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  • RESEARCH ARTICLE
    Pengxiao Zhou, Zhong Li, Yimei Zhang, Spencer Snowling, Jacob Barclay
    Frontiers of Environmental Science & Engineering, 2023, 17(12): 152. https://doi.org/10.1007/s11783-023-1752-7

    ● Online learning models accurately predict influent flow rate at wastewater plants.

    ● Models adapt to changing input-output relationships and are friendly to large data.

    ● Online learning models outperform conventional batch learning models.

    ● An optimal prediction strategy is identified through uncertainty analysis.

    ● The proposed models provide support for coping with emergencies like COVID-19.

    Accurate influent flow rate prediction is important for operators and managers at wastewater treatment plants (WWTPs), as it is closely related to wastewater characteristics such as biochemical oxygen demand (BOD), total suspend solids (TSS), and pH. Previous studies have been conducted to predict influent flow rate, and it was proved that data-driven models are effective tools. However, most of these studies have focused on batch learning, which is inadequate for wastewater prediction in the era of COVID-19 as the influent pattern changed significantly. Online learning, which has distinct advantages of dealing with stream data, large data set, and changing data pattern, has a potential to address this issue. In this study, the performance of conventional batch learning models Random Forest (RF), K-Nearest Neighbors (KNN), and Multi-Layer Perceptron (MLP), and their respective online learning models Adaptive Random Forest (aRF), Adaptive K-Nearest Neighbors (aKNN), and Adaptive Multi-Layer Perceptron (aMLP), were compared for predicting influent flow rate at two Canadian WWTPs. Online learning models achieved the highest R2, the lowest MAPE, and the lowest RMSE compared to conventional batch learning models in all scenarios. The R2 values on testing data set for 24-h ahead prediction of the aRF, aKNN, and aMLP at Plant A were 0.90, 0.73, and 0.87, respectively; these values at Plant B were 0.75, 0.78, and 0.56, respectively. The proposed online learning models are effective in making reliable predictions under changing data patterns, and they are efficient in dealing with continuous and large influent data streams. They can be used to provide robust decision support for wastewater treatment and management in the changing era of COVID-19 and also under other unprecedented emergencies that could change influent patterns.

  • REVIEW ARTICLE
    Zhiguo Su, Lyujun Chen, Donghui Wen
    Frontiers of Environmental Science & Engineering, 2024, 18(3): 36. https://doi.org/10.1007/s11783-024-1796-3

    ● Impact of WWTP effluent discharge on ARGs in downstream waterbodies is hotspot.

    ● Various mechanisms influence the diffusion of ARGs in effluent-receiving waterbodies.

    ● Controlling AMR risk of WWTPs needs further investigation and management strategies.

    Antimicrobial resistance (AMR) has emerged as a significant challenge in human health. Wastewater treatment plants (WWTPs), acting as a link between human activities and the environment, create ideal conditions for the selection and spread of antibiotic resistance genes (ARGs) and antibiotic-resistant bacteria (ARB). Unfortunately, current treatment processes are ineffective in removing ARGs, resulting in the release of large quantities of ARB and ARGs into the aquatic environment through WWTP effluents. This, in turn, leads to their dispersion and potential transmission to human through water and the food chain. To safeguard human and environmental health, it is crucial to comprehend the mechanisms by which WWTP effluent discharge influences the distribution and diffusion of ARGs in downstream waterbodies. In this study, we examine the latest researches on the antibiotic resistome in various waterbodies that have been exposed to WWTP effluent, highlighting the key influencing mechanisms. Furthermore, recommendations for future research and management strategies to control the dissemination of ARGs from WWTPs to the environment are provided, with the aim to achieve the “One Health” objective.

  • REVIEW ARTICLE
    Shuting Zhuang, Jianlong Wang
    Frontiers of Environmental Science & Engineering, 2024, 18(3): 38. https://doi.org/10.1007/s11783-024-1798-1

    ● Removal of cesium from radioactive wastewater is still a challenging.

    ● Main approaches used for waste treatment in Fukushima Daiichi accident were reviewed.

    ● Kurion/SARRY system + desalination system and ALPS were briefly introduced.

    ● The removal of cesium by adsorption and membrane separation were summarized.

    Radiocesium is frequently present in radioactive wastewater, while its removal is still a challenge due to its small hydrated radius, high diffusion coefficient, and similar chemical behavior to other alkali metal elements with high background concentrations. This review summarized and analyzed the recent advances in the removal of Cs+ from aqueous solutions, with a particular focus on adsorption and membrane separation methods. Various inorganic, organic, and biological adsorbents have undergone assessments to determine their efficacy in the removal of cesium ions. Additionally, membrane-based separation techniques, including reverse osmosis, forward osmosis, and membrane distillation, have also shown promise in effectively separating cesium ions from radioactive wastewater. Additionally, this review summarized the main approaches, including Kurion/SARRY system + desalination system and advanced liquid processing system, implemented after the Fukushima Daiichi nuclear power plant accident in Japan to remove radionuclides from contaminated water. Adsorption technology and membrane separation technology play a vital role in treatment of contaminated water.

  • RESEARCH ARTICLE
    Min Cheng, Zhiyuan Zhang, Shihui Wang, Kexin Bi, Kong-qiu Hu, Zhongde Dai, Yiyang Dai, Chong Liu, Li Zhou, Xu Ji, Wei-qun Shi
    Frontiers of Environmental Science & Engineering, 2023, 17(12): 148. https://doi.org/10.1007/s11783-023-1748-3

    ● Screened 8862 metal-organic frameworks for I2 capture via molecular simulation.

    ● Ranked metal-organic frameworks on predicted I2 uptake and identified Top 10.

    ● Established quantitative structure-property relationships via machine learning.

    We performed large-scale molecular simulation to screen and identify metal-organic framework materials for gaseous iodine capture, as part of our ongoing effort in addressing management and handling issues of various radionuclides in the grand scheme of spent nuclear fuel reprocessing. Starting from the computation-ready experimental (CoRE) metal-organic frameworks (MOFs) database, grand canonical Monte Carlo simulation was employed to predict the iodine uptake values of the MOFs. A ranking list of MOFs based on their iodine uptake capabilities was generated, with the Top 10 candidates identified and their respective adsorption sites visualized. Subsequently, machine learning was used to establish structure-property relationships to correlate MOFs’ various structural and chemical features with their corresponding performances in iodine capture, yielding interpretable common features and design rules for viable MOF adsorbents. The research strategy and framework of the present study could aid the development of high-performing MOF adsorbents for capture and recovery of radioactive iodine, and moreover, other volatile environmentally hazardous species.

