Forecasting carbon prices in China's pilot carbon market: A multi-source information approach with conditional generative adversarial networks.

In recent years, the Chinese government has actively pursued the implementation of its 'dual-carbon' strategy, concurrently establishing a national carbon emissions trading market. Accurate carbon price forecasts have become essential for policymakers and investors involved in related initiatives. Nevertheless, influenced by the interaction of various information sources, carbon trading prices exhibit non-linear and non-stationary characteristics, posing challenges for accurate prediction. Current research, centered around deep learning models, predominantly emphasizes intricate network structures, optimisation algorithms, and data decomposition. However, these models face a developmental bottleneck in extracting carbon price features and efficiently leveraging multi-source information. Consequently, novel ideas and methodologies are imperative. This study focuses on the Hubei and Guangdong regional carbon markets as research subjects. It develops a prediction framework based on a generative adversarial network model to capture the time-series change characteristics of carbon trading prices and the condition matrix. First, a generator prediction model is used to obtain the input matrix features and extract the time series features through a complex network to predict the carbon price data at the next moment using a fully connected layer. Second, a discriminator is utilised to distinguish between the actual values and the predicted values. The generator and the discriminator undergo continuous iterative training and alternate optimisation. This process aims to bring the generated prediction distributions closer to the actual sample data, resulting in more accurate final predictions. The empirical results convincingly show that the proposed model achieves unparalleled forecasting precision in both markets. The proposed model demonstrates the lowest MAE (0.804 and 0.839), lowest MAPE (0.023 and 0.018), lowest RMSE (1.174 and 1.383), and highest R2 (0.971 and 0.989) across both markets, indicating superior predictive accuracy. Additionally, the proposed model consistently outshines traditional forecasting approaches across one-step, five-step, and ten-step forecasts, affirming its robustness and universal applicability in modelling carbon trading price series. The findings suggest that this study can aid policymakers in optimizing the carbon pricing system. Furthermore, it offers a reference for policymakers to comprehensively leverage external factors, such as regulating traditional energy prices, leveraging international carbon market experiences, and monitoring economic dynamics. This comprehensive strategy can streamline the exploration and management of carbon price fluctuations, ultimately strengthening the carbon market's risk control system.

Washing antimony and arsenic from agricultural soil with eco-friendly organic acids and the relevant bioavailability assessment.

Antimony (Sb) and arsenic (As) contamination in agricultural soil poses human health risks through agricultural products. Soil washing with degradable low molecular weight organic acids (LMWOAs) is an eco-friendly strategy to remediate agricultural soils. In this study, three eco-friendly LMWOAs, oxalic acid (OA), tartaric acid (TA), and citric acid (CA), were used to treat Sb and As co-contaminated agricultural soil from Xikuangshan mine area. The OA, TA, and CA washed out 18.4, 16.8, and 26.6% of Sb and 15.3, 19.9, and 23.8% of As from the agricultural soil, with CA being the most efficient reagent for the soil washing. These organic acids also led to pH decline and macronutrients losses. Fraction analysis using a sequential extraction procedure showed that the three organic acids targeted and decreased the specifically sorbed (F2) (by 19.3-37.6% and 2.41-23.5%), amorphous iron oxide associated (F3) (by 49.1-61.2% and 51.2-70.2%), and crystallized iron oxide associated (F4) (by 12.3-26.0% and 26.1-29.1%) Sb and As. The leachability of Sb and As, as well as their concentrations and bioconcentration factor (BCF) in vegetables reduced due to the soil washing. It demonstrated that the bioavailability of both the elements was decreased by the organic acids washing. The concentrations of Sb and As in typical vegetable species cultivated in CA washed soil were less than the threshold value for consumption safety, while those in OA and TA washed soils were still higher than the value, suggesting that only CA is a potential washing reagent in soil washing for Sb- and As-contaminated agricultural soil.

Sustainable Environmental Assessment of Waste-to-Energy Practices: Co-Pyrolysis of Food Waste and Discarded Meal Boxes.

The reuse of biomass waste is conducive to the recovery of resources and can solve the pollution problem caused by incineration and landfill. For this reason, the thermogravimetric analyzer (TGA) was used to study the pyrolysis of the mushroom sticks (MS) and discarded meal boxes at different heating rates (10 °C·min-1, 20 °C·min-1, 30 °C·min-1). The statistical analysis showed that the factors of pyrolysis temperature and particle size had a greater effect, while the heating rate was significant. The TGA revealed that the maximum weight loss rate of the co-pyrolysis of MS and discarded meal boxes increased with the rise of the heating rate, the temperature at which the pyrolysis started and ended increased, and the thermal weight loss displayed a hysteresis phenomenon. By comparing the theoretical heat weight loss curves with the experimental curves, a synergistic effect of the co-pyrolysis process between MS and discarded meal boxes was demonstrated, and the co-pyrolysis process resulted in a reduction in the solid residue content of the products. The Coats-Redfern method was used to fit the pyrolysis process of MS and discarded meal boxes, which applied the first-order kinetic model to describe the main process of pyrolysis and obtained the reaction activation energy between 43 and 45 kJ·mol-1. The results indicated that co-pyrolysis of MS and discarded meal boxes could decrease the activation energy of the reaction, make the reaction easier, promote the degree of pyrolysis reaction, reduce the generation of pollutants, and provide a theoretical basis for the recycling and energy utilization of MS and discarded meal boxes.

