• Energy Research
• 2021-2025close
• 12. Responsible consumption close
• 14. Life underwater close
• Chinese Academy of Sciences close

Bioenergy is considered a sustainable substitute to fossil-fuel resources and the development of a prudent combination of renewable and innovative conversion technologies are essential for the valorization and effective conversion of biowaste to value-added commodities. Here, a negative pressure-induced carbonization process was proposed for the valorization of lignin-enriched biowaste precursor to bio-oil and environmental materials (biochar) at various temperatures. The high heating values (HHV) of the as-prepared biochars from the lignin enriched precursor under negative pressure (low-medium vacuum) were within 25.9-31.5 MJ/kg, which matched satisfactorily to the commercial charcoal. Whereas, the bio-oils produced from the lignin enriched precursor under vacuum conditions was a blend of complex aromatic and straight-chain hydro-carbons, including aldehyde, ketone, phenol, and furans, exhibiting ability as potential heating-oil with HHV within 21.2-28.2 MJ/kg. Moreover, the biochars produced under vacuum environments at higher temperature showed greater stability (22.5-35.9%) than those produced under N2 atmosphere.

This product used a machine learning approach (feed-forward neural network - FFNN) to reconstruct a high-resolution (0.25° × 0.25°) ocean subsurface (1–2000 m) salinity dataset for the period 1993–2018 by merging in situ salinity profile observations with high-resolution (0.25° × 0.25°) satellite remote sensing altimetry absolute dynamic topography (ADT), sea surface temperature (SST), sea surface wind (SSW) field data, and a coarse resolution (1° × 1°) gridded salinity product. The new 0.25° × 0.25° reconstruction shows more realistic spatial signals in the regions with strong mesoscale variations, e.g., the Gulf Stream, Kuroshio, and Antarctic Circumpolar Current regions, than the 1° × 1° resolution product, indicating the efficiency of the machine learning approach in bringing satellite observations together with in situ observations. The large-scale salinity patterns from 0.25° × 0.25° data are consistent with the 1° × 1°gridded salinity field, suggesting the persistence of the large-scale signals in the high-resolution reconstruction.Time Range:1993.01-2018.12Region:GlobalLongitude:180°W~180°ELatitude:70°S~70°NParameters:SalinityHorizontal Resolution:0.25° × 0.25°Vertical Resolution:41 levels (1-2000 m)Temporal Resolution:monthlyStorage Format:netcdf This product used a machine learning approach (feed-forward neural network - FFNN) to reconstruct a high-resolution (0.25° × 0.25°) ocean subsurface (1–2000 m) salinity dataset for the period 1993–2018 by merging in situ salinity profile observations with high-resolution (0.25° × 0.25°) satellite remote sensing altimetry absolute dynamic topography (ADT), sea surface temperature (SST), sea surface wind (SSW) field data, and a coarse resolution (1° × 1°) gridded salinity product. The new 0.25° × 0.25° reconstruction shows more realistic spatial signals in the regions with strong mesoscale variations, e.g., the Gulf Stream, Kuroshio, and Antarctic Circumpolar Current regions, than the 1° × 1° resolution product, indicating the efficiency of the machine learning approach in bringing satellite observations together with in situ observations. The large-scale salinity patterns from 0.25° × 0.25° data are consistent with the 1° × 1°gridded salinity field, suggesting the persistence of the large-scale signals in the high-resolution reconstruction.Time Range:1993.01-2018.12Region:GlobalLongitude:180°W~180°ELatitude:70°S~70°NParameters:SalinityHorizontal Resolution:0.25° × 0.25°Vertical Resolution:41 levels (1-2000 m)Temporal Resolution:monthlyStorage Format:netcdf

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).

The macroalgal industry is expanding, and the quest for novel ingredients to improve and develop innovative products is crucial. Consumers are increasingly looking for natural-derived ingredients in cosmetic products that have been proven to be effective and safe. Macroalgae-derived compounds have growing popularity in skincare products as they are natural, abundant, biocompatible, and renewable. Due to their high biomass yields, rapid growth rates, and cultivation process, they are gaining widespread recognition as potentially sustainable resources better suited for biorefinery processes. This review demonstrates macroalgae metabolites and their industrial applications in moisturizers, anti-aging, skin whitening, hair, and oral care products. These chemicals can be obtained in combination with energy products to increase the value of macroalgae from an industrial perspective with a zero-waste approach by linking multiple refineries. The key challenges, bottlenecks, and future perspectives in the operation and outlook of macroalgal biorefineries were also discussed.

