Volume 41 Issue 5
Sep.  2024
Turn off MathJax
Article Contents

HUANG Wei, ZHANG Hongying, XIAO Xiangze, LIN Lang, WANG Cheng. Challenges and countermeasures in implementing carbon labeling for agricultural products[J]. Journal of Zhejiang A&F University, 2024, 41(5): 909-918. doi: 10.11833/j.issn.2095-0756.20240373
Citation: HUANG Wei, ZHANG Hongying, XIAO Xiangze, LIN Lang, WANG Cheng. Challenges and countermeasures in implementing carbon labeling for agricultural products[J]. Journal of Zhejiang A&F University, 2024, 41(5): 909-918. doi: 10.11833/j.issn.2095-0756.20240373

Challenges and countermeasures in implementing carbon labeling for agricultural products

doi: 10.11833/j.issn.2095-0756.20240373
  • Received Date: 2024-05-29
  • Accepted Date: 2024-08-26
  • Rev Recd Date: 2024-08-24
  • Available Online: 2024-09-25
  • Publish Date: 2024-09-25
  • The implementation of carbon labeling for agricultural products can promote precise and efficient carbon reduction in agricultural sector, support the realization of agricultural ecological value, innovate agricultural income models, and enhance domestic and international market competitiveness. China started late in this respect compared with foreign countries, with insufficient guidance from the top, and it was necessary to accelerate the implementation process. Difficulties existing in the implementation process of carbon labeling for agricultural products were analyzed. On the one hand, the carbon footprint accounting capacity for agricultural products was weak. Due to incomplete accounting standards and the weak data base, the accounting results were incomplete and inconsistent and comparability was low. On the other hand, there was insufficient driving force for the implementation of carbon labeling for agricultural products. Factors such as limited awareness, ability, and motivation of agricultural producers, weak willingness of consumers to pay, and lack of established standards and systems all contributed to limited credibility of accounting and certification results, and funding and other elements of security were not guaranteed. The main paths for promoting the application of carbon labeling for agricultural products were discussed, such as speeding up the development of accounting standards, consolidating the data base, promoting international mutual recognition of standards, data, and results, so as to enhance the capacity of carbon footprint accounting. Then, sound carbon labeling system should be established, including certification system and factor support system. Finally, the promotion of carbon labeling should be intensified by developing green consumption scenarios and providing technical support. [Ch, 2 fig. 1 tab. 45 ref.]
  • [1] DONG Linghui, MAO Fengcheng, ZHOU Yufeng, GU Lei, ZHOU Tianhuan, LI Zhengcai, ZHOU Guomo.  Carbon footprint assessment and emission reduction path analysis offive major bamboo shoot export products . Journal of Zhejiang A&F University, 2024, 41(5): 887-897. doi: 10.11833/j.issn.2095-0756.20240277
    [2] KONG Delei, JIANG Peikun.  Approaches and policy recommendations for reducing emissions and increasing carbon sinks in crop industry under the background of carbon peak and carbon neutrality . Journal of Zhejiang A&F University, 2023, 40(6): 1357-1365. doi: 10.11833/j.issn.2095-0756.20220742
    [3] XU Qihu, LIN Liping, XUE Chunquan, LUO Yong, LEI Yuancai.  Component specific carbon content and storage of Cinnamomum camphora in Guangdong Province . Journal of Zhejiang A&F University, 2019, 36(1): 70-79. doi: 10.11833/j.issn.2095-0756.2019.01.010
    [4] HE Tao, SUN Yujun.  Dynamic monitoring of forest carbon stocks based on the InVEST model . Journal of Zhejiang A&F University, 2016, 33(3): 377-383. doi: 10.11833/j.issn.2095-0756.2016.03.002
    [5] GUO Hanru, ZHANG Maozhen, XU Lihua, YUAN Zhenhua, CHEN Tiange.  Geographically weighted regression based on estimation of regional forest carbon storage . Journal of Zhejiang A&F University, 2015, 32(4): 497-508. doi: 10.11833/j.issn.2095-0756.2015.04.002
    [6] XU Yabin, LI Lanying, ZHOU Zigui, ZHANG Yong, HUANG Yujie.  Energy intensity, industrial structure and selection of low-carbon policy . Journal of Zhejiang A&F University, 2015, 32(4): 603-610. doi: 10.11833/j.issn.2095-0756.2015.04.017
    [7] PENG Weiliang, GU Lei, HU Chenpei, ZHOU Pengfei, HONG Minghui, LI Cuiqin.  A research on consumers’ willingness to pay for low-carbon floor to the scenario simulation of carbon labeling floor . Journal of Zhejiang A&F University, 2015, 32(5): 655-660. doi: 10.11833/j.issn.2095-0756.2015.05.001
    [8] SHAO Xinghua, WANG Aibin.  Organic carbon and black carbon with fertilization in paddy and upland soils . Journal of Zhejiang A&F University, 2014, 31(4): 554-559. doi: 10.11833/j.issn.2095-0756.2014.04.010
    [9] BAI Yanfeng, ZHANG Shougong, JIANG Chunqian.  International comparison of carbon flows of harvested wood products . Journal of Zhejiang A&F University, 2014, 31(1): 72-77. doi: 10.11833/j.issn.2095-0756.2014.01.011
    [10] ZHOU Pengfei, GU Lei, PENG Weiliang, ZHOU Yufeng, LI Cuiqin, LIU Hongzheng.  A carbon footprint assessment and composition analysis of flattened bamboo chopping board . Journal of Zhejiang A&F University, 2014, 31(6): 860-867. doi: 10.11833/j.issn.2095-0756.2014.06.006
    [11] ZHANG Zhe, SHEN Yueqin, LONG Fei, ZHU Zhen, HE Xiangrong.  Knowledge mapping of research on forest carbon sinks . Journal of Zhejiang A&F University, 2013, 30(4): 567-577. doi: 10.11833/j.issn.2095-0756.2013.04.017
    [12] LI Cuiqin, ZHOU Yufeng, GU Lei, SHI Yongjun, SHEN Zhenming, XU Xiaojun, LI Ruijun.  Carbon transfer of Phyllostachys edulis filar products . Journal of Zhejiang A&F University, 2013, 30(1): 63-68. doi: 10.11833/j.issn.2095-0756.2013.01.009
