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Allelochemicals sustained-release microspheres (ACs-SMs) exhibited great inhibition effect on algae, however, few studies have focused on ACs-SMs toxicity on invertebrate. In this study, the effects of single high-concentration ACs (15 mg/L, SH-ACs), repeated low-concentration ACs (3 × 5 mg/L, RL-ACs) and ACs-SMs containing 15 mg/L ACs exposure on the ingestion, incorporation, and digestion of Daphnia magna Straus (DS) were investigated by stable isotope

Efficient use of renewable energy is one of the critical measures to achieve carbon neutrality. Countries have introduced policies to put carbon neutrality on the agenda to achieve relatively zero emissions of greenhouse gases and to cope with the crisis brought about by global warming. This work analyzes the wave energy with high energy density and wide distribution based on understanding of various renewable energy sources. This study provides a wave energy prediction model for energy harvesting. At the same time, the Gated Recurrent Unit network (GRU), Bayesian optimization algorithm, and attention mechanism are introduced to improve the model's performance. Bayesian optimization methods are used to optimize hyperparameters throughout the model training, and attention mechanisms are used to assign different weights to features to increase the prediction accuracy. Finally, the 1-hour and 6-hour forecasts are made using the data from China's NJI and BSG observatories, and the system performance is analyzed. The results show that, compared with mainstream prediction algorithms, GRU based on Bayesian optimization and attention mechanism has the highest prediction accuracy, with the lowest MAE of 0.3686 and 0.8204, and the highest R2 of 0.9127 and 0.6436, respectively. Therefore, the prediction model proposed here can provide support and reference for the navigation of ships powered by wave energy. Export Date: 29 December 2022; Article; CODEN: APEND; 通讯地址: Lv, Z.; Extended Energy Big Data and Strategy Research Center, China; 电子邮件: lvzhihan@gmail.com; 基金资助详情: SKLMCPTS202103011; 基金资助详情: National Natural Science Foundation of China, NSFC, 61902203; 基金资助文本 1: Funding: This work was supported by the National Natural Science Foundation of China [grant number 61902203 ]; the open project of the Xinhua News Agency State Key Laboratory of Media Convergence Production Technology and System [grant number SKLMCPTS202103011 ].; 参考文献: Zhou, J., Zhang, Y., Zhang, Y., Parameters identification of photovoltaic models using a differential evolution algorithm based on elite and obsolete dynamic learning[J] (2022) Appl Energy, 314; Bi, H., Shang, W.L., Chen, Y., GIS aided sustainable urban road management with a unifying queueing and neural network model[J] (2021) Appl Energy, 291; Von Wald, G., Sundar, K., Sherwin, E., Optimal gas-electric energy system decarbonization planning[J] (2022) Adv Appl Energy, 6; 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For seismic stratigraphy, a key issue is distinguishing the characteristics of seismic reflections generated by geologic events with different scales, which in turn assists in sequence stratigraphic interpretation. Data-driven signal decomposition approaches, such as variational-mode decomposition (VMD) and multichannel VMD (MVMD), can use waveform similarity to decompose seismic data into several intrinsic mode functions (IMFs). Unfortunately, it is a hard task to define the number of IMFs. To overcome the shortcoming of previous works, we have constructed an enhanced MVMD and then developed a workflow to decompose seismic data. We first determined the relationship between the IMFs and structures with different scales. Then, we developed a method to set the number of IMFs using contraction operator mapping and scale-space representation. Finally, we developed a workflow and applied it to synthetic and field data to identify seismic sequence stratigraphy boundaries. Synthetic and field data examples indicate that our workflow preserves lateral continuity and precisely extracts IMFs caused by depositional sequences with different geologic scales, facilitating the interpretation of subtle depositional patterns.

