Carbon footprint of cotton production in China: Composition, spatiotemporal changes and driving factors

Structural characteristics and drivers of greenhouse gas emissions at county-level and long-time scales: A case study of the Anji County, China

To achieve carbon neutrality, the Chinese government needs to gain a comprehensive understanding of the sources and drivers of greenhouse gas (GHG) emissions, particularly at the county level. Anji County in eastern China is a typical example of an industrial transformation from quarrying to a low-carbon economy. This study analyzed the decoupling types and structural characteristics of GHG emissions and the driving factors of carbon dioxide (CO2) emissions in the Anji from 2006 to 2019, and explored the differences between county-level and provincial-level or city-level results. It was observed that energy-related activities are the main source of GHG emissions in Anji and that economic development is the driving factor behind the increasing CO2 emissions. However, industrial transformation and upgradation coupled with the alternative use of clean energy limit the growth of GHG emissions. This study details the GHG emissions of county during the industrial transformation stage and provides corresponding policy recommendations for county governments.

Rapid detection of multi-scale cotton pests based on lightweight GBW-YOLOv5 model

BACKGROUND

Pest infestation is one of the primary causes of decreased cotton yield and quality. Rapid and accurate identification of cotton pest categories is essential for producers to implement effective and expeditious control measures. Existing multi-scale cotton pest detection technology still suffers from poor accuracy and rapidity of detection. This study proposed the pruned GBW-YOLOv5 (Ghost-BiFPN-WIoU You Only Look Once version 5), a novel model for the rapid detection of cotton pests.

RESULTS

The detection performance of the pruned GBW-YOLOv5 model for cotton pests was evaluated based on the self-built cotton pest dataset. In comparison with the original YOLOv5 model, the pruned GBW-YOLOv5 model demonstrated significant reductions in complexity, size, and parameters by 68.4%, 66.7%, and 68.2%, respectively. Remarkably, the mean average precision (mAP) decreased by a mere 3.8%. The pruned GBW-YOLOv5 model outperformed other classic object detection models, achieving an outstanding detection speed of 114.9 FPS.

CONCLUSION

The methodology proposed by our research enabled rapid and accurate identification of cotton pests, laying a solid foundation for the implementation of precise pest control measures. The pruned GBW-YOLOv5 model provided theoretical research and technical support for detecting cotton pests under field conditions. © 2024 Society of Chemical Industry.

Green, chemical-free, and high-yielding extraction of nanocellulose from waste cotton fabric enabled by electron beam irradiation

Recycling and high-value reutilization of waste cotton fabrics (WCFs) has attracted a widespread concern. One potential solution is to extract nanocellulose. Sulfuric acid hydrolysis is a conventional method for the production of nanocellulose with high negative charge from WCFs. However, the recycling and disposal of chemicals in nanocellulose production, along with low yields, remain significant challenges. Consequently, there is a pressing need for a sustainable method to produce nanocellulose at higher yield without the use of chemicals. Herein, we propose a green, sustainable and chemical-free method to extract nanocellulose from WCFs. The nanocellulose displayed a rod-like shape with a length of 50-300 nm, a large aspect ratio of 18.4 ± 2 and the highest yield of up to 89.9 %. The combined short-time and efficient two-step process, involving electron beam irradiation (EBI) and high-pressure homogenization (HPH), offers a simple and efficient alternative approach with a low environmental impact, to extract nanocellulose. EBI induced a noticeable degradation in WCFs and HPH exfoliated cellulose to nano-size with high uniformity via mechanical forces. The as-prepared nanocellulose exhibits excellent emulsifying ability as the Pickering emulsion emulsifier. This work provides a facile and efficient approach for nanocellulose fabrication as well as a sustainable way for recycle and reutilization of the waste cotton fabrics.