  • RESEARCH ARTICLE
    Yue Yang, Ze Fu, Qi Zhang
    Frontiers of Environmental Science & Engineering, 2024, 18(2): 15. https://doi.org/10.1007/s11783-024-1775-8

    ● A protocol is proposed for simultaneous oil/water separation and electricity generation.

    ● Oil/water separation efficiency achieves > 99% only out of solar energy.

    ● A derived extra electricity power of ~0.1 W/m2 is obtained under solar radiation.

    ● The protocol offers a prospect of solar-driven water treatment and resource recovery.

    Oily wastewater from ocean oil spills endangers marine ecosystems and human health. Therefore, developing an effective and sustainable solution for separating oil-water mixtures is urgent. Interfacial solar photothermal evaporation is a promising approach for the complete separation of two-phase mixtures using only solar energy. Herein, we report a carbonized wood-based absorber with Janus structure of comprising a hydrophobic top-layer and an oleophobic bottom-layer for simultaneous solar-driven oil-water separation and electricity generation. Under sunlight irradiation, the rapid evaporation of seawater will induce a separation of oil-water mixtures, and cause a high salt concentration region underlying the interface, while the bottom “bulk water” maintains in a low salt concentration, thus forming a salinity gradient. Electricity can be generated by salinity gradient power. Therefore, oil-water separation efficiency of > 99% and derived extra electricity power of ~0.1 W/m2 is achieved under solar radiation, demonstrating the feasibility of oil-water separation and electricity production synchronously directly using solar energy. This work provides a green and cost-effective path for the separation of oil-water mixtures.

  • REVIEW ARTICLE
    Yanpeng Huang, Chao Wang, Yuanhao Wang, Guangfeng Lyu, Sijie Lin, Weijiang Liu, Haobo Niu, Qing Hu
    Frontiers of Environmental Science & Engineering, 2024, 18(3): 29. https://doi.org/10.1007/s11783-024-1789-2

    ● The application of ML in groundwater quality assessment and prediction is reviewed.

    ● Bibliometric analysis is performed and summarized to promote application.

    ● The details of the application of ML in GQAP are comprehensively summarized.

    ● Challenges and opportunities of using ML models in GQAP are discussed.

    Groundwater quality assessment and prediction (GQAP) is vital for protecting groundwater resources. Traditional GQAP methods can not adequately capture the complex relationships among attributes and have the disadvantage of being computationally demanding. Recently, the application of machine learning (ML) in GAQP (GQAPxML) has been widely studied due to ML’s reliability and efficiency. While many GQAPxML publications exist, a thorough review is missing. This review provides a comprehensive summary of the development of ML applications in the field of GQAP. First, the workflow of ML modeling is briefly introduced, as are data preparation, model development, model evaluation, and model application. Second, 299 publications related to the topic are filtered, mainly through ML modeling. Subsequently, many aspects of GQAPxML, such as publication trends, the spatial distribution of study areas, the size of data sets, and ML algorithms, are discussed from a bibliometric perspective. In addition, we review in detail the well-established applications and recent findings for several subtopics, including groundwater quality assessment, groundwater quality modeling using groundwater quality parameters, groundwater quality spatial mapping, probability estimation of exceeding the groundwater quality threshold, groundwater quality temporal prediction, and the hybrid use of ML and physics-based models. Finally, the development of GQAPxML is explored from three perspectives: data collection and preprocessing, model building and evaluation, and the broadening of model applications. This review provides a reference for environmental scientists to better understand GQAPxML and promotes the development of innovative methods and improvements in modeling quality.

  • PREFACE
    Jiuhui Qu, Jiming Hao, Yi Qian
    Frontiers of Environmental Science & Engineering, 2024, 18(6): 66. https://doi.org/10.1007/s11783-024-1826-1
  • RESEARCH ARTICLE
    Wiley Helm, Shifa Zhong, Elliot Reid, Thomas Igou, Yongsheng Chen
    Frontiers of Environmental Science & Engineering, 2024, 18(2): 17. https://doi.org/10.1007/s11783-024-1777-6

    ● A machine learning approach was applied to predict free chlorine residuals.

    ● Annual data were obtained from chlorination unit at a 98 MGD water treatment plant.

    ● The last model iteration returned a high prediction value ( R 2 = 0.937).

    ● Non-intuitive parameters were found to be highly significant to predictions.

    Chlorine-based disinfection is ubiquitous in conventional drinking water treatment (DWT) and serves to mitigate threats of acute microbial disease caused by pathogens that may be present in source water. An important index of disinfection efficiency is the free chlorine residual (FCR), a regulated disinfection parameter in the US that indirectly measures disinfectant power for prevention of microbial recontamination during DWT and distribution. This work demonstrates how machine learning (ML) can be implemented to improve FCR forecasting when supplied with water quality data from a real, full-scale chlorine disinfection system in Georgia, USA. More precisely, a gradient-boosting ML method (CatBoost) was developed from a full year of DWT plant-generated chlorine disinfection data, including water quality parameters (e.g., temperature, turbidity, pH) and operational process data (e.g., flowrates), to predict FCR. Four gradient-boosting models were implemented, with the highest performance achieving a coefficient of determination, R2, of 0.937. Values that provide explanations using Shapley’s additive method were used to interpret the model’s results, uncovering that standard DWT operating parameters, although non-intuitive and theoretically non-causal, vastly improved prediction performance. These results provide a base case for data-driven DWT disinfection supervision and suggest process monitoring methods to provide better information to plant operators for implementation of safe chlorine dosing to maintain optimum FCR.

  • RESEARCH ARTICLE
    Hong Yu, Beidou Xi, Lingling Shi, Wenbing Tan
    Frontiers of Environmental Science & Engineering, 2023, 17(12): 153. https://doi.org/10.1007/s11783-023-1753-6

    ● Microplastics (MPs) decreased the protein/amino sugars and increased the lipids.

    ● MPs conferred a lower DOM aromaticity and a higher lability.

    ● The larger amount of MPs, the more inhibited humification degree of DOM.

