Measurement report: Regional characteristics of seasonal and long-term variations in greenhouse gases at Nainital, India, and Comilla, Bangladesh

Emissions of greenhouse gases (GHGs) from the Indian subcontinent have increased during the last 20 years along with rapid economic growth; however, there remains a paucity of GHG measurements for policy-relevant research. In northern India and Bangladesh, agricultural activities are considered to play an important role in GHG concentrations in the atmosphere. We performed weekly air sampling at Nainital (NTL) in northern India and Comilla (CLA) in Bangladesh from 2006 and 2012, respectively. Air samples were analyzed for dry-air gas mole fractions of CO2, CH4, CO, H2, N2O, and SF6 and carbon and oxygen isotopic ratios of CO2 (δC-CO2 and δO-CO2). Regional characteristics of these components over the Indo-Gangetic Plain are discussed compared to data from other Indian sites and Mauna Loa, Hawaii (MLO), which is representative of marine background air. We found that the CO2 mole fraction at CLA had two seasonal minima in February–March and September, corresponding to crop cultivation activities that depend on regional climatic conditions. Although NTL had only one clear minimum in September, the carbon isotopic signature suggested that photosynthetic CO2 absorption by crops cultivated in each season contributes differently to lower CO2 mole fractions at both sites. The CH4 mole fraction of NTL and CLA in August–October showed high values (i.e., sometimes over 4000 ppb at CLA), mainly due to the influence of CH4 emissions from the paddy fields. High CH4 mole fractions sustained over months at CLA were a characteristic feature on the Indo-Gangetic Plain, which were affected by both the local emission and air mass transport. The CO mole fractions at NTL were also high and showed peaks in May and October, while CLA had much higher peaks in October– March due to the influence of human activities such as emissions from biomass burning and brick production. The N2O mole fractions at NTL and CLA increased in June–August and November–February, which coincided with the application of nitrogen fertilizer and the burning of biomass such as the harvest residues and dung for domestic cooking. Based on H2 seasonal variation at both sites, it appeared that the emissions in this region were related to biomass burning in addition to production from the reaction of OH and CH4. The SF6 mole fraction was similar to that at MLO, suggesting that there were few anthropogenic SF6 emission sources in the district. The variability of the CO2 growth rate at NTL was different from the variability in the CO2 growth rate at MLO, which is more closely linked to the El Niño–Southern Oscillation (ENSO). In addition, the growth rates of the CH4 and SF6 mole fractions at NTL showed an anticorrelation with those at MLO, indicating that the frequency of southerly air masses strongly influenced these mole fractions. These findings showed that rather large regional cliPublished by Copernicus Publications on behalf of the European Geosciences Union. 16428 S. Nomura et al.: Regional characteristics of seasonal and long-term variations matic conditions considerably controlled interannual variations in GHGs, δC-CO2, and δO-CO2 through changes in precipitation and air mass.