Spatial autocorrelation and driving factors of carbon emission density of crop production in China

Mitigating carbon emissions from crop production is essential for addressing global warming. At a macro-level, existing studies have often relied on the calculation of carbon emission intensity of crop production to understand comparable carbon effects between regions. However, this approach obscures the differences in crop planting scale and natural attributes across regions, leaving room for improvement in the methods and scope of analysis. To extend the existing research, we proposed an idea for calculating the carbon emission density of crop production based on planting area. Additionally, we developed an analytical framework for driving factors of carbon emission density of crop production from a spatial interaction perspective. The provincial carbon emission density of crop production in mainland China between 2000 and 2020 was calculated, and spatial econometric models were utilized to investigate the spatial autocorrelation and driving factors. The results indicate that the national average carbon emission density of crop production was 1.462 t/hm2 annually. Over 21 years, the carbon emission density of agricultural materials, rice cultivation, soil management, and straw burning evolved from 0.384 to 0.470 t/hm2, 0.409 to 0.367 t/hm2, 0.171 to 0.169 t/hm2, and 0.317 to 0.448 t/hm2, respectively. The global Moran's index indicated a positive spatial autocorrelation of carbon emission density of crop production and the subdivided carbon sources among provinces. Regarding direct effects, an increase in the proportion of paddy fields in cropland composition and irrigation efficiency would significantly promote the carbon emission density, while factors such as cropland area, multiple cropping, agricultural personnel numbers, departmental proportion, and disaster degree would decrease the local carbon emission density. Certain factors, such as cropland area and agricultural disasters, had a spatial spillover effect on carbon emission density between provinces. The study suggests harnessing key drivers and spatial spillover effects to achieve regional low-carbon crop production.

Multi-objective optimization of saline water irrigation in arid oasis regions: Integrating water-saving, salinity control, yield enhancement, and CO2 emission reduction for sustainable cotton production

Brackish water stands as a promising alternative to mitigate freshwater scarcity in arid regions. However, its application poses potential threats to agricultural sustainability. There is a need to establish a clear understanding of the economic and ecological benefits. We conducted a two-year (2021-2022) field experiment to investigate the effects of four different irrigation water salinity levels on soil electrical conductivity, cotton yield, water use efficiency, CO2 emissions, and carbon sequestration. The salinity levels were designated as CK (0.85 g L-1), S1 (3 g L-1), S2 (5 g L-1), and S3 (8 g L-1). Results indicated that using irrigation water with high salinity (≥5 g L-1) led to the accumulation of salt in the soil, and a decrease in plant biomass and seed cotton yield. Compared to CK, the S3 treatment decreased by 18.72 % and 20.10 % in the respective two years. Interestingly, using brackish water (3 L-1 and 5 g L-1) decreased the rate and cumulative CO2 emissions, and increased the carbon emission efficiency and carbon sequestration by 0.098-0.094 kg kg-1 and 871-1859 kg ha-1 in 2021, 0.098-0.094 kg kg-1 and 617-1995 kg ha-1 in 2022, respectively. To comprehensively evaluate the tradeoff between economic and ecological benefits, we employed the TOPSIS method, and S1 was identified as the optimal irrigation salinity. Through fitting analysis, the most suitable irrigation salinity levels for 2021 and 2022 were determined as 3.52 g L-1 and 3.31 g L-1, respectively. From the perspective of water conservation, salinity management, yield improvement, and reduction of CO2 emissions, it is feasible to utilize brackish water for irrigation purposes, as long as the salinity does not exceed 3.52 g L-1 (first year) and 3.31 g L-1 (second year).

Trends and driving forces of agricultural carbon emissions: A case study of Anhui, China

To facilitate accurate prediction and empirical research on regional agricultural carbon emissions, this paper uses the LLE-PSO-XGBoost carbon emission model, which combines the Local Linear Embedding (LLE), Particle Swarm Algorithm (PSO) and Extreme Gradient Boosting Algorithm (XGBoost), to forecast regional agricultural carbon emissions in Anhui Province under different scenarios. The results show that the regional agricultural carbon emissions in Anhui Province generally show an upward and then downward trend during 2000-2021, and the regional agricultural carbon emissions in Anhui Province in 2030 are expected to fluctuate between 11,342,100 tones and 14,445,700 tones under five different set scenarios. The projections of regional agricultural carbon emissions can play an important role in supporting the development of local regional agriculture, helping to guide the input and policy guidance of local rural low-carbon agriculture and promoting the development of rural areas towards a resource-saving and environment-friendly society.

