Designing surface CO2 monitoring network to constrain the Indian land fluxes. (1st December 2019)

• Record Type: Journal Article
• Authors: Nalini, K.; Sijikumar, S.; Valsala, Vinu; Tiwari, Yogesh K.; Ramachandran, Radhika
• Is Part Of: Atmospheric environment. Volume 218(2019)
• Publication Date: 2019-12-01
• Subjects: Carbon dioxide -- Bayesian inversion -- Optimal network -- Potential stations; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2019.117003
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: Optimal network design, for ground-based monitoring of atmospheric mole fractions of carbon dioxide (CO2 ) over India to better constrain the Indian terrestrial surface fluxes, is proposed here using a Lagrangian Particle Dispersion Model FLEXPART and Bayesian inversion methods. Potential emission sensitivity from FLEXPART, prior flux uncertainties from CASA-GFED biosphere fluxes and CDIAC fossil fuel fluxes, and assumed uniform observational uncertainty of 2 ppm are used to calculate prior and posterior cost functions. A total of 73 grid cells are identified over the Indian region in 2°x2° latitude by longitude resolution assuming each cell as a potential site, ' a-priori' . Further, the effectiveness of CO2 observations from these locations to reduce the Indian terrestrial flux uncertainty is quantified using an incremental optimization method. Based on the above objective, we have (a) ranked the existing nine stations, (b) devised a methodology to design an extended network by adding a few more potential stations to the existing stations, and (c) identified a completely new set of optimal stations for measuring atmospheric CO2 over India. The study shows that the base network of existing stations scattered over India could reduce the uncertainty of Indian terrestrial surface flux estimation in an inversion framework, at this resolution, by more than 30% during post-monsoon and winter season, and by more than 15% during other parts of the year. Addition of five new stations to the base network could reduce the uncertainty by an additional 15% for all the seasons reaching up to 45%. In the 'new network', twelve stations are able to achieve an equivalent flux uncertainty reduction of fourteen stations achieved by the 'extended network' during each season. Locations of stations are more important than the magnitude of reduction since it depends on the values of the prior and observational uncertainties. The most important and essential 'new' stations in the extended network are over the northeastern region and Indo-Gangetic plain, during most of the year. Only during the post-monsoon season, additional stations are required in the western peninsular region. Finally, a consolidated set for all seasons comprising seventeen members is proposed. The study highlights a major zone of CO2 'observational void' that exists in potential locations near east and northeast parts of India. Immediate requirement of CO2 monitoring initiative in these areas is highly recommended. Highlights: Designed an optimal network for monitoring CO2 fluxes over India. Existing CO2 monitoring stations over India could reduce flux uncertainty by 30%. The most required stations are over the northeastern and Indo-Gangetic region. New optimal network highlights 'observational void' over east and northeast India.