Weather data 159
Monthly precipitation data for Nainital uses the monthly precipitation of the state of Uttarakhand, which includes 160 Nainital. The data during January 2007 to December 2017 were taken from the rainfall report on the IMD (India Meteorological  website (http://www.data.jma.go.jp/gmd/cpd/monitor/climatview/frame.php?y=2019&m=7&d=30&e=0). 168

Back trajectory analysis 169
To determine the sources of regional air masses affecting the stations (NTL and CLA), we calculated backward air 170 trajectories using the Meteorological Data Explorer (METEX) system (Zeng and Fujinuma, 2004)  The ratio of air mass from south was calculated by the frequency of the air mass from south side on the flask sampling 176 date with reference to the backward air trajectories data. 177

Data analysis method for short-term and long-term 178
Mean values for every 10 days were calculated from the weekly data and were used to calculate the long-term trend 179 and smoothing fitting curve. The value of the missing period was supplemented with an approximate expression of the values 180 before and after the missing period for calculating the continuous long-term trend and smoothing fitting curve. 181 Long-term trends of the mole fractions were calculated based on the idea of Thoning et al. (1989) with a cut-off 182 frequency of 667 days (0.5472 cycles yr -1 ) for a FFT filter. The smoothing fitting curve was made for an FFT filter with a cut-183 off frequency of 50 days (7.3 cycles yr -1 ). 184 We defined and expressed seasonal component by a "Δ" term (e.g., ΔCO2) which was calculated by subtraction of the 185 long-term trend curve from 10 days mean of real data. Also, we defined and expressed short-term variations by a "d" term 186 (e.g., dCO2), which were characterized by the deviation of 10 days mean of real data from the smoothing fitting curve. Figure  187 2(c) shows how such components were calculated. Growth rates of mole fraction of observed gases were calculated using the 188 long-term trends. 189 GHGs emissions while passing over the Indo-Gangetic Plain. However, the CO2 mole fraction changed not only due to 198 transport but also due to the photosynthetic sink strength of terrestrial ecosystems and cultivated crops. 199

Results and discussion
Annual mean GHG mole fractions at NTL and CLA are summarized in Table 1. Annual CO2 mole fractions at both sites 200 were quite low compared to MLO and other Indian sites such as CRI. For example, in 2010, 386.5 ppm was reported at NTL, 201 391.9 ppm at CRI (Bhattacharya et al., 2009), and 391.3 ppm was reported at PON (Lin et al. 2015). Note that there is no data 202 for CLA in 2010, however the annual CO2 mole fraction at CLA is usually only 1-2 ppm higher than at NTL. This seemed to 203 be due to the influence of photosynthesis at both sites. Generally, the CO2 mole fractions at NTL and CLA decreased strongly 204 (typically twice a year) due to photosynthesis of local crops, making the annual CO2 levels lower than at other sites despite the 205 likelihood that anthropogenic emission are high in this area. 206 On the other hand, the annual mean mole fractions of CH4, CO, H2, and N2O at NTL and CLA (Table 1) [Lin et al., 2015]). In this region, high CH4 and N2O emissions 210 were possible from paddy fields and cultivated areas. Also, much CO is considered to be produced by biomass burning in this 211 region. As for H2, the mole fraction at CLA was higher than those at other Indian sites, however, it was relatively low at NTL 212 compared to other sites such as CRI (Bhattacharya et al., 2009), PON, and PBL (Lin et al., 2015), but similar to HLE, which 213 is located on a higher mountain. In the case of the SF6 mole fraction, it has smaller regional differences, suggesting there are 214 no remarkable SF6 sources near the measurement sites. Below we describe in detail the characteristics of sources and sinks of 215 each component (CO2, δ 13 C-CO2, δ 18 O-CO2 CH4, CO, H2, N2O, and SF6) at NTL and CLA on the Indo-Gangetic Plain in terms 216 of seasonal variations, amplitudes, and growth rates. 