Deciphering the Drivers of CO2 Emissions in Haryana: A Comprehensive Analysis from 2005 to 2023

Parveen Kumar¹Nudrat Fatima²Muhammad Kamran Khan³Hind Alnafisah^4*

• ¹1. Department of Humanities and Social Sciences, National Institute of Technology, Kurukshetra, Haryana India, Kurukshetra, India
• ²Department of Management studies, Bahria University, Pakistan, Bahria, Pakistan
• ³Department of Management studies, Bahria University,Pakistan, Bahria, Pakistan
• ⁴Economics Department, College of Business Administration/ Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

The imminent threat of global warming has garnered widespread attention on both international and national stages, underscoring its urgency. As the Earth's climate continues to evolve, the consequences of rising temperatures, shifting weather patterns, and environmental disruptions are becoming increasingly evident. At the heart of this global challenge lies the critical concern of greenhouse gas emissions, with carbon dioxide (CO2) being a pivotal contributor (Lamb et al., 2021). Reducing emissions can help address climate change, expand access to clean energy, and promote socio-economic development in nations (Mehmood et al.,2023). India, as one of the world's most populous and rapidly developing nations, plays a substantial role in the global climate landscape (Kumar, 2020). The country's economic growth, industrialization, and urbanization have led to a surge in energy consumption, often driven by the burning of fossil fuels. India's energy demand is rising rapidly, with significant implications for the global energy market (Radulescu et al.,2024). The Government of India has made substantial progress in expanding access to electricity and clean cooking solutions while implementing various energy market reforms and integrating a high share of renewable energy sources into its grid. With a population of 1.45 billion and a rapidly growing economy, India's energy needs are surging as the nation urbanizes and its manufacturing sector expands. This increased demand is met through a diverse mix of energy sources, with coal expected to remain the dominant energy supplier. Furthermore, India continues to strengthen its institutional framework to attract the necessary investments to meet its growing energy needs.The energy sector, largely reliant on fossil fuels, is a major contributor to greenhouse gas emissions and climate change. Under the Paris Climate Agreement, India has pledged to decrease the emissions intensity of its gross domestic product (GDP) by 33-35% from 2005 to 2030, a significant increase from its previous commitment of a 20-25% reduction from 2005 to 2020 (National Action Plan 2008). Consequently, India's carbon footprint has expanded significantly, making it one of the top contributors to global CO2 emissions. India's global share of CO2 emissions reached 7.07% in 2022, marking an increase of 182% since 2000 (OWID, 2024). Haryana, one of the northernmost states in India, is strategically located adjacent to the national capital, Delhi, and is bordered by Uttar Pradesh to the east, Punjab to the west, Himachal Pradesh to the north, and Rajasthan to the south. The state encircles New Delhi from three sides and is one of India's major automobile hubs, contributing to two-thirds of the country's passenger car production, 50% of its tractors, and 60% of its motorcycles. In addition to its strength in the automotive sector, Haryana has also emerged as a prominent base for the knowledge industry, particularly in IT and biotechnology. Haryana's development trajectory, marked by industrial growth, agricultural activities, and urban expansion, offers a unique case study for understanding localized drivers of CO2 emissions. Throughout the reference period, Haryana's per capita emissions consistently exceeded the national average (OWID,2024). The to about 12% in 2023. Haryana's CO2 emission levels are significantly higher compared to many other Indian states due to its industrial belt, high vehicular density, and extensive agricultural burning practices. Key metrics often show that Haryana's air quality index frequently exceeds safe limits, with CO2 and particulate matter (PM2.5, PM10) levels consistently above the national averages. As Haryana continues to evolve, so do its challenges and responsibilities in the realm of environmental sustainability. Furthermore, emissions from the waste sector decreased from around 4% in 2005 to roughly 3% in 2023 (GHGPI 2023).Previous studies have extensively explored the relationship between GDP and environmental degradation in India and other countries; however, there is a noticeable gap in research specifically focusing on Haryana, particularly with a quadratic approach to GDP. This study introduces novel dimensions by incorporating indicators such as CO2 emissions, economic growth in terms of GDP per capita, and the square of GDP to test the Environmental Kuznets Curve (EKC) hypothesis. Additionally, factors like population growth and life expectancy are included. This approach provides a more nuanced understanding of the complex relationship between economic growth and environmental degradation, enriching the existing literature by examining less conventional variables.The remainder of the paper is structured as follows: Section 2 delves into the literature review, while Section 3 expounds on the methodological considerations for estimating