Biochar application to reduce CO2 emissions from farmland and increase crop yields: a 22-year study based on big data analysis and ideal scenario modeling

被引:1
|
作者
Chen, Can [1 ,2 ]
Wang, Kexin [1 ]
Cai, Peng [2 ]
Dai, Zaiqiang [2 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Coll Appl Meteorol, Nanjing 210044, Peoples R China
[2] Wuxi Univ, Coll Atmosphere & Remote Sensing, Wuxi 214105, Peoples R China
基金
中国国家自然科学基金;
关键词
Biochar; CO2; emissions; Big data analysis; The ideal scenario; Farmland in northern China; CARBON-DIOXIDE; SOIL; TEMPERATURE; SANDY; N2O; RESPONSES; QUALITY; FLUXES; GROWTH;
D O I
10.1007/s11356-023-28256-8
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
How to reduce the emission of greenhouse gas CO2 from farmland and to improve crop yield is one of the most concerned agricultural ecological environment issues for scientists at present. As an excellent soil conditioner, biochar has a very broad research value and application path in the field. Taking farmland in northern China as the research object, this paper studied the impact of biochar application on soil CO2 emission potential and crop yield in farmland in northern China through big data analysis and modeling methods. The results show that the ideal scenario for increasing crop production and reducing CO2 emissions should be that the raw materials for the preparation of biochar are wheat straw and rice straw; the preparation temperature is 400-500 celcius, the C/N ratio of biochar is 80-90, the pH of biochar is 8-9, the soil texture is sandy soil or loam soil, soil bulk density is 1.2-1.4 g cm(-3), the soil pH is less than 6, the soil organic matter content is 10-20 g kg(-1), and the soil C/N is less than 10; the application amount of biochar is 20-40 t ha(-1); and the use time of biochar is 1 year. In view of this, this study selected the data of microbial biomass (X-1), soil respiration rate (X-2), soil organic matter (X-3), soil moisture content (X-4), average soil temperature (X-5), and CO2 emissions (Y) for correlation analysis and path analysis, and finally obtained the multiple stepwise regression equation between CO2 emissions and various impact factors as follows: Y = - 27.981 + 0.6249 X-1 + 0.5143 X-2 + 0.4257X(3) + 0.3165X(4) + 0.2014X(5) (R-2 = 0.867, P < 0.01, n = 137). Microbial biomass and soil respiration rate directly affect CO2 emissions, reaching a highly significant level (P < 0.01); the second is soil organic matter, soil moisture content, and average soil temperature. The indirect relationship between CO2 emissions and soil average temperature, microbial biomass, and soil respiration rate is the strongest, followed by soil organic matter and soil moisture content.
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页码:83319 / 83329
页数:11
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