Exploring the capacity of renewable energy consumption to reduce outdoor air pollution death rate in Latin America and the Caribbean region

Abstract

The impact of renewable energy consumption on reducing the outdoor air pollution death rate, in nineteen Latin America & the Caribbean countries, from 1990 to 2016, using the econometric technique of Quantile Regression for Panel Data, was researched. Results show that economic growth, and fossil fuel consumption, are positively related to CO2 emissions, while renewable energy consumption bears a negative relationship with it. Furthermore, fossil fuel consumption has a positive impact on the mortality rate and economic growth a negative one. The negative effect of renewable energy consumption on the mortality rate is only observable on the right tail of its distribution. The modelisation reveals two ways in which the consumption of renewable energy can reduce the outdoor air pollution death rates: (i) directly, by increasing renewable energies; and (i) indirectly because the increase in the consumption of renewable energies implies a decrease in the consumption of energy from fossil fuels. The phenomenon of increasing urbanisation is a point where the action of public policymakers is decisive for the reduction of outdoor air pollution death rates. Here, the question is not to reduce the level of urbanisation but to act on the "quality" of urbanisation, to make cities healthier. The research concludes that public policymakers must focus on intensifying the transition from fossil to renewable energies and improving the quality of cities.

Testing the Role of Trade on Carbon Dioxide Emissions in Portugal

“…The variable of income per capita (LogGDP) indicates a positive effect on CO 2 emissions from quartile 4 to quartile 9. This result is according to the EKC assumption (Balsalobre-Lorente et al 2021; Leitão and Lorente 2020;Ike et al 2020;Koengkan et al 2020). Table 10 presents the econometric results considering the cointegration models to test the long-run impacts of energy consumption, trade intensity, and income per capita on carbon emissions.…”

“…In this case, we observe improvements in environmental quality and pollution. According to the recent literature of Balsalobre-Lorente et al (2021), Pata and Caglar (2021), Leitão and Lorente (2020), Ike et al (2020), and Koengkan et al (2020), in the short run, there is a positive impact of income per capita on CO 2 emissions (GDP > 0); however, we expect a negative effect of income per capita (GDP < 0) on carbon dioxide emissions in the long run.…”

“…The link between economic growth and the environmental Kuznets curve (EKC) was introduced by Grossman and Krueger (1995) and Holtz-Eakin and Selden (1995), who demonstrated that economic growth is directly correlated with climate change and greenhouse gas emissions (Leitão and Lorente 2020;Ike et al 2020;Sarkodie and Ozturk 2020;Koengkan et al 2020). In the short run, the empirical research considers a positive correlation between economic growth and carbon dioxide emissions, showing that economic activities encourage environmental damage.…”

“…In the short run, the empirical research considers a positive correlation between economic growth and carbon dioxide emissions, showing that economic activities encourage environmental damage. However, in the long run, the countries and governments are preoccupied with environmental protection and their quality (Koengkan et al 2020), and pollution intensity decreases.…”

“…We observe that the empirical studies as Gessesse and He (2020), Sarkodie and Ozturk (2020), Shahbaz et al (2021), Burakov (2019), and Özokcu and Özdemir (2017) use time series (autoregressive distributed lag-ARDL model, vector error correction model-VECM, and Granger causality). Moreover, there exist other studies such as Leitão and Lorente (2020), Ike et al (2020), and Koengkan et al (2020) that applied panel data (fixed effects-FE, random effects-RE, FMOLS-fully modified ordinary least squares, DOLS-dynamic ordinary least squares, GMM-system estimator, and method of moments quantile regression).…”