1School of Economics, Ocean University of China, Qingdao 266100, China 2Institute of Marine Development, Ocean University of China, Qingdao 266100, China 3School of Foreign Languages, Ocean University of China, Qingdao 266100, China 4Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China 5University of Chinese Academy of Sciences, Beijing 100049, China
There are eight provinces and autonomous regions (Gansu Province, Ningxia Hui Autonomous Region, Xinjiang Uygur Autonomous Region, Inner Mongolia Autonomous Region, Tibet Autonomous Region, Qinghai Province, Shanxi Province, and Shaanxi Province) in Northwest China, most areas of which are located in arid and semi-arid regions (northwest of the 400 mm precipitation line), accounting for 58.74% of the country's land area and sustaining approximately 7.84×106 people. Because of drought conditions and fragile ecology, these regions cannot develop agriculture at the expense of the environment. Given the challenges of global warming, the green total factor productivity (GTFP), taking CO2 emissions as an undesirable output, is an effective index for measuring the sustainability of agricultural development. Agricultural GTFP can be influenced by both internal production factors (labor force, machinery, land, agricultural plastic film, diesel, pesticide, and fertilizer) and external climate factors (temperature, precipitation, and sunshine duration). In this study, we used the Super-slacks-based measure (Super-SBM) model to measure agricultural GTFP during the period 2000-2016 at the regional level. Our results show that the average agricultural GTFP of most provinces and autonomous regions in arid and semi-arid regions underwent a fluctuating increase during the study period (2000-2016), and the fluctuation was caused by the production factors (input and output factors). To improve agricultural GTFP, Shaanxi, Shanxi, and Gansu should reduce agricultural labor force input; Shaanxi, Inner Mongolia, Gansu, and Shanxi should decrease machinery input; Shaanxi, Inner Mongolia, Xinjiang, and Shanxi should reduce fertilizer input; Shaanxi, Xinjiang, Gansu, and Ningxia should reduce diesel input; Xinjiang and Gansu should decrease plastic film input; and Gansu, Shanxi, and Inner Mongolia should cut pesticide input. Desirable output agricultural earnings should be increased in Qinghai and Tibet, and undesirable output (CO2 emissions) should be reduced in Inner Mongolia, Xinjiang, Gansu, and Shaanxi. Agricultural GTFP is influenced not only by internal production factors but also by external climate factors. To determine the influence of climate factors on GTFP in these provinces and autonomous regions, we used a Geographical Detector (Geodetector) model to analyze the influence of climate factors (temperature, precipitation, and sunshine duration) and identify the relationships between different climate factors and GTFP. We found that temperature played a significant role in the spatial heterogeneity of GTFP among provinces and autonomous regions in arid and semi-arid regions. For Xinjiang, Inner Mongolia, and Tibet, a suitable average annual temperature would be in the range of 7°C-9°C; for Gansu, Shanxi, and Ningxia, it would be 11°C-13°C; and for Shaanxi, it would be 15°C-17°C. Stable climatic conditions and more efficient production are prerequisites for the development of sustainable agriculture. Hence, in the agricultural production process, reducing the redundancy of input factors is the best way to reduce CO2 emissions and to maintain temperatures, thereby improving the agricultural GTFP. The significance of this study is that it explores the impact of both internal production factors and external climatic factors on the development of sustainable agriculture in arid and semi-arid regions, identifying an effective way forward for the arid and semi-arid regions of Northwest China.
