Energy Consumption In Sectors Research Articles

Safe Insulation from the Inside as a Solution to the Energy and Climate Crisis

Along with rapid climate changes, issues related to energy efficiency and efficient use of energy are becoming more and more relevant in the EU. One of the energy-consuming sectors is buildings, which are responsible for about 40% of the EU final energy consumption and 36% of CO2 emissions. In addition to this, the current energy crisis has acutely raised the issue of energy poverty. Therefore, one of the ways to fight with energy poverty and high energy consumption in buildings is insulation from the inside. However, warming from the inside is risky due to hygrothermal processes and mold risks. This study assesses the hygrothermal performance of masonry walls with 9 interior insulation systems exposed to different external conditions in the climate chambers. Masonry walls were tested in a steady cycle, a dynamic cycle, a dynamic cycle with rain and a steady cycle as drying. Also, an identical simulation of the hygrothermal process was carried out in the DELPHIN software to compare results of both testing methods. Both vapor-open and vaportight systems were chosen as insulation systems. Results show that the hygrothermal behavior of vapor-open and vapor-tight insulation systems are different under different test cycles regarding different vapor diffusion resistance of materials. Mathematical simulations results are different from the climate chamber simulations, because of the change in material humidity, that are changing during climate chambers simulations. From this it can be concluded that mathematical simulations do not give a complete vision of hydrothermal processes, because they are dynamic, but in modeling the properties of materials are defined. The study provides valuable data on hygrothermal processes in different wall insulation systems from the inside.

Modeling, analysis and forecasting of the Jordan’s transportation sector energy consumption using artificial neural networks

Modeling, analysis and forecasting of the Jordan’s transportation sector energy consumption using artificial neural networks

The Complex Interplay Between Sectoral Energy Consumption and Economic Growth: Policy Implications for Iran and Beyond

Iran's abundant energy reserves starkly contrast with recent power and gas shortages, particularly impacting the industrial sector. Furthermore, long-term trends reveal a concerning pattern where total primary energy consumption has outpaced economic growth, doubling in recent decades. These challenges emphasize the need for a thorough evaluation of the intricate interplay between sectoral energy consumption and economic output in Iran, bearing profound policy implications. The current study employs ARDL and VECM approaches to analyze empirical long- and short-term dynamics. Regarding Iran, the results unveil causal relationships from industrial energy consumption to GDP and from GDP to energy consumption in buildings. Notably the significant positive value of elasticity of GDP with respect to industrial energy use highlights the need for nuanced energy management measures. Variations across sectors underscore the justification for recognizing industrial energy consumption as productive energy use. The results gain additional support from a panel data analysis spanning fourteen diverse countries, bearing significance for IAMs applied in climate change research. While IAMs traditionally employ total energy consumption or the sectoral energy uses collectively, as production factors, the research highlights the need to reevaluate model frameworks for potential different outcomes from established practices.

Driving forces of CO2 emissions from the transport, storage and postal sectors: A pathway to achieving carbon neutrality

In tandem with the urbanisation process, China's transport sector is currently experiencing rapid development and was ranked third out of all the industrial sectors in terms of generating CO2 emissions in 2020, which poses a huge challenge to achieving carbon neutrality. Primarily using the energy consumption data from China's transport, storage and postal sectors (TSPS) and input and output data between 2007 and 2020, this study first uses the Tapio decoupling model to evaluate the decoupling effect in the TSPS. Structural decomposition analysis is then applied to explore sectoral linkages and decompose the forces driving CO2 emissions. Additionally, we explore the main determinants of the energy structure effect and final demand in terms of energy consumption and industrial sector demand. Our results show that the target sector experienced a weak decoupling, which implies that the low-carbon transformation of this sector became increasingly apparent. Factor decomposition shows that improvements in energy intensity, energy structure and the production input and output structure have contributed significantly to reducing CO2 emissions, but these gains have been largely offset by final demand, resulting in a net reduction of 27.97 million tons from 2007 to 2020. The increased usage of low carbon forms of energy, such as natural gas, is the key driver behind the emissions reduction effect in terms of the energy structure. However, the higher final demand from the construction sector and the wholesale and retail trades are the main factors that have increased CO2 emissions. By adopting a sectoral and energy structure decomposition perspective, our study can be used to provide guidance to governments seeking to pursue carbon-reduction policies to achieve carbon peak and carbon neutrality, in the TSPS in particular.

