Abstract

This article aims to study the impact of China’s Two Control Zones policy on sulfur dioxide emissions from 1997 to 2018. First, this paper applies the DID model and uses the panel data of prefecture-level cities to preliminarily analyze the impact of the Two Control Areas Policy on sulfur dioxide. DID results show that the two control zones policy has indeed played a role in reducing sulfur dioxide emissions. After individually controlling the covariates, the two control zones policy has a minor effect on promoting the reduction of sulfur dioxide emissions. The covariates are sorted in order of reduction degree from small to large, namely Popu, GDP, industry, and FDI. By continuously adding control variables, it can be found that the addition of GDP has almost no effect on the emission reduction effect of the two control areas policy. FDI and Popu has a worsening effect on the emission reduction effect of the two control areas policy; the addition of industry can reduce sulfur dioxide The deteriorating effect of the platoon will be partially offset. Secondly, to reduce the error of DID estimation, this paper further uses the PSM-DID method for the robustness test. The PSM-DID inspection results once again confirmed that the two control areas policy has a significant role in reducing acid rain and sulfur dioxide pollution in the region. Finally, based on the analysis results of the two models, this article proposes corresponding policy recommendations on further using the two control areas policy to reduce sulfur dioxide emissions from the perspective of the government and enterprises.

Abstract

The adoption of innovation in the building sector is currently too low for the ambitious sustainability goals that our societies have agreed upon. The concept of smart building, for instance, is being implemented too slowly. One of the main reasons for this is that technologies have to be proven effective and reliable before being introduced at large scale in buildings. Testbeds and demonstrators are seen as a crucial infrastructure to test and demonstrate the impact of solutions in the building sector and hence facilitate their adoption in buildings. The KTH Live-In Lab is a platform of building testbeds designed to this scope. This work describes the Live-In Lab vision, approach, technical features, provides an overview on the multidisciplinary projects that it has enabled and discusses its replicability.

Abstract

Multimetallic layered composites (MMLC) have been explored for their suitability as nuclear fuel cladding in nuclear reactors. We studied the radiation resistance of a new MMLC, i.e., T91(Fe90Cr9Mo1)/Fe-Cr-Si (Fe86Cr12Si1), for nuclear fuel cladding in Generation IV reactors, such as Molten Salt Reactor (MSR). We used a multi-objective optimization (MOO) approach to parameterizing a Modified Embedded Atom Method (MEAM) forcefield with Ziegler-Biersack-Littmark (ZBL) modification that can reproduce the two alloy’s mechanical properties and perform the high energy collision cascade simulations. We performed simulations for a broad range of Primary Knock on Atom (PKA) energies, 10-100keV, at 1000K to investigate the effect of the PKA energy on the radiation damage. We found that the diffusion coefficient follows a linear trend with the radiation dose but inversely relates to PKA energies. The mean squared displacement (MSD) at the thermal spike (TS) phase is independent of the PKA energy and decreases during the ballistic phase of the cascade simulation at higher PKA energy. We revealed structural rearrangement for Fe-Cr, Si-Cr, Cr-Mo, and Mo- Mo neighboring atoms upon reaching a critical radiation dose. Our investigation also shows that the number of defects decreases as the PKA energy increases.

Abstract

To realize the initiative of carbon peak and carbon neutral in China, the traditional energy system dominated by high-carbon fuels must be transformed to a clean and low-carbon energy system. Because of its resource potential and cleaner advantages, the development of distributed solar PV generation can significantly increase the supply of cleaner energy while offering the associated benefits. Distributed PV generation such distributed roof PV generation will be an important part of the new electrical power system dominated by new energy including solar and wind power. To attain this target, more distributed PV generation will need to be developed in China for the coming decades. However, the current incentives have not been sufficiently aggressive, and the distributed PV industry has been slow to develop. Existing policies for distributed PV generation thus need to be further improved. To provide effective support for decision makers in China, an economic feasibility analysis is performed in this study to explore the profitability of distributed roof PV production in a target area. The results show that the development of distributed roof PV production is not economically viable in China under the current conditions. Based on this analysis, some policy recommendations are presented to improve the current incentive polices aimed at promoting the development of distributed roof PV in China.

