International Journal of Environment and Pollution (8 papers in press)

Regular Issues

• Coordinated scheduling of photovoltaic greenhouse energy based on PBFT consensus mechanism  
  by Hui Yan, Dejin Chu, Yunxin Long, Ping Yu, Duo Long 
  Abstract: Aiming at the demand of photovoltaic greenhouse energy management, this paper proposes a collaborative control method of photovoltaic greenhouse energy based on PBFT consensus mechanism. Firstly, the characteristics of photovoltaic output of photovoltaic greenhouse are analyzed, and the influence of weather and other factors on photovoltaic power generation system is considered. Secondly, a distributed energy system model composed of multiple photovoltaic greenhouses is constructed, and a distributed economic scheduling model is introduced to achieve the maximum utilization and economy of energy. Finally, combined with PBFT consensus mechanism, a distributed algorithm is designed, which enables each greenhouse to make power scheduling decisions together to ensure the consistency and stability of scheduling results. The simulation results show that the proposed method can effectively optimize the energy dispatching, reduce the cost and improve the reliability of the system
  Keywords: photovoltaic greenhouse; distributed energy scheduling; PBFT consensus mechanism; energy storage; cost-effectiveness.
  DOI: 10.1504/IJEP.2024.10063371
   
  
• An environmental pollution assessment method for tourist attractions in nature reserves based on factor analysis  
  by Qiong Da, Fang Zhou, Nima Ciren 
  Abstract: In order to improve the accuracy of environmental pollution assessment and shorten the assessment time, a factor analysis based environmental pollution assessment method for tourist attractions in nature reserves is proposed. Firstly, establish an environmental pollution assessment index system for tourist attractions. Secondly, based on the evaluation index system, collect relevant data on environmental pollution in tourist attractions, including air pollution data, water pollution data, soil pollution data, noise pollution data, ecosystem data, and socio-economic data. Finally, a standardized matrix was constructed using factor analysis to extract common factor variables of environmental pollution risk in tourist attractions. Calculate the comprehensive factor score of environmental pollution risk and complete the environmental pollution assessment of tourist attractions. The experimental results show that the environmental pollution assessment results of this method are completely consistent with the actual results, and have a shorter assessment time.
  Keywords: factor analysis method; nature reserves; tourist attractions; environmental pollution assessment.
  DOI: 10.1504/IJEP.2024.10063450
   
  
• An evaluation and analysis method of heavy metal pollution in soil of agricultural land around mining areas based on double index method  
  by Xiaojie Hou, Yanle Zhang, Xuan Liu, Chunsheng Zhou, Xingjie Dang, Jianing Hu 
  Abstract: To analyse the pollution degree of soil heavy metals more effectively, aiming at the agricultural land around the mining area, an evaluation and analysis method of heavy metal pollution in soil of agricultural land around mining areas based on double index method is proposed. Based on the correction characteristics of indicator factors, soil heavy metal pollution assessment indicators are selected. The polarization fluorescence spectroscopy method is used to extract the characteristic information of heavy metals in the soil. Using the single factor index method and the Nemerow pollution index method to form the "double index method", the evaluation results of soil heavy metal pollution level are obtained based on data normalization processing. Experiment shows that the highest fit between the evaluation results of this method and the actual pollution level can reach 97.26%, and the sensitivity ranges from 0.91 to 0.97, indicating the effectiveness of this method.
  Keywords: single factor index method; Nemerow pollution index method; mining area pollution; agricultural land soil; heavy metal pollution; evaluation and analysis method.
  DOI: 10.1504/IJEP.2024.10063517
   
  
• Towards sustainable transportation and integrating ANN, RSM, and exergy analysis for biofuel-diesel blend optimisation of biodiesel ignition enhancer blends  
  by S. Ajay, S. Sivani Hansiha, G. Madhan, K. Manikandan 
  Abstract: In light of mounting environmental concerns and diminishing fossil fuel reserves, the search for environmentally friendly transportation alternatives has taken on more urgency. This research aims to improve combustion efficiency and lower emissions by determining the optimum ignition enhancer mixes for biodiesel, a promising sustainable fuel source. To accomplish long-term optimization of biodiesel ignition enhancer blends, this study employs a multi-pronged strategy using Artificial Neural Networks (ANN), Response Surface Methodology (RSM), and Exergy Analysis. In the first step, we build an ANN model to predict, from the chemical and physical features of biodiesel-diesel-ignition enhancer mixtures, their ignition characteristics. The ignition performance prediction accuracy of the ANN model is guaranteed by its training on a large dataset of experimental outcomes. Second, the optimal mix ratios of biodiesel, diesel, and ignition enhancer are determined using RSM. This method methodically investigates the parameter space, revealing the best blend ratios that provide the desired combustion efficiency and emissions goals without compromising on sustainability standards. In addition, exergy analysis is used to evaluate the improved blends' thermodynamic efficiency and ecological effect.
  Keywords: artificial neural networks; exergy; response surface models; biodiesel; ignition enhancer.
  DOI: 10.1504/IJEP.2024.10064513
   
