The development of unimolecular conjugated polymeric micelles for the highly selective detection and recovery of gold from electronic waste

2019 ◽  
Vol 43 (30) ◽  
pp. 11811-11815 ◽  
Author(s):  
Jilin Liu ◽  
Ting Yang ◽  
Zhiru Hu ◽  
Guodong Feng
Keyword(s):  
Carbon Dioxide ◽  
Sustainable Development ◽  
Development Strategy ◽  
Conjugated Polymer ◽  
Carbon Dioxide Emissions ◽  
Polymeric Micelles ◽  
Electronic Waste ◽  
Selective Detection

Gold recycling is a sustainable development strategy that will save a large amount of carbon dioxide emissions. In this work, we have developed a conjugated polymer, that can not only detect Au content in e-waste but also extract Au from e-waste.

scholarly journals How Does Green Technology Innovation Affect Carbon Emissions? A Spatial Econometric Analysis of China’s Provincial Panel Data

2021 ◽  
Vol 9 ◽  
Author(s):  
Aixin Cai ◽  
Shiyong Zheng ◽  
LiangHua Cai ◽  
Hongmei Yang ◽  
Ubaldo Comite
Keyword(s):  
Carbon Dioxide ◽  
Sustainable Development ◽  
Economic Development ◽  
Panel Data ◽  
Technological Innovation ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Technology Innovation ◽  
Green Technology ◽  
Research Results

Due to an increasing number of issues such as climate change, sustainable development has become an important theme worldwide. Sustainable development is inseparable from technological innovation. Only by making technological breakthroughs can we ensure the overall integration of economic development and environmental protection. Here, based on China’s inter-provincial panel data from 2006 to 2019, we examine the relationship between green technological innovation and carbon dioxide (CO2) emissions in 30 provinces (excluding Hong Kong, Macao, Taiwan, and Tibet) and sub-regions (eastern, central, and western China) in China using a space panel econometric model based on the STIRPAT equation. Additionally, we use geographic information analysis methods to analyze the spatial pattern and evolution characteristics of CO2 emissions. Our major finding is that, from the perspective of the whole country, green technology innovation has a negative correlation with carbon emissions, but the effect is not obvious. In addition, from the regional sample, green technology innovation in the eastern and central regions can effectively reduce carbon emissions, while in the western region, green technology innovation can promote carbon emissions in the province. At the same time, the research results show a strong spatial spillover effect of inter-provincial carbon dioxide emissions, and the progress of green technology in neighboring provinces has a negative impact on carbon emissions in their own provinces. Therefore, cross-province policies and actions for reducing carbon emissions are necessary. Additionally, our results show that carbon-emission driving factors, such as economic development, industrial structure, energy consumption structure, and population, have a significant positive effect on carbon dioxide emissions. Based on the above research results, we put forward corresponding policy recommendations.

Preliminary Study on Low-Carbon Urban Development and Low-Carbon Design

2014 ◽  
Vol 1010-1012 ◽  
pp. 1854-1857
Author(s):  
Xiao Na Li ◽  
Yuan Zhang
Keyword(s):  
Carbon Dioxide ◽  
Sustainable Development ◽  
Urban Development ◽  
Carbon Dioxide Emissions ◽  
Low Carbon ◽  
Carbon Consumption ◽  
Low Carbon Economy ◽  
Preliminary Study ◽  
Development Methods ◽  
Carbon Economy

In advocating the principle of sustainable development, urban development calls for reducing the carbon dioxide emissions to promote low carbon economy. Low-carbon design is the foundation and effective method of low-carbon economy development. By analyzing the principles of low-carbon urban development, methods of low-carbon design were discussed so as to guide people's low carbon consumption and reduce carbon footprint. Low-carbon design process was proposed at last. In this way, the development of low-carbon urban could be carried out by starting from the source.

scholarly journals Forecasting Energy-Related Carbon Dioxide Emissions in Thailand’s Construction Sector by Enriching the LS-ARIMAXi-ECM Model