Transforming agrifood systems in a win-win for health and environment: evidence from organic rice-duck coculture

BACKGROUND

Rice-duck coculture is an ecological agricultural mode; however, the nutritional and environmental benefits of transforming from conventional rice monoculture to rice-duck coculture are unknown. Based on survey data and the life-cycle assessment approach, this study conducted a carbon footprint evaluation of conventional rice monoculture (CR), organic rice monoculture (OR), and organic rice-duck coculture (ORD) using different functional units.

RESULTS

The carbon footprint per hectare of ORD (7842 ± 284 kg CO₂ eq ha^-1 ) was slightly lower than that of CR (7905 ± 412 kg CO₂ eq ha^-1 ), while higher than that of OR (7786 ± 235 kg CO₂ eq ha^-1 ). Although the rice yield of ORD was slightly lower than that of CR, its nutrient density unit (NDU) did not decrease significantly due to the additional duck yield. Thus, the carbon footprint per NDU of ORD was significantly lower than that of OR by 24.3% (P < 0.05) and was 5.8% higher than that of CR, but this was not statistically significant. Due to the higher economic profits of ORD, its unit of carbon footprint per economic profit was significantly reduced (by 47.1-75.7%) compared with the other two farming modes, while the net ecosystem economic budget was significantly increased by 98.5-341.9% (P < 0.05).

CONCLUSION

Transforming from a rice monoculture to a coculture system will contribute to a win-win situation for human health and environmental sustainability. This study highlighted the abundant nutritional output function of the rice-duck coculture and analyzed the urgency and necessity of transitioning from traditional agriculture to ecological agriculture from the production and consumption perspectives. © 2022 Society of Chemical Industry.

Spatial-temporal evolution of pumped hydro energy storage potential on the Qinghai-Tibet Plateau and its future trend under global warming

Global warming has brought extensive and far-reaching impacts on human life and production. A pumped hydro energy storage contributes to the large-scale development of renewable energy and serves as an important measure to mitigate climate change. Despite considerable efforts in estimating the potential of the pumped hydro energy storage, research gaps in response to global warming remain. In this regard, this study conducts a novel assessment of the pumped hydro energy storage's potential from a dynamic perspective, taking the Qinghai-Tibet Plateau as the study area. The spatiotemporal evolution of the pumped hydro energy storage's potential over the past few decades (the 1970s-2017) is analyzed, and its response to precipitation is identified innovatively. On this basis, the trend in the future period is further predicted for the first time, which is divided into near, short, medium, and long terms. Results show that the pumped hydro energy storage potential has a generally upward but not monotonic trend, decreasing from the 1970s to 1995 and then rising more dramatically, with slopes of 5548.5 ± 69.2 GWhyr^-1 and -238.1 ± 90.4 GWhyr^-1. In the majority (68.6 %) of lake basins (68.6 %), changes in precipitation positively contribute to the pumped hydro energy storage potential, resulting in a noticeable growth in the future. Under the representative concentration pathway of 8.5, the mean potential density is projected to rise by 23.4 %, 25.2 %, 28.3 %, and 30.6 % in the near, short, medium, and long terms, respectively. This result indicates that high-intensity greenhouse gas emissions under this scenario will lead to a greater potential for the pumped hydro energy storage in the future.

