Forthcoming and Online First Articles

International Journal of Environment and Pollution

International Journal of Environment and Pollution (IJEP)

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International Journal of Environment and Pollution (12 papers in press)

Regular Issues

  • Coordinated scheduling of photovoltaic greenhouse energy based on PBFT consensus mechanism   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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
     
  • Optimisation of the energy consumption in activated sludge treatment plants using simulation model   Order a copy of this article
    by Souad Zairi, Boumediene Meddah, Miloud Slimani 
    Abstract: This article aims to illustrate how modelling can be used to optimise energy consumption in a large wastewater treatment plant located in Saida, Algeria. An aeration control strategy is proposed to regulate the operation of surface aerators. The study involves implementing aeration control in the WEST software platform and analysing the impact of its implementation in terms of energy consumption reduction. Dynamic simulations were carried out using the activated sludge model (ASM2dModTemp), calibrated and validated with real operating data. The results show that aeration represents 51% of the total energy required in a wastewater treatment plant. The control approach used maintains treatment effectiveness and produces excellent effluent quality. Significant reductions were achieved, including 93% for oxygen demand, 98% for suspended solids, 20% for total phosphorus, and 98% for ammonium levels. This approach successfully reduced energy consumption by 26% within a month of implementation on a processing line.
    Keywords: energy consumption; wastewater treatment plant; WWTP; aeration control strategy; activated sludge model; ASM2dModTemp; dynamic simulations.
    DOI: 10.1504/IJEP.2024.10065791
     
  • Modelling citizen participation in apathetic urban communities: suggestions based on Nairobis urban solid waste related flood risk management practices   Order a copy of this article
    by Janes Odongo, Boqian Zhang, Donghui Ma 
    Abstract: As cities grow, they become more complex and challenging to govern. Citizens and stakeholders contribute to shaping this complexity through their actions and inactions. Consequently, the United Nations recognises the need for wholesome stakeholder participation in governance and calls upon cities to implement this in their policies and programmes. Despite this call to action, stakeholders often display apathy towards their neighbourhoods, leading to pollution and the prevalence of avoidable disasters, including urban flooding. To facilitate a deeper understanding of and address this issue, we conducted this descriptive study in Nairobi, guided by the theory of participatory urban governance. The study was conducted through a comprehensive research methodology, including literature review and primary data collection from structured questionnaires, Key Informant Interviews, Observation and mapwork. It describes prevailing stakeholder participation dynamics, the resulting challenges to solid waste and flood risk management, and designs a technology-led prospective stakeholder participation model that can aid sustainable urban solid waste and related flood risk management. The design of these instruments was guided by a call by 88.89% of sampled respondents who said that traders
    Keywords: participatory urban governance; stakeholder apathy; solid waste management; flood risk management; sustainable urbanism; Nairobi.
    DOI: 10.1504/IJEP.2024.10066038
     
  • Determinants of CO2 emissions in ASEAN: a quantitative research on the role of tourism   Order a copy of this article
    by Ly Hoang Phu, Vo Huyen Bao Anh, Pham Ngoc Trang, Ha Anh Thao, Pham Hong Nhung 
    Abstract: CO2 is a greenhouse gas capable of absorbing and retaining temperature in the atmosphere. As CO2 emissions increase, the amount of greenhouse gases in the atmosphere also increases, leading to the greenhouse effect and increasing the average temperature of the Earth. An increase in Earth's average temperature can lead to serious consequences such as climate change, global warming, rising sea levels, loss of biodiversity, economic impacts, and human health. The study explores the factors affecting CO2 emissions in ASEAN countries, including Brunei, Cambodia, Laos, Indonesia, Malaysia, Myanmar, Philippines, Singapore, Thailand, and Vietnam in the period 2012 - 2017. OLS linear regression analysis method is used to analyze the relationship between factors affecting CO2 emissions. This study uses the random effects model REM to analyze panel data. Secondary data after being screened and aggregated from the World Bank, will be processed by Stata software. Research shows that GDP per capita, fossil fuel consumption, trade openness, total household spending, and tourism revenue exert a positive impact on CO2 emissions.
    Keywords: CO2 emissions; ASEAN; tourism.
    DOI: 10.1504/IJEP.2024.10066639
     
  • Novel determination method for chemical oxygen demand in water based on sulfate radical digestion and turbidimetry   Order a copy of this article
    by Fukang Ji, Yongxiang Li, Xinbo Zhang, Fengyi Zhao, Mengdi Zhang, Juncheng Wang, Xiaofang Sun 
    Abstract: Sulphate radical-based advanced oxidation processes (SR-AOPs) have gained considerable popularity in the fields of organic contaminant degradation and industrial wastewater treatment. However, there are few reports focusing on study and application of such promising technology in determination or online monitoring of chemical oxygen demand (COD) in water quality. Herein, a novel determination method of COD based on photoactivated SR-AOPs and barium sulphate turbidimetry was proposed, in which, sulphate radicals (SO4) are mainly responsible for the digestion of organic pollutants, not hydroxyl radicals (OH). For improving the precision and accuracy of this determination method, all the parameters affecting on the digestion and detection were investigated. Performance verification results showed that this method has a good linearity (R2 = 0.9988), precision (2.26%), accuracy (0.43%) and low method detection limit (2.4431 mg/L) within a range of 5~200 mg/L, under the optimised process conditions.
    Keywords: chemical oxygen demand; determination method; sulphate radical; turbidimetry.
    DOI: 10.1504/IJEP.2024.10066640