    [13] SUN Chong, LIU Qijing.  Carbon storage changes for major forest types in Beijing . Journal of Zhejiang A&F University, 2013, 30(1): 69-75. doi: 10.11833/j.issn.2095-0756.2013.01.010
    [14] BAI Yanfeng, JIANG Chunqian, ZHANG Shougong, LEI Jingpin.  Carbon accounting approaches for wood products and potential applications . Journal of Zhejiang A&F University, 2013, 30(3): 423-427. doi: 10.11833/j.issn.2095-0756.2013.03.020
    [15] WENG Zhi-xiong, SHEN Yue-qin, Lü Qiu-ju, ZHAO Sheng-jun, MA Yin-fang.  Analysis on the public carbon footprint of Zhejiang Province . Journal of Zhejiang A&F University, 2012, 29(2): 265-271. doi: 10.11833/j.issn.2095-0756.2012.02.017
    [16] WANG Xi-feng, SHEN Yue-qin, WANG Feng, ZHENG Xu-li, HU Zhong-ming.  Carbon-fixing oriented management patterns of Phyllostachys pubescens and their benefits . Journal of Zhejiang A&F University, 2011, 28(6): 943-948. doi: 10.11833/j.issn.2095-0756.2011.06.018
    [17] BAI Yan-feng, JIANG Chun-qian, LU De, ZHU Zhen.  Carbon stock change of harvested wood products in China . Journal of Zhejiang A&F University, 2007, 24(5): 587-592.
    [18] ZHOU Guo-mo, LIU En-bin, SHE Guang-hui.  Summary of estimated methods on forest soil's carbon pool . Journal of Zhejiang A&F University, 2006, 23(2): 207-216.
    [19] GAO Ying.  Countermeasures for green barrier and trade of China’s agricultural products . Journal of Zhejiang A&F University, 2006, 23(1): 98-102.
    [20] Jiang Peikun, JiangQiuyi, Xu Qiufang, Qian Xinbiao, Jin Lei..  Study on Root Exudates of Chinese Fir Seedling Using Carbon 14. . Journal of Zhejiang A&F University, 1994, 11(3): 241-246.
  • [1]
    IPCC, Emissions Trends and Drivers. In IPCC, 2022: Climate Change 2022: Mitigation of Climate Change [M]. Cambridge: Cambridge University Press, 2022: 238.
    [2]
    GAO Ming, ZHANG Zhexi. Positioning and policy suggestions of China’s agricultural green development under the targets of carbon peaking and carbon neutrality[J]. Journal of Huazhong Agricultural University (Social Sciences Edition), 2022(1): 24 − 31.
    [3]
    LAL R. Soil carbon sequestration impacts on global climate change and food security[J]. Science, 2004, 304(5677): 1623 − 1627.
    [4]
    ZHANG Mingjie, ZHANG Jinghong, LI Wentao, et al. Review on research of crop carbon footprint accounting in China[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2023, 44(5): 148 − 154.
    [5]
    MA Haibo, ZHU Qiang. Accounting carbon footprint of rice in China based on life cycle evaluation[J]. Journal of Arid Land Resources and Environment, 2023, 37(6): 11 − 19.
    [6]
    LU Yujia, CHEN Yangfen, KANG Yongxing. Agricultural and rural modernization under the new development pattern in China[J]. Research of Agricultural Modernization, 2022, 43(2): 211 − 220.
    [7]
    WEIDEMA B P, THRANE M, CHRISTENSEN P, et al. Carbon footprint: a catalyst for life cycle assessment?[J]. Journal of Industrial Ecology, 2008, 12(1): 3 − 6.
    [8]
    International Organization for Standardization. Greenhouse Gases−Carbon Footprint of Products-Requirements and Guidelines for Quantification: ISO 14067−2018 [S]. Switzerland: ISO Copyright Office, 2018.
    [9]
    KONG Delei, JIANG Peikun. Approaches and policy recommendations for reducing emissions and increasing carbon sinks in crop industry under the background of carbon peak and carbon neutrality[J]. Journal of Zhejiang A&F University, 2023, 40(6): 1357 − 1365.
    [10]
    ZHU Rui, QIN Peng. Principles and routines of the regulation of Chinese carbon label content[J]. China Population, Resources and Environment, 2020, 30(2): 60 − 69.
    [11]
    COHEN M A , VANDENBERGH M P. The potential role of carbon labeling in a green economy [J]. Energy Economics, 2012, 34 (1): 53 − 63.
    [12]
    WACKERNAGEL M, REES W. Our Ecological Footprint: Reducing Human Impact on the Earth [M]. Gabriola: New Society Publisher, 1996.
    [13]
    HU Yu, DING Fei, ZHAO Bin, et al. Small label and big strategies: construction and practice of carbon labeling system for agricultural products[J]. Environmental Protection, 2022, 50(16): 22 − 27.
    [14]
    ZHANG Dan. Carbon Footprint and Low Carbon Strategy for Grain Production in China [D]. Beijing: China Agricultural University, 2017.
    [15]
    OZLU E, ARRIAGA F J, BILEN S, et al. Carbon footprint management by agricultural practices [J/OL]. Biology, 2022, 11 (10): 1453[2024-04-29]. doi: 10.3390/biology11101453.
    [16]
    HOLKA M, KOWALSKA J, JAKUBOWSKA M. Reducing carbon footprint of agriculture: can organic farming help to mitigate climate change? [J/OL]. Agriculture, 2022, 12 (9): 1383[2024-04-29]. doi: 10.3390/agriculture12091383.
    [17]
    ZHANG Lu, GUO Qing. Impact mechanism of carbon labeling on low-carbon agri-product consumption behavior: an empirical research based on structural equation modeling and mediation test[J]. Systems Engineering, 2015, 33(11): 66 − 74.
    [18]
    ZHANG Xiongzhi, WANG Yan, WEI Huihuang, et al. The impacts and countermeasures of carbon label on import and export trade of China’s agricultural products[J]. China Population, Resources and Environment, 2017, 27(11): 10 − 13.
    [19]
    ZHANG Dan, ZHANG Weifeng. Low carbon agriculture and a review of calculation methods for crop production carbon footprint accounting[J]. Resources Science, 2016, 38(7): 1395 − 1405.
    [20]
    ZHANG Li. Integrative Effects of Green Manure and Straw Incorporation on Greenhouse Gas Emissions and Environmental Performance under the Typical Rice Cropping Systems in Southern China [D]. Nanjing: Nanjing Agricultural University, 2018.
    [21]