    Chemodiversity of dissolved organic matter (DOM) is a crucial factor controlling soil nutrient availability, greenhouse gas emissions, and pollutant migration. Microplastics (MPs) are widespread pollutants in terrestrial ecosystems in many regions. However, the effects of MPs on DOM chemodiversity are not sufficiently understood, particularly under different types of polymers. Using UV–Vis spectroscopy, 3D fluorescence spectroscopy, and Fourier-transform ion cyclotron resonance mass spectrometry, the effects of three prevalent MPs [polyethylene, polystyrene, and polyvinyl chloride (PVC)] on the chemical properties and composition of soil DOM were investigated via a 310-d soil incubation experiment. The results showed that MPs reduced the aromatic and hydrophobic soil DOM components by more than 20%, with PVC MPs having the greatest effect. Furthermore, as MP contents increase, the humification level of soil DOM significantly decreases. MPs increased DOM molecules with no heteroatom by 8.3%–14.0%, but decreased DOM molecules with nitrogen content by 17.0%–47.8%. This may be because MPs cause positive “priming effect,” resulting in the breakdown of bioavailable components in soil DOM. This is also related to MPs changing microbial richness and diversity and enriching microbial communities involved in lignin compositions degradation. In the presence of MPs, soil DOM chemodiversity depended on soil pH, electrical conductivity, dissolved organic carbon, soil organic matter, bacterial Shannon, and fungal Chao index. Specifically, DOM in MP-contaminated soils featured more lipids and less condensed aromatics and proteins/amino sugars, thereby conferring a lower DOM aromaticity and higher lability.

  • PERSPECTIVES
    Yisheng Shao, Yijian Xu
    Frontiers of Environmental Science & Engineering, 2023, 17(12): 156. https://doi.org/10.1007/s11783-023-1756-3

    ● Urban water systems are challenged by climate change.

    ● Proactive adaptation and positive mitigation were proposed as the coping strategies.

    ● Proactive adaptation is to enhance the resilience of urban water systems.

    ● Positive mitigation is to strengthen the energy conservation and carbon reduction.

    Urban water systems are facing various challenges against climate change, impacting cities’ security and their sustainable development. Specifically, there are three major challenges: submersion risk of coastal cities as glaciers melt and sea level rises, more and severe urban flooding caused by extreme weather like intensified storm surge and heavy precipitation, and regional water resource patterns challenged by alteration of spatial distribution of precipitation. Regarding this, two strategies including proactive adaptation and positive mitigation were proposed in this article to realize the reconstruction and optimization of urban water systems, to enhance their resilience, and eventually increase their adaptability and coping ability to climate change. The proactive adaptation strategy consists of 1) construction of sponge cities to accommodate the increased regular rainfall and to balance the alterations of spatial redistribution of precipitation; 2) reconstruction of excess stormwater discharge and detention system to increase capability for extreme precipitation events based on flood risk assessment under future climate change; 3) deployment of forward-looking, ecological, and integrated measures to improve coastal protection capability against inundation risks caused by climate change and sea level rise. The positive mitigation strategy is to employ the systematic concept in planning and design and to adopt advanced applicable energy-saving technologies, processes, and management practices, aiming at reduction in flux of urban water systems, reinforcement in energy conservation and carbon reduction in both water supply systems and wastewater treatment systems, and thus a reduction of greenhouse gas emission from urban water systems.

  • REVIEW ARTICLE
    Xingyue Chen, Peng Zhang, Yang Wang, Wei Peng, Zhifeng Ren, Yihong Li, Baoshuai Chu, Qiang Zhu
    Frontiers of Environmental Science & Engineering, 2023, 17(12): 149. https://doi.org/10.1007/s11783-023-1749-2

    ● Up-to-date information on the preparation of zeolite from CFA were summarized.

    ● The applications of CFA zeolites in environmental protection field were reviewed.

    ● The feasibility analysis of industrial production of CFA zeolites were discussed.

    The by-product of coal combustion, coal fly ash (CFA), has become one of the world’s most emitted solid wastes, and bulk utilization while achieving high value-added products is the focus of current research. Using CFA to prepare zeolite cannot only reduce environmental pressure, but also obtain high value-added products, which has a good market prospect. In this paper, the research progress of hydrothermal synthesis method of CFA zeolites is reviewed in detail and summarized several other synthetic methods of CFA zeolites. This review also presents an overview of CFA zeolites application in environmental applications like water treatment, gas adsorption and soil remediation. However, a considerable number of literature data have documented using CFA zeolites for water treatment, whereas research on CFA zeolites application to gas adsorption and soil remediation is still limited. In addition, the current status of basic research on the industrial production of CFA zeolites is briefly summarized, and the development trend of the synthetic zeolite of CFA is prospected. After the feasibility analysis of the industrial production of CFA zeolite, it is concluded that the only two methods with high feasibility for industrial application are two-step hydrothermal and alkali melting methods, and the industrial production technology still needs to be studied in depth.

  • RESEARCH ARTICLE
    Xinrui Yuan, Kangping Cui, Yihan Chen, Shiyang Wu, Yao Zhang, Tong Liu
    Frontiers of Environmental Science & Engineering, 2023, 17(12): 154. https://doi.org/10.1007/s11783-023-1754-5

    ● Co-occurrence of SMX and Gd(III) enhances HGT of ARGs and MRGs.

    ● Gd(III) alone negatively impacts ARGs and MRGs proliferation and spread.

    Streptomyces , Pseudomonas and Thauera were abundant in the presence of SMX.

    ● A positive correlation between internal ARGs and MGEs.

    With the increasing use of antibiotics and rare earth elements (REE) during the coronavirus disease (COVID-19) pandemic, the co-occurrence of sulfamethoxazole (SMX) and gadolinium (Gd) has increased in wastewater treatment plants (WWTPs). However, the effects of SMX and Gd exposure on the transmission of antibiotic resistance genes (ARGs) and heavy metal resistance genes (MRGs) remain unknown. This study investigated the impacts of SMX and Gd on the fate of ARGs and MRGs in an activated sludge system. The diversity and relative abundance of ARGs, MRGs, and mobile genetic elements (MGEs) were detected by metagenomic sequencing. The results revealed an increased abundance of ARGs but a decreased abundance of MRGs under the joint effect of SMX and Gd. In addition, Gd alone exerted adverse effects on the proliferation and spread of ARGs and MRGs. However, SMX alone resulted in an increase in the diversity of ARGs and MRGs and promoted the growth of Pseudomonas, Thauera, and Streptomyces in the activated sludge system. Interestingly, a positive correlation was observed between most ARGs and MGEs. These findings provide comprehensive insights into the effects of co-occurring REEs and antibiotics on the fate of ARGs, MRGs, and MGEs, providing evidence to assist in controlling the spread and proliferation of ARGs and MRGs in activated sludge systems.

