Spatiotemporal heterogeneity in meteorological and hydrological drought patterns and propagations influenced by climatic variability, LULC change, and human regulations

This study aims to quantify meteorological-hydrological drought propagations and examine the potential impacts by climatic variability, LULC change (LULC), and human regulations. An integrated observation-modeling framework quantifies drought propagation intervals and assesses mechanisms influencing hydrological droughts. Meteorological droughts are characterized using the Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological droughts are assessed through the Standardized Streamflow Index (SSI) across diverse climatic zones. Cross-correlation analysis between SPEI and SSI time series identifies the lag time associated with the highest correlation as the drought propagation interval. Mechanisms are investigated via a coupled empirical-process modeling framework incorporating the Soil and Water Assessment Tool (SWAT). Discrepancies between simulated and observed SSI time series help quantify the extent of human regulation impacts on hydrological drought characteristics and propagation. The Yellow River Basin (YRB), divided into six subzones based on climate characteristics, is selected as the case study. Key findings include: (1) Meteorological droughts were extremely severe across most YRB during the 1990s, while the 2000s showed some mitigation primarily due to precipitation increases. (2) Hydrological droughts and propagation times from meteorology to hydrology demonstrated substantial spatiotemporal variability. In general, summer propagation times were shorter than other seasons. (3) Propagation times were shorter in arid regions with cropland or built-up land cover versus grassland and woodland, while the reverse held for humid regions. (4) Human regulations prolonged propagation times, likely due to reservoir regulations designed to overcome water deficits. While the YRB is the focus of this paper, the methodologies and findings are applicable to other regions worldwide to enhance drought forecasting and water resource management. In various hydrological and climatic contexts worldwide.

Biomedical therapeutic compression textiles: Physical-mechanical property analysis to precise pressure management

Biomedical therapeutic compression textiles (TCTs) have been extensively applied in the prevention and treatment of chronic venous insufficiency of lower extremities. An efficiency and operable development strategy to achieve the morphologic control and pressure fitness of TCTs needs to be proposed to improve the medical precision and patient adherence. Therefore, the present study qualitatively explored the influencing mechanisms of each knitting variable on physical-mechanical properties and pressure behaviors of TCTs. Then constructed the quantitative models to digitalize the knitting variables for determination of yarn-machinery setting design values. The results revealed that the feeding velocity of elastic inlay yarn materials and loop size settings impacted the pressure values owing to the diversities of fabric dimensions and mechanical tensile properties, respectively. Simultaneously, the derivation ratios of proposed circumferential and pressure models evaluated by experimental validated trials were approximately 1.1% and 10.8%, respectively. This study provided the fundamental references for the design, manufacturing, and property controlling of compression textiles to improve the biomedical therapeutic effectiveness for targeted users.

Bioaerosols in the atmosphere: A comprehensive review on detection methods, concentration and influencing factors

In the past few decades, especially since the outbreak of the coronavirus disease (COVID-19), the effects of atmospheric bioaerosols on human health, the environment, and climate have received great attention. To evaluate the impacts of bioaerosols quantitatively, it is crucial to determine the types of bioaerosols in the atmosphere and their spatial-temporal distribution. We provide a concise summary of the online and offline observation strategies employed by the global research community to sample and analyze atmospheric bioaerosols. In addition, the quantitative distribution of bioaerosols is described by considering the atmospheric bioaerosols concentrations at various time scales (daily and seasonal changes, for example), under various weather, and different underlying surfaces. Finally, a comprehensive summary of the reasons for the spatiotemporal distribution of bioaerosols is discussed, including differences in emission sources, the impact process of meteorological factors and environmental factors. This review of information on the latest research progress contributes to the emergence of further observation strategies that determine the quantitative dynamics of public health and ecological effects of bioaerosols.

The impact of green credits on high-quality energy development: evidence from China

The implementation of green credits has become an important engine for China's high-quality energy development (HQED). On the basis of constructing an index of HQED and the panel data of thirty provinces in China from 2008 to 2019, this study empirically investigated the effects of green credits on HQED and the action mechanisms behind it in a multi-dimensional manner using a panel fixed-effects model, mediating-effects model, and spatial Durbin model. The results indicated that green credits had significantly contributed to China's HQED, and that conclusion still held true after a series of robustness tests were conducted. It was found that industrial structures and human capital were important channels through which green credits influenced China's HQED. Moreover, the spatial spillover effects of green credits on HQED were also confirmed. Finally, in terms of temporal heterogeneity, the positive effects of green credits on HQED were found to have increased significantly after 2012. Also, in terms of regional heterogeneity, this study observed that the positive influence of green credits on HQED was more significantly in central and western China than in eastern China, and in southern China than in northern China. The results obtained in this research investigation will potentially provide some important insights for energy planners and policymakers to further the understanding of the drivers of HQED, and the corresponding transmission mechanisms and regional differences.

