中国水稻食物系统碳足迹结构组成和地区差异

doi:10.16258/j.cnki.1674-5906.2023.08.006

生态环境学报 ›› 2023, Vol. 32 ›› Issue (8): 1405-1418.DOI: 10.16258/j.cnki.1674-5906.2023.08.006

中国水稻食物系统碳足迹结构组成和地区差异

王金明¹(), 秦晓波¹^,^*(), 万运帆¹, 周盛¹, 张志伟¹^,²

1.中国农业科学院农业环境与可持续发展研究所/农业部农业环境重点实验室/中国农业科学院碳达峰碳中和研究中心，北京 100081
2.南京信息工程大学，江苏南京 210044

收稿日期:2023-04-28 出版日期:2023-08-18 发布日期:2023-11-08
通讯作者: *秦晓波。E-mail: qinxiaobo@caas.cn
作者简介:王金明（1996年生），女，硕士研究生，研究方向为农业温室气体排放与减排。E-mail: wangjinming0305@163.com
基金资助:
国家重点研发计划(2021YFD1700202-05);江西省中央引导地方科技发展资金项目(20221ZDH04057);国家自然科学基金项目(41775157)

Structure and Regional Differences of Carbon Footprint of Rice Food System in China

WANG Jinming¹(), QIN Xiaobo¹^,^*(), WAN Yunfan¹, ZHOU Sheng¹, ZHANG Zhiwei¹^,²

1. Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences/Key Laboratory for Agro-Environment, Ministry of Agriculture and Rural Affairs/Carbon Peak Carbon Neutral Research Center, Chinese Academy of Agricultural Sciences, Beijing 100081, P. R. China
2. Nanjing University of Information Science & Technology, Nanjing 210044, P. R. China

Received:2023-04-28 Online:2023-08-18 Published:2023-11-08

摘要/Abstract

摘要：

水稻是中国及全球食物系统的重要组成部分，以食物系统视角研究其生命周期碳足迹对实现水稻食物系统低碳转型和绿色发展具有重要意义。该研究基于中国2018年22个水稻主产省份的统计数据，结合生命周期评估（LCA）法和国际水稻研究所（IRRI）开发的CF-Rice水稻碳足迹计算工具，计算并分析了中国水稻食物系统“从摇篮到销售”的碳足迹及其结构组成、地区差异和水稻类型差异。结果表明：1）以单位产量碳足迹进行比较（以CO₂ eq计），晚籼稻 (2.31 kg?kg^-1)>中籼稻 (1.32 kg?kg^-1)>粳稻 (1.13 kg?kg^-1)>早籼稻 (1.08 kg?kg^-1)；以单位面积碳足迹进行比较（以CO₂ eq计），晚籼稻 (9.15×10³ kg?hm^-2)>中籼稻 (6.34×10³ kg?hm^-2)>粳稻 (5.56×10³ kg?hm^-2)>早籼稻 (4.16×10³ kg?hm^-2)；2）稻田甲烷（CH₄）是水稻食物系统碳足迹最主要的组成部分，占36.2%－71.5%，其次是施肥，占8.69%－20.0%，收获环节占8.41%－18.5%，产前环节占4.97%－12.1%，机械作业、仓储、加工、包装和运输环节虽占比较小（均<10%）但也不容忽视；3）早籼稻、中籼稻和晚籼稻没有表现出明显的空间分布规律，而粳稻呈现出自北向南碳足迹增加的趋势，具体表现为：除山东外，东北地区（黑龙江、吉林、辽宁）和华北地区（内蒙古、河北）的粳稻碳足迹低于华东地区（安徽、江苏、浙江）、华中地区（河南、湖北）和西南地区（云南）；4）从温室气体的构成来看，CH₄对水稻食物系统碳足迹的贡献率最高，达到20.1%－76.4%，其次为二氧化碳（CO₂），贡献率为21.1%－72.3%，氧化亚氮（N₂O）的贡献率最低，仅有1.76%－10.7%。水稻食物系统碳足迹的地区和类型差异主要与气候条件、种植管理措施和排放因子有关，因此，控制稻田CH₄排放，优化水肥管理，减少能源消耗及粮食损失和浪费可有效降低水稻食物系统碳足迹。

关键词: 水稻食物系统, 碳足迹, 生命周期评估, 地区差异, 类型差异

Abstract:

