An Aging Giant At The Center of Global Warming: Population Dynamics and Its Effect on CO2 Emissions in China

Managing the aging crisis and mitigating CO2 emissions are currently two great challenges faced by China. Revealing the complex correlation between aging and CO2, and projecting their future dynamics are fundamentally necessary to inform effective strategies and policies toward a low-carbon and sustainable development in China. In this paper, we quantitatively investigated the impacts of population aging, economy, and energy intensity on CO2 emissions through a STIRPAT model based on balanced provincial panel data from 1995-2019, and employed a cohort model and scenario analysis to project the demographic change and CO2 emissions till 2050. It is found that CO2 emissions in China has witnessed a significant growth during 1995-2019, and will exhibit an inverted U-shaped growth till 2050 with its peak appears between 2030-2040. Every 1% increase of aging will exert a 0.69% emission of CO2 in China. However, a big regional difference was also detected as aging contributed to CO2 reduction in the eastern region, but stimulated CO2 emissions in the central and western regions. Policy implications for achieving a low-carbon and aging-oriented sustainable development include the integration of aging into the decision-making of industrial structure upgrading and CO2 emission reduction in both national and region levels, the promotion of the further transition to low-carbon consumption and green products in the eastern region, and strengthening the deep fusion of aging-oriented industries with local resource and environmental endowment in the central and western regions such as the development of eco-agriculture and green pension industries.

Analysis of the Driving Factors of Building Energy Consumption Growth in Smart Cities Based on the STIRPAT Model

Energy consumption in smart cities relates to every energy consumed to carry out an activity, produce something, or exist in a structure. The most common measurement of energy efficiency is energy consumption per square meter in city residential areas. The states’ problematic energy consumption characteristics in smart cities may include climatic change, rainfall issues, water scarcity, and electricity generation. Thus, based on the states of households, an expanded proposed system of statistic determination impact conversion by positive, accurate technology (STIRPAT) model has been developed. STIRPAT model is collaborative research that aims to learn about the dynamic connections between human systems and the surrounding environment. There are two methods of the STIRPAT model to satisfy the characteristic of the proposed approach. The energetic counseling framework is an emerging technique that overcomes climatic change, electricity generation, and rainfall issues by sensing it in the environment. An algorithmic approach of the standard genetic method offers to conclude the problems into a cloud block mechanism for visualizing the states. Thus, the integrated technique of these two methods shows the factual implementation to overcome the statistical problems. Further research shows that, since the significant effect had been taken into account, the energy consumption per square meter in metropolitan residential buildings peak occurred eleven years later than without considering the dilution effect. The performance ratio of the STIRPAT model is estimated to be 98.3% by comparing with overall researches.

Impact of Economic Policy Uncertainty on Carbon Emissions: Evidence from 137 Multinational Countries

With growing economic policy uncertainty (EPU) and the importance of protecting the natural environment worldwide, the relationship between EPU and carbon emissions should be investigated further. However, conclusions in the existing literature on the relationship between EPU and carbon emission are inconclusive. This paper aims to examine the influence of EPU on carbon emissions according to the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model. To investigate such essential issues, we conduct GMM estimations by utilizing cross-country data covering 137 countries during the period 1970–2018, obtained from World Bank and OECD statistics. Our empirical estimations support that EPU would bring about more carbon emissions, while we conduct empirical analysis by changing the system of measurement, employing alternative estimation and constructing new samples. Our study provides substantial policy implications for government participation in international treaties on environmental protection to mitigate environmental degradation.

Decoupling Analysis of Greenhouse Gas Emissions from Economic Growth: A Case Study of Tunisia

The study examined the impact of different factors on greenhouse gas (GHG) emissions, by applying the extended STIRPAT model and decoupling analysis for Tunisia for the period 1990–2018. Furthermore, the study utilizes Tapio decoupling model, and the Auto-Regressive Distributed Lag (ARDL) bounds test approach to examine the relationship between the variables of greenhouse gas (GHG) emissions, economic growth, energy consumption, urbanization, innovation, and trade openness. The findings validated an inverted U-shape relationship between GDP and GHG emissions. In addition, we find that the consumption of renewable energy contributes to the reduction of GHG emissions in the long run. The findings call authority for the adaption of the regulatory framework relating to energy management, energy efficiency and the development of renewable energies, as well as to initiate energy market reforms, implement mitigation strategies and encourage investments in clean energies.

Exploring the Dependence and Influencing Factors of Carbon Emissions from the Perspective of Population Development

Working towards sustainable population development is an important part of carbon mitigation efforts, and decoupling carbon emissions from population development has great significance for carbon mitigation. Based on the construction of a comprehensive population development index (PDI), this study adopts a decoupling model to explore the dependence between carbon emissions and PDI across 30 Chinese provinces from 2001 to 2017. Then, the stochastic impacts by regression on population, affluence and technology (STIRPAT) model is used to investigate the impact of population factors on carbon emissions. The results show that the decoupling relationship between carbon emissions and PDI has experienced a transformation from expansive negative coupling to expansive coupling and then to weak decoupling at the national level, while some provinces have experienced the same evolutionary process, but the decoupling state in most provinces is not ideal. Sending talent to western provinces and developing low-carbon supporting industries will accelerate carbon decoupling. At the national level, incorporating environmental protection into the existing education system as part of classroom teaching could contribute to carbon decoupling.

Technology Innovation, Economic Growth and Carbon Emissions in the Context of Carbon Neutrality: Evidence from BRICS

This study selects the panel data of five BRICS nations (Brazil, Russia, India, China, South Africa) from 1990 to 2019 to empirically explore the impact of technological innovation and economic growth on carbon emissions under the context of carbon neutrality. Granger causality test results signify that there exists a one-way causality from technology patent to carbon emission and from economic growth to carbon emission. We also constructed an improved Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model. The regression results manifest that technology patents contribute to the realization of carbon emission reduction and carbon neutralization, while the economic growth of emerging economies represented by BRICS countries significantly improves carbon emissions, but every single BRICS country shows differentiated carbon emissions conditions with their economic development stages. The impact of the interaction term on carbon emissions for the five BRICS countries also presents country-specific heterogeneity. Moreover, the Environmental Kuznets Curve (EKC) test results show that only Russia and South Africa have an inverted U-shaped curve relationship between economic growth and carbon emissions, whereas Brazil, India and China have a U-shaped curve relationship. There exists no EKC relationship when considering BRICS nations as a whole. Further robustness tests also verify that the conclusions obtained in this paper are consistent and stable. Finally, the paper puts forward relevant policy suggestions based on the research findings.

Nexus of co2 emissions and economic growth in pakistan: analysis by using extended stirpat model

The main purpose of this study is to analyze the relationship between economic growth (GDP per capita) and CO2 emissions in Pakistan. This study applies the theoretical framework of Dietz and Rosa’s STIRPAT Model, widely used for assessing the environment quality. The additional major determinants of CO2 emissions introduced by the extended STIRPAT model include total energy use, Industry, value-added, financial development, trade openness, and urban population. The empirical results reveal that; total energy use has a positive and significant relationship with CO2 emissions. The relationship between GDP and CO2 emissions is positive and insignificant in the country. Industry, value-added has an insignificant relationship with CO2 emissions in the country. The urban population has a direct and positive relationship with CO2 emissions. Trade openness has a long-run positive and significant relationship with CO2 emissions in the country. In general, this case study offers a relevant policy for controlling the enhancement in the CO2 emissions in the selected sample unit; Pakistan, and other similar states that possess the same socio-economic condition.