Abstract
This research paper explores the relationship between green resources, product recycling, CO2 emission, and clean environment, using time series data spanning from 1990 to 2021. The sample of the study was the green energy sector of Pakistan and clean energy was taken as the dependent variable while green energy resources, product recycling, and CO2 emissions were chosen as independent variables. Correlation matrix and multiple regression analysis were applied to determine the relationship between green energy resources, product recycling, CO2 emissions, and clean environment. The results of the study show that there is significant positive relationship between green energy resources and product recycling with clean environment but negative association between CO2 emissions and clean environment. These results provide valuable insight for policy makers to focus on development of green energy resources and encourage products recycling as an effective strategy to mitigate the depletion of natural resources and improvement of clean environment to attain sustainability in the energy sector.
Introduction
Background of Study
The goal of “Net Zero Emission by 2050 scenario” and rising global temperature at a 1.5°C level set by International Energy Agency (IEA) appears difficult due to Ukraine-Russia war and US-European sanctions on Russia. The rise in global average temperature was around 2.1°C above pre-industrial level in 2021. The energy sector is responsible for around three-quarters of the emissions. It is estimated that global population will likely to grow to two billion by 2050, and the rising per capita income will definitely push up energy demand. The current energy system is not capable to meet these challenges. However, the future prospectus of renewables is promising because annual additions of solar and wind energy are approaching 500 GW by 2030 and coal consumption is likely to be decreased by 20 percent. A fall in global energy–related CO2 by 40 percent is likely to be seen by 2050. Although global electricity demand will likely to be doubled by 2050, yet the rapid adoption of renewables by the energy sector will meet this demand and also reduce the level of emission globally. Under “Net Zero Emission” new energy economy, there will be 240 million rooftop solar PV systems and 1.6 billion electric cars on roads by 2050. Figures 1 and 2 show the growth of Solar PV and wind energy generation during 2010 and 2030 and emission scenario during 2000 and 2050, indicating high level of growth of renewables and substantial reduction in the level of emission. Solar PV and wind generation scenario by 2010–2030. Source: World Economic outlook, IEA, 2021. Global emissions scenario by 2000–2050. Source: World Energy Outlook, 2021.
However, the International Energy Authority (IEA) has warned that a failure to accelerate clean energy transitions would continue to leave people exposed to air pollution. Today, 90% of the world’s population breathes polluted air, leading to over 5 million premature deaths a year. It is expected to see rising numbers of premature deaths from air pollution during the next decade. In the NZE, there are 2.2 million premature deaths per year by 2030, a 40% reduction from today (Word Energy Outlook (2021)).
Pakistan faces numerous environmental challenges that pose severe threats to human health and life. Climate change, in particular, has emerged as a non-traditional threat and Pakistan is among the top ten countries which are likely to be effected by its consequences. Climate change adversely impacts health, agriculture, and overall economy of the country. The main factors contributing to climate change in Pakistan include rising carbon emissions, deforestation, population explosion, and insufficient finances to mitigate and reduce its effects (Riedel, 2011; Xiao et al., 2016). Given the pressing environmental challenges and the rising environmental pollution in Pakistan, recycling emerges as an essential strategy for preserving the planet for future generations. Recycling allows for the creation of new products from old, discarded items that are of no use, thereby reducing the demand for new resources and minimizing waste generation. By implementing effective recycling practices, Pakistan can mitigate plastic pollution, conserve resources, reduce carbon emissions, and promote a more sustainable development in future. Recycling is widely recognized as an effective method to alleviate environmental pressures on society by conserving renewable energy, reducing pollution, and minimizing the cost of solid waste (Shi et al., 2020)). The improper disposal of plastic waste, with approximately 8 million tons dumped into oceans globally, further exacerbates the problem. The decomposition time for plastic ranges from over 100 years for simple plastic bags to 100–600 years or even longer for complex plastics. Different plastic items contribute varying proportions of pollution, with food wrappers and containers accounting for 31.15%, bottles and container caps for 15.5%, plastic bags for 11.18%, straw and stirrers for 8.13%, and beverage bottles for 7.27% of environmental pollution (Eneh and Oluigbo (2012).
