Abstract
Upholding sustainability in the use of energies for the increasing global industrial activity has been one of the priority agendas of the global leaders of the West and East. The projection of different GHGs has thus been the important policy agenda of the economies to justify the positions of their own as well as of others. Methane is one of the important components of GHGs, and its main sources of generation are the agriculture and livestock activities. Global diplomacy regarding the curtailment of the GHGs has set the target of reducing the levels of GHGs time to time, but the ground reality regarding the reduction is far away from the targets. Sometimes, the targets are fixed without the application of scientific methods. The aim of the present study is to examine sustainability of energy systems through the forecasting of the methane emission and agricultural output of the world’s different income groups up to 2030 using the data for the period 1981–2012. The work is novel in two senses: the existing studies did not use both the Box–Jenkins and artificial neural network methods, and the present study covers all the major economic groups in the world which is unlike to any existing studies. Two methods are used for forecasting of the two. One is the Box–Jenkins method, where linear nature of the two variables is considered and the other is artificial neural network methods where nonlinear nature of the variables is also considered. The results show that, except the OECD group, all the remaining groups display increasing trends of methane emission, but unquestionably, all the groups display increasing trends of agricultural output, where middle- and upper middle-income groups hold the upper berths. The forecasted emission is justified to be sustainable in major groups under both methods of estimations since overall growth of agricultural output is greater than that of methane emission.
Highlights
From the last half of 19th century to till date, economic growth turns into the most important particle of almost all socioeconomic systems in our mother earth
Looking at the autocorrelation functions (ACFs) and partial autocorrelation functions (PACFs), we have identified the orders of AR and MA processes. ere may be more than one alternative of the shapes of ACF and PACF, and we will have to determine the optimum structure of ARIMA
We have attempted to make forecasting of methane emissions and agricultural value added by BJ and artificial neural network (ANN) methods and tested sustainability of such emissions vis-a-vis agricultural output for the major economic groups of the world for the time up to 2030. e results for methane emissions are seen to be declining for the OECD group but
Summary
From the last half of 19th century to till date, economic growth turns into the most important particle of almost all socioeconomic systems in our mother earth. To achieve the higher growth trajectory, each and every economy put all of their resources on the board without giving any potentiality to future generations. It is only in late 90s, when scarcity of resources and a relatively new term “global warming” knocking the door of the policy and law makers around the world, human beings push forward the agenda of sustainability. It has been historically evidenced that growth can revolutionize the structural changes in both production and consumption Such changes may occur from either directions or both, that is, either from level or composition or from both of them [3]. Both the level and the composition of production and consumption activities affect environmental degradation and raise the scope of greenhouse gas (GHG) emissions, owing to which the prospects
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