Experimental and numerical investigation of a real-scale air to multiple PCM heat exchanger

Energy consumption by residential sectors has proliferated due to urbanization and lifestyle changes. Passive cooling and heating systems can reduce energy consumption and CO2 emissions in residential and commercial sectors. Phase change materials provide an efficient solution for passive energy storage, addressing a building's needs for free cooling and heating. These materials absorb and release heat energy, enhancing the overall efficiency of the energy management system. By employing energy storage devices, it becomes feasible to reduce and shift peak loads to off-peak hours. This study optimized the size and configuration of air-to-multiple PCM heat exchanger through the utilization of a 2D ANSYS (Fluent 19.2) model. This study employs multiple phase change materials (PCMs) with varying melting temperatures as a heat transfer technique to reduce the melting and solidifying times of the PCMs. Furthermore, it was observed that the arrangement of PCMs in series affected melting and solidification times, so two scenarios have been examined. The air-to-multiple PCM system has been investigated through numerical simulations and experimental analyses, focusing on the liquid fractions within the PCM and the outlet air temperatures across the air channels. The total time for entirely melting PCMs RT25HC and RT21HC is less than 4 h, but the solidification time for PCM-RT21HC needs more than 12 h. In both scenarios, PCM-RT21HC melted first, while PCM-RT25HC solidified first.

REVIEWING THE ROLE OF ARTIFICIAL INTELLIGENCE IN ENERGY EFFICIENCY OPTIMIZATION

Artificial intelligence (AI) is revolutionizing the field of energy efficiency optimization by enabling advanced analysis and control of energy systems. This review provides a concise overview of the role of AI in enhancing energy efficiency. AI technologies, such as machine learning and neural networks, are being increasingly applied to optimize energy consumption in various sectors, including buildings, transportation, and industrial processes. These technologies analyze vast amounts of data to identify patterns and trends, enabling more precise control of energy systems and the prediction of energy demand. One of the key advantages of AI in energy efficiency optimization is its ability to adapt and learn from data, leading to continuous improvement in energy-saving strategies. AI algorithms can optimize energy consumption based on factors such as weather conditions, occupancy patterns, and energy prices, resulting in significant cost savings and environmental benefits. Furthermore, AI enables the integration of renewable energy sources into existing energy systems by predicting renewable energy generation and optimizing its use. This integration helps reduce reliance on fossil fuels and mitigates greenhouse gas emissions, contributing to a more sustainable energy future. However, the implementation of AI in energy efficiency optimization is not without challenges. These include data privacy concerns, the need for specialized skills to develop and deploy AI solutions, and the complexity of integrating AI systems into existing energy infrastructure. Addressing these challenges will be crucial for realizing the full potential of AI in energy efficiency optimization. In conclusion, AI holds great promise for enhancing energy efficiency by enabling more intelligent control and optimization of energy systems. By leveraging AI technologies, organizations can achieve significant energy savings, reduce costs, and contribute to a more sustainable and resilient energy future.
 Keywords: Role, AI, Energy, Efficiency, Optimization.

Investigation into the Environmental Sustainability Actions Adapted by Small and Medium Enterprises of the Accommodation and Tour Operator Sectors of Sri Lanka

Tourism is a key driver of development for many countries, including Sri Lanka. In 2018, it generated USD 4.38 million in foreign exchange, contributed by 4.9 percent to the GDP, and generated over 380,000 direct and indirect employment opportunities. The contribution of Small and Medium Enterprises (SMEs) to this industry prevents economic leakages and increases the multiplier effect. The tourism industry also can destroy the very environment it depends on for sustenance, through heavy emissions from energy use and waste production. Research has highlighted the importance of the quality of the environment as a pull factor for destination profitability in the long run. The tourism transport-related emissions for Sri Lanka are high, the accommodation sector's GHG emissions at 3 percent is more than the global average of 1%, indicating major areas for improvement. With the accommodation sector's energy consumption predicted to surpass that of the industrial sector, the attention given to sustainable tourism practices by the SMEs that make up the industry must be investigated. In that context, this research aims to investigate the energy-saving and waste-reduction practices towards emission reduction, adopted by the Tour Operator (TO) and Accommodation Provider (AP) SMEs in the tourism industry of Sri Lanka. To do so, a qualitative methodology was adopted with a narrative inquiry over a virtual platform with 06 TOs and 17 APs identified through convenience sampling, and data analysis performed through thematic content analysis technique. Notable results for AP revealed that 12 APs consume electricity off the grid, with solar energy utilization still being limited to obtaining hot water for guest bathrooms for 5 APs, due to the high initial cost involved, and lack of adequate technical know-how in solar battery maintenance (3Aps in Tissamaharama). Poor government support towards renewable energy discouraged 17 APs from adopting the same. Energy use for TO is minimized through the use of hybrid along with conventional fossil-fuel-powered vehicles for tours. Single-use plastic items reintroduced during the COVID-19 pandemic for AP are gradually being replaced by reusable glass bottles, wooden/ metal cutlery, and paper/metal straws. All AP practice waste segregation, and the 3R concept (reduce, reuse, recycle). 4 TOs provide reusable metal bottles that are refilled during the tour using larger water cans and a handheld pump. As the sustainable practices of TO are currently optional, it is recommended to include sustainability criteria into registration process with the SLTDA. For AP it is recommended for the government to play a more active facilitating role in the renewable energy sector and to ensure the skills requirement for device maintenance is promptly met.
 
