Coal efficiency, carbon reduction, and future policy perspective in Pakistan’s economic growth: a decomposition and decoupling approach

Pakistan is moving toward the large-scale use of coal. Coal plays a dominant role in Pakistan’s energy mix and is estimated to reach 30% by 2030. The purpose of this study is to analyze coal imports and indigenous reserves in relation to CO2 emissions. In particular, this study constructs the logarithmic mean Divisia index (LMDI) method to see the impact of the factors, decoupling index for the economic relationship, and pollution from coal-fired power plants from 1986 to 2019. The empirical results show that 1) coal consumption and imports are interrelated, while coal production has had the lowest production level since 1986; 2) the energy intensity impact plays a medium role in decreasing coal utilization, followed by the coal share effect; however, the aggregated impact accounts for 0.023% of the total coal use; 3) the economic and population activity effects progressively increase with coal consumption by 0.25% and 0.35%, respectively, with the annual average growth; 4) only “three” decoupling states were observed: expansive coupling, expansive negative decoupling, and weak decoupling. Expansive negative decoupling occurred due to high energy share and energy intensity. Expansive coupling occurred only in 2001 due to rapid growth in coal proportion and a sluggish decrease in energy intensity, and weak decoupling showed a decoupling association between economic growth and coal utilization; and 5) the various coal compositions, such as moisture, volatile matter, fixed carbon, ash, and sulfur, can be evaded by 1.82, 4.83, 5.16, 1.43, and 0.39 Mt currently. Finally, environmental analysis recognized that implementing clean coal technologies significantly saves fuel and, consequently, reduces emissions. This study also discusses further policies

Energy substitution effect on transport sector of Pakistan: A trans-log production function approach

Abstract(#br)Transport sector of Pakistan is one of the highest fossil fuel consumption and carbon dioxide (CO 2 ) emission sector. As a key user of fossil fuel energy, Pakistan’s transport sector has created many problems i.e. noise, air pollution, CO 2 emissions and environmental problem. In this study, trans-log production function model for Pakistan’s transport sector is established and input factors of labor, capital, and energy consumption are comprised. The output elasticity of an individual, input elasticity between a pair of factors, and elasticity of substitution between input factors are analyzed. To manage the multicollinearity issue, ridge regression is applied at different values of K. From 1991 to 2018, the outcomes show that output elasticities and a pair of input factor’s elasticities are increasing. The elasticities of substitutions between labor-energy consumption and capital-energy consumption show higher outcomes because of the more elevated amount of substitution elasticities. The substitution elasticity between labor and capital starts from 0.9797 to 0.9326 with slightly decreasing trend. The outcomes suggest that maximum output can be achieved by increasing capital and energy technologies. By allocating the maximum capital in the transport industry, energy-saving technologies, substitution between energy and capital, and substitution among capital-labor can enhance environmental protection. In the above’s view function, the present study estimates the level of energy-saving and CO 2 emissions reduction under the different scenarios from 2015 to 2018. The policy suggestions of the results are given below

Nexus between Economy, Agriculture, Population, Renewable Energy and CO2 Emissions: Evidence from Asia-Pacific Countries

This study uses panel co-integration methods and Granger causality examines to scrutinize the dynamic causal relationship between carbon dioxide (CO2) emissions, gross domestic product (GDP), renewable energy (RE), agriculture value added (AVA) and population for the thirteen developed and developing Asia Pacific countries (APCs) covering the period 2005-2017. The results evaluate in two ways: in the short-run, Granger causality test (GCT) is operating from AVA to GDP and express bidirectional causation among GDP and agriculture. In the distant future, there is causality from RE and Population to CO2emissions. The short-run causality is important due to the agriculture sector which causes in boosting GDP while economic development, population and clean energy (including waste and combustible) raise CO2 emissions causes in the reduction of production and services. The research finds out that reduction in AVA, GDP increase, uncontrolled population and lack of attention on clean energy are interrelated in creating emissions. Policy recommendation insights that Asian Pacific establishments should control the population, less use of fossil fuel, encourage clean energy technologies such as solar and wind to fight with global warming

Analysis of Energy Crisis, Energy Security and Potential of Renewable Energy: Evidence from Pakistan

