Graphitic carbon nitride (g-C3N4), with facile synthesis, unique structure, high stability, and low cost, has been the hotspot in the field of photocatalysis. However, the photocatalytic performance of g-C3N4 is still unsatisfactory due to insufficient capture of visible light, low surface area, poor electronic conductivity, and fast recombination of photogenerated electron-hole pairs. Thus, different modification strategies have been developed to improve its performance. In this review, the properties and preparation methods of g-C3N4 are systematically introduced, and various modification approaches, including morphology control, elemental doping, heterojunction construction, and modification with nanomaterials, are discussed. Moreover, photocatalytic applications in energy and environmental sustainability are summarized, such as hydrogen generation, CO2 reduction, and degradation of contaminants in recent years. Finally, concluding remarks and perspectives on the challenges, and suggestions for exploiting g-C3N4-based photocatalysts are presented. This review will deepen the understanding of the state of the art of g-C3N4, including the fabrication, modification, and application in energy and environmental sustainability.

Four products were obtained from sodium dodecylbenzene sulfonate (SDBS) and formaldehyde (40% solution) using a simple reaction. The products were characterized by TGA, IR, UV and MS to confirm the major chemicals in each sample. The new products could reduce the interfacial tension between oil and water in the experimental temperature range further compared to SDBS. The emulsion ability was also enhanced by SDBS-1 to SDBS-4. The oil-displacement efficiencies of SDBS-1 to SDBS-4 were obviously higher than that of SDBS, and the oil-displacement efficiency of SDBS-2 was the best, with an efficiency of 25%. The experimental results all indicate that these products have an excellent ability to reduce oil–water interfacial tension and that they can be used in the oil and petrochemical industry for oil production and have certain practical uses.

Frequent oil spills have caused serious consequences to the ecosystem and environment. Therefore, in order to reduce and eliminate the impact of oil spills on biology and the environment, oil spill remediation materials must be considered. As a kind of cheap and biodegradable natural organic cellulose oil-absorbing material, straw has an important practical significance in the treatment of oil spills. In order to improve the ability of rice straw to absorb crude oil, rice straw was first treated with acid and was then modified with sodium dodecyl sulfate (SDS) through a simple charge effect. Finally, the performance of oil absorption was tested and evaluated. The results illustrate that the oil absorption performance was greatly improved under the conditions of 10% H2SO4, for a 90 min reaction at 90 °C, under 2% SDS, and reacted for 120 min at 20 °C, and the rate of adsorption for rice straw to crude oil was raised by 3.33 g/g (0.83 to 4.16). Then, the rice stalks before and after the modification were characterized. Contact angle analysis shows that the modified rice stalks display better hydrophobic–lipophilic properties than unmodified rice stalks. The rice straw was characterized by XRD and TGA, and the surface structure of the rice straw was characterized by FTIR and SEM, which explain the mechanism of surface-modified rice straws with SDS to improve their oil absorption capacity.

This paper measures the human development indices of 31 inland provinces (municipalities) in China in a continuous time series during 2000-2017 according to the 2010 HDI compilation method. It uses a geographically and temporally weighted regression model for conducting an empirical study on the effects of R&D investment and network penetration on human development in each province (municipality) of China. There is significant spatial and temporal heterogeneity in the impact of R&D investment and network penetration on human development across provinces (municipalities) in China due to differences in resource endowments and economic and social development. For R&D investment, eastern provinces (municipalities) have mostly positive effects on human development, and central regions have mostly weak positive or negative effects. In contrast, western provinces (municipalities) show different development paths, with weak positive effects in the early stage and significant positive effects after 2010. Most provinces (municipalities) show a continuous and increasing positive effect for network penetration. The marginal contributions of this paper are mainly in improving the shortcomings in research perspectives, empirical methods, and research data in the study of human development influencing factors in China relative to the study of HDI itself in terms of measurement or application dimensions. This paper constructs a human development index for China, analyzes its spatial and temporal distribution, and explores the impact of R&D investment and network penetration on human development in China, with the hope of providing lessons for China and developing countries to promote the level of human development and cope with the pandemic. KeywordsR&D investment • Network penetration • Human development level • Geographically and temporally weighted regression model * Hongli Zhang

Understanding the effect mechanisms of various factors on land subsidence may help in the development of scientific measures to control land subsidence. Previous studies mainly focused on exploring local effect mechanisms, such as extracting hotspots and analyzing their spatiotemporal distribution characteristics and identifying the interaction mechanisms of the associated factors. However, the scarcely discussed structural effect mechanisms on a small scale suggests a need to further explore the effects on land subsidence. Therefore, in this paper, an analytical framework was proposed to elaborate the structural effect mechanisms of influencing factors on land subsidence. First, the local effect mechanisms were identified using the geographically and temporally weighted regression (GTWR) model, followed by a spatial clustering analysis and the detection of their aggregation pattern using the spatially constrained multivariate clustering (SCMC) model to show the structural mechanisms. Study datasets included the monitoring results of land subsidence during 2003–2010 and the related socioeconomic factors by using synthetic aperture radar (SAR) images from Beijing. Factors such as population, annual average rainfall, underground water, and static load were identified to measure the changes in land subsidence, and all of these had both negative and positive impacts. Among these, the annual average rainfall had the largest coefficient variation range. These four geographically associated factors revealed various spatiotemporal effects on land subsidence in Beijing, showing land subsidence changes resulting from the urbanization process of Beijing during that period.