GREENHOUSE GASES
| Title |
Authors |
Affiliation of the authors |
Issue |
Pages |
PDF |
| A hybrid model based on an artificial neural network with a long chain of short-term memory elements and a discrete wavelet transform for predicting surface methane content in the Arctic area | Buevich, A.G., Sergeev, A.P., Shichkin, A.V., Baglaeva, E.M., Subbotina, I.E., Butorova, A.S. | Institute of Industrial Ecology | v13, 3 2023 | 428-436 | | | Monitoring of the methane concentration changes in the Arctic atmosphere in 2019—2021 according to the TROPOMI spectrometer data | Bogoyavlensky, V.I., Sizov, O.S., Nikonov, R.A., Bogoyavlensky, I.V. | OGRI RAS | v12, 3 2022 | 304-319 | | | Dynamics in the content of greenhouse gases in the surface layer of atmospheric air of the Arctic Island of Bely in the summer period 2015—2017 | Subbotina, I.E., Baglaeva, E.M., Buevich, A.G., Sergeev, A.P., Shichkin, A.V. | Institute of Industrial Ecology | v12, 1 2022 | 68-76 | | | Assessment of energy-related environmental impacts during the implementation of promising projects for the development of deposits in the Arctic territories of the Russian eastern regions | Saneev, B.G., Maysyuk, E.P., Ivanova, I.Y. | ESI SB RAS | v11, 4 2021 | 466-480 | | | Earth degassing in the Arctic: the genesis of natural and anthropogenic methane emissions | Bogoyavlensky, V.I., Sizov, O.S., Nikonov, R.A., Bogoyavlensky, I.V., Kargina, T.N. | OGRI RAS | 3 (39) 2020 | 6-22 | | | Two-step combined algorithm for improving the accuracy of predicting methane concentration in atmospheric air based on the NARX neural network and subsequent prediction of residuals | Subbotina, I.E., Buevich, A.G., Sergeev, A.P., Shichkin, A.V., Baglaeva, E.M., Remezova, M.S. | Institute of Industrial Ecology, UFU | 2 (38) 2020 | 59-67 | | | Some results of greenhouse gases monitoring in the Arctic region of Russia | Antonov, K.L., Markelov, Y.I., Markelov, Y.I., Buevich, A.G., Medvedev, A.N., Manzhurov, I.L. | Institute of Industrial Ecology | 1 (29) 2018 | 56-67 | |
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