CO2 emissions in Haryana, including an overview of the data sources utilized. In Section 4, we present the state-level results, and the concluding remarks can be found in Section 5.Numerous studies have identified a dynamic relationship between economic growth variables and environmental degradation. For example, Danish et al. (2021) analyzed the Indian economy from 1971 to 2018, focusing on CO2 emissions, nuclear energy, population density, and GDP using the Dynamic Autoregressive Distributed Lag Model (DARDL). They concluded that both nuclear energy and population density contribute to the Environmental Kuznets Curve (EKC). . Olhan (2015) explored the impact of population density, energy consumption, economic growth, and trade openness on CO2 emissions during the period 1970-2013. The study confirmed a long-run relationship between these factors, showing that population density, energy consumption, and economic growth significantly increased CO2 emissions. A similar study conducted by Pandey and Rastogi (2018) for the period 1971 to 2017 found that economic growth led to an increase in CO2 emissions. Kartal et al. (2023) investigated the long-term implications of reduced coal consumption on energy usage, CO2 emissions, and economic growth, focusing specifically on China and India. Utilizing yearly data from 1990 to 2021 and employing an innovative dynamic autoregressive distributed lag model, their findings revealed that coal consumption causally influenced CO2 emissions. Mehmood et al. (2024) examined the relationship between various types of CO2 emissions and economic growth in the United States and China using the bootstrap autoregressive distributed lag approach. Their findings indicated that CO2 emissions from coal exceeded those from oil in both countries. The study also revealed a positive correlation between GDP and CO2 emissions. Akram et al. (2023) conducted a study to analyze the convergence and divergence of CO2 emissions across 16 major Indian states from 2003 to 2019. They found that Haryana continues to follow an upward trajectory in per capita CO2 emissions during the study period. Acheampong et al. (2019) examined the complex interplay between economic growth, energy consumption, and CO2 emissions in sub-Saharan Africa and globally over the past decade.The study uncovered that economic expansion stimulated energy consumption in sub-Saharan Africa while simultaneously reducing carbon emissions globally and in the Caribbean Latin American region. Interestingly, carbon emissions positively correlated with economic growth, while energy consumption had an adverse impact on GDP in most regions. An Environmental Kuznets Curve (EKC) phenomenon was observed both globally and within sub-Saharan Africa, highlighting the intricate relationship between economic advancement and environmental considerations over the past decade. Jian et al. ( 2021) analyzed the influence of non-economic factors on energy consumption and CO2 emissions in China from 1991 to 2019. The study found that education, law and order, and social globalization had a mitigating effect, while population growth positively correlated with energy consumption and CO2 emissions during this period. Yuping et al. (2021) employed advanced econometric methodologies to examine the shortand long-term elasticities of CO2 emissions from various macroeconomic factors. Their findings indicated that renewable energy consumption and globalization contributed to reducing CO2 emissions, whereas non-renewable energy sources had a negative impact. The study also confirmed the EKC hypothesis in Argentina, showing that economic growth initially increased environmental pollution until a certain income threshold was reached, beyond which further growth reduced the environmental impact. Khezri et al. (2022) conducted an in-depth investigation into the impact of renewable energy deployment on short-term emissions reductions across 19 advanced and developing nations, including 17 countries in sub-Saharan Africa. The study revealed that increased economic complexity was associated with higher energy efficiency and reduced CO2 emissions. It also suggested that adopting renewable energy sources could effectively mitigate short-term carbon emissions, particularly in nations with lower economic complexity. Armeanu et al. (2018) explored the relationship between pollution and the economy within EU-28 countries, focusing on the EKC theory. Using data from 1990 to 2014 and a specialized mathematical model, the study provided evidence supporting the EKC theory for specific pollution categories. They found correlations between GDP per capita and greenhouse gas pollution, as well as between energy consumption and greenhouse gas pollution. The analysis indicated that economic growth led to increased greenhouse gas pollution in the short term, and there was a bidirectional relationship between energy usage and greenhouse gas pollution. (Liu et al., 2023;Kumar, 2019 andRamadhan et al.,2023) found that urban population growth increased demands for vehicles, buildings, and food, leading to higher greenhouse gas (GHG) emissions. Urbanization triggered changes in housing, household size, and industrial structure, driving up energy demand and CO2 emissions. Cavusoglu and Gimba (2021) found that over the long term, inflation and CO2 emissions negatively affected life expectancy, while GDP per capita, food production, human