Curbing global solid waste emissions toward net-zero warming futures

Enhancing Methane Production in Anaerobic Digestion of Food Waste Using Co-Pyrolysis Biochar Derived from Digestate and Rice Straw

Anaerobic digestion (AD) is a preferred method for food waste (FW) treatment due to its sustainability and potential for production of renewable bioenergy. However, the accumulation of volatile fatty acids (VFAs) and ammonia often destabilizes the AD process, and managing the digestate byproduct poses additional challenges. This study investigates the use of co-pyrolysis biochar synthesized from digestate and rice straw (DRB) to enhance methane production and AD efficiency. DRB addition increased cumulative methane yield by 37.1%, improved VFA conversion efficiency, and achieved a 42.3% higher NH3-N-removal rate compared to the control group. The COD-removal rate was 68.7% throughout the process. Microbial analysis revealed that DRB selectively enriched Fastidiosipila and Methanosarcina, promoting direct interspecies electron transfer (DIET) and methane yield. These findings highlight DRB's potential to enhance AD efficiency and support closed-loop resource utilization.

Polymerization of beneficial plant height QTLs to develop superior lines which can achieving hybrid performance levels

Heterosis, a key technology in modern commercial maize breeding, is limited by the narrow genetic base which hinders breeders from developing superior hybrid varieties. By integrating big data and functional genomics technologies, it becomes possible to create new super maize inbred lines that resemble hybrid varieties through the aggregation of multiple QTL parental advantage loci. In this study, we utilized a combination of resequencing and field selfing selection methods to develop three pyramiding QTL lines (PQLs) (PQL4, 6, and 7), each containing 15, 12, and 12 QTL loci respectively. Among the three PQLs, PQL6 (266.78 cm/119.39 cm) demonstrated hybrid-like performance comparable to the hybrid (276.96 cm/127.02 cm) (P < 0.05). Testcross between PQL6 and the parental lines revealed that PQL6 had accumulated and fixed advanced parent alleles for superior traits in plant and ear height. The significant increase in PQL6 plant height primarily resulted from the aggregation of two major effective QTL (qEH2-1 and qEH8-1 on chromosomes 2 and 8), indicating that the aggregation of major effective QTL is a key selection indicator. Furthermore, PQL6 exhibited slow vegetative growth but experienced a rapid height increase during the reproductive stage, particularly in the 1-2 weeks before flowering, when its growth rate accelerated and surpassed that of the hybrid varieties. Our study explored the time period and key parameter indicators for molecular breeding of maize, providing a theoretical concept and practices for further complex multi-trait design and aggregation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-025-01546-4.

Global natural and anthropogenic methane emissions with approaches, potentials, economic costs, and social benefits of reductions: Review and outlook

The increase in atmospheric methane (CH4) level directly contributes to approximately one-fifth of global mean temperature rise since preindustrial era, only next to CO2. Global anthropogenic CH4 emissions has augmented by nearly three-fifths during the past five decades; due to climate change, natural CH4 emissions are plausibly projected to increase in the foreseeable future. Thereby, examining and projecting long-term natural and anthropogenic CH4 emissions and sinks are imperative. According to peer-reviewed literatures as information sources for this compendium, we recapitulate natural and anthropogenic CH4 emissions, summarize available abatement approaches and their mitigation potentials, and investigate and encapsulate economic costs and social benefits of reductions. We list current challenges in realizing CH4 emissions reductions and suggest possible technical pathways for future mitigation.

Optimizing the greenhouse gas emissions of waste transfer and transport: An integration of life cycle assessment and vehicle routing problem

This study presents a comprehensive analysis of greenhouse gas (GHG) emissions associated with waste transfer and transport, incorporating derived leachate treatment-a factor often overlooked in existing research. Employing an integration model of life cycle assessment and a vehicle routing problem (VRP) methods, we evaluated the GHG reduction potential of waste transfer and transport system. Two Chinese counties with different topographies and demographics were selected, yielding 80 scenarios that factored in waste source separation as well as vehicle capacity, energy sources, and routes. The functional unit (FU) is transferring and transporting 1 tonne waste and treating derived leachate. The GHG emissions varied from 12 to 39 kg CO2 equivalent per FU. Waste source separation emerged as the most impactful mitigation strategy, not only for the studied system but for an integrated waste management system. Followings are the use of larger capacity vehicles and electrification of the vehicles. These insights are instrumental for policymakers and stakeholders in optimizing waste management systems to reduce GHG emissions.

Improved medical waste plasma gasification modelling based on implicit knowledge-guided interpretable machine learning

Ensuring the interpretability of machine learning models in chemical engineering remains challenging due to inherent limitations and data quality issues, hindering their reliable application. In this study, a qualitatively implicit knowledge-guided machine learning framework is proposed to improve plasma gasification modelling. Starting with a pre-trained machine learning model, parameters are further optimized by integrating the heuristic algorithm to minimize the data fitting errors and resolving implicit monotonic inconsistencies. The latter is comprehensively quantified through Monte Carlo simulations. This framework is adaptive to different machine learning techniques, exemplified by artificial neural network (ANN) and support vector machine (SVM) in this study. Validated by a case study on plasma gasification, the results reveal that the improved models achieve better generalizability and scientific interpretability in predicting syngas quality. Specifically, for ANN, the root mean square error (RMSE) and knowledge-based error (KE) reduce by 36.44% and 83.22%, respectively, while SVM displays a decrease of 2.58% in RMSE and a remarkable 100% in KE. Importantly, the improved models successfully capture all desired implicit monotonicity relationships between syngas quality and feedstock characteristics/operating parameters, addressing a limitation that traditional machine learning struggles with.

