Sustainable Development Research

Research on the Construction and Planning of Industrial Complexes in Scenic Areas

Lin Zhou, Hu Chen — Fri, 28 Mar 2025 00:00:00 +0800

With the stable development of the social economy and the continuous improvement of living standards, people increasingly pursue spiritual fulfillment through tourism. Under the current national push for high-quality tourism development and the comprehensive implementation of rural revitalization strategies, while tourism resources flourish, the development of surrounding towns and villages often lags behind scenic areas, creating disparities. By studying the construction and planning of industrial complexes in scenic areas, we can drive further economic development in neighboring towns and villages, increase income, and enhance the comprehensive competitiveness of scenic areas. This study focuses on the Baili Rhododendron Scenic Area, integrating spatial layout optimization, ecological conservation, and cultural inheritance into a holistic planning framework. It explores the "industrial complex" model to achieve natural ecological protection, deep industrial integration, and balanced regional economic development.

Efficient Electrochemical Nitrate Reduction to Optimize the Nitrogen Cycle

Xu hui — Mon, 07 Apr 2025 00:00:00 +0800

This study investigates the potential of electrochemical nitrate reduction (ECNR) technology in optimizing the nitrogen cycle, addressing the critical issue of nitrate pollution. By examining various electrode materials, operational parameters, and system designs, the research aims to enhance the efficiency and selectivity of nitrate reduction. Experimental results reveal significant variations in nitrate reduction efficiency among different electrode materials, with platinum demonstrating the highest performance. The study underscores the importance of material selection, electrolyte conditions, and precise control of operational parameters in achieving effective nitrate remediation. The findings contribute valuable insights for both academic research and practical applications, highlighting ECNR’s promise in mitigating nitrate pollution and promoting a healthier nitrogen cycle.

Research on the Path of Integrating the Spirit of Third-Line Construction into Learning-Oriented City Construction-Taking Chengdu as an Example

Sun Zhila, Lai lu — Tue, 08 Apr 2025 00:00:00 +0800

This paper examines the potential of "The Spirit of the Third Line Construction"to contribute to the development of Chengdu as a learning city. The Third-line Construction, a massive industrial relocation effort in the 1960s and 70s, instilled values of self-reliance, innovation, and dedication that continue to resonate in western China. This paper argues that these values can be leveraged to address the challenges facing Chengdu in its quest to become a leading learning city. Through a review of existing literature and analysis of Chengdu’s urban development initiatives, this paper identifies specific paths for integrating the the spirit of the third line construction into learning city construction. The findings provide practical recommendations for policymakers and stakeholders on how to foster innovation, promote lifelong learning, and enhance community engagement in Chengdu.

Analysis of Factors Influencing the Willingness to Accept Carbon Inclusion Market Based on Structural Equation Modeling——Taking Xi'an City as an Example

Yangchen Sun — Wed, 16 Apr 2025 00:00:00 +0800

The purpose of this paper is to investigate the willingness of Xi'an residents to accept carbon benefits, using a combination of principal component analysis and structural equation modeling. First, the data were collected from 16 questions using a five-point scale, and after confirming that the data were suitable for principal component analysis by KMO and Bartlett's test of sphericity, five principal components were extracted, with a cumulative variance explained rate of 87.116%, which realized dimensionality reduction and retained the key information. Second, structural equation modeling was used to construct the model with cognitive situation and decision-making behavior as latent variables. It was found that the perception of the carbon inclusion program's effect on carbon emissions significantly affects the cognitive situation, the greatest impact on satisfaction is whether participants are willing to promote the Carbon for All program, and the use of the carbon inclusion platform by people around us has the greatest impact on the practice situation. This study provides a basis for in-depth understanding of residents' willingness to accept carbon benefits, as well as a reference for the promotion and development of carbon benefits.

Investigation on Tourism Trends Using K-means Clustering and Regression Analysis

Anna Sheila Ilumin Crisostomo, Badar Al Dhuhli, Reggie C. Gustilo — Thu, 08 May 2025 00:00:00 +0800

Purpose: The purpose of this study was to analyze tourism trends by determining the clusters of tourists based on common factors. Three (3) characteristics were explored using k-means clustering namely tourists’ demographics, travel patterns and travel preferences. These clusters were based on individual’s age, gender, country of origin, frequency of travel, travel destinations and seasons. Regression analysis was also performed to determine the factors that influence the length of stay of tourists in their travel destinations.

