The impact of renewable and non-renewable energy consumption on carbon emission intensity in China: Fresh evidence from novel dynamic ARDL simulations.

Given the dire state of global warming, it is critical to investigate the elements that influence carbon emissions intensity and to precisely monitor progress in carbon emissions intensity growth in order to meet the aim of lowering CO2 emissions. This research explores the association among renewable energy and non-renewable energy consumption, the urban population, research and development expenditure, technological innovation, and carbon emissions intensity in China using annual time series data over the period 1990 to 2019. The Dynamic ARDL simulation technique was utilized to investigate the long-run and short-run correlations between renewable and non-renewable energy consumption and CEI. The results suggest that there is strong evidence of a long-run correlation between the variables. The findings indicate that in the long-run, renewable energy and non-renewable energy consumption, and research and development expenditure have a positive influence on CEI by 0.27%, 0.75%, and 0.21%, whereas the urban population has a negative influence by 2.31%, respectively. However, the urban population and technological innovation have positively affected the short-run CEI by 12.17% and 0.23%, respectively. Policies should focus on continuous investment in renewable energy sources, clean energy innovation, improving energy efficiency, forest restoration, and carbon neutrality initiatives to lessen the environmental extreme pressure associated with CO2 emissions.

Exploring the impact of carbon emissions and co-macroeconomic determinants on China's sustainable apple export.

China is the foremost global consumer, producer, and exporter of fresh apples. In 2021, China produced roughly 44 million tons of apples and exported just over 1 million tons, a nearly 2% increase over the previous year. However, the ongoing COVID-19 pandemic has had a detrimental impact on global trade and has led to a decrease in China's agricultural exports. The present study aims to contribute to the existing body of literature by analyzing plausible macroeconomic determinants that might impact China's apple exports. We used novel dynamic autoregressive distributed lag (DYARDL) simulations to model causal relationships among fundamental economic parameters. We made use of annual time series data from 1990 to 2020 from the World Bank and China's national statistical bureau. We found that increases in apple orchard area, apple production, and trade openness had a positive impact on apple exports over both the short and long term. Conversely, decreases in the prices of exported apples, agrochemicals, and carbon emissions in the agricultural sector had a positive impact on the long-term and short-term exportation of apples. Finally, we note that pictographic illustrations from the DYARDL simulations provide corroborative evidence for our findings. Based on the study results, this study proposes that the adoption of technological advancements in apple orchards could potentially enhance apple production while simultaneously upholding environmental sustainability.

Can environmentally friendly technology help China to achieve a carbon neutrality target by 2060? An asymmetrical based study in China.

Climate change-related environmental challenges are prompting an increasing number of countries to set carbon-neutral targets. Since 2007, China has pursued numerous initiatives to attain carbon neutrality by 2060, including increasing the percentage of non-fossil energy, developing zero-emission and low-emission technologies, and taking actions that reduce CO2 emissions or boost carbon sinks. As a result, utilizing quarterly data from 2008/Q1 to 2021/Q4, and applying the nonlinear autoregressive distributed lag (NARDL) approach, this study evaluates the effectiveness of the measures taken by China to improve the ecological situation. The results of the study show that the measures enacted to reduce CO2 emissions did not accomplish their ultimate purpose. Specifically: (i) high-speed railways and new energy vehicles do not improve the environment in the long run; (ii) investments and patents in the energy sector, as well as low-carbon sources, will degrade the environment; (iii) only investments in the treatment of environmental pollution will improve the ecological situation. Various policy implications are suggested based on the empirical results in order to attain environmental sustainability.

Asymmetric effect of electricity consumption on CO2 emissions in the USA: analysis of end-user electricity consumption by nonlinear quantile approaches.

