Comparative study on performances of a heat-pipe PV/T system and a heat-pipe solar water heating system

The heat-pipe solar water heating (HP-SWH) system and the heat-pipe photovoltaic/thermal (HP-PV/T) system are two practical solar systems, both of which use heat pipes to transfer heat. By selecting appropriate working fluid of the heat-pipes, these systems can be used in the cold region without being frozen. However, performances of these two solar systems are different because the HP-PV/T system can simultaneously provide electricity and heat, whereas the HP-SWH system provides heat only. In order to understand these two systems, this work presents a mathematical model for each system to study their one-day and annual performances. One-day simulation results showed that the HP-SWH system obtained more thermal energy and total energy than the HP-PV/T system while the HP-PV/T system achieved higher exergy efficiency than the HP-SWH system. Annual simulation results indicated that the HP-SWH system can heat the water to the available temperature (45°C) solely by solar energy for more than 121 days per year in typical climate regions of China, Hong Kong, Lhasa, and Beijing, while the HP-PV/T system can only work for not more than 102 days. The HP-PV/T system, however, can provide an additional electricity output of 73.019 kWh/m², 129.472 kWh/m², and 90.309 kWh/m² per unit collector area in the three regions, respectively.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.     

Linking landscape development intensity within watersheds to methyl-mercury accumulation in river sediments

An indicator of the disturbance of natural systems, the landscape development intensity (LDI) index, was used to assess the potential for land-use within watersheds to influence the production/accumulation of methyl-mercury (MeHg) in river sediments. Sediment samples were collected from locations impacted by well-identified land-use types within the Mobile-Alabama River Basin in Southeastern USA. The samples were analyzed for total-Hg (THg) and MeHg concentrations and the obtained values correlated to the calculated LDI indexes of the sampled watersheds to assess the impact of prevalent land use/land cover on MeHg accumulation in sediments. The results show that unlike THg, levels of MeHg found in sediments are impacted by the LDI indexes. Overall, certain combinations of land-use types within a given watershed appear to be more conducive to MeHg accumulation than others, therefore, pointing to the possibility of targeting land-use practices as potential means for reducing MeHg accumulation in sediments, and ultimately, fish contamination.     

Immobilization of fungal laccase onto a nonionic surfactant-modified clay material: application to PAH degradation

Nonionic surfactant-modified clay is a useful absorbent material that effectively removes hydrophobic organic compounds from soil/groundwater. We developed a novel material by applying an immobilized fungal laccase onto nonionic surfactant-modified clay. Low-water-solubility polycyclic aromatic hydrocarbons (PAHs) (naphthalene/phenanthrene) were degraded in the presence of this bioactive material. PAH degradation by free laccase was higher than degradation by immobilized laccase when the surfactant concentration was allowed to form micelles. PAH degradation by immobilized laccase on TX-100-modified clay was higher than on Brij35-modified clay. Strong laccase degradation of PAH can be maintained by adding surfactant monomers or micelles. The physical adsorption of nonionic surfactants onto clay plays an important role in PAH degradation by laccase, which can be explained by the structure and molecular interactions of the surfactant with the clay and enzyme. A system where laccase is immobilized onto TX-100-monomer-modified clay is a good candidate bioactive material for in situ PAHs bioremediation.     

The fractionation and geochemical characteristics of rare earth elements measured in ambient size-resolved PM in an integrated iron and steelmaking industry zone

Environmental Science and Pollution Research - Improved understanding of the fractionation and geochemical characteristic of rare earth elements (REEs) from steel plant emissions is important due...     

Decoupling of nonferrous metal consumption from economic growth in China

Nonferrous metal is an important basis material for the development of the national economy, and its consumption directly affects economic development. It has great significance in the effective utilization of nonferrous metals, development of an environment-friendly society, and investigation of the decoupling of nonferrous metal consumption and GDP growth. The decoupling indicators for nonferrous metal consumption and GDP growth (D _r) in China from 1995 to 2010 were calculated in this study, and the results were analyzed. A productive model based on BP neural network was established. Then, the decoupling indicators for nonferrous metal consumption and GDP growth in China for the period of 2011–2020 were predicted. For the period of 1995–2010, the annual average decoupling indicators were <1 for copper, aluminum, zinc, lead, and nickel, except for tin, which was 0.21. The analysis showed that the decoupling of nonferrous metal consumption and GDP growth is in a less optimistic situation to copper, aluminum, zinc, lead, and nickel in China from 1995 to 2010. The annual average decoupling indicator for tin was 0.21, which indicates relative decoupling. For the period of 2011–2020, the predicted decoupling indicators for copper, aluminum, zinc, lead, nickel, and tin were between 0 and 1. This finding indicates the implementation of relative decoupling. However, the total consumption of nonferrous metals did not decouple from GDP growth.     

Rebound effect and its decomposition – an analysis based on energy types in China

Rebound effect derived from energy efficiency improvement has been widely invested. However, most of studies focus on the rebound effect of the energy composite level and neither distinguish nor compare different energy types. We compare the differences in energy saving and energy rebound between primary and secondary energy sources, and further decompose the rebound effect into production rebound part and final demand component. To do so, we add a module for rebound into a comparative state China-CGE model. We design and test two simulation scenarios using the model. In Scenario 1, all production sectors’ energy efficiency of using primary energy increases by 5%. In Scenario 2, all production sectors’ energy efficiency of using secondary energy increases by 5%. The results show that Scenario 2 leads to more GDP growth and more energy saving. Our scenarios show rebound effects range between 9.6% and 27.9%, and in general are higher when energy efficiency of using primary energy sources is improved. Our decomposition analysis shows that improving energy efficiency in production sectors would stimulates energy use of final demand. Indeed, the consumption side has significant contribution to rebound in secondary energy use, especially in crude oil and gas. This study reveals that improving efficiency of using secondary energy is better than improving that of primary energy, both in terms of economic impact and energy rebound. And complementary policies that prevent energy services prices from falling too much can be adopted to reduce rebound. Controlling residential energy use could also be effective in reducing rebound, this has particular implication to economies in which residential energy consumption are far from saturation.