Design of Ti-Pt Co-doped α-Fe(2)O(3) photoanodes for enhanced performance of photoelectrochemical water splitting

This study demonstrates Ti and Pt co-doping can synergistically improve the PEC performance of the α-Fe₂O₃ photoanode. By varying the doping methods, the sample with in-situ Ti ex-situ Pt doping (Ti_i-Pt_e) exhibits the best performance. It demonstrates that Ti doping in bulk facilities charge separation and Pt doping on the surface further accelerates charge transfer. In contrast, Ti doping on the surface inhibits charge separation, and Pt doping in bulk hinders charge separation and transfer. HCl treatment is used to minimize the onset potential further, while it is favorable for the ex-situ doped α-Fe₂O₃, which is more efficient on Ti_e than the Pt_e-doped ones. On the ex-situ Ti-doped α-Fe₂O₃ after HCl treatment, anatase TiO₂ is probed, suggesting that Ti-O bonds accumulate when Fe-O bonds are partly removed, which enhances the charge transfer in surface states. Unfortunately, HCl treatment also induces lattice defects that are adverse to charge transport, inhibiting the performance of in-situ doped α-Fe₂O₃ and excessively treated ex-situ doped ones. Coupled with methanol solvothermal treatment and NiOOH/FeOOH cocatalysts loading, the optimized Ti-Pt/Fe₂O₃ photoanode exhibits an impressive photocurrent density of 2.81 mA cm^-2 at 1.23 V vs. RHE and a low onset potential of 0.60 V vs. RHE.

Potential hot spots contaminated with exogenous, rare earth elements originating from e-waste dismantling and recycling

Dismantling and recycling e-waste has been recognized as a potential emission source of rare earth elements (REEs). However, the presence of REEs in typical regional soils has yet to be studied. Given the potential health implications of such soil contamination, it is vital to study the characteristics, spatial distribution, and pollution level of REEs caused by e-waste dismantling as well as determine the influencing mechanism. This study focused on Guiyu Town as an example site, which is a typical e-waste dismantling base. From the site, 39 topsoil samples of different types were collected according to grid distribution points. Soil profiles were also collected in the dismantling and non-dismantling areas. The REE characteristic parameters showed that the REE distribution was abnormal and was affected by multiple factors. The results of the integrated pollution index showed that approximately 61.5% of soil samples were considered to be lightly polluted. Spatial distribution and correlation analysis showed that hot spots of REE-polluted soil coincided with known, main pollution sources. Moreover, there was a significant negative correlation (p ≤0.05) between the REE concentration and the distance from the pollution source. E-waste disassembly and recycling greatly affect the physical and chemical properties of the surrounding soil as well as downward migration areas. In the disassembly area, REE accumulated more easily in the surface layer (0-20 cm). Geographical detector results showed that distance factor was the main contribution factor for both light rare earth elements (LREE) and heavy rare earth element (HREE) (q = 34.59% and 53.33%, respectively). REE distribution in soil was nonlinear enhanced by different factors. Taken together, these results showed that e-waste disassembling and recycling not only directly affected the spatial distribution of REEs, but that their distribution was also affected by land use type and soil properties.

Effects of Microplastics on Higher Plants: A Review

Microplastics pose great risks to terrestrial systems owing to their large quantity and strong persistence. Higher plants, an irreplaceable part of the terrestrial ecosystem, are inevitably exposed to microplastics. This review highlights the effects of microplastics on higher plant growth and performance. The tested microplastics, plant species, and cultural methods used in existing studies were summarized. We discussed the reasons why these microplastics, plants, and methods were selected. The various responses of higher plants to microplastics in both soils and waters were critically reviewed. We also highlighted the influencing mechanisms of microplastics on higher plants. Conclusively, more than 13 types of common microplastics and more than 30 species of higher plants have been selected and studied by the published literatures. Soil culture tests and hydroponic experiments are almost equally divided. The effects of microplastics on higher plants varied among microplastic properties, plant species, and environmental factors. Microplastics had no or positive effects on higher plants under certain experimental conditions. However, more studies showed that microplastics can inhibit higher plant growth and performance. We reduced the inhibitory mechanisms into direct and indirect mechanisms. The direct mechanisms include blocking pores or light, causing mechanical damage to roots, hindering genes expression, and releasing additives. The indirect mechanisms contain changing soil properties, affecting soil microbes or soil animals, and affecting bioavailability of other pollutants. This review improves the understanding of effects and influencing mechanisms of microplastics on higher plants.