Rice is an important part of the food system in China and the world. It is of great significance to study the life cycle carbon footprint of rice food system from the perspective of food system for low-carbon transformation and green development. Based on statistics from 22 major rice-producing provinces in China in 2018, the cradle-to-market carbon footprint of Rice food systems in China, including its structural composition, regional differences and rice type differences was calculated and analyzed by using the life cycle assessment (LCA) method and the CF-Rice rice carbon footprint calculation tool developed by the International Rice Research Institute (IRRI). The results showed that 1) when comparing carbon footprint per unit production (CO₂ eq), the carbon footprint was in the order of late indica rice (2.31 kg?kg^-1), middle indica rice (1.32 kg?kg^-1), japonica rice (1.13 kg?kg^-1) and early indica rice (1.08 kg?kg^-1). When comparing carbon footprint per unit area (CO₂ eq), the carbon footprint was in the order of late indica rice (9.15×10³ kg?hm^-2), middle indica rice (6.34×10³ kg?hm^-2), japonica rice (5.56×10³ kg?hm^-2) and early indica rice (4.16×10³ kg?hm^-2); 2) Methane (CH₄) in paddy field was the most important component of the carbon footprint of rice food system, accounting for 36.2%-71.5%, followed by fertilization (8.69%-20.0%), harvest (8.41%-18.5%) and prenatal (4.97%-12.1%). Mechanical operations, storage, processing, packaging and transportation, although only accounting for less than 10%, were also significant sources of emissions; 3) early indica rice, middle indica rice and late indica rice showed no obvious spatial distribution pattern, while the main producing areas of japonica rice had a large spatial span and showed an increasing trend of carbon footprint from north to south, specifically as follows: except for Shandong, the carbon footprint of japonica rice in Northeast (Heilongjiang, Jilin, Liaoning) and North China (Inner Mongolia, Hebei) was lower than that in East (Anhui, Jiangsu, Zhejiang), central (Henan, Hubei) and southwestern China (Yunnan); 4) from the perspective of the composition of greenhouse gases, the contribution rate of CH₄ to the carbon footprint of rice food system was the highest, reaching 20.1%-76.4%, followed by that of CO₂ (21.1%-72.3%), and that of N₂O (1.76%-10.7%) was the lowest. The regional and type differences of rice food system carbon footprint were mainly related to climatic conditions, planting management measures and emission factors. Hence, in order to reduce the carbon emissions of rice food system, it is necessary to take overall consideration to reduce the CH₄ emission of rice field, improve water and fertilizer management, reduce energy consumption, and decrease food loss and waste.

Key words: rice food systems, carbon footprint, life cycle assessment, regional variation, type difference

中图分类号:

S511
X16

王金明, 秦晓波, 万运帆, 周盛, 张志伟. 中国水稻食物系统碳足迹结构组成和地区差异[J]. 生态环境学报, 2023, 32(8): 1405-1418.

WANG Jinming, QIN Xiaobo, WAN Yunfan, ZHOU Sheng, ZHANG Zhiwei. Structure and Regional Differences of Carbon Footprint of Rice Food System in China[J]. Ecology and Environment, 2023, 32(8): 1405-1418.

图/表 12

参考文献 58

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地区	排放系数/(kg∙hm^-2)
地区	早籼稻	中籼稻	晚籼稻	粳稻
全国	80.2	193	207	131
河北				56.0
内蒙古				42.3
辽宁				75.3
吉林				44.0
黑龙江				82.0
江苏		159		159
浙江	154		287	276
安徽	128	167	258	167
福建	151	408	287
江西	76.5		199
山东				39.4
河南		142		142
湖北	124	189	253	189
湖南	76.4	226	199
广东	78.0		214
广西	83.8		217
海南	50.0		181
重庆		283
四川		237
贵州		290
云南		91.2		91.2
陕西		185

地区	排放系数/(kg∙hm^-2)
地区	早籼稻	中籼稻	晚籼稻	粳稻
全国	80.2	193	207	131
河北				56.0
内蒙古				42.3
辽宁				75.3
吉林				44.0
黑龙江				82.0
江苏		159		159
浙江	154		287	276
安徽	128	167	258	167
福建	151	408	287
江西	76.5		199
山东				39.4
河南		142		142
湖北	124	189	253	189
湖南	76.4	226	199
广东	78.0		214
广西	83.8		217
海南	50.0		181
重庆		283
四川		237
贵州		290
云南		91.2		91.2
陕西		185