    ZHU Qiang, DUAN Jihong, QlAN Yuhao, et al. Carbon footprint of organic rice based on life cycle theory: case of mountain organic rice in Jinzhai County[J]. Journal of Arid Land Resources and Environment, 2019, 33(10): 41 − 46.
    [22]
    HE Hao, WU Longmei, HUANG Qing, et al. Study on carbon footprints and economic benefits of different rice cropping patterns in double cropping rice area of southern China[J]. Guangdong Agricultural Sciences, 2021, 48(11): 8 − 17.
    [23]
    XU Heshui. Investigation on Soil Carbon Sequestration and Mitigation of Greenhouse Gas Emission by the Integrated Rice-Azolla Cropping System in Double Rice Cropped Region [D]. Beijing: China Agricultural University, 2017.
    [24]
    CHEN Zhongdu, XU Chunchun, JI Long, et al. Carbon footprint analysis of double cropping rice production in the middle Yangtze River valley based on household surveys[J]. Chinese Journal of Rice Science, 2018, 32(6): 601 − 609.
    [25]
    HU Naijuan, SHI Hang, ZHU Liqun. Effects of different straw returning modes on carbon footprint in a rice-wheat rotation system[J]. Resources and Environment in the Yangtze Basin, 2018, 27(12): 2775 − 2783.
    [26]
    ADEWALE C, REGANOLD J P, HIGGINS S, et al. Improving carbon footprinting of agricultural systems: boundaries, tiers, and organic farming[J]. Environmental Impact Assessment Review, 2018, 71(7): 41 − 48.
    [27]
    CHEN Ru, ZHANG Ruoyan, HAN Hongyun, et al. Is farmers’ agricultural production a carbon sink or source?-Variable system boundary and household survey data [J/OL]. Journal of Cleaner Production, 2020, 266 : 122108[2024-04-29]. doi: 10.1016/j.jclepro.2020.122108.
    [28]
    CHEN Zhongdu, XU Chunchun, JI Long, et al. Dynamic of carbon footprint and its composition for double rice production in Southern China during 2004−2014[J]. Chinese Journal of Applied Ecology, 2018, 29(11): 3669 − 3676.
    [29]
    WANG Guangyu, ZHU Lijun, ZHANG Yang. Carbon footprints of three cultivation systems for double-cropping rice in the Yangtze River Plain of Anhui Province[J]. Jiangsu Agricultural Sciences, 2021, 49(3): 91 − 95.
    [30]
    LIN Zhimin, LI Zhou, WEN Peiying, et al. Field greenhouse gas emission characteristics and carbon footprint of ratoon rice[J]. Chinese Journal of Applied Ecology, 2022, 33(5): 1340 − 1351.
    [31]
    ZHOU Haozhi, WU Mengqin, LUO Xixiu, et al. Evaluating carbon footprint and economic benefit under different cultivation modes of ratooning rice[J]. Journal of Huazhong Agricultural University, 2023, 42(2): 71 − 78.
    [32]
    CHEN Zhongdu, XU Chunchun, JI Long, et al. Carbon and nitrogen footprints of double rice production in Yangtze River Based on farm survey data: a case study of Jiangxi and Hunan[J]. Crops, 2023(2): 229 − 237.
    [33]
    FENG Chen. Carbon Footprint of Rice Production and Carbon Emission Reduction Potential of Chemical Fertilizer Reduction in Liaoning Province [D]. Shenyang: Shenyang Agricultural University, 2022.
    [34]
    KOUAZOUNDE J B, GBENOU J D, BABATOUNDE S, et al. Development of methane emission factors for enteric fermentation in cattle from Benin using IPCC Tier 2 methodology[J]. Animal, 2015, 9(3): 526 − 533.
    [35]
    WANG Xinglai, MIAO Shujie, QIAO Yunfa. Evaluating the carbon footprint of the rice-wheat rotation system based on localized parameters in Jiangsu Province[J]. Ecology and Environmental Sciences, 2023, 32(9): 1682 − 1691.
    [36]
    RONDONI A, GRASSO S. Consumers behaviour towards carbon footprint labels on food: a review of the literature and discussion of industry implications [J/OL]. Journal of Cleaner Production, 2021, 301 [2024-04-29]. doi: 10.1016/j.jclepro.2021.127031.
    [37]
    CANAVARI M, CODERONI S. Consumer stated preferences for dairy products with carbon footprint labels in Italy[J]. Agricultural and Food Economics, 2020, 8(1): 1 − 16.
    [38]
    EDENBRANDT A K, NORDSTROM J. The future of carbon labeling-Factors to consider[J]. Agricultural and Resource Economics Review, 2023, 52(1): 151 − 167.
    [39]
    ZHOU Weiyang. Research on the Willingness of Residents in Zhejiang Province to Pay for Low-carbon Label Agricultural Products: A Case Study of Rice [D]. Hangzhou: Zhejiang A&F University, 2023.
    [40]
    ZHANG Xiaoyu, MA Ying, MA Jia, et al. Metropolitan resident’s cognition and willingness of payment for low-carbon agricultural products: empirical analysis on low-carbon vegetables in Shanghai[J]. Acta Agriculturae Shanghai, 2019, 35(3): 116 − 122.
    [41]
    ESCOBAR N, TIZADO E J, ERMGASSEN E K H J Z, et al. Spatially-explicit footprints of agricultural commodities: Mapping carbon emissions embodied in Brazil’s soy exports [J/OL]. Global Environmental Change, 2020, 62 : 102067[2024-04-29]. doi: 10.1016/j.gloenvcha.2020.102067.
    [42]
    GAO Tao, LIU Qing, WANG Jianping. A comparative study of carbon footprint and assessment standards[J]. International Journal of Low-Carbon Technologies, 2014, 9(3): 237 − 243.
    [43]
    TONG Qingmeng, SHEN Xue, ZHANG Lu, et al. Standard system of accounting footprint based on life cycle assessment method: international standards and practices[J]. Journal of Huazhong Agricultural University (Social Sciences Edition), 2018(1): 46 − 57, 158.
    [44]
    XIE Yayan, SU Yang, LI Feng. The evolutionary game analysis of low carbon production behaviour of farmers, government and consumers in food safety source governance [J/OL]. International Journal of Environmental Research and Public Health, 2022, 19 (19): 12211[2024-04-29]. doi: 10.3390/ijerph191912211.
    [45]
    CARRERO I, VALOR C, ESTELA D, et al. Designed to be noticed: a reconceptualization of carbon food labels as warning labels [J/OL]. Sustainability, 2021, 13 (3): 1581[2024-04-29]. doi:10.3390/su13031581.
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(2)  / Tables(1)