Methodology: This research conducted a survey from 150 respondents of different age groups, gender, and nationalities. Frequency of travel in a year, length of stay per travel, seasons, destinations, purpose of travel and preferred booking method were the parameters inquired in the survey. The collected dataset was utilized to characterize the clusters of tourists with common considerations. Additionally, regression analysis was used to forecast predictors influencing tourists’ length of stay.

Findings: Three (3) parameters were considered in performing k-means clustering such as tourists’ demographic profiles, travel patterns and preferences. Regression analysis likewise was employed to predict visitors’ length of stay using age, gender, purpose of travel, travel season, and preferred destination as independent variables. In participants’ demographics, number of clusters generated was k=5. Gender and nationalities were found to be randomly clustered while other parameters were categorized according to various age groups and frequency of travel. Consequently, for tourists’ travel patterns, age, gender, country of origin, frequency of stay, purpose of travel, length of stay and travel seasons were used as parameters. The elbow method knee-point revealed (k=6) as the optimal number of clusters. Moreover, travel preferences parameter was also considered for clustering where predictors like gender, age, country of origin, frequency of travel, purpose of travel, travel season and length of stay were utilized. The optimal number of clusters for this category generated K=5. Regression analysis revealed gender, age and purpose of travel as significant factors influencing tourists’ average length of stay. The combination of these variables generated the lowest value of MSE=0.64.

Research limitations/implications: A limited dataset of 150 respondents mainly from Asia and Middle East were utilized in performing preliminary initiatives in analyzing tourism trends. The predictors used in the analysis were restricted to gender, age, country of origin, travel frequency, length of stay, travel season and travel destinations. Supplementary parameters ca be considered in a big data setting for similar studies in the future. K-means clustering was selected among other algorithms with attributes commonality while regression analysis was employed to determine the factors influencing tourists’ length of stay in their destinations.

Social Implications: Results of this study will greatly support individual tourists in determining trends in various travel destinations. Similarly, business owners gain benefit forecasting travellers’ requirements such as accommodation, food, services, etc. Research findings likewise provide informed decisions for stakeholders

Originality / Value: The dataset used were participants from different countries and nationalities which include Philippines, Saudi Arabia, United Arab Emirates, Oman, USA, Portugal, Germany, Malaysia, Thailand, Qatar, Finland, Denmark, Spain Taiwan, South Korea, Singapore, Australia, Austria, England, UK, India and China. The presented codes were programmed in python where analyses and interpretations were based on formulated objectives. K-means clustering, and regression analysis were both employed to present varied clusters according to tourists’ demographic profiles, travel patterns and preferences. Different factors were identified and used to predict tourists’ length of stay in their preferred destinations.

Underwater Access Door System for Tidal Power Generation

Xiaonan Miao, Jia Li — Tue, 13 May 2025 00:00:00 +0800

The difficulty in maintaining tidal power generation equipment is an important factor restricting its development. The tidal power underwater access door system uses a power device to drive the metal seal. When the machine is stopped, a temporary channel is formed between the rotating and stationary parts. After drainage, personnel can maintain the rotating parts through the channel. In the past four years of use, the system has good stability and zero leakage, solving the problem of having to pull out of the sea for maintenance of tidal power generation equipment and reducing maintenance costs.

Research on the Construction of an Evaluation System for the Diversion Effect of Urban Tourist Flow

