Abstract

The pollutant removal of wastewater treatment has been facing the challenge of increasing energy consumption and varying spatial heterogeneity in China. This paper first employed an input-output (IO) model to calculate the sectoral wastewater pollutant (COD) discharge coefficients and a multi-regional input-output (MRIO) model was employed to explore the provincial virtual wastewater pollutant (COD) flows in China. Then, the energy efficiencies of wastewater treatment plants (WWTPs) in different provinces were inventoried. This study developed an assessment framework combining the multi-regional input-output model, virtual pollutant, and embodied energy. The critical pollutant discharge sectors (Service, Agriculture, Textile industry, Food and tobacco processing, Manufacture of chemical products, Production and distribution of tap water) and provinces (Shandong, Jiangsu, Guangdong, Henan, Zhejiang, Hubei, Sichuan) were identified. It was found that the pattern of virtual wastewater pollutant flows in China was efficient in energy saving. Majority of virtual wastewater COD (wwCOD) was transferred from higher energy efficient provinces to lower energy efficient provinces for saving 1.6×107 kW.h electricity. The study may help optimize the spatial regulation of national energy conservation and pollution reduction.

Abstract

Urban form play an important role in influencing building energy use. Previous empirical studies on urban form and building energy mostly represented urban form as separate indicators of form components and socio-economic conditions. However, urban form is a complex system that consists of different components and interactions. Thus, simply considering urban form as an aggregation of their components and properties often suffers from strong correlations among these factors and the confounding effect as in previous studies. To better understand the energy performance of complex urban form, this study identifies urban form typologies in Seoul using unsupervised learning and examines the energy performance of those typologies. The Gaussian mixture model (GMM), a widely used clustering method, is adopted to identify 16 urban form typologies based on 10 common urban form and population distribution factors. Electricity use and gas use in different typologies in 2019 are collected and compared using the Brown Forsythe ANOVA and Games Howell post hoc test. Results suggest that urban form typologies reflect energy efficiency to a certain degree, and the difference in energy efficiency across urban form typologies is more significant in gas than in electricity because of occupant behavior differences in their use. Among the urban form typologies, high-rise high-density urban form type is the most efficient, and the high-rise mixed type is the least efficient. The findings from this research could help urban planners and designers to understand the relationship between complex urban form and building energy better to support planning and design toward an energy-efficient urban form.

Abstract

Stationary battery storages become a promising solution for improving flexibility of renewable energy system to balance the fluctuating of power production and demand. However, each application has a specific operational strategy, consequently a specific dynamic operational profile which leads to a different estimated battery lifetime due to the degradation of battery capacity over its operation in the application. An accurate knowledge about battery lifetime, and battery state of health at different operational conditions is important to ensure a feasible techno-economic assessment. This paper deals with the techno-economic evaluation of a battery system integrated into a residential grid-connected PV system considering two battery models with and without battery degradation. The battery life cycle cost, the self-sufficiency ratio and battery lifetime are analyzed for techno-economic assessment of a residential grid-connected hybrid PV-battery system. The results show that the simulation without battery degradation gives 31.43% lower life cycle cost and 7.4% higher self-sufficiency ratio, compared to the modeling with battery degradation. This proves the importance of battery aging model for assessing a battery integrated into a renewable PV system.

Abstract

In this paper, logarithmic mean Divisia index (LMDI) method was used to analyze China’s energy-related CO2 emissions from 1980 to 2019. Four contributing factors including energy intensity, carbon intensity, economic development and population size were selected. The results show that China’s CO2 emissions increased from 1.49Gt to 9.68Gt from 1980 to 2019. Per capita GDP is the dominating positive factor, accounting for 293.51%, while energy intensity is the major negative factor, contributing -189.91%. Thus the efforts for carbon peak and neutrality in China should be focused on economic structure adjustment and energy efficiency promotion.