Current recycling strategies and high-value utilization of waste cotton

The rapid development of the textile industry and improvement of people's living standards have led to the production of cotton textile and simultaneously increased the production of textile wastes. Cotton is one of the most common textile materials, and the waste cotton accounts for 24% of the total textile waste. To effectively manage the waste, recycling and reusing waste cotton are common practices to reduce global waste production. This paper summarizes the characteristics of waste cotton and high-value products derived from waste cotton (e.g., yarns, composite reinforcements, regenerated cellulose fibers, cellulose nanocrystals, adsorptive materials, flexible electronic devices, and biofuels) via mechanical, chemical, and biological recycling methods. The advantages and disadvantages of making high-value products from waste cotton are summarized and discussed. New technologies and products for recycling waste cotton are proposed, providing a guideline and direction for merchants and researchers. This review paper can shed light on converting textile wastes other than cotton (e.g., bast, silk, wool, and synthetic fibers) into value-added products.

Sensitivity analysis of greenhouse gas emissions at farm level: case study of grain and cash crops

Sensitivity analysis is useful to downgrade/upgrade the number of inputs to limit greenhouse emissions and enhance crop yield. The primary data from the 300 rice (grain crop) and 300 cotton (cash crop) farmers were gathered in face-to-face interviews by applying a multistage random sampling technique using a well-structured pretested questionnaire. Energy use efficiency was estimated with data envelopment analysis (DEA) model, and a second-stage regression analysis was conducted by applying Cobb-Douglas production function to evaluate the influencing factors affecting. The results exhibit that chemical fertilizers, diesel fuel and water for irrigation are the major energy inputs that are accounted to be 15,721.55, 10,787.50 and 6411.08 MJ ha-1 for rice production, while for cotton diesel fuel, chemical fertilizer and water for irrigation were calculated to be 13,860.94, 12,691.10 and 4456.34 MJ ha-1, respectively. Total GHGs emissions were found to be 920.69 and 954.71 kg CO2eq ha-1 from rice and cotton productions, respectively. Energy use efficiency (1.33 and 1.53), specific energy (11.03 and 7.69 MJ ha-1), energy productivity (0.09 and 0.13 kg MJ-1) and energy gained (14,497.85 and 20,047.56 MJ ha-1) for rice and cotton crop, respectively. Moreover, the results obtained through the second-stage regression analysis revealed that excessive application of fertilizer had a negative impact on the yield of rice and cotton, while farm machinery, diesel fuel and biocides had a positive effect. We hope that these findings could help in the management of the energy budget that we believe will reduce the high emissions of GHGs to address the growing environmental hazards.

Spatial and Temporal Characteristics and Drivers of Agricultural Carbon Emissions in Jiangsu Province, China

Scientific measurement and analysis of the spatial and temporal distribution characteristics of agricultural carbon emissions (ACEs) and the influencing factors are important prerequisites for the formulation of reasonable ACEs reduction policies. Compared with previous studies, this paper fully considers the heterogeneity of rice carbon emission coefficients, measures and analyzes the spatial and temporal characteristics of ACEs in Jiangsu Province from three carbon sources, including agricultural land use, rice cultivation, and livestock and poultry breeding, and explores spatial clustering patterns and driving factors, which can provide a reference for agricultural low-carbon production. The results indicate that from 2005 to 2020, Jiangsu's ACEs showed a decreasing trend, with an average annual decrease of 0.32%, while agricultural carbon emission density (ACED) showed an increasing trend, with an average annual increase of 0.16%. The area with the highest values for ACEs is concentrated in the northern region of Jiangsu, while the areas with the highest values for ACED are distributed in the southern region. The spatial clustering characteristics of ACEs have been strengthening. The "H-H" agglomeration is mainly concentrated in Lianyungang and Suqian, while the "L-L" agglomeration is concentrated in Zhenjiang, Changzhou, and Wuxi. Each 1% change in rural population, economic development level, agricultural technology factors, agricultural industry structure, urbanization level, rural investment, and per capita disposable income of farmers causes changes of 0.112%, -0.127%, -0.116%, 0.192%, -0.110%, -0.114%, and -0.123% in Jiangsu's ACEs, respectively. To promote carbon emission reduction in agriculture in Jiangsu Province, we should actively promote the development of regional synergistic carbon reduction, accelerate the construction of new urbanization, and guide the coordinated development of agriculture, forestry, animal husbandry, and fisheries industries.