Environmental sensors gradually develop errors during the course of a deployment. Operators routinely check, clean, and recalibrate each sensor, but current practice treats the checks as error-free and reports no uncertainty for the corrected data. We present a statistical method that quantifies uncertainty in both the checks and the corrections, combines information across a sensor network to improve estimates for new sensors, and is efficient enough for routine use.

The team launched a specialized balloon from India to capture the weak electric fields that connect Earth to the upper atmosphere. Measuring these fields is difficult because the stratosphere is highly resistant to electrical currents flowing between Earth and upper atmosphere and the equipment itself can create interference. By using a new sensor design, the team successfully recovered noise-free data. These results help to map the global electric circuit in tropical regions.

We developed and tested an affordable, open-source camera system for long-term and temporary monitoring. Flexible settings, automated storage, and data transfer allow it to meet varied needs and operate in remote or harsh environments. Tests at volcanoes and in the laboratory showed reliable performance and enabled measurements of lava flows, volcanic plumes, and rapid processes. The system could broaden visual monitoring at less-monitored sites and support other environmental applications.

Ammonia from agriculture can harm ecosystems and air quality, but tracking emissions accurately is difficult. We developed a method combining in situ measurements and satellite observations to estimate ammonia emissions across the Netherlands. In situ measurement captures local detail while satellites provide broad coverage; combining both improves estimates. We also identified where new measurement stations would most improve emission monitoring, helping guide future network design.

Earthquake planning needs more than maps of past shaking. This study uses long-term strong-motion records from the İzmir Basin to update future earthquake scenarios and identify areas that may face repeated or uncertain high shaking. The results show that the Tuzla Fault scenario gives the largest potential impact area. The workflow can help cities use monitoring data to guide preparedness, inspection, and resilience planning before damaging earthquakes occur.

To enable the use of the Recoverable Autonomous Sonde for exploring Qilin Subglacial Lake in Antarctica, its original thermal head was upgraded. The material was changed from pure copper to chromium‑zirconium copper, and the thermal head was redesigned as a solid construction to withstand high water pressures. Additionally, the incorporation of a water‑jetting component significantly improved drilling performance in clear, dust‑laden, and debris‑rich ice.

This study presents a new framework showing how instrument noise can affect the ability of seismic networks to detect earthquakes after signal correction. The results demonstrate that modern dense networks may become increasingly limited by instrument quality rather than station spacing alone, with important implications for future seismic-network design and optimization.

This study investigates concepts of measuring magnetic fields with CubeSats. An exemplary instrument including the sensor, electronics, and boom was designed, built and tested. A novel Application-Specific Integrated Circuit has been used and concepts of larger missions have been adapted. Tests have shown the radiation hardness of the electronics and an improved performance over existing concepts. The results validate the technology and set further directions of CubeSat instrument developments.

Scientific observations carry context such as uncertainty, quality assessments and modeling decisions, yet usually merely average values survive when data moves between research teams. This paper presents a method for packing that context into compact binary codes inside standard data formats. Three linked projects show network effects when information accumulates across independent teams. The approach merges with existing analyses and works despite current scientific incentive structures.

Landers and rovers deployed during planetary surface missions are expected to encounter small-scale surficial changes due to natural processes such as wind erosion and/or artificial processes caused by robotic/human exploration. By measuring centimeter-scale changes in sand cover at a Mars analog site, we show that a ground-based LiDAR system situated on a mobile platform can identify similar changes on planetary surfaces in short timeframes and without compromising accuracy.