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Carbon emission factor of different fuel types. Source: Inter- Governmental panel for climatic change (IPCC)
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Energy related CO2 emissions are important factors responsible for greenhouse effect. Unprecedented increase in anthropogenic gas emissions in the recent decades have led to climatic changes. This study was aimed to decompose the changes in CO2 emissions in Pakistan for the time periods of 1990–2017. The log mean Divisia index was employed to find...
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... are four main fuels in Pakistan including, oil, natural gas, hydroelectricity and coal. In this study, the economy is divided into three sectors such as, industry, agriculture and services sector and used the energy consumption data of different fuel types for each of the sector (Table 2). For each fuel type, consumed in these sectors, the amount of energy is calculated related to CO 2 emissions. ...Similar publications
The continuous increase in carbon dioxide (CO2) emission leads to an adverse climate change, that has a disastrous impact on the socio-economic lives of the human being. Therefore, to reduce the environmental impact on human life, it is necessary to provide mitigation measures for CO2 emissions and to investigate the influence of pre-determined fac...
Citations
... O′ Mahony et al. (2012) utilized the LMDI to identify and analyze the driving forces of CO 2 emissions in eleven final energy-consuming sectors of Ireland [27]. Meantime, the LMDI was also applied in the research of US [28], India [29], Turkey [30], Australia [31], Philippine [32], Pakistan [33], and Saudi Arabia [34]. There are also an increasing number of researchers who have applied the LMDI to find the factors of China's CO 2 emissions in the relevant literature [35][36][37][38][39]. ...
... 47 Pakistan is an ordinary victim, accounting for only 0.8% of global greenhouse gas emissions and ranking 135th worldwide. 48 However, the country faces huge consequences from climate change, ranking in the top 10 most unprotected countries according to an enduring climate risk index. 49 It is approximated that Pakistan loses 6% of its gross domestic product to environmental problems yearly, equivalent to PKR 36.5 billion. ...
The study examined the decoupling relationship between industry carbon emissions and economic growth using the most current updated data. We collected data from the industry sector of Pakistan from 1991 to 2018. This study used two techniques, Tapio’s elasticity and fluctuation index, to test the decoupling relationship and the relationship’s stability between industry carbon emissions and economic growth. First, we analyzed the decoupling relationship between industry carbon emissions and economic growth in Pakistan using Tapio’s decoupling model, decoupling the elasticity of technology, scale and structure. Second, the decoupling volatility index was used to determine the stability of the technology, scale and structure elasticity. The Tapio decoupling elasticity technique results confirmed the significant relationship between industry CO 2 emissions, economic growth and added value comes out to be a simple feature of each stage and undergoes expansive negative and strong decoupling processes. The outcomes of elastically decoupled volatility indexes suggest that three out of four indices are high, indicating unstable decoupling conditions. This study concludes that growth and volatility were the crucial characteristics of industrial carbon emissions during 1991–2018. Hence, the industry’s carbon emissions were increased from 16.67 million tons in 1991 to 55.70 million tons in 2018, an average yearly growth of 4.56%.
... Another way for the reduction of fluctuations in renewable energy generation is by following distributed renewable generation which can be done by preferring small power plants in the large geographical area instead of one single large power plant packing around one area [89]. The reason behind this is that simple natural phenomena like clouding could affect around three-fourth of the output of solar photovoltaic cells within less than 15 min [90]. ...
The power sector of Pakistan is facing many issues such as departmental mismanagement, huge dependence on imported fossil fuels, the greater cost of power generation, lower production of energy along with old monitoring and controlling mechanism equipped with outdated devices. These all issues are responsible for energy crises in the country for the last two decades. The motive of this paper is to implement a smart grid model as per National Institute of Standards and Technology (NIST) interoperability (protocols and standards, release 4.0) in Pakistan's electric network for the efficient management of an integrated energy system. In this regard, discusses the current condition of Pakistan's power sector for smart grid integration. Issues and challenges are presented for smart grid deployment with possible approaches to tackle these problems. Implement smart grid model and its synopsis with the help of available smart technologies and energy resources that are responsible to interconnect the power sector organizations and national power system. The implemented model and its synopsis are evaluated using SWOT (Strength, Weaknesses, Opportunities and Threads) and STEEPLE (Social, Technical, Environmental, Economic, Political, Legal, and Ethical) analysis. In this paper, the authors find the smart grid as the best option and shows that how smart grid technology can be implemented in Pakistan and how this technology can manage the integrated energy system efficiently.
... According to Global Climate Risk Index (CRI) Pakistan has been ranked as the world's 5th the most affected country in twenty-year period from 1999 to 2018 hit by extreme weather events 2 . As estimated annual cost of environmental problems in Pakistan amounts to 6% of its GDP equivalent to PKR.365 billion (Economics Survey of Pakistan 2014, p. 245; Khan et al. 2019). Unfortunately, during this entire scenario, the higher energy demand and the inefficient and underdeveloped technological sector has further fuelled up the CO 2 emissions. ...
