Nitrogen-enriched micro-mesoporous carbon derived from polymers organic frameworks for high-performance capacitive deionization

Nitrogenization is an effective method for improving the capacitive deionization（CDI） performance of porous carbon materials. In particular, polymer organic frameworks with heteroatom doping, containing an ordered pore structure and excellent electrochemical stability, are ideal precursors for carbon materials for high-performance CDI. In this study, a nitrogen-enriched micro-mesoporous carbon（NMC） electrode was fabricated by carbonizing a Schiff base network-1 at 500, 600, and 700 °C. Scanning ...     

Water quality soft-sensor prediction in anaerobic process using deep neural network optimized by Tree-structured Parzen Estimator

● Hybrid deep-learning model is proposed for water quality prediction. ● Tree-structured Parzen Estimator is employed to optimize the neural network. ● Developed model performs well in accuracy and uncertainty. ● Usage of the proposed model can reduce carbon emission and energy consumption. Anaerobic process is regarded as a green and sustainable process due to low carbon emission and minimal energy consumption in wastewater treatment plants (WWTPs). However, some water quality metrics are not measurable in real time, thus influencing the judgment of the operators and may increase energy consumption and carbon emission. One of the solutions is using a soft-sensor prediction technique. This article introduces a water quality soft-sensor prediction method based on Bidirectional Gated Recurrent Unit (BiGRU) combined with Gaussian Progress Regression (GPR) optimized by Tree-structured Parzen Estimator (TPE). TPE automatically optimizes the hyperparameters of BiGRU, and BiGRU is trained to obtain the point prediction with GPR for the interval prediction. Then, a case study applying this prediction method for an actual anaerobic process (2500 m³/d) is carried out. Results show that TPE effectively optimizes the hyperparameters of BiGRU. For point prediction of COD_eff and biogas yield, R² values of BiGRU, which are 0.973 and 0.939, respectively, are increased by 1.03%–7.61% and 1.28%–10.33%, compared with those of other models, and the valid prediction interval can be obtained. Besides, the proposed model is assessed as a reliable model for anaerobic process through the probability prediction and reliable evaluation. It is expected to provide high accuracy and reliable water quality prediction to offer basis for operators in WWTPs to control the reactor and minimize carbon emission and energy consumption.     

Spherical Bi2O3/ATO catalyst with N2 pre-reduction electrocatalytic reduction of CO2 to formic acid

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,an...     

Excessive Cu and Zn affecting on distribution of the metals and activities of glycolytic and nitrogen incorporating key enzymes in mycelia of ectomycorrhizal fungi Suillus bovinus

ＩｎｔｒｏｄｕｃｔｉｏｎＥｃｔｏ ｍｙｃｏｒｒｈｉｚａｌｆｕｎｇｉａｒｅｋｎｏｗｎｔｏａｍｅｌｉｏｒａｔｅｍｅｔａｌｔｏｘｉｃｉｔｙｔｏｔｈｅａｓｓｏｃｉａｔｅｄｈｉｇｈｅｒｐｌａｎｔｓ (Ｂｒａｄｌｅｙ ,1981;1982 ;Ｂｒｏｗｎ ,1985;Ｂｕｃｋｉｎｇ ,1995) .Ｔｈｅｉｍｐｒｏｖｅｍｅｎｔｏｆｈｅａｖｙｍｅｔａｌｔｏｌｅｒａｎｃｅｂｙｍｙｃｏｒｒｈｉｚａｌｉｎｆｅｃｔｉｏｎｉｓｒｅｌａｔｅｄｔｏａｒｅｄｕｃｔｉｏｎｏｆｓｈｏｏｔｔｉｓｓｕｅｃｏｎｃｅｎｔｒａｔｉｏｎ ,ｃｏｕｐｌｅｗｉｔｈａｎｉｎｃｒｅａ…     

Landscape patterns and their evolutions in the suburban ecotone A case study of the eastern suburb of Beijing

Ｌａｎｄｓｃａｐｅｐａｔｔｅｒｎｓａｎｄｔｈｅｉｒｅｖｏｌｕｔｉｏｎｓ１０ｔｈｅｓｕｂｕｒｂａｎｅｃｏｔｏｎｅ──ＡｃａｓｅｓｔｕｄｙｏｆｔｈｅｅａｓｔｅｒｎｓｕｂｕｒｂｏｆＢｅｉｊｉｎｇＹａｎｇＪｕｒｏｎｇ，ＺｈａｎｇＨｏｎｇｍｅｉ，ＨｕａｎｇＹｉ...     

