Sb release characteristics of the solid waste produced in antimony mining smelting process

Sb release characteristics of blast furnace slag, mining waste rock and tailing sand were investigated in static immersion and dynamic leaching test. These three kinds of waste samples were collected from the antimony mine in Lengshuijiang, China, produced in mining smelting process. Effects of solid/liquid ratio, sample size and pH of leaching solution on Sb release characteristics were inspected based on the analysis of scanning electron microscope, pH and EC of leachate. The optimal parameters for Sb leaching of each sample were analyzed. For blast furnace slag and mining waste rock, Sb release contents increased along with the decline of solid/liquid ratio. The maximum accumulative release contents were 42.13, 34.26 mg/kg at the solid/liquid ratio of 1:20. While Sb release content for tailing sand decreased first and then increased with the reduction of solid/liquid ratio. When the solid/liquid ratio was 1:5, the accumulative Sb release content reached the most (24.30 mg/kg). Sb release content of mining waste rock increased with the drop of leaching solution pH, with the highest accumulative release content of 26.01 mg/kg at pH 2.0. Sb release contents of blast furnace slag and tailing sand showed positive correlation with the variation of leaching solution pH. The maximum accumulative release contents of these two samples were 215.91 and 147.83 mg/kg, respectively, when leaching solution pH was 7.0. In summary, Sb release capacity of the three samples in descending order was tailing sand, blast furnace slag and mining waste rock. pH and EC of the leachate in dynamic test varied independently with the initial pH of leaching solution while showing close relationship with mineral hydrolysis in the waste.     

Current status and historical variations of phthalate ester (PAE) contamination in the sediments from a large Chinese lake (Lake Chaohu)

The residual levels of phthalate esters (PAEs) in the surface and two core sediments from Lake Chaohu were measured with a gas chromatograph–mass spectrometer (GC–MS). The temporal–spatial distributions, compositions of PAEs, and their effecting factors were investigated. The results indicated that di-n-butyl phthalate (DnBP), diisobutyl phthalate (DIBP), and di(2-ethylhexyl) phthalate (DEHP) were three dominant PAE components in both the surface and core sediments. The residual level of total detected PAEs (∑PAEs) in the surface sediments (2.146?±?2.255 μg/g dw) was lower than that in the western core sediments (10.615?±?9.733 μg/g) and in the eastern core sediments (5.109?±?4.741 μg/g). The average content of ∑PAEs in the surface sediments from the inflow rivers (4.128?±?1.738 μg/g dw) was an order of magnitude higher than those from the lake (0.323?±?0.093 μg/g dw), and there were similar PAE compositions between the lake and inflow rivers. This finding means that there were important effects of PAE input from the inflow rivers on the compositions and distributions of PAEs in the surface sediments. An increasing trend was found for the residual levels of ΣPAEs, DnBP, and DIBP from the bottom to the surface in both the western and eastern core sediments. Increasing PAE usage with the population growth, urbanization, and industrial and agricultural development in Lake Chaohu watershed would result in the increasing production of PAEs and their resulting presence in the sediments. The significant positive relationships were also found between the PAE contents and the percentage of sand particles, as well as TOC contents in the sediment cores.     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

Trends and variations of pH and hardness in a typical semi-arid river in a monsoon climate region during 1985–2009

The rapid growth of urbanization and industrialization, along with dramatic climate change, has strongly influenced hydrochemical characteristics in recent decades in China and thus could cause the variation of pH and general total hardness of a river. To explore such variations and their potential influencing factors in a river of the monsoon climate region, we analyzed a long-term monitoring dataset of pH, SO₄ ^2?, NO_x, general total hardness (GH), Mg²⁺, Ca²⁺, and Cl^? in surface water and groundwater in the Luan River basin from 1985 to 2009. The nonparametric Seasonal Kendall trend test was used to test the long-term trends of pH and GH. Relationship between the affecting factors, pH and GH were discussed. Results showed that pH showed a decreasing trend and that GH had an increasing trend in the long-term. Seasonal variation of pH and GH was mainly due to the typical monsoon climate. Results of correlation analysis showed that the unit area usage amounts of chemical fertilizer, NO₃ ^?, and SO₄ ^2? were negatively correlated with pH in groundwater. In addition, mining activity affected GH spatial variation. Acid deposition, drought, and increasing the use of chemical fertilizers would contribute to the acidification trend, and mining activities would affect the spatial variation of GH. Variations of precipitation and runoff in semi-arid monsoon climate areas had significant influences on the pH and GH. Our findings implied that human activities played a critical role in river acidification in the semi-arid monsoon climate region of northern China.     

