Sensitivity of the Transport of Plastic Nanoparticles to Typical Phosphates Associated with Ionic Strength and Solution pH.

The influence of phosphates on the transport of plastic particles in porous media is environmentally relevant due to their ubiquitous coexistence in the subsurface environment. This study investigated the transport of plastic nanoparticles (PNPs) via column experiments, paired with Derjaguin-Landau-Verwey-Overbeek calculations and numerical simulations. The trends of PNP transport vary with increasing concentrations of NaH2PO4 and Na2HPO4 due to the coupled effects of increased electrostatic repulsion, the competition for retention sites, and the compression of the double layer. Higher pH tends to increase PNP transport due to the enhanced deprotonation of surfaces. The release of retained PNPs under reduced IS and increased pH is limited because most of the PNPs were irreversibly captured in deep primary minima. The presence of physicochemical heterogeneities on solid surfaces can reduce PNP transport and increase the sensitivity of the transport to IS. Furthermore, variations in the hydrogen bonding when the two phosphates act as proton donors will result in different influences on PNP transport at the same IS. This study highlights the sensitivity of PNP transport to phosphates associated with the solution chemistries (e.g., IS and pH) and is helpful for better understanding the fate of PNPs and other colloidal contaminants in the subsurface environment.

China's logistics green competitiveness promotion path: a fuzzy-set qualitative comparative analysis approach.

Increasingly serious environmental problems are forcing many industries to gradually turn to green development, and green competitiveness has become the vision of policymakers and industry practitioners. The impact of the development of the logistics industry on the environment cannot be ignored, but the promotion path of its green competitiveness has not been fully studied. Based on Porter's diamond model, this study uses fuzzy-set qualitative comparative analysis to explore the condition configuration of the logistics industry in 30 provincial regions in mainland China to enhance green competitiveness and effectively combine theory with practice. Factors considered include logistics technology innovation ability, logistics market demand, proportion of tertiary industry, management level of logistics enterprises, environmental regulation, and the internet. The results show that the green competitiveness of the logistics industry is influenced by many factors and cannot be sufficiently explained by a single factor. The findings point to three paths with equal authenticity to improve the green competitiveness of the logistics industry. By comparing the same types of high configuration and low configuration, this study finds that environmental regulation is an important external driving force for regions with low added value of output products, and for regions with certain geographical advantages and numerous logistics enterprises, in addition to the management level of logistics enterprises, support from the internet is also particularly important in improving the green competitiveness of logistics. These findings can provide a practical reference for the promotion of green competitiveness in the logistics industry in different regions.

Spatial-temporal variation characteristics and evolution of the global industrial robot trade: A complex network analysis.

Industrial robots are a strategic future technology and an important part of the development of artificial intelligence, and they are a necessary means for the intelligent transformation of manufacturing industry. Based on global industrial robot trade data from 1998 to 2017, this paper applies the dynamic complex network analysis method to reveal the spatial and temporal variation characteristics and trade status evolution of the global industrial robot trade network. The results show that the global industrial robot network density has steadily increased, and the industrial robot trade has been characterized by 'diversification'. The number of major industrial robot exporters in the world is increasing, and the import market is increasingly diversified. The export market structure is relatively tight, the centrality of the global industrial robot trade network shows a downward trend, and the dissimilarity of the 'core-edge' clusters decreases year by year. The trade status of 'catch-up' countries represented by China has rapidly increased. However, Japan, Germany, and Italy are still in the central position of the industrial robot trade. Moreover, trade of the 'catch-up' countries' is dominated by imports, and exports of industrial robot products are insufficient. Finally, policy suggestions are provided according to the results.