Spatiotemporal variation in pCO₂, CH₄, N₂O, DOM, and ancillary water quality measured in the Ganges, Mekong, and Yellow River during 2016 to 2019
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| Formato: | Dataset Open Access |
| Lenguaje: | en |
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PANGAEA
2021
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| author | Begum, Most Shirina Bogard, Matthew J Butman, David Chea, Eliyan Kumar, Sanjeev Lu, Xixi Nayna, Omme K Ran, Lishan Richey, J E Tareq, Shafi M Xuan, Do Thi Yu, Ruihong Park, Ji-Hyung |
| author_facet | Begum, Most Shirina Bogard, Matthew J Butman, David Chea, Eliyan Kumar, Sanjeev Lu, Xixi Nayna, Omme K Ran, Lishan Richey, J E Tareq, Shafi M Xuan, Do Thi Yu, Ruihong Park, Ji-Hyung |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | Despite growing research on greenhouse gas (GHG) emissions from inland waters, few systematic efforts have been made to assess the regional-scale GHG emissions from Asian rivers under increasing anthropogenic stress. We examined factors controlling longitudinal and seasonal variations in the partial pressure of CO₂ (pCO₂), and CH₄ and N₂O concentrations in the Ganges, Mekong, and Yellow River (Huang He) by simultaneously measuring gas concentrations and stable C isotopes, and optical properties of dissolved organic matter (DOM) from 2016 to 2019. The levels of pCO₂ and CH₄ were distinctively higher in polluted tributaries and affected reaches of the Ganges and Mekong than in the Yellow River. The highest levels of N₂O were found in the Ganges, followed by Yellow River and Mekong. Across these basins, dry-season mean concentrations of CO₂, CH₄, and N₂O were 1.6, 2, and 7 times higher than those measured in the monsoon season, respectively. This seasonality was consistent with that of δ¹³C-CO₂, while δ¹³C-CH₄ showed an opposite pattern. The overall results suggest that neglecting localized pollution impacts on GHG emissions from increasingly urbanized river basins can result in inaccurate estimates of global riverine GHG emissions. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_926582 |
| institution | PANGAEA |
| language | en |
| publishDate | 2021 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Spatiotemporal variation in pCO₂, CH₄, N₂O, DOM, and ancillary water quality measured in the Ganges, Mekong, and Yellow River during 2016 to 2019 Begum, Most Shirina Bogard, Matthew J Butman, David Chea, Eliyan Kumar, Sanjeev Lu, Xixi Nayna, Omme K Ran, Lishan Richey, J E Tareq, Shafi M Xuan, Do Thi Yu, Ruihong Park, Ji-Hyung Air-water gas flux, river, Lauerwald et al. (2015); Biological index; Calculated according to Huguet et al. (2009); Calculated according to McKnight et al. (2001); Calculated according to Zsolnay et al. (1999); Carbon, organic, dissolved; Carbon, organic, particulate; Carbon dioxide, flux, in mass carbon; Carbon dioxide (water), partial pressure; Conductivity, electrolytic; Date/Time of event; Distance; Event label; Fluorescence, dissolved organic matter; Fluorescence