^{-3}$), the radon-induced contribution accounts for roughly 6.5% of the total baseline rate. The remaining ~93.5% is attributed to a radon-independent baseline originating from the surrounding rock and structural materials.

Significance and Claims

The paper claims to provide the first high-precision and efficiency-corrected mapping of the $\gamma$-ray flux in Hall C of LNGS. By combining spatial mapping with simultaneous radon monitoring, the study establishes that the environmental $\gamma$-ray field in Hall C is not only position-dependent but also time-dependent, driven significantly by variations in radon activity.

The authors emphasize that these results substantially improve the radiological characterization of Hall C. The derived flux values and the understanding of the radon-$\gamma$ correlation provide key inputs for:

1. Designing detector shieldings for current and future rare-event experiments (e.g., DarkSide-20k, CUPID).
2. Estimating expected background levels more accurately.
3. Defining sensitivity goals for low-background experiments operating in this environment.

The work concludes that the measured flux values should be understood as corresponding to the specific radon activity present during each measurement, highlighting the necessity of joint and continuous monitoring of these environmental parameters for accurate background modeling.