Urban heat vulnerability: A dynamic assessment using multi-source data in coastal metropolis of Southeast China.

Extreme heat caused by global climate change has become a serious threat to the sustainable development of urban areas. Scientific assessment of the impacts of extreme heat on urban areas and in-depth knowledge of the cross-scale mechanisms of heat vulnerability forming in urban systems are expected to support policymakers and stakeholders in developing effective policies to mitigate the economic, social, and health risks. Based on the perspective of the human-environment system, this study constructed a conceptual framework and index system of "exposure-susceptibility-adaptive capacity" for urban heat vulnerability (UHV) and proposed its assessment methods. Taking Xiamen City, a coastal metropolis, as an example, spatial analysis and Geodetector were used to explore the spatial and temporal changes, spatial characteristics, and patterns of UHV under multiple external disturbances from natural to anthropological factors, and to reveal the main factors influencing UHV forming and spatial differentiation. Results showed that the exposure, susceptibility, adaptive capacity, and UHV in Xiamen City had a spatial structure of "coastal-offshore-inland". On the hot day, both the exposure and UHV showed a temporal pattern of "rising and then falling, peaking at 14:00" and a spatial pattern of "monsoonal-like" movement between coast and inland. Coastal zoning with favorable socioeconomic conditions had less magnitude of changes in UHV, where the stability of the urban system was more likely to be maintained. During the hot months, the high UHV areas were mainly distributed in the inland, while coastal areas showed low UHV levels. Further, coastal UHV was mainly dominated by "heat exposure", offshore by "comprehensive factors", and inland in the northern mountainous areas by "lack of adaptive capacity". Multi-scale urban adaptive capacity was confirmed to alter spatial distribution of exposure and reshape the spatial pattern of UHV. This study promotes the application of multi-scale vulnerability framework to disaster impact assessment, enriches the scientific knowledge of the urban system vulnerability, and provides scientific references for local targeted cooling policy development and extreme heat resilience building programs.

The Reinforcing Effect of Waste Corrugated Paper Fiber on Polylactic Acid.

To improve the recycle value of waste paper and promote circular economic development, waste corrugated paper fiber (WCPF) was used as a reinforcing agent to prepare waste corrugated paper fiber/polylactic acid (WCPF/PLA) composites via dichloromethane solvent which can be reused. The WCPF in the waste corrugated paper is extracted by beating in a Valli beating machine for different time lengths and grinding in a disc grinder. The effects of beating time and the content of WCPF on the microstructure, mechanical properties, thermal decomposition process, and crystallization properties of the WCPF/PLA composite were studied. The result shows that the WCPF can be well separated from each other and can be evenly dispersed in the PLA matrix. When 25 wt% WCPF which was beat for 30 min was used, the composite has the greatest improvement in tensile property. This study provides a new process for the recycling of waste paper in the application of polymer reinforcement. The research on waste paper fiber and degradable polymer composite is of great significance for reducing environmental pollutants and developing circular economy.

Determination of Arsenic Species in Ophiocordyceps sinensis from Major Habitats in China by HPLC-ICP-MS and the Edible Hazard Assessment.

This study sought to determine the concentration and distribution of arsenic (As) species in Ophiocordyceps sinensis (O. sinensis), and to assess its edible hazard for long term consumption. The total arsenic concentrations, measured through inductively coupled plasma mass spectrometry (ICP-MS), ranged from 4.00 mg/kg to 5.25 mg/kg. As determined by HPLC-ICP-MS, the most concerning arsenic species­AsB, MMAV, DMAV, AsV, and AsШ­were either not detected (MMAV and DMAV) or were detected as minor As species (AsB: 1.4⁻2.9%; AsV: 1.3⁻3.2%, and AsШ: 4.1⁻6.0%). The major components were a cluster of unknown organic As (uAs) compounds with AsШ, which accounted for 91.7⁻94.0% of the As content. Based on the H2O2 test and the chromatography behavior, it can be inferred that, the uAs might not be toxic organic As. Estimated daily intake (EDI), hazard quotient (HQ), and cancer risk (CR) caused by the total As content; the sum of inorganic As (iAs) and uAs, namely i+uAs; and iAs exposure from long term O. sinensis consumption were calculated and evaluated through equations from the US Environmental Protection Agency and the uncertainties were analyzed by Monte-Carlo Simulation (MCS). EDItotal As and EDIi+uAs are approximately ten times more than EDIiAs; HQtotalAs and HQi+uAs > 1 while HQiAs < 1; and CRtotal As and CRi+uAs > 1 × 10−4 while CRiAs < 1 × 10−4. Thus, if the uAs is non-toxic, there is no particular risk to local consumers and the carcinogenic risk is acceptable for consumption of O. sinensis because the concentration of toxic iAs is very low.

[Current status of bio-based materials industry in China].

In recent years, bio-based materials are becoming a new dominant industry leading the scientific and technological innovation, and economic development of the world. We reviewed the new development of bio-based materials industry in China, analyzed the entire market of bio-based materials products comprehensively, and also stated the industry status of bio-based chemicals, such as lactic acid, 1,3-propanediol, and succinic acid; biodegradable bio-based polymers, such as co-polyester of diacid and diol, polylactic acid, carbon dioxide based copolymer, polyhydroxyalknoates, polycaprolactone, and thermoplastic bio-based plastics; non-biodegradable bio-based polymers, such as bio-based polyamide, polytrimethylene terephthalate, bio-based polyurethane, and bio-based fibers.