Abstract

Gas hydrates are snow-like materials made of water molecules trapping gas molecules under high-pressure and low-temperature conditions such as that at chokes and valves installed on natural gas wellheads and pipelines. Electricity was found generated from flowing methane-, ethane-, propane-, and CO2-hydrates along PVC tubes in laboratories. The rate of building electric charges and the level of the built voltage were found to depend on pressure drop/volume expansion when the hydrate was released to the PVC tube. Sparks/light were emitted when the static voltage reached a level of about 300 mV in the system investigated. An explanation of the observed sparks/light is the generation of static electricity when gas-hydrate passed through the PVC tube at a high velocity (flow electrification), or triboelectricity. The charge level is higher for poorly conductive gas-hydrate flowing through the PVC tube. In addition, the large amounts of gas bubbles flowing through the tube should amplify the static electricity. However, in this investigation, it was noticed that no spark/light was observed and no voltage pulse was detected during the active flow of hydrates. Instead, sparks/light were observed and voltage pulses were detected after the choking valve was switched on. The positive voltage probe was connected to the choking valve and the negative voltage probe was connected to the PVC tube. The voltage meter measured positive pulses of voltage difference between the two probes when the choking valve was off. This indicates current flow from the choking valve to the PVC tube, or electron charge flow from the PVC tube to the choking valve. Our hypothesis to explain these phenomena is that the flowing hydrates captured electrons from the low-conductive PVC tube and transported them in the flow stream, resulting in a “Positive charged” PVC tube in the entry portion. When the flow was terminated by valve closing, the electrons in the down-stream of the PVC tube flew back to the entry portion to minimize the charge unbalance, causing sparks/light and current flow from the choking valve to the PVC tube. This hypothesis needs to be proven in future investigations. Further studies are recommended in this area and more investigations are required for flowing methane-, ethane-, propane-hydrates. Potential applications of the hydrate-triboelectricity include harvesting electricity in the downstream of surface chokes installed on the natural gas wellheads where there exist flowing gas hydrates.

Abstract

The incorporation of phase change material (PCM) into building fabrics would significantly enhance thermal energy storage, thereby enabling energy savings and CO2 emission reductions. However, the integration method remains a major challenge with the detrimental effects on structural integrity, durability of building elements and performance. This paper proposes a way of integrating PCM into concrete building elements by utilizing additive manufacturing and construction automation technologies. Additive manufacturing of concrete allows the manufacture of non-rectilinear building elements that cannot be constructed using the traditional construction method, thanks to the three-dimensional (3D) concrete printing technology. The concrete elements were constructed as hollow-core using the 3D concrete printing method and PCM incorporated into the hollow-core for thermal energy storage enhancement. Subsequently, the paper assesses performance enhancement of PCM incorporated concrete elements using experimental simulated test rooms and numerical assessment on full-scale buildings. The results reveal that the hollow-core concrete enables a large amount of PCM incorporation of up to 9.88% by weight of concrete, with the increase of heat storage capacity by 7.02 kJ/kg. The simulated test rooms experiment reports that the PCM incorporated hollow-core panels reduced the peak indoor temperature of the test room by 3.86 ℃ while enhancing the thermal storage capacity by 181%. Moreover, the numerical study on buildings incorporated with the innovative PCM panels demonstrated significant energy savings of up to 48% for the Australian climatic conditions.

Abstract

Over the past decade, the number of wildfire has increased significantly around the world, especially in the State of California. The high-level concentration of greenhouse gas (GHG) emitted by wildfires aggravates global warming that further increases the risk of more fires. Therefore, an accurate prediction of wildfire occurrence greatly helps in preventing large-scale and long-lasting wildfires and reducing the consequent GHG emissions. Various methods have been explored for wildfire risk prediction. However, the complex correlations among a lot of natural and human factors and wildfire ignition make the prediction task very challenging. In this paper, we develop a deep learning based data augmentation approach for wildfire risk prediction. We build a dataset consisting of diverse features responsible for fire ignition and utilize a conditional tabular generative adversarial network to explore the underlying patterns between the target value of risk levels and all involved features. For fair and comprehensive comparisons, we compare our proposed scheme with five other baseline methods where the former outperformed most of them. To corroborate the robustness, we have also tested the performance of our method with another dataset that also resulted in better efficiency. By adopting the proposed method, we can take preventive strategies of wildfire mitigation to reduce global GHG emissions

