Spatial-Temporal Variation of Aridity Index of China during 1960–2013

Aridity index, as the ration of potential evapotranspiration and precipitation, is an important indicator of regional climate. GIS technology, Morlet wavelet, Mann-Kendall test, and principal component analysis are utilized to investigate the spatial-temporal variation of aridity index and its impacting factors in China on basis of climate data from 599 stations during 1960–2013. Results show the following. (1) Boundaries between humid and semihumid region, and semihumid and semiarid region coincide with 400 mm and 800 mm precipitation contour lines. (2) Average annual aridity index is between 3.4 and 7.5 and shows decrease trend with a tendency of –0.236 per decade at 99% confidence level. (3) The driest and wettest month appear in December and July, respectively, in one year. (4) Periods of longitudinal and latitudinal shift of aridity index 1, 1.5, and 4 contours coordinate are 10 and 25 years, 6 and 26 years, and 5 and 25 years, respectively. (5) Four principal components which affect aridity index are thermodynamic factors, water and radiation factors, geographical and air dynamic factors, and evaluation factor, respectively

Correction: Song, J.; Yang, X.; Zhang, J.; Long, Y.; Zhang, Y.; Zhang, T. Assessing the Variability of Heavy Metal Concentrations in Liquid-Solid Two-Phase and Related Environmental Risks in the Weihe River of Shaanxi Province, China. Int. J. Environ. Res. Public Health 2015, 12, 8243-8262.

The authors wish to make the following corrections to this paper [1]. [...

Statistical Distribution of Streambed Vertical Hydraulic Conductivity along the Platte River, Nebraska

Streambed vertical hydraulic conductivity (Kv) plays an important role in understanding and quantifying the stream–aquifer interactions. While several researchers have discussed the spatial variability of streambed horizontal hydraulic conductivity or Kv at one or several close-located sites in a river, they did not develop any statistical distribution analysis of streambed Kv at distant sites along a large river. In this paper, the statistical distribution and spatial variation of streambed Kv at 18 test sites in a 300-km reach of the Platte River in Nebraska are presented. Insitu permeameter tests using the falling-head method were carried out to calculate the streambed Kv values. Fine-grained sediments transported by two tributaries, the Loup River and the Elkhorn River, to the Platte River appear to result in lower streambed Kv values downstream of the confluences between the Platte River and the tributaries. The streambed Kv values were found to be normally distributed at nearly each test site. When the correlated Kv values were eliminated from the grid sampling plots, the remaining independent sub-datasets of streambed Kv values were still in normal distribution at each test site. Furthermore, the combined streambed Kv values upstream of the first confluence between the Platte River and the Loup River was normally distributed, which may be due to the lack of tributaries in-between and thus streambed sediments were well distributed in this reach and belonged to a single population of hydraulic conductivity values. In contrast, the combined dataset of all measurements conducted downstream of this confluence was no longer in normal distribution, presumably as a result of the mixing of different sediment sources

Characterization of Particle and Gaseous Emissions from Marine Diesel Engines with Different Fuels and Impact of After-Treatment Technology

The International Maritime Organization (IMO) Marine Environment Protection Committee (MEPC) and some countries have gradually strengthened the laws regulating ship exhaust emissions. The aim of this paper is to estimate the impact of an after-treatment technology exhaust gas cleaning (EGC) system on marine diesel engine emissions and the cost advantage compared to using low-sulfur fuel oil. The emission characteristics of SO2 and particulate matter (PM) produced from high sulfur oil and low sulfur oil in a low-speed two-stroke marine diesel engine were also presented. The removal efficiency of SO2 has been tested and the PM removal efficiency was also predicted in this study. When using high sulfur oil, the emission factor of SO2 and PM were from 8.73 g/kWh to 11.6 g/kWh and 2.0 g/kWh to 2.7 g/kWh, respectively. These values are significantly higher than the emission values from using low sulfur oil. The fuel sulfur content (FSC) was the key factor affecting the emission factors of SO2 and PM. The fuel change could reduce the mass emission factor of PM, which is above 90% for the total particle emission with the two fuels. When using the EGC system, the desulfurization efficiencies were above 99%. The pH values at a 25, 39, 53, and 67% load were also stabilized to be around 7.5, 7.6, 7.7, and 8, respectively. The EGC system can also capture part of the primary PM and secondary PM formed from SO2. The EGC system was more effective for PM of the size larger than 1 μm. Thus, according to this study, the usage of low sulfur oil and EGC will also substantially decrease the emission of currently unregulated hazardous chemical species in the exhaust gas of ships in addition to satisfying future emissions regulations of ship. Furthermore, the EGC system also had a significant cost advantage compared to using low-sulfur fuel oil

