A multi-strategy improved rime optimization algorithm for three-dimensional USV path planning and global optimization.

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).

Coking exhaust contributes to airborne particulate matter in the Beijing-Tianjin-Hebei region.

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.

An interpolation method incorporating the pollution diffusion characteristics for soil heavy metals - taking a coke plant as an example.

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.

Apportionment and location of heavy metal(loid)s pollution sources for soil and dust using the combination of principal component analysis, Geodetector, and multiple linear regression of distance.

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.

Discharge Patterns of Potentially Harmful Elements (PHEs) from Coking Plants and Its Relationship with Soil PHE Contents in the Beijing-Tianjin-Hebei Region, China.

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.

Influencing factors and prediction of arsenic concentration in Pteris vittata: A combination of geodetector and empirical models.

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.

[Heavy Metal Contents of Soil and Surface Dust and Its Ecological Risk Analysis in a Multifunctional Industrial Park].

A multifunctional industrial park can perform both producing and living functions. The smelting and processing of non-ferrous metals may lead to soil pollution, posing risks to human beings. In this study, an industrial park located in central Anhui Province, China, with copper (Cu) processing and mechanical components as the main industries, was selected as the study object.

[Analysis of the Spatial Distribution of Heavy Metals in Soil from a Coking Plant and Its Driving Factors].

Coking plants are typical industrial pollution sites and may release heavy metals into the environment, posing a threat to human health. Scholars have discovered that different types of heavy metals are released during different coking production processes and lead to spatial differences in heavy metals. Research on the spatial distribution and driving factors of pollutants in the soil inside and outside coking plants is important for sampling design, risk assessment, pollution prevention and control, etc.

Bioaccessibility of metals/metalloids in willow catkins collected in urban parks of Beijing and their health risks to human beings.

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.