  • PERSPECTIVES
    Hui Huang, Rui Ma, Hongqiang Ren
    Frontiers of Environmental Science & Engineering, 2024, 18(6): 72. https://doi.org/10.1007/s11783-024-1832-3

    ● Wastewater treatment targets and processes change with demands.

    ● Research hotspots in wastewater treatment were described using bibliometrics.

    ● Five pathways for technology development were proposed.

    ● Material genetics, synthetic biology, artificial intelligence were highlighted.

    The “dual-carbon” strategy promotes the development of the wastewater treatment sector and is an important tool for leading science and technology innovations. Based on the global climate change and the new policies introduced by China, this paper described the new needs for the development of wastewater treatment science and technology. It offered a retrospective analysis of the historical trajectory of scientific and technological advancements in this field. Utilizing bibliometrics, it delineated the research hotspots within wastewater treatment, notably highlighting materials genomics, artificial intelligence, and synthetic biology. Furthermore, it posited that, in the future, the field of wastewater treatment should follow the paths of technological innovations with multi-dimensional needs, such as carbon reduction, pollution reduction, health, standardisation, and intellectualisation. The purpose of this paper was to provide references and suggestions for scientific and technological innovations in the field of wastewater treatment, and to contribute to the common endeavor of moving toward a Pollution-Free Planet.

  • OPINIONS
    Chengjun Li, Riqing Yu, Wenjing Ning, Huan Zhong, Christian Sonne
    Frontiers of Environmental Science & Engineering, 2024, 18(3): 39. https://doi.org/10.1007/s11783-024-1799-0
  • REVIEW ARTICLE
    Shan-Shan Yang, Wei-Min Wu, Federica Bertocchini, Mark Eric Benbow, Suja P. Devipriya, Hyung Joon Cha, Bo-Yu Peng, Meng-Qi Ding, Lei He, Mei-Xi Li, Chen-Hao Cui, Shao-Nan Shi, Han-Jun Sun, Ji-Wei Pang, Defu He, Yalei Zhang, Jun Yang, Deyi Hou, De-Feng Xing, Nan-Qi Ren, Jie Ding, Craig S. Criddle
    Frontiers of Environmental Science & Engineering, 2024, 18(6): 78. https://doi.org/10.1007/s11783-024-1838-x

    ● Insect damaging and penetrating plastic materials has been observed since 1950s.

    ● Biodegradation of plastics by insects has become hot research frontiers.

    ● All major plastics can be biodegraded with half-live on hourly basis.

    ● The biodegradation is performed by the insect hosts together with gut microbiota.

    ● Future perspectives focus on biodegradation mechanisms and potential applications.

    Insects damaging and penetrating plastic packaged materials has been reported since the 1950s. Radical innovation breakthroughs of plastic biodegradation have been initiated since the discovery of biodegradation of plastics by Tenebrio molitor larvae in 2015 followed by Galleria mellonella in 2017. Here we review updated studies on the insect-mediated biodegradation of plastics. Plastic biodegradation by insect larvae, mainly by some species of darkling beetles (Tenebrionidae) and pyralid moths (Pyralidae) is currently a highly active and potentially transformative area of research. Over the past eight years, publications have increased explosively, including discoveries of the ability of different insect species to biodegrade plastics, biodegradation performance, and the contribution of host and microbiomes, impacts of polymer types and their physic-chemical properties, and responsible enzymes secreted by the host and gut microbes. To date, almost all major plastics including polyethylene (PE), polypropylene (PP), polyvinyl chloride (PVC), polyethylene terephthalate (PET), polyurethane (PUR), and polystyrene (PS) can be biodegraded by T. molitor and ten other insect species representing the Tenebrionidae and Pyralidae families. The biodegradation processes are symbiotic reactions or performed by synergistic efforts of both host and gut-microbes to rapidly depolymerize and biodegrade plastics with hourly half-lives. The digestive ezymens and bioreagents screted by the insects play an essential role in plasatic biodegradation in certain species of Tenebrionidae and Pyralidae families. New research on the insect itself, gut microbiomes, transcriptomes, proteomes and metabolomes has evaluated the mechanisms of plastic biodegradation in insects. We conclude this review by discussing future research perspectives on insect-mediated biodegradation of plastics.

  • PERSPECTIVES
    Tong Zhu, Yingjun Liu, Shunqing Xu, Guanghui Dong, Cunrui Huang, Nan Sang, Yunhui Zhang, Guanyong Su, Jingwen Chen, Jicheng Gong, Guohua Qin, Xinghua Qiu, Jing Shang, Haobo Wang, Pengpeng Wang, Mei Zheng
    Frontiers of Environmental Science & Engineering, 2024, 18(6): 76. https://doi.org/10.1007/s11783-024-1836-z

    ● Environmental health research has surged in China over the past decade

    ● The scope extends beyond health effects of classic pollutants to include those of emerging pollutants and climate change

    ● Future research priorities and opportunities are proposed

    Environmental health research aims to identify environmental conditions suitable for the healthy living and reproduction of human beings. Through the interdisciplinary research bridging environmental sciences and health/medical sciences, the impacts of physical, chemical, and biological environmental factors on human health are investigated. This includes identifying environmental factors detrimental to human health, evaluating human exposure characteristics to environmental factors, clarifying causal relationships between environmental exposure and health effects, analyzing the underlying biochemical mechanisms, linking environmental factors to the onset and progression of diseases, establishing exposure-response relationships, and determining effect thresholds. Ultimately, the results of environmental health research can serve as a scientific basis for formulating environmental management strategies and guiding prevention and intervention measures at both the public and individual levels. This paper summarizes the recent advances and future perspectives of environmental health research in China, as reported by a group of Chinese scientists who recently attended a workshop in Hainan, China. While it is not intended to provide a comprehensive review of this expansive field, it offers a glimpse into the significant progress made in understanding the health impacts of environmental factors over the past decade. Looking ahead, it is imperative not only to sustain efforts in studying the health effects of traditional environmental pollution, but also to prioritize research on the health impacts of emerging pollutants and climate change.