217 3.2 CO2 and δ 13 C-CO2 218 3.2.1 CO2 mole fraction and growth rate variations 219 Figure 4 shows the time series of the atmospheric CO2 mole fraction and the isotopic ratio of δ 13 C-CO2 at our sampling 220 sites (NTL and CLA) together with data from CRI on the west coast of India and MLO in Hawaii. The CO2 mole fractions at 221 NTL and CLA in August-October were characteristically lower (approximate 10-20 ppm) than the mole fractions observed 222 at CRI and MLO. The CRI and MLO sites are representative of CO2 mole fractions in the Southern and Northern Hemisphere, 223 respectively, for the period of the southwest monsoon season (June-September). On the other hand, the δ 13 C-CO2 at NTL and 224 CLA were inversely correlated with the CO2 mole fractions, and generally the values at both sites were higher than at MLO 225 and CRI. 226 Air masses at NTL and CLA in August-October passed over the Indo-Gangetic Plain and the southeast area of India,227 respectively, while the air masses of CRI were transported from the Indian Ocean region (Fig. 3). Thus, it was suggested that 228 the air mass from the Indian Ocean in August-October prevailing over CRI was hardly influenced by anthropogenic emission 229 and photosynthesis over the Indian subcontinent, whereas CO2 mole fractions over NTL and CLA seemed to be influenced 230 during these season by the sources and sinks on the Indo-Gangetic Plain and the south/east areas of the Indian subcontinent. 231 Such transport characteristics must affect the annual average and growth rates in the CO2 molar ratio and δ 13 C-CO2 in addition 232 to their seasonal variations. 233 relationship is often explained from the viewpoint of a global temperature anomaly, which has a strong relationship with the 240 ENSO index. On the other hand, the variability at NTL has no associations with the variability in the CO2 growth rate at MLO 241 and the ENSO index ( Fig. 5[b]). Both growth rates seemed to be slightly inversely correlated with each other from 2007 to 242 2015. However, since then, similar relatively high growth rates have been observed for both sites around 2015-2016 and 2018-243 2019, indicating that overall, the CO2 growth rate at NTL is less correlated with the CO2 growth rate at MLO and the ENSO 244 index. 245 It is well known that the Indian Ocean Dipole controls meteorological conditions such as air mass transportation and 246 precipitation patterns on the Indian subcontinent (e.g., Saji et al., 1999, Ashok et al., 2004, Hong et al., 2008. Such changes 247 in regional climatic pattern could affect the CO2 uptake flux by plants in the surrounding area and the atmospheric movement, 248 leading to a change in the CO2 growth rate. However, we did not find a simple relationship between DMI and CO2 growth rate 249 at NTL (Fig. 5[b]). Here we have shown that the pattern of CO2 growth rate in this region is different from the global pattern 250 seen in places like MLO, but the relationship between local climatic factors and changes in CO2 sinks and emissions is likely 251 to be complex, and further study is needed to interpret the differences. 252 In Bangladesh, rice, being the staple food, is cultivated three times a year in some regions. Usually rice is grown twice 290 (Aus and Amon rice) from April-October (including the monsoon season), however, often rice is also cultivated (Boro rice) in 291 the winter season from November-April (SID/MP, 2018). Other agricultural products include maize, jute, and vegetables in 292 the summer season, and small amount of wheat in the winter season. Therefore, we concluded that the observed lower CO2 293 mole fractions in July-October and February-March were influenced by CO2 uptake by local plants (mainly rice). Especially 294 at CLA, the lower mole fraction in February-March was clear and a strong contribution from CO2 uptake from Boro rice was 295 estimated. As another viewpoint on CO2 seasonal variation, we observed that the CO2 maximum in May was not so high, while 296 the CO2 mole fraction in December was higher. Because precipitation in Bangladesh is stronger than in the north Indian region, 297 the duration of rice cultivation over summertime is also longer than in north India. Therefore, the contribution of plant uptake 298 to the CO2 mole fraction in the atmosphere at CLA over the summer season is likely to be relatively large compared to that at 299 NTL. 300 Thus, the decreases in the CO2 mole fractions in February-March and September in NTL and CLA were estimated to 301 be caused by photosynthesis of plants cultivated in each season over the Indo-Gangetic Plain. NTL and CLA indicated this 302 more clearly compared with other Indian sites due to the proximity to the source region. Figure 7(a) shows the relationships 303 between the annual mean CO2 mole fraction and δ 13 C-CO2 in 2010 and 2012. The slope between the CO2 mole fraction and 304 δ 13 C-CO2 showed -0.050 and -0.054‰ ppm -1 which indicated that the spatial variability of the atmospheric CO2 mole fraction 305 (e.g., a lower mole fraction at NTL than at MLO and CRI) basically occurred due to CO2 exchange between the atmosphere 306 and terrestrial biosphere. 