Pollution and environment degradation have become serious challenges for the entire world, especially for developing countries. Shadow economy is viewed one of the key factors which can significantly affect environmental quality due to its close and direct relationship with environmental degradation. This study contributes by testing whether an enormous informal sector may be accompanied by higher environmental degradation and investigates the relationship between shadow economy and the prominent sources of environmental degradation. While utilizing data from 1966 to 2008 by accounting an ideal region (Pakistan) as highly exposed to environmental risks, we arrive at several important conclusions. Through the lens of ARDL bound testing procedure, we found that there is significant co-integration association between shadow economy and environmental degradation. The same also holds between shadow economy and the prominent sources of CO2 emissions. While controlling for other determinants of pollution, our estimates confirm that shadow economy not only boosts CO2 emissions but also the various sources of environmental degradation are induced through higher informal sector. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS) and dynamic OLS (DOLS). Consequently, this study put forward policy recommendations aimed at plummeting the size of informal economy through implementing robust regulating policy instruments to minimize the environmental degradation.
... Therefore, it is seen that it is used in the analysis of different sectors in many countries. For example; China [[7]- [9]], Greece [10], India [11], Pakistan ( [12], Nigeria [13], Spain [14], Mexico [15], Philippines [16] ve Turkey [17]- [21]. Studies frequently use five primary factors, industrial operation, industry structure, energy structure, energy intensity, and emission factor. ...
... Khan et al. [12] have used the LMDI method to calculate changes in CO2 emissions in Pakistan over 1900-2017. The goal of this was to reduce the changes in CO2 emissions. ...
The European Union has put forward a vision under the EU Green Deal’s name to take the lead in its priorities, fulfill the Agreement’s criteria, and subsequently accept the first EU climate law on March 5, 2020. The law framework aims to impose tax obligations on consumption goods imported by the EU from abroad, especially on energy-intensive sectors, by applying the carbon border adjustment mechanism. Our main goal is to determine what kind of measures can be taken to ensure that the iron and steel industry is least affected by the EU border carbon regulation. We are an absolute exporter, are least affected by the EU carbon border adjustment. For this reason, the change in energy-related greenhouse gas emissions from the iron and steel industry from 1998 to 2018 was analyzed using the LMDI model to investigate the potential effects of carbon border adjustment in the iron and steel industry. The analyzes were made with five significant factors that determine the change of emissions. These factors are; changes in economic activity, activity mix, energy intensity, energy mix, and emission factors. Analysis has suggested that the economic activity effect has raised CO2 emissions. This method indicates that the energy intensity’s impact could be the first key determinant of GHG emissions. Turkey should attempt to implement low-carbon development policies and reduce energy-related emissions in the iron & steel sector are the least impacted by the EU’s carbon border adjustment.
... The result shows that the primary sources of CO2 emissions are economic activity. Roinioti and Koroneos (2017) and Khan et al. (2019) arrive at a similar finding for the case of Greece and Pakistan economy, respectively. Likewise, Cherniwchan(2012) examines the role of observed industrialization on the environmental quality for 157 economies over 1970-2000. ...
Structural transformation has been recognized as a critical mechanism for improving living standards for developing countries in Africa. However, the growing evidence indicates that such change is associated with considerable damage to the environment quality and, hence, challenging sustainable development. The present study investigates industrialization's influence on the environment quality for 20 low-income countries in Sub-Saharan Africa during 1980-2018. We employed two measurements for environmental quality, which are CO2 and nitrous dioxide emissions. Likewise, the study applied the Fully modified OLS and the Dynamic OLS as the most modern and suitable techniques related to the panel data analysis. Overall, the FMOL and DOLS results show that industrialization has an insignificant influence on environmental quality. The results also show that these countries' population size is the main driver for environmental quality changes. This finding implies that these countries should continue in their current efforts regarding promoting the industrial sector without wondering about sustainable development.
... There is extensive literature that establishes a causal relationship with mixed findings between energy consumption and economic activity. Several studies have found that the causality runs from the consumption of energy to the growth of economies which means that the conservation of energy can be detrimental to economic growth (Khan 2019;Gökmenoğlu and Taspinar 2016;Zeb et al. 2014). About 19% of growth rate was reported in Pakistan's transportation sector from the year 1990 to 2015 which is regarded to be a tremendous pace, and inefficient transportation could be improved (Ahmad and Puppim 2016). ...