Green Policy Framework
The Government of Pakistan recognizes the urgent need to address environmental challenges and promote sustainability. In line with this objective, a long-term policy framework is proposed, building upon successful initiatives such as the “Clean Green Pakistan” campaign, the “Billion Tree Tsunami” program, and the “National Conservation Strategy”. This framework aims to enhance environmental conservation, waste recycling, and sustainable practices throughout the country. The “Clean Green Pakistan Initiative” was launched in 1990 to promote cleanliness and greenery in cities of Pakistan. A web portal was launched for citizens to register and report their activities to earn points. Medals were awarded to citizens achieving the given target. It encouraged the citizen to participate in maintaining cleanliness and green spaces, improving overall cleanliness and greenery of cities. “Billion Tree Tsunami Program” was launched in 2014 by provincial Government of Khyber Pakhtunkhwa (KPK) to restore forests and degraded land to combat global warming and fulfill the Bonn Challenge commitment. Under this program, about 350,000 ha of forests and degraded land was restored. It added plantation of three-quarters of a billion new trees within a year. The effect of this policy was positive because it improved ecosystems, increased forest cover, reduced carbon emissions, enhanced biodiversity, and promoted sustainable practices of land use. In 12018, “National Conservation Strategy” containing 14 points was prepared and it focus areas included soil conservation, efficient irrigation, watershed protection, forestry, rangeland restoration, water body conservation, biodiversity conservation, energy efficiency, renewable resources, pollution prevention, waste management, institutional support, population, environmental integration, and cultural heritage preservation. The underlying objective of this strategy was to adopt sustainable agricultural practices, water resource protection, biodiversity conservation, reduced pollution, renewable energy development, efficient resource utilization, improved waste management, and preservation of cultural heritage.
“The Clean Green Pakistan” initiative led to improved cleanliness, greenery, and citizen participation in environmental conservation efforts. “The Billion Tree Tsunami program” successfully restored large areas of forests and degraded land, contributing to climate change mitigation, biodiversity conservation, and sustainable land management. “The National Conservation Strategy” provides a comprehensive framework for addressing multiple environmental challenges and promoting sustainable development. However, these policy initiatives have so far not proved successful for controlling level of emissions, climate change, product recycling, and use of green energy resources at large scale. Pakistan is still dependent on non-renewable resources.
Products Recycling
Daily Waste Generation in 10 Big Cities of Pakistan.
Source: Shirazi and Kazmi. (2014).
Waste is classified on the basis of its source and composition. The good practices of waste management not only help better manage waste but also save natural resources when it is re-used or recycled according to set guideline of its disposal. There are 12 categories of waste which can be further divided into two main categories, that are organic (biodegradable) waste comprising 58 percent of total waste and combstible waste which is 33 percent of total waste and is produced during various energy generation processes. The Figure 3 shows the composition materials present in waste products. The quantification of the products is based on the general consumption of these products. Quantification of different waste products (in %).
Categories of Municipal Wastes in Pakistan (in %).
Source: Mahar et al., (2007).