  • REVIEW ARTICLE
    Manshu Zhao, Xinhua Wang, Shuguang Wang, Mingming Gao
    Frontiers of Environmental Science & Engineering, 2024, 18(1): 1. https://doi.org/10.1007/s11783-024-1761-1

    ● Cr self-catalysis behaviors during Cr-initiated AOPs were described.

    ● Cr transformation in AOPs-based synergistic systems was reviewed.

    ● Discussed detection methods for active species related to Cr-initiated AOPs systems.

    ● This review provided insights into Cr self-catalysis and its applications.

    Chromium (Cr), as a transition metal material with multiple redox states, has exhibited the catalysis toward Fenton-like reactions over a wide pH range. Although it is not sensible to add Cr reagents as catalysts due to its toxicity, it is highly promising to remediate Cr-containing wastewater through Cr-initiated advanced oxidation processes (Cr-initiated AOPs), which are clean and low-cost. Moreover, the widely concerned Cr-complexes, considered as obstacles in the remediation process, can be effectively destroyed by AOPs. Cr self-catalysis is defined as Cr species is both substrate and catalyst. However, the full understanding of Cr self-catalysis, including the generation of intermediates Cr(IV)/Cr(V), the synergetic effects with co-existing ions, and the accumulation of toxic Cr(VI), remains a challenge for the practical application of Cr-initiated AOPs. In this review, relevant researches on Cr self-catalysis during Cr-initiated AOPs are summarized. Specifically, the Cr-Fenton-like reaction, Cr substituted materials, and Cr-sulfite reactions are explored as key mechanisms contributing to Cr self-catalysis. Moreover, Cr transformation processes, including synchronously Cr removal, Cr redox reactions, and Cr(VI) accumulation, in AOPs-based synergistic systems are systematically analyzed. Detailed approaches for the detection of active species in AOPs-based systems are also presented. The primary objective of this review is to explore the application of AOPs for Cr-containing wastewater remediation based on Cr self-catalysis, and provide fundamental insights and valuable information for future research on Cr-initiated AOPs.

  • RESEARCH ARTICLE
    Di Liu, Yan Wang, Tianrong He, Deliang Yin, Shouyang He, Xian Zhou, Yiyuan Xu, Enxin Liu
    Frontiers of Environmental Science & Engineering, 2023, 17(12): 145. https://doi.org/10.1007/s11783-023-1745-6

    ● AOM input elevates water-soluble cysteine and labile DOM fractions in soil.

    ● AOM input fuels potential Hg methylators and non-Hg methylators in soil.

    ● Decayed algal aggregate is Hg methylating “hotspot” and MeHg source in soil.

    ● AOM-driven SDOM variations elevate soil MeHg production and bioaccumulation in rice.

    Algal-derived organic matter (AOM) regulates methylmercury (MeHg) fate in aquatic ecosystems, whereas its role in MeHg production and bioaccumulation in Hg-contaminated paddies is unclear. Pot and microcosm experiments were thus performed to understand the response characteristics of MeHg concentrations in soil and rice in different rice-growing periods to algal decomposition. Compared to the control, algal decomposition significantly increased soil water-soluble cysteine concentrations during the rice-tillering and grain-filling periods (P < 0.05). It also significantly lowered the molecular weight of soil-dissolved organic matter (SDOM) during the rice-tillering period (P < 0.05) and SDOM humification/aromaticity during the grain-filling period. Compared to the control, AOM input increased the abundance of potential Hg and non-Hg methylators in soil. Furthermore, it also greatly increased soil MeHg concentrations by 25.6%–80.2% and 12.6%–66.1% during the rice-tillering and grain-filling periods, with an average of 42.25% and 38.42%, respectively, which were significantly related to the elevated cysteine in soil and the decrease in SDOM molecular weight (P < 0.01). In the early stage (within 10 days of microcosm experiments), the MeHg concentrations in decayed algal particles showed a great decrease (P < 0.01), suggesting a potential MeHg source in soil. Ultimately, algal decomposition greatly increased the MeHg concentrations and bioaccumulation factors in rice grains, by 72.30% and 16.77%, respectively. Overall, algal decomposition in Hg-contaminated paddies is a non-negligible factor promoting MeHg accumulation in soil-rice systems.

  • REVIEW ARTICLE
    Xiaolong Yao, Kuan Wan, Wenxin Yu, Zheng Liu
    Frontiers of Environmental Science & Engineering, 2024, 18(9): 110. https://doi.org/10.1007/s11783-024-1870-x

    ● Water vapor’s effect on VOC adsorption in various porous carbons was investigated.

    ● How adsorbent and adsorbate properties affect moist VOC adsorption was studied.

    ● The challenges of using carbon materials for moist VOC adsorption were addressed.

    ● Theoretical and technical guidance on efficiently purifying moist VOC gases is given.

    Volatile organic compounds (VOC) have been proven to cause considerable harm to both the ecological environment and human health. Anthropogenic VOC emissions are primarily generated by the industrial sector. The utilization of porous carbon as an adsorbent has emerged as an effective method for the efficient removal of VOC from industrial sources. However, during the actual production processes, VOC exhaust gases are often mixed with water vapor, which poses challenges for adsorption purification. This review provides a comprehensive overview of the remarkable advancements in various carbon materials in terms of their ability to adsorb both VOC and water vapor. Additionally, it systematically summarizes the influence of surface groups on adsorbents and the molecular properties of VOC on their adsorption by carbon materials. Furthermore, this review introduces the mechanism underlying adsorption-adsorbent interactions and discusses the construction of models for adsorbing water vapor and VOC. The challenges associated with the application of carbon materials for VOC adsorption in humid environments are also addressed. This review aims to offer theoretical and technical guidance for the effective purification of moist VOC waste gases emitted from industrial sources, thereby achieving precise control of VOC emissions.

  • RESEARCH ARTICLE
    Xin Tang, Yin Ye, Chunlin Wang, Bingqian Wang, Zemin Qin, Cui Li, Yanlong Chen, Yuheng Wang, Zhiling Li, Miao Lv, Aijie Wang, Fan Chen
    Frontiers of Environmental Science & Engineering, 2024, 18(1): 4. https://doi.org/10.1007/s11783-024-1764-y

    ● Stable and efficient U extraction with electrical energy production was achieved.

    ● The U(VI) removal proceeded via a diffusion-controlled U(VI)-to-U(IV) reduction.

    ● Electro-microbiome was constructed for microbial-driven ectopic U extraction.

