Changes in crop mix and the effects on agricultural carbon emissions in China

Figures & data

Figure 1. Geographical divisions and main grain-producing provinces of China. Note: it is produced by authors in ArcGIS 10.4.

Table 1. Description of the data used.

Data	Measurement unit	Used unit	Description	Source
Areas of crops	10^3ha	ha	The area of all croplands sown or transplanted with crops that are harvested within the calendar year	China Statistical Yearbook
Pesticide	10^4t	kg	The actual amount of pesticide used for agricultural production during the year	China Rural Statistical Yearbook and Provincial Statistical Yearbooks
Fertilizer (N, P, K, Compound)	10^4t	kg	The actual amount of chemical fertilizer used for agricultural production during the year
Diesel	10^4t	kg	The actual amount of diesel used for agricultural production during the year
Irrigation area	10^3ha	ha	The amount of cultivated land that can be irrigated normally in a normal year
Plastic film	10^4t	kg	The actual amount of plastic film used for agricultural production during the year

Figure 2. Flowchart of analyzing crop-mix type changes. Note: it is produced by authors in Visio 2019.

Table 2. Carbon emission factors of different sources.

Emission sources		Emission coefficients	Unit	Reference
CH4	Paddy field	249.5	Kg/ha	Yan et al. (2003)
N2O	Paddy field	0.24	Kg/ha	Min and Hu (2012)
	Maize field	2.532	Kg/ha
	Wheat field	1.75	Kg/ha
	Beans field	2.29	Kg/ha
	Vegetable field	4.9444	Kg/ha
	Other crops field	0.95	Kg/ha
CO2	Pesticide	18	Kg/kg	Huang et al. (2013)
	N fertilizer	10.18	Kg/kg
	P fertilizer	1.5	Kg/kg
	K fertilizer	0.98	Kg/kg
	Compound fertilizer	3.443	Kg/kg	Ye et al. (2021)
	Diesel	3.93	Kg/kg	Huang et al. (2013)
	Electricity for irrigation	72.811	Kg/ha	Wu et al. (2021)
	Plastic film	19	Kg/kg

Figure 3. Provincial crop-mix types in China. (a) and (b) are the distribution of crop-mix types in 2005 and 2020, respectively. (c) depicts the changes in the numbers of crop-mix types. (d) to (f) show the numbers of crops at the first, second, and third positions, respectively. Note: it is produced by authors in ArcGIS 10.4.

Figure 4. Changes in crop-mix types in China from 2005 to 2020. Note: it is produced by authors in ArcGIS 10.4.

Figure 5. Trends of proportions of various crops from 2005 to 2020. Note: it is produced by authors in ArcGIS 10.4.

Table 3. Carbon emission intensity of cropping systems in China (t/ha).

Provinces	2005	2010	2015	2020	Mean	Trend (S)
Beijing	5.728	5.217	6.893	7.005	6.339	0.178
Tianjin	5.836	6.458	5.706	4.010	5.697	−0.144
Hebei	5.393	4.811	4.848	3.733	4.765	−0.087
Shanxi	2.583	2.814	2.875	2.632	2.794	0.007
Inner Mongolia	2.242	2.750	3.136	2.536	2.676	0.024
Liaoning	4.929	5.451	5.225	4.407	5.138	−0.051
Jilin	3.763	4.228	4.468	3.956	4.188	0.011
Heilongjiang	2.951	3.521	3.941	3.453	3.505	0.035
Shanghai	7.678	7.075	7.162	8.162	7.466	0.027
Jiangsu	6.110	6.279	6.098	5.847	6.136	−0.022
Zhejiang	8.432	9.324	9.853	9.346	9.604	0.100
Anhui	4.240	4.631	4.803	4.674	4.700	0.036
Fujian	7.504	8.152	7.931	9.152	8.782	0.179
Jiangxi	5.850	5.997	5.955	5.561	5.906	−0.014
Shandong	4.803	4.643	4.356	3.682	4.430	−0.079
Henan	3.526	4.031	4.175	3.662	3.919	0.010
Hubei	5.304	5.362	5.362	4.786	5.318	−0.030
Hunan	5.514	5.754	5.558	5.392	5.723	−0.011
Guangdong	6.721	7.425	7.245	7.062	7.348	0.043
Guangxi	4.714	5.241	5.241	4.931	5.146	0.009
Hainan	6.784	8.108	8.316	7.999	8.046	0.105
Chongqing	3.828	4.109	4.084	4.032	4.086	0.017
Sichuan	3.825	4.016	3.975	3.473	3.900	−0.017
Guizhou	2.708	2.811	2.794	2.496	2.764	−0.015
Yunnan	3.806	4.148	4.464	3.686	4.129	0.010
Tibet	1.714	2.100	2.627	1.877	2.136	0.030
Shaanxi	3.721	4.397	5.000	4.666	4.621	0.089
Gansu	2.469	2.893	3.455	2.958	3.056	0.058
Qinghai	1.834	1.993	2.248	1.662	2.003	0.006
Ningxia	3.194	3.691	3.724	3.750	3.723	0.049
Xinjiang	3.556	3.966	4.596	4.121	4.143	0.060

Figure 6. Spatial pattern of CI from cropping systems in China. (a) to (d) are the CIs in 2005, 2010, 2015, and 2020, respectively. (e) is the trend of CIs from 2005 to 2020. Note: it is produced by authors in ArcGIS 10.4.

Figure 7. Percentage and number of changes in crop mix type and CI. Note: it is produced by authors in Excel 2019.

Table 4. Correlation between crops and carbon emissions in China.

Crops	Rice	Wheat	Maize	Beans	Potato	Cotton	Oil crop	Hemp	Sugar	Tobacco	Vegetable	Melon
The number of provinces correlated	14	6	13	4	9	2	5	0	4	2	20	14
Average coefficient	0.808	0.687	0.773	0.691	0.737	0.661	0.745	0.566	0.687	0.715	0.814	0.792

Figure 8. Spatial pattern of correlations between various crops and CI from 2005 to 2020. Note: it is produced by authors in ArcGIS 10.4.

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