307 Furthermore, we examined the relationship of the CO2 mole fraction and carbon isotope ratio, because there are some 308 seasonal differences in the species cultivation. On the Indo-Gangetic Plain, rice (especially in Bangladesh) and wheat 309 (especially in North India), as C3 plants, are cultivated in January-March, while C4 plants (e.g., maize, sugarcane, sorghum 310 and Bajra (Pearl millet) in addition to rice are cultivated on the Indo-Gangetic Plain and in Bangladesh in June-September 311 (DAC/MA, 2015; SID/MP, 2018; DES/MAFW, 2019). We calculated the end member of the isotope value for absorbed CO2 312 by using intercept values of the "Keeling plot" between the reciprocal of the CO2 mole fraction and the ratio of δ 13 C-CO2 313 obtained from two continuous datasets of air samples, which has > 1 ppm difference in CO2 mole fraction and > 0.05‰ in 314 δ 13 C-CO2. Since in this study two datasets had 1-week intervals, we assumed that the difference in CO2 and δ 13 C between two 315 datasets would include broader influences of photosynthetic activities from relatively large areas on the Indo-Gangetic Plain. 316 We found that the intercept values of NTL and CLA showed differences in January-March and June-September ( Fig.  317   7[b]), which appeared to reflect the differences in the contributions of C3 and C4 plants in this region. In June-September, we 318 found relatively heavier intercept values at both NTL (-25.0 ± 2.4‰) and CLA (-23.5 ± 4.1‰), suggesting that C4 plants partly 319 contributed to the CO2 absorption (or emission) in this season, while in January-March, the end member showed -29.0 ± 4.3‰ 320 (NTL) and -28.3 ± 4.0‰ (CLA), which were similar to the general C3 plant (rice or wheat). If we assume the value for C4 plant 321 to be -12 to -14‰, the contributions of C4 plant in NTL and CLA were approximately 25 ± 5% and 31 ± 9%, respectively. a similar proportion as estimated by the C isotope ratio. In the case of Bangladesh, despite there being no recent data reported, 325 according to data in 2008, the area for maize was approximately < 10% compared to the rice area. However, based on the 326 recent C isotope ratio, it appears likely that more maize has been cultivated. 327

δ 18 O-CO2 328
In general, δ 18 O-CO2 is related to that value of water in plants and soil, because oxygen atom of CO2 can be exchanged 329 with oxygen atom of H2O in plant and bacteria cells during photosynthesis and soil respiration. Plants and soil water mainly 330 originate from rainwater in the study region, however, in the case of the agricultural area, water is often introduced by irrigation 331 systems using river and groundwater. In many cases, photosynthesis produced relatively heavier δ 18 O-CO2 than soil respiration 332 because δ 18 O-H2O in plant becomes heavier than soil water due to plant transpiration. VSMOW water as mentioned in section 2.3), which was higher than that of rain and other water reservoirs, suggesting that Based on the fact that during the summer monsoon season, δ 18 O-CO2 decreased from 1 to -2‰ with a decrease of δ 18 O-367 H2O from 0 to -10 or -15‰ in the rain, the range of variation in δ 18 O-CO2 was approximately one third or one fifth that of rain. 368 Because land water may come from both rain and irrigation systems, the real ranges of δ 18 O in soil water and plant water are 369 likely to be smaller than in the case of rain only. Furthermore, because CO2 from soil respiration contributes more in the rainy 370 season, a balance between photosynthesis and respiration CO2 will, in general, have a small effect on the seasonal variation. 371 As for the annual trend of δ 18 O-CO2 shown in Figure 8 correlation can be seen. Therefore, the amount of precipitation partly contributes to the regional level of δ 18 O-CO2. However, 381 it must be influenced not only by precipitation but also by seasonal changes in air flow patterns and rain systems, as explained 382 above, as well as by the water reservoir situation, soil water content at that time, and photosynthesis in the region.