 Keywords: Small and medium enterprises, Sustainable tourism development, Energy saving practices, Waste reduction

Unveiling the Spatial-Temporal Characteristics and Driving Factors of Greenhouse Gases and Atmospheric Pollutants Emissions of Energy Consumption in Shandong Province, China

As the largest energy-consuming province in China, Shandong faces the dual task of greenhouse gas (GHG) reduction and atmospheric pollution control. Based on the latest activity data and updated emission factors, this study establishes a high-resolution emission inventory (5 km × 5 km) for GHGs and main atmospheric pollutants from the energy consumption sectors of Shandong Province from 2010 to 2021, quantifies the relationship between social economic factors and GHGs and atmospheric pollutants emissions using the expanded stochastic environmental impact assessment (STIRPAT) model, and forecasts the future emission trend with the help of the scenario analysis method. Results indicate that the electricity and transportation sectors are the main contributors to all pollutants. Spatially, the high value of pollutants is mainly concentrated in the urban agglomerations of central and eastern Shandong. Up to 72% of GHGs and 50% of air pollution emissions are attributed to the top 10% of emission grids. Emission peaks occur mainly in summer and winter due to straw burning, increased utilization of temperature-controlled facilities, and expansion of plant capacity. Population, energy consumption, the proportion of secondary industry, and energy consumption intensity are the most significant influencing factors for pollutant emissions. Scenario analysis results indicate Shandong province can reach its carbon peak in 2027 without sacrificing population growth or economic progress.

Comparative life cycle assessment of light frame timber and reinforced concrete masonry structural systems for single-family houses in Luxembourg

The building sector's significant greenhouse gas emissions and energy consumption present added challenges to meeting European climate commitments amidst rapid population growth. In Luxembourg, single-family houses dominate the residential buildings, noticeably contributing to construction waste and CO2 emissions. This study compares the environmental impacts of a three-story reinforced concrete masonry single-family house and an identical timber building in Luxembourg, emphasizing greenhouse gas emissions and embodied energy. A cradle-to-grave life cycle assessment was conducted using Building Information Modelling (BIM) models to analyze the global warming potential and primary energy requirements. Environmental product declarations from the producers and the ÖKOBAUDAT German database were used to determine the environmental impacts of the materials. The results show that the timber building outperforms the concrete building with a 43.5% lower global warming potential, while the concrete building demonstrates a 15.6% reduction in primary energy demand. This aligns with the average outcomes of seven similar studies discussed in this paper, at 33.2% and 4.7%, respectively. Moreover, the timber building is 78.6% lighter than the concrete one. When evaluating benefits and loads beyond the system boundary, the timber building provides 3.6 and 4 times greater advantages in terms of global warming potential and primary energy, respectively, compared to the reinforced concrete masonry building. Additionally, the study explores the impact of reusing the floors in the timber building. The cradle-to-grave LCA reveals that reusing the timber slabs improves the building's global warming potential and primary energy by 2.4% and 1.2%, respectively. However, when considering the benefits and loads beyond the system boundary, floor system reuse exhibits a 38.9% surge in global warming advantages while reducing primary energy benefits by 28.1%. The findings advocate for a policy promoting timber construction and reuse in Luxembourg, aiming to achieve the net-zero emission target by 2050.

