Abstract. Atmospheric greenhouse gases (GHGs), such as carbon dioxide (CO 2 ) and methane (CH 4 ), are important climate forcing agents due to their significant impacts on the climate system. The present study brings out first continuous measurements of atmospheric GHGs using highprecision LGR-GGA over Shadnagar, a suburban site of Central India during the year 2014. The annual mean CO 2 and CH 4 over the study region are found to be 394 ± 2.92 and 1.92 ± 0.07 ppm (µ ± 1σ ) respectively. CO 2 and CH 4 show a significant seasonal variation during the study period with maximum (minimum) CO 2 observed during pre-monsoon (monsoon), while CH 4 recorded the maximum during postmonsoon and minimum during monsoon. Irrespective of the seasons, consistent diurnal variations of these gases are observed. Influences of prevailing meteorology (air temperature, wind speed, wind direction, and relative humidity) on GHGs have also been investigated. CO 2 and CH 4 show a strong positive correlation during winter, pre-monsoon, monsoon, and post-monsoon with correlation coefficients (R s ) equal to 0.80, 0.80, 0.61, and 0.72 respectively, indicating a common anthropogenic source for these gases. Analysis of this study reveals the major sources for CO 2 are soil respiration and anthropogenic emissions while vegetation acts as a main sink, whereas the major source and sink for CH 4 are vegetation and presence of hydroxyl (OH) radicals.

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Abstract-Melody extraction algorithms for single-channel polyphonic music typically rely on the salience of the lead melodic instrument, considered here to be the singing voice. However the simultaneous presence of one or more pitched instruments in the polyphony can cause such a predominant-F0 tracker to switch between tracking the pitch of the voice and that of an instrument of comparable strength, resulting in reduced voice-pitch detection accuracy. We propose a system that, in addition to biasing the salience measure in favor of singing voice characteristics, acknowledges that the voice may not dominate the polyphony at all instants and therefore tracks an additional pitch to better deal with the potential presence of locally dominant pitched accompaniment. A feature based on the temporal instability of voice harmonics is used to finally identify the voice pitch. The proposed system is evaluated on test data that is representative of polyphonic music with strong pitched accompaniment. Results show that the proposed system is indeed able to recover melodic information lost to its single-pitch tracking counterpart, and also outperforms another state-of-the-art melody extraction system designed for polyphonic music.Index Terms-Fundamental frequency estimation, music information retrieval (MIR), music transcription, predominant pitch detection.

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