CH4 390
The CH4 mole fractions at NTL and CLA are illustrated in Figure 9(a). We detected high CH4 mole fractions at NTL 391 and CLA, where they sometimes exceeded 2,100 and 4,000 ppb, respectively, showing that the Indo-Gangetic Plain region 392 had relatively strong CH4 emissions. The seasonal amplitude of the CH4 mole fraction, especially at CLA (486 ± 225 ppb; 393 Table 2) was much larger than the those of other Indian sites such as NTL (114 ppb ratios of CH4 to CO in biomass burning such as crop residue burning, firewood burning, and biogas burning were 0.04-0.90 430 ppb ppb -1 . Therefore, the ratios observed in these seasons could suggest a strong influence on CH4 and CO emissions from 431 biomass burning (such as crop residue burning), despite the other large CH4 emissions such as paddy fields and waste treatment, 432 which will increase the ratio, especially at CLA in July-September. 433 As a result, it is evident that annual CH4 mole fractions at the sites used in this study on the Indo-Gangetic Plain are 434 enriched by various CH4 sources, depending on the season. Generally speaking, because April-June is a dry and hot season, 435 CH4 decomposition processes will proceed, decreasing its mole fraction at both sites. 436 The variability in the CH4 growth rate in the trend line at NTL was different to the variability at MLO (Fig. 9[b]), which 437 may be influenced by regional climatic condition, including the Indian Ocean Dipole. Because the frequency of air mass 438 transportation from the south increased if the Indian Ocean Dipole was often activated, the air mass passed over the Indo-439 Gangetic Plain (which has strong CH4 emissions), reaching NTL with a high CH4 mole fraction. The difference between the 440 variability in the CH4 growth rate between NTL and CLA may also be explained by the above hypothesis. If the frequency of 441 air mass transportation from the south increased by the activation of Indian Ocean Dipole (e.g., in 2015) because the air mass 442 was directly transported from the Indian Ocean with a relatively low CH4 mole fraction, the CH4 mole fraction at CLA would 443 become relatively low compared to a usual year ( Fig. 9[b]). On the other hand, as mentioned previously, in 2015-2017, even 444 in high Indian Ocean Dipole mode, Bangladesh had relatively high precipitation which could strengthen CH4 production from 445 rice paddy fields and other aquatic environments. This potential situation well-matched the high CH4 mole fraction in summer

CO 448
High annual CO mole fractions at both NTL and CLA (Table 1)  In addition, the seasonal amplitude of the CO mole fraction (Table 2)  The trend in the CO mole fraction and its inter-annual variability at NTL was similar to those in CH4 at NTL (Fig. 9[b] 483 and Fig. 10[b]). The mole fractions of CO and CH4 at NTL tended to be slightly higher when the air mass passed over the

H2 490
Mole fractions, growth rates, and seasonal variations of H2 at both sites are shown in Figure 11(a-d). It was found 491 that CLA, especially, showed a higher mole fraction than the other sites. Novelli et al. (1999) reported that the mainly sources 492 of H2 were combustion (fossil fuel combustion and biomass burning) and photochemical sources such as the oxidation of CH4 493 and non-CH4 hydrocarbons (NMHCs), which account for 90% of the total source. The other 10% is attributed to emissions 494 from volcanoes, oceans, and nitrogen fixation by legumes. Therefore, we have to assume that there are some emission sources 495 at CLA. 496 On the other hand, H2 is removed from the troposphere by reacting with OH and by deposition and oxidation at 497 surface soil. The amounts of sources and sinks for H2 in the global budget were estimated to be equal, resulting in a near-498 equilibrium state (Novelli et al., 1999). The strengths of H2 removal in the atmosphere over the Indian subcontinent do not 499 differ greatly by region according to Yashiro et al. (2011), whereas the strengths of H2 sources may differ by region (Price et 500 al., 2007). Lin et al. (2015) reported that H2 mole fractions at Indian sites were influenced by biomass burning and were 0-40 501 ppb higher than those at regional background sites (e.g., eastern Kazakhstan and central China). Figure 11 December at NTL, and the maximum in November-January and the minimum in June-August at CLA, which were different 504 from the averaged seasonal variation in the Northern Hemisphere, which showed the maximum in March-April and the 505 minimum in August-September (Novelli et al., 1999). 