Exploring the relationship between economic diversification and energy-related CO2 emissions in a petroleum-producing country

Purpose This study aims to quantify sectoral energy and carbon intensity, revisit the validity of the Environmental Kuznets Curve (EKC) and explore the relationship between economic diversification and CO2 emissions in Bahrain. Design/methodology/approach Three stages were followed to understand the linkages between sectoral economic growth, energy consumption and CO2 emissions in Bahrain. Sectoral energy and carbon intensity were calculated, time series data trends were analyzed and two econometric models were built and analyzed using the autoregressive distributed lag method and time series data for the period 1980–2019. Findings The results of the analysis suggest that energy and carbon intensity in Bahrain’s industrial sector is higher than those of its services and agricultural sectors. The EKC was found to be invalid for Bahrain, where economic growth is still coupled with CO2 emissions. Whereas CO2 emissions have increased with growth in the manufacturing, and real estate subsectors, the emissions have decreased with growth in the hospitability, transportation and communications subsectors. These results indicate that economic diversification, specifically of the services sector, is aligned with Bahrain’s carbon neutrality target. However, less energy-intensive industries, such as recycling-based industries, are needed to counter the environmental impacts of economic growth. Originality/value The impacts of economic diversification on energy consumption and CO2 emissions in the Gulf Cooperation Council petroleum countries have rarely been explored. Findings from this study contribute to informing economic and environment-related policymaking in Bahrain.

Spatial-temporal distribution and source analysis of atmospheric particulate-bound cadmium from 1998 to 2021 in China.

Cadmium (Cd) is one of the most serious atmospheric heavy metal pollutants in China. PM2.5, PM10, and total suspended particle (TSP) are all important media for population Cd exposure. However, no studies so far have systematically explored the spatial and temporal distribution of atmospheric Cd bound to all these media in China, and the specific industrial sectors that contribute to the airborne Cd level are still unclear at present. In this study, we constructed the spatial and temporal distribution of PM (PM2.5, PM10, and TSP) binding Cd concentrations in China. Quantitative source apportionment of atmospheric Cd was carried out by analyzing the association of 23 industrial or energy-consuming sectors with Cd concentrations. Our results showed PM2.5, PM10, and TSP binding Cd concentrations decreased by 5.8%, 5.9%, and 6.1% per year at the national level, respectively. High PM-Cd concentrations were concentrated and distributed mainly in central and northwestern China. In addition, the medians of atmospheric PM2.5, PM10, and TSP binding Cd concentrations at the national level were 0.0026μg/m3, 0.0036μg/m3, and 0.0042μg/m3, respectively. The main sources of PM-Cd include nonferrous metal smelting (Zn, Pb, Al) (47%), glass production (13%), pesticide production (12%), cement production (10%), and coal consumption (9%). This study analyzes comprehensively the atmospheric PM-bound Cd pollution, identifies the major industrial sectors that affect atmospheric Cd concentrations at the macroscale for the first time, and provides a basis for further reduction in the atmospheric Cd pollution.

Effects of energy consumption on human development and industrial sector performance in selected Sub-Saharan Africa and OECD countries: comparative analysis

ABSTRACT The objectives of this study are to implicitly investigate the relationship that exist between energy consumption (renewable and non-renewable energy) and human development (with the Human Development Index as proxy); and energy consumption and industrial sector performance (with industrial output as proxy) in selected sub-Saharan Africa and the Organization for Economic Co-operation and Development (OECD) countries. Four groups of models were specified and estimated using Panel data for 21 countries according to income criteria from 1990 to 2022. These data were analyzed using Panel Ordinary Least Square (OLS) before which they were filtered with the use of Augmented Dickey Fuller (ADF) unit root test while the Johansen cointegration test was used to justify the long-run relationship among all included variables. The findings of this study revealed that energy consumption was positively related and statistically significant in explaining changes in human development and industrial sector performance in the selected sub-Saharan Africa and the OECD countries. However, changes in Human Development Index (HDI) were not statistically significant in explaining changes inindustrial sector performance in both regions. The results of the estimated models revealed a three-way directional causality among the selected variables. Additionally, it was established that a significant gap exist in human development, energy consumption and industrial sector performance, in favour of the selected OECD countries. Furthermore, it was also established that energy consumption and industrial output are potent determinants of human development in the selected OECD and sub-Saharan African Countries.

