Influence of meteorological parameters on atmospheric CO2 at Bharati, the Indian Antarctic research station

• Published in: Polar Research
• Main Authors: Mahesh Pathakoti, Sreenivas Gaddamidi, Biswadip Gharai, Prijith Sudhakaran Syamala, Pamaraju Venkata Narasimha Rao, Saroj Bandh Choudhury, Kaila Venkata Raghavendra, Vinay Kumar Dadhwal
• Format: Article in Journal/Newspaper
• Language: English
• Published: Norwegian Polar Institute 2018
• Subjects: Carbon dioxide; Li-Cor CO2/H2O analyser; precipitation; relative humidity; wind speed; long-range air-mass transport; geo; envir; Antarctic; Austral; Indian; Antarc*; Antarctica; Polar Research
• Online Access: https://doi.org/10.1080/17518369.2018.1442072; https://doaj.org/article/4a381dffab7f4a0f81d9570805ccb542

During the 35th Indian Scientific Expedition to Antarctica, measurements of atmospheric carbon dioxide (CO2) were carried out using a Li-Cor CO2/H2O analyser at Bharati, the Indian Antarctic research station. This study examines the short-term variability of atmospheric CO2 during the austral summer (January–February) of 2016. An average of 396.25 ± 4.20 ppm was observed during the study period. Meteorological parameters such as relative humidity, precipitation, wind speed, air temperature and atmospheric boundary layer height in conjunction with photosynthetically active radiation, the biological activity indicator which modulates atmospheric CO2 concentration have been investigated. High wind speed (>20 m s−1) combined with precipitation scavenges CO2 in the atmosphere, resulting in low concentrations at the study site. The lowest CO2 concentration of 385 ppm coincided with heavy precipitation of 15 mm during study period. Statistical analysis of the data shows that precipitation and relative humidity independently correlated 55% (r = −0.55) and 32% (r = −0.32), respectively, with the variability of CO2 mixing in the atmosphere at the study site. Atmospheric CO2 was significantly correlated with precipitation alone with a p value of 0.003. Further, multiple regression analysis was performed to test the significant relation between variability of atmospheric CO2 and meteorological parameters. Long-range air-mass transport analysis depicted that the majority of the air masses are reaching the study site through the oceanic region.