排放源	碳排放系数	啊啊啊啊
泡田	331 kg∙hm^-2	International Rice Research Institute, 2022
种子	1.84 kg∙hm^-2	王兴等, 2017
农药	66.3 kg∙hm^-2	International Rice Research Institute, 2022
氮肥	5.68 g∙kg^-1
灌溉耗电	97.0 kg∙hm^-2
农机耗能	230 kg∙hm^-2
仓储耗电	11.0 kg∙t^-1
加工耗电	23.0 kg∙t^-1
包装耗电	2.00 kg∙t^-1
拖拉机耗能	0.257 g∙kg^-1∙km^-1

排放源	碳排放系数	啊啊啊啊
泡田	331 kg∙hm^-2	International Rice Research Institute, 2022
种子	1.84 kg∙hm^-2	王兴等, 2017
农药	66.3 kg∙hm^-2	International Rice Research Institute, 2022
氮肥	5.68 g∙kg^-1
灌溉耗电	97.0 kg∙hm^-2
农机耗能	230 kg∙hm^-2
仓储耗电	11.0 kg∙t^-1
加工耗电	23.0 kg∙t^-1
包装耗电	2.00 kg∙t^-1
拖拉机耗能	0.257 g∙kg^-1∙km^-1

环节	方式	项目	数值	参考文献
水稻种植		稻谷水分含量/%	14.5	国家发展和改革委员会, 2011
	灌溉/多次排水周期	水分管理方式的影响系数 (N/A)	0.550	International Rice Research Institute, 2022
	短时通气<1个月	稻田通气方式的影响系数 (N/A)	1.00
	短期<1个月: 晚籼稻	秸秆还田的尺度因子 (N/A)	1.00
	长期>1个月: 早籼稻、中籼稻、粳稻		0.190
	农家肥	有机肥料修正的尺度因子 (N/A)	0.210
收获和收获后		收获时的稻谷损失率	0.013	International Rice Research Institute, 2022
	晒干	晒干过程的稻谷损失率	0.040
	粮仓储存6个月	仓储过程的稻谷损失率	0.075
	基础技术 (柴油或汽油)/白米	精制过程的稻谷损失率	0.080
	基础技术 (柴油或汽油)/白米	副产品 (谷壳/米糠) 率	0.200/0.100
	拖拉机	运输距离/km	50.0
	早籼稻	价格/(￥∙t^-1)	2480	国家发展和改革委员会, 2018
	中籼稻/晚籼稻		2580
	粳稻		2620

中国水稻食物系统碳足迹结构组成和地区差异

Structure and Regional Differences of Carbon Footprint of Rice Food System in China

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参考文献 58

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Metrics

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变量	敏感性系数
变量	早籼稻	中籼稻	晚籼稻	粳稻
产量	-0.895	-0.905	-0.925	-0.897
生育期	0.363	0.575	0.720	0.443
种子用量	0.025	0.005	0.006	0.028
稻田CH₄排放量	0.362	0.577	0.715	0.443
农家肥用量	0.017	0.034	0.015	0.022
氮肥用量	0.192	0.131	0.087	0.200
运输距离	0.011	0.009	0.005	0.011
稻米价格	0.078	0.075	0.075	0.074

国家	单位面积碳足迹/(10³ kg∙hm^-2)	单位产量碳足迹/(kg∙kg^-1)	稻田CH₄排放占比/%	施肥占比/%	参考文献
意大利		2.90	68	9	Blengini et al., 2009
美国		1.47	69	19	Brodt et al., 2014
日本		1.46	75	7	Hokazono et al., 2012
泰国	4.92	0.93			Arunrat et al., 2022
印度	2.44	0.23-2.06	60	29	Nayak et al., 2022
中国	6.00±0.10	0.8±0.02			Yan et al., 2015a
	4.87±0.42	0.51-0.75			Fan et al., 2022
		1.24			Tian et al., 2021
		1.77			Xia et al., 2016
	7.28±0.08	1.06±0.03			Xu et al., 2017
	6.30±1.82	1.46±0.50	53	15	本研究

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[2]	姜超强, 李晨, 朱启法, 徐海清, 刘炎红, 沈嘉, 阎轶峰, 余飞, 祖朝龙. 皖南不同种植模式碳汇效应及经济效益评价[J]. 生态环境学报, 2022, 31(7): 1285-1292.
[3]	郝小雨, 王晓军, 高洪生, 毛明艳, 孙磊, 马星竹, 周宝库, 迟凤琴, 李伟群. 松嫩平原不同秸秆还田方式下农田温室气体排放及碳足迹估算[J]. 生态环境学报, 2022, 31(2): 318-325.