ABSTRACT
The impact of Ba-modified peanut shell biochar (Ba-PSB) on Pb(II) removal was studied and BaCl2 was used as a modifier. It was shown that the PSB obtained at 750 °C had the best adsorption effect, and the Ba-PSB had a larger specific surface area and a good adsorption effect on Pb(II). At pH = 5, concentration was 400 mg/L, time was 14 h, and temperature was 55 °C, the loading amount of black peanut shell biochar (BPSB), red peanut shell biochar (RPSB), Ba-BPSB, and Ba-RPSB reached 128.050, 98.217, 379.330, and 364.910 mg/g, respectively. In addition, based on the non-linear fitting, it was found that the quasi-second-order kinetic model, and isothermal model could be applied to describe Pb(II) adsorption on PSB and Ba-PSB. The adsorption behavior of PSB unmodified and modified was a spontaneous process. Moreover, chemical modification of BPSB, RPSB, Ba-BPSB, and Ba-RPSB for hindering of -COOH and -OH groups revealed 81.81, 77.08, 86.90, and 83.65% removal of Pb(II), respectively, which was due to the participation of -COOH, while 17.61, 21.70, 12.77, and 15.06% was from -OH group, respectively. The increase of cation strength (Na+, K+, Ca2+, and Mg2+) will reduce the adsorption capacity of PSB for Pb(II).
Subject(s)
Arachis , Water Pollutants, Chemical , Lead , Adsorption , Water , Charcoal , Water Pollutants, Chemical/analysis , KineticsABSTRACT
Pine wilt disease has caused huge losses in ecological and economic values in China, especially in the southern parts. Analyzing the spatial distribution of pine wilt disease and quantifying the impact of environmental factors on its occurrence were of great significance for its prevention and control. In this study, we examined the spatial pattern of pine wilt disease occurrence and its response to environmental variables in Nankang District, Ganzhou, Jiangxi Province, using kernel-smoothing density, Ripley's K function, and point process model. The results showed that the occurrence of pine wilt disease in the study region was not randomly distributed, but was obviously clustered at some areas. Terrain, vegetation, and human activity were the main factors affecting the heterogeneous distribution of pine wilt disease. Spatial point pattern analysis showed that altitude, slope, distance to the nearest road, road density, distance to nearest settlement, canopy closure, and vegetation type had significant effects on the occurrence of pine wilt disease. In addition to strengthening the control of disease transmission caused by human activities, we should also consider the effects of terrain and vegetation types for early warning and monitoring in forest disease management.
Subject(s)
Pinus , China/epidemiology , Humans , Spatial AnalysisABSTRACT
The distribution pattern of forest fuel loading is driven by the interaction of environmental factors, such as terrain and vegetation. Based on field sampling data of surface dead fuels of seven main forest types in southern Jiangxi Province, and according to the classification standard of different time-lags, we constructed structural equation models to explore the relationship between surface fuel loadings and environmental factors such as terrain and vegetation etc. We analyzed the influence path of each factor and its direct, indirect, and total influence. The results showed that the coniferous and broad-leaved mixed forest had the highest loadings and the Phyllostachys heterocycla pure forest had the lowest loadings for all the 1, 10, and 100 h time-lag fuels. The influencing coefficient of environmental factors for 1 h time-lag fuels were ranked as: slope (0.40) > crown height (0.07) > tree species (-0.03) > canopy closure (0.01). For the 10 h time-lag fuels, the environmental factors were ranked as: diameter at breast height (0.15) >tree species (-0.09) > aspect (-0.08) > canopy closure (-0.06). For the 100 h time-lag fuels, the environmental factors were ranked as: aspect (0.25) > diameter at breast height (0.19) > canopy closure (-0.08) > tree species (0.02). The influencing coefficient of environmental factors for the total fuels were ranked as: slope (0.22) > tree species (-0.04), canopy closure (-0.04) > crown height (-0.01).
Subject(s)
Forests , Tracheophyta , China , Models, Theoretical , TreesABSTRACT
Specific detection of tumors is of pivotal importance to cancer prevention and therapy yet a big challenge. Photoacoustic imaging (PAI) as an emerging non-invasive modality has shown great potential in biomedical and clinical applications. The performance of PAI largely depends on the light-absorption coefficient of the imaged tissue and the PAI contrast agent being used, either endogenously or exogenously. The exogenous contrast agents developed so far have greatly helped to improve PAI, but still have some limitations, such as lack of targeting capacity and easy clearance by the host immune system. Herein, we fabricated a biomimetic nanoprobe with cell membrane coating as a novel PAI contrast agent, namely, MPD [membrane-coated poly(lactic-co-glycolic acid) (PLGA)/dye]. In brief, the organic dye 1,1'-dioctadecyl-3,3,3',3'-tetramethylindotricarbocyanine iodide (DiR) was encapsulated by the Food and Drug Administration-approved polymer, poly(lactic-co-glycolic acid) (PLGA), to form polymer nanoparticles by emulsification. The nanoparticles are further coated with the cancer cell membrane to form MPD. MPD has outstanding biocompatibility, tumor specificity, and in vivo stability. Thus, MPD is a versatile NIR-I theranostic nanoplatform for PAI-guided cancer diagnosis and therapy.