Over the last thirty years, Asian countries have become a chief player in the worldwide scene. Pakistan is facing an acute energy disaster since last decade that impacts on social and economic development. Sustainable energy supply is an essential feature for the economic growth of any society. From the last five years, Pakistan is facing a shortfall between 4,000-5,000 megawatt. This study inspects the association between energy security, energy crisis, energy demand, energy supply, and renewable potential in Pakistan. It also evaluates the final energy demand-supply gap, provincial renewable energy distribution, sectorial distribution, and policy recommendation for future energy. For this study, we applied renewable and non-renewable energy scenarios during 2014-2035 and Market-Allocation method to prove the energy situation in Pakistan. The outcomes show that renewable resources are the best option in reducing energy risk, import cost, and enhance environmental and economic sustainability. With the objectives of our key findings, targeted suggestions and policies are given

Differentiation of Small Hepatic Hemangioma from Small Hepatocellular Carcinoma with Tri-Phasic Helical Computed Tomography Method

Background: Hepatocellular carcinoma (HCC) ranks second amongst all causes of cancer deaths globally. It is on a rise in Pakistan and might represent the most common cancer in adult males. Among women, HCC is the 7th most common cancer and 6th most common cancer related death. In Pakistan prevalence of HCC varies from 3.7%-16% of malignant tumors and most common cause of HCC is viral hepatitis B, C and D related cirrhosis. Pakistan contributes significantly to global burden of hepatitis C, which is a known risk factor for HCC, and has one of the highest prevalence rates (>3%) in the world. Objective: To find out the difference of small hemangioma from small hepatic cellular carcinoma by using tri- phasic helical Computed Tomography method. Methodology: In this descriptive study, among 81 patients of suspected hepatocellular carcinoma and hepatocellular hemangioma were selected with age and gender discrimination by convenient sampling, at Department of Radiology, UOL Teaching hospital Lahore Pakistan. 128 slice Computed Tomography Toshiba Aquilion machine was used. Results: Out of 81 patients collected with the suspicion of hepatic hemangioma and hepatocellular carcinoma , 41 were females and 40 were males who visited radiology department. It shows 50.6% were females and males were 49.4%. Out of 81 patients, 25 patients came with HHS and 31 were with HCC. 25.9% develop carcinoma on left side, 32.1% on right side, 6.2% on R/L side and remaining 35.8% were Nill. Out of 81 patients 8 develop carcinoma on anterior, 5 on both, 3 on caudate, 5 on lateral,13 on both 4 on middle, 7 on posterior, 6 on segment eight, 1 on segment 4, 1 on segment 7, 1 on segment 2 and remaining 36 sites were nill. 27.5% males develop HCC and 48.8% females develop HCC. Out of 81 patients 36.6% female patients develop HHS and 25.0% male patients develop HHS. Conclusion: In this study we conclude that females develop a large number of HCC and HHS than males. Hepatocellular carcinoma shows enhancement in early arterial and early washout phase while post-contrast images showing capsule-appearance which is relatively specific for HCC. On the other hand, HHS shows uniform enhancement in arterial phase and iso- or hyper-attenuating to liver parenchyma on delayed phase. Keywords: Hepatocellular carcinoma, Hepatocellular hemangioma, Computed tomography DOI: 10.7176/JHMN/73-07 Publication date: April 30th 202

Depression, Anxiety And Stress Among Medical And Allied Health Sciences Students At Sargodha Medical College

Abstract Objective: This study attempts to determine the frequency of depression, anxiety and stress and associated factors among medical and allied health sciences students of Sargodha Medical College.  Methods: The nature of the study is cross-sectional, among 350 (175 each) medical and allied health sciences students of Sargodha Medical College. The students were recruited using convenient sampling. Socio-demographic information was recorded and depression, anxiety and stress were assessed using the depression, anxiety and stress scale (DASS-21). Statistical Package for Social Sciences (SPSS) version 24.0 was used for data entry and analysis. Results: The study shows that nearly half of medical students (53.1%) had depression, 69.7% had anxiety and 44% had stress; while among allied health sciences students, 60.6% were depressed, 73.7% had anxiety and 45.1% had reported stress. The mean depression score among medical students was 12.19 ± 9.98 and 13.29 ± 11.12 among allied health sciences students (p≤0.332). Conclusion: Based on the results, it is recommended that various methods should be adapted and prioritized for enhancing the mental health of the students to support and improve academic learning among students.