Seismic acoustic-impedance (AI) inversion, which estimates the AI of the reservoir from seismic and other geophysical data, is a type of nonlinear inverse problem that faces the local minima issue during optimization. Without requiring an accurate initial model, global optimization methods have the ability to jump out of local minima and search for the optimal global solution. However, the low-efficiency nature of global optimization methods hinders their practical application, especially in large-scale AI inversion problems (AI inversion with a large number of traces). We have developed a new intelligent seismic AI inversion method based on global optimization and deep learning. In this method, global optimization is used to generate data sets for training a deep-learning network, and it is used to first accelerate and then surrogate global optimization. In other words, for large-scale seismic AI inversion, global optimization only inverts the AI model for a few traces, and the AI models of most traces are obtained by deep learning. The deep-learning architecture that we used to map from the seismic trace to its corresponding AI model is established based on U-Net. Because the time-consuming global optimization inversion procedure can be avoided for most traces, this method has a significant advantage over conventional global optimization methods in efficiency. To verify the effectiveness of our method, we compare its performance with the conventional global optimization method on 3D synthetic and field data examples. Compared to the conventional method, our method only needs approximately one-tenth of the computation time to build AI models with better accuracy.

This paper aims to discuss an environmental, social, and economic analysis of energy utilization of crop residues from life cycle perspectives in China. The methodologies employed to achieve this objective are environmental life cycle assessment (E-LCA), life cycle cost (LCC), and social life cycle assessment (S-LCA). Five scenarios are developed based on the conversion technologies and final bioenergy products. The system boundaries include crop residue collection, transportation, pre-treatment, and conversion process. The replaced amounts of energy are also taken into account in the E-LCA analysis. The functional unit is defined as 1 MJ of energy produced. Eight impact categories are considered besides climate change in E-LCA. The investment capital cost and salary cost are collected and compared in the life cycle of the scenarios. Three stakeholders and several subcategories are considered in the S-LCA analysis defined by UNEP/ SETAS guidelines. The results show that the energy utilization of crop residue has carbon emission factors of 0.09–0.18 kg (CO2 eq per 1 MJ), and presents a net carbon emissions reduction of 0.03–0.15 kg (CO2 eq per 1 MJ) compared with the convectional electricity or petrol, but the other impacts should be paid attention to in the biomass energy scenarios. The energy utilization of crop residues can bring economic benefit to local communities and the society, but the working conditions of local workers need to be improved in future biomass energy development.

Seismic fault interpretation is one of the key steps for seismic structure interpretation, which is a time-consuming task and strongly depends on the experience of the interpreter. Aiming to automate fault interpretation, we have considered it as an image segmentation issue and adopt a solution using a residual UNet (ResUNet), which introduces residual units to UNet. Using the ResUNet model, we develop a fault-versus-azimuth analysis based on offset vector tile data, which, as common-azimuth seismic data, provide more detailed and useful information for interpreting seismic faults. To avoid manual efforts for picking training labels and the inaccuracy introduced by different interpreters, we use synthetic seismic data with a random number of faults with different locations and throws as the training and validation data sets. ResUNet is finally trained using only synthetic data and tested on field data. Field data applications show that the proposed fault-detection algorithm using ResUNet can predict seismic faults more accurately than coherence- and UNet-based approaches. Moreover, geologic fault interpretation results computed using common-azimuth data exhibit higher lateral resolution than those computed using poststack seismic data.

China’s fossil energy is characterized by an abundance of coal and a relative lack of oil and natural gas. Developing a strategy in which coal can replace oil and natural gas is, therefore, a necessary and practical approach to easing the excessive external dependence on oil and natural gas. Based on the perspective of energy security, this paper proposes a technical framework for defining the substitution of oil and natural gas with coal in China. In this framework, three substitution classifications and 11 industrialized technical routes are reviewed. Then, three scenarios (namely, the cautious scenario, baseline scenario, and positive scenario) are developed to estimate the potential of this strategy for 2020 and 2030. The results indicate that oil and natural gas replaced by coal will reach 67 to 81 Mt and 8.7 to 14.3 Gm3 in 2020 and reach 93 to 138 Mt and 32.3 to 47.3 Gm3 in 2030, respectively. By implementing this strategy, China’s external dependence on oil, natural gas, and primary energy is expected to be curbed at approximately 70%, 40%, and 20% by 2030, respectively. This paper also demonstrates how coal, as a substitute for oil and natural gas, can contribute to carbon and pollution reduction and economic cost savings. It suggests a new direction for the development of the global coal industry and provides a crucial reference for energy transformation in China and other countries with similar energy situations.

