Integrated management of municipal solid waste(MSW)is a major environmental challenge encountered by many countries.To support waste treatment/management and national macroeconomic policy development,it is essential t...Integrated management of municipal solid waste(MSW)is a major environmental challenge encountered by many countries.To support waste treatment/management and national macroeconomic policy development,it is essential to develop a prediction model.With this motivation,a database of MSW generation and feature variables covering 130 cities across China is constructed.Based on the database,advanced machine learning(gradient boost regression tree)algorithm is adopted to build the waste generation prediction model,i.e.,WGMod.In the model development process,the main influencing factors on MSW generation are identified by weight analysis.The selected key influencing factors are annual precipitation,population density and annual mean temperature with the weights of 13%,11%and 10%,respectively.The WGMod shows good performance with R^(2)=0.939.Model prediction on MSW generation in Beijing and Shenzhen indicates that waste generation in Beijing would increase gradually in the next 3–5 years,while that in Shenzhen would grow rapidly in the next 3 years.The difference between the two is predominately driven by the different trends of population growth.展开更多
Research on anion exchange membrane fuel cells(AEMFCs)mainly focuses on the membrane module,and improving its performance has always been the focus of researchers.To create high-performance anion exchange membranes(AE...Research on anion exchange membrane fuel cells(AEMFCs)mainly focuses on the membrane module,and improving its performance has always been the focus of researchers.To create high-performance anion exchange membranes(AEMs),a series of side chain type AEMs were prepared by introducing different proportions of side chains containing anisotropic poly cations with relatively stable piperidinium ring cations and side quaternary ammonium cations as cation groups,using poly(p-terphenyl isatin)(PTI),a main chain polymer without aryl ether bonds.The dense surface of the PTI-N-n series membranes is shown by SEM images;TEM images show that the ion domains are clearly distributed in the membrane,so a continuous ion transport channel is constructed.PTI-N-100 has the highest hydroxide conductivity at 80℃,reaching 96.83 mS cm^(-1) due to multiple transport sites.The PTI-N-100 membrane has a peak power density of 180 mW cm^(2) based on the highest ionic conductivity.Therefore,we believe that the introduction of multi-cations contributes to the performance of anion exchange membranes.展开更多
基金supported by the National Key R&D Program of China(Nos.2018YFD1100600,2018YFC1902900).
文摘Integrated management of municipal solid waste(MSW)is a major environmental challenge encountered by many countries.To support waste treatment/management and national macroeconomic policy development,it is essential to develop a prediction model.With this motivation,a database of MSW generation and feature variables covering 130 cities across China is constructed.Based on the database,advanced machine learning(gradient boost regression tree)algorithm is adopted to build the waste generation prediction model,i.e.,WGMod.In the model development process,the main influencing factors on MSW generation are identified by weight analysis.The selected key influencing factors are annual precipitation,population density and annual mean temperature with the weights of 13%,11%and 10%,respectively.The WGMod shows good performance with R^(2)=0.939.Model prediction on MSW generation in Beijing and Shenzhen indicates that waste generation in Beijing would increase gradually in the next 3–5 years,while that in Shenzhen would grow rapidly in the next 3 years.The difference between the two is predominately driven by the different trends of population growth.
基金The authors gratefully acknowledge the financial support of this work by Natural Science Foundation of China(grant no 22075031)Jilin Provincial Science&Technology Department(grant no 20220201105GX)。
文摘Research on anion exchange membrane fuel cells(AEMFCs)mainly focuses on the membrane module,and improving its performance has always been the focus of researchers.To create high-performance anion exchange membranes(AEMs),a series of side chain type AEMs were prepared by introducing different proportions of side chains containing anisotropic poly cations with relatively stable piperidinium ring cations and side quaternary ammonium cations as cation groups,using poly(p-terphenyl isatin)(PTI),a main chain polymer without aryl ether bonds.The dense surface of the PTI-N-n series membranes is shown by SEM images;TEM images show that the ion domains are clearly distributed in the membrane,so a continuous ion transport channel is constructed.PTI-N-100 has the highest hydroxide conductivity at 80℃,reaching 96.83 mS cm^(-1) due to multiple transport sites.The PTI-N-100 membrane has a peak power density of 180 mW cm^(2) based on the highest ionic conductivity.Therefore,we believe that the introduction of multi-cations contributes to the performance of anion exchange membranes.