    ● Metabolic pathways of anode biofilm were deciphered by metagenomics.

    The extraction of uranium (U) from U-bearing wastewater is of paramount importance for mitigating negative environmental impacts and recovering U resources. Microbial reduction of soluble hexavalent uranium (U(VI)) to insoluble tetravalent uranium (U(IV)) holds immense potential for this purpose, but its practical application has been impeded by the challenges associated with managing U-bacterial mixtures and the biotoxicity of U. To address these challenges, we present a novel spontaneous microbial electrochemical (SMEC) method that spatially decoupled the microbial oxidation reaction and the U(VI) reduction reaction. Our results demonstrated stable and efficient U extraction with net electrical energy production, which was achieved with both synthetic and real wastewater. U(VI) removal occurred via diffusion-controlled U(VI)-to-U(IV) reduction-precipitation at the cathode, and the UIVO2 deposited on the surface of the cathode contributed to the stability and durability of the abiotic U(VI) reduction. Metagenomic sequencing revealed the formation of efficient electroactive communities on the anodic biofilm and enrichment of the key functional genes and metabolic pathways involved in electron transfer, energy metabolism, the TCA cycle, and acetate metabolism, which indicated the ectopic reduction of U(VI) at the cathode. Our study represents a significant advancement in the cost-effective recovery of U from U(VI)-bearing wastewater and may open a new avenue for sustainable uranium extraction.

  • RESEARCH ARTICLE
    Lizheng Guo, Xinyan Xiao, Kassim Chabi, Yiting Zhang, Jingjing Li, Su Yao, Xin Yu
    Frontiers of Environmental Science & Engineering, 2024, 18(3): 35. https://doi.org/10.1007/s11783-024-1795-4

    ● The VBNC pathogens were quantified for the first time in public tap water.

    ● The VBNC pathogens ranged from 1 to 103 cell equivalent/100 mL in tap water.

    ● Regrowth of pathogenic bacteria was found after long stagnation of tap water.

    ● Spatial and temporal factors explained 17.1% and 26.0% of the community variation.

    Viable but non-culturable (VBNC) bacteria have been detected in source water and effluent of drinking water treatment processes, leading to significant underestimation of viable cell counts. Limited information exists on VBNC bacteria in tap water, particularly in public places. To address this gap, a comprehensive nine-month study was conducted in a major city in south-eastern China, using culture-based and quantitative PCR with propidium monoazide (PMA) dye methods. Forty-five samples were collected from five representative public places (railway station, campus, hospital, shopping mall, and institution). The findings revealed that culturable bacteria represented only 0–17.51% of the viable 16S rRNA genes, suggesting that the majority of viable bacteria existed in an uncultured or VBNC state. Notably, opportunistic pathogens such as Escherichia coli, Enterococcus faecalis, Pseudomonas aeruginosa, Salmonella sp., and Shigella sp. were primarily detected as VBNC cells, with concentrations ranging from 1.03 × 100 to 3.01 × 103, 1.20 × 100 to 1.42 × 102, 1.32 × 100 to 8.82 × 100, 1.00 × 100 to 6.71 × 101, and 2.07 × 100 to 1.93 × 102 cell equivalent/100 mL, respectively. Culturable P. aeruginosa was observed in tap water after prolonged stagnation, indicating potential risks associated with bacterial regrowth. Spatial and temporal factors accounted for 17.1% and 26.0%, respectively, of the variation in tap water community structure during the sampling period, as revealed by 16S rRNA amplicon sequencing. This study provides quantitative insights into the occurrence of VBNC bacteria in tap water and highlights the need for more sensitive monitoring methods and microbial control techniques to enhance tap water safety in public locations.

  • RESEARCH ARTICLE
    Junge Xu, Dong Wang, Die Hu, Ziwei Zhang, Junhong Chen, Yingmu Wang, Yifeng Zhang
    Frontiers of Environmental Science & Engineering, 2024, 18(3): 37. https://doi.org/10.1007/s11783-024-1797-2

    ● Magnetic Co- γ -Fe2O3/MoS2 were prepared via facile hydrothermal methods.

    ● Doping γ -Fe2O3 with cobalt greatly increased PMS activation for BPA abatement.

    ● The compounding of MoS2 significantly enhanced the stability of the catalyst.

    ● Hybrid radical-nonradical pathways acted for effective degradation of BPA.

    ● The toxicity of intermediates was lower than BPA via T.E.S.T analysis.

    Iron-based catalysts have been widely used to treat refractory organic pollutants in wastewater. In this paper, magnetic Co-γ-Fe2O3 was synthesized by a facile tartaric acid-assisted hydrothermal method, and Co-γ-Fe2O3/MoS2 nanocomposite catalyst was obtained via in situ growth of MoS2 nanosheets on Co-γ-Fe2O3 nanoparticles. The nanocomposite catalysts were used to decompose bisphenol A (BPA) by activating peroxymonosulfate (PMS). It was shown that only 0.15 g/L catalyst and 0.5 mmol/L PMS degraded 10 mg/L of BPA (99.3% within 10 min) in the pH range of 3–9. PMS was activated due to redox cycling among the pairs Co(III)/Co(II), Fe(III)/Fe(II), and Mo(VI)/Mo(IV). Quenching experiments and electron paramagnetic resonance spectroscopy demonstrated that both radical and non-radical pathways were involved in BPA degradation, in which active radical sulfate radical and non-radical singlet oxygen were the main reactive oxygen species. Ten intermediates were identified by liquid chromatography-coupled mass spectrometry, and three possible BPA degradation pathways were proposed. The toxicity of several degradation intermediates was lower, and Co-γ-Fe2O3/MoS2 exhibited excellent reusability and could be magnetically recovered.

  • REVIEW ARTICLE
    Lijuan Gu, Hailong Lu
    Frontiers of Environmental Science & Engineering, 2023, 17(12): 144. https://doi.org/10.1007/s11783-023-1744-7

    ● Structural and thermodynamical properties of semi-clathrate hydrate are summarized.

    ● Properties of quaternary salts and gas mixture hydrate are summarized.

    ● Challenges persist in the application of semi-clathrate hydrates for carbon capture and separation.