UV/peroxydisulfate (PDS) and UV/hydrogen peroxide (H2O2) can effectively degrade halophenols (HPs, e.g., 2,4-bromophenol and 2,4,6-trichlorophenol); meanwhile, information about the discrepancies in the related degradation kinetics and mechanisms of these two processes is limited. To gain this knowledge, the degradation of two typical HPs (i.e., bromophenols and chlorophenols) in UV/PDS and UV/H2O2 processes were investigated and compared. The results showed that the degradation rates of HPs with different substitution positions in the UV/PDS process were in the order of para-substituted HPs (i.e., 4-BP and 4-CP) > ortho-substituted HPs (i.e., 2-BP and 2-CP) > meta-substituted HPs (i.e., 3-BP and 3-CP), while in the UV/H2O2 process, these rates were in the order of para-substituted HPs > meta-substituted HPs > ortho-substituted HPs. These discrepancies were ascribed to the different reaction activities of SO4˙− and HO˙ with HPs, which were calculated based on the competition method. Further density functional theory (DFT) calculations suggested that SO4˙− reacts more readily with HPs via electron transfer than HO˙. In the presence of water matrices (such as Cl−, HCO3− and natural organic matter (NOM)), the degradation of 2-BP in both UV/PDS and UV/H2O2 treatment processes was inhibited due to the scavenging of free radicals by these background substances. The degradation products and pathways further confirmed that SO4˙− is a strong one-electron oxidant that reacts with HPs mainly via electron transfer, while HO˙ reacts with HPs via electron transfer and hydroxyl addition.

Algae, which are ubiquitous in surface waters (e.g., lakes, ponds, wetlands) may play an important role in sunlight-driven transformation of compounds. This study is to investigate the role of algae (Chlorella Vulgaris) in chlortetracycline (CTC) photolysis and explore the photosensitive mechanism. The algae were found to significantly accelerate the photodegradation rate of CTC and extracellular organic matters (EOMs) were confirmed to be the major active substances. Triplet state EOMs (3EOMs*) were verified to be the dominant reactive species with 93% contribution to the indirect photodegradation rate of CTC, while ·OH and 1O2 contributed minor (7%). The steady-state concentration of 3EOMs* was determined by probe compounds (2,4,6-trimethylphenol) to be 3.50 × 10−14–1.88 × 10−13 M with the increase of EOMs from 2.0 to 8.0 mg L−1. The rate constant for reaction of 3EOMs* with CTC was calculated to be 3.17 × 109 M−1s−1. 3EOMs* were found to react with CTC mainly via electron transfer, on basis of susceptible reaction of 3EOMs* with the hydroxyl and amidogen groups in CTC. In addition, the energy transfer of 3EOMs* to CTC was possible according to the higher energy of 3EOMs* than that of triplet CTC.

Organic phosphorus flame retardants (OPFRs), as a new type of emerging contaminant, have drawn great attention over the last few years, due to their wide distribution in aquatic environments and potential toxicities to humans and living beings. Various treatment methods have been reported to remove OPFRs from water or wastewater. In this review, the performances and mechanisms for OPFRs removal with different methods including adsorption, oxidation, reduction and biological techniques are overviewed and discussed. Each technique possesses its advantage and limitation, which is compared in the paper. The degradation pathways of typical OPFRs pollutants, such as Cl-OPFRs, alkyl OPFRs and aryl OPFRs, are also reviewed and compared. The degradation of those OPFRs depends heavily upon their structures and properties. Furthermore, the implications and future perspectives in such area are discussed. The review may help identify the research priorities for OPFRs remediation and understand the fate of OPFRs during the treatment processes.