CO2 Emissions in Pakistan
CO2 emissions in Pakistan have become a growing concern due to its significant impact on climate change and environmental degradation. Pakistan, as a developing country with a rapidly growing population and expanding industrial sector, transportation, and number of vehicles, has experienced a surge in energy consumption and subsequent CO2 emissions over the past few decades. The main contributors to CO2 emissions in Pakistan are the burning of fossil fuels for electricity generation, industrial activities, transportation, and residential energy consumption. The country heavily relies on fossil fuels such as coal, natural gas, and oil for its energy needs, which leads to rising substantial CO2 emissions. Additionally, outdated and inefficient technologies, inadequate emission control measures, and a lack of awareness about latest practices and technologies further exacerbate the emission levels. According to available data, Pakistan’s CO2 emissions have shown an upward trend in recent years. This increase is a result of the country’s rapid economic growth, urbanization, and industrialization. However, it is important to note that Pakistan’s per capita CO2 emissions remain relatively low as compared to developed countries. The government of Pakistan has recognized the urgency to address CO2 emissions and has taken several initiatives to mitigate their adverse effects. Efforts include the promotion of renewable energy sources, such as wind and solar power, as well as the implementation of energy efficiency measures. Furthermore, policies and regulations aimed at reducing emissions from the industrial sector and promoting sustainable transportation are being introduced. International collaborations and financial support have also played a crucial role in assisting Pakistan’s efforts to tackle CO2 emissions. The country has actively participated in global climate change conferences and accords, demonstrating its commitment to combate climate change and reduce greenhouse gas emissions. However, despite these efforts, challenges still exist due to limited financial resources, inadequate infrastructure, and non-availability of clean technologies
Research Objectives and Motivation of Study
The low use of green energy resources, low level of product recycling, and high level of CO2 emissions in Pakistan have motivated the authors to investigate their causes and effects because if the current situation is continued Pakistan’s energy security will be in threat and it will not be able to bear the rising cost of non-renewable energy resources and unpredictable climate disasters and polluting environment because of its precarious financial position due to looming threat of sovereign default. However, there is still time and opportunities to shift the strategy from non-renewables to green energy resources, products recycling, and controlling emissions. This is the reason that authors have intended to carry out research to investigate the relationship between green energy resources, product recycling, CO2 emissions, and clean environment so that an effective solution may be proposed to improve the quality of environment. In line with this motivation, the main objective of this study is to analyze the role of green energy resources and products recycling in clean environment. Another objective is to examine the effects of the rising level of CO2 emissions on the clean environment in Pakistan.
In the light of these objectives, the following hypotheses have been developed. Ho: Green energy resources have no significant impact on clean environment. H1: Green energy resources have significant impact on clean environment. H0: Products recycling has no impact on clean environment in Pakistan. H1: Products recycling has a significant impact on clean environment in Pakistan. Ho: CO2 emissions have no significant impact on clean environment in Pakistan. H1: CO2 emission has a significant impact on clean environment in Pakistan.
These hypotheses will be tested through data, and an econometric model will be employed to analyze the relationship between independent and dependent variables empirically. The novelty of this study is that despite the recognition of the importance of recycling and green energy resources, there is a lack of comprehensive research on the specific impact of recycling practices and green resources exploitation and CO2 on clean environment. This study aims to bridge this gap by examining the effectiveness of recycling initiatives in reducing different types of pollution and their potential to contribute to environmental sustainability in the country. This study will contribute to the existing body of literature by providing insights into the impact of recycling and green energy resources on clean environment. The findings will apprise the policy makers, environmental organizations, and stakeholders about the significance of implementing and promoting green resources and recycling practices and controlling CO2 as crucial steps towards environmental preservation and sustainable development.
Literature Review
