Elsevier

Agricultural Systems

Volume 196, February 2022, 103347
Agricultural Systems

Towards sustainable circular agriculture: An integrated optimization framework for crop-livestock-biogas-crop recycling system management under uncertainty

https://doi.org/10.1016/j.agsy.2021.103347Get rights and content

Highlights

  • Agricultural resources and wastes are managed in the crop-livestock-biogas-crop recycling system.

  • Cross-sectoral energy-water-food nexus optimization framework is constructed.

  • Efficient and environmental-friendly water and land resources allocation strategies are generated.

  • Global warming mitigation potential of the recycling system is assessed.

  • Interrelations, uncertainties, and risks are handled in the recycling system.

Abstract

Context

Growing socio-economic development and population poses unprecedented challenges for agriculture in meeting increasing demand of food, water, and energy. Rethinking the future agricultural production to simultaneously safeguard resources security and regulate environmental pollution is essential. Circular agriculture opens up a new path for the high-efficiency and environmental-friendly production. An integrated energy-water-food nexus optimization approach for managing agricultural resources and wastes in line with the principles of sustainable circular agriculture management is lacking.

Objective

This study therefore proposes an integrated uncertain optimization model to manage agricultural crop-livestock-biogas-crop recycling systems from a cross-sectoral energy-water-food nexus perspective in the changing environment. The aims are to: (1) balance objectives of input reduction, output promotion, ensuring equity, and global warming mitigation; (2) generate sustainable resources allocation strategies based on efficiency and recycling; (3) assess the global warming mitigation potential of the recycling systems from a life cycle perspective; and (4) deal with interactions, complexities, uncertainties, and risks existed in the recycling systems.

Methods

The proposed model framework is based on a stochastic multi-objective programming, while triangular fuzzy numbers, fuzzy credibility constrained programming, Stewart model, analytic hierarchy process, and opportunity carbon footprint are integrated to enhance its practicability and feasibility. The model is verified through a real-world case study in the Zhanghe Irrigation District, Hubei province, China.

Results and conclusions

Results show that optimal water and land resources allocation solutions are more efficient than current strategies, with water consumption per unit area decreasing by 13.63% and rice production per unit area improving by 22.06%. Paddy field and biogas leakage are two of the largest sources of GHG emission, calling for agronomic and engineering measures to improve farmland management and biogas generation technology. Livestock breeding contributes 10% of the total GHG emission, along with generating 76% of the total biogas, indicating the great significance of manure recycle. Overall, 4.26 × 108 kg CO2 is reduced in the recycling system, contributed by chemical fertilizer reduction, agricultural wastes recycle, and non-renewable energy replacement.

Significance

The study offers a potential nexus optimization approach for sustainable management of agricultural recycling systems from a holistic perspective. It can be used as a general model to extend to other agricultural systems suffering from similar resources and environmental crisis.

Introduction

Food security, population growth, resource depletion, energy crisis, climate change, and environmental pollution have placed unprecedented pressure on agricultural development (Burian et al., 2019; Geng et al., 2019). Agriculture is a chief source of food and waste, as well as greenhouse gas (GHG) emission, responsible for around 13% of global anthropogenic emissions (IPCC, 2013). In this context, we need to rethink the future agricultural development to safeguard food security and relieve environmental pressure on agricultural production simultaneously. The traditional linear “resource-product-use-dispose” production pattern has been under scrutiny as an underlying cause that encourages unrestrained growth of resource demand, waste, and pollution (Hass et al., 2020; Thakker and Bakshi, 2021). As highlighted in many studies (Xu et al., 2020; Atinkut et al., 2020; Gao et al., 2019; Antoniou et al., 2019), gradual transition from a linear to a circular approach is a promising avenue towards sustainability in a way that integrating efficient resources utilization with multilevel-recycling and reusing agricultural wastes.

