The supreme motive for the church's obedience to her Lords command to “Go ye into all the world” must be to glorify God by proclaiming Him as the One who is so abundantly worthy to be known and praised for who and what He is. The church must do its best with all the means it has been providentially given by God.Īlong with its labors within its own membership, the labors of missions puts the church in the position of serving as God's servant in the accomplishment of His eternal purposes of election and reprobation. The objects of mission work are all whom God in His providence brings into their path. This work must be performed to the fullest of the ability God gives. Mission and evangelism work is not a matter of choice, but one of obedience. In His “Great Commission” Jesus stated the task in the most simple terms: teach.įirst, the church of Christ performs the work of missions in obedience to her King, Jesus. The AED-BP results on the Annual Maximum Runoff series for the stations Yichang and Hankou along the Yangtze river are among the first that show a possible effect of the presence of the Three Gorges dam.The task of the church in her work of missions is to teach. The results show that AED-BP has a performance that is similar to PLD-MC, but has an advantage in that it is not necessary to select a distribution family for the data. The change points found in the original publications are used as a reference in this present paper. The real data are the hydro-meteorological data analysed in other studies. Synthetic data were generated from three parametric distributions: Fréchet with a constant shape parameter, log-normal, and gamma distributions. The methods were applied to both synthetic and real data. To evaluate the practical usability of confidence curves constructed by AED-BP, its properties were examined and its performance was compared to that of PLD-MC. A confidence curve provides a representation of the uncertainty in the outcome of the change point analysis. The method is compared with a method based on parametric Profile Likelihood and a Deviance function combined with Monte Carlo simulation (PLD-MC). In this paper, a method based on Approximate Empirical likelihood ratio and a Deviance function combined with bootstrapping (AED-BP) is proposed to construct a confidence curve for the location of a change point. Our results clearly indicate that pathways for the retrofitting of buildings and the decarbonisation in electricity generation need to be taken into account jointly when designing renewable and low-carbon heat systems to optimally reduce carbon emissions towards 2050 and reduce future carbon lock-ins. The results show that (i) the committed emissions are ten times lower between 20 in scenarios in which ambitious measures are taken for the insulation of buildings and the decarbonisation in electricity generation, (ii) only in these ‘ambitious scenarios’ low temperature heat systems, such as heat pumps and low temperature heat networks, are optimal solutions for minimising committed emissions, (iii) if less ambitious insulation and decarbonisation measures are taken, high temperature heat options can be part of the heat mix with lowest committed emissions, and (iv) the minimum heat density for low temperature heat networks is not always achieved, creating risks for carbon lock-ins when applying these heat networks. Nine scenarios with different pathways for the insulation of buildings and the decarbonisation in electricity generation were considered and applied to three neighbourhoods in the city of Amsterdam, the Netherlands. To establish this approach, we integrated bottom-up heat demand modelling at neighbourhood scale with a mixed-integer non-linear optimisation problem. We propose a computational approach for finding a mix of heat options per neighbourhood that minimises cumulative carbon emissions between 20, referred to as committed emissions, while at the same time adhering to technological constraints at both the household and neighbourhood scales. Infrastructure for heat provision in the built environment needs to change remarkably to support lowering carbon emissions and achieving climate mitigation targets before 2050.
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