According to World Energy Outlook (2021), the renewable sources of energy such as solar PV and wind continue to grow rapidly, and electric vehicles set new sales records despite the fact that economies are still feeling pressurized of COVID-19 lockdowns. A virtual cycle is revolving due to policy action and technology innovation and its speed is now sustained by lower costs. In most markets, solar PV and wind are assumed to be the cheapest sources of new electricity generation. Now, clean energy technology is a major area of investment and employment and a dynamic area of global collaboration and completion. Durrani, et al. (2021) argued that rapid and uneven recovery from COVID-19 pandemic has put a severe strain on the current energy system due to the steep rise in the prices of natural gas, oil, coal, and electricity markets. All progress made by renewables and electric mobility in the past few years lost momentum due to a big rebound in coal and oil use. This is the reason that second largest annual increase has been noted in CO2 emission in the history and only one third of investment could be mobilized for spending on development of sustainable energy sources. The developing countries are specifically facing serious public health crisis due to shortage of funds, affecting progress towards universal energy access in Sub-Saharan Africa and some Asian countries. The rapid economic development, urban sprawl, and unplanned industrialization in developing countries of South Asia have led to improved socio-economic conditions but have also resulted in lower air quality. The decline in air quality has posed serious threats to the local community in terms of health, viability, and overall quality of life. Yang, et al. (2021) stated that the worrying points is that many developing countries are facing emission-intensive scenario due to rapid urbanization and industrialization. The current energy system is not capable to meet these challenges. However, the future prospectus of renewables is promising because annual additions of solar and wind energy are approaching 500 GW by 2030, and coal consumption is likely to be decreased by 20 percent. A fall in global energy–related CO2 by 40 percent is likely to be seen by 2050. Although global electricity demand will likely be doubled by 2050, rapid adoption of renewables by energy sector will reduce the level of emission globally. There is a sharp divergence in the speed of energy transition particularly in the developing countries. There appears to be a conflict in the areas of trade and energy-intensive goods as well as in international investment and finance. All countries need to align their policies and investment planning and contribute significantly in global transition. The good news is that now all technologies which needed to attain emission cuts by 2030 are available and about half of emission reduction by 2050 will come from clean technologies. So, the role of clean technologies innovation is significant for emission reduction. There is further need to focus on pollutant industries like iron and steel, cement and transport, deployment of hydrogen based and other low carbon fuels, and carbon capture, utilization and storage (CCUS) are imperative for this purpose. In their study, Tang et al. (2019) and Shi et al. (2020) focused on optimizing global air quality data in a high-density country like Pakistan using the Spatiotemporal Land Use Regression (LUR) model. They found that various factors such as transportation systems, land use trends, local meteorological conditions, regional characteristics, landscape characteristics, and satellite-based evidence accounted for 54.5 percent of the atmospheric PM2.5 concentration. This research emphasized the significance of considering multiple facets of plastic waste in coastal and marine ecosystems, including different types and shapes of plastic contaminants. Shen et al. (2020) highlighted the potential of biodegradable plastics (BPs) as a solution to the global disposition of plastic waste due to their biodegradability and harmlessness. However, the long-term feasibility of BPs for waste management and global contamination of plastics remains uncertain, necessitating comprehensive research. Grimaud, Perry, and Laratte (2018) conducted a Life Cycle Assessment (LCA) to assess the environmental impact of recycling aluminum cables. Their study, which followed the standards of the International Organization for Standardization, focused on a recycling plant in France (MTB Recycling) that utilized mechanical isolation and optical sorting measures to produce high-purity aluminum. The findings revealed significant environmental advantages of recycled aluminum compared to primary aluminum, emphasizing the benefits of product-centric cable recycling pathways and the effectiveness of mechanical separation of metal smelting recycling. Eneh and Oluigbo (2012) investigated the effect of liquid and solid waste pollution on climate and the release of greenhouse gases (GHGs) into the atmosphere. They emphasized the need for waste disposal activities such as reuse, recycling, and the use of recycled materials to improve energy efficiency and mitigate the trapping of solar heat energy in the atmosphere, which contributes to global warming. Mahar et al. (2007) and Whitmarsh (2009) evaluated the solid waste management (SWM) practices in urban areas of Pakistan. Their study focused on five major cities and provided a comprehensive analysis of various aspects of SWM, including waste generation, storage, collection, physical composition, transportation, processing, and disposal. The research identified critical issues and proposed significant steps to enhance existing procedures.
In short, the reviewed literature highlights the challenges posed by air emissions, recycling practices, and solid waste management in developing countries. The studies emphasize the need for comprehensive research and effective strategies to address these environmental issues, improve air quality, mitigate plastic pollution, promote sustainable waste management practices, and reduce greenhouse gas emissions.