Given the high expectations for a circular future, scholars have dedicated on investigating and understanding the basic concept and theoretical connotation of circular agriculture (CA), assessing various CA modes in different scales, and tracing the progress of CA towards sustainability (Wu et al., 2015; Trendov, 2017; Moraga et al., 2019). For example, Fan et al., 2018a, Fan et al., 2018b analyzed different circular agriculture models and explores the environmental impacts using Life Cycle Assessment method in Xingyuan, Fuqing, Fujian. Results showed that a longer industrial chain of circular agriculture is not better. Barros et al. (2020) conducted a systematic literature review on circular practices in agro-industrial sector, encouraging the implementation or increment of circular practices application in agricultural sector. Li et al. (2021) applied entropy method to develop an evaluation indicators system for circular agriculture, and evaluated the key driven factors. They found that agricultural technology and per capita water resources were positively related to system performance. Meanwhile, several specific CA patterns in line with local characteristics have been employed, such as the “Pig-Biogas-Fruit” mode in south China (Song et al., 2014) and the “Four-in-one” mode in north China (Zeng et al., 2007). However, seeking for efficient and circular resources management strategies in the circular agricultural systems is more practical and promising towards sustainability. Above concern leads to the necessity of optimization modelling, which has proven an effective way to manage resources (Suo et al., 2018; Thomas et al., 2018; Ji et al., 2020; Li et al., 2022).

Evidently, no optimization modelling framework has been constructed aiming at sustainable management of agricultural recycling systems. This study bridges this gap. As the demand for agricultural wastes recycle and cleaner renewable energy production growing rapidly, a crop-livestock-biogas-crop recycling (CLBCR) system fosters opportunities for managing resources in a more sustainable manner. Hereinto, primary resources are reused, as well as wastes are recycled from crop production subsystem to livestock breeding subsystem to biogas production subsystem and finally back to crop production subsystem. Thus, this study explores optimal resources management strategies and examines performance of the optimization model in the CLBCR system. The integrated optimization model addresses three major questions. (1) How to quantify interactions, synergies and tradeoffs among elements, dimensions, and sectors? (2) How to estimate the cross-sectoral environmental impacts? (3) How to handle complexities, uncertainties, and risks owing to changing environment? We also discuss to what extend can the CLBCR system contribute to global warming mitigation and renewable energy strategies, comparing with traditional agricultural systems.

Firstly, managing the CLBCR system is a compound process, hereinto water, food, and energy resources are highly interwoven, crop production, livestock breeding, and biogas production are interrelated, and the targets associated with social, economic, resource, and environmental dimensions are conflict. Specifically, water is used for food production, forage processing, and biogas production. Energy is consumed during the process of food production, including irrigation, drainage, seeding, tillage, and harvest, in turn, crop straw is used for biogas generation. To comprehensively quantify above interdependencies, a novel cross-sectoral energy-water-food (CEWF) nexus approach is desired. Additionally, sustainable resources management seeks for a balance among multiple objectives, such as reducing resources input, improving system output, regulating environmental impacts, and ensuring allocation equity. Obviously, these objectives are contradictory in practice. Pursuing only one-fold aspect may influence other aspects and cause serious consequences (Liu et al., 2018). Therefore, multi-objective programming (Ren et al., 2019; Mosleh et al., 2017) is introduced to quantify connections among the CEWF nexus and reconcile conflict sustainable goals in the CLBCR system.

The second major issue is how to estimate the cross-sectoral environmental impacts. The CLBCR system is not only the vital producer of food, livestock, and biogas, but also a large contributor to anthropogenic GHG emission, such as CO2, N2O, and CH4 (FAO, 2014). Taking the crop production subsystem as an example, fertilizer application, pesticide application, electricity utilization, and agricultural machinery produce CO2. The N2O is emitted from fertilizer application, nitrogen volatilization, and nitrogen leaching. The CH4 released from paddy field also contributes to potential global climate warming. Accuracy measurement of the GHG emission from the CLBCR system lays the foundation for environment-friendly management and global warming mitigation. Thus, carbon footprint (Zhang et al., 2017) is introduced to evaluate the GHG emission in the whole life cycle of the CLBCR system from a systematic perspective. Furthermore, the aim of the CLBCR system as a sustainability strategy should not get out of sight: can it actually mitigate the social-economic and environmental pressures and in what way such a recycling system contributes to GHG emission mitigation? Therefore, the opportunity carbon footprint is introduced to assess GHG emission mitigation potential of the CLBCR system, based on the concept of opportunity cost in economics (Gao, 2014).