capital, and health expenditure had a notably positive influence. Das and Debnath (2023) investigated the net impact of CO2 emissions on life expectancy in India. Using the ARDL cointegration technique, the study concluded that there is a long-term and quadratic relationship between life expectancy and CO2 emissions. Wang and Li (2021) investigated 154 countries and observed that population aging, per capita GDP, population density, and life expectancy have nonlinear effects on per capita CO2 emissions, whereas population, urbanization, and unemployment have linear effects. Several studies, such as those by Rajan et al. (2020) andTam et al. (2023), have explored greenhouse gas (GHG) emissions in India using various methodologies, including annual energy statistics and input-output methods, primarily at the national level. However, our review identifies a research gap concerning Haryana, where no studies have examined the relationship between net state domestic product, life expectancy, population growth, and CO2 emissions at the state level. This paper aims to address this gap by analyzing the multifaceted factors influencing CO2 emissions in Haryana from 2005 to 2023.The EKC hypothesis, first proposed by Grossman and Krueger in 1995, posits a link between environmental degradation and economic development. According to this hypothesis, there is an inverted U-shaped relationship between environmental decline and economic progress.Initially, environmental degradation increases with economic growth, but it eventually decreases after reaching a certain income threshold. This concept serves as a key indicator of a country's stage of economic development. They have described this relationship as follows:□□□□2 ! = □□ " + □□ # □□□□□□□□ ! + □□ $ □□□□□□□□□□ ! + □□ % □□□□ + □□ !(1)In Equation 1, CO2 represents carbon dioxide emissions, NSDP denotes net state domestic product, NSDPS indicates the square of Net State Domestic Product, while Zt represents other factors influencing the dependent variable (life expectancy and population growth) in our study (Table 1).Additionally, □□ ! signifies the error term. To structure our econometric analysis, the econometric methods used in this study draw inspiration from prior research (Charfeddine and Mrabet 2017;Merlin and Chen 2021; Moridian et al., 2024).□□□□2 ! = □□ " + □□ # □□□□□□□□ ! + □□ $ □□□□□□□□□□ ! + □□ % □□□□ + □□ & □□□□ ! + □□ ! (2)In our subsequent empirical analysis, author elucidates the procedures for addressing heteroscedasticity's impact by logarithmically transforming variables, following the approach recommended by Wang and Zhang (2020).□□□□□□□□2 ! = □□ " + □□ # □□□□□□□□□□□□ ! + □□ $ □□□□□□□□□□□□□□ ! + □□ % □□□□ ! + □□ & □□□□ ! + □□ '! (3)In the transformed equation, the ln denotes the natural logarithm; the subscripts't' (t = 1, . Descriptive statistics for all variables under analysis are presented in The pairwise correlation matrix is presented in Table 3.The results demonstrate a strong positive correlation between CO2 emissions, NSDP and NSDP. The correlation coefficient between CO2 emissions and life expectancy is 0.68 and a moderate positive correlation between GDP and life expectancy. However, there exists a weak negative correlation between CO2 emission and population growth (PG). The results of the Dynamic Ordinary Least Squares (DOLS) regression analysis, presented in Infrastructure development, waste generation, and deforestation further compound theseThis study thoroughly examines the factors influencing CO2 emissions in the state of Haryana, India, spanning the period from 2005 to 2023. Notably, it highlights a positive and statistically significant relationship between CO2 emissions and both NSDP and population growth. This finding underscores the challenge of balancing economic growth and population expansion with environmental sustainability in Haryana. Conversely, the study reveals a negative association between CO2 emissions and life expectancy, suggesting that efforts to enhance public health and life expectancy may inadvertently lead to reduced CO2 emissions. The research emphasizes significant findings, including a strong positive correlation between GDP and CO2 emissions, indicating that as income levels rise, pollution levels also increase.However, the study also uncovers complexities within this relationship, with the emergence of inverted U-shaped (EKC) patterns presenting nuanced scenarios. Overall, these findings underscore the complex interplay between environmental factors and socio-economic indicators in pursuing sustainable development goals in Haryana. They call for a nuanced approach to policymaking that harmonizes economic growth, population management, and environmental conservation in the region. In light of these results, policymakers in Haryana are encouraged to consider strategies prioritizing environmental sustainability alongside economic and social development. These strategies may include promoting renewable energy sources, improving urban planning to reduce emissions from transportation, and implementing policies supporting both public health and environmental well-being. In essence, this study contributes valuable insights into the intricate relationship between various factors and CO2 emissions in Haryana, providing a foundation for informed and sustainable policy decisions to mitigate the adverse effects of CO2 emissions while fostering holistic development in the