    CO2 is considered as the main contributor to global warming, and hydrate enclathration is an efficient way for carbon capture and separation (CCS). Semi-clathrate hydrate (SCH) is a type of clathrate hydrate capable of encaging CO2 molecules under mild temperature and pressure conditions. SCH has numerous unique advantages, including high thermal stability, selective absorption of gas molecules with proper size and recyclable, making it a promising candidate for CCS. While SCH based CCS technology is in the developing stage and great efforts have to be conducted to improve the performance that is determined by their thermodynamical and structural properties. This review summarizes and compares the thermodynamic and structural properties of SCH and quaternary salt hydrates with gas mixtures to be captured and separated. Based on the description of the physical properties of SCH and hydrate of quaternary salts with gas mixture, the CO2 capture and separation from fuel gas, flue gas and biogas with SCH are reviewed. The review focuses on the use of tetra-n-butyl ammonium halide and tetra-n-butyl phosphonium halide, which are the current application hotspots. This review aims to provide guidance for the future applications of SCH.

  • RESEARCH ARTICLE
    Yuyao Zhang, Litao Jia, Jin Zhao, Xuming Liu, Shuyu Dong, Chuanyang Liu, Yuanyuan Cui
    Frontiers of Environmental Science & Engineering, 2024, 18(3): 32. https://doi.org/10.1007/s11783-024-1792-7

    ● Simultaneous water recovery and salt separation from hypersaline brine is feasible.

    ● Water recovery shows an obvious boundary at saline concentration of 115 g/L.

    ● Cl removal is exponentially correlated with specific water extraction efficiency.

    ● Radical precipitation of Mg2+ and Ca2+ leads to more amine residues in raffinate.

    The feasibility of simultaneous water recovery, salt separation and effective descaling of hypersaline brine was investigated by diisopropylamine (DIPA)-based directional solvent extraction (DSE), using diluted/concentrated seawater with initial saline concentration range of 12–237 g/L at extraction temperatures of 5 and 15 °C, respectively. The water recovery shows an obvious boundary at saline concentration of 115 g/L under dual effect of specific water extraction efficiency and extraction cycles. High Cl ion concentration in product water is in sharp contrast to the nearly complete removal of SO42– and hardness ions, indicating that DIPA-based DSE process indeed achieved efficient separation and purification of Cl ion from hypersaline brines. Especially, the radical precipitation of Mg2+ and Ca2+ ions in form of Mg(OH)2 and CaCO3 demonstrates effective descaling potential, although it leads to more DIPA residues in dewatered raffinate than product water. Moreover, an exponential correlation between the Cl removal efficiency and specific water extraction efficiency further reveals the intrinsic relationship of water extraction process and transfer of Cl ion to the product water. Overall, the study provides a novel approach for integrating the water recovery and separation of Cl ion from ultra-high-salinity brines with radical precipitation of Mg2+ and Ca2+ ions in one step.

  • PERSPECTIVES
    Zhiqiang Zuo, Min Zheng, Tao Liu, Yongzhen Peng, Zhiguo Yuan
    Frontiers of Environmental Science & Engineering, 2024, 18(2): 26. https://doi.org/10.1007/s11783-024-1786-5

    ● The historical development of free nitrous acid (FNA) technologies is reviewed.

    ● The roles of novel acid-tolerant ammonia oxidizers are highlighted.

    ● Acid-tolerant ammonia oxidizers can self-sustain high-level FNA production.

    ● The next-generation in situ FNA-based technologies are discussed.

    The biocidal effects of free nitrous acid (FNA) have found applications in multiple units in an urban wastewater system, including sewer networks, wastewater treatment processes, and sludge treatment processes. However, these applications are associated with chemical costs as both nitrite and acid are needed to produce FNA at the required levels. The recent discovery of novel acid-tolerant ammonia oxidizers offers the possibility to produce FNA from domestic wastewater, enabling the development of next-generation FNA-based technologies capable of achieving self-sustaining FNA production. In this study, we focus on the concept of in situ FNA generation facilitated by acid-tolerant ammonia oxidizers and highlight the multiple benefits it creates, after a brief review of the historical development of FNA-based technologies. We will discuss how wastewater systems can be made more energy-efficient and sustainable by leveraging the potential of acid-tolerant ammonia oxidizers.

  • RESEARCH ARTICLE
    Luning Lian, Yi Xing, Dayi Zhang, Longfei Jiang, Mengke Song, Bo Jiang
    Frontiers of Environmental Science & Engineering, 2024, 18(1): 5. https://doi.org/10.1007/s11783-024-1765-x

    ● Dimethoate degraders were identified via MMI and DNA-SIP.

    ● MMI identified Pseudomonas, Bacillus, Ramlibacter, Arthrobacter , and Rhodococcus.

    ● DNA-SIP identified Ramlibacter , Rhodococcus and Arthrobacter.

    ● Both oph B and oph C2 were involved in dimethoate metabolism.

    ● MMI shows higher resolution than DNA-SIP in identifying functional microbes.

    Microorganisms are crucial in the bioremediation of organophosphorus pesticides. However, most functional microorganisms (> 99%) are yet to be cultivated. This study applied two cultivation-independent approaches, DNA-SIP and magnetic-nanoparticle mediated isolation (MMI), to identify the functional microorganisms in degrading dimethoate in agricultural soils. MMI identified five dimethoate degraders: Pseudomonas, Bacillus, Ramlibacter, Arthrobacter, and Rhodococcus, whereas DNA-SIP identified three dimethoate degraders: Ramlibacter, Arthrobacter, and Rhodococcus. Also, MMI showed higher resolution than DNA-SIP in identifying functional microorganisms. Two organic phosphohydrolase (OPH) genes: ophC2 and ophB, were involved in dimethoate metabolism, as revealed by DNA-SIP and MMI. The degradation products of dimethoate include omethoate, O,O,S-trimethyl thiophosphorothioate, N-methyl-2-sulfanylacetamide, O,O-diethyl S-hydrogen phosphorodithioate, O,O,O-trimethyl thiophosphate, O,O,S-trimethyl thiophosphorodithioate, and O,O,O-trimethyl phosphoric. This study emphasizes the feasibility of using SIP and MMI to explore the functional dimethoate degraders, expanding our knowledge of microbial resources with cultivation-independent approaches.

  • RESEARCH ARTICLE
    Junchen Li, Sijie Lin, Liang Zhang, Yuheng Liu, Yongzhen Peng, Qing Hu
    Frontiers of Environmental Science & Engineering, 2024, 18(3): 31. https://doi.org/10.1007/s11783-024-1791-x

    ● A novel brain-inspired network accurately predicts sewage effluent quality.