Data and Methodology
This study utilizes a quantitative research design to investigate the impact of green energy resources, products recycling, and CO2 emissions on the clean environment in Pakistan. The study was conducted across the entire country of Pakistan, considering its population of 230.0.0 million (according to the 2019 census). Secondary data was used in this research, and it was collected from World Development Indicators, Pakistan Economic Survey, 2020, and State Bank of Pakistan and World Energy Outlook Report, 2021. Different statistical techniques such as descriptive statistics, correlation matrix, and Multiple regression analysis were used to analyze the relationship between green energy resources, product recycling, CO2 emissions, and clean environment. There are various reasons for using the above statistical techniques for this study. This study has applied a quantitative research design for measuring and analyzing numerical data and, therefore, the selected statistical techniques are most suitable for handling interpreting numerical data. As the study is based on entire Pakistan and the analysiss of this large-scale geographical area needs robust statistical approach to analyze data collected from the whole country about wastes and environmental degradation. Moreover, secondary data collected from World Development Indicators, Pakistan Economic Survey, State Bank of Pakistan and World Energy Outlook is reliable and there is need to process and analyze such data through statistical techniques. Descriptive statistics are valuable tools for summarizing and presenting core characteristics of the data. In this study, it has provided an overview of the central tendencies and variations among variables related to green energy resources, product recycling, CO2 emissions, and clean environment. The correlation matrix is a suitable tool to measure degree of relationship between variables. This technique helps identify correlation between green energy resources, product recycling, CO2 emissions, and clean environment. Multiple regression analysis is an effective statistical tool to estimate how three independent variables, green energy resources, product recycling, and CO2 emissions collectively impact the dependent variable, clean environment. It helps us measure strength and direction of these relationships to predict how change in one or more independent variables affects the dependent variable (clean environment). In other words, this statistical techniques have facilitated us to quantify the relationships between independent and dependent variables and to predict about their behavior. The high R-squared value indicates a good fit of the regression model to the data, suggesting that the included independent variables explain a substantial portion of variation in the clean environment. This implies that the model has strong practical power for predicting and understanding the clean environment. In short, the selected statistical techniques fully align with research design, type of data the complexity of research problem and provide an effective framework for examining the relationship between energy resources, product recycling, CO2 emissions, and the clean environment in Pakistan. The general form of econometric model developed for this study is displayed in the following equation
CE = Clean energy sources
PR = Products recycling.
GER = Green energy resources
E = CO2 Emissions
Ԑ = Error term.
This model is transformed into a mathematical equation as follows
Y = Clean environment.
bo, b1, b2, and b3 = Coefficients.
X1 = Products recycling
X2 = Green energy resources
X3 = CO2 Emissions
€ = Error term.
Results and Discussion
Descriptive Statistics
Descriptive statistics is a fundamental technique in data analysis that helps summarize and describe the main features of a dataset. It involves the use of various measures, such as measures of central tendency (mean, median, mode) and measures of variability (standard deviation, range), to provide insights into the data. Descriptive statistics is vital for understanding and interpreting data for exploratory research study before moving towards advance statistical analysis. The results of descriptive statistics of this study are presented in the following table.
Descriptive Statistics of the Variables.
Correlation Analysis
Results of Correlation Matrix.
The results in the above table show the correlation coefficient between product recycling (PR) and green energy resources (GER) is .733,042 that indicates strong positive correlation between two variables. It means if one variable increases, the other variable will also tend to increase. The correlation coefficient between product recycling (PR) and CO2 is −.356183. This value indicates a moderate negative correlation between product recycling and CO2 emissions. A negative correlation means that if one variable increases, the other variable will tends to decrease. In this case, when PR increases, CO2 emission will tends to decrease. It means that product recycling will not only save natural resources but also improve the level of CO2 emissions in Pakistan. The correlation coefficient between GER and CO2 is .225242. This value indicates a weak positive correlation between GER and CO2. The relationship between these two variables is less pronounced as compared to the other correlations. Thus, the correlation analysis results reveal that PR and GER have a relatively strong positive correlation, PR and CO2 have a moderate negative correlation, and GER and CO2 have a weak positive correlation. The results of correlation matrix provide insight to the policy makers to develop regulatory framework and allocate required resources to encourage recycling process and use of green energy resources and also devise strategies to penalize those who violate of law and are found to be inovolved in intentional polluting of environment.
Regression Analysis
Regression analysis is a statistical technique which is used to analyze the relationship between a dependent variable and one or more independent variables. It allows us to examine how changes in one variable are associated with changes in another variable. This identification is crucial for knowing patterns, making predictions, and understanding the impact the behavior of variables. Moreover, by analyzing historical data, regression analysis can help estimate the value of the dependent variable based on the values of independent variables. While correlation does not imply causation but regression analysis can provide insights into potential causal relationships between variables. By controlling for other factors, regression models can help identify the impact of a particular independent variable on the dependent variable, helping researchers understand the causal mechanisms at work. It provides statistical measures of the goodness-of-fit of a model. Through hypothesis testing, researchers can evaluate the significance of the regression coefficients and determine whether the relationships observed are statistically significant or occurred by chance. The results of regression analysis of this study are presented in the following table.