index; Ganges_G1; Ganges_G10; Ganges_G11; Ganges_G11_1; Ganges_G11_2; Ganges_G12; Ganges_G13; Ganges_G13_1; Ganges_G14; Ganges_G14_1; Ganges_G2; Ganges_G2_1; Ganges_G3; Ganges_G3_1; Ganges_G4; Ganges_G5; Ganges_G6; Ganges_G7; Ganges_G7_1; Ganges_G8; Ganges_G9; Ganges_H1; Ganges_H1_1; Ganges_H2; Ganges_H3; Ganges_J1; Ganges_J2; Ganges_J3; Ganges_J3_1; Ganges_J3_2; Ganges_J4; Ganges_T1; Ganges_T1_1; Ganges_T2; Ganges_T2_1; Ganges_T3; Ganges_T3_1; Ganges_T4; Ganges_T4_1; Ganges_T4_2; Ganges_T5; Ganges_T6; Ganges_W1; Ganges_W2; Ganges_W3; Ganges_W4; Ganges_W4_1; Ganges_W5; Ganges_W6; Ganges_W6_1; Ganges_W7; Ganges_W7_1; Ganges_W8; Greenhouse gases; HAND; Humification index; Ion chromatography; Latitude of event; Longitude of event; Mekong_M1; Mekong_M10; Mekong_M10_1; Mekong_M11; Mekong_M11_1; Mekong_M2; Mekong_M2_1; Mekong_M3; Mekong_M3_1; Mekong_M4; Mekong_M5; Mekong_M5_1; Mekong_M6; Mekong_M6_1; Mekong_M7; Mekong_M7_1; Mekong_M8; Mekong_M8_1; Mekong_M9; Mekong_M9_1; Mekong_T1; Mekong_T2; Mekong_T2_1; Mekong_T3; Mekong_T3_1; Mekong_T4; Mekong_T4_1; Mekong_T5; Mekong_T5_1; Mekong_T6; Mekong_T6_1; Mekong_T7; Mekong_T7_1; Mekong_W1; Mekong_W1_1; Mekong_W2; Mekong_W2_1; Mekong_W3; Mekong_W4; Mekong_W5; Mekong_W5_1; Mekong_W6; Mekong_W6_1; Mekong_W7; Mekong_W7_1; Methane; Methane, flux, in mass carbon; Nitrogen, inorganic, dissolved; Nitrogen, organic, particulate; Nitrogen in ammonium; Nitrogen in nitrate; Nitrous oxide, dissolved; Nitrous oxide, flux, in mass nitrogen; organic matter; Oxygen, dissolved; Parallel factor analysis (PARAFAC); pH; Phosphorus in orthophosphate; River; Sample comment; Sample ID; Sampling by hand; Season; Specific ultraviolet absorbance normalized to DOC, 254 nm, per mass carbon; Specific UV absorbance 254nm, DOC normalised, Weishaar et al. (2003); Suspended matter, total; Temperature, water; water pollution; Yellow_T1; Yellow_T1_1; Yellow_T2; Yellow_T2_1; Yellow_Y1; Yellow_Y2; Yellow_Y3; Yellow_Y4; Yellow_Y4_1; Yellow_Y5; Yellow_Y6; Yellow_Y7; Yellow_Y8; δ13C; δ13C, carbon dioxide, dissolved; δ13C, methane, dissolved Despite growing research on greenhouse gas (GHG) emissions from inland waters, few systematic efforts have been made to assess the regional-scale GHG emissions from Asian rivers under increasing anthropogenic stress. We examined factors controlling longitudinal and seasonal variations in the partial pressure of CO₂ (pCO₂), and CH₄ and N₂O concentrations in the Ganges, Mekong, and Yellow River (Huang He) by simultaneously measuring gas concentrations and stable C isotopes, and optical properties of dissolved organic matter (DOM) from 2016 to 2019. The levels of pCO₂ and CH₄ were distinctively higher in polluted tributaries and affected reaches of the Ganges and Mekong than in the Yellow River. The highest levels of N₂O were found in the Ganges, followed by Yellow River and Mekong. Across these basins, dry-season mean concentrations of CO₂, CH₄, and N₂O were 1.6, 2, and 7 times higher than those measured in the monsoon season, respectively. This seasonality was consistent with that of δ¹³C-CO₂, while δ¹³C-CH₄ showed an opposite pattern. The overall results suggest that neglecting localized pollution impacts on GHG emissions from increasingly urbanized river basins can result in inaccurate estimates of global riverine GHG emissions. |
