Low-dimensional metal oxides-based electronic noses have been applied in various fields, such as food quality, environmental assessment, coal mine risk prediction, and disease diagnosis. However, the applications of these electronic noses are limited for conditions such as precise safety monitoring because electronic nose systems have problems such as poor recognition ability of mixed gas signals and sensor drift caused by environmental factors. Advanced algorithms, including classical gas recognition algorithms and neural network-based algorithms, can be good solutions for the key problems. Classical gas recognition methods, such as support vector machines, have been widely applied in electronic nose systems in the past. These methods can provide satisfactory results if the features are selected properly and the types of mixed gas are under five. In many situations, this can be challenging due to the drift of sensor signals. In recent years, neural networks have undergone revolutionary changes in the field of electronic noses, especially convolutional neural networks and recurrent neural networks. This paper reviews the principles and performances of typical gas recognition methods of the electronic nose up to now and compares and analyzes the classical gas recognition methods and the neural network-based gas recognition methods. This work can provide guidance for research in related fields.

In this work, the relationship and kinetics of biodegradation and bio-adsorption of benzo[a]pyrene (BaP) by Bacillus and Ascomycota were explored, and the metabolites of BaP under mixed microbial coculture were analyzed and characterized. The results show that BaP was removed through both biosorption and biodegradation. Under mixed microbial coculture, biosorption played a significant role in the early stage and biodegradation was predominant in the later stage. During the removal of BaP, the fungi exhibited remarkable adsorption capabilities for BaP with an adsorption efficiency (AE) of 38.14 %, while bacteria had a best degradation for BaP with a degradation efficiency (DE) of 56.13 %. Under the mixed microbial culture, the removal efficiency (RE) of BaP by the synergistic action of fungi and bacteria reached up to 76.12 % within 15 days. Kinetics analysis illustrated that the degradation and adsorption process of BaP were well fit to the first-order and the pseudo-second-order kinetic models, respectively. The research on the relationship between degradation and adsorption during microbial removal of BaP, as well as the synergistic effects of fungi and bacteria, will provide a theoretical guidance for two or even synthetic microbial communities.

Rare earth metal–organic frameworks (RE-MOFs) are mainly composed of rare earth ions and organic ligands, taking advantage of the strengths of both metal–organic frameworks (MOFs) and rare earth ions. Rare earth ions have the unique feature of unfilled 4f electron shells, which endows them with higher coordination numbers, unique luminescence properties, larger Stokes shifts, longer fluorescence lifetimes, and higher luminescence quantum efficiency. The MOFs combined with a variety of organic ligands can effectively guide the antenna effect to sensitize the rare earth ions and thus enhance the photon emission, making RE-MOFs a promising material in the field of fluorescent probes. In this paper, the recent advances in design principles, strategies, synthesis means, and monitoring mechanisms of RE-MOF materials for pollutant monitoring are presented. The intrinsic correlation between the luminescence performance of RE-MOFs, the detection of contaminants and the selection of organic ligands, and the adjustment of the MOF backbone structure is systematically and comprehensively discussed. Finally, the future development direction and application prospects of RE-MOF materials are summarized and discussed.

Aiming at the task of noise suppression caused by the photoionization detector (PID) monitoring signal of volatile organic compounds (VOCs) due to local non-uniformity of the photocathode surface of PID in the ionization chamber, this paper proposes an analytical method of a PID signal with the adaptive weight of the small wave package decomposition node. The PID signal is transmitted to the upper machine software through the single-chip microcontroller. The appropriate wavelet packet decomposition level is determined according to the time frequency characteristics of the original signal of the PID, and the optimal wavelet packet base is selected through the polynomial fitting of the signal quality evaluation index. By comparing the quality of signals processed by the traditional wavelet packet denoising method and the denoising method presented in this paper, the superiority of the proposed method in the denoising signals of PID was verified. This method can eliminate the noise generated by local non-uniformity on the photocathode surface of the PID ionization chamber in a high humidity environment, which lays a foundation for the accurate monitoring of VOCs in a high humidity environment.

The process of mining produces a large amount of heavy metals and high-sulfate mine water, which is the main factor leading to environmental degradation in the mining area, and the removal of heavy metals and the recovery of sulfate from mine water is a difficult problem faced by mines today. Currently, sulfate is treated as a hazardous substance and is not recycled. In this paper, the precipitation–adsorption bipolar membrane electrodialysis (BMED) multi-technology-coupled recovery of sulfate method was used to treat mine water. The results showed that the coupling technology could remove heavy metals and sulfate in water better, while the sulfate desalination rate was about 96.8%, current efficiency was 54.2%, energy consumption was 0.823 kWh/kg, and the acid production concentration was 0.168 at an electrolyte concentration of 0.1 mol/L, an operating voltage of 12 V, an initial salt concentration of 30 g/L, and a flow rate of 3.5 mL/min. Mechanistic results showed that the precipitation–adsorption method could realize the removal of heavy metals from mine water. The BMED process realized the removal of sulfate and also the recovery of acid. The multi-technology coupling of precipitation–adsorption and bipolar membrane electrodialysis explored in this paper provides a direction for the in-depth treatment of mine water.