Size, morphology, and composition of airborne particles strongly affect human health and visibility, precipitation, and the kinetic characteristics of particles. In this study, the morphology and chemical composition of particles emitted from conventional (diesel and gasoline) and alternative (CNG and methanol) fuel vehicles were characterized through scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX). The SEM images revealed that the size of primary particles (without agglomeration) was approximately 10 nm in the exhaust from all the tested vehicles. The particles emitted from gasoline vehicle (GV), CNG vehicle (CNGV), and methanol vehicle (MV) had the same median diameter, 62 nm, which was smaller than those from heavy diesel vehicle (HDV) and light diesel vehicle (LDV). Soot was observed in the HDV, LDV, and GV samples but not in the CNGV and MV. The fractal dimension, which was used to quantify the degree of irregularity of soot, was 1.752 ± 0.014, 1.789 ± 0.076, and 1.769 ± 0.006 in the exhaust from HDV, LDV, and GV samples, respectively. The particles discharged by all tested vehicles contained the elements C, O, Fe, and Na. The main element in the samples of HDV, LDV, and GV was C, while O was the main element in the samples of alternative fuel vehicles. The profiles of minor elements were more complex in the emissions of alternative fuel vehicles than those in the emissions of conventional fuel vehicles. The results improved our understanding of the morphology and elemental composition of particles emitted from vehicles powered by diesel, gasoline, CNG, and methanol.
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Surface sediments were collected from 122 sites in the upstream of the Yellow River, China. The concentration of Fe, Mn, Cu, Ni, Zn, Cr, Pb, and Cd in sediments was investigated to explore the spatial distribution based on statistics and interpolation method. The results suggested that the concentrations of heavy metals were lower than potential effect levels (PEL). The samples above threshold effect level (TEL) for Pb and Zn were less than 10%, while almost 50% of samples for Ni exceeded PEL. Pb and Zn in sediments performed little or no adverse effects on the aquatic ecosystems. Higher concentrations of all heavy metals occurred in Qinghai and Gansu sections; the concentrations of Cu, Ni, and Zn were significantly higher than the Inner Mongolia section. Lower concentration of Fe, Mn, Cu, Ni, and Zn appeared in Qinghai section; the concentrations of Fe, Mn, Cr, and Pb manifested relatively steady and similar distributions and approximately decreasing tendency along the upstream of Yellow River.
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土壤酶能反映土壤生物化学过程的强度与方向,深入解析土壤酶活性与环境因子的相关性,有助于探索土壤生态过程,为开展土壤系统的科学调控提供科学依据.以塔里木河上游阿拉尔垦区为研究区,选择新开棉田、10 a棉田、30 a棉田、果园、人工林、天然林、荒草地、盐碱地及沙地等不同土地利用类型为研究对象,运用经典统计学分析绿洲土壤酶活性及环境因子的分异规律,并结合冗余分析技术研究土壤酶活性与环境因子相关关系.经典统计学分析显示,土壤过氧化氢酶、脲酶、转化酶、碱性磷酸酶活性均值分别为4.27 m L·g-1、0.34 mg·g-1、2.08 m L·g-1、0.08 mg·g-1.冗余分析结果表明:全氮、有机质、有效磷、土壤含水量、全盐与土壤酶活性呈极显著相关性(P0.01);土壤容重与土壤酶活性表现为显著相关性;其他环境因子与土壤酶活性的相关性均不显著(P0.05).环境因子与土壤酶活性相关性大小排序为全氮有机质有效磷土壤含水量全盐容重速效钾p H. 相似文献