  
• Altered composition of the Indonesian gut microbiome and heavy metal resistance genes abundance in response to heavy metal exposure  
  by Fitria Nungky Harjanti, Maulida Aisyah Khairunnisa, Ruri Agung Wahyuono, Arif Luqman, Anjar Tri Wibowo 
  Abstract: Exposure to heavy metals poses a significant risk to human health due to their accumulation through inhalation, ingestion, and contact with contaminants. Such exposure can profoundly alter the gut microbiome, potentially causing gastrointestinal disorders and heightened infection vulnerability. Indonesia, like other nations, grapples with heavy metal-related health issues. Nonetheless, the extent of heavy metal contamination in the Indonesian population and its impact on their gut microbiome remain unexplored. Our study aimed to evaluate heavy metal prevalence in stools from coastal and highland Indonesian populations and discern its potential effect on gut microbiome. We detected copper (Cu), barium (Ba), manganese (Mn), and zinc (Zn) in fecal samples, with notable concern regarding barium contamination (13 of 20 participants), known for its adverse health impacts. Genes linked to heavy metal resistance were widely distributed in both populations' stool samples, including znuC, nikE, modC, mntH, and arsB. Copper levels correlated negatively with Prevotella abundance, suggesting inhibition of its growth, while barium levels correlated positively with Prevotella, Faecalibacterium, and Ruminococcus abundance, indicating an antagonistic Ba-Cu relationship in shaping the microbiome.
  Keywords: heavy metals; barium; metal resistance genes; gut microbiome.
  DOI: 10.1504/IJEP.2024.10065024
   
  
• Peak carbon emission prediction of tourist attractions based on fuzzy support vector machine  
  by Xiumei Feng 
  Abstract: In order to address the issues of low stability, low sensitivity, and low accuracy in traditional peak carbon emission prediction methods, a peak carbon emission prediction of tourist attractions based on fuzzy support vector machine is proposed. Tourist attraction carbon emission data is collected, and various factors such as average emission, total emission, and growth rate are obtained through statistical analysis. By combining Pearson correlation coefficient and information gain, the interrelationships between various factors are determined, clarifying the key influencing factors of tourist attraction carbon emissions. Key influencing factors such as number of consumers, transportation mode, energy utilization, and tourist behavior are taken as input vectors, and carbon emission peaks are taken as output vectors to construct an optimized fuzzy support vector machine, obtaining relevant prediction results. The experimental results demonstrate that this method has high stability, sensitivity, and accuracy, enabling precise prediction of tourist attraction carbon emission peaks
  Keywords: fuzzy support vector machine; tourist attractions; carbon emissions; prediction; Pearson correlation coefficient.
  DOI: 10.1504/IJEP.2024.10065073
   
  
• Optimisation method for atmospheric environment pollution monitoring site selection based on improved genetic algorithm  
  by Bo Yang 
  Abstract: There are some problems in traditional atmospheric environment pollution monitoring point optimization method, such as low spatial coverage rate, long task completion time and high construction cost. Therefore, an optimisation method for atmospheric environment pollution monitoring site setting based on improved genetic algorithm is proposed. The dynamic response of atmospheric environment pollution monitoring network structure is analysed, and candidate monitoring site setting are screened. Considering the objectives of maximum closeness, maximum concentration, construction cost, population and spatial coverage, the objective function of atmospheric environment pollution monitoring point optimization is built. The objective function is solved by using the improved genetic algorithm, and the optimal solution is the monitoring point optimisation result. Experimental results show that the maximum spatial coverage of this method is 99.6%, the task completion time fluctuates between 0.21s and 0.62s, and the total cost is 1.589
  Keywords: improved genetic algorithm; atmospheric environment; pollution monitoring; monitoring site selection; objective function.
  DOI: 10.1504/IJEP.2024.10065374
   
  
• A comprehensive evaluation method for environmental pollution in tourist attractions based on improved principal component analysis  
  by Jingjing Yan 
  Abstract: In order to solve the problem of low reliability of current environmental pollution assessment methods, a comprehensive assessment method of environmental pollution in tourist scenic spots based on improved principal component analysis was proposed. First, collect air, water and soil pollution data of tourist attractions. Then, the original pollution data is cleaned, and the data clustering method is used to classify the pollution data, and the comprehensive evaluation index system of environmental pollution in tourist attractions is established. Finally, the entropy method is used to calculate the evaluation values of various indicators, and the comprehensive evaluation results of pollution in tourist attractions are obtained. The experimental results show that the correlation of the evaluation index is always controlled above 0.90, and the convergence rate of the method is fast, and the optimal solution can be approached within 150 iterations, and the application effect is good.
  Keywords: tourist attractions; comprehensive evaluation of pollution; principal component analysis; weighted assignment.
  DOI: 10.1504/IJEP.2024.10065395