Thirdly, unpredictable natural conditions, inaccurate information collection, and subjective decision-making preferences compound the challenges of resources management and add further risks (Regulwar and Gurav, 2011; Zhang and Guo, 2017), leading to the necessity of uncertain optimization techniques. Fuzzy mathematical programming is available for addressing vague information and subjective decision judgements, expressed as fuzzy sets with membership function (Zadeh, 1965). In this study, triangular fuzzy number a˜=a1a2a3 is used for addressing uncertain socio-economic parameters and available water supply. In addition, violation of constraints usually occurs under such a vague environment, fuzzy credibility-constrained programming is needed to tradeoff system objectives and violation risk (Liu and Iwamura, 1998). By integrating stochastic expected value model Liu and Liu, 2002 and multi-objective programming, stochastic multi-objective programming is applied for tackling randomness of water inflow levels, as well as reconciling conflict objectives among different spheres. Analytic hierarchy process method (Saaty, 1990a, Saaty, 1990b) is used for determining weights of objectives before solving the multi-objective programming. Besides, Gini coefficient (Gini, 1921) and Stewart model (Stewart et al., 1976) are incorporated for quantifying inequity of resources allocation and reflecting the response of crop yield to water shortage in each growth stage, respectively.

Finally, an integrated optimization modelling framework is developed for sustainable management of the CLBCR system from a CEWF nexus perspective, by incorporating carbon footprint assessment, opportunity carbon footprint, fuzzy numbers, fuzzy credibility-constrained programming, Gini coefficient, and Stewart model into the stochastic multi-objective programming. The integrated model framework aims to seek for coordinated resources allocation solutions considering resources input reduction, agricultural wastes recycle, global warming mitigation and socio-economic security, consequently promote sustainable circular agricultural development. Afterwards, the feasibility and applicability of the optimization modelling framework is tested in the Zhanghe Irrigation District, central China. Optimal results can be helpful for exploring high-efficiency and environmental-friendly strategies for circular agriculture, and provide managerial insights into tradeoffs among resources allocation, resources security, and global warming mitigation.

Section snippets

Description of the crop-livestock-biogas-crop recycling system

The crop-livestock-biogas-crop recycling (CLBCR) system contains three subsystems: crop production subsystem, livestock breeding subsystem, and biogas production subsystem. The system boundary and material flows of the CLBCR system is described in Fig. 1. Cyclic utilization of agricultural wastes links each subsystem and extends the traditional agricultural systems towards a new phase of high-efficiency recycle. Specifically, primary waste, such as straw, bran, and husks produced during the

Characterization of study region

The developed model was applied to a real-world case study to demonstrate its feasibility and applicability. The study area contains Jingmen city, Jingzhou district of Jingzhou city, and Dangyang city in Hubei province, north of the Yangtze River Basin, central China. These three areas constitutes the biggest irrigation district in Hubei province, namely the Zhanghe Irrigation District (ZID), with a designed irrigation acreage of 173, 700 ha. Salient features of ZID include high average annual

Optimization results and comparison

By solving the developed model in the optimization software, optimal resources allocation results under different scenarios are obtained. Fig. 3 depicts not only the contribution of each water source on rice production but also water scarcity index during each period in each subarea under each hydrological year when λ = 0.8. In detail, precipitation satisfied the maximum water requirement of rice in wet year, contributed 66% water supply for rice production in normal year, and occupied 20% of

Discussion

This study is devoted to sustainable circular agriculture management in agricultural recycling systems with optimization model framework and nexus approach. Academically, it boosts the circular agriculture development by introducing operational research method in the recycling systems. From a practical point of view, it helps managers gain insights int systematic, circular, and sustainable decisions from various perspectives. Detailed significance, advantages, drawbacks, and further efforts of

Conclusion

An integrated fuzzy credibility-constrained stochastic multi-objective programming model is established for cross-sectoral resources allocation in the crop-livestock-biogas-crop recycling (CLBCR) system under uncertainty. The study offers a potential optimization-based approach for sustainable circular agriculture management from a holistic perspective. The main innovations and contributions can be drawn as (1) developing an integrated inexact optimization modelling framework for sustainable

Supplementary data

Supplementary material

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This research was supported by the National Key R&D Program of China (No. 2017YFC0403201) and National Natural Science Foundation of China (No. 51621061).

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