Abstract

The objective of this paper is to proof that intermittent renewable supply sources can be integrated to develop a reliable baseload plant, which can generate electricity at a competitive cost to the conventional generation. A methodology has been developed to optimize the design of a hybride plant, which is based on several technologies including; solar PV, wind, hydrogen generation/fuel cells, and batteries to serve as a renewable energy baseload plant. The methodology includes site selection to ensure maximum integration among the intermittent supply sources as well as optimized sizing of both generation and storage technologies. The objective function is for the least Levelized Cost of Energy (LCoE). The system reliability is judged using the Loss of Power Supply Probability (LoPSP) criterion. A MATLAB algorithm has been developed for the initial sizing of the system components, which searches for the optimum solution within the applicability domain. This is followed by HOMER software-based optimization technique for the plant operation. A case study for baseload hybrid plant of a capacity 200 MW is presented. The location of the plant is screened among several sites in Egypt to achieve the best optimum combination of both solar and wind generation considering; resource intensity, site conditions and constraints, as well as integration between solar PV and wind outputs. According to the selected site and according to the developed optimization methodology, the system has a combination of renewable generation/storage capacities of; 87.5% wind and 12.5% solar PV, and storage of 75% fuel cell and 25% battery. This injects energy to the grid with an energy mix of 89 % from direct renewable power sources (solar PV & wind), 8 % from the fuel cell, and 3 % from the battery. This energy mix ensures a steady output baseload of 200 MW throughout the year with zero LoPSP, at a LCoE of 8.61 ¢/kWh. Relaxing the LoPSP constraint to 2.5% resulted in 26.83% reduction in the LCoE to 6.8 ¢/kWh. According to this study, renewable energy generation can be used toward achieving 100% baseload power systems at competitive energy cost to the conventional generation.

Abstract

Investigating the effect of China’s clean coal technology policy on air quality is of great significance for promoting energy transformation and formulating follow-up policies. Utilizing 31 provincial cities data in Chinese mainland from 2013 to 2020, the spatial variation characteristic and change rate of air quality index (AQI) are discussed in this study. Amongst, the AQI in 2020 is predicted by deep learning approaches, to eliminate the uncertainty that COVID-19 bring about. The association analysis between AQI and socio-economic factors is also conducted, to clarify the internal mechanism of clean coal technology policy. The results show that 1) The AQI can be better predicted by the tailored Convolutional Neural Network-Long Short Term Memory (CNN-LSTM) network; 2) the air pollution in China shows an integration trend, embodying heavy and slight pollution in Northern and Southern China, respectively; 3) the clean coal technology policy has an average reduction effect of 18.82% on AQI. And there is a 2-year time lag before the policy takes any strong positive effects; 4) the clean coal technology policy mainly improved air quality through the way of emission reduction and de-industrialization. Practicable policy suggestions are put forward to supporting emission reduction, promoting energy transformation in China and applicable to other developing countries with scarce energy resources and severe air pollution.

Abstract

Building-integrated photovoltaic (BIPV) technology plays an important role on the path to carbon neutral society. The CdTe-based vacuum PV glazing is proposed to improve the thermal performance of the PV glazing. Therefore, the goals of renewable energy production and energy-efficient building can be achieved at the same time. To fully understand the dynamic heat transfer process and thermal behaviour, this study conducted a comprehensive numerical evaluation based on a mathematic heat transfer model for the CdTe-based vacuum PV glazing. It was found the average dynamic solar heat gain coefficient (SHGC) of the CdTe-based vacuum PV glazing is 0.147 and will increase with the increment of incident solar radiation. The dynamic overall heat transfer coefficient (U-value) varies from 0.451 to 0.467 W/m2K under summer conditions which are higher than which under winter conditions. The solar radiation dominates the total heat transfer compared with the temperature difference in the daytime. The solar radiation and ambient temperature have a negative effect on the PV efficiency and a distinctly positive effect on the outside surface temperature. However, the inside surface temperature is much more stable. A sensitivity analysis was also conducted to investigate the thermal response of the vacuum PV glazing with different design parameters and various environmental conditions. The emissivity of low-e coating is the most effective design parameter. The results indicate that the vacuum PV glazing can perform an excellent thermal insulation performance and contribute to the optimization of the design parameters in future studies.