Article views(56) PDF downloads(3) Cited by()

Related
Proportional views

Challenges and countermeasures in implementing carbon labeling for agricultural products

doi: 10.11833/j.issn.2095-0756.20240373

Abstract: The implementation of carbon labeling for agricultural products can promote precise and efficient carbon reduction in agricultural sector, support the realization of agricultural ecological value, innovate agricultural income models, and enhance domestic and international market competitiveness. China started late in this respect compared with foreign countries, with insufficient guidance from the top, and it was necessary to accelerate the implementation process. Difficulties existing in the implementation process of carbon labeling for agricultural products were analyzed. On the one hand, the carbon footprint accounting capacity for agricultural products was weak. Due to incomplete accounting standards and the weak data base, the accounting results were incomplete and inconsistent and comparability was low. On the other hand, there was insufficient driving force for the implementation of carbon labeling for agricultural products. Factors such as limited awareness, ability, and motivation of agricultural producers, weak willingness of consumers to pay, and lack of established standards and systems all contributed to limited credibility of accounting and certification results, and funding and other elements of security were not guaranteed. The main paths for promoting the application of carbon labeling for agricultural products were discussed, such as speeding up the development of accounting standards, consolidating the data base, promoting international mutual recognition of standards, data, and results, so as to enhance the capacity of carbon footprint accounting. Then, sound carbon labeling system should be established, including certification system and factor support system. Finally, the promotion of carbon labeling should be intensified by developing green consumption scenarios and providing technical support. [Ch, 2 fig. 1 tab. 45 ref.]

HUANG Wei, ZHANG Hongying, XIAO Xiangze, LIN Lang, WANG Cheng. Challenges and countermeasures in implementing carbon labeling for agricultural products[J]. Journal of Zhejiang A&F University, 2024, 41(5): 909-918. doi: 10.11833/j.issn.2095-0756.20240373
Citation: HUANG Wei, ZHANG Hongying, XIAO Xiangze, LIN Lang, WANG Cheng. Challenges and countermeasures in implementing carbon labeling for agricultural products[J]. Journal of Zhejiang A&F University, 2024, 41(5): 909-918. doi: 10.11833/j.issn.2095-0756.20240373
  • 根据联合国政府间气候变化专门委员会(Intergovernmental Panel on Climate Change, IPCC)的报告,2019年全球农业、林业和其他土地利用贡献的温室气体排放量占总排放量的22%,为第三大碳源[1]。同时,农业又是一个巨大的碳汇系统,是固碳增汇的重要领域[2]。因此发展低碳农业,充分运用和提升农业固碳功能,是减排的关键途径和重要突破口,对缓解全球气候变化至关重要[34]

    2020年9月,中国在第75届联合国大会一般性辩论上宣布,中国二氧化碳(CO2)排放量力争于2030年前达到峰值,努力争取2060年前实现碳中和。现阶段中国农业二氧化碳排放量占当量排放总量的5%以上[5],各地区农业生产仍然面临同质化严重、碳排放偏高及绿色程度不足等问题,难以满足国内外市场对低碳环保、高品质农产品日益增长的需求[6]。同时,国际绿色贸易壁垒愈演愈烈,出口产品很可能将面临被征收“碳关税”进而推高成本,长远来看,势必会削弱中国农产品出口的竞争力和议价权。