Results of Regression Analysis.
Discussion
Now we discuss the results in detail.
The coefficient value of green energy resources (GER) is .596562, the value of standard error is .113446, t-statistic is 5.258554, and probability is .0012. This indicates that a one-unit increases in the green energy resources is associated with a .596562 unit increase in the clean environment (Y), holding other variables constant. The t-statistic of 5.258554 suggests that the coefficient is statistically significant at the .05 significance level (since the associated p-value is below .05). Therefore, the green energy resource has a positive and significant effect on the clean environment. The results of this study are consistent with World Energy Outlook (2021), which highlighted the importance of green energy resources and their increasing role in electricity generation and transportation. The next variable is product recycling (PR) and its coefficient value is .45526, standard error is .112464, t-statistic is 5.125844, and the value of probability is .0010. It reveals that a one-unit increases in product recycling is associated with a .45526 unit increase in the clean environment, holding other variables constant. Similar to GER, the coefficient is statistically significant (p-value <.05), suggesting a positive and significant relationship between product recycling and a clean environment. These results support the findings of Grimaud, Perry, and Laratte (2018) who reveal significant environmental advantages of recycled aluminum products as compared to primary aluminum, emphasizing the benefits of product recycling strategy for improvement of clean environment. The third independent variable is CO2 (carbon dioxide emissions) and its coefficient value is −.667933, std. error is .198161, t-statistic is 3.370661, and probability is .0119. The coefficient for CO2 emissions suggests that a one-unit increases in carbon dioxide emissions is associated with a −.667933 unit decrease in a clean environment, holding other variables constant. The coefficient is statistically significant (p-value <.05), indicating that higher carbon dioxide emissions have negative impact on clean environment. The two variables have negative association; if one variable increases another variable will tend to be decreased. These findings support the results of Su et al. (2020) and Yang, et al. (2021) who found that that many developing countries are facing emission-intensive scenario and polluted environment due to rapid urbanization and industrialization. The value of R2 is .823621 which indicates that approximately 82.36% of the variation in the dependent variable (clean environment) can be explained by the independent variables collectively in the model. A higher R2 value suggests a goodness-of-fit of the model to the data. The value of adjusted R2 .773228 takes into account the number of variables and sample size, providing a penalized version of R2. It is slightly lower than the R2 value, suggesting that the inclusion of some independent variables may not contribute significantly to the model’s explanatory power. The value of S.E. of regression 1.147131 represents the standard error of the regression, which provides an estimate of the average distance between the observed values and the predicted values by the regression model. The value of F-statistic tests shows the overall significance of the regression model. In this case, the F-statistic is 16.34368 with a probability of .002304 which indicates that overall, model is statistically significant. The Durbin–Watson test is used to detect the presence of autocorrelation (correlation between residuals and independent variables) and its value 1.693375 suggests that there is a minimal positive autocorrelation in the model. In a nutshell, the regression analysis reveals several significant relationships between the independent variables and a clean environment. Green energy resources (GER) and product recycling (PR) have positive and significant effects on clean environment against carbon dioxide emissions (CO2) which has negative effect on it. The model has a high R2 value, indicating a goodness of fit, and overall, the model is statistically significant.
Thus, it has been empirically proved that the use of green energy resources, product recycling, and controlling CO2 emissions can improve the level of clean environment significantly in Pakistan. The policy makers, environmental organizations, and other stakeholders should take benefits from these findings to improve the quality of environment and to control the environmental problems which are making the lives of people miserable. But the current energy system is not capable to meet these challenges. The emissions are rising in Pakistan due to use of fossil fuel in electricity generation, transportation, industrial, and agriculture sectors, resulting increasing emissions in the environment and spoiling clean environment. The situation demands immediate action through proper allocation of resources and effective implementation of policy framework.
