Economic growth,electricity consumption,urbanization and environmental degradation relationship in United Arab Emirates

The present study explores the relationship between economic growth, electricity consumption, urbanization and environmental degradation in case of United Arab Emirates (UAE). The study covers the quarter frequency data over the period of 1975–2011. We have applied the ARDL bounds testing approach to examine the long run relationship between the variables in the presence of structural breaks. The VECM Granger causality is applied to investigate the direction of causal relationship between the variables. Our empirical exercise reported the existence of cointegration among the series. Further, we found an inverted U-shaped relationship between economic growth and CO₂ emissions i.e. economic growth raises energy emissions initially and declines it after a threshold point of income per capita (EKC exists). Electricity consumption declines CO₂ emissions. The relationship between urbanization and CO₂ emissions is positive. Exports seem to improve the environmental quality by lowering CO₂ emissions. The causality analysis validates the feedback effect between CO₂ emissions and electricity consumption. Economic growth and urbanization Granger cause CO₂ emissions.     

Testing environmental Kuznets curve hypothesis: The role of renewable and non-renewable energy consumption and trade in OECD countries

This paper investigates the causal relationships between per capita CO₂ emissions, gross domestic product (GDP), renewable and non-renewable energy consumption, and international trade for a panel of 25 OECD countries over the period 1980–2010. Short-run Granger causality tests show the existence of bidirectional causality between: renewable energy consumption and imports, renewable and non-renewable energy consumption, non-renewable energy and trade (exports or imports); and unidirectional causality running from: exports to renewable energy, trade to CO₂ emissions, output to renewable energy. There are also long-run bidirectional causalities between all our considered variables. Our long-run fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) estimates show that the inverted U-shaped environmental Kuznets curve (EKC) hypothesis is verified for this sample of OECD countries. They also show that increasing non-renewable energy increases CO₂ emissions. Interestingly, increasing trade or renewable energy reduces CO₂ emissions. According to these results, more trade and more use of renewable energy are efficient strategies to combat global warming in these countries.     

Do nuclear and renewable energy improve the environment? Empirical evidence from the United States

The central focus of this article is to assess the dynamic effects of nuclear and renewable energy consumption on CO₂ emissions, for a given level of income and energy consumption. We apply an autoregressive distributed lag (ARDL) approach to cointegration to U.S. data from 1960 to 2010. We find that nuclear energy consumption indeed reduces CO₂ emissions in both the short- and long-run, while renewable energy consumption does only in the short-run. We also find that income increases CO₂ emissions in the long-run after showing the environmental Kuznets curve (EKC) initially in the short-run. Finally, energy consumption is found to have a negative impact on reducing CO₂ emissions in the short- and long-run.     

CO2, economic growth,and energy consumption in China's provinces: Investigating the spatiotemporal and econometric characteristics of China's CO2 emissions

This study addresses the spatiotemporal variations at play in China's CO₂ emissions, based on an estimation of emission levels in the period 1995–2012 and an provincial analysis of the relationship of CO₂ emissions to economic growth and energy consumption. Using a series of econometric models and data on the combustion of fossil fuels and cement manufacturing, the study first estimated CO₂ emission levels during the study period, exploring their spatiotemporal pattern. The results indicate that both China's total and its per capita CO₂ emissions have increased significantly over the study period, with both measures evidencing a similar evolution (albeit one that is characterized by noticeable regional discrepancies at the provincial level and which displays properties of convergence). From a geographical perspective, we found both total and per capita CO₂ emissionsto be higher in China's eastern region than in the country's central and western regions. Panel data analysis was subsequently undertaken in order to quantify the dynamic casual relationship between economic growth, energy consumption, and CO₂ emissions. The empirical results indicated that the variables were in fact cointegrated and exhibited a long-run positive relationship. The results of further Granger causality tests indicated the existence of a bidirectional positive causality between economic growth and energy consumption, as well as between energy consumption and CO₂ emissions, and a unidirectional positive causality running from economic growth to CO₂ emissions. The findings of this study suggest that China is, in the long run, dependent on carbon energy consumption for its rapid economic growth, a dependency which is the cause of considerable increases in CO₂ emissions. China should therefore make greater efforts to develop low-carbon technologies and renewable energy, and improve energy efficiency in order to reduce emissions and achieve green economic growth.     

