The dihydrate phosphoric acid process is the mainstream technique. However, the phosphogypsum (PG) produced contains high levels of impurities such as phosphorus and fluorine, severely constraining its valorization. In order to elucidate the occurrence patterns of phosphorus and fluorine impurities in PG, this study employed analytical methods including XRF, XRD, AMICS (Automated Mineralogy Integrated with Chemistry System), XPS, and chemical element balance analysis. We investigated the occurrence states of phosphorus, fluorine, silicon, iron, and aluminum elements in PG from wet-process phosphoric acid production, as well as the distribution characteristics of phosphorus and fluorine impurities. Additionally, we utilized Density Functional Theory (DFT) calculations to determine the binding energies of major minerals with water-soluble phosphate and fluoride groups, and analyzed the zeta potentials of gypsum and quartz mineral surfaces. The results indicate that the main mineral phases in PG are gypsum, quartz, potassium silicate minerals, aluminosilicate minerals, and hematite, predominantly occurring in monomineralic forms. Phosphorus impurities primarily exist in calcium silicate and hematite minerals, while fluorine is mainly associated with gypsum and potassium silicate minerals. DFT calculations demonstrate strong binding energies between calcium silicate and hematite minerals with PO₄ ³⁻, as well as between gypsum and quartz minerals with F⁻. The acidic conditions in the separation tank during wet-process phosphoric acid production may contribute to the distinctive distribution characteristics of phosphorus and fluorine impurities in PG.

As a large-volume industrial solid waste generated during the production of wet-process phosphoric acid, the primary disposal method for phosphogypsum (PG) currently involves centralized stockpiling, which requires substantial land use. Additionally, PG contains impurities, such as phosphorus, fluorine, and alkali metals, that may pose potential pollution risks to the surrounding environment. However, the mechanisms governing the co-release of phosphorus and fluorine impurities alongside valuable metal cations during leaching remain unclear, posing challenges to efficient disposal and utilization. This study compares the leaching characteristics of cations and anions in PG of different particle sizes through static pH leaching experiments. Using Visual MINTEQ simulation combined with XRD, XPS, and FT-IR characterization methods, we analyzed the leaching mechanisms and key controlling factors for various metal elements and inorganic elements, like phosphorus and fluorine, under different pH conditions. The experimental results show that Ca, Al, Fe, Ti, Ba, Sr, Y, and PO₄³⁻ in PG are more easily released under acidic conditions, while Si, Zn, Co, and F are primarily influenced by the content of soluble components. The dynamic “dissolution–crystallization” reaction of CaSO₄·H₂O significantly impacts the leaching of fluorine, and the XRD, XPS, and FT-IR characterization results confirm the presence of this reaction during the leaching process. This research provides theoretical guidance for the environmental risk assessment of stockpiled PG and the recovery of phosphorus, fluorine, and valuable metal resources from PG.

Because of its low whiteness, complex composition, radioactivity and high impurity percentage, the usage of phosphogypsum (PG) resources is limited. A theoretical foundation for upgrading and bleaching PG can be obtained by researching the presence and status of impurities in the material and its symbiotic connection with gypsum. This paper makes use of an automatic mineral phase analyzer, optical microscope, XRF, XRD and SEM-EDS. After analyzing the chemical makeup of PG, phase composition and particle size composition, the distribution law and symbiotic interaction between impurities and gypsum in various particle sizes were discovered. Using a flotation test, the process mineralogy analysis results were confirmed. According to the XRF and XRD study results, the primary impurity elements in PG are Si, P and F. Si is more abundant in PG that is between +850 μm and −37.5 μm in size. The concentrations of gypsum and quartz in PG are 82.59% and 8.73%, respectively, according to the results of XRD and process mineralogy. The monomer dissociation degree of the gypsum mineral phase is as high as 90.47%. Gibbsite and pyrite are the primary causes of the low whiteness of PG and are clearly related to the quartz mineral phase. The coupling process of “flotation + pickling” produced purified PG with a purity of 95.35%, whiteness of 70.76% and SiO₂ content of 2.73%. The quality met the first-class index standards of PG in GB/T23456-2018.

Facing the challenges of high complexity in Building Information Modeling (BIM) technology application and insufficient realization of its benefits, this study identifies key influencing factors of BIM effectiveness through the literature analysis and multi-case research. A comprehensive evaluation system is constructed, covering six dimensions—technical level and application capability, organizational and management, human capability, economic and market factors, project factors, and external environment—with 30 specific indicators. Based on 257 valid questionnaire responses, a Structural Equation Model is developed, and reliability/validity tests as well as model fit verification are conducted using SPSS and AMOS. The findings reveal that human capability factors (weight: 0.182) serve as the core driver for realizing BIM value. Technical conditions, project characteristics, and external environment exhibit balanced influences (each with a weight of 0.164), while economic market (weight: 0.167) and organizational management (weight: 0.159) require collaborative optimization to enhance synergy. A four-dimensional coordination system—”technology support-organizational collaboration-human capability-policy guidance”—is proposed based on these conclusions. Practical application demonstrates that this system improves BIM implementation efficiency by 23% and reduces project rework rates by 40%, providing quantifiable implementation pathways for construction enterprises to optimize resource allocation and advance digital transformation. The research aims to offer theoretical guidance and technical support for promoting the digital evolution of the construction industry.

The current green building assessment system suffers from issues such as insufficient coverage of smart indicators, significant biases in subjective weighting, and weak dynamic adaptability, which restrict the scientific promotion of green buildings. This study focuses on the gaps in the quantitative assessment of smart technologies in China’s green building evaluation standards (such as the current Green Building Evaluation Standard). While domestic standards are relatively well-established in traditional dimensions like energy conservation and environmental protection, there are fragmentation issues in the assessment of smart technologies such as the Internet of Things (IoT) and BIM. Moreover, the coverage of smart indicators in non-civilian building fields is significantly lower than that of international systems such as LEED and BREEAM. This study determined the basic framework of the evaluation indicator system through the Delphi method. Drawing on international experience and contextualized within China’s (GB/T 50378-2019) standards, it systematically integrated secondary indicators including “smart security,” “smart energy,” “smart design,” and “smart services,” and constructed dual-drive evaluation dimensions of “greenization + smartization.” This elevated the proportion of the smartization dimension to 35%, filling the gap in domestic standards regarding the quantitative assessment of smart technologies. In terms of research methods, combined weighting using the Analytic Hierarchy Process (AHP) and entropy weight method was adopted to balance subjective and objective weights and reduce biases (the resource conservation dimension accounted for 39.14% of the combined weights, the highest proportion). By integrating the grey clustering model with the whitening weight function to handle fuzzy information, evaluations were categorized into four grey levels (D/C/B/A), enhancing the dynamic adaptability of the system. Case verification showed that Project A achieved a comprehensive evaluation score of 5.223, with a grade of B. Among its indicators, smart-related ones such as “smart energy” (37.17%) and “smart design” (37.93%) scored significantly higher than traditional indicators, verifying that the system successfully captured the project’s high performance in smart indicators. The research results indicate that the efficient utilization of resources is the core goal of green buildings. Especially under pressures of energy shortages and carbon emissions, energy conservation and resource recycling have become key priorities. The evaluation system constructed in this study can provide theoretical guidance and technical support for the promotion, industrial upgrading, and sustainable development of green buildings (including non-civilian buildings) under the dual-carbon goals. Its characteristic of “dynamic monitoring + smart integration” forms differentiated complementarity with international standards, making it more aligned with the needs of China’s intelligent transformation of buildings.