Bioaugmentation: a new strategy for removal of recalcitrant compounds in wastewater—a case study of quinoline

ＩｎｔｒｏｄｕｃｔｉｏｎＩｎｒｅｃｅｎｔｙｅａｒｓｘｅｎｏｂｉｏｔｉｃｓｈａｖｅｃａｕｇｈｔｗｏｒｌｄｓａｔｔｅｎｔｉｏｎｂｅｃａｕｓｅｔｈｅｙａｒｅｐｏｏｒｌｙｂｉｏｄｅｇｒａｄａｂｌｅａｎｄｔｈｒｅａｔｅｎｐｕｂｌｉｃｈｅａｌｔｈｉｆｈａｎｄｌｅ...     

A neural network model forecasting for prediction of daily maximum ozone concentration in an industrialized urban area

Prediction of ambient ozone concentrations in urban areas would allow evaluation of such factors as compliance and noncompliance with EPA requirements. Though ozone prediction models exist, there is still a need for more accurate models. Development of these models is difficult because the meteorological variables and photochemical reactions involved in ozone formation are complex. In this study, we developed a neural network model for forecasting daily maximum ozone levels. We then compared the neural network's performance with those of two traditional statistical models, regression, and Box-Jenkins ARIMA. The neural network model for forecasting daily maximum ozone levels is different from the two statistical models because it employs a pattern recognition approach. Such an approach does not require specification of the structural form of the model. The results show that the neural network model is superior to the regression and Box-Jenkins ARIMA models we tested.     

Changes of landscape pattern and its influence on environment in Dongling District,Shenyang City, China

ＣｈａｎｇｅｓｏｆｌａｎｄｓｃａｐｅｐａｔｔｅｒｎａｎｄｉｔｓｉｎｆｌｕｅｎｃｅｏｎｅｎｖｉｒｏｎｍｅｎｔｉｎＤｏｎｇｌｉｎｇＤｉｓｔｒｉｃｔ，ＳｈｅｎｙａｎｇＣｉｔｙ，Ｃｈｉｎａ￥ＺｈａｏＹｉ；ＬｉｕＺｈｅｎｇｕｏ；ＸｕＬａｎ（Ｉｎｓｔｉｔｕｔｅｏ...     

Experimental and mechanism studies on seawater flue gas desulfurization

ＩｎｔｒｏｄｕｃｔｉｏｎＩｎｓｔａｌｌａｔｉｏｎｏｆｓｃｒｕｂｂｅｒｓｏｒｔｈｅｕｓｅｏｆｌｏｗｓｕｌｆｕｒ ｃｏｎｔａｉｎｉｎｇｃｏａｌａｒｅｔｗｏｏｐｔｉｏｎｓｕｓｅｄｂｙｐｏｗｅｒｐｌａｎｔｓｔｏｒｅｄｕｃｅＳＯ2 ｅｍｉｓｓｉｏｎｓ.ＴｈｅｍａｊｏｒｉｔｙｏｆｐｏｗｅｒｐｌａｎｔｓｃｏｎｔｒｏｌＳＯ2 ｅｍｉｓｓｉｏｎｓｕｓｉｎｇｌｉｍｅｂａｓｅｄｓｃｒｕｂｂｉｎｇ ,ａｌｔｈｏｕｇｈｔｈｉｓｄｅｓｕｌｆｕｒｉｚａｔｉｏｎｐｒｏｃｅｓｓｈａｓａｎｕｍｂｅｒｏｆａｄｖａｎｔａｇｅｓ,ｉｔａｌｓｏｈ…     

Transmembrane transport of polycyclic aromatic hydrocarbons by bacteria and functional regulation of membrane proteins

• Explaintheadsorption, uptake and transmembrane transport of PAHs by bacteria. • Analyze functional regulation of membrane proteins inthe transmembrane transport. • Proteomics technology such as iTRAQ labeling was used to access expressed proteins. • Single cell analysis technology wereused to study the morphological structure. In recent years, increasing research has been conducted on transmembrane transport processes and the mechanisms behind the microbial breakdown of polycyclic aromatic hydrocarbons (PAHs), including the role of membrane proteins in transmembrane transport and the mode of transmission. This article explains the adsorption, uptake and transmembrane transport of PAHs by bacteria, the regulation of membrane protein function during the transmembrane transport. There are three different regulation mechanisms for uptake, depending on the state and size of the oil droplets relative to the size of the microbial cells, which are (i) direct adhesion, (ii) emulsification and pseudosolubilization, and (iii) interfacial uptake. Furthermore, two main transmembrane transport modes are introduced, which are (i) active transport and (ii) passive uptake and active efflux mechanism. Meanwhile, introduce the proteomics and single cell analysis technology used to address these areas of research, such as Isobaric tags for relative and absolute quantitation (iTRAQ) technology and Nano Secondary ion mass spectrometry (Nano-SIMS). Additionally, analyze the changes in morphology and structure and the characteristics of microbial cell membranes in the process of transmembrane transport. Finally, recognize the microscopic mechanism of PAHs biodegradation in terms of cell and membrane proteins are of great theoretical and practical significance for understanding the factors that influence the efficient degradation of PAHs contaminants in soil and for remediating the PAHs contamination in this area with biotechnology.