Mediation of The Superior-Subordinate Communication In Determining Work Engagement Among Bureaucrats

This study aims to investigate how the superior-subordinate communication mediates policy formulation and employees' dedication in work engagement among the serving bureaucracy in Punjab (province of Pakistan) government. The study used a cross-sectional design vis-à-vis survey method to collect data from a representative sample (n=250) of serving bureaucrats of the Punjab government. The findings showed that there was a positive association between policy formulation (PF) and dedication towards work engagement (WE). Furthermore, the findings revealed that the relationship between policy formulation (PF) and dedication towards work engagement (WE) was partially mediated by superior-subordinate communication (SSC). The study addressed the research gap regarding the association of the policy formulation (PF) and dedication towards work engagement (WE) by examining the mediation of superior-subordinate communication (SSC) in their association by progressing the LMX theory in a less researched context of Pakistan. The results explained how more sophisticated work engagement could be achieved in the implementation of the policies by improving the communication channels between superiors and subordinates among the different ranks of the bureaucrats.&nbsp

Sectorial study of technological progress and CO 2 emission: Insights from a developing economy

ABSTRACT(#br)Many studies have stated that technological progress is an important driver of carbon dioxide (CO 2 ) emissions and energy consumption. However, the sectorial differences in the relationship between CO 2 emission and technological progress have been understudied by scholars. This study attempts to fill such gap by empirically investigating the impact of technological progress on CO 2 emissions. A quantile regression method and balanced national data from Pakistan covering the period of 1991–2017 are used to establish relationships among the variables. The results and analysis reveal that the agriculture and services sectors have a negative impact on CO 2 emissions, whereas the construction, manufacturing, and transportation sectors greatly contribute to these emissions. The lower, medium, and upper-level emitters are used to understand the percentile conditions of each variable. A scenario analysis is also performed to forecast the reduction proportion of CO 2 emissions for the best understanding and policy implication in 2030, 2035, and 2040. The results of this study provide useful insights into the relationship between technological progress and CO 2 emissions and suggest different scenarios for reducing CO 2 emissions in the future that can support policy makers and planners

Integrating life cycle assessment and machine learning to enhance black soldier fly larvae-based composting of kitchen waste

Around 40% to 60% of municipal solid waste originates from kitchens, offering a valuable resource for compost production. Traditional composting methods such as windrow, vermi-, and bin composting are space-intensive and time-consuming. Black soldier fly larvae (BSFL) present a promising alternative, requiring less space and offering ease of handling. This research encompasses experimental data collection, life cycle assessment, and machine learning, and employs the Levenberg– Marquardt algorithm in an Artificial Neural Network, to optimize kitchen waste treatment using BSFL. Factors such as time, larval population, aeration frequency, waste composition, and container surface area were considered. Results showed that BSFL achieved significant waste reduction, ranging from 70% to 93% by weight and 65% to 85% by volume under optimal conditions. Key findings included a 15-day treatment duration, four times per day aeration frequency, 600 larvae per kilogram of waste, layering during feeding, and kitchen waste as the preferred feed. The larvae exhibited a weight gain of 2.2% to 6.5% during composting. Comparing the quality of BSFL compost to that obtained with conventional methods revealed its superiority in terms of waste reduction (50% to 73% more) and compost quality. Life cycle assessment confirmed the sustainability advantages of BSFL. Machine learning achieved high accuracy of prediction reaching 99.5%.Web of Science1516art. no. 1247

Determination of Renal Changes by Ultrasonography in Patients with Type-2 Diabetes Mellitus

Background: Diabetes Type 2 causes damage to the kidneys; leading to diabetic nephropathy and high blood pressure. The aim of this study is determination of renal changes on ultrasonography in diabetic patients. Objective: This study evaluates changes in kidneys in patients presenting with type II diabetes mellitus having normal renal function test as compared to non-diabetics. Methods: It was a cross sectional descriptive study conducted on 116 patients with type 2 diabetes mellitus by using convenient sampling technique. The study was conducted at Ultrasound Department of Gulab Devi hospital Hospital from July 2019 to September 2019. Results: Out of 116 patients there were 43(37.1%) female and 73(62.1%) were male. The mean age of the participants was 53.24 ±10.49. This study shows that the mean volume of Rt kidney was 1.229E2 ±38.39 ranging from 25ml to 218ml and mean volume of Lt kidney was 1.1691E2 ±41.96 ranging from 26ml to 231ml in patients presenting with DM Type 2 and mean parenchymal thickness of the Rt kidney 14.40 ±6 range from 0.86mm to 1.25mm and Lt kidney 13.7 ±5 range from1.2mm to 25mm.This study showed that mean volume of both kidneys and  parenchymal thickness increased in patients having diabetes mellitus. Conclusion: Ultrasound is a reliable and easily available modality to detect renal changes and complications in earlier stages of Diabetes mellitus. Keywords: Type II diabetes mellitus, Renal changes, Ultrasonography DOI: 10.7176/JHMN/68-07 Publication date: November 30th 201