China's low-carbon competitiveness and its effect decomposition from the perspective of wellbeing performance of ecological input

From the perspective of wellbeing performance of ecological input,this paper constructs a low-carbon competitiveness evaluation model with wellbeing performance of carbon emissions as the measurement standard,and uses the LMDI factor decomposition method to decompose the total effect of low-carbon competitiveness changes into technology effect and service effect.And then it conducts positive analysis and comparison of the low-carbon competitiveness and its effect contribution of G20 countries from1990 to 2018.The results are as follows:Firstly,in 2018,the UK,France,Argentina,Brazil,and Germany had higher low-carbon competitiveness.From 1990 to 2018,the low-carbon competitiveness of the UK,Turkey,Germany,Italy,and Brazil increase rapidly.Secondly,from 1990 to 2018,the total effect of low-carbon competitiveness of G20 member states was all positive,that is to say,the overall wellbeing performance of carbon emissions increased,technology effect and service effect are positive in 17 countries and negative in 2 countries respectively.Thirdly,China's low-carbon competitiveness is low,lacking static and dynamic advantages,although the technology effect is the highest,but the service effect is the lowest,resulting in a low total effect,which indicates that the wellbeing performance of economic growth is the main bottleneck of China's low-carbon development.Finally,the policy recommendations for China's future low-carbon transition and sustainable development are put forward.

Sustainable Urban Development Evaluation of Shanghai:An Ecological Wellbeing Performance Perspective

Against the backdrop of aggravating resource and environment restriction,it is an inevitable choice to adopt the sustainable development pattern to maximize social well-being within the ecological threshold.From the perspective of ecological well-being performance,ecological footprint per capita and human development index were selected to construct the evaluation index system for sustainable urban development,and DEA applied to calculate the input-output efficiency,so as to analyze the sustainable development level of Shanghai from 1999 to 2012.The results showed that①human development index,ecological footprint per capita of Shanghai grew in step with economic development,but ecological footprint per capita level exceeded the ecological carrying capacity,thus the overall ecological conditions remained in the state of worsening "deficit";②ecological well-being performance of Shanghai in most years remained in the DEA ineffective state,and the scale return had decreased gradually since 2005.In addition,the paper gave pertinent suggestions.

Comparison for ecological economic performance of Chinese sea perch(Lateolabrax Maculatus)under different aquaculture systems

Chinese sea perch(Lateolabrax Maculatus)is one of the main marine fish culture species in China,its green development has received increasing attention and its ecological economic study is rare.Based on field survey,this paper takes water pollution tax of China as conversion indicator for aquaculture eutrophication to simulate aquaculture waste fee for further analyzing the ecological impact of Chinese sea perch’s aquaculture.For data analysis,data envelopment analysis model has been used.The comparison for Chinese sea perch’s economic performance and ecological economic performance under its main aquaculture systems has been done.The results show that:1.The simulated waste fee has no significant impact for the comparison.2.Ranking for ecological economic performance’s ecological economic,technical and scale efficiency is as follow:pond farming,offshore cage culture and cage culture.3.Offshore cage culture is the only system presenting positive increase for ecological economic performance,which makes its aquaculture activity more sustainable than other systems.4.The key point of green development is to maximize the ecological economic efficiency of main aquaculture systems.Thus,offshore cage culture is the most sustainable aquaculture system among China’s current marine fish culture systems,and other systems need innovation for achieving the green development of China’s aquaculture.

Utilizing interpretable stacking ensemble learning and NSGA-Ⅲ for the prediction and optimisation of building photo-thermal environment and energy consumption

This study develops an approach consisting of a stacking model integrated with a multi-objective optimisation algorithm aimed at predicting and optimising the ecological performance of buildings.The integrated model consists of five base models and a meta-model,which significantly improves the prediction performance.Specifically,the R2 value was improved by 9.19% and the error metrics MAE,MSE,MAPE,and CVRMSE were reduced by 69.47%,79.88%,67.32%,and 57.02%,respectively,compared to the single prediction model.According to the research on interpretable machine learning,adding the SHAP value gives us a deeper understanding of the impact of each architectural design parameter on the performance.In the multi-objective optimisation part,we used the NSGA-Ⅲ algorithm to successfully improve the energy efficiency,daylight utilisation and thermal comfort of the building.Specifically,the optimal design solution reduces the energy use intensity by 31.6 kWh/m^(2),improves the useful daylight index by 39%,and modulated the thermal comfort index,resulting in a decrement of 0.69℃ for the summer season and an enhancement of 0.64℃ for the winter season,respectively.Overall,this study provides building designers and decision makers with a tool to make better design decisions at an early stage to achieve a better combination of energy efficiency,daylight utilisation and thermal comfort optimisation in an integrated manner,providing an important support for achieving sustainable building design.