Soil, air, tree bark, rice, wheat, invertebrates, and chicken tissues around a typical endosulfan-contaminated site were analyzed in each season in each of two years. The total endosulfan (the sum of α-, β-endosulfan and endosulfan sulfate) were significantly different in soil and air samples collected in the four seasons (P 3 , respectively, in autumn, 3.32 ng/g d.w. and 2.48 ng/m 3 , respectively, in winter, 2.10 ng/g d.w. and 0.93 ng/m 3 , respectively, in spring, and 1.03 ng/g d.w. and 0.83 ng/m 3 , respectively, in summer. The total endosulfan concentrations in tree bark, rice, wheat, and invertebrates were 23.0–278 (mean 95.5) ng/g d.w., 7.36–35.5 (mean 17.4) ng/g d.w., 34.3–158 (mean 83.1) ng/g d.w., and 401–4354 (mean 2125) ng/g lipid weight, respectively. The total endosulfan concentrations in the chicken gizzard, heart, liver, and meat samples were 552, 212, 699, and 221 ng/g lipid weight, respectively. The endosulfan concentrations in soil, air, and biota around the site were strongly influenced by endosulfan emissions from the site, and the concentrations had decreased to half the initial concentrations six months after endosulfan production stopped. The invertebrate and chicken bioconcentration and biomagnification factors indicated that endosulfan accumulated in the invertebrates and chicken tissues was slightly biomagnified by chickens.

Low-rank coal contains abundant hydroxyl, carboxyl and alkyl side chains, and reactions related to these groups are the main reason for the spontaneous combustion of low-rank coal. Here, two different low-rank coals (BRXL, YJL52) are selected. Firstly, the ignition temperatures of the coals are determined by thermogravimetric method. Secondly, the coals are heated at 100°C temperature intervals before the ignition temperature in the thermogravimetry, and infrared measurement is performed to explore the changes of these groups. Combining previous studies in the literatures with infrared analysis, it is found that reactions related are as follows: phenolic hydroxyl converting into alcoholic hydroxyl, alcoholic hydroxyl further oxidizing to carboxyl, and carboxyl decarboxylating into alkyl side chains. After that, the changes of phenolic hydroxyl and carboxyl on the surface of the coal at 100°C temperature intervals are determined by titration, which further reveal the main reactions occurred in every temperature interval. Additionally, the actual heat release in different temperature ranges is discussed with the reaction enthalpies of the above-mentioned main reactions. As a result, the key temperature stage that causes spontaneous combustion is found. The screening study in this paper on the reaction of low-rank coal before spontaneous combustion provides a theoretical basis for the control of spontaneous combustion of low-rank coal.

UV/peroxydisulfate (PDS) and UV/hydrogen peroxide (H

In algae rich waters, sunlight-driven transformation of antibiotics could be accelerated via sensitization by algae extracellular organic matter (EOM), and this photosensitization process will be affected by coexisting humic substances. In this study, we explored the effect and mechanism of humic substances on photodegradation of chlortetracycline (CTC) mediated by EOM. We found that humic substances exhibited a marked inhibitory effect on the EOM-mediated photodegradation of CTC. Given that humic substances exhibited little effects on the EOM-mediated formation of triplet state species, the quenching effect of humic substances on reactive species was excluded. The inhibitory effect of humic substances was mainly attributed to the back reduction of CTC oxidation intermediates by the antioxidant moieties in humic substances. The ozone oxidation treatment for humic substances was applied to destroy antioxidant moieties. After ozonation, the inhibitory effects of humic substances were greatly decreased, confirming the dominant role of antioxidant moieties in humic substances, which inhibited CTC photodegradation mediated by EOM via reducing oxidation intermediates of CTC. This back reduction was further verified to be exergonic via reactive Gibbs free energy, indicating the back reduction by humic substances of CTC oxidation intermediates could occur spontaneously. The present study will be helpful for predicting the fate and risk of CTC in algae rich water environments, and is of great significance for the study of phototransformation of other antibiotics.

Life cycle assessment (LCA) is a methodological tool that estimates the environmental footprint from a cradle-to-grave perspective. With the increased need for the geographically explicit assessment, the geographic information system (GIS) is integrating into LCA as a frontier methodology to spatialize the environmental footprint. This paper reviews a total of 105 publications about GIS-LCA, including 50 methodological studies that are analyzed following the four phases of LCA and 55 applied studies that are classified into different domains. The review shows that although GIS-LCA methodology has certain explorations and practices and a large number of cases are carried out in the energy industry, agricultural sector, urban facility, and waste management, the current knowledge system faces several challenges in spatializing environmental footprint. In this case, a universal methodology framework of GIS-LCA and specific schemes are proposed to address the following issues: (1) how to set up a geographically referenced system in the goal and scope definition phase; (2) how to spatialize life-cycle data and integrate and compute foreground and background data in the inventory analysis phase; (3) how to develop spatialized characterization factors with different requirements on resolution and data availability in the impact assessment phase; and (4) how to uniform the contribution analysis of different zones, unit processes, and elementary flows to visualize spatialized environmental footprint in the interpretation phase. The framework we developed provides preliminary practices and recommendations for spatializing environmental footprint, which lays a foundation to support future work.

