摘要
在陇中黄土高原干旱半干旱区,采用小区定位试验,对不同生物质炭水平(0 t·hm^(-2)、10 t·hm^(-2)、20 t·hm^(-2)、30 t·hm^(-2)、40 t·hm^(-2)、50 t·hm^(-2))下农田土壤温室气体(CO_2、N_2O和CH_4)的日排放通量及其影响因子进行连续观测,并确定1 d中不同生物质炭处理水平下的最佳观测时间。结果表明:6个生物质炭输入水平处理下,春小麦地土壤CH_4、N_2O和CO_2通量变化趋势与气温日变化轨迹大体一致,均表现为白天排放量大于夜间,并在4:00—5:00时,出现对CH_4通量的吸收峰,以及N_2O与CO_2的排放低谷;全天内各处理CH_4平均排放通量依次为:10.14mg·m^(-2)·h^(-1)、7.82mg·m^(-2)·h^(-1)、6.57mg·m^(-2)·h^(-1)、-0.10mg·m^(-2)·h^(-1)、1.05mg·m^(-2)·h^(-1)和2.89mg·m^(-2)·h^(-1),N_2O平均排放通量依次为:288.79mg·m^(-2)·h^(-1)、201.78mg·m^(-2)·h^(-1)、157.14mg·m^(-2)·h^(-1)、112.06mg·m^(-2)·h^(-1)、154.60mg·m^(-2)·h^(-1)和164.02mg·m^(-2)·h^(-1),CO_2平均排放通量依次为:85.44 mg·m^(-2)·h^(-1)、80.91 mg·m^(-2)·h^(-1)、76.49 mg·m^(-2)·h^(-1)、65.29 mg·m^(-2)·h^(-1)、67.19 mg·m^(-2)·h^(-1)和69.10 mg·m^(-2)·h^(-1);当生物质炭输入量小于30 t·hm^(-2)时,土壤CH_4、N_2O、CO_2排放通量随其输入量增加而显著减小,但当其输入量超过30 t·hm^(-2)时,3种温室气体排放通量则呈显著增大趋势;当生物质炭输入水平为30 t·hm^(-2)时,春小麦土壤全天表现为CH_4的吸收汇,其余各水平处理下的土壤表现为CH_4的弱排放源;6种处理水平下,全天春小麦地土壤表现为N_2O、CO_2的排放源。0~5 cm的土壤温度及水分(y)与生物质炭输入量(x)回归方程分别为y=-0.017 6x+16.585(R^2=0.302 6,r=-0.55,P<0.05)和y=0.056 5x+13.626(R^2=0.815 1,r=0.903,P<0.05),生物质炭输入量与0~5 cm的土壤水分呈显著正相关关系;无生物质炭输入处理下3种温室气体的吸收或排放通量与地表温度及5 cm地温均呈显著正相关关系,其他各处理也表现出不同程度的正相关关系。因此,当生物质炭输入水平为30 t·hm^(-2)时,更有利于CH_4、N_2O和CO_2 3种温室气体的增汇减排;生物质炭输入水平差异引起的土壤温度及水分差异可能是不同生物质炭处理CH_4、N_2O和CO_2日排放通量产生差异的主要原因;由矫正系数及最佳时段温室气体排放量与累积排放量回归分析可得,3种温室气体的最佳同期观测时间为8:00—9:00。
Biochar is a carbon-rich solid product obtained from heating biomass under oxygen-limited conditions. Biochar application has the potential to mitigate greenhouse gas emission. Dryland farming areas in Northwest China emit substantial amounts of greenhouse gases. The aim of this study was to determine the effects of different biochar rates on diurnal variations in methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2) emissions in the western Loess Plateau. Treatments included 6 biochar application rates (3 replications): 0 t·hm^-2 (control, B0), 10 t·hm^-2 (B1), 20 t·hm^-2 (B2), 30 t·hm^-2 (B3), 40 t·hm^-2 (B4) and 50 t·hm^-2 (B5) t·hm^-2. Soil moisture and temperature were measured concurrently with gas measurement. The results showed distinct diurnal variations in CO2, CH4 and N2O fluxes for different biochar application rates. The trends of change in the fluxes of the 3 gases (CH4, N2O and CO2) were consistent with daily variations in temperature. Daytime fluxes were greater than nighttime fluxes. The order of absorption peak of CH4 was B0 (10.14 mg·m^-2·h^-1) 〉 B1 (7.82 mg·m^-2·h^-1) 〉 B2 (6.57 mg·m^-2·h^-1) 〉 B5 (2.89 mg·m^-2·h^-1) 〉 B4 (1.05 mg·m^-2·h^-1) 〉 B3 (-0.10 mg·m^-2·h^-1). A similar order was noted for average emission flux of N2O, given as B0 (288.79 mg·m^-2·h^-1) 〉 B1 (201.78 mg·m^-2·h^-1) 〉 B5 (164.02 mg·m^-2·h^-1) 〉 B2 (157.14 mg·m^-2·h^-1) 〉 B4 (154.60 mg·m^-2·h^-1) 〉 B3 (112.06 mg·m^-2·h^-1). The order of average emission flux of CO2 was B0 (85.44 mg·m^-2·h^-1) 〉 B1 (80.91 mg·m^-2·h^-1) 〉 B2 (76.49 mg·m^-2·h^-1) 〉 B5 (69.10 mg·m^-2·h^-1) 〉 B4 (67.19 mg·m^-2·h^-1) 〉 B3 (65.29 mg·m^-2·h^-1). The results showed that when biochar input was less than 30 t·hm^-2, mean emission fluxes of CH4, N2O and CO2 dropped with increasing biochar application rate. However, when biochar input exceed 30 t·hm^-2, the mean emission fluxes of CH4, N2O and CO2 increased with increasing biochar application rate. The soil was a good source of atmospheric CH4 for all treatments (except for 30 t·hm^-2) and sources of atmospheric N2O and CO2, irrespective of treatment. Soil temperature at 5 cm depth was correlated with biochar application rate — y = -0.017 6x + 16.585 (R2 = 0.302 6, r = -0.55, P 〈0.05), but soil moisture at 5 cm soil depth was linearly correlated with biochar application rate — y = 0.056 5x + 13.626 (R2=0.815 1, r = 0.903, P 〈 0.05). The average fluxes of CH4, N2O and CO2 under the control treatment were positively correlated with soil temperature of both soil surface and the 0-5 cm depth. The others treatments were also positively correlated with different levels of biochar. Biochar application at 30 t·hm^-2 reduced greenhouse gas emission. The differences in both soil temperature and moisture caused by different input levels of biochar were the main reasons for the differences in CH4, N2O and CO2 emissions. Correction coefficient and regression analysis of optimal measure time revealed that the optimal observation period of the three greenhouse gases was between 8 a.m. and 9 a.m.
作者
宋敏
蔡立群
齐鹏
Stephen Yeboah
张仁陟
罗珠珠
潘占东
卢廷超
SONG Min CAI Liqun QI Peng Stephen Yeboah ZHANG Renzhi LUO Zhuzhu PAN Zhandong LU Tingchao(College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China Gansu Provincial Key Lab of Aridland Crop Science, Lanzhou 730070, China Gansu Province Research Center for Water-saving Agriculture Engineering Technology, Lanzhou 730070, China Department of Textile Engineering, Anhui Vocational and Technical College, Hefei 230514, China CSIR-Crops Research Institute, P.O. BOX 3780-Kumasi, Ghana)
出处
《中国生态农业学报》
CAS
CSCD
北大核心
2016年第10期1300-1309,共10页
Chinese Journal of Eco-Agriculture
基金
甘肃省干旱生境作物学重点实验室开放基金课题(GSCS-2012-13)
国家自然科学基金项目(31160269,31571594)
“十二·五”《循环农业科技工程》项目(2012BAD14B03)
甘肃省自然科学基金项目(145RJZA204,145RJZA106)资助~~
关键词
旱作农田
春小麦
生物质炭
温室气体
排放通量
日变化
土壤温度
土壤水分
Dry farmland
Spring wheat
Biochar
Greenhouse gases
Emission flux
Diurnal variation
Soil temperature
Soil moisture