| title | Spatiotemporal variation in pCO₂, CH₄, N₂O, DOM, and ancillary water quality measured in the Ganges, Mekong, and Yellow River during 2016 to 2019 |
| topic | Air-water gas flux, river, Lauerwald et al. (2015); Biological index; Calculated according to Huguet et al. (2009); Calculated according to McKnight et al. (2001); Calculated according to Zsolnay et al. (1999); Carbon, organic, dissolved; Carbon, organic, particulate; Carbon dioxide, flux, in mass carbon; Carbon dioxide (water), partial pressure; Conductivity, electrolytic; Date/Time of event; Distance; Event label; Fluorescence, dissolved organic matter; Fluorescence index; Ganges_G1; Ganges_G10; Ganges_G11; Ganges_G11_1; Ganges_G11_2; Ganges_G12; Ganges_G13; Ganges_G13_1; Ganges_G14; Ganges_G14_1; Ganges_G2; Ganges_G2_1; Ganges_G3; Ganges_G3_1; Ganges_G4; Ganges_G5; Ganges_G6; Ganges_G7; Ganges_G7_1; Ganges_G8; Ganges_G9; Ganges_H1; Ganges_H1_1; Ganges_H2; Ganges_H3; Ganges_J1; Ganges_J2; Ganges_J3; Ganges_J3_1; Ganges_J3_2; Ganges_J4; Ganges_T1; Ganges_T1_1; Ganges_T2; Ganges_T2_1; Ganges_T3; Ganges_T3_1; Ganges_T4; Ganges_T4_1; Ganges_T4_2; Ganges_T5; Ganges_T6; Ganges_W1; Ganges_W2; Ganges_W3; Ganges_W4; Ganges_W4_1; Ganges_W5; Ganges_W6; Ganges_W6_1; Ganges_W7; Ganges_W7_1; Ganges_W8; Greenhouse gases; HAND; Humification index; Ion chromatography; Latitude of event; Longitude of event; Mekong_M1; Mekong_M10; Mekong_M10_1; Mekong_M11; Mekong_M11_1; Mekong_M2; Mekong_M2_1; Mekong_M3; Mekong_M3_1; Mekong_M4; Mekong_M5; Mekong_M5_1; Mekong_M6; Mekong_M6_1; Mekong_M7; Mekong_M7_1; Mekong_M8; Mekong_M8_1; Mekong_M9; Mekong_M9_1; Mekong_T1; Mekong_T2; Mekong_T2_1; Mekong_T3; Mekong_T3_1; Mekong_T4; Mekong_T4_1; Mekong_T5; Mekong_T5_1; Mekong_T6; Mekong_T6_1; Mekong_T7; Mekong_T7_1; Mekong_W1; Mekong_W1_1; Mekong_W2; Mekong_W2_1; Mekong_W3; Mekong_W4; Mekong_W5; Mekong_W5_1; Mekong_W6; Mekong_W6_1; Mekong_W7; Mekong_W7_1; Methane; Methane, flux, in mass carbon; Nitrogen, inorganic, dissolved; Nitrogen, organic, particulate; Nitrogen in ammonium; Nitrogen in nitrate; Nitrous oxide, dissolved; Nitrous oxide, flux, in mass nitrogen; organic matter; Oxygen, dissolved; Parallel factor analysis (PARAFAC); pH; Phosphorus in orthophosphate; River; Sample comment; Sample ID; Sampling by hand; Season; Specific ultraviolet absorbance normalized to DOC, 254 nm, per mass carbon; Specific UV absorbance 254nm, DOC normalised, Weishaar et al. (2003); Suspended matter, total; Temperature, water; water pollution; Yellow_T1; Yellow_T1_1; Yellow_T2; Yellow_T2_1; Yellow_Y1; Yellow_Y2; Yellow_Y3; Yellow_Y4; Yellow_Y4_1; Yellow_Y5; Yellow_Y6; Yellow_Y7; Yellow_Y8; δ13C; δ13C, carbon dioxide, dissolved; δ13C, methane, dissolved |
| url | https://doi.org/10.1594/PANGAEA.926582 |