The impact of trade openness on global carbon dioxide emissions: Evidence from the top ten emitters among developing countries

This study aims to analyze the relationship between carbon dioxide (CO₂) emissions, trade openness, real income and energy consumption in the top ten CO₂ emitters among the developing countries; namely China, India, South Korea, Brazil, Mexico, Indonesia, South Africa, Turkey, Thailand and Malaysia over the period of 1971–2011. In addition, the possible presence of the EKC hypothesis is investigated for the analyzed countries. The Zivot–Andrews unit root test with structural break, the bounds testing for cointegration in the presence of structural break and the VECM Granger causality method are employed. The empirical results indicate that (i) the analyzed variables are co-integrated for Thailand, Turkey, India, Brazil, China, Indonesia and Korea, (ii) real income, energy consumption and trade openness are the main determinants of carbon emissions in the long run, (iii) there exists a number of causal relations between the analyzed variables, (iv) the EKC hypothesis is validated for Turkey, India, China and Korea. Robust policy implications can be derived from this study since the estimated models pass several diagnostic and stability tests.     

Climate change and its impacts on Vietnam agriculture: A macroeconomic perspective

Vietnam is an important contributor to the world's food industry as a major exporter of rice, seafood, and coffee. Climate change poses a serious threat to Vietnam's agricultural sector since it adversely affects food security in Vietnam and globally. This study investigates the short- and long-term effects of climate change on Vietnam's agriculture, both in terms of production and values at the macro level. Using the Autoregressive Distributed Lag (ARDL) model and the Toda-Yamamoto (1995) Granger causality test with annual data from 1990 to 2019, we confirm the detrimental impacts of global warming on Vietnam's agricultural performance in both the short and long term. We also reveal the favorable effects of CO₂ emissions, land, and fertilizer on Vietnam's agricultural production and economics. Other factors, including rainfall and labor, however, adversely affect Vietnam's agricultural output and economic performance. Based on the study's results, we provide policy recommendations to assist the government limit the negative effects of climate change on the national economy, thereby promoting poverty alleviation and sustainable development in Vietnam.     

Does energy intensity contribute to CO2 emissions? A trivariate analysis in selected African countries

The present study investigates the dynamic relationship between energy intensity and CO₂ emissions by incorporating economic growth in environment CO₂ emissions function using data of Sub Saharan African countries. For this purpose, we applied panel cointegration to examine the long run relationship between the series. We employed the VECM Granger causality to test the direction of causality amid the variables.At panel level, our results validate the existence of cointegration among the series. The long run panel results show that energy intensity has positive and statistically significant impact on CO₂ emissions. There is also positive and negative link of non-linear and linear terms of real GDP per capita with CO₂ emissions supporting the presence of environmental Kuznets curve (EKC). The causality analysis reveals the bidirectional causality between economic growth and CO₂ emissions while energy intensity Granger causes economic growth and hence CO₂ emissions, while across the individual countries, the results differ. This paper opens up new insights for policy makers to design comprehensive economic, energy and environmental policy for sustainable long run economic growth.     

Climate change and the fate of cereal aphids in Southern Britain

Climate change will drive dramatic changes in the abundance and distribution of species. Assessing the impacts of climate change on our agricultural systems is essential for mitigation planning. Here, I combine projections from the UK Hadley Centre's HadRM03 climate change model for Southern Britain with a general mechanistic model of the interaction between climate, temperate grass physiology and cereal aphid population dynamics. Aphids are one of the largest and most important groups of crop pests and disease vectors worldwide but particularly in temperate regions. The model predicts an increasingly dramatic decline in cereal aphid abundance from the 1961 to 1990 baseline with increasing CO₂ emissions: low emissions=?5%, medium low=?12%, medium high=?61%, and high=?92%. Of the six climate variables used in the model, changes in temperature and rainfall were the most important across all emissions scenarios and, counter‐intuitively, the direct impact of elevated CO₂ actually declines as emissions increase. The results suggest that the pest status of cereal aphids in Southern Britain will significantly decline by the end of this century.     

