Integrating sustainability in atmospheric chemistry analysis
The concepts that help us to better understand the atmospheric chemistry, including the composition and dynamics of air particles and gaseous species, and their impact on climate and human health, rely on the development of sensitive and selective analytical methods that allow one to measure an ever-increasing range of analytes, whose physicochemical features vary both in time and space. Motivated by the ongoing awareness of the need to adopt eco-friendly practices, this perspective highlights analytical practices with the potential to meet green and sustainable requirements and that have offered an almost unexplored playground for deciphering and mapping the intricacies of atmospheric chemistry. The most promising green metrics currently available to estimate the environmental impact and efficiency of analytical methods are also highlighted. Rather than presenting new quantitative data, this perspective offers a critical and conceptual discussion aimed at advancing the adoption of sustainable analytical solutions in the highly challenging field of atmospheric chemistry analysis. • Eco-friendly analytical methods for atmospheric chemistry analysis. • Advances in sustainable air sampling: novel adsorbent materials. • Advances in the characterization of organic aerosols combined with machine leaning. • Advances in sustainable air quality monitoring using GC-IMS and IoT-based devices. • Metric tools for assessing the green profile and efficiency of analytical methods.
Authors
- Regina M.B.O. Duarte (ORCID: https://orcid.org/0000-0002-1825-6528)
- Armando C. Duarte (ORCID: https://orcid.org/0000-0002-4868-4099)
Institutions
- University of Aveiro (PT)
Publication Details
- Journal
- Current Opinion in Green and Sustainable Chemistry
- Published
- 2025-09-04
- DOI
- https://doi.org/10.1016/j.cogsc.2025.101048
- Primary Topic
- Atmospheric chemistry and aerosols
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Fundação para a Ciência e a Tecnologia