506 Because the burning of biomass (such as harvest residuals and dung) appeared to be actively carried out on the Indo-507 Gangetic Plain (including at NTL) during April-May and at CLA during November-February, H2 production must, therefore, 508 increase during these seasons. Furthermore, since higher CH4 mole fractions at NTL and CLA were observed during August-509 September and September-October due to strong paddy field emissions at those times, H2 production from CH4 degradation 510 can also increase. Figure 11(e) and (f) show short-term variable components (such as dCO and dH2, and dCH4, and dH2) at 511 both NTL and CLA during those periods, and that they had positive correlations. These figures may suggest some relationship 512 between H2 emission with biomass burning, and between photochemical reactions between OH and CH4, respectively. 513 Furthermore, the minimum H2 in June-August was influenced by a fresh air mass from the Indian Ocean which is only 514 minimally affected by anthropogenic emission. 515 As mentioned above, the H2 mole fraction level at CLA was higher than that at NTL. The amplitude of the seasonal 516 variation of the H2 mole fraction (Table 2)  in 2005, including around 49% from nitrogen fertilizer use. In particular, they reported that northern India (the Indo-Gangetic 524 Plain) has the highest N2O emission in India because nitrogen fertilizer was applied to extensive paddy fields, was denitrified, 525 and N2O was produced and emitted to the atmosphere. Ganesan et al. (2013) reported that the N2O mole fraction at Darjeeling 526 (north-eastern Indian site) was enhanced due to air mass transportation from the Indo-Gangetic Plain. The annual mean N2O 527 mole fraction at NTL (Table 1) appeared to be almost the same as at Darjeeling sites in North India and was higher than at 528 another two Indian sites (CRI [Bhattacharya et al., 2009] and HLE [Lin et al., 2015]) and at MLO (Fig. 12[a]). 529 annual mean mole fraction during 2013-2019 at CLA on the Eastern Indo-Gangetic Plain was 1-2 ppb higher than at NTL on 532 the Western Indo-Gangetic Plain (Table 1), and the seasonal amplitude of the N2O mole fraction (Table 2)  seemed to have relatively higher mole fractions than the sites in this study. As for the seasonal variation in the N2O mole 538 fraction at NTL, a higher mole fraction was seen in May-September (Fig. 12[c]). Generally, nitrogen fertilizer was frequently 539 applied to paddy fields in May-September in northern India. Delhi and reported that the flux increased immediately after the application of nitrogen fertilizer to the fields. Therefore, high 541 N2O levels and increases in the N2O mole fraction at NTL in May-September were influenced by the enhancement of the N2O 542 flux due to the denitrification of nitrogen fertilizer in paddy fields. 543 The N2O mole fraction at CLA increased in November-February (Fig. 12[d]) and such seasonal variation was almost 544 identical to the seasonal variation in CO at CLA. The seasonal component in the N2O mole fraction (ΔN2O = deviation of N2O 545 mole fraction from the long-term trend) at CLA showed positive correlations (R 2 = 0.81-0.88) with that of the CO mole fraction 546 (ΔCO) each year (Fig. 11[e]). Also, their ratio (ΔN2O/ΔCO) showed 0.013-0.015 ppb ppb -1 , which was same (0.015 ppb ppb -547 1 ) as the ratio of total N2O and total CO emissions in Bangladesh from the EDGAR v4. dung burning is one of major N2O sources among many kinds of biomass burning in India, its contribution was also possible. 557 On the other hand, nitrification and denitrification processes of nitrogen fertilizer in rice paddy soil are considered 558 to be major causes of N2O emissions in this region (EDGAR v4.3.2), however, the emission rate appeared to have seasonal 559 variation. Related to the irrigation system, the N2O flux was thought to be larger in alternating wet and dry conditions than After the summer monsoon (from October), the water level in the paddy field intermittently changed with the situation. 