STRATEGIES FOR A LOW-CARBON FOOD SYSTEM IN CHINA

doi:10.15302/J-FASE-2023494

RESEARCH ARTICLE

Xinpeng JIN¹, Xiangwen FAN¹, Yuanchao HU², Zhaohai BAI¹, Lin MA¹(

)

¹. Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Soil Ecology, Center for Agricultural Resources Research, Institute of Genetic and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050021, China
². School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China

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Abstract

● A provincial stage-specific greenhouse gas (GHG) accounting model for the Chinese food system was developed.

● From 1992 to 2017, the net GHG emission from the Chinese food system increased by 38% from 785 to 1080 Tg CO₂-eq.

● In 2017, top GHG emission regions were located in the central and southern China, the North China Plain and Northeast China, while GHG sink regions were Tibet, Qinghai and Xinjiang.

● Total GHG emission from the Chinese food system could be reduced to 355 Tg CO₂-eq in a low-carbon scenario, with enhancing mitigation technologies, transforming diet and its related conditions and increasing agricultural activities contributing 60%, 25% and 15% of the GHG reductions, respectively.

In China, there has been insufficient study of whole food system greenhouse gas (GHG) accounting, which limits the development of mitigation strategies and may preclude the achievement of carbon peak and carbon neutrality goals. The paper presents the development of a carbon extension of NUFER (NUtrient flows in Food chain, Environment and Resources use model), a food system GHG emission accounting model that covers land use and land-use change, agricultural production, and post-production subsectors. The spatiotemporal characteristics of GHG emissions were investigated for the Chinese food system (CFS) from 1992 to 2017, with a focus on GHG emissions from the entire system. The potential to achieve a low-carbon food system in China was explored. The net GHG emissions from the CFS increased from 785 Tg CO₂ equivalent (CO₂-eq) in 1992 to 1080 Tg CO₂-eq in 2017. Agricultural activities accounted for more than half of the total emissions during the study period, while agricultural energy was the largest contributor to the GHG increase. In 2017, highest emitting regions were located in central and southern China (Guangdong and Hunan), the North China Plain (Shandong, Henan and Jiangsu) and Northeast China (Heilongjiang and Inner Mongolia) and contributed to over half of the total GHG emissions. Meanwhile, Xinjiang, Qinghai and Tibet are shown as carbon sink areas. It was found that food-system GHG emissions could be reduced to 355 Tg CO₂-eq, where enhancing endpoint mitigation technologies, transforming social-economic and diet conditions, and increasing agricultural productivities can contribute to 60%, 25% and 15%, respectively. Synergistic mitigation effects were found to exist in agricultural activities.

Keywords greenhouse gas emissions food system life cycle assessment environmental input-output analysis mitigation strategies

Corresponding Author(s): Lin MA

Just Accepted Date: 29 March 2023 Online First Date: 12 May 2023

Cite this article:

Xinpeng JIN,Xiangwen FAN,Yuanchao HU, et al. STRATEGIES FOR A LOW-CARBON FOOD SYSTEM IN CHINA[J]. Front. Agr. Sci. Eng. , 12 May 2023. [Epub ahead of print] doi: 10.15302/J-FASE-2023494.

URL:

https://academic.hep.com.cn/fase/EN/10.15302/J-FASE-2023494
https://academic.hep.com.cn/fase/EN/Y/V/I/0

Fig.1 Scope of the GHG emission accounting for the food system. These icons in the figure were from Vecteezy, and were used within the scope of its license agreement.

Tab.1 Data used in the GHG emission accounting and scenario analyses in this study

