The RIME optimization algorithm (RIME) represents an advanced optimization technique. However, it suffers from issues such as slow convergence speed and susceptibility to falling into local optima. ...In response to these shortcomings, we propose a multi-strategy enhanced version known as the multi-strategy improved RIME optimization algorithm (MIRIME). Firstly, the Tent chaotic map is utilized to initialize the population, laying the groundwork for global optimization. Secondly, we introduce an adaptive update strategy based on leadership and the dynamic centroid, facilitating the swarm's exploitation in a more favorable direction. To address the problem of population scarcity in later iterations, the lens imaging opposition-based learning control strategy is introduced to enhance population diversity and ensure convergence accuracy. The proposed centroid boundary control strategy not only limits the search boundaries of individuals but also effectively enhances the algorithm's search focus and efficiency. Finally, to demonstrate the performance of MIRIME, we employ CEC 2017 and CEC 2022 test suites to compare it with 11 popular algorithms across different dimensions, verifying its effectiveness. Additionally, to assess the method's practical feasibility, we apply MIRIME to solve the three-dimensional path planning problem for unmanned surface vehicles. Experimental results indicate that MIRIME outperforms other competing algorithms in terms of solution quality and stability, highlighting its superior application potential.
Coking was regarded as a predominant source of air pollution. Despite the adoption of more environmentally friendly equipment, whether the coking enterprises in the Beijing–Tianjin–Hebei (BTH) region ...are still causing regional air pollution is worthy of study, which is essential for the control of coking enterprises in this area. To improve the prediction accuracy of large-scale air pollutant distribution, the air particle distribution in the BTH region was simulated via land use regression (LUR) combined with Bayesian maximum entropy (BME); then, the distribution was correlated with the exhaust gas emitted from coking enterprises. Results indicated that the R2 of the “LUR + BME” method reached 0.95, higher than 0.82 using LUR alone. The air quality distribution presented a pattern of “low in the northern mountains and high in the southern plains”, similar to the distribution of coking enterprises in BTH region. A significant correlation was found between exhaust emissions from coking enterprises and air quality in the BTH region, confirming the contribution of coking emissions to air pollution in this region, and the necessity to continue the strict control on coking enterprises in BTH area.
•Land use regression with Bayesian maximum entropy was applied to PM10 simulation.•The air pollutant concentration increase from northwest to southeast in BTH area.•Positive correlation exists between coking exhaust emissions and air quality.
The Beijing-Tianjin-Hebei (BTH) region in China is a rapid development area with a dense population and high-pollution, high-energy-consumption industries. Despite the general idea that the coking ...industry contributes greatly to the total emission of potentially harmful elements (PHEs) in BTH, quantitative analysis on the PHE pollution caused by coking is rare. This study collected the pollutant discharge data of coking enterprises and assessed the risks of coking plants in BTH using the soil accumulation model and ecological risk index. The average contribution rate of coking emissions to the total emissions of PHEs in BTH was ~7.73%. Cross table analysis indicated that there was a close relationship between PHEs discharged by coking plants and PHEs in soil. The accumulation of PHEs in soil and their associated risks were calculated, indicating that nearly 70% of the coking plants posed a significant ecological risk. Mercury, arsenic, and cadmium were the main PHEs leading to ecological risks. Scenario analysis indicated that the percentage of coking plants with high ecological risk might rise from 8.50% to 20.00% as time progresses. Therefore, the control of PHEs discharged from coking plants in BTH should be strengthened. Furthermore, regionalized strategies should be applied to different areas due to the spatial heterogeneity of risk levels.
Phytoextraction using hyperaccumulator, Pteris vittata, to extract arsenic (As) from soil has been applied to large areas to achieve an As removal rate of 18% per year. However, remarkable difference ...among different studies and field practices has led to difficulties in the standardization of phytoextraction technology. In this study, data on As concentration in P. vittata and related environmental conditions were collected through literature search. A conceptual framework was proposed to guide the improvement of phytoextraction efficiency in the field. The following influencing factors of As concentration in this hyperaccumulator were identified: total As concentration in soil, soil available As, organic matter in soil, total potassium (K) concentration in soil, and annual rainfall. The geodetection results show that the main factors that affect As concentration in P. vittata include soil organic matter (q = 0.75), soil available As (q = 0.67), total K (q = 0.54), and rainfall (q = 0.42). The predictive models of As concentration in P. vittata were established separately for greenhouse and field conditions through multivariate linear stepwise regression method. Under greenhouse condition, soil available As was the most important influencing factor and could explain 41.4% of As concentration in P. vittata. Two dominant factors were detected in the field: soil available As concentration and average annual rainfall. The combination of these two factors gave better prediction results with R2 = 0.762. The establishment of the model might help predict phytoextraction efficiency and contribute to technological standardization. The strategies that were used to promote As removal from soil by P. vittata were summarized and analyzed. Intercropping with suitable plants or a combination of different measures (e.g., phosphate fertilizer and water retention) was recommended in practice to increase As concentration in P. vittata.
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•Key influencing factors for As accumulation by P. vittata were identified via correlation and Geodetector.•As accumulation by P. vittata in the field was well predicted using soil available As and rainfall.•A conceptual framework for the application of phytoextraction in the field was proposed.
The measurement of instantaneous speed is often used in the vibration and noise control of equipment. This paper designs an instantaneous speed measurement method based on A/D sampling method. This ...method mainly obtains the instantaneous speed indirectly by obtaining the square wave signal. The experimental results show that this method is simple and feasible, and provides a reference for the establishment of instantaneous speed measurement system.
