论文题目:

Carbon dioxide and methane supersaturation in lakes of semi-humid/semi-arid region, Northeastern China

英文论文题目:

Carbon dioxide and methane supersaturation in lakes of semi-humid/semi-arid region, Northeastern China

第一作者:

温志丹

英文第一作者:

Wen, Z. D.

联系作者:

宋开山

英文联系作者:

Song, K. S.

发表年度:

2016

卷:

138

期:

页码:

65-73

摘要:

Understanding concentrations of carbon dioxide (CO2) and methane (CH4) in lakes is an important part of a comprehensive global carbon budget. We estimated data on the partial pressure of CO2 (pCO(2)) and CH4 (pCH(4)) from sampling with 95 lakes in semi-humid/semi-arid region of Northeastern China during ice free period. Both pCO(2) and pCH(4) varied greatly among the study sites. p(CO2) values in these lakes ranged from 21.9 to 30,152.3 mu atm (n = 403), and 91% of lakes in this survey were supersaturated with CO2. p(CH4) values ranged from 12.6 to 139,630.7 atm with all sites in this study of CH4 sources to the atmosphere during the ice-free period. The collected urban lakes samples exhibited higher pCO(2) and pCH(4) than wild lakes samples. Either the mean value of p(CO2) or p(CH4) in saline waters is higher than in fresh waters. Correlation analysis implied that the partial pressure of the GHGs (CO2 and CH4) showed statistically correlations with water environment indicators like pH, dissolved organic carbon (DOC), total nitrogen (TN), total phosphorus (TP), and chlorophyll a (Chla). However, the most of the relationships showed a high degree of scatter, only pH might be used as the predictor of the gas partial pressure based on the result of this study (r(pCO2) = -0.437, p < 0.01, n = 382; r(pCH4) = -0265, p < 0.01, n = 400). Furthermore, salinity could be a good predictor for p(CO2) and p(CH4) in 83 freshwater lakes in our study (r(pCO2) = 0.365, r(pCH4) = 0.323, p < 0.01, n = 348). The mean CO2 flux increased with the decreasing lake area size. The calculated annual areal carbon emission rate is 560.2 g C m(-2) from 95 lakes in Northeastern China. We could not extrapolate carbon emission from these lakes to the boreal region or a wider scale because of the change of environmental conditions.

英文摘要:

Understanding concentrations of carbon dioxide (CO2) and methane (CH4) in lakes is an important part of a comprehensive global carbon budget. We estimated data on the partial pressure of CO2 (pCO(2)) and CH4 (pCH(4)) from sampling with 95 lakes in semi-humid/semi-arid region of Northeastern China during ice free period. Both pCO(2) and pCH(4) varied greatly among the study sites. p(CO2) values in these lakes ranged from 21.9 to 30,152.3 mu atm (n = 403), and 91% of lakes in this survey were supersaturated with CO2. p(CH4) values ranged from 12.6 to 139,630.7 atm with all sites in this study of CH4 sources to the atmosphere during the ice-free period. The collected urban lakes samples exhibited higher pCO(2) and pCH(4) than wild lakes samples. Either the mean value of p(CO2) or p(CH4) in saline waters is higher than in fresh waters. Correlation analysis implied that the partial pressure of the GHGs (CO2 and CH4) showed statistically correlations with water environment indicators like pH, dissolved organic carbon (DOC), total nitrogen (TN), total phosphorus (TP), and chlorophyll a (Chla). However, the most of the relationships showed a high degree of scatter, only pH might be used as the predictor of the gas partial pressure based on the result of this study (r(pCO2) = -0.437, p < 0.01, n = 382; r(pCH4) = -0265, p < 0.01, n = 400). Furthermore, salinity could be a good predictor for p(CO2) and p(CH4) in 83 freshwater lakes in our study (r(pCO2) = 0.365, r(pCH4) = 0.323, p < 0.01, n = 348). The mean CO2 flux increased with the decreasing lake area size. The calculated annual areal carbon emission rate is 560.2 g C m(-2) from 95 lakes in Northeastern China. We could not extrapolate carbon emission from these lakes to the boreal region or a wider scale because of the change of environmental conditions.

刊物名称:

Atmospheric Environment

英文刊物名称:

Atmospheric Environment

英文参与作者:

Song, K. S., Zhao, Y., Jin, X. L.