    因此,发展低碳农业迫在眉睫。这不仅需要加快农业低碳技术的研发与普及应用,还需要推进农产品碳足迹、碳标识的实施。碳足迹的概念基于生态足迹[4,7]。根据ISO 14067—2018《温室气体-产品碳足迹-量化要求及指南》,产品碳足迹是基于生命周期法(life cycle assessment,LCA)评估得到的一个产品体系中对温室气体排放和清除的总和,以二氧化碳当量表示[8]。全生命周期包括原材料获取和预处理、生产、分销和储存、使用、废弃与回收等阶段。碳标识是一种环境标志,由碳足迹衍化而来,以标签的形式展现产品全生命周期温室气体排放量[910],目的是传达产品对温室效应产生的影响,以提升环保意识,引导低碳选择和消费[11],通常以单位产品质量的二氧化碳当量表示。加强农产品碳足迹研究和管理,建立和实施农产品碳标识制度,对于缓解全球变暖、促进可持续发展、实现碳达峰和碳中和(“双碳”)目标可起到关键作用[2]。一是明晰农产品全生命周期各环节的碳排放,精准减碳;二是可促进农业收入模式创新,为乡村绿色振兴注入新活力与思路;三是积累本地化排放因子数据,提高碳排放核算结果的精准性和国际认可度,从而提升国际市场竞争力。

    本研究梳理了农产品碳足迹、碳标识的实施探索,着重分析了农产品碳标识实施困境,并讨论了农产品碳标识应用推广的主要路径,以期为该领域的相关研究和工作提供有益参考。

    • 1990年代初,WACKERNAGEL等[12]提出了“生态足迹”概念,用于评估人类为了维持自身生活方式和经济发展而消耗的自然资源,以及容纳废弃物所需要的土地和水域面积,衡量人类活动对自然环境造成的压力。碳足迹作为生态足迹的一个分支,于2003年由英国提出[4, 7],随后于2007年,英国率先推出第1批包括食品、日用品在内的碳标识产品,成为全球最早实行产品碳标识制度的国家。次年,英国标准协会发布了全球首个产品碳足迹方法标准PAS 2050—2008《商品和服务在生命周期内的温室气体排放评价规范》。随后,日本、美国、加拿大、韩国等12个国家及地区也制定了适用本国的碳足迹、碳标识制度及相关标准规范。2018年,国际标准化组织(ISO)为统一产品碳足迹评价标准规范,发布ISO 14067—2018《温室气体-产品碳足迹-量化要求及指南》,是国际公认用于量化产品碳足迹的国际标准化组织标准。

      中国碳足迹、碳标识工作起步较晚,但近年来已经引起高度重视。2023和2024年,中国相继发布了《关于加快建立产品碳足迹管理体系的意见》和《关于建立碳足迹管理体系的实施方案》,从制定产品碳足迹核算标准、构建产品碳足迹因子数据库、建立产品碳足迹标识认证制度、推动国际衔接等方面,提出了碳足迹管理体系建设路线图。

    • 2021年,法国通过了在产品上添加“碳排放分数”标签的修正法案,成为首个将产品碳标识写入法律文本的国家。但目前国际上大部分包含农产品的碳标识制度的实施仍为非强制性,如2011年日本试行农产品碳标识制度,韩国的低碳标签,美国、加拿大等国家的非政府组织和私营部门发起的自愿性碳标识计划等。

      中国尚未形成农产品碳标识制度,碳足迹核算方面仅出台了团体标准《种植业农产品与农加工产品碳足迹量化与评价导则》,碳标识实施则是以地方探索实践为主。如2021年,浙江省杭州市临安区太湖源镇“天目水果笋”碳标识成为全国首枚初级农产品碳标识,且当地结合数字公证技术生成数字化证书,对“天目水果笋”的低碳环保经营状况全程溯源[13]。2023年12月,四川蒲江爱媛橙通过采用水电、有机肥等方式降碳,成为全国橙类水果首个加贴碳标识的农产品,其“从摇篮到大门”(cradle to gate)即包括原材料获取和生产阶段的碳足迹为0.295 kg·个−1,比普通橙碳足迹(0.500 kg·个−1)少近一半。此外,海南白沙绿茶、江苏响水西兰花、浙江西湖龙井、四川耙耙柑、江苏岔东大米等也相继推出碳标识。

    • 农产品碳足迹能显示农产品整个生命周期的碳排放,明晰不同地区、不同作物、不同环节对全球气候变化的贡献,例如有研究表明:对于小麦、玉米等作物,肥料施用导致的氧化亚氮(N2O)排放及灌溉耗电是主要的温室气体排放源,对于水稻,稻田甲烷(CH4)则是主要排放源[4, 1415]。因此,为了减少碳排放,国内外均已有基于碳足迹分析推动农业降碳的研究,并提出了包括如规范并削减农药、化肥及农膜等农业投入品及能源的消耗,运用更绿色高效的种植生产技术方式,更新更先进的生产设备,采用保护性耕作方法与增加有机肥料施用等一系列举措[1516]。进一步探究农产品碳足迹随时间演变的趋势、空间分布特性和组成异同,可以因地制宜,为各地定制更切合实际、易于执行和落地的减排措施,并指导优化农业生产的区域布局[4]。同时,农业龙头企业还可以通过自身影响力,引导和推动上游农资投入品生产企业,以及下游农产品加工企业协同减碳,带动整条产业链低碳发展。