Fuzzy logic-based energy management in smart grids for renewable integration

This study explores the creation and execution of energy management methods using fuzzy logic in smart grids, with the goal of effectively incorporating renewable energy sources. The research employs empirical data that includes information on renewable energy production, changes in energy use, the current state of battery storage, and control measures taken. The data analysis demonstrates significant variations in renewable energy sources, namely solar energy ranging from 350 kW to 410 kW, wind energy changing from 180 kW to 220 kW, and hydro energy varied from 120 kW to 150 kW. The energy consumption in different sectors exhibits varied patterns. Residential consumption ranges from 250 kW to 275 kW, industrial demand increases from 300 kW to 330 kW, and commercial consumption fluctuates from 200 kW to 225 kW. The battery storage status shows changes, with Battery 1 seeing an increase from 150 kWh to 165 kWh, Battery 2 fluctuating between 180 kWh and 195 kWh, and Battery 3 maintaining a stable range of 200 kWh to 215 kWh. The use of control actions based on fuzzy logic demonstrates flexibility, where Control Action 1 ranges from 0.6 to 0.8, Control Action 2 fluctuates from 0.5 to 0.7, and Control Action 3 varies from 0.6 to 0.9. The study highlights the flexibility and quick response of the energy management system based on fuzzy logic. It can adjust control actions in real-time to accommodate changes in renewable energy generation, consumption patterns, and battery storage. This indicates its potential to optimize energy flow and ensure grid stability in smart grids, facilitating the efficient integration of renewable energy.

한국의 에너지 소비와 경제성장의 탈동조화에 대한 분석

Purpose - This study analyzed the decoupling phenomenon between energy consumption and economic growth in Korea from 1990 to 2021. The main purpose of this study is to suggest policy implications for achieving a low-carbon society and decoupling that Korea must move forward in the face of the climate change crisis.
 Design/methodology/approach - This study investigated the relationship between energy consumption and economic growth by energy source and sector using the energy-EKC (EEKC) hypothesis which included the energy consumption on the traditional Environmental Kuznets Curve (EKC), and the impulse response function (IRF) model based on Bayesian vector auto-regression (BVAR).
 Findings - During the analysis period, the trend of decoupling of energy consumption and economic growth in Korea is confirmed starting from 1996. However, the decoupling tendency appeared differently depending on the differences in energy consumption by sources and fields. The results of the IRF model using data on energy consumption by source showed that the impact of GDP and renewable energy consumption resulted in an increase in energy consumption of bio and waste, but a decrease in energy consumption by sources, and the impact of trade dependence was found to increase the consumption of petroleum products.
 Research implications or Originality - According to the main results, efficient distribution by existing energy source is required through expansion of development of not only renewable energy but also alternative energy. Additionally, in order to increase the effectiveness of existing energy policies to achieve carbon neutrality, more detailed strategies by source and sector of energy consumption are needed.

Türkiye’de 2030 Yılına Kadar Bina Sektöründeki Enerji Tüketim Tahmini

As in the rest of the world, energy consumption is increasing in Turkey as a result of population growth and technological developments. Energy efficiency studies are becoming more and more important for Turkey, which meets more than half of its energy needs from imported sources. When the sectors where energy is consumed intensively are analyzed, it is seen that the share of building sector energy consumption in total energy consumption is approximately 20%. This high rate shows that energy efficiency studies in the building sector will reduce the amount of energy imports and the current account deficit, as well as help to ensure security of supply.
 In this study, Turkey's population, Gross Domestic Product (GDP), number of buildings and the total amount of energy consumed in buildings in the past 20 years are used to estimate how much energy will be consumed in the building sector for the future. Within the scope of the study, how much energy will be consumed in the building sector in Turkey until 2030 is estimated by using Artificial Neural Networks (ANN) method in Matlab program. It is calculated that Turkey will consume 37.868 thousand Tons of Oil Equivalent (TOE) of energy in the building sector in 2030. In addition, the importance of energy efficiency studies in the building sector is emphasized.

Повышение энергоэффективности регионов России как государственная задача

Normative legal documents adopted in our country in the field of electric power industry impose obligatory re-quirements to improve energy efficiency of the Russian Federation and its constituent entities. The materials of this article are intended to contribute to the implementation of the state task. The article presents the results of a study related to determining the degree of mutual influence and interdependence of the energy supply of the region, the energy intensity of the region and the gross regional product per capita in order to improve regional energy efficiency. To do this, paired correlation coefficients are calculated, data on energy consumption in var-ious sectors of the regional economy and types of production are analyzed, typological grouping of the coun-try’s regions by three components is carried out. The obtained results allow regional authorities to make neces-sary decisions both strategically and tactically, taking into account the specifics and regional energy assets, aimed at improving the energy efficiency of the region.