The study examines the asymmetric effect of electricity consumption on carbon dioxide (CO2) emissions by analyzing end-user groups. In this context, the study focuses on the USA, which is the largest economy. The study includes the most available monthly data from January 1973 to November 2021, performs nonlinear quantile approaches as Granger causality-in-quantiles, nonparametric causality-in-quantiles, and quantile-on-quantile regression (QQR). Besides, quantile regression (QR) approach is used for robustness checks. The empirical results show that (i) correlation relationship between the electricity consumption and CO2 emissions changes according to the terms; (ii) there are generally causality effects in quantiles excluding some lower (0.05, 0.25), middle (0.70, 0.75), and high (0.95) quantiles, while the results for end-user groups vary; (iii) similarly, there is nonparametric causality from the end-user electricity consumption indicators to the CO2 emissions for the mean (return) and the variance (volatility) in most of the quantiles excluding some; (iv) the effects of the electricity consumption indicators on the CO2 emissions are higher in lower quantiles; (v) the QR results show the robustness of the QQR results. Overall, the effects of the electricity consumption indicators on the CO2 emissions are asymmetric and change according to the terms, quantiles, mean, variance, and end-user groups. Furthermore, policy implications are discussed.

The impact of economic growth, energy consumption, trade openness, and financial development on carbon emissions: empirical evidence from Malaysia.

Globally, the rising concentration of anthropogenic greenhouse gases emission in the atmosphere is extremely detrimental to the environment. The high concentration among all greenhouse gases is carbon dioxide emission. Therefore, this study explores the linkages between energy consumption, trade openness, globalization, urbanization, and carbon dioxide emission for Malaysia over the spans from 1978 to 2018. ARDL bound testing model was employed to investigate involvement in the elevation of carbon dioxide emissions in the economy. The study illustrates that a 1% growth in energy consumption, trade openness, and urbanization will deteriorate the environment by 0.18%, 0.03%, and 2.51% respectively. Further, variance decomposition analysis predicts that all the determinants in the study have significantly caused carbon dioxide emission in Malaysia. The paper presents scientific support for further studies and argues for the use of innovation shocks as a policy instrument for a prosperous future by formulating more successful environmental policies.

Climate change impacts on agriculture sector: A case study of Pakistan / Impactos das mudanças climáticas no setor agrícola: um estudo de caso do Paquistão

ABSTRACT: The current article looks at the effects of climate change on agriculture, especially crop production, and influence factors of agricultural development in terms of their rational use in Pakistan. Due to the dependence of economic development, and agriculture in the South Asian region on access to renewable national resources and the associated vulnerability to climate change, the limited financial and professional resources of the Islamic Republic of Pakistan require a clear definition of national priorities in this area. In the preparation of this article, general scientific cognition methods, in particular, empirical-theoretical methods were used. Grouping and classification methods have been used to process and systematize the data. The ability to change productivity, depending on the variation of the average annual air temperature and the average annual precipitation rate, was considered using a two-factor regression model. The main finding of the study is that temperature and precipitation have a negative impact on agricultural production. This study can provide a scientific justification for the specialization of agricultural production in the regions of Pakistan as well as the execution of the necessary agricultural activities.

RESUMO: O objetivo deste artigo é examinar os efeitos das mudanças climáticas na agricultura, especialmente a produção agrícola e os fatores de influência do desenvolvimento agrícola em termos de uso racional no Paquistão. Devido à dependência do desenvolvimento econômico e da agricultura na região do sul da Ásia do acesso a recursos nacionais renováveis ​​e à vulnerabilidade associada às mudanças climáticas, os recursos financeiros e profissionais limitados da República Islâmica do Paquistão exigem uma definição clara das prioridades nacionais nessa área. Na preparação deste artigo, foram utilizados métodos gerais de cognição científica, em particular métodos teórico-empíricos. Os métodos de agrupamento e classificação foram utilizados para processar e sistematizar os dados. A capacidade de alterar a produtividade, dependendo da variação da temperatura média anual do ar e da taxa média anual de precipitação, foi considerada usando um modelo de regressão de dois fatores. A principal descoberta do estudo é que a temperatura e a precipitação têm um impacto negativo na produção agrícola. Este estudo pode fornecer uma justificativa científica para a especialização da produção agrícola nas regiões do Paquistão, bem como a execução das atividades agrícolas necessárias.