    • 2022年,中国提出要研发应用减碳增汇型农业技术,探索建立碳汇产品价值实现机制。开展农产品碳足迹、碳标识工作,可以通过碳溢价、碳金融、碳交易3个方面将农产品固碳增汇的生态价值进行量化、交易及变现[13]。碳溢价方面,碳标识既能吸引具有绿色消费意愿的消费者[11],也能满足政府以及有减碳责任的企业、大型活动等的采购需求,赋予农产品碳价值附加;碳金融方面,碳标识可以成为开展绿色低碳生产的农业生产者获得金融扶持的重要采信依据,并开发适宜的碳金融工具;碳交易方面,碳标识能够核定出农产品的减排固碳量,通过参与农业碳汇交易获得收益。

    • 开展农产品碳足迹、碳标识实践也是展示企业低碳生产实力和社会责任的重要窗口,有助于提升企业形象和农产品的市场竞争力。有研究表明:农产品碳标识不仅可以有效地帮助消费者区分高碳产品与低碳产品,还能够调动消费者的绿色消费意识,促进消费者选购绿色低碳的产品[17]。同时,消费者的选购行为也能够直接反馈到企业及销售商[11],推动生产者低碳发展并开展碳足迹、碳标识工作以及农业绿色低碳转型。另一方面,随着国际绿色贸易壁垒进程的加快,碳排放量高的农产品的出口成本将明显提高,很有可能显著削弱中国农产品原有的低成本价格优势,降低在国际贸易中的主动权和掌控力[18]。此外,由于缺少公认的本地化碳排放因子,出口时不得不采用默认的高限值碳排放因子,进一步增加碳关税负担。因此,通过农产品碳足迹、碳标识的实施,积累本地化的排放因子数据,能够提高碳排放核算结果的精准性和国际认可度,从而提升国际市场竞争力及议价权。

      近2年各地均在积极探索实施农产品碳标识,但中国“大国小农”的基本国情和“条块分割”的行政管理体制,决定了农产品碳标识制度不能完全依赖于市场力量和消费者驱动,而政府顶层指导的不足,导致了农产品碳标识在实施过程中仍存在较大的困境。

    • 按照生命周期评估方法,农产品碳足迹包括农资等投入品的生产、运输,农产品生产、加工,农产品分销存储运输,农产品使用和废弃等全生命周期排放的温室气体(图1) [4, 19]

      Figure 1.  Boundary of carbon footprint accounting for agricultural products

      尽管目前国际上有较权威的ISO 14067和PAS 2050标准,但它们并没有详细到特定行业如农业[11]。目前,国内也尚未出台足够权威的农产品碳足迹核算国家标准和行业标准等,难以统一核算边界和方法,从而导致国内不同学者核算的农产品碳足迹结果差异较大。

      为更好对比以往的研究,本研究以水稻为例,搜索了近年来国内已发表的核算碳足迹的研究文章,结果发现:目前大多数农产品核算,重点关注上游和生产环节的碳排放[19],主要包括农资生产和使用过程中所导致的间接温室气体排放,农田机械作业消耗的能源产生的间接温室气体排放,以及农产品种植过程中的直接温室气体排放[20],而覆盖全生命周期的核算较为少见[21]。因此,本研究选取其中核算间接排放和直接排放的文章共10余篇,梳理碳足迹核算结果如表1所示。可知:最小为1 495.7 kg·hm−2 [22],最大达13 894.4 kg·hm−2 [23],相差近10倍,造成差异的原因主要是核算边界、数据来源、地区、时间等不一致。由于直接排放受到生产方式以及秸秆处理的影响,目前很多研究采用了改良的种植模式如使用绿肥、“稻萍”共生等,且未考虑秸秆处理。为更好对比结果,表1尽量选择常规生产方式且不考虑秸秆处理。

      地区 时间 单位面积碳足迹
      范围/(kg·hm−2)
      平均值/
      (kg·hm−2)
      核算边界 数据来源 参考文献
      浙江 2004—2014,2020 2 056.0~2 114.6 2 085.3 间接排放 统计数据 [22, 28]
      安徽 2004—2014,2019,2020 2 056.0~3 397.6 2 485.1 间接排放 统计数据、调研 [22, 2829]
      福建 2004—2014,2019,2020 1 500.0~1 657.4 1 578.7 间接排放 统计数据、试验 [22, 28, 30]
      2019 2 827.3~3 706.9 3 154.8 直接+间接排放 试验
      广东 2018,2020 1 815.2~2 555.0 2 119.9 间接排放 统计数据、试验 [20, 22]
      2018 11 921.0 11 921.0 直接+间接排放 试验
      广西 2020 2 057.7 2 057.7 间接排放 统计数据 [22]
      海南 2004—2014,2020 1 495.7~1 500.0 1 497.9 间接排放 统计数据 [22, 28]
      湖北 2020,2021 1 623.2~2 445.7 1 994.7 间接排放 统计数据、试验 [22, 31]
      2021 8 633.7~11 329.2 9 874.8 直接+间接排放 试验
      湖南 2020,2023 1 675.3~2 415.9 1 955.2 间接排放 统计数据、调研 [2224, 32]
      2015,2017 8 464.4~13 894.4 10 503.1 直接+间接排放 调研
      江苏 2018 1 838.0 1 838.0 间接排放 试验、调研 [20, 25]
      2015,2018 5 414.0~5 777.0 5 595.5 直接+间接排放
      江西 2018,2020,2023 2 246.0~2 415.9 2 305.4 间接排放 统计数据、调研 [20, 22, 24, 32]
      2017,2018 8 464.4~10 406.2 9 295.8 直接+间接排放 调研
      辽宁 2022 1 723.0~2 712.0 2 263.3 间接排放 调研 [33]
      2022 7 128.0~10 527.0 9 256.3 直接+间接排放