Conclusions and Policy Implications
On the basis of the above discussion, we can draw a conclusion about the significant relationships between various independent variables and their impact on the clean environment. It is noted that green energy resources and product recycling have positive and significant relationship with clean environment. So, the government of Pakistan must focus on the development of green resources and promote recycling of products. The development of green resources will not only improve quality of environment but also reduce huge financial cost of using non-renewable resources, which was estimated around US$19 billion in 2022. It is huge savings for the country which has been facing threat of sovereign default. In this way, Pakistan can get sustainability security of energy and food in future. It has also been noted in the empirical results that CO2 emissions is one of the major causes of environment pollution because it has negative association with clean environment. It means if CO2 emission increases, the level of clean environment will likely to be decreased significantly. The negative relationship emphasizes that Pakistan concentrates on the control of emissions through policy and fiscal strategies so that the quality of environment may be improved.
The policy implications of this study are that the policy makers should take concrete policy initiatives to promote the use of green energy resources. These policy initiatives may include subsidies for renewable energy technologies and tax rebate for using clean energy and development of infrastructure for generation of clean energy. Similarly, the policy makers can encourage the investors through fiscal incentives to invest product recycling programs at national level and motivate the people to participate in recycling activities. This objective can be achieved through public awareness campaigns, supporting recycling efforts, and implementing regulations that force the manufactures to play responsible role for recycling and disposal of their products. In addition, the policy makers should take policy steps to reduce carbon dioxide emissions (CO2) by fixing emission targets, imposing carbon taxes, and supporting transition to cleaner technologies and energy sources. Moreover, both industrial and transport sectors can be regulated in order to make industrial process and transportation emission-free. These objectives cannot be achieved without collaborative efforts of public and private sectors. Policy makers should encourage collaboration between government, businesses, and non-governmental organizations to work together towards achieving a clean environment. In this way, environmental issues can be resolved efficiently. The policy makers should develop an efficient monitoring and reporting systems of environmental indicators in order to track the impact of policies and interventions. There is also need to invest in the research and development, and the policy makers should allocate resources to encourage research and development in the fields of green energy, recycling technologies, and carbon reduction strategies. Public awareness and educational programs relating to the importance of clean environment can play a significant role in creating awareness among the businesses and general public about the benefits of clean environment. It is generally observed that the policies are not implemented effectively in Pakistan and this is the reason that green energy sector could not be developed. It is the right time that policymakers should establish and enforce comprehensive regulatory frameworks that govern environmental protection, including setting standards for emissions, waste management, and sustainable resource use. There must be some rewards for environmentally friendly behavior and heavy penalties for polluters and non-compliance. In this respect, strong policy initiatives should be taken. As almost all countries are facing similar environmental issues, there is an urgent need for international cooperation. The policy makers should evolve an international cooperation and seek global technological support to address cross-border environmental challenges, such as carbon emissions and sustainable use of resources.
Theoretical Contribution of Study
The theoretical contribution of this study is stated as under:
The results of this study support theory of green energy transition which suggests that transitioning from fossil fuels to renewable energy sources can lead to environmental benefits by reducing pollution and greenhouse gas emissions. Studies such as the “Environmental Kuznets Curve” (EKC) hypothesis and empirical research on renewable energy adoption and environmental quality provide support for the positive relationship between green energy resources and a clean environment. The positive and significant relationship between product recycling (PR) and a clean environment is consistent with the principles of the circular economy. Economic theories related to the circular economy emphasize the importance of recycling and resource efficiency in reducing waste and pollution. Studies exploring economic and environmental benefits of recycling, such as life cycle assessments and studies on waste management policies, can further support the findings.
The findings of this study also support theory of economic growth and environmental quality. The inclusion of a constant term (C) in the model highlights the baseline clean environment level when all independent variables are zero. This can be linked to the broader economic theory of the Environmental Kuznets Curve (EKC), which suggests an inverted U-shaped relationship between income or economic growth and environmental quality. The constant term captures the minimum level of cleanliness in the absence of specific interventions or external factors. Empirical studies exploring the relationship between economic growth and environmental quality, including the EKC literature, can provide further theoretical underpinnings for interpreting the constant term.