As the largest industrial water consumer in China, the coal power industry faces extreme pressure to balance its expansion and water shortage. Introducing non-coal power to replace coal power is universal knowledge to reduce water consumption, but the water conservation efforts and effects of the coal power industry itself are usually neglected or underestimated. This work aims to bring attention to the importance of the coal power industry’s own water conservation through a case study of China. A bottom-up province-level inventory that focuses on power-cycle water consumption in 2016 was developed, and how self-improvement measures improve this inventory from 2016 to 2020 is evaluated. The results show dynamically varied provincial water consumption intensities of the coal power industry with 0.52–1.85 L/kWh in 2016, which are expected to decrease by 0.04–0.27 L/kWh with a country’s total water conservation potential of 645 million m3 by 2020 thanks to self-improvement measures. The water conservation potential is almost equal to that from introducing non-coal power at 676 million m3. The considerable water conservation of self-improvement makes its effect after 2020 promising in coal-dominant provinces with high water consumption intensities of the coal power industry while introducing non-coal power may be preferred in other provinces.

Accurately estimating greenhouse gas (GHG) emissions from the Chinese coal-to-electricity chain is critical to meet the global goal of carbon reduction, but the efforts in previous work based on statistical data were not ideal. Here, we ingeniously proposed an improved estimation method from a bottom-up perspective, integrating ten technical indicators affecting point-source GHG emissions from coal mines, coal transport routes, and coal power units. This method quantifies provincial GHG emission factors of the coal-to-electricity chain in 2016, varying greatly within 964-1232 g CO2eq / kWh, and explains for the first time how the micro technical indicators affect macro carbon emission levels. Our estimates have a higher spatial resolution and lower uncertainty than existing studies, which can well represent the status quo in different provinces. Based on these emission factors, the total GHG emissions from the Chinese the coal-to-electricity chain in 2016 are estimated at 4232 Mt CO2eq and being spatially intensive in northern and eastern China. They are expected to peak in 2025 according to current policy but in advance by 2019 if transformation is accelerated. The variation province by province suggests that carbon reduction strategies should be tailored to the local specific situation and overall coordinated across the country.

Remediation and management of contaminated sites have become a prevalent problem under the current situation in China. The present study was conducted to investigate the concentration, transmission, and health risk of organochlorine pesticides (OCPs) in soil, air, and vegetation at and around a typical pesticide-contaminated site located in southwestern China. Exchange flux between soil and air was calculated to investigate the transmission of OCPs. Hexachlorocyclohexane (ΣHCHs, top soil: 19.1 mg/kg d.w., air: 52.3 ng/m3, vegetation: 0.17 mg/kg d.w.) and dichlorodiphenyltrichloroethane (ΣDDTs, top soil: 200 mg/kg d.w., air: 130 ng/m3, vegetation: 0.78 mg/kg d.w.) were the dominant pollutants at the contaminated site. Around the site, the soil, air, and vegetation samples had higher OCP concentrations than those in the normal areas, which were found to be dominated by ΣHCHs (top soil: 129 ng/g d.w., air: 5.09 ng/m3, vegetation: 81.8 ng/g d.w.) and ΣDDTs (top soil: 360 ng/g, air: 7.47 ng/m3, vegetation: 189 ng/g d.w.). The fugacity fractions of OCPs (>0.7) showed a net volatilization from soil into air, indicating that soil is an obvious pollution source for the atmosphere, especially at the site. Through human health risk evaluation, serious carcinogenic risk (CRn) and hazardous index (HIn) were found at the site (CRn: 7.4 × 10−6–1.04 × 10−4, HIn: 0.02 to 8.97) and the nearby areas (CRn: 3.37 × 10−6 for adults and 1.68 × 10−6 for children on average).