Vehicle emission implications of drivers’ smart advisory system for traffic operations in work zones

Wireless communication systems have been broadly applied in various complicated traffic operations to improve mobility and safety on roads, which may raise a concern about the implication of the new technology on vehicle emissions. This paper explores how the wireless communication systems improve drivers’ driving behaviors and its contributions to the emission reduction, in terms of Operating Mode (OpMode) IDs distribution used in emission estimation. A simulated work zone with completed traffic operation was selected as a test bed. Sixty subjects were recruited for the tests, whose demographic distribution was based on the Census data in Houston, Texas. A scene of a pedestrian’s crossing in the work zone was designed for the driving test. Meanwhile, a wireless communication system called Drivers Smart Advisory System (DSAS) was proposed and introduced in the driving simulation, which provided drivers with warning messages in the work zone. Two scenarios were designed for a leading vehicle as well as for a following vehicle driving through the work zone, which included a base test without any wireless communication systems, and a driving test with the trigger of the DSAS. Subjects’ driving behaviors in the simulation were recorded to evaluate safety and estimate the vehicle emission using the Environmental Protection Agency (EPA) released emission model MOVES. The correlation between drivers’ driving behavior and the distribution of the OpMode ID during each scenario was investigated. Results show that the DSAS was able to induce drivers to accelerate smoothly, keep longer headway distance and stop earlier for a hazardous situation in the work zone, which driving behaviors result in statistically significant reduction in vehicle emissions for almost all studied air pollutants (p-values range from 4.10E-51 to 2.18E-03). The emission reduction was achieved by the switching the distribution of the OpMode IDs from higher emission zones to lower emission zones.

Implications: Transportation section is a significant source of greenhouse gas emissions. Many studies demonstrate that the wireless communication system dedicated for safety and mobility issues may contribute to the induction in vehicle emissions through changing driving behaviors. An insight into the correlation between the driving behaviors and the distribution of Operating Mode (OpMode) IDs is essential to enhance the emission reduction. The result of this study shows that with a Drivers Smart Advisory System (DSAS) drivers accelerated smoothly and stopped earlier for a hazardous situation, which induce the switch of the OpMode IDs from high emission zones to lower emission zones.     

三峡库区消落带水淹初期主要优势草本植物生态位变化特征

根据三峡库区初期水位涨落情况,以空间代替时间法,连续两年对典型消落带区域地上植被进行调查,通过计算生态位宽度和生态位重叠来分析不同水淹时间下优势草本植物生态位的变化特征。结果表明,一年水淹区段在未水淹时,植物生态位宽度普遍较窄,此时生态位明显特化,而第二年水淹极大的增加了适应干湿变化的物种的优势度。水淹前生态位重叠值大于0.5的只有12对,小于0.2种对为189对,其中生态位重叠值为零的为103对;水淹后生态位重叠值大于0.5的有24对,小于0.2种对为53对,其中生态位重叠值为零的为6对,说明生境由干燥到湿润的变化,对湿润环境相对适应的物种存活,优势植物生态位重叠明显增加。经两年水淹区段中,第一年以毛马唐的生态位宽度最高,其余17种物种生态位宽度小于0.2的物种占优势物种的61%,第二年以雾水葛和鳢肠的生态位宽度较大,其余15种物种生态位宽度小于0.2的物种占优势物种的50%,共同出现的物种仅有8种。生态位重叠值大于0.5的种对由5对上升到17对,生态位重叠值为零的种对由10对减低到2对,说明连续水淹产生更加均一的生境类型,对资源要求相似的物种是增加的。     

南方丘陵地区河谷城市用地时空演变与驱动分析——以上饶市城区为例

以揭示中国南方丘陵地区河谷城市的空间演变过程和特征为目的,以上饶市城区为例,在遥感与GIS技术的支持下,对1988~2013年间上饶市城区城市用地的时空演变过程、特征及驱动影响因素进行了研究。结果表明,1988~2013年的25 a间,上饶市城区城市用地呈现出快速增长的态势,城市形态的演变具有明显的时空特征:时间序列上,不论扩展幅度还是扩展速度,2001~2013年间的值均高于1988~2001年间的值,前后两个时段的扩展特征呈现出明显的差异性;空间格局上,上饶市城区以老城区的中心广场为中心向四周扩展,先后经历了放射性扩展、组团式分散扩展两个阶段,同时呈现出明显的方向分异性,西南和西为其主要扩展方向,而其东南方向的扩展速度最为缓慢。自然环境中的地貌对上饶市城区城市用地的扩展起到很大的限制作用,经济社会的发展、政策规划等因素成为城市用地扩张与时空演化的外在驱动因素。     

Plasticity in metamorphic traits of <Emphasis Type="Italic">Rana kukunoris</Emphasis> tadpoles: The interactive effects of food level and rearing temperature

Larval amphibians are particularly likely to encounter variation in rearing temperature and resource availability due to variation in aquatic breeding habitats. In this study, plasticity in growth rates, larval mass, larval period, and size at metamorphosis were examined in Rana kukunoris Nikolskii, 1918 under different combinations of temperature and food level. Larval period and larval body mass was sensitive to food level, and varied with temperature. Tadpoles metamorphosed at an older age at low temperature than those reared at warm temperature. Food level was a significant affect on larval period at low temperature, but not at warm temperature. Mass was heavier for tadpoles reared at low temperatures than those reared at warm temperatures. The effect of food level depended on temperature, because larvae reared at low temperature that were offered a high food level achieved a larger size than larvae offered a low food level, but this did not occur at warm temperature. Therefore, we suggest that high food availability at low temperature prolonged developmental periods, thus larvae are larger as metamorphs than those reared at warm temperatures.