Abstract

With high population density and intensive energy consumption, Beijing has long been facing the huge challenge of ecological security in context of coordinated development of environment, economy and dispersed urban functions. Combining statistical and grid data, this paper analyzed the ecological security status in Beijing from three scales, i.e., city, sub-city and grid, based on an emergetic ecological footprint model. Results show that Beijing has been in ecological deficit and sub-security status with uneven spatial distribution. Concrete measures are then suggested to promote the ecological security of Beijing.

Abstract

In order to accelerate the realization of the global “double-carbon” goal, we introduced game theory into the electricity market to formulate a reasonable strategy to transaction. A strategy of purchasing and selling power is proposed in this paper. Firstly, we devised a transaction strategy based on Stackelberg game. Then, we designed an incentive mechanism for this game. This mechanism takes the reputation value of users as an index and adopts the smart contract technology in blockchain, which can reduce the transaction risk. The proposed strategy can encourage users to use electricity reasonably and sale surplus electricity to the grid. In addition, it can increase the benefits of electric power aggregator and users effectively.

Abstract

In order to identify the key variables affecting peak cooling load of a high-rise office building, especially the related elements of architectural design, a MC simulation method based on LHS is proposed and the meta-model GSA based on TGP is implemented in this paper. Finally, to illustrate the methodology in a clear way, a case study of a high-rise office building in Tianjin, China has been used in this paper. The results show that the key factors affecting peak cooling load are solar heat gain coefficient (SHGC), west window to wall ratio (Rw) and number of floors (NF), and the interaction terms of input factors are not significant. This process makes it possible for designer or decision makers to carry out building energy efficiency design and optimization design scheme.

Abstract

China’s wastewater treatment facilities have become increasingly energy-intensive in recent decades. In this study, the relative energy efficiencies of 283 regional wastewater treatment plants in Jing-jin-Ji area (JJJ) were evaluated using a slacks-based measure data envelopment analysis (DEA). Results showed that the efficiencies of 276 wastewater treatment plants have notable improving potential according to the production frontier of DEA. The energy cost of wastewater treatment plants (WWTPs) was quantified for JJJ and analyzed according to the spatial discrepancies. This paper may shed lights on assessment and evaluation of regional wastewater treatment plants considering the energy efficiency.

Abstract

The carbon footprint of Bitcoin has drawn wide attention, though Bitcoin’s long-term impact on the climate remains uncertain. In this paper, we present a framework that leverages some fundamental concepts in energy economics and finance to overcome uncertainties in previous estimates and project Bitcoin’s worldwide electricity consumption and carbon footprint in the long-term. If Bitcoin’s future market capitalization growth rate in the long-term is assumed to fall within the range of historical growth rates of several comparable mainstream financial assets, we find that the annual electricity consumption of Bitcoin may increase from 190 to 7,500 TWh between 2021 and 2100. The future carbon footprint of Bitcoin strongly depends on the decarbonization pathway of the electricity sector. If the electricity sector achieves carbon neutrality by 2060,Bitcoin’s annual carbon footprint will peak in 2023, with cumulative emissions of about 1 GtCO2 by 2100. However, in the business-as-usual scenario, emissions sum to a staggering 30 GtCO2 through 2100—the equivalent of total global emissions from 2019. In light of these results, we discuss implications for policy in reducing Bitcoin’s future carbon footprint.

Abstract

Compared with air source heat pumps, solar assisted heat pumps have attracted more attention due to the efficient utilization of solar energy. As an important component of SAHP system, the design of collector-evaporator is mainly focused on improving the absorption of solar energy, and neglect the effective utilization of air energy. Low solar radiation cannot provide enough heat to meet users’ demand on cloudy or rainy days. Therefore, a new type of integrated solar-air source heat pump system is proposed, taking into account the utilization of solar energy and air energy at the same time. To study the heating performance of the SASHP system, an on-site measurement is carried out. The results show that the collector-evaporator has higher evaporation temperature than the traditional evaporator, and the evaporation temperature increases as the ambient temperature rises. Furthermore, the SASHP system COP is 4%-7% higher than that of the traditional ASHP system.