  Climate change resulting from the misuse and over-exploitation of natural
resources has affected and continues to impact the planet's ecosystem. This
pressing issue is leading to the development of novel technologies to sense and
measure damaging gas emissions. In parallel, the accelerating evolution of
wireless communication networks is resulting in wider deployment of mobile
telecommunication infrastructure. With 5G technologies already being
commercially deployed, the research community is starting research into new
technologies for 6G. One of the visions for 6G is the use of the terahertz
(THz) spectrum. In this paper, we propose and explore the use of THz spectrum
simultaneously for ultrabroadband communication and atmospheric sensing by
leveraging the absorption of THz signals. Through the use of machine learning,
we present preliminary results on how we can analyze signal path loss and power
spectral density to infer the concentration of different climate-impacting
gases. Our vision is to demonstrate how 6G infrastructure can provide sensor
data for climate change sensing, in addition to its primary purpose of wireless
communication.