      Table 1.  Carbon footprint for rice production

      图2所示:直接排放的甲烷、氧化亚氮等温室气体远超过间接排放,其中甲烷的排放约占直接和间接总排放的66%[2425]。同时,秸秆处理及碳固定部分的核算也鲜少被考虑[14, 20, 23]。然而有研究表明:秸秆焚烧排放比例对碳足迹的贡献平均高达18%[14]。同样,农业土壤有较强的碳封存能力,土壤碳库容量约为大气碳库的3倍,生物碳库的4倍,每年的碳库存可能抵消全球化石燃料排放量的5%~15%[26],因此固碳部分的贡献也不应被忽略[3, 27]

      Figure 2.  Carbon footprint for rice production

    • 准确核算农产品碳足迹需要对农产品进行全生命周期跟踪,并精确量化各个阶段的碳排放,对数据的完整性、准确性、可溯源都有很高的要求,这也是目前核算农产品碳足迹时面临的一大难题。国内目前核算农产品碳足迹主要有2种数据来源:一是《农产品成本收益资料汇编》等统计数据,二是调研、试验数据。前者虽然易于获得,但往往与个体的实际情况存在一定的差异,且无法反映生产方式和技术的绿色特征或先进水平[14]。由于农业生产者建立碳排放管理相关制度的难度太大,因此,难以通过调研、试验获取涉碳实景数据,准确性也不高。一方面是涉及上游供应链的碳排放数据难以溯源,运输过程的碳排放数据难以获取;另一方面是直接排放、秸秆处理、碳固定部分的碳足迹所需数据较复杂,难以核算,目前主要是通过气相色谱仪等仪器分析采集的气体样品测算直接排放[25, 2829, 31],通过测算耕层土壤有机碳储量测算碳固定[20]等,但受到研究设备和条件的限制,监测精度和数据可靠性可能不足[2829],难以大批量和大规模推广。

      由于数据收集难度大,需使用背景数据库,包括上游供应链的碳排放数据、直接排放系数、土壤有机碳固定系数、秸秆焚烧排放系数等,但目前国内还缺少与实际生产行为相匹配的本地化数据库[14]。若参考以往研究或全国平均数据设置排放系数,由于气候、水文等地理条件,以及种植习惯、生产技术等方面的差异,排放系数的准确性和权威性都有待提升[34]。若采用国际上较为通用的Gabi、Ecoinvent等数据库,可能会导致碳足迹核算结果缺乏本地性且被高估[4]。有研究表明:使用Ecoinvent的排放因子核算水稻碳足迹,比使用中国产品全生命周期温室气体排放系数库(China Products Carbon Footprint Factors Database, CPCD)的排放因子,提高17.52%[35]

      农产品碳足迹核算是碳标识实施的基础,然而目前国内农产品碳足迹核算标准不健全、碳排放数据基础单薄,导致了农产品碳足迹核算结果的不完整和不一致,可比性也很低。这不仅会造成碳标识实施困境,还可能会进一步对农业低碳发展造成影响[26]。生产者方面,难以对照国内外先进水平,比较识别可能的降碳环节,从而进行针对性减碳;同时可能会因不同市场或客户的要求进行多次不同的碳足迹核算,不仅造成资源浪费,还会导致同一产品有不同的碳足迹,使消费者产生困惑;出口时结果也难以得到国际认可,从而不得不依赖国外相关机构以及对方设定的碳排放因子高限值,进一步增加碳关税负担。消费者方面,难以准确判断哪些产品更低碳,从而进行绿色低碳消费,影响了市场的公平竞争。认证机构方面,认证难度加大,结果的准确性、可靠性和公信力都难以保证,容易进一步造成市场混乱。政府方面,在制定相关激励机制并开展监管工作时,难以确保公平性,可能会错误引导资金等的资源流向。

    • 从主观认识与意识角度来看,中国农业经营主体仍以小农户为主,可能会更关注经济效益,而对气候变化和低碳转型的重要性,以及碳关税等国际绿色贸易壁垒造成的影响缺乏明确和深刻的认识,从而不愿或者不主动开展碳足迹、碳标识工作。从投入产出比角度来看,农业生产者本身往往利润不高,而开展碳排放管理、挖掘农产品减碳潜力、人员培训、碳足迹核算、碳标识认证等环节,意味着企业需要在人力、物力和财力上做出额外投入;同时,为实现农产品生产低碳转型,往往需要在生产技术上做改进[1516],并从种植模式、施肥、灌溉到包装、运输等各个环节都更精细化,也需要不低的投入。从农产品产量来看,加贴碳标识的农产品往往对产品质量有更高的要求,可能会导致单位产量降低,如浙江嘉兴阳光玫瑰葡萄,原本产量可达37.5 t·hm−2,但加贴碳标识后,要求只能产出22.5 t·hm−2,以保证葡萄吸收足够养分,品质更稳定。这些都很可能在短期内给农业生产者带来一定的经济压力。

    • 近年来国内外有关低碳农产品消费意愿的研究均在增加,结论比较相似。消费者虽然有一定的支付意愿,但支付水平都相对有限,主要是因为比起质量、口感、健康(如有机标签)等因素,碳标识的支付意愿更依赖利他心理[3637],且碳标识尚未大规模实施,消费者也可能很难评估其益处[38]。有研究对浙江杭州、绍兴、台州的全年龄段,不同学历、职业、收入的居民发放低碳大米消费意愿相关问卷。通过对185份有效问卷的分析,结果表明:尽管当前消费者对环境保护持积极态度,但对农产品碳标识的认知较低,有近80.00%的居民并不了解具体含义,很可能会影响支付意愿和支付溢价水平;同时,虽然92.97%的居民愿意购买加贴碳标识农产品,但是8.70%的居民不愿意额外支付,44.90%愿意支付10.00%以下的溢价水平[39]。还有研究对上海的低碳蔬菜消费意愿进行了分析,共回收857份问卷。结果表明:有93.30%的居民愿意购买加贴碳标识蔬菜,但77.30%的居民愿意支付10.00%以下的溢价水平,平均支付意愿为溢价6.00%[40]