The linkages between deforestation,energy and growth for environmental degradation in Pakistan

This study explores the validation of the Environmental Kuznets Curve (EKC) hypothesis for Pakistan using time series data from 1980–2013 with deforestation as an indicator (dependent variable) for environmental degradation, and four independent variables (economic growth, energy consumption, trade openness, and population) were also examined. The Autoregressive Distributed Lag (ARDL) bounds testing approach to cointegration and the VECM–Granger causality test were applied. The results confirmed the existence of cointegration among the variables both in long- and short-run paths. However, the diminishing negative impact of economic growth on deforestation in the long-run confirms the EKC hypothesis for deforestation in Pakistan. Moreover, economic growth and energy consumption Granger cause deforestation. A bidirectional causal effect is detected between economic growth and energy consumption, however, in the long-run, economic growth and trade openness Granger cause energy consumption. This study was designed with several significant tests to ensure the reliability of results for policy use and to contribute to future studies on the environment-growth-energy nexus.     

Does globalization impede environmental quality in India?

Using annual data for the period 1970–2012, the study explores the relationship between globalization and CO₂ emissions by incorporating energy consumption, financial development and economic growth in CO₂ emission function for India. It applies Lee and Strazicich (2013) unit root test for examining the stationary properties of variables in presence of structural breaks and employs the cointegration method proposed by Bayer and Hanck (2013) to test the long-run relationships in the model. The robustness s of cointegration result from the latter model was further verified with the application of the ARDL bounds testing approach to cointegration proposed by Pesaran et al. (2001). After confirming the existence of conitegration, the overall long run estimates of the estimation of carbon emission model points out that acceleration in the process of globalization (measured in its three dimensions – economic, social and political globalizations) and energy consumption result in increasing CO₂ emissions, along with the contribution of economic development and financial development toward the deterioration of the environmental quality by raising CO₂ emissions over the long-run. This finding validates the holding of environmental Kuznets curve (EKC) hypothesis for the Indian context.     

The renewable energy-growth nexus with carbon emissions and technological innovation: Evidence from the Nordic countries

Despite the fact that previous studies have extensively investigated the renewable energy-growth nexus, those studies have not considered the role of technological innovation. This study examines the relationship between renewable energy consumption, technological innovation, economic growth, and CO₂ emissions in the four Nordic countries by constructing a vector autoregression (VAR) model. On the basis of a modified version of the Granger non-causality test, the results show a unidirectional causality running from renewable energy to CO₂ emissions for Denmark and Finland and a bidirectional causality between these variables for Sweden and Norway. The findings also indicate a unidirectional causality running from technological innovation to renewable energy and from growth to renewable energy for the four Nordic countries. The results could not confirm any causality from renewable energy to growth. Three policy implications are offered: (i) renewable energy improves environmental well-being, (ii) the Nordic countries have very low energy intensities and high energy efficiencies, and (iii) technological innovation plays an effective role in the renewable energy-growth nexus.     

Impact of Grazing Intensity and Seasons on Greenhouse Gas Emissions in Tropical Grassland

Greenhouse gases (GHG) can be affected by grazing intensity, soil, and climate variables. This study aimed at assessing GHG emissions from a tropical pasture of Brazil to evaluate (i) how the grazing intensity affects the magnitude of GHG emissions; (ii) how season influences GHG production and consumption; and (iii) what are the key driving variables associated with GHG emissions. We measured under field conditions, during two years in a palisade-grass pasture managed with 3 grazing intensities: heavy (15 cm height), moderate (25 cm height), and light (35 cm height) N₂O, CH₄ and CO₂ fluxes using static closed chambers and chromatographic quantification. The greater emissions occurred in the summer and the lower in the winter. N₂O, CH₄, and CO₂ fluxes varied according to the season and were correlated with pasture grazing intensity, temperature, precipitation, % WFPS (water-filled pores space), and soil inorganic N. The explanatory variables differ according to the gas and season. Grazing intensity had a negative linear effect on annual cumulative N₂O emissions and a positive linear effect on annual cumulative CO₂ emissions. Grazing intensity, season, and year affected N₂O, CH₄, and CO₂ emissions. Tropical grassland can be a large sink of N₂O and CH₄. GHG emissions were explained for different key driving variables according to the season.     

