As a class of famous carbon materials, biochars (BCs) and their derivative materials with excellent physicochemical properties and diversified functionalities present great potential in wastewater treatment fields. This review focuses on the latest development in reported biochar-based materials as superior adsorbents or catalysts for removing harmful organic contaminants from wastewater. The construction and properties of biochar-based materials are briefly introduced at the beginning. As one of the major factors affecting the properties of BCs, the wide diversity of feedstocks, such as agricultural and forest residues, industrial by-products as well as municipal wastes, endows BCs different chemical compositions and structures. Woody and herbaceous BCs usually have higher carbon contents, larger surface areas and strong aromaticity, which is in favor of the organic contaminant removal. Driven by the desire of more cost-effective materials, several types of biochar-based hybrid materials, such as magnetic BC composites (MBC), nanometal/nanometallic oxides/hydroxide BC composites and layered nanomaterial-coated BCs, as well as physically/chemically activated BCs, have also been developed. With the help of foreign materials, these types of hybrid BCs have excellent capacities to remove a wide range of organic contaminants, including organic dyestuff, phenols and chemical intermediates, as well as pharmaceutically active compounds, from aquatic solutions. Depending on the different types of biochar-based materials, organic contaminants can be removed by different mechanisms, such as physical adsorption, electrostatic interaction, π-π interaction and Fenton process, as well as photocatalytic degradation. In summary, the low cost, tunable surface chemistry and excellent physical-chemical properties of BCs allow it to be a potential material in organic contaminant removal. The combination of BCs with foreign materials endows BCs more functionalities and broader development opportunities. Considering the urgent demand of practical wastewater treatment, we hope more researches will focus on the applications and commercialization of biochar-based materials.

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Developing specialties in orchard fruits productions with ecological and economic benefits is a practical and effective way to guarantee eco-friendliness and increase farmers’ income in the Loess Plateau area. Therefore, to understand these factors, the study constructs an agriculture ecological cognition index from three dimensions of eco-agriculture cognitions (increase income cognition, water conservation cognition and eco-product price cognition). Our analysis was based on micro survey data from 416 farmers in Shaanxi and Ningxia, China. The study used two main econometric models, double-hurdle and Interpretative Structural Modeling (ISM), to examine the relationship and influence pathways between cognition of ecological agriculture and farmers’ specialty orchard fruit planting behavior. The results show that: (i) the cognition of eco-agriculture affects whether farmers plant specialty fruits (participation decision). The cognition of eco-agriculture increases income and the cognition of eco-product price significantly affect the scale of specialty orchard fruits planting (quantity decision). (ii) Household resource endowments influence specialty orchard fruit planting responses through ecological farming cognitions. (iii) The factors influencing the participation and quantity decisions of orchard fruit planting are significantly different. Therefore, when the government actively encourages farmers to participate in specialty orchard planting, it should fully consider the cognitive factors of ecological agriculture of the growers and develop targeted training strategies.

Ediacara-type macrofossils characterize the late Ediacaran Period and are pivotal in understanding the early evolution of animals on the eve of the Cambrian explosion and useful in late Ediacaran biostratigraphy. They have been discovered on almost all major paleocontinents, except the North China and Tarim blocks, as well as on a series of northwestwest–oriented cratonic fragments between the two blocks, including the Olongbuluke terrane of the Qaidam block, where the terminal Ediacaran successions developed. We report a newly discovered terminal Ediacaran biotic assemblage, the Quanjishan assemblage, containing Ediacara-type fossils from the Zhoujieshan Formation of the Quanji Group in the Olongbuluke terrane, Qaidam Basin, northwestern China. The Quanjishan assemblage is dominated by the non-biomineralized tubular taxon Shaanxilithes, which has the potential to be a terminal Ediacaran index fossil, and by the iconic frondose rangeomorph Charnia, which represents the only unambiguous Ediacara-type fossil discovered in northwestern China. The co-occurrence of Charnia and Shaanxilithes from the Quanjishan assemblage likely constrains the depositional age of the Zhoujieshan Formation to be terminal Ediacaran (ca. 550–539 Ma) and the immediately underlying Hongtiegou diamictites to be late Ediacaran, probably representing post-Gaskiers glacial deposition. The occurrence of post-Gaskiers Ediacaran glaciation and similarities between the late Ediacaran–early Paleozoic lithostratigraphic and biostratigraphic sequences in the Olongbuluke terrane of the Qaidam block and the North China block suggest that these two blocks may have been located close to each other during this time period, and situated in the middle to high latitudes instead of the equatorial region.

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The allocation efficiency of China’s agricultural science and technology resources (ASTR) varies in different regions and has a complicated spatial distribution pattern. To visually study whether there are correlations and mutual influences between the allocation efficiency of different regions, we use social network analysis methods (SNA). The study found that: (i) China’s allocation efficiency of ASTR has significant spatial correlation and spillover effects. The overall network density is declining. (ii) The spatial correlation network has significant regional heterogeneity. Some eastern provinces play “intermediaries” and “bridges” in the network. (iii) Geographical proximity, differences in economic development levels, industrial structure levels, and differences in urbanization have a significant impact on the formation of spatial association networks.

BACKGROUND Rural China is characterized as having different rates of economic growth. The resource and socioeconomic statuses of farm households greatly affect their productivity and the activities they engage in. The main objective in this study was to explore the mechanisms concerning how socioeconomic status of kiwifruit growers affects their adoption of biological control technology (BCT). To achieve this objective, field survey data from 650 kiwifruit farmers in specific kiwifruit growing areas of Shaanxi and Sichuan provinces in China were investigated. The binary probit model and Bootstrap dual mediated utility models served to assess socioeconomic status's effect on farmers' BCT adoption. RESULTS This study discovered a significant positive correlation between socioeconomic status and the adoption rate of biological control technology. Farmers of various socioeconomic status have significant differences in the rate of BCT adoption. This study's empirical analysis found that exploratory learning and exploitative learning under dual learning had a significant mediating effect on farmers' socioeconomic status when it came to BCT acceptance. CONCLUSION Results show that the rate of BCT adoption is related to farmers' socioeconomic status and dual learning mode, which provides new insights for understanding how farmers implement new technology. This study will help agricultural extension departments increase their awareness of BCT adoption by farmers, and the development of diverse learning approaches in response to differences in socioeconomic status of farmers may significantly increase their likelihood to implement BCT. © 2021 Society of Chemical Industry.

Purpose Based on the survey data of 650 kiwi growers from Shaanxi and Sichuan provinces, this paper used multiple endogenous transformation regression models to explore the effect of the joint adoption of green production technology on farmer’s welfare. The purpose of the study is to analyze the influence of green production technology on the yield, household income and socioeconomic characteristics of Kiwi fruit growers. Design/methodology/approach In the context of the study, multiple endogenous transformation model (MESR) are adopted, but self-actualization tactics were adopted to deal with the instrumental variables. The empirical data has been collected via a combined hierarchical sampling and random sampling, whereas a well-structured Likert scale questionnaire was adopted as well. The empirical data has been processed with the help of STATA 15.1 version. Findings The study found a positive impact of adopting green production technology. Moreover, the joint adoption of green production technology by kiwi growers has significantly increased the yield, economic values of Kiwi and household income of kiwi farmers. The households with higher asset value, better land quality, weaker credit constraints, more technical training and stronger government promotion and support from local governments are the most likely to adopt pest control technology and soil management technology jointly. Originality/value The prime innovation of the paper is to measure the impact of technology combination adoption on farmer’s welfare is evaluated, rather than the impact of single sub technology on farmer’s’ welfare.