The control of soil pollution in China has become an issue, and in this study, a compound contaminated site was selected and focus on the site and its nearby environment, organochlorine pesticides (OCPs) were investigated in both soil (top and deep soil) and air samples. The main pollutants in top soils at site are dichlorodiphenyltrichloroethane (DDTs, 0.05–104 mg/kg d.w., avg: 14.5 mg/kg d.w.) and hexachlorobenzene (HCB, 0.02–4.85 mg/kg d.w., avg: 0.72 mg/kg d.w.) which is in accordance with its production history. As for the deep soils, ΣOCPs at site were found concentrated at workshops especially the technical pesticide workshop (5.29–22.1 mg/kg d.w., avg: 9.15 mg/kg d.w.) and the history DDTs’ workshop (4.00–64.8 mg/kg d.w., avg: 20.4 mg/kg d.w). Around site, OCPs were mainly concentrated at layers of −20 cm and the −40 cm and decreased with distance being far away, at 5000 m, the ΣOCPs was comparable with normal agriculture soil (22.1−91.4 ng/g d.w., avg: 55.4 ng/g d.w.). ΣOCPs in the air samples ranged 64.6–823 ng/m3 (avg: 459 ng/m3) at site and 9.93–176 ng/m3 (avg: 50.8 ng/m3) around site which are all dominated with DDTs and HCHs. Soil–air exchange fugacity was calculated to judge the transportation of the OCPs and the results showed soils at the site and its nearby areas (within 5000 m) are releasing most of the OCPs into air, and accordingly through evaluation, inhalation was found to be the major source for human health risk, which is a great threat to the workers at site and the nearby residents.

The use of biobased materials to replace their conventional, synthetic counterparts is clearly increasing today. An interesting application, printed circuit board substrates based on biobased materials, has recently been proposed, produced, and tested by several researchers. Building on these exploratory studies, this paper aims to evaluate and compare the environmental impact of biobased and conventional printed circuit board substrates. The conventional materials for printed circuit board substrates are epoxy resin reinforced by woven glass fibre fabric. Recent studies demonstrate that epoxidized linseed oil reinforced by flax fibre can meet most of the requirements specified in standards for printed circuit board substrates. A functional unit of 1 m2 of a printed circuit board substrate was selected for the comparative cradle-to-grave life cycle assessment, and incineration with energy recovery has been considered as an end-of-life scenario. The comparative life cycle assessment documented in this paper shows that a biobased printed circuit board substrate offers a clear impact reduction compared to the conventional design for most impact categories, except for freshwater toxicity, eutrophication, and land use. These are well-known problems for agro-products with pesticide and fertilizer use in cultivation. The environmental impact caused in the End-of-Life stage is generally negligible compared to the production stage for both types of printed circuit board substrates. However, the biobased substrate has a higher embodied energy compared to the conventional substrate, and consequently enables lowering of the fuel use for incineration or providing a higher energy output in the case of a combustion scenario. It can be concluded that the biobased design, composed of flax-fibre reinforced epoxidized linseed oil, is characterized by a lower overall environmental impact. The aggregated weighted eco-points score obtained using the ReCiPe methodology is 42% lower than for the conventional design for the chosen functional unit and scenario. Because the extensively measured technical properties of the biobased substrate were found to comply with almost all international standard specifications, the biobased design offers promising perspectives for further study. However, for industrial application, the major weaknesses of biobased materials, such as the high water absorbance, must be addressed. In addition, the higher land use raises considerable concern, indicating conflicts over food cultivation for use of biobased materials for manufacturing purposes.

The Chinese government is going to &ldquo, push ahead the revolution of energy production and consumption, and establish a clean, low-carbon, secure, and efficient energy system&rdquo, which points out a direction for the energy industry in the new era. Using the analytic hierarchy process of the system analysis method, we constructed an indicator system of the modern Chinese energy system, and by determining the weighting of each indicator, we obtained the composite index of the modern Chinese energy system, as well as four sub-indexes of clean, low-carbon, secure, and efficient. Then, we investigated policy changes and energy development characteristics of important periods, and performed historical trend analysis. Finally, we forecasted the composite index and four sub-indexes by 2050, and proposed an energy development path and policy suggestions to achieve a modern Chinese energy system as soon as possible.