Sectoral foreign direct investment and environmental degradation: new insights from diversification of energy mix containing fossil fuels and renewable energy.

The objective of the study is to extend the existing literature by investigating the effects of foreign direct investment, gross domestic products and per capita and energy diversification on the nitrogen oxide emissions in Brazil, Russia, India, China and South Africa (BRICS) by using annual data during the period 1992-2019. As per our knowledge, the present study is a first of its kind to examine the impact of a new energy diversification index, based on Herfindahl-Hirschman framework on pollution. This study has adopted a new quantile regression augmented method of moments, which is capable of producing the total impacts of the independent variables across the entire distribution of nitrogen oxides emissions. The findings suggest that an increase in foreign direct investment leads to a decrease in nitrogen oxides emissions at the aggregate level and in both manufacturing and service sectors. We observe that foreign direct investment leads to an increase in nitrogen oxides emissions in the agricultural sector in most of the quantiles. Diversification towards renewable energy causes a decrease in nitrogen oxides emissions in most quantiles at aggregate level, agricultural and manufacturing sectors, whilst diversification leads to an increase in nitrogen oxides emissions in the service sector. The findings also suggest that GDP per capita leads to an increase in NOx emissions in all the quantiles. The study suggests the policy to use and attract more clean energy through foreign direct investment for towards the achievement of sustainable development.

Effects of socioeconomic and natural factors on air pollution in China: A spatial panel data analysis.

China's energy use has increased significantly in recent years with the country's rapid economic growth and large-scale urbanization. Therefore, air pollution has become a major issue. In this study, we conducted spatial autocorrelation and spatial panel regression analyses of sulfur dioxide (SO2) and nitrogen oxide (NOX) emissions using the panel data of 31 provincial-level administrative units in China during the period 2011-2017 to comprehensively understand the factors affecting air pollutant emissions. This study contributes to the literature by considering comprehensive factors and spatial effects in the panel-data econometric framework of the whole country of China. The analysis of spatial characteristics shows that during the study period, pollutant emissions in China declined, although emissions in northern regions were still relatively high. Furthermore, SO2 and NOX emissions showed significant positive spatial autocorrelations. The results of a fixed-effect spatial lag model showed that both socioeconomic and natural factors were statistically significant for air pollutant emissions, although the degree differed by the type of pollutant. The population, the urbanization rate, the share of added value of secondary industry, and heating and cooling degree days positively affected emissions, while population density, per-capita gross regional product, precipitation, and relative humidity negatively affected emissions. Based on these results, we have put forward suggestions to address the issue of air pollution and achieve environmental sustainability, such as the promotion of regional cooperation and a transition of the economic structure.

A Spatial Panel Data Analysis of Economic Growth, Urbanization, and NOx Emissions in China.

Abstract: Is nitrogen oxides emissions spatially correlated in a Chinese context? What is the relationship between nitrogen oxides emission levels and fast-growing economy/urbanization? More importantly, what environmental preservation and economic developing policies should China's central and local governments take to mitigate the overall nitrogen oxides emissions and prevent severe air pollution at the provincial level in specific locations and their neighboring areas? The present study aims to tackle these issues. This is the first research that simultaneously studies the nexus between nitrogen oxides emissions and economic development/urbanization, with the application of a spatial panel data technique. Our empirical findings suggest that spatial dependence of nitrogen oxides emissions distribution exists at the provincial level. Through the investigation of the existence of an environmental Kuznets curve (EKC) embedded within the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework, we conclude something interesting: an inverse N-shaped EKC describes both the income-nitrogen oxides nexus and the urbanization-nitrogen oxides nexus. Some well-directed policy advice is provided to reduce nitrogen oxides in the future. Moreover, these results contribute to the literature on development and pollution.