      从这些研究可以看出:虽然消费者的低碳消费意愿较高,但支付溢价水平有限,而由于成本及产品质量提升,加贴碳标识后,农产品价格普遍上涨,如四川蒲江爱媛橙价格至少上涨20.0%,浙江嘉兴阳光玫瑰葡萄也上涨了25.0%,均已超过消费者的支付意愿。同时,需要注意的是,这2项研究的受访者为浙江和上海居民,经济条件稍好,理念相对超前,因此若在全国层面来看,形势可能不容乐观。

    • 从顶层设计来看,目前国家层面农产品碳足迹和碳标识的相关标准、制度尚未建立健全,导致企业在开展农产品碳足迹核算时缺乏统一指导,难度较大,结果的可信度也有待提高;第三方机构开展碳标识认证时也缺乏统一规范和监管,碳标识的社会认可度和公信力也有限,将造成消费者对碳标识缺乏信任而降低购买意愿,更难以得到国际认可并应用。

      从要素保障来看,虽然中国碳足迹管理相关文件提出要在财政、金融、市场等方面出台碳足迹、碳标识推广的相关政策,激励企业开展产品碳足迹碳标识工作,但目前相关机制和具体实施细则尚在积极推进建立中,还需要时间落实,制度保障方面还有一定的缺失。早在2013年,日本农林水产省牵头推出“J-Credit Scheme”,将减少和吸收的温室气体量作为信贷依据,农林水产企业、森林拥有者等可以出售或捐赠碳资产,或将其用于抵消其他生产活动的温室气体排放[13]。截至目前已注册1 134件项目,核准1 042 万t二氧化碳。中国也亟需加快相关制度进程。

    • 在农产品碳足迹核算边界方面,政府应结合实际情况,制定与国际标准相协调的农产品碳足迹核算标准,统一规定核算的边界、方法、数据质量要求等,不仅要将直接排放、秸秆处理和碳固定部分纳入核算边界,还需要核算分销存储、使用、废弃与回收阶段的碳足迹,覆盖全生命周期。

      在农产品碳足迹核算数据基础方面,政府应构建健全的农业碳排放监测(monitoring)、报告(reporting)、核实(verification)体系(MRV)[13],确保数据的准确性和可靠性。综合考虑不同区域之间水文、土壤以及农产品种类等的差异,发布专门面向农产品的本地化背景数据库,依法合规收集整理相关的实景数据资源,保障数据可核算、可核查、可溯源,并通过试验测算、汇总结果数据、建立模型等方式,设置并不断迭代本地化的直接排放系数、土壤有机碳固定系数、秸秆焚烧排放系数、供应链数据[41]等,覆盖农业生产上中下游全链条,为农业生产者开展碳足迹核算、碳标识认证提供能力基础。

      此外,尽管目前不同国家和地区在农产品碳足迹核算、碳标识认证等方面的标准可能存在一定差异[42],但长期来看,国际化和普适性已经成为未来发展的共识[43]。因此,不管是在核算边界、方法还是数据方面,都应积极参与国际相关交流与合作,推动核算能力向国际先进水平靠拢,在标准规范制(修)订、方法学研究、数据库建设等方面的衔接互认,从而推动数据及核算结果的互信互认,避免农产品碳排放在出口时被高估,从而提升农产品的出口竞争力及议价权。

    • 需要政府来主导[7],正视农户动力不足、能力不足的客观事实,加强市场监管、生态环境、农业农村等各主管部门之间的协同合作[15],共同推动农产品碳足迹、碳标识的实施。

      加快出台碳标识认证及监管制度,在全国层面规范碳标识认证管理办法,明确适用范围、标识式样、认证流程、管理要求等,提高公信力、社会接受度和市场认可度[13]。同时,加强对认证机构的备案管理,并进一步培育国内的认证机构,获得国际认可,以提供合规、高效、安全、低成本的碳标识认证服务。

      完善要素支持制度[44],健全多元投入资金保障机制,推进农业生态价值的实现,真正将农业生产者节能降碳的努力转换为实际的利益,充分调动主动性和积极性。对于开展碳足迹碳标识管理的农业生产者,完善相关激励措施和资金政策,缓解可能面临的经济压力。积极引导银行等金融机构持续推出和农产品碳足迹、碳标识相挂钩的绿色金融产品,确保碳标识成为有效的碳信用担保[13]。也可在前期推广碳标识时,对购买贴标农产品的消费者予以适当补贴。此外,针对农产品生态价值的商业转化模式还有待探索与创新,根据中国农业大国的特色,构建基于农产品碳标识的农业碳资产管理体系,并强化监管力度与治理效能,确保农业生产者的减排固碳行动能有效转化为真正的经济效益[13]

    • 鼓励大型商超、电商采销碳标识农产品,还可设置专门的低碳专区,提供更便捷的购物体验。普及低碳知识,提升农业生产者低碳生产的意识,同时,设计更醒目和易于理解的农产品碳标识[38, 45],并大力宣传,营造良好的低碳消费氛围,逐渐养成低碳生活理念和习惯,反过来促进生产者通过低碳生产和使用碳标识提高市场竞争力,形成良性循环。

      提供技术支持及培训,助力农业生产者开展碳足迹管理工作,对照国内外先进水平精准降碳。加快低碳农业技术的研发和推广,并在数智融合的趋势下,引入大数据、物联网、人工智能等先进技术[7],开发提供技术升级、能源替代、管理优化等服务。

Reference (45)

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return