Xiaoyun Tang, Qiongfeng He, Xiling Zhou — Sat, 17 May 2025 00:00:00 +0800

To address the challenge of assessing real-time urban tourist flow diversion effectiveness, this study incorporates knowledge graph technology, leveraging extensive research results as foundational data. Through the steps of information extraction, knowledge fusion and knowledge processing of the keywords of the article, the index system was preliminarily established by combining the quantitative and qualitative methods of expert consultation. In this study, the Delphi method was used to optimize the index system, and an evaluation index system consisting of 1 standard-level index, 6 system-level indicators and 21 index-level indicators was constructed. Then, the analytic hierarchy process was used to calculate the weights of the index system. Through research and interviews, practical experience and literature to determine the index measurement and scoring rules, combined with the national scientific and technological innovation project based on this institute, the pilot evaluation of tourist flow regulation in Suzhou, Tianshui, Wuhu and other places was carried out, and the evaluation system and method were verified. This comprehensive method, which is based on a knowledge graph and combines qualitative and quantitative approaches, offers a novel idea for constructing an index system, especially in the absence of mature theoretical references and practical experiences. This study effectively solves the problem of the evaluation system of the effectiveness of urban tourist flow control, and has strong theoretical innovation and practical significance.

The Study on Nitrogen Removal Enhancement from Secondary Biochemical Effluent by Sulfur Autotrophic Denitrification Composite Filler

Yi Rong, Hua Fang — Thu, 22 May 2025 00:00:00 +0800

Experiments were conducted using simulated secondary effluent from wastewater treatment plants. A composite filler was prepared by mixing sulfur and pyrite (FeS₂) as electron donors for microorganisms to evaluate the nitrate removal efficiency under different filler compositions. Three iron-carbon-based composite sulfur autotrophic denitrification fillers were synthesized with varying pyrite-to-sulfur mass ratios (2:1, 1:1, and 1:2, labeled as FS1, FS2, and FS3, respectively). A synergistic autotrophic-heterotrophic denitrification biofilter system was established to compare the operational conditions and nitrogen removal performance among mixed autotrophic-heterotrophic, heterotrophic, and autotrophic denitrification processes. The results showed that the FS2 system (FeS₂:S = 1:1) achieved the shortest start-up time (7 days), 33% and 50% faster than FS1 (FeS₂:S = 2:1) and FS3 (FeS₂:S = 1:2), respectively. During the start-up phase, FS2 exhibited the highest NO₃⁻-N removal rate (1.82 mg/(L·h)), significantly outperforming FS1 (1.25 mg/(L·h)) and FS3 (0.98 mg/(L·h)). The optimal HRT for pyrite-based systems was 24 h, with FS2 achieving the highest NO₃⁻-N removal efficiency (94.2%), followed by FS3 (84.2%) and the pure sulfur system (80%). When HRT was reduced to 12 h, FS2 maintained a removal efficiency of 81.3%, while FS1 and FS3 declined to 78.5% and 65.2%, respectively. Within pH 6.5–8. 0, FS2 demonstrated stable NO₃⁻-N removal (95%–98%) with minimal effluent pH fluctuation (±0.3 from initial pH 7.0), whereas FS1 and FS3 exhibited larger pH variations (±1.2 and ±1.8, respectively), indicating inferior buffering capacity. The FS2 filler (FeS₂:S = 1:1) exhibited superior denitrification efficiency, rapid system start-up, and robust pH stability, making it a promising candidate for enhancing nitrogen removal in secondary effluent treatment.

Research on the Construction of CuFeS2/ Bi2O3 Composite Materials and Degradation of Bisphenol A by Activating PMS

Shiqi Huang, Jingjing Xu — Fri, 23 May 2025 00:00:00 +0800

Bisphenol A (BPA) is harmful to human health. Advanced oxidation technologies using peroxymonosulfate (PMS) can effectively remove organic pollutants. Among these technologies, bimetallic sulfides stand out for their excellent activation ability. This study focuses on CuFeS₂, and CuFeS₂/Bi₂O₃ catalysts were prepared using a hydrothermal method. The CFSBO-2/PMS system can degrade up to 84.06% of BPA in just 30 seconds. XRD analysis shows that compared to the original CFS, the CFSBO catalyst significantly enhances the intensity of diffraction peaks, indicating improved crystallinity. The system maintains high degradation efficiency as the pH increases from 3.6 to 9.0, suggesting that the catalyst is highly adaptable to different water treatment conditions. The main active species generated are SO₄−•, •OH, and ¹O₂. PMS activation in this system is driven by the redox cycles of Cu⁺/Cu²⁺, Fe²⁺/Fe³⁺, and Bi³⁺/Bi⁵⁺.