The accurate identification of sources for soil heavy metal(loid) is difficult, especially for multi-functional parks, which include multiple pollution sources. Aiming to identify the apportionment ...and location of heavy metal(loid)s pollution sources, this study established a method combining principal component analysis (PCA), Geodetector, and multiple linear regression of distance (MLRD) in soil and dust, taking a multi-functional industrial park in Anhui Province, China, as an example. PCA and Geodetector were used to determine the type and possible location of the source. Source apportionment of individual elements is achieved by MLRD. The detection results quantified the spatial explanatory power (0.21 ≤ q ≤ 0.51) of the potential source targets (e.g., river and mining area) for the PCA factors. A comparative analysis of the regression equation (Model 1 and Model 3) indicated that the river (0.50 ≤ R2 ≤0.78), main road (0.47 ≤ R2 ≤ 0.81), and mine (0.14 ≤ R2 ≤ 0.92) (p < 0.01) were the main sources. Different from the traditional source apportionment methods, the current method could obtain the exact contributing sources, not just the type of source (e.g., industrial activities), which could be useful for pollution control in areas with multiple sources.
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•PCA- Geodetector-MLRD was used to determine the location of the sources, not just the type of source.•The river, main road, mining area, metal plant, and community can significantly explain the PCA factors.•A distance-based prediction model for heavy metal concentration was established and its effectiveness was verified.
Air pollution and its resulting health risks in Beijing City have been widely investigated by scientists and administrators. However, the health risks caused by willow and poplar catkins in April and ...May (known as “spring snow”) have been rarely reported. Poplar and willow are the two common trees in Beijing City that generate many whirling catkins in the air. The chemical composition of catkins remains unknown. In this study, catkins and dust samples were collected in several parks in Beijing. The total concentrations of metals/metalloids in catkins measured through inductively coupled plasma mass spectrometry were generally lower than those of the corresponding dust samples, and they were lower than the risk control standard for soil contamination of development land. The simulated rain and lung fluid extraction rates of catkin samples were significantly higher than those of the dust samples. The concentration of extracted Pb and Zn using simulated rainwater exceeded the environmental quality standards for surface water (0.1 and 2.0 mg/L for Pb and Zn, respectively), indicating the possibility of runoff pollution. Scanning electron microscopy images showed that fine particles (<10 μm) are attached to the surface of catkins. Therefore, the metals/metalloids in fine particles adsorbed by the catkin samples possess higher bioaccessibility than that in the dust samples based on different sizes of particles. A significant correlation is found between Pb in catkin and Pb in dust. Therefore, attention should be paid to the possible increase in metal/metalloid concentrations in catkins planted in contaminated areas.
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•Fine particles (<10 μm) are attached to the surface of catkins.•Bioaccessibility of metals/metalloids in catkins was higher than that in dusts.•Correlation was found between Pb in catkin and Pb in dust.•Potential risks of catkins need to consider in contaminated areas.
The existing spatial interpolation methods in the prediction of soil heavy metal distribution are generally based on spatial auto correlation theory, rarely considering the pollution patterns. By ...contrast, in polluted sites, heavy metals have a strong heterogeneity even within a very small area, which is not exactly in line with auto correlation theory. This contradiction may lead to inaccuracy in spatial prediction. Atmospheric diffusion and deposition are one of the main sources of soil heavy metal pollution caused by coal-related production activities. To improve the prediction accuracy, the diffusion patterns of pollutants were considered in this paper by integrating Geodetector, Co-Kriging (COK), and partition interpolation. Geodetector was used to identify the main driving factors of soil pollution, based on which, the main driving factors were used as covariates introduced into the interpolation method (COK). Specifically, the amount of particulate matter deposition obtained by a pollutant diffusion model (AERMOD) was used as a covariate. For comparison, the distances to quenching, coke oven, and ammonium sulfate section were also used as covariates. Compared with the Ordinary Kriging method, the method COK-AERMOD established here decreased the root mean square error values of As (2.05 reduced to 1.89), Cd (0.18 reduced to 0.16), Cr (19.07 reduced to 12.97), Cu (6.92 reduced to 4.72), Hg (0.32 reduced to 0.28), Ni (16.92 reduced to 16.10), Pb (18.29 reduced to 16.62), and Zn (159.68 reduced to 153.66). This method in this paper is informative for the interpolation of soil elements in contaminated areas with known pollution source and diffusion patterns.
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•Pollutant diffusion mechanisms were applied to Co-Kriging interpolation through Geodetector and AERMOD models.•The Geodetector identified the main driver factor that affect the distribution of heavy metals.•AERMOD model-based Co-Kriging improves the prediction accuracy of As, Cu, and Pb.
In order to solve the “window effect” and “aperture repetition effect” caused by limited measurement aperture, a patch near-field acoustic holography method based on two-level iteration is proposed. ...After analyzing the principle and process of patch near-field acoustical holography based on orthogonal spherical wave, a patch near-field acoustical holography method based on two-level iteration is proposed. The validity of the method is verified by simulation and experiment. Compared with the reconstruction results of patch near-field acoustical holography based on orthogonal spherical wave, it shows the superiority of patch near-field acoustical holography based on two-level iteration.
According to the theory of hydro-elasticity, a three-dimensional simplified model of propeller-shaft-shell is established by using three-dimensional hydro-elastic acoustic software. The sound source ...level curve of underwater acoustic radiation is calculated for different double shell spacing under three different excitation sources: external fluid excitation, tail-paddle excitation and internal mechanical excitation. The calculation results show that under all kinds of excitation, the total sound level of sound radiation is slightly lower than the sound level of L and 1.5L when the distance between inner and outer casings is 0.5L.
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