Unlocking the significant worldwide potential of better waste and resource management for climate mitigation: with particular focus on the Global South

Numbers do matter; the Intergovernmental Panel on Climate Change (IPCC)'s 2010 data that the waste sector is responsible for just 3% of global greenhouse gas (GHG) emissions has led to the misperception that solid waste management (SWM) has little to contribute to climate mitigation. Global efforts to control methane emissions and divert organic waste from landfills had already reduced direct emissions. But end-of-pipe SWM has also been evolving into more circular waste and resource management, with indirect GHG savings from the 3Rs (reduce, reuse, recycle) which IPCC accounts for elsewhere in the economy. The evidence compiled here on both direct emissions and indirect savings demonstrates with high confidence that better waste and resource management can make a significant contribution to climate mitigation, and must form a core part of every country's nationally determined contribution. Even the most advanced countries can still achieve much from the 3Rs. In the Global South, the challenge of extending waste collection to all and stopping open dumping and burning (sustainable development goal 11.6.1), essential to improve public health, can be turned into a huge opportunity. Moving early to divert waste from landfill by separation at source and collecting clean organic and dry recycling fractions, will mitigate global GHG emissions, slash ocean plastics and create decent livelihoods. But this can only happen with targeted climate, plastics and extended producer responsibility finance; and help to local communities to help themselves.

Unlocking the potential of biogas systems for energy production and climate solutions in rural communities

On-site conversion of organic waste into biogas to satisfy consumer energy demand has the potential to realize energy equality and mitigate climate change reliably. However, existing methods ignore either real-time full supply or methane escape when supply and demand are mismatched. Here, we show an improved design of community biogas production and distribution system to overcome these and achieve full co-benefits in developing economies. We take five existing systems as empirical examples. Mechanisms of synergistic adjusting out-of-step biogas flow rates on both the plant-side and user-side are defined to obtain consumption-to-production ratios of close to 1, such that biogas demand of rural inhabitants can be met. Furthermore, carbon mitigation and its viability under universal prevailing climates are illustrated. Coupled with manure management optimization, Chinese national deployment of the proposed system would contribute a 3.77% reduction towards meeting its global 1.5 °C target. Additionally, fulfilling others' energy demands has considerable decarbonization potential.

Decreasing Greenhouse Gas Emissions from the Municipal Solid Waste Sector in Chinese Cites

Municipal solid waste (MSW) management systems play a crucial role in greenhouse gas (GHG) emissions in China. Although the government has implemented many policies to improve the MSW management system, the impact of these improvements on city-level GHG emission reduction remains largely unexplored. This study conducted a comprehensive analysis of both direct and downstream GHG emissions from the MSW sector, encompassing sanitary landfill, dump, incineration, and biological treatment, across 352 Chinese cities from 2001 to 2021 by adopting inventory methods recommended by the Intergovernmental Panel on Climate Change (IPCC). The results reveal that (1) GHG emissions from the MSW sector in China peaked at 70.6 Tg of CO2 equiv in 2018, followed by a significant decline to 47.6 Tg of CO2 equiv in 2021, (2) cities with the highest GHG emission reduction benefits in the MSW sector were historical emission hotspots over the past 2 decades, and (3) with the potential achievement of zero-landfilling policy by 2030, an additional reduction of 203.7 Tg of CO2 equiv is projected, with the emission reduction focus toward cities in South China (21.9%), Northeast China (17.8%), and Southwest China (17.3%). This study highlights that, even without explicit emission reduction targets for the MSW sector, the improvements of this sector have significantly reduced GHG emissions in China.

Harnessing Atomically Dispersed Cobalt for the Reductive Catalytic Fractionation of Lignocellulose

The reductive catalytic fractionation (RCF) of lignocellulose, considering lignin valorization at design time, has demonstrated the entire utilization of all lignocellulose components; however, such processes always require catalysts based on precious metals or high-loaded nonprecious metals. Herein, the study develops an ultra-low loaded, atomically dispersed cobalt catalyst, which displays an exceptional performance in the RCF of lignocellulose. An approximately theoretical maximum yield of phenolic monomers (48.3 wt.%) from lignin is realized, rivaling precious metal catalysts. High selectivity toward 4-propyl-substituted guaiacol/syringol facilitates their purification and follows syntheses of highly adhesive polyesters. Lignin nanoparticles (LNPs) are generated by simple treatment of the obtained phenolic dimers and oligomers. RCF-resulted carbohydrate pulp are more obedient to enzymatic hydrolysis. Experimental studies on lignin model compounds reveal the concerted cleavage of Cα-O and Cβ-O pathway for the rupture of β-O-4 structure. Overall, the approach involves valorizing products derived from lignin biopolymer, providing the opportunity for the comprehensive utilization of all components within lignocellulose.

Solid waste, a lever for decarbonization

Reducing methane emissions from solid waste is already technically possible.