Oak Ridge National Laboratory (ORNL), United States
Pesticide (kg CE/kg)
4.9341
Oak Ridge National Laboratory (ORNL), United States
Plastic film (kg CE/kg)
5.1800
Institute of Resource, Ecosystem and Environment of Agriculture of Nanjing Agricultural University (IREEA), China
Diesel (kg CE/kg)
0.5927
Intergovernmental Panel on Climate Change (IPCC), United Nations
Irrigation (kg/km2)
266.4800
Duan et al. (2011), China
Plowing (kg/km2)
312.6000
China Agricultural University (CAU), China
Variable type
Variable
Mean
Standard deviation
Input factors
Number of agricultural labor force (×104 persons)
1165.3802
787.6478
Total power of agricultural machinery (×104 kW)
1424.8896
960.7656
Volume of effective component of fertilizer (×104 t)
89.1750
71.8066
Use of agricultural diesel (×104 t)
32.3338
25.3809
Use of agricultural plastic film (×104 t)
5.1745
6.0462
Use of agricultural pesticide (×104 t)
1.5174
1.6592
Total sown area of farm crops (×103 hm2)
3121.5603
2140.6714
Output factors
Gross output value of agriculture (×108 CNY, at 2000 constant price)
306.0458
234.7596
CO2 emissions (×104 t)
217.4791
157.7604
Region
Province/ Autonomous region
Labor Force (×104 persons)
Machinery (×104 kW)
Fertilizer (×104 t)
Diesel (×104 t)
Plastic Film (×104 t)
Pesticide (×104 t)
Land (×103 hm2)
Earnings (×108 CNY)
CO2 Emissions (×104 t)
Arid
Gansu
1799.4180
1752.1940
81.5529
26.8824
11.3788
4.1811
3909.8470
388.6244
273.9565
Ningxia
355.0647
627.2294
33.3706
17.2529
1.0324
0.2182
1179.5180
96.6187
78.3374
Xinjiang
1136.8940
1530.3290
151.1882
59.6412
16.1241
1.8047
4461.7940
531.6966
383.4737
Semi-
Tibet
226.8471
345.2588
4.4353
2.7294
0.0859
0.0929
239.1765
25.8114
12.9417
arid
Shanxi
2001.4290
2470.2410
103.7412
27.6823
3.8182
2.4718
3781.5060
380.3657
243.2440
Qinghai
323.8235
365.8294
8.0941
5.8235
0.3171
0.1871
522.7882
37.3417
27.3607
Shaanxi
2289.5120
1773.7060
180.0824
65.1411
3.1341
1.1465
4217.3530
525.5955
335.4848
Inner Mongolia
1190.0530
2534.3290
150.9353
53.5177
5.5053
2.0365
6660.5000
462.3124
385.0342
Average
1165.3802
1424.8896
89.1750
32.3338
5.1745
1.5174
3121.5603
306.0458
217.4791
Region
Province/ Autonomous region
Growth rate (%)
Labor force
Machinery
Fertilizer
Diesel
Plastic film
Pesticide
Land
Earnings
CO2 emissions
Arid
Gansu
-28.9125
80.1400
44.8062
183.3333
203.8941
513.1579
14.4511
145.9105
74.5302
Ningxia
-24.0474
52.5223
72.4576
95.6522
214.5833
62.5000
21.0231
232.7867
57.0062
Xinjiang
35.6767
199.8355
215.9091
121.1587
202.1566
102.9412
80.6876
134.5649
148.8370
Semi-
Tibet
7.4723
454.6725
136.0000
785.7143
1700.0000
57.1428
10.6880
-13.6474
86.7169
arid
Shanxi
-30.5950
2.5275
34.5977
28.6344
77.1739
74.8571
-6.3576
174.4045
18.5313
Qinghai
-14.7356
79.0008
22.2222
8.4746
1216.6670
0.0000
-0.7585
117.6976
20.6629
Shaanxi
-38.4843
108.2558
77.6677
66.3082
72.7273
28.1553
-6.7415
168.9692
39.7402
Inner Mongolia
-28.9657
146.6933
213.6364
170.9030
176.3006
262.9213
29.2709
119.9713
98.7764
Statistic
Temperature
Precipitation
Sunshine duration
q statistic
0.2442
0.0173
0.0203
P value
0.9817
1.0000
1.0000
Temperature
Precipitation
Sunshine duration
Temperature
Precipitation
Y
Sunshine duration
Y
N
Temperature
Precipitation
Sunshine duration
Temperature
0.2442
Precipitation
0.3004
0.0173
Sunshine duration
0.2981
0.0550
0.0203
Climate factor
Graphical representation
Interaction
Temperature∩Precipitation
Enhances, nonlinear
Temperature∩Sunshine duration
Enhances, nonlinear
Precipitation∩Sunshine duration
Enhances, nonlinear
Temperature
5°C-7°C
7°C-9°C
9°C-11°C
11°C-13°C
13°C-15°C
15°C-17°C
Average GTFP
0.3960
0.6615
0.4857
0.6785
0.5673
0.6748
5°C-7°C
7°C-9°C
Y
9°C-11°C
Y
Y
11°C-13°C
Y
N
Y
13°C-15°C
Y
N
N
N
Over 15°C
Y
N
Y
N
N
Precipitation
0-200 mm
200-400 mm
400-600 mm
600-800 mm
Over 800 mm
Average GTFP
0.5073
0.5749
0.5911
0.5772
0.4411
0-200 mm
200-400 mm
N
400-600 mm
N
N
600-800 mm
N
N
N
Over 800 mm
N
N
N
N
Sunshine
1000-1500 h
1500-2000 h
2000-2500 h
Average GTFP
0.5803
0.5827
0.5804
1000-1500 h
1500-2000 h
N
2000-2500 h
N
N
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2020, Vol. 12 
), ZHANG Yibo3, SUN Lingxiao4, YU Xiang4, YU Yang4,5,*(