563 Therefore, relatively a higher N2O emission rate likely occurred during the winter season, when rice (Boro rice) was still grown, 564 enhancing the N2O mole fraction in the winter season. Further observations of high frequency variations of both N2O and CO 565 mole fractions will contribute towards precisely evaluating the N2O emission sources at this site. 566 The N2O growth rates at NTL and CLA were similar to that of MLO ( Fig. 12[b]), however, the variations in the N2O 567 growth rate at both NTL and CLA were larger than that of MLO during 2016-2020. The variation in the N2O growth rate 568 showed a similar pattern to the growth rates of CO and H2 ( Fig. 9[b] and Fig. 10[b]), indicating that the sources of these gases 569 had basically common characteristics. 570

SF6
fractions at NTL and CLA were almost the same as the background SF6 mole fraction (e.g., MLO in Fig. 13[a] and other sites 574 such as HLE, PON, and PBL [Lin et al., 2015]). In addition, the annual amplitudes of the SF6 mole fraction at Indian sites 575 (HLE, PON, and PBL) were 0.15, 0.24, and 0.48 ppt, respectively, which were almost within the same range (0.15-0.23 ppt) 576 as at NTL and CLA (Table 2). These results suggested that there was no large SF6 source on the Indo-Gangetic Plain. 577 Figure 13(c) and (d) show that the seasonal variations of the SF6 mole fraction at NTL and CLA decreased in summer 578 (NTL: July, CLA: June-August), which was the same variation as those detected at PON and PBL (Lin et al., 2015). In the 579 summer season, air masses from the south via the Indian Ocean prevailed in the NTL and CLA regions, as shown in Figure 2. 580 Generally, the SF6 mole fraction in the Southern Hemisphere was lower than that in the Northern Hemisphere (Geller et al., 581 1997). Thus, the seasonal variation in the SF6 mole fraction was explained by the frequency of air mass transportation from 582 the south. 583 Figure 13(b) shows the interannual variability of the SF6 growth rate at NTL, CLA, and MLO and southern air mass 584 contribution at NTL and CLA. The variability in the SF6 growth rate at NTL was different to the variability at MLO, and in 585 fact we could see an anticorrelation between them. In the case of CLA, an anticorrelation was not so clear because of a relatively 586 shorter data record. The decrease in the growth rate at NTL seemed to have a relationship with the increase in the frequency 587 of southern air mass transportation. This indicated that the growth rate of the SF6 mole fraction at NTL may be controlled by 588 the regional climatic condition though the transportation process. Because SF6 had weaker sources in Northern India, the 589 variation in its trend could be explained more clearly by the influence of the air mass movements. 590 As mentioned above, anticorrelation in the growth rates between MLO and this region was also seen in CO2 and CH4. 591 Therefore, we must take into consideration the influence of the variation in large-scale atmospheric circulation to the GHG 592 mole fraction and trends in their growth rates in the Indian region. to the change between wet and dry climatic conditions. Therefore, seasonal variations in the atmospheric CO2 mole fraction 602 were strongly influenced by the crop CO2 sink at that time. In general, low CO2 mole fractions in the winter season in the 603 Northern Hemisphere were not observed, however, we observed relatively lower mole fractions during January-March in this 604 region, especially at CLA. In Bangladesh, rice is grown even in the winter season. The δ 13 C-CO2 signature showed C3 plants 605 (e.g., rice and wheat) affected the CO2 mole fractions in the winter season, while in the summer season the δ 13 C-CO2 signature 606 showed C4 plants (corn, sugar cane etc.) contributed some portion. 