Breaking the unsustainable paradigm: exploring the relationship between energy consumption, economic development and carbon dioxide emissions in Ecuador

Energy consumption is a crucial driver for economic development, improving the quality of life of the population of a country. This study attempts to contribute to the discussion by employing a systemic approach and methodology to examine the relationship between energy consumption (EC), gross domestic product (GDP) and carbon dioxide emissions (CO2) in Ecuador using time series from 1990 to 2018 with a mixed methodology (quantitative and qualitative). The energy balance and the enlarged Kaya identity are utilised to quantify the environmental impact of human activities. Furthermore, correlational cointegration and Granger causality tests are used to analyse the long-term and short-term relationships between variables in different sectors. The results reveal that there is no Granger causality between the variables in the agriculture and transport sectors, but there are unidirectional causality relationships in the industry and services sectors. In the industry sector, the study finds that EC Granger causes GDP (Wald test p value = 0.0038) and CO2 Granger causes GDP (Wald test p value = 0.0433). In the services sector, GDP Granger causes CO2 (Wald test p value = 0.0075), and EC Granger causes CO2 (Wald test p value = 0.0122), reinforcing the loop between GDP and CO2 in both the sectors. The analysed relationships help to inform policymakers about the likely impact of interventions. In addition, the study shows that Ecuador is in the initial phase of the Environmental Kuznets Curve, and provides strategies to manage sectoral energy consumption and valuable insights for other developing countries in Latin America seeking to pursue sustainable development.

Where there is policy, there is strategy: The impact of a green credit policy on the debt allocation strategy of business groups

The literature on the relationship between green credit and firms' financing strategy focuses largely on standalone firms. Our study extends this literature by examining business groups, focusing on whether and how business groups respond to green credit by proactively adjusting their financing strategy–intra-group debt allocation. Using the promulgation of China's new green credit policy as a quasi-natural experimental setting, our results show that business groups in high–energy consumption sectors have responded to the green credit policy by strategically centralizing borrowing at the parent level, and increased financial constraints and financing costs owing to green credit serve as the mechanisms underlying this causal effect. Analyses on firm heterogeneity illustrate that this effect is more pronounced in groups with private ownership and those without political or bank connections. Moreover, group debt centralization is found to mitigate the negative effects of green credit on R&D investments and investment efficiency. We further document that business groups in high-energy consumption sectors have reduced their carbon emissions since the EECG, and this effect only exists for those without financial constraints. Our study offers a finer-grained understanding of business groups' strategic responses to green credit and sheds new light on the efficiency of their internal capital markets.

Does digital transformation restrict the carbon emission intensity of enterprises? Evidence from listed manufacturing enterprises in China

AbstractDigitalization and greening are key themes in global development, the manufacturing industry, as a major sector of energy consumption and carbon emissions, is in urgent need of transformation to realize energy conservation and emission reduction, digital transformation provides an opportunity for its green development. However, whether digital transformation can restrain the carbon emission intensity (CEI) of enterprises is still controversial. Based on the data of China's A‐share manufacturing listed companies from 2013 to 2020, this paper uses fixed effect model and intermediary effect model to explore the relationship between digital transformation and enterprise CEI and the influence path. the results show that: (1) Digital transformation has significantly reduced the CEI of manufacturing enterprises. (2) Mechanism analysis indicates that green technological innovation and resource allocation efficiency play a chain mediating role in this relationship. (3) Heterogeneity analysis shows that the carbon emission reduction effect of digital transformation is more significant when enterprises belong to an energy‐intensive manufacturing industry or face strong environmental regulations and industry competition. The analysis of this paper not only deepens enterprises' understanding of digital transformation and green development but also provides a policy basis for China to advocate the coordinated development of the digital economy and green economy.

A Panel Examination of Economic Growth and Environmental Pressure in the Middle East and South Asia

The study observes the relationship between environmental scarcity and per capita income through carbon dioxide in twenty-six countries from 1990 to 2020. The detailed objective is to find whether the projected associations validate the inverted U-shaped hypothesis as demonstrated by the Environmental Kuznets Curve (EKC). Using panel fixed and random effects valuation procedures, the manuscript finds the negative and significant impact of income on pollution, which proves the validity of EKC. But energy consumption, population and industrial sectors have positive effects on the environment. Besides this, we also found inverted U curve status by using generalize method of moments (GMM) technique. Therefore, we reveal that the increase in income will reduce the pollution in our study sample.