    ● Sewage-surface images are utilized in data analysis by the model.

    ● The developed method outperforms traditional ones by reducing error by 23%.

    ● The model offers the potential for cost-effective monitoring.

    Efficiently predicting effluent quality through data-driven analysis presents a significant advancement for consistent wastewater treatment operations. In this study, we aimed to develop an integrated method for predicting effluent COD and NH3 levels. We employed a 200 L pilot-scale sequencing batch reactor (SBR) to gather multimodal data from urban sewage over 40 d. Then we collected data on critical parameters like COD, DO, pH, NH3, EC, ORP, SS, and water temperature, alongside wastewater surface images, resulting in a data set of approximately 40246 points. Then we proposed a brain-inspired image and temporal fusion model integrated with a CNN-LSTM network (BITF-CL) using this data. This innovative model synergized sewage imagery with water quality data, enhancing prediction accuracy. As a result, the BITF-CL model reduced prediction error by over 23% compared to traditional methods and still performed comparably to conventional techniques even without using DO and SS sensor data. Consequently, this research presents a cost-effective and precise prediction system for sewage treatment, demonstrating the potential of brain-inspired models.

  • RESEARCH ARTICLE
    Ying Han, Ying Yang, Weibao Liu, Yilong Hou, Ce Wang, Jiangwei Shang, Xiuwen Cheng
    Frontiers of Environmental Science & Engineering, 2024, 18(1): 9. https://doi.org/10.1007/s11783-024-1769-6

    ● A three-phase catalytic system was constructed to degrade typical dyes RhB.

    ● RhB could be effectively removed at the pH range of 3–9 within 10 min.

    ● The synergistic mechanism of MnFe-LDH catalysis on PMS/O3 was investigated.

    ● The degradation pathways and ecotoxicity of the intermediates of RhB were proposed.

    This study developed a novel MnFe-LDH/PMS/O3 three-phase catalytic system to degrade the organic dye RhB, which was used to address the drawbacks of persulfate oxidation and ozonation techniques. The structure, ionic and elemental composition, specific surface area, and magnetic properties of the LDHs were investigated using a variety of physicochemical characterization tools. The results showed that MnFe-LDH had a large specific surface area, a rich crystalline phase composition, and a functional group structure. The RhB degradation rate of MnFe-LDH/PMS/O3 was 0.34 min−1, which was much higher than that of other comparative systems. RhB could be completely degraded in 10 min after optimization and had a significant effect on TOC removal. The system was found to be effective over a wide pH range. Common anions were largely unaffected and humic acid acted as an inhibitor. At the same time, the system had generally effective degradation performance for different dyes. Combined with quenching experiments and EPR, it was found that SO4•−, •OH, O2•−, and 1O2 all participated in the reaction, and •OH contributed more. The degradation pathway of RhB was derived by LC-MS, and the T.E.S.T. evaluation found that the toxicity of the intermediate product was significantly reduced. Finally, the stability and availability of LDHs were verified using cycling experiments and metal ion leaching. This work provides a theoretical basis and data support for the synergistic catalysis of PMS/O3 and the deep treatment of dye wastewater.

  • RESEARCH ARTICLE
    Jinglu Song, Yi Lu, Thomas Fischer, Kejia Hu
    Frontiers of Environmental Science & Engineering, 2024, 18(1): 11. https://doi.org/10.1007/s11783-024-1771-z

    ● The effect modifications of urban landscape were explored at the intra-urban level.

    ● Higher levels of green spaces could alleviate adverse health impacts of heatwaves.

    ● Higher building density and nighttime land surface temperatures aggravate impacts.

    ● Effects of urban landscape were more significant in older adults and males.

    ● Pronounced effect modifications were observed under hotter and longer heatwaves.

    Despite increased attention given to potential modifiers of temperature-mortality associations, evidence for variations between different urban landscape characteristics remains limited. It is in this context that in this paper effect modifications of multiple urban landscape characteristics are explored under different heatwave definitions for different age groups and gender in Hong Kong, China. Daily meteorological data and heatwave-related mortality counts from 2008 to 2017 were collected from the Hong Kong Census and Statistics Department, China. A case-only design was adopted, combined with logistic regression models to examine the modification effects of five urban landscape characteristics under six heatwave definitions. Stratified analyses were conducted to investigate age- and gender-specific effect modifications. It is found that individuals living in greener areas experienced lower levels of mortality during or immediately after heatwaves. In contrast, a higher building density and nighttime land surface temperature (LST) were associated with a higher heatwave-related mortality risk. Pronounced effect modifications of these urban landscape characteristics were observed under hotter and longer heatwaves, and in older adults (age ≥ 65 years) and males. The findings provide a scientific basis for policymakers and practitioners when considering measures for coping with hotter, longer, and more frequent heatwaves in the context of global climate change.

  • RESEARCH ARTICLE
    Qiyue Wu, Yun Geng, Xinyuan Wang, Dongsheng Wang, ChangKyoo Yoo, Hongbin Liu
    Frontiers of Environmental Science & Engineering, 2024, 18(1): 8. https://doi.org/10.1007/s11783-024-1768-7

    ● PLS-VAER is proposed for modeling of PM2.5 concentration.

    ● Data are decomposed by PLS to capture nonlinear feature.

    ● VAER can improve the predictive performance by variational inference.

    ● The proposed model provides a novel method for monitoring indoor air quality.

    Exposure to poor indoor air conditions poses significant risks to human health, increasing morbidity and mortality rates. Soft measurement modeling is suitable for stable and accurate monitoring of air pollutants and improving air quality. Based on partial least squares (PLS), we propose an indoor air quality prediction model that utilizes variational auto-encoder regression (VAER) algorithm. To reduce the negative effects of noise, latent variables in the original data are extracted by PLS in the first step. Then, the extracted variables are used as inputs to VAER, which improve the accuracy and robustness of the model. Through comparative analysis with traditional methods, we demonstrate the superior performance of our PLS-VAER model, which exhibits improved prediction performance and stability. The root mean square error (RMSE) of PLS-VAER is reduced by 14.71%, 26.47%, and 12.50% compared to single VAER, PLS-SVR, and PLS-ANN, respectively. Additionally, the coefficient of determination (R2) of PLS-VAER improves by 13.70%, 30.09%, and 11.25% compared to single VAER, PLS-SVR, and PLS-ANN, respectively. This research offers an innovative and environmentally-friendly approach to monitor and improve indoor air quality.