This comparative field study examined the responses of bacterial community structure and diversity to the revegetation of zinc (Zn) smelting waste slag with eight plant species after 5 years. The microbial community structure of waste slag with and without vegetation was evaluated using high-throughput sequencing. The physiochemical properties of Zn smelting slag after revegetation with eight plant rhizospheres for 5 years were improved compared to those of bulk slag. Revegetation significantly increased the microbial community diversity in plant rhizospheres, and at the phylum level, Proteobacteria, Acidobacteria, and Bacteroidetes were notably more abundant in rhizosphere slags than those in bulk waste slag. Additionally, revegetation increased the relative abundance of plant growth-promoting rhizobacteria such as Flavobacterium, Streptomyces, and Arthrobacter as well as symbiotic N2 fixers such as Bradyrhizobium. Three dominant native plant species (Arundo donax, Broussonetia papyrifera, and Robinia pseudoacacia) greatly increased the quality of the rhizosphere slags. Canonical correspondence analysis showed that the differences in bacterial community structure between the bulk and rhizosphere slags were explained by slag properties, i.e., pH, available copper (Cu) and lead (Pb), moisture, available nitrogen (N), phosphorus (P), and potassium (K), and organic matter (OM); however, available Zn and cadmium (Cd) contents were the slag parameters that best explained the differences between the rhizosphere communities of the eight plant species. The results suggested that revegetation plays an important role in enhancing bacterial community abundance and diversity in rhizosphere slags and that revegetation may also regulate microbiological properties and diversity mainly through changes in heavy metal bioavailability and physiochemical slag characteristics.
Studying the modes of selenium occurrence in high-Se soils and its behaviors can improve understanding and evaluating its cycling, flux, and balance in geo-ecosystems and its influence on health. In this paper, using a modified sequential chemical extraction technique, seven operationally defined selenium fractions and Se valence distribution were determined about five soils in which paddy was planted (W1, W2, W3, W4, W5) and five soils in which maize was planted (H1, H2, H3, H4, H5) around the selenium-rich core, Ziyang County, Shaanxi Province, China. The results show that selenium fractions in the soils mainly include sulfide/selenide and base-soluble Se, and ligand-exchangeable Se is also high for five soils in which paddy was planted. For water-soluble Se, Se (IV) is main Se valence and almost no Se (VI) was determined about five soils in which paddy was planted, while almost 1:1 of Se (IV) and Se (VI) coexist about five soils in which maize was planted. For exchangeable Se, similar results were found. For the first time, two typical high-Se soils (W1 soil and H1 soil) were chosen to measure the pH-dependent solid-solution distribution of selenite in the pH range 3–9, and the results were explained using LCD (ligand and charge distribution) adsorption modeling. The desorbed selenite concentrations from the two soils are in general underestimated by the model due to a comparable binding affinity of phosphate and selenite on goethite and much lower amount of total selenite than total reactively adsorbed phosphate. The pH dependency of adsorption of selenite added to the soil can be successfully described with the LCD model for W1 soil. Whereas considering the influence of Al-oxides, by lowering selenite adsorption affinity constant K of Se adsorption on goethite by 16 times, the LCD model can describe the adsorption much better. The results can help to understand selenium cycling, flux, and balance in typical high-Se soils.
ABSTRACTIt is well known that high-efficiency wall-flow particulate filter is the most commonly used technology that can effectively reduce both particulate matter (PM) and particulate number (PN) to comply with the latest emission legislations. Ash, defined as the noncombustible, non-evaporative residue derived mostly from lubricants, has critical impact on engine backpressure, particulate filter filtration efficiency and durability performance, therefore, the investigation of ash impact on particulate filter is of great importance. Due to cost-saving potential, several published methods from different laboratories for accelerated ash loading under carefully controlled conditions are described in this review, including some characterization methods that have been used for the evaluation of filter performance. In addition, the impact of ash deposit on back pressure and regeneration performance are also discussed in this review. 相似文献
A method was proposed to identify the main influence factors of soil heavy metals.The influence degree of different environmental factors was ranked.Parent material, soil type, land use and industrial activity were main factors.Interactions between some factors obviously affected soil heavy metal distribution. Identifying the factors that influence the heavy metal contents of soil could reveal the sources of soil heavy metal pollution. In this study, a categorical regression was used to identify the factors that influence soil heavy metals. First, environmental factors were associated with soil heavy metal data, and then, the degree of influence of different factors on the soil heavy metal contents in Beijing was analyzed using a categorical regression. The results showed that the soil parent material, soil type, land use type, and industrial activity were the main influencing factors, which suggested that these four factors were important sources of soil heavy metals in Beijing. In addition, population density had a certain influence on the soil Pb and Zn contents. The distribution of soil As, Cd, Pb, and Zn was markedly influenced by interactions, such as traffic activity and land use type, industrial activity and population density. The spatial distribution of soil heavy metal hotspots corresponded well with the influencing factors, such as industrial activity, population density, and soil parent material. In this study, the main factors affecting soil heavy metals were identified, and the degree of their influence was ranked. A categorical regression represents a suitable method for identifying the factors that influence soil heavy metal contents and could be used to study the genetic process of regional soil heavy metal pollution. 相似文献