Nitrogen-Use Efficiency,Nitrous Oxide Emissions,and Cereal Production in Brazil: Current Trends and Forecasts

The agriculture sector has historically been a major source of greenhouse gas (GHG) emissions into the atmosphere. Although the use of synthetic fertilizers is one of the most common widespread agricultural practices, over-fertilization can lead to negative economic and environmental consequences, such as high production costs, depletion of energy resources, and increased GHG emissions. Here, we provide an analysis to understand the evolution of cereal production and consumption of nitrogen (N) fertilizers in Brazil and to correlate N use efficiency (NUE) with economic and environmental losses as N₂O emissions. Our results show that the increased consumption of N fertilizers is associated with a large decrease in NUE in recent years. The CO₂ eq. of N₂O emissions originating from N fertilization for cereal production were approximately 12 times higher in 2011 than in 1970, indicating that the inefficient use of N fertilizers is directly related to environmental losses. The projected N fertilizer forecasts are 2.09 and 2.37 million ton for 2015 and 2023, respectively. An increase of 0.02% per year in the projected NUE was predicted for the same time period. However, decreases in the projected CO₂ eq. emissions for future years were not predicted. In a hypothetical scenario, a 2.39% increase in cereal NUE would lead to $ 21 million savings in N fertilizer costs. Thus, increases in NUE rates would lead not only to agronomic and environmental benefits but also to economic improvement.     

Environmental Kuznets Curve hypothesis and the role of globalization in selected African countries

The present study incorporates globalization and energy intensity into the CO₂ emissions function and investigates the presence of Environmental Kuznets Curve (EKC) in 19 African countries for the time period of 1971–2012. We have applied the ARDL bounds testing approach for cointegration to examine the long run relationship in the variables. Our results confirmed the presence of cointegration between the series in Africa, Algeria, Angola, Cameroon, Congo Republic, Ghana, Kenya, Libya, Morocco, Nigeria, South Africa, Sudan, Tanzania, Togo, Tunisia, Zambia and Zimbabwe. The results indicated the positive effect of energy intensity on CO₂ emissions in Africa, Algeria, Angola, Cameroon, Congo Republic, Ghana, Kenya, Libya, Morocco, Nigeria, South Africa, Sudan, Togo, and Tunisia while energy intensity declines CO₂ emissions in the case of Zambia and Zimbabwe. Globalization decreases CO₂ emissions in Africa, Angola, Cameroon, Congo Republic, Egypt, Kenya, Libya, Tunisia and Zambia but increases CO₂ emissions in Ghana, Morocco, South Africa, Sudan and Tanzania. The EKC exists in Africa, Algeria, Cameroon, Congo Republic, Morocco, Tunisia and Zambia but U-shaped relationship is found between economic growth and CO₂ emissions in Sudan and Tanzania.     

Estimating the environmental Kuznets curve for Spain by considering fuel oil prices (1874–2011)

We perform a structural analysis on an environmental Kuznets curve (EKC) for Spain by exploiting long time series (1874–2011) and by using real oil prices as an indicator of variations in fuel energy consumption. This empirical strategy allows us to both, capture the effect of the most pollutant energy on carbon dioxide (CO₂) emissions and, at the same time, preclude potential endogeneity problems derived from the direct inclusion of fuel consumption in econometric specification. Knowing the extent to which oil prices affect CO₂ emissions has a straightforward application for environmental policy. The dynamics estimates of the long and short-term relationships among CO₂, economic growth and oil prices are built through an autoregressive distributed lag (ARDL) model. Our test results support the EKC hypothesis. Moreover, real oil prices are clearly revealed as a valuable indicator of pollutant energy consumption.     

