Instrumentation and its development play a key role in advancing research, providing state-of-the-art tools to address open scientific questions. Over the last several decades, atmospheric environmental monitoring has benefited from novel spectroscopic measurement techniques that arose from breakthroughs in photonic technologies from the UV to THz spectral regions. These advances open new research avenues for observation of spatial and long-term trends in the concentration and optical properties of atmospheric constituents, and for studying atmospheric processes in laboratories and atmospheric simulation chambers. These advances are vital for expanding our insight into atmospheric composition and processes, and ultimately their impacts on air quality and global climate change.
The upcoming session of "Advanced Spectroscopic Measurement Techniques and Applications for Atmospheric Science" focuses on the latest developments and advances in a broad range of spectroscopic instrumentation and technologies, and their use in a variety of atmospheric applications. It aims to be a platform for sharing information on the state-of-the-art and emerging developments for atmospheric sensing. This interdis¬ciplinary forum aims to foster discussion among experimentalists, atmospheric scientists, and development engineers. It is also an opportunity for R&D and analytical equipment companies to evaluate the capabilities of new instrumentation and techniques.
Topics for presentation include developments, demonstrations and applications of novel spectroscopic methods and instruments dedicated to measuring atmospheric aerosols, isotopologues, greenhouse gases and other trace gases, as well as associated atmospheric meteorological parameters such as temperature, wind speed, humidity, etc. Studies of vertical concentration profiles and flux measurements are all welcome when the instrumentation is a focus of the work. Spectroscopic methods could include high sensitivity and selectivity spectroscopy (such as dual-comb spectroscopy, cavity-enhanced absorption/Raman spectroscopies, photoacoustic & photothermal spectroscopy and other spectroscopic methods), low-cost optical sensors, heterodyne radiometry and imaging spectroscopy. Applications include laboratory demonstration, ground and airborne platforms (UAV/drone, balloon, aircraft) observations, smog chamber studies. Approaches using new spectral data analysis tools (including machine learning) are encouraged.
The upcoming session of "Advanced Spectroscopic Measurement Techniques and Applications for Atmospheric Science" focuses on the latest developments and advances in a broad range of spectroscopic instrumentation and technologies, and their use in a variety of atmospheric applications. It aims to be a platform for sharing information on the state-of-the-art and emerging developments for atmospheric sensing. This interdis¬ciplinary forum aims to foster discussion among experimentalists, atmospheric scientists, and development engineers. It is also an opportunity for R&D and analytical equipment companies to evaluate the capabilities of new instrumentation and techniques.
Topics for presentation include developments, demonstrations and applications of novel spectroscopic methods and instruments dedicated to measuring atmospheric aerosols, isotopologues, greenhouse gases and other trace gases, as well as associated atmospheric meteorological parameters such as temperature, wind speed, humidity, etc. Studies of vertical concentration profiles and flux measurements are all welcome when the instrumentation is a focus of the work. Spectroscopic methods could include high sensitivity and selectivity spectroscopy (such as dual-comb spectroscopy, cavity-enhanced absorption/Raman spectroscopies, photoacoustic & photothermal spectroscopy and other spectroscopic methods), low-cost optical sensors, heterodyne radiometry and imaging spectroscopy. Applications include laboratory demonstration, ground and airborne platforms (UAV/drone, balloon, aircraft) observations, smog chamber studies. Approaches using new spectral data analysis tools (including machine learning) are encouraged.