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
How to reduce the emission of greenhouse gas CO 2 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. Ta...
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| Vydáno v: | Environmental science and pollution research international Ročník 30; číslo 35; s. 83319 - 83329 |
|---|---|
| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.07.2023
Springer Nature B.V |
| Témata: | |
| ISSN: | 1614-7499, 0944-1344, 1614-7499 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | How to reduce the emission of greenhouse gas CO
2
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 CO
2
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 CO
2
emissions should be that the raw materials for the preparation of biochar are wheat straw and rice straw; the preparation temperature is 400–500 ℃, 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 CO
2
emissions (
Y
) for correlation analysis and path analysis, and finally obtained the multiple stepwise regression equation between CO
2
emissions and various impact factors as follows:
Y
= − 27.981 + 0.6249
X
1
+ 0.5143
X
2
+ 0.4257
X
3
+ 0.3165
X
4
+ 0.2014
X
5
(
R
2
= 0.867,
P
< 0.01,
n
= 137). Microbial biomass and soil respiration rate directly affect CO
2
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 CO
2
emissions and soil average temperature, microbial biomass, and soil respiration rate is the strongest, followed by soil organic matter and soil moisture content. |
|---|---|
| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 1614-7499 0944-1344 1614-7499 |
| DOI: | 10.1007/s11356-023-28256-8 |