Global warming regarded as the major global issue over the past few decades, whereas carbon dioxide (CO2) emissions have been cited as one of the main causes of this problem. Therefore, this study aims to investigate the effect of energy consumption, economic development, and population growth on high CO2 emitting sectors of Pakistan such as transportation, industrial, and household. The data used in this study was taken from multiple databases from 2000 to 2018. We employed novel grey relational analysis (GRA) models to assess the connection between gross domestic product (GDP) per capita, population, energy consumption, and CO2 emission. Furthermore, the Hurwicz method was used to analyze which factor contributing more to CO2 emission. Result reveals that CO2 emission, gross domestic product per capita, population, and energy consumption showed a strong association among all sectors. Whereas, population contributes more to intensifying CO2 emissions in the transportation sector of Pakistan. This study provides useful insights for policymakers to take preventive and corrective measures to overcome CO2 emissions as well as sustainable development.
... It is estimated that in Pakistan the carbon emissions have raised from 76 million tons in 1990 to 200 million tons in the year of 2006 and CO2 emissions by an average increase of 6.5% annually and would grow to 482 million tons by 2020. Khan and Jamil (2015) tried to decompose the changes in overall CO2 emissions in Pakistan for the period of 1990 to 2012 by using Log Mean Divisia Index (LMDI). On the basis of findings, the researchers suggest that policy makers should try to encourage the conversion of the output level towards more energy efficient sectors in Pakistan. ...
The study attempts to examine various factors responsible for environmental degradation in Pakistan. Contributing towards economic growth, these factors added pollutants as a byproduct to the environment. Carbon dioxide (CO2) emission rate is one of such pollutants and has been used as a dependent variable in the study. Numerous factors are responsible for environmental damage, but the study includes the major ones. These determinants are economic growth, population, energy consumption and industrialization, and time-series data of these variables from 1972 to 2018 are utilized for empirical analysis in the study. Long run relationship is computed using Auto Regressive Distributed Lag (ARDL). Findings of the study revealed that three factors; population, energy consumption and industrialization are positively and significantly contributed to environmental degradation in Pakistan. While, economic growth is negatively contributing towards environmental degradation. The paper concluded with a finding that population growth needs to be controlled. Besides this, clean and green energy should be promoted. Lastly, EPAs must be strengthened for their effective role.
... Pakistan contributes 0.8% in global greenhouse gases, but it faces disproportionately large consequences of climate change. An estimated annual cost of environmental problems in Pakistan amounts to 6% of its GDP [18]. ...
The role of financial development for the environment has been extensively debated but the empirical results largely remain inconclusive. Empirical studies generally assume symmetric relationships, which can produce biased results. This study investigates the role of asymmetries in shaping the relationship of financial development (FD) with the environment by employing nonlinear autoregressive distributed lag (NARDL) model over the period 1972–2018. The structural unit root test of Zivot and Andrews indicates that all variables are integrated of order one and bound tests confirm long run relationship between the variables. The results validate the asymmetric association between FD and the environment as CO2 emissions are largely affected by negative shocks in FD in the short and long run. The dynamic multiplier analysis also supports the results by showing the dominance of a higher impact of a negative component of FD on carbon emissions than a positive component. This study concludes that assuming the symmetric effect of FD on CO2 emissions might be misleading. The study suggests that the policy makers may strive to achieve high growth rates using environmentally friendly financial development. Moreover, the negative asymmetric impact of FD needs to be considered in the development of financial sector.
... The last 6 years data, i.e., 2011e2016 shows weak decoupling state, which is expected to be transformed due to strict environmental regulations converted in to strong decoupling state at the end of this decade and hereafter. Khan and Jamil (2015) confined that Pakistan's urban areas largely influenced with high particulate emissions due to large dependency on fossil fuel energy consumption, which in turn to lead GHG emissions. On the other hand, high population density and its annual growth results in excessive energy demand, which turned into greater food grain demand in a country. ...
The United Nation Sustainable Development Goals emphasized to meet the global food security challenges by mechanized farming; access of clean water challenges by renewable freshwater withdrawals; clean energy issues determined by clean fuel and cleaner technologies; and combat climate change by limiting anthropogenic emissions of carbon, fossil fuel, and Greenhouse Gas emissions in the air. This study examined the aforementioned United Nation Sustainable Development Goals in the context of Pakistan by using a time series data from 1970-2016. The study employed Tapio’s elasticity of decoupling state to analyze the relationship between water-energy-food resources and carbon-fossil-greenhouse gas emissions in a given country context. The results of Tapio elasticity found that carbon-fossil-greenhouse gas emissions’ contamination in water-energy-food’s resources are quite visible that exhibit weak decoupling state, expensive negative decoupling state, and strong decoupling state in the different decade’s data, which substantiate the ecological cost in water-energy-food’s resources. The results emphasized the need to adopt different sustainable instruments in a way to limit carbon-fossil-greenhouse gas emissions in water-energy-food resources through cleaner production technologies, renewable energy mix, environmental certification, anti-dumping tariff duty, strict environmental regulations, etc. These instruments would be helpful to achieve environmental sustainability agenda for mutual exclusive global gains.