Assessing the impacts of meteorological factors on soybean production in China: What role can agricultural subsidy play?

Cereal and oilseed crops possess significance in meeting global food security. China, housing the most number of people, remains the top importer of oilseed crops (i.e., soybeans) to produce energy and meet its food needs. With such significance, the present study investigates the impact of meteorological factors on soybean production in China using the annual data from 1978 to 2020. It also incorporated other essential determinants of soybean production, such as agricultural subsidy, cultivated area, and fertilizer use. For data analysis, it employed the autoregressive distributed lag (ARDL) method and the Quantile Regression (QR) technique. The findings from an ARDL model unveiled meteorological factors such as the yearly average temperature and CO₂ emissions declined soybean production in the long–run and short–run analysis, whereas the yearly average precipitation improved soybean production. Besides, agricultural subsidy, cultivated area, and fertilizer use also enhanced soybean production in the long–and short–run analyses. In addition, the findings from the Quantile Regression (QR) technique showed that temperature and CO₂ emissions negatively affected soybean production in each quantile (i.e., 0.1–0.90), while precipitation and agricultural subsidy positively augmented soybean production across all quantiles (i.e., 0.1–0.90). Based on these results, the study provides clear policy implications, such as governments should provide crop-specific subsidies instead of input-based subsidies to embolden the impact of agricultural subsidies. Also, ecological improvement campaigns should be launched to attract farmers' attention to sustainable agriculture practices to meet meteorological challenges.     

Impacts of climate change on paddy rice yield in a temperate climate

The crop simulation model is a suitable tool for evaluating the potential impacts of climate change on crop production and on the environment. This study investigates the effects of climate change on paddy rice production in the temperate climate regions under the East Asian monsoon system using the CERES‐Rice 4.0 crop simulation model. This model was first calibrated and validated for crop production under elevated CO₂ and various temperature conditions. Data were obtained from experiments performed using a temperature gradient field chamber (TGFC) with a CO₂ enrichment system installed at Chonnam National University in Gwangju, Korea in 2009 and 2010. Based on the empirical calibration and validation, the model was applied to deliver a simulated forecast of paddy rice production for the region, as well as for the other Japonica rice growing regions in East Asia, projecting for years 2050 and 2100. In these climate change projection simulations in Gwangju, Korea, the yield increases (+12.6 and + 22.0%) due to CO₂ elevation were adjusted according to temperature increases showing variation dependent upon the cultivars, which resulted in significant yield decreases (?22.1% and ?35.0%). The projected yields were determined to increase as latitude increases due to reduced temperature effects, showing the highest increase for any of the study locations (+24%) in Harbin, China. It appears that the potential negative impact on crop production may be mediated by appropriate cultivar selection and cultivation changes such as alteration of the planting date. Results reported in this study using the CERES‐Rice 4.0 model demonstrate the promising potential for its further application in simulating the impacts of climate change on rice production from a local to a regional scale under the monsoon climate system.     

Exploiting Co-Benefits of Increased Rice Production and Reduced Greenhouse Gas Emission through Optimized Crop and Soil Management

