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Abstract Cities are the major contributors to energy consumption and CO2 emissions, as well as being leading innovators and implementers of policy measures in climate change mitigation. Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is an agglomeration of cities put forward by China to strengthen international cooperation among “Belt and Road” countries and promote low-carbon, inclusive, coordinated and sustainable development. Few studies have discussed the emission characteristics of GBA cities. This study, for the first time, compiles emission inventories of 11 GBA cities and their surroundings based on IPCC territorial emission accounting approach, which are consistent and comparable with the national and provincial inventories. Results show that (a) total emissions increased from 426 Mt in 2000 to 610 Mt in 2016, while emissions of GBA cities increased rapidly by 6.9% over 2000–2011 and peaked in 2014 (334 Mt); (b) raw coal and diesel oil are the top two emitters by energy type, while energy production sector and tertiary industry are the top two largest sectors; (c) GBA cities take the lead in low-carbon development, emitted 4% of total national emissions and contributed 13% of national GDP with less than a third of national emission intensities and less than three-quarters of national per capita emissions; (d) Macao, Shenzhen and Hong Kong have the top three lowest emission intensity in the country; (e) most of GBA cities are experiencing the shift from an industrial economy to a service economy, while Hong Kong, Shenzhen, Foshan and Huizhou reached their peak emissions and Guangzhou, Dongguan and Jiangmen remained decreasing emission tendencies; (g) for those coal-dominate or energy-production cities (i.e. Zhuhai, Zhongshan, Zhaoqing, Maoming, Yangjiang, Shanwei, Shaoguan and Zhanjiang) in mid-term industrialization, total emissions experienced soaring increases. The emission inventories provide robust, self-consistent, transparent and comparable data support for identifying spatial–temporal emission characteristics, developing low-carbon policies, monitoring mitigation progress in GBA cities as well as further emissions-related studies at a city-level. The low-carbon roadmaps designed for GBA cities and their surroundings also provide a benchmark for other developing countries/cities to adapting changing climate and achieve sustainable development.

Currently, natural gas in Brazil represents around 12.9% of the primary energy supply, with consistent annual growth during the last decade. However, Brazil is entering a time of uncertainty regarding future gas supply, mainly as import from Bolivia is being renegotiated. As such, diversification of gas supply sources and routes need to be considered. Energy systems and infrastructure models are essential tools in assisting energy planning decisions and policy programmes at regional and international levels. In this study, a novel combination of a simulation-based integrated assessment model (MUSE-South_Brazil) and the recently-developed Gas INfrastructure Optimisation model (GINO) is presented. The Brazilian region represented by the five southern states served by the Bolivian gas pipeline (GASBOL) has been investigated. Modelled projections suggest that regional gas demand would increase from 38.8 mcm/day in 2015 to 104.3 mcm/day by 2050, mainly driven by the increasing demand in the industry and power sectors. Therefore existing regional gas infrastructure would be insufficient to cover future demands. Three different renegotiation scenarios between Brazil and Bolivia were modelled, obtaining distinct cost-optimal infrastructure expansion pathways. Depending on the scenario, the model expects gas demand to be covered by other supply options, such as an increase in pre-salt production, LNG imports and imports from a new Argentinian pipeline.

Abstract Steady-state convective heat-transfer and pressure-drop characteristics for laminar air-flows over a horizontally-orientated simulated printed-circuit board (PCB) assembly have been measured experimentally and predicted numerically. The considered assembly consisted of a plate with uniformly-spaced identical electrically-heated rectangular uniform ribs mounted orthogonal to the mean air-flow. Mathematical correlations were determined between the cavity-height to ribs' protrusion and width-to-protrusion ratios, namely ( H B ) and ( L B ), respectively, and the Reynolds number (Rec) of the air-flow with the steady-state Nusselt number (Nuc) and friction factor (fc), both of these latter parameters being highly dependent on H B . When H B ≥8 , natural convection provided a significant portion of the total rate of heat transfer, and mixed (i.e. forced plus natural) convection ensued. For assemblies with ribs each of the same volume, the assembly with the ribs having a larger top surface-area has the higher heat-transfer coefficient and smaller pressure drop under otherwise identical conditions.

The goal of this paper is to assess the suitability of hybrid PVT systems for the provision of electricity and hot water (space heating is not considered) in the UK domestic sector, with particular focus on a typical terraced house in London. A model is developed to estimate the performance of such a system. The model allows various design parameters of the PVT unit to be varied, so that their influence in the overall system performance can be studied. Two key parameters, specifically the covering factor of the solar collector with PV and the collector flow-rate, are considered. The emissions of the PVT system are compared with those incurred by a household that utilises a conventional energy provision arrangement. The results show that for the case of the UK (low solar irradiance and low ambient temperatures) a complete coverage of the solar collector with PV together with a low collector flow-rate are beneficial in allowing the system to achieve a high coverage of the total annual energy (heat and power) demand, while maximising the CO2 emissions savings. It is found that with a completely covered collector and a flow-rate of 20L/h, 51% of the total electricity demand and 36% of the total hot water demand over a year can be covered by a hybrid PVT system. The electricity demand coverage value is slightly higher than the PV-only system equivalent (49%). In addition, our emissions assessment indicates that a PVT system can save up to 16.0tonnes of CO2 over a lifetime of 20years, which is significantly (36%) higher than the 11.8tonnes of CO2 saved with a PV-only system. All investigated PVT configurations outperformed the PV-only system in terms of emissions. Therefore, it is concluded that hybrid PVT systems offer a notably improved proposition over PV-only systems. © 2014 The Authors.

