Sectoral Environmental Degradation And Environmental Sustainability

Global warming and air pollution are regarded as the major global issues over the past few decades,and the environmental pollution which holds the largest share of carbon dioxide emissions,have been cited primarily because of human activities as a major cause of this problem.Accuracy estimates for environmental pollution is a key element in defining the best strategies for reducing emissions from various sectors of the economy.Therefore,the research stream has been divided into three phases.The first phase of the 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 from 2000 to 2018.We employed novel Grey Relational Analysis(GRA)models to assess the connection between GDP per capita,population,energy consumption,and CO2 emission.Further,the Hurwicz method was used to analyze which factor contributing more to CO2 emission.Result reveals that CO2 emission,GDP per capita,population and energy consumption showed a strong association among all sectors.Whereas,population contributes more to intensifying air pollution in the transportation sector of Pakistan.In the second phase of study,an initial attempt has been made to estimate and forecast the GHG emissions in Pakistan from five major sectors such as energy,industrial,agriculture,waste,land-use change,and forestry.The data was taken from the official website of Pakistan climate database from 1990 to2016.We employed advanced mathematical modeling,namely a non-homogenous discrete grey model(NDGM)to predict sector-wise GHGs emissions.Moreover,the present study is a milestone in the GHGs growth analysis by utilizing the Synthetic Relative Growth Rate(SRGR)and Synthetic Doubling Time model(SDTM).The results reveal that the industry,land-use change and forestry contribute more in terms of increasing GHGs emissions till 2024,whereas,agriculture and waste required comparatively less time to reduce GHGs emissions double in number among five sectors.All five sectors show an increasing trend in forecasting GHGs emissions between 1990 and 2016.However,the results indicate that land-use change and forestry and industrial sector are more likely to be a reason for the increase in GHGs emissions in the future followed by Agriculture,energy and waste sector.The land-use change and forestry found prone to increase emission in the future,the doubling time()suggests less time expected to reduce GHGs.While in the third phase of the research,we primarily forecast growth trends in renewable and non-renewable energy production and consumption in Asia and Oceania region from 2017 to 2025 by applying novel grey forecasting model namely grey Even model(EGM),Discrete grey model(DGM),non-homogeneous discrete grey model(NDGM)and Optimized Discrete grey model(ODGM).Mean absolute Percentage Error(MAPE)was employed to measure the performance of all four grey models.Data used for forecasting was collected from the official website of International Energy Agency(IEA)for the period of 1980 to 2016.Result reveals that the consumption and production of coal as non-renewable energy source is comparative very high than any other energy source and depicted increasing trend till 2025.However,the petroleum production remained consistent for many years but the consumption level was higher than its production.Moreover,in nuclear and other renewable energy sources under NDGM grey model,the production was high as compared to its consumption.Further,NDGM showed better performance over other grey forecasting models.This study suggest provides useful information for policy and decision makers to make environment more sustainable.This study provides useful insights for policymakers,government,and decisionmakers to take serious measures to reduce environmental pollution as well as achieve sustainability.