2018 ◽  
Vol 10 (10) ◽  
pp. 3593 ◽  
Author(s):  
Jindamas Sutthichaimethee ◽  
Kuskana Kubaha
Keyword(s):  
Carbon Dioxide ◽  
Sustainable Development ◽  
Error Correction ◽  
Co2 Emissions ◽  
Development Policy ◽  
Carbon Dioxide Emissions ◽  
Forecasting Model ◽  
Construction Sector ◽  
Error Correction Mechanism

The Thailand Development Policy focuses on the simultaneous growth of the economy, society, and environment. Long-term goals have been set to improve economic and social well-being. At the same time, these aim to reduce the emission of CO2 in the future, especially in the construction sector, which is deemed important in terms of national development and is a high generator of greenhouse gas. In order to achieve national sustainable development, policy formulation and planning is becoming necessary and requires a tool to undertake such a formulation. The tool is none other than the forecasting of CO2 emissions in long-term energy consumption to produce a complete and accurate formulation. This research aims to study and forecast energy-related carbon dioxide emissions in Thailand’s construction sector by applying a model incorporating the long- and short-term auto-regressive (AR), integrated (I), moving average (MA) with exogenous variables (Xi) and the error correction mechanism (LS-ARIMAXi-ECM) model. This model is established and attempts to fill the gaps left by the old models. In fact, the model is constructed based on factors that are causal and influential for changes in CO2 emissions. Both independent variables and dependent variables must be stationary at the same level. In addition, the LS-ARIMAXi-ECM model deploys a co-integration analysis and error correction mechanism (ECM) in its modeling. The study’s findings reveal that the LS-ARIMAXi -ECM model is a forecasting model with an appropriate time period (t − i), as justified by the Q-test statistic and is not a spurious model. Therefore, it is used to forecast CO2 emissions for the next 20 years (2019 to 2038). From the study, the results show that CO2 emissions in the construction sector will increase by 37.88% or 61.09 Mt CO2 Eq. in 2038. Also, the LS-ARIMAXi -ECM model has been evaluated regarding its performance, and it produces a mean absolute percentage error (MAPE) of 1.01% and root mean square error (RMSE) of 0.93% as compared to the old models. Overall, the results indicate that determining future national sustainable development policies requires an appropriate forecasting model, which is built upon causal and contextual factors according to relevant sectors, to serve as an important tool for future sustainable planning.

The Effect of Industrial Structure Change on Carbon Dioxide Emissions: A Cross-Country Panel Analysis

2020 ◽  
Vol 8 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Jichang Dong ◽  
Jing He ◽  
Xiuting Li ◽  
Xindi Mou ◽  
Zhi Dong
Keyword(s):  
Carbon Dioxide ◽  
Sustainable Development ◽  
Carbon Dioxide Emissions ◽  
Service Sector ◽  
Energy Use ◽  
Industrial Structure ◽  
Negative Impact ◽  
Structure Change ◽  
Per Capita ◽  
Cross Country

AbstractReduction of carbon dioxide (CO2) emissions is one of the biggest challenges for global sustainable development, in which economic growth characterized by industrialization plays a formidable role. We innovatively adopted the input and output (I-O) table of 41 countries released by World I-O Database to determine the industrial structure change and analyze its impact on CO2 emission evolution by developing a cross-country panel model. The empirical results show that industrial structure change has a significantly negative effect on CO2 emissions; to be specific, 0.1 unit increase in the linkage of manufacturing sector and service sector will lead to a decrease of 0.94 metric tons per capita CO2 emissions, indicating that upgrading industrial structure contributes to carbon mitigation and sustainable development. Further, urbanization, technology and trade openness have significantly negative impact on CO2 emissions, while economy growth and energy use take positive impacts. In particular, a 1% increase in per capita income will contribute to an increase of 8.6 metric tons per capita CO2 emissions. However, the effect of industrial structure on environment degradation is moderated by technology level. These findings fill the gaps of previous literature and provide valuable references for effective policies to mitigate CO2 emissions and achieve sustainable development.

Sign in / Sign up

Export Citation Format

Share Document