Meeting the future food security challenge without further sacrificing environmental integrity requires transformative changes in managing the key biophysical determinants of increasing agronomic productivity and reducing the environmental footprint. Here, we focus on Chinese rice production and quantitatively address this concern by conducting 403 on-farm trials across diverse rice farming systems. Inherent soil productivity, management practices and rice farming type resulted in confounded and interactive effects on yield, yield gaps and greenhouse gas (GHG) emissions (N₂O, CH₄ and CO₂-equivalent) with both trade-offs and compensating effects. Advances in nitrogen, water and crop management (Best Management Practices—BMPs) helped closing existing yield gaps and resulted in a substantial reduction in CO₂-equivalent emission of rice farming despite a tradeoff of increase N₂O emission. However, inherent soil properties limited rice yields to a larger extent than previously known. Cultivating inherently better soil also led to lower GHG intensity (GHG emissions per unit yield). Neither adopting BMPs only nor improving soils with low or moderate productivity alone can adequately address the challenge of substantially increasing rice production while reducing the environmental footprint. A combination of both represents the most efficient strategy to harness the combined-benefits of enhanced production and mitigating climate change. Extrapolating from our farm data, this strategy could increase rice production in China by 18%, which would meet the demand for direct human consumption of rice by 2030. It would also reduce fertilizer nitrogen consumption by 22% and decrease CO₂-equivalent emissions during the rice growing period by 7% compared with current farming practice continues. Benefits vary by rice-based cropping systems. Single rice systems have the largest food provision benefits due to its wider yield gap and total cultivated area, whereas double-rice system (especially late rice) contributes primarily to reducing GHG emissions. The study therefore provides farm-based evidence for feasible, practical approaches towards achieving realistic food security and environmental quality targets at a national scale.     

Implications of CO2 fertilization for future climate change in a coupled climate–carbon model

The terrestrial carbon cycle plays a critical role in determining levels of atmospheric CO₂ that result from anthropogenic carbon emissions. Elevated atmospheric CO₂ is thought to stimulate terrestrial carbon uptake, through the process of CO₂ fertilization of vegetation productivity. This negative carbon cycle feedback results in reduced atmospheric CO₂ growth, and has likely accounted for a substantial portion of the historical terrestrial carbon sink. However, the future strength of CO₂ fertilization in response to continued carbon emissions and atmospheric CO₂ rise is highly uncertain. In this paper, the ramifications of CO₂ fertilization in simulations of future climate change are explored, using an intermediate complexity coupled climate–carbon model. It is shown that the absence of future CO₂ fertilization results in substantially higher future CO₂ levels in the atmosphere, as this removes the dominant contributor to future terrestrial carbon uptake in the model. As a result, climate changes are larger, though the radiative effect of higher CO₂ on surface temperatures in the model is offset by about 30% due to reduced positive dynamic vegetation feedbacks; that is, the removal of CO₂ fertilization results in less vegetation expansion in the model, which would otherwise constitute an important positive surface albedo‐temperature feedback. However, the effect of larger climate changes has other important implications for the carbon cycle – notably to further weaken remaining carbon sinks in the model. As a result, positive climate–carbon cycle feedbacks are larger when CO₂ fertilization is absent. This creates an interesting synergism of terrestrial carbon cycle feedbacks, whereby positive (climate–carbon cycle) feedbacks are amplified when a negative (CO₂ fertilization) feedback is removed.     

Effects of Climate Change Drivers on Nitrous Oxide Fluxes in an Upland Temperate Grassland

Despite increasing interest in the patterns of trace gas emissions in terrestrial ecosystems, little is known about the impacts of climate change on nitrous oxide (N₂O) fluxes. The aim of this study was to determine the importance of the three main drivers of climate change (warming, summer drought, and elevated CO₂ concentrations) on N₂O fluxes from an extensively managed, upland grassland. Over a 2-year period, we monitored N₂O fluxes in an in situ ecosystem manipulation experiment simulating the climate predicted for the study area in 2080 (3.5°C temperature increase, 20% reduction in summer rainfall and atmospheric CO₂ levels of 600 ppm). N₂O fluxes showed significant seasonal and interannual variation irrespective of climate treatment, and were higher in summer and autumn compared with winter and spring. Overall, N₂O emissions showed a positive correlation with soil temperature and rainfall. Elevated temperature had a positive impact on mean annual N₂O fluxes but effects were only significant in 2007. Contrary to expectations, neither combined summer drought and warming nor the simultaneous application of elevated atmospheric CO₂ concentrations, summer drought and warming had any significant effect on annual N₂O fluxes. However, the maximum N₂O flux rates observed during the study occurred when elevated CO₂ was combined with warming and drought, suggesting the potential for important, short-term N₂O–N losses in enriched CO₂ environments. Taken together, our results suggest that the N₂O responses of temperate, extensively managed grasslands to future climate change scenarios may be primarily driven by temperature effects.