The findings of this study also align with value-belief-norm theory, which is related to the environmental concern and behavior of different variables. The results of this study clearly highlights if green energy resources are used and product recycling is increased it will definitely have positive impact on clean environment. It will also provide guidance to policy makers if CO2 emission level decreases; it will certainly improve the quality of environment that is more beneficial for the whole world. By integrating these economic theories and relevant studies into the interpretation of the results, a more comprehensive understanding of the relationship between the independent variables and a clean environment can be achieved. The results of this study contribute to the theoretical understanding of the factors that influence a clean environment. The findings indicate that both green energy sources (GER) and product recycling (PR) have positive and significant effects on the clean environment. This suggests that policies and initiatives aimed at increasing the adoption of green energy sources and promoting product recycling can contribute to environmental sustainability.
Practical Contribution
The results of this study have some valuable practical implications. They provide an insight to the policy makers and environmental organizations to utilize the findings related to green energy resources and product recycling to support their environmental indicatives. They should promote the adoption of renewable energy technologies and execute effective recycling programs to clean the environment. These results also emphasize on the need of more investment in clean energy technologies and public awareness about the benefits of clean environment. The findings of this study reveal that CO2 emissions have negative impact on clean environment. This is not the issue of Pakistan but it is a global issue. The policy makers and environmental organizations should collaborate and take strong policy initiatives to control and reduce rising level of emission by focusing on green energy resources and clean technologies. The people through media campaign should realize that clean environment is a vital issue and it must be addressed through collective efforts because the polluted environment is equally affecting human beings, animals, plants, natural resources, earth temperature, food security, and the level of global warming. The negative effect of CO2 emission on clean environment is a great challenge for policy makers and emphasis on strong policy initiatives to control and reduce rising level of emission by focusing on the use of green energy resources and clean technologies. Thus, the results of the regression analysis provide theoretical insights into the factors influencing a clean environment. They suggest practical implications for policymakers, environmental organizations and other stakeholders to focus on promoting green energy sources, encouraging product recycling, and further investigating the relationship between carbon dioxide emissions and environmental cleanliness. The model’s fit and diagnostic measures offer guidance on the overall significance and reliability of the model for understanding and predicting the clean environment.
Limitations and Direction for Further Research
The limitations of this study are listed below: • The regression analysis used in the study establishes a relationship between the independent variables (green energy resources and CO2 emissions) and the dependent variable (clean environment), but it does not prove causality. There may be other unobserved factors or relevant variables that influence the clean environment. • The study’s findings are limited to Pakistan and have been carried out in the specific context, and its results may not be applicable to other regions, countries, or time periods because of different environmental conditions. • This study includes three independent variables (green energy resources, product recycling, and CO2 emissions); there may be other important variables not considered in the analysis that could influence the clean environment. Factors such as population density, industrial activities, or policy interventions could have an impact on the relationship between variables.
The suggestions for further research are given below: The future research should conduct longitudinal studies for a better understanding of the causal relationships between green energy resources, CO2 emissions, and the clean environment. By analyzing data over a longer period, researchers can predict how changes in the independent variables precede changes in the dependent variable, providing stronger evidence of causality. Moreover, future research could consider a more comprehensive set of independent variables to capture the complexity of environmental factors through multivariate analysis. More variables such as population growth, land use, technological advancements, and policy interventions would provide a more nuanced understanding of the relationship between green energy sources, CO2 emissions, and the clean environment. Future researchers can also conduct comparative studies across different countries or regions that would help assess the generalizability of the findings. Comparative analysis would provide insights into the effectiveness of different environmental approaches in promoting the clean environment. The new researchers can also identify the mechanisms through which green energy resources, product recycling, and CO2 emissions affect the clean environment. Understanding the underlying processes, such as technological advancements, energy efficiency measures, or policy implementation, would contribute to more targeted and effective environmental policies and interventions.
Footnotes
Acknowledgments
The authors are grateful to the anonymous referees of the journal for their extremely useful suggestions to improve the quality of the article.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Heilongjiang Higher Education Teaching Reform Project (SJGY20220492) Research on Ideological and political function Construction and Education Paradigm of Finance Course under the background of “New Liberal Arts” construction.
Data Availability Statement
The data that supports the findings of this study will be made available by corresponding author on strong request.