Type	2050 business as usual	2050 low-carbon	Data sources
GDP and population	Both GDP and population follow the SSP2s	Both GDP and population follow the SSP1s	[49]
GDP	Increase by 308% compared to 2015	Increase by 323% compared to 2015
Population	Decrease to 1286 million	Decrease to 1250 million
Diet	Keep the current trend toward a fatter eating pattern	Turn to the recommendation of Chinese Nutrition Society	[50,51]
Cereals	5179 kJ (+8% compared to 2010)	3998 kJ (–16%)
Red meat	1918 kJ (+15%)	1114 kJ (–33%)
Poultry	268 kJ (+21%)	465 kJ (+109%)
Milk	511 kJ (+114%)	473 kJ (+98%)
Fruit and vegetable	779 kJ (–19%)	1214 kJ (+26%)
Agricultural productivities	Keep unchanged	Crop productivity forecasts originate from the SSP1 results in GLOBIOM Taking the USA as a reference, pig and poultry productivities are predicted to increase by 20% over 2010. For beef cattle, dairy cattle, sheep, goats and layer, the increase rates are assumed to be 40%	[52–54]
Rice	–	6.6 t·ha^–1
Wheat	–	7.6 t·ha^–1
Corn	–	9.1 t·ha^–1
Pork	–	110 kg per head
Beef	–	191 kg per head
Milk	–	10.8 t per head
Mitigation technologies	No further measures are adoptedAll emission factors keep unchanged, related activity data changes in current trend	All effective activities are adopted to reduce GHG emission	–
Agricultural inputs changed
Nitrogen fertilizer	13% higher than 2017 (BAU scenario in cited paper)	22% lower than 2017 (4R nutrient management adopted, with enhanced organic fertilizer returning)	[55]
Phosphorus fertilizer	5% higher than 2017 (BAU and SSP2 scenarios in cited papers)	69% lower than 2017 (manure is well managed and returned to the field)	[56,57]
Potash fertilizer	19% higher than 2017 (SSP2 in cited paper)	15% higher than 2017 (SSP1 in cited paper)	[58]
Diesel	74% higher than 2017 (BAU scenario in cited paper)	44% higher than 2017 (low-carbon scenario in cited paper)	[59]
Pesticides	15% (just assumption, an average change of nitrogen and phosphorus fertilizer)	13% lower than 2017 (just assumption, an average change of nitrogen and phosphorus fertilizer)	–
Irrigation	53% higher than 2017 (BAU scenario in cited paper)	31% higher than 2017 (low-carbon scenario in cited paper)	[59]
Film	77% higher than 2017 (SSP2 scenario in cited paper)	40% higher than 2017 (SSP1 scenario in cited paper)	[55,60]
Technology & management changed
Cropland carbon sink ability	–	120% high than current practice (mineral fertilizer + straw returning + no tillage)	[61]
Grassland carbon sink ability	–	Increase by 0.017 ha⁻¹·yr⁻¹ CO₂-eq compared to present condition (optimizing grazing intensity)	[62]
Rice cultivation	–	–32% (off-season application of straw + mid-season draining)	[63]
Straw return ratio	–	Reach 80% (catch up with developed countries)	[55]
Manure return ratio	–	Reach 80% (catch up with developed countries)	[55]
Soil N₂O emission	–	–25% (integrated nitrogen management)	[64,65]
Enteric CH₄	–	–13% (reducing the forage-to-concentrate ratio + feed addictive)	[66]
Manure management CH₄	–	–60% (covering + manure addictives + acidification)	[67,68]
Manure management N₂O	–	–15% (manure addictives + optimizing house condition)	[66,67]
Fertilizer production	–	–44% (catch up with the emission intensity in Europe)	[69]
Diesel	–	–32% (increase mechanical efficiency + equipment alteration)	[59]
Film production	–	–38% (equipment alteration + change film production structure + new material)	[70]
Irrigation	–	–39% (increase mechanical efficiency + equipment alteration)	[59]
Straw burning ratio	–	None	–
CO₂ emission intensity in each economic sector	–	–35% (same as the decrease between 2005 and 2030)	[71]

Tab.2 The descriptions of scenarios and the changes to corresponding activity data and parameters

Fig.2 GHG emissions from the CFS by sector from 1992 to 2017 (a) and the Sankey diagram illustrating the link between GHG emission sectors, gas types and stages in the CFS (b), where the percentages in parentheses are the emission change between 1992 and 2017 (b).

Fig.3 Spatial distribution of greenhouse gas (GHG) emissions from agricultural activities (a), agricultural energy use (b), LULUC (land use and land-use change) as net carbon sink, with negative values representing GHG emissions and positive values representing carbon sinks (c), post-production (d), and whole food system and the emissions from the whole food production system (e) in 2017. NCP, North China Plain: BJ, Beijing; TJ, Tianjin; HE, Hebei; SX, Shanxi; SD, Shandong; HA, Henan. NE, Northeast China: LN, Liaoning; JL, Jilin; HL, Heilongjiang. MLY, middle and lower reaches of Yangtze River: SH, Shanghai; JS, Jiangsu; ZJ, Zhejiang; AH, Anhui; JX, Jiangxi; HB, Hubei; HN, Hunan. SE, Southeast China: FJ, Fujian; GD, Guangdong; GX, Guangxi; HI, Hainan. SW, Southwest China: CQ, Chongqing; SC, Sichuan; GZ, Guizhou; YN, Yunnan; XZ, Tibet. NW, Northwest China: IM, Inner Mongolia; SN, Shaanxi; GS, Gansu; QH, Qinghai; NX, Ningxia; XJ, Xinjiang.

Tab.3 The subsector disaggregated GHG emissions from the Chinese food system in 2017 and 2050 scenarios

Fig.4 Mitigation potential of different measures in the Chinese food system. 2050 BAU, 2050 business as usual scenario; 2050 LC, 2050 low-carbon scenario.

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