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Data demonstrating the influence of the latent storage efficiency on the dynamic thermal characteristics of a PCM layer.

ABSTRACT: Dynamic thermal characteristics, for each month of the year, of PCM layers with different melting temperatures and thermophysical properties, in a steady periodic regime, were determined (Mazzeo et al., 2017 [1]). The layer is subjected to climatic conditions characterizing two locations, one with a continental climate and the second one with a Mediterranean climate. This data article provides detailed numerical data, as a function of the latent storage efficiency, including monthly average daily values: of the latent energy fraction, of the decrement factors of the temperature, of the heat flux and of the energy, and of the time lags of the maximum and minimum peaks of the temperature and of the heat flux.

SUBMITTER: Mazzeo D

PROVIDER: S-EPMC5403787 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Data demonstrating the influence of the latent storage efficiency on the dynamic thermal characteristics of a PCM layer.

Mazzeo D D Oliveti G G Arcuri N N

Data in brief 20170411

Dynamic thermal characteristics, for each month of the year, of PCM layers with different melting temperatures and thermophysical properties, in a steady periodic regime, were determined (Mazzeo et al., 2017 [1]). The layer is subjected to climatic conditions characterizing two locations, one with a continental climate and the second one with a Mediterranean climate. This data article provides detailed numerical data, as a function of the latent storage efficiency, including monthly average dail ...[more]

PMID: 28462366

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Project description:The Yellow River Basin (YRB) is China's substantial energy consumption base. The issue of carbon emission efficiency directly affects the ecological protection and high-quality development of the YRB. It is the key to achieving carbon peak in 2030 and carbon neutralization in 2060 ("30.60") double carbon emission reduction targets. Therefore, taking YRB as the research object, this paper first calculates the carbon emission and the decoupling state in the YRB. Secondly, the super-efficiency slacks-based measurement (SE-SBM) model is combined with the Malmquist index to analyze the temporal and spatial evolution characteristics of YRB's carbon emission efficiency from static and dynamic perspectives. Thirdly, the dynamic evolution characteristics of carbon emission efficiency are analyzed with the help of the Kernel density function. Finally, the Tobit model analyzes the influencing factors of YRB's and China's carbon emission efficiency. The results show that: (1) Among the nine provinces of YRB, the decoupling state between carbon emissions and economic growth in most provinces changes from weak decoupling to strong decoupling, and the decoupling elasticity index shows a fluctuating downward trend. (2) There are significant differences in carbon emission efficiency among provinces, but on the whole, it shows a stable growth trend. The high-value area of carbon emission efficiency is increasing, and the phenomenon of two-level differentiation is improving. The decline of the technological progress index causes the Malmquist index in Qinghai and Ningxia. On the contrary, the rise of the Malmquist index in the other seven provinces is caused by improving the technical efficiency index. (3) Industrial structure, economic development, and industrialization are the main positive factors affecting YRB's carbon emission efficiency. Urbanization level, green development level, and energy consumption level are the leading negative indicators hindering YRB's improvement of carbon emission efficiency. Therefore, targeted emission reduction suggestions should be formulated according to YRB's resource endowment and development stage characteristics.

Dataset Information

Data demonstrating the influence of the latent storage efficiency on the dynamic thermal characteristics of a PCM layer.

Publications

Data demonstrating the influence of the latent storage efficiency on the dynamic thermal characteristics of a PCM layer.

Similar Datasets

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