The development of China's Circular Economy: From the perspective of environmental regulation

While achieving rapid economic growth, the pressure caused by environmental pollution and resource depletion has increasingly become a bottleneck in China's economic development, making the development of a circular economy particularly important. The extant literature has not focused on the influence of environmental regulation on a circular economy performance. This study uses the metafrontier global direction distance function (Metafrontier-Global-DDF) super-efficiency data envelopment analysis (DEA) model to estimate the circular economy performance and decomposition values of circular economy growth rate in 286 prefecture-level cities in China from 2003 to 2018. It further tests the influences of environmental regulations on circular economy performance and its influencing mechanism. The results show that environmental regulation can play a linear role in promoting the performance of the circular economy, mainly through the "catch-up effect," while "innovation effect" and "demonstration effect" have not yet played an effective role. This study provides evidence for the performance evaluation of the circular economy in China and the relationship between environmental regulations and circular economy performance. The future development of a circular economy still needs the active development of circular economy technology in each city. The role of the "innovation effect" and "demonstration effect" in improving the performance of the circular economy should be further enhanced.

Coupled effects of landscape structures and water chemistry on bacterioplankton communities at multi-spatial scales

Bacterioplankton communities in rivers are strongly influenced by the surrounding landscape, yet the relationships between land use and bacterioplankton communities at multi-spatial scales and the mechanisms that shape bacterioplankton communities remain unclear. Here, we collected surface water samples from 14 tributaries of the Yuan River, a secondary tributary of the Yangtze River, which has been heavily impacted by human activities. We characterized the bacterioplankton communities by high-throughput sequencing techniques, and managed to identify the mechanisms governing bacterioplankton community assembly. The results showed that, in general, both landscape compositions and landscape configurations had significant effects on bacterial communities, and the effects were greater at the buffer scale than at the sub-basin scale. Additionally, there was no distinct distance-decay pattern for the effects of landscape structures on bacterial communities from the near-distance (100 m) to the long-distance (1000 m) buffer zones, with the maximal effects occurring in the 1000 m circular buffer (wet season) and 500 m riparian buffer (dry season) zone, respectively. Land use influenced the bacterioplankton community both directly through exogenous inputs (mass effect) and indirectly by affecting water chemistry (species sorting). Variance partitioning analyses showed that the total explanations of bacterial community variations by water chemistry and the intersections of water chemistry and land use (56.2% in wet season and 50.4% in dry season) were higher than that of land use alone (6.1% in wet season and 25.4% in dry season). These suggest that mass effects and species sorting jointly shaped bacterial community assembly, but that the effects of species sorting outweighed those of mass effects. Nevertheless, more biotic and abiotic factors need to be considered to better understand the microbial assembly mechanisms in anthropogenically influenced riverine ecosystems.

Spatial-temporal patterns and influencing factors of ecological land degradation-restoration in Guangdong-Hong Kong-Macao Greater Bay Area

Despite the fact that urban agglomerations have undergone extensive ecological land coverage modifications, exploration of the patterns and driving mechanisms associated with ecological land degradation (ELD) and ecological land restoration (ELR) in urban agglomerations is still limited. This study combined remote sensing technology, as well as landscape index and geographical detector to characterize the spatiotemporal patterns of ELD (isolating, adjacent, and enclosing degradation) and ELR (outlying, edge-expansion, and infilling restoration) in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 1990 to 2019. Subsequently, the contributions, interactions, and driver changes were quantified. The results showed an ecological land shift from over-exploitation to balanced co-existence, which was facilitated by a spatiotemporal pattern transition from adjacent degradation-led (1990-2010) to edge-expansion restoration-led (2010-2019). Land urbanization rate and population density showed a stronger promoting effect on ELD than natural factors, while tertiary industry, topography, and soil conditions were more significant in ELR. The factors' nonlinear interaction enhanced the degradation-restoration pattern evolution and continued to increase over time-particularly the interaction between construction land expansion and other drivers. Additionally, from 2010 to 2019, 80% of the ELR socio-economic factors turned from negative to positive and gradually became to play a significant role. This study is expected to help ecological protection and restoration planners/managers recognize the factors' interactions and variations, and ultimately improve the ecological network structure that is designed to integrate the city with the ecosystem.