607 The seasonal variations in δ 18 O-CO2 showed almost the same variation as that in the δ 18 O in local rain. Effects of the 608 amount of precipitation and the origin of moisture, appeared to affect δ 18 O in local rain and CO2. As a result, δ 18 O in CO2 was 609 affected by the climatic variation related to the amount of precipitation, which was enhanced during 2015-2017. These facts 610 are also consistent with the explanation that CO2 exchange by photosynthesis (and respiration) by land biomass strongly 611 affected CO2 seasonality in mole fraction. major emission sources in this region. Because CH4 production activities increased after rice planting, we observed the highest 615 peak in September-October at both sites and a small peak in spring at CLA. A large amount of precipitation during those 616 seasons is likely to have affected the CH4 production rate of rice paddy fields through soil anaerobic conditions and, as a result, 617 increased the atmospheric CH4 mole fraction. Air mass transport also influenced seasonal variation and the variability of its 618 growth rate. Beside emissions from rice paddy fields, we identified the relationship between biomass burning and the CH4 619 mole fraction in a season other than September-October, when biomass burning occurred frequently. In addition, enteric 620 fermentation and wastewater handling were large emission sources in this region. The large number of sources appeared to 621 increase the average CH4 mole fraction in this region. 622 CO was strongly related to biomass burning activities at both sites. The mole fraction was high in the dry season and 623 after crop harvesting. At CLA in winter, a higher mole fraction was observed together with a high N2O mole fraction, which 624 may suggest some link to biomass burning as a N2O source. The CO level gradually decreased throughout the observed period. 625 CO emissions must, therefore, be reduced by various technical progresses including automobile emission and industrial 626 combustion efficiency improvements. 627 We observed higher N2O levels in the crop season (i.e., the rainy season) from May-September at NTL, but much 628 higher levels in the winter season at CLA. N2O is known to be mainly emitted from soil though nitrogen fertilizer applications 629 to rice fields and crop lands in this region. However, for CLA, we estimated seasonal variations in the emission rate due to the 630 water level in the rice paddy field, because intermittent irrigation in winter generally produces more N2O than continuously 631 flooded conditions in the rainy season. 632 H2 showed some relationship to both CO and CH4 mole fractions. We found that CO had a good correlation with H2 in 633 the biomass burning season, indicating some H2 contribution from biomass burning. On the other hand, in the season when the 634 CH4 mole fraction was high, the H2 mole fraction was also relatively high compared to CH4, suggesting that chemical reactions 635 of CH4 and H2 may contribute some portion of the H2 mole fraction. 636 SF6 showed consistent mole fractions with other Indian sites. Seasonal variations were strongly related to the southern 637 air mass frequency, because the SF6 mole fraction in the southern region was relatively low. 638 We found that the interannual variabilities in CH4, SF6 and also partly in CO2, growth rates at NTL were anticorrelated 639 with those at MLO, which is located in the Pacific. Growth rates for many GHGs are known to be influenced by El Nino events 640 for many reasons (e.g., hot climate, dry conditions on a global scale). However, in the Indian region, growth rates of some 641 GHGs seemed to be more affected by the regional climate condition, which usually affects air circulation and precipitation in 642 the Indian region. In the case of CLA, although the data duration was insufficiently short, growth rates of CO2, CH4, and SF6 643 changed differently from those at MLO, which could be partly explained by the climatic variations. Because CLA is located 644 relatively close to the ocean, sometimes the variation was thought to be different from that at NTL. 645 These findings have not been reported previously. In this study, long-term records of GHGs data at NTL enabled a 646 long-term analysis. These findings suggested that the mole fractions of GHGs and their emissions on the Indian subcontinent 647 could change with climatic conditions in this region in the near future, in addition to changes in anthropogenic activities 648 relating to GHG emissions and countermeasure for the emissions. Therefore, long-term GHG monitoring should be continued 649 and the effectiveness of countermeasures for reducing GHG emissions on the Indian subcontinent, including the Indo-Gangetic 650 Plain, should be evaluated. 651 Tables  851   852   Table 1