Abstract This work reports the use of mid- and near-infrared spectroscopy (MIR and NIR) to predict the kinematic and dynamic viscosities of biodiesel–diesel blends. A partial least square regression (PLSR) modeling method was employed to develop the calibration models based on information from four commonly used biodiesel and three different commercial diesel fuels. For MIR spectroscopy, wavelengths in the fingerprint region of 550–1500 cm−1 were chosen for developing the model. The root mean square error of prediction (RMSEP) for kinematic viscosity and dynamic viscosity were 0.114 and 0.119 mm2/s, respectively, based on the validation set that consisted of 26 biodiesel–diesel blend samples made of six different biodiesel and three different diesel fuels. For the NIR spectroscopy, the PLSR model established using the spectral regions of 1100–1500 nm, 1600–1700 nm, and 1800–2200 nm obtained better results. The RMSEP were 0.070 mm2/s for kinematic viscosity and 0.062 mm2/s for dynamic viscosity prediction. The results indicated that both MIR and NIR can be used to accurately predict the viscosities of biodiesel–diesel blends, but better results can be obtained using NIR spectroscopy.

Abstract Uninterrupted energy harvest is critical for self-sustained wastewater monitoring in order to achieve efficient and resilient operation of decentralized onsite wastewater treatment facilities. To address this long-standing challenge, an integrated power entity consisting of a miniature microbial fuel cell (volume: 1.5 mL) and a triggered power management system was developed in this study to power the potentiometric millimeter-sized solid-state water sensors for real-time in situ monitoring and uninterrupted transmission of sensor readings (indicating ammonium concentration) under both ammonium shock and toxic shock in wastewater. Specifically, a data trigger including two capacitors, an operation amplifier and a low-power comparator is equipped in the power management system as a switch for turning on power discharge for data transmission once the ammonium shock is captured by the potentiometric sensors, enabling a sufficient recharge duration to store the power needed for high frequency data transmission (16.23 times/min) required under shocks. Furthermore, this power-sensor entity possesses a unique dual-screening capability of capturing the ammonium and toxic shocks, providing an early warning for swift decision making, reducing ~17% of ammonium discharge and saving ~42% of energy consumption in decentralized onsite wastewater treatment facilities.

Abstract Carbon capture and storage (CCS) technology is an important option in the portfolio of emission mitigation solutions in scenarios that lead to deep reductions in greenhouse gas (GHG) emissions. We focus on CCS application in hard-to-abate sectors (cement industry, iron and steel, chemicals) and introduce industrial CCS options into the MIT Economic Projection and Policy Analysis (EPPA) model, a global multi-region multi-sector energy-economic model that provides a basis for the analysis of long-term energy deployment. We use the EPPA model to explore the potential for industrial CCS in different parts of the world, under the assumptions that CCS is the only mitigation option for deep GHG emission reductions in industry and that negative emission options are not available for other sectors of the economy. We evaluate CCS deployment in a scenario that limits the increase in average global surface temperature to 2 °C above preindustrial levels. When industrial CCS is not available, global costs of reaching the target are higher by 12% in 2075 and 71% in 2100 relative to the cost of achieving the policy with CCS. Overall, industrial CCS enables continued growth in the use of energy-intensive goods along with large reductions in global and sectoral emissions. We find that in scenarios with stringent climate policy, CCS in the industry sector is a key mitigation option, and our approach provides a path to projecting the deployment of industrial CCS across industries and regions.

Abstract The distributed generation (DG) of combined heat and power (CHP) for commercial buildings is gaining increased interest, yet real-world installations remain limited. This lack of implementation is due, in part, to the challenging economics associated with volatile utility pricing and potentially high system capital costs. Energy technology application analyses are also faced with insufficient knowledge regarding how to appropriately design (i.e., configure and size) and dispatch (i.e., operate) an integrated CHP system. Existing research efforts to determine a minimum-cost-system design and dispatch do not consider many dynamic performance characteristics of generation and storage technologies. Consequently, we present a mixed-integer nonlinear programming (MINLP) model that prescribes a globally minimum cost system design and dispatch, and that includes off-design hardware performance characteristics for CHP and energy storage that are simplified or not considered in other models. Specifically, we model the maximum turn-down, start up, ramping, and part-load efficiency of power generation technologies, and the time-varying temperature of thermal storage technologies. The consideration of these characteristics can be important in applications for which system capacity, building demand, and/or utility guidelines dictate that the dispatch schedule of the devices varies over time. We demonstrate the impact of neglecting system dynamics by comparing the solution prescribed by a simpler, linear model with that of our MINLP for a case study consisting of a large hotel, located in southern Wisconsin, retrofitted with solid-oxide fuel cells (SOFCs) and a hot water storage tank. The simpler model overestimates the SOFC operational costs and, consequently, underestimates the optimal SOFC capacity by 15%.