How does technological innovation mitigate CO2 emissions in OECD countries? Heterogeneous analysis using panel quantile regression

To verify how does the development of technological innovation effectively mitigate carbon dioxide (CO₂) emissions in Organization for Economic Co-operation and Development (OECD) countries, this study first investigates the direct impacts and moderating effects of technological innovation, measured by the development of patents on CO₂ emissions by employing a balanced panel dataset for 35 OECD countries covering 1996-2015. Also, to examine the potential heterogeneity and asymmetry, the panel quantile regression approach is utilized. The empirical results indicate that technological innovation directly reduces CO₂ emissions; however, this impact is significantly heterogeneous and asymmetric across quantiles. Furthermore, through analyzing the influencing mechanism, the technological innovation affects the impacts of economic growth and renewable energy through its moderating effects. Moreover, the moderating effects of technological innovation is also heterogenous. Accordingly, the main contribution of this study is that the potential heterogeneity and asymmetry of both the direct impact and moderating effect of technological innovation on CO₂ emissions in OECD countries are systematically analyzed by employing the panel quantile regression approach.

Assessing environmental interference in northern China using a spatial distance model: From the perspective of geographic detection

The rapid development of society and the expansion of human activities have resulted in interference with the natural environment. Assessing the environmental interference (EI) caused by human activities is highly important for socio-economic sustainable development. In this study, the spatial distance model (SDM) and resource endowment index (REI)-human activity index (HAI) ratio model were developed to calculate the environmental interference index (EII) in northern China (NC). The current spatial distribution and patterns of EII in NC were analyzed based on geographic information system (GIS) technology. In addition, the factors that influence the level of EI were examined through a geographical detector method. The results showed that the EII value in the eastern region was significantly higher than that in the western region and that differences in EI were spatial heterogeneity. The spatial distribution of EI was analyzed at the provincial, municipal and county scales, respectively. It was found that its distribution was closely related to urban development. The spatial distribution of EI displayed longitudinal zonality. East of 104.987°E, there were many large cities, such as Beijing, Tianjin, Qingdao and Zhengzhou, with high population densities and developed economies. Thus, these areas had high EI values. To the west of 104.987°E, such as in the Qinghai, Gansu, Xinjiang and Inner Mongolia regions, the EI values were generally low, with low environmental quality and fewer human activities. The level of EI in the Huang-Huai-Hai Plain region was higher than that in other areas, displaying obvious spatial dependence. Moreover, the distribution of EI exhibited high-high and low-low aggregation patterns, which accounted for 24.06% and 27.35% of the total study area, respectively. Specifically, in NC, the EI caused by human activities displayed obvious regional characteristics. In addition, the factors that influence EI were determined through a geographical detector model. The land use intensity was the direct factor related to changes in and the levels of EI, and the cover and growth of vegetation were the most important factors associated with mitigating human interference. The assessment results can provide a reference for the formulation of environmental governance and related policies.

Environmental efficiency of electric power industry, market segmentation and technological innovation: Empirical evidence from China

Environmental efficiency of electric power industry (EEE) is crucial to sustainable development. Among all the factors affecting the efficiency, there lacks enough knowledge of the role of governments and institutions in it. The purpose of this study is to explore the effect of market segmentation (ME) on environmental efficiency of electric power industry and its influencing mechanism from the perspective of technological innovation. The empirical results generated by the system generalized method of moments (GMM) approach indicate that market segmentation has significantly negative effect on environmental efficiency of electric power industry. As evidence we find shows, market segmentation hinders technological innovation, which is an important factor affecting environmental efficiency of electric power industry. Additionally, the inhibiting effect of market segmentation on environmental efficiency of electric power industry is more significant in provinces with weak institutional quality. The conclusions share insights in how to improve environmental efficiency of electric power industry in China by weakening market segmentation.

Analysis of the impact path on factors of China's energy-related CO2 emissions: a path analysis with latent variables

Identifying the impact path on factors of CO₂ emissions is crucial for the government to take effective measures to reduce carbon emissions. The most existing research focuses on the total influence of factors on CO₂ emissions without differentiating between the direct and indirect influence. Moreover, scholars have addressed the relationships among energy consumption, economic growth, and CO₂ emissions rather than estimating all the causal relationships simultaneously. To fill this research gaps and explore overall driving factors' influence mechanism on CO₂ emissions, this paper utilizes a path analysis model with latent variables (PA-LV) to estimate the direct and indirect effect of factors on China's energy-related carbon emissions and to investigate the causal relationships among variables. Three key findings emanate from the analysis: (1) The change in the economic growth pattern inhibits the growth rate of CO₂ emissions by reducing the energy intensity; (2) adjustment of industrial structure contributes to energy conservation and CO₂ emission reduction by raising the proportion of the tertiary industry; and (3) the growth of CO₂ emissions impacts energy consumption and energy intensity negatively, which results in a negative impact indirectly on itself. To further control CO₂ emissions, the Chinese government should (1) adjust the industrial structure and actively develop its tertiary industry to improve energy efficiency and develop low-carbon economy, (2) optimize population shifts to avoid excessive population growth and reduce energy consumption, and (3) promote urbanization steadily to avoid high energy consumption and low energy efficiency.