Abstract Biomass, as a renewable and sustainable energy resource, can be converted into environmentally friendly and practically valuable biofuels and chemical materials via pyrolysis. However, the process optimization and pyrolysis efficiency are restricted by the limited perception of the complicated mechanisms and kinetics for biomass pyrolysis. Here, to establish an in-depth mechanism model for biomass pyrolysis, we presented a novel investigation for the thermal evolutions and pyrolysis kinetics of the functional groups in peanut shell matrix by using in-situ Fourier transform infrared spectrometry (in-situ FTIR) and thermogravimetric analysis-Fourier transform infrared spectrometry-mass spectrometry (TG-FTIR-MS). The in-situ FTIR spectrum deconvolution for the solid matrix was innovatively introduced to identify and quantify the real-time evolution and thermal dynamics of the functional groups during peanut shell pyrolysis. The result for the first time proposed that the pyrolysis mechanisms of total OH at 20–380 °C, aliphatic C-Hn groups at 20–500 °C, C O groups at 260–500 °C, and C–O groups at 300–500 °C were dominant by diffusion and order-based chemical reactions. The TG-FTIR-MS analysis was conducted for the online monitoring of the released volatiles and gases, the amounts of which were in the sequence of C O > CO2 > aliphatic C–O-(H) > C–O-(C) in esters > aromatics > H2O > phenolic hydroxyl > aliphatic hydrocarbons > CO. The study established a novel methodology to evaluate the biomass pyrolysis mechanisms at the molecular level, which provided valuable information for developing advanced pyrolysis techniques on a large scale for sustainable ecosystem.

AbstractAlthough the process of microbial degradation of coal to produce biomethane has got much attention from many research works, the products profiles of coal at the initial stage of methanogenic bioconversion are not clear yet. In this study, five coal‐degrading bacterial strains (CD1, CD10, CD20, CD24, and CD25) from a methanogenic community were isolated and identified. Among them, CD1 and CD24 belong to Paenibacillus sp., CD10 and CD20 belong to Bacillus sp., and CD25 belongs to Stenotrophomonas sp. After biotreatment of lignite and bituminous coal, the kinds of newly produced compounds were 33 and 45, respectively. Metabolomics analysis showed that a large number of alkane compounds and heterocyclic aromatic compounds were produced after degradation of bituminous coal and lignite by isolated bacteria, and most of the compounds had been produced in a hydroxylated or acylated manner, indicating that the initial microbial treatment enhanced the bioavailability of coal. Some alkaloids and biosurfactants were also detected in the aforementioned products, such as glycerophosphocholine, proveratrol A, proveratrol B, surfactin, etc. These microbial metabolites may play an important role in solubilization during the degradation of coal. This study added to the understanding of the complicated metabolic process of methanogenic coal bioconversion and enabled effective production of biomethane with appropriate metabolic strategies.

Half the population of China live in coastal zones where 70% of large cities are also located. Intensive human activities pose significant environmental and ecological hazards to these cities that are already vulnerable to natural hazards and climate change. The sustainable development of coastal cities is thus both a national and international issue. Rongcheng is a typical coastal city in east China. It is a national marine ranch demonstration area that is subjected to multi-stressors from human activities and climate change. The dominant economic sectors include aquaculture and fisheries, agriculture, shipping and tourism. A multitude of resulting pressures come mainly from intensified human activities, such as intensive aquaculture, overfishing, industrial pollutants, agricultural runoff, land reclamation and port expansion. In addition, Rongcheng is also facing exogenic pressures from extreme climate events such as intensified storms, storm surges, droughts and sea ice. A growing awareness of these problems brought together a trans-disciplinary group from local government, research institutions, local practitioners and coastal representatives to jointly explore and co-design adaptive coastal management options. In this transdisciplinary study, a social-ecological analysis based on a combination of the Systems Approach Framework and the Drivers-Pressures-States-Impacts-Responses framework was used to analyze and formulate an adaptive management plan for the sustainability of Rongcheng. More than 40 stakeholders including government, companies, civil society and institutions participated in the study through questionnaires and on-site meetings. A statistical analysis of the results identified urgent issues impeding the sustainable development of Rongcheng. The issues identified were poorly regulated aquaculture, loss of shoreline, and the decline of seagrass and cultural heritage. The study identified management options and measures, some of which were adopted by the local government in a co-designed management plan. The measures included upgrading of aquaculture industry, habitat conservation and restoration, and the development of cultural tourism. Another outcome was the increased knowledge exchange between stakeholders to inform management, policy, and decision making, as well as raised awareness of vulnerability to natural hazards and climate change. The success of this case study provides a reference for the adaptive management of other coastal cities and their sustainable development in a changing climate.

An urgent demand for recycling spent lithium-ion batteries (LIBs) is expected in the forthcoming years due to the rapid growth of electrical vehicles (EV). To address these issues, various technologies such as the pyrometallurgical and hydrometallurgical method, as well as the newly developed in-situ roasting reduction (in-situ RR) method were proposed in recent studies. This article firstly provides a brief review on these emerging approaches. Based on the overview, a life cycle impact of these methods for recovering major component from one functional unit (FU) of 1 t spent EV LIBs was estimated. Our results showed that in-situ RR exhibited the lowest energy consumption and greenhouse gas (GHG) emissions of 4833 MJ FU−1 and 1525 kg CO2-eq FU−1, respectively, which only accounts for ~23% and ~64% of those for the hydrometallurgical method with citric acid leaching. The H2O2 production in the regeneration phase mainly contributed the overall impact for in-situ RR. The transportation distance for spent EV LIBs created a great hurdle to the reduction of the life cycle impact if the feedstock was transported by a 3.5–7.5 t lorry. We therefore suggest further optimization of the spatial distribution of the recycling facilities and reduction in the utilization of chemicals.