Fractal analysis of relation between strength and pore structure of hardened mortar

© 2016 Elsevier Ltd The pore structure is the fatal factor which influences the strength of cement mortar and concrete. A lot of researches on the relationship between the strength and the pore structure were developed. Initially, porosity is the only factor in the strength models. As the development of research, it is illustrated that the pore size distribution also has significant effect on the strength. The pore size distribution is taken into consideration in the strength model in different forms. However, these models are still unavailable to simulate the relationship between strength and pore structure, because the parameters used for representing the pore size distribution are not accurate enough. In the present research, strength and pore structure were tested on thirteen Portland cement mortar mixtures to collect the original data of the strength and pore structure. In order to enhance the reliability of the strength model, the pore volume and the pore size distribution were all considered. The fractal theory was employed to characterize the pore size distribution more accurately than ever used parameters. According to the regression analysis results, the fractal dimension of pore surface and the capillary pore volume were respectively selected as representative parameters of pore size distribution and pore volume. The research results indicate that the relations between strength and fractal dimension and capillary pore volume present positive power function and negative power function respectively. The ratio of fractal dimension to capillary pore volume is addressed as the new parameter for strength model. Finally, relational expression of power function is proposed between the compressive strength and the ratio of fractal dimension to capillary pore volume. Regression analysis indicates that the strength model relative to pore structure addressed in this study has high prediction accuracy

Simulating and predicting river discharge time series using a wavelet-neural network hybrid modelling approach

Accurate simulation and prediction of the dynamic behaviour of a river discharge over any time interval is essential for good watershed management. It is difficult to capture the high-frequency characteristics of a river discharge using traditional time series linear and nonlinear model approaches. Therefore, this study developed a wavelet-neural network (WNN) hybrid modelling approach for the predication of river discharge using monthly time series data. A discrete wavelet multiresolution method was employed to decompose the time series data of river discharge into sub-series with low (approximation) and high (details) frequency, and these sub-series were then used as input data for the artificial neural network (ANN). WNN models with different wavelet decomposition levels were employed to predict river discharge 48 months ahead of time. Comparison of results from the WNN models with those of the ANN models alone indicated that WNN models performed a more accurate prediction

Application of Nitrogen and Oxygen Isotopes for Source and Fate Identification of Nitrate Pollution in Surface Water: A Review

Nitrate pollution in surface water has become an environmental problem of global concern. The effective way for controlling the nitrate pollution of surface water is to identify the pollution source and reduce the input of nitrate. In recent decades, nitrogen (δ15N) and oxygen (δ18O) isotopes of nitrate has been used as an effective approach for identifying the source and fate of nitrate pollution in surface water. However, owing to the complexity of nitrate pollution source and the influence of isotopic fractionation, the application of this method has some limitations. In this work, we systematically discussed the fundamental principle of using nitrogen and oxygen isotopes to trace the nitrate source, the fate identification of nitrate, and the major testing techniques. Subsequently, the applications of nitrogen and oxygen isotopes for source identification of surface water were illustrated. However, there are still significant gaps in the application of the source identification and transformation mechanisms to nitrate and many research questions on these topics need to be addressed

Interactive Influence of Soil Erosion and Cropland Revegetation on Soil Enzyme Activities and Microbial Nutrient Limitations in the Loess Hilly-Gully Region of China

Soil erosion is a major form of land degradation, especially in agroecosystems, which has been effectively controlled by vegetation restoration. However, the interactive role of erosion and cropland revegetation on soil enzyme activities and microbial nutrient limitations is less understood. To address this issue, we examined carbon (C), nitrogen (N), and phosphorus (P) in bulk soils and microbial biomass, enzyme activities, and microbial nutrient limitations in the 0–200 cm soils in eroded and deposited landscapes occupied by cropland, revegetated forest, and grassland. The results showed that the activities of C-, N-, and P-acquiring enzymes were larger in the deposited landscape than in the eroded landscape for 0–20 cm soils in forest and grassland but not in cropland. Microbial metabolism was co-limited by N and P, and the threshold element ratio (TERL) indicated that P was the most limiting factor. Microbial N limitation was lower in the deposited than the eroded zone, especially in surface soils in revegetated forest and grassland. The TERL value was larger at the deposited than at the eroded zone, and a greater difference was found in the surface soils of forest and grassland. Microbial nutrient limitations were mostly explained by C/P and N/P. Conclusively, the deposited areas were characterized by ameliorated enzyme activities, decreased microbial N limitation but relatively strengthened microbial P limitation compared to the eroded area, and such variations existed in the revegetated forest and grassland but not in the cropland, which thus contributes to a better understanding of C and nutrient cycling for agroecosystems and revegetation ecosystems in eroded environments