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• Presenting a set of mathematical models for green flowshop scheduling problems. • Considering common carbon reduction policies and their corresponding scenarios. • Providing analysis of models and insights to design a framework for green flowshops. • Industries can use our cost-effective strategies to meet limits mandated by government. • Government can explore our integrated framework to gauge impacts of carbon policies. In this paper we consider, from an environmental policy-maker perspective, how carbon reduction policies impact the economic competitiveness of the manufacturing sector. Specifically, we focus on flowshop scheduling – which typically aims to minimize makespan for purely economic objectives – and consider how three common carbon reduction policies – namely, taxes on emissions, baselines on emissions, and emissions trading schemes – can create competitive green flowshops that balance minimization of makespan and carbon emissions. The goal is to enable policy-makers to understand how to set policies and control parameters to achieve environmental objectives while ensuring global economic competitiveness of industry. We initially present a set of mixed-integer linear programming (MILP) models for flowshop scheduling problems operating in a regulated environment in which each carbon reduction policy is adopted. We then introduce a bi-objective scheduling framework for the corresponding problem to obtain alternative solutions under each policy. These models and their computational results however, are not the main focus of the study, but are presented as a means to demonstrate how green policies co-exist with economic objectives, with policy-makers in control of the balance. To this end, based on financial data from Australia's carbon emissions profile, we provide a policy-oriented analysis of the models, and some managerial insights into the effect of scheduling strategies on carbon emissions under different reduction policies. These insights offer support to both environmental policy-makers and corporate production and sustainability managers to determine whether it is technically feasible and profitable to replace traditional scheduling strategies with environmentally friendly scheduling strategies. [ABSTRACT FROM AUTHOR]

• Direct and indirect effects of sectors on net energy consumption are analysed. • Level effect is identified as the major driver for increasing energy consumption. • Manufacturing has the largest energy consumption reduction potential. • How to decrease net energy consumption has been offered to policy-makers. This paper provides a comprehensive analysis of Australian net energy consumption between 2004–05 and 2014–15. Results from environmentally-extended input-output (EEIO) analysis show that the Transport sector has the largest direct effect on net energy consumption in industrial sectors, which decreased by about 35% for net energy consumption per million $AUD in the period. The Export sector has the largest direct net energy consumption while Households consumption results in the largest net energy consumption embodied in different categories of Final demand. The structural decomposition analysis (SDA) decomposes the change of net energy consumption into five drivers, in which net energy intensity mainly reduces Australian net energy consumption by about 8000 Petajoules, while the level effect of Final demand increases it by about 10,000 Petajoules. Analysis of forward and backward linkages highlights the Manufacturing sector as the key industrial sector with the largest energy consumption reduction potential via minor changes in its input and Final demand. This indicates that more attention should be given to the reduction of energy demand from the consumption patterns of Households consumption, the improvement of energy intensity, and the application of cleaner technologies in the Transport and Manufacturing sectors. The Australian Environmental-Economic Accounts is combined with Australian input-output tables to construct the EEIO tables for net energy consumption. The combination of economic and environmental data sets provides a depth of understanding their potential to inform environmental policy decisions. The novelty of the research is the combination of economic and energy data sets, the application of EEIO model, the implementation of the additive SDA method, and the use of forward and backward linkages for the Australian energy system. [ABSTRACT FROM AUTHOR]

• Bottom-up estimation tool to develop electric public transport (EPT) charging loads. • Uses GTFS public data and can be scaled to hundreds of cities/states globally. • EPT could add 17% to critical peak demand on some distribution zone substations. Battery electrified public transit (BEPT), including buses and passenger ferries, is a promising solution to transport-related climate emissions and urban air pollution, but introduces potentially challenging large, coincident demand in the low-voltage distribution network. This paper presents a tool for estimating the energy and charging demand of electrified public transit using public data that is available in over 150 cities/states globally and demonstrates it in two case studies. The tool applies heuristic vehicle scheduling to existing public General Transit Feed Specification data to model the charging profiles and electricity consumption of BEPT for various charging regimes across different geographical scales. For the case study of New South Wales, Australia, the impacts of BEPT are most significant at the low-voltage network, where adding a battery-electric bus depot was found to increase the annual critical peak demand at the local zone substation in Summer by up to 17% while exacerbating demand during the daily evening peak period by 20–30%. Across the entire state of NSW, a full transition to BEPT increases annual electricity consumption by 1.28–1.34% and peak daily demand by 1–3%. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, our goal is to examine the unit root null hypothesis in energy consumption for Australian states and territory. We consider sectoral energy consumption for Australia and its six states and one territory using time series data for the period 1973–2007. This is the first study that does this. Generally, except for some cases in South Australia, we find strong support that shocks to energy consumption have a temporary effect on energy consumption in Australia. [Copyright &y& Elsevier]

• Development of a new enthalpy-based Climatic Cooling Potential index. • Critical evaluation of using enthalpy to evaluate Climatic Cooling Potential. • Practical significance of the enthalpy-based Climatic Cooling Potential. • Critical discussion of climatic effects on applicability of Ventilative Cooling. • Spatiotemporal analysis of the Climatic Cooling Potential in Australia. Ventilative Cooling is a promising technique to improve the energy efficiency of buildings through reduced need for mechanical cooling to maintain thermal comfort. To assess the feasibility of Ventilative Cooling in a specific location, it is useful for designers to be able to evaluate the climate potential for cooling. This paper describes a new and enhanced version of the Climatic Cooling Potential (CCP) method, which is a simplified method to evaluate the climate potential for passive cooling that does not require detailed knowledge of the building characteristics. The proposed Enthalpy Climatic Cooling Potential (CCP h) integrates humidity into the climate evaluation, using the enthalpy difference between indoors and outdoors, instead of the temperature difference. It accounts for latent heat, providing a better estimate of locations where the use of outside air will be beneficial from an energy perspective. The methods were compared by mapping the Ventilative Cooling potential for the Australian climate, using weather data from 391 weather stations across Australia. Results showed that most of the highly populated cities in the south of Australia have a climate suitable for Ventilative Cooling. This is true even in the summer period, although the area where the climate is beneficial is significantly larger during the shoulder seasons and winter. The analysis showed that using the CCP index, rather than the new CCP h index, can lead to an under-estimation of the cooling potential during dry winters and an over-estimation during humid summers, due to the contribution of the latent heat. [ABSTRACT FROM AUTHOR]