沉淀浮选法治理含重金属废水的研究

本文采用沉淀浮选法治理含重金属废水，找到了气浮活性好，来源广泛，价廉，几乎无毒的气浮剂ＡＳ；考察了沉淀浮选法的影响因素，确定了沉淀浮洗法治理含重金属废水的最佳工艺条件，处理实际废水的实验证明，沉淀浮洗法不仅能治理含重金属废水，还十分有效地回收了废水中的有价元素，总金属回收率达９９．２７％，且总金属富集比达１１３．５（倍），此外，还对气浮剂ＡＳ的作用机理进行了探讨，本研究结果对沉淀浮选法治理含重金属     

化学法处理高浓度电镀废水

分析、总结了采用化学法处理高浓度电镀废水中的含氰废水、含镍废水、含铬废水和含酸废水的工程设计、调试和实际运行情况。实践表明,化学法处理高浓度电镀废水是行之有效的,而用PH／ORP计控制好废水处理中的化学反应是稳定运行的关键。     

沉淀浮选法处理矿山含重金属废水技术初探

本文介绍了一种新的废水处理技术－沉淀浮选法处理矿山含重金属废水的性能，并对其净化机理作了探讨，还将其与传统的化学沉淀净化法作了比较，为矿山废水的治理及综合利用指出了一条切实可行的新途径。     

浅析电镀含铜和含镍污泥的资源化回收工艺

电镀污泥中含有大量重金属，属于危险废物，但经恰当处理，对金属进行回收，可产生一定的经济效益和环境效益，其中的铜和镍最具有回收价值。本文简述了电镀含铜和含镍污泥的资源化回收工艺，并对其中的物料平衡和金属平衡作了分析。     

某金铜矿山含铜酸性废水处理研究

采用石灰调pH—铁屑置换—石灰沉淀处理工艺对废水进行试验，结果表明，采用该工艺处理含铜酸性矿山废水，不仅能使处理后的水满足排放标准，同时还能回收废水中的铜。     

含铜制药有机废水的处理研究

通过试验，采用将化学沉淀和生物处理相结合的工艺流程及方法处理含铜有机废水，经处理后的出水Cu^2 符合排放标准。     

含硒废水处理新方法

含硒废水通常采用生物法、絮凝沉淀法和过滤法处理.在生物法中,采用厌氧生物处理来降低原始废液中可溶的硒酸盐与亚硒酸盐,并转化为不溶性的单质硒,从而以不溶性单质硒的形式去除硒酸盐或亚硒酸盐;在絮凝沉淀法中,通常是向生物处理后的废水中加入一种金属盐,使该金属盐与可溶性硒反应并生成一种不溶性硒化合物,从而以不溶性硒化合物形式去除残留的可溶性硒;在过滤法中,将絮凝沉淀法中残留在废水中的不溶性硒去除,这样就能在不用大量化学药剂和不产生大量沉淀的情况下去除含硒废水中的可溶性硒.本文介绍的新工艺出水中硒浓度≤0.1 mg/L,而且处理成本也大大降低.     

XFZ型综合重金属废水处理设备

正由哈尔滨先锋环保设备制造有限公司开发的XFZ型综合重金属废水处理设备,适用于电镀、化工、冶金、酸洗等行业的重金属废水处理。主要技术内容一、基本原理将水轮机中的旋流原理和凝聚沉淀处理技术相结合,使化学药剂与废水充分接触,分子间碰撞机会增     

尾矿库酸性矿山重金属废水处理工程案例分析

某矿区尾矿库采用"二段式石灰—铁盐+混凝沉淀"工艺处理尾矿库渗出的酸性重金属废水,经工程运行结果证明,该工艺可有效去除废水中的铜、砷、镍等重金属离子,处理后出水指标达到广东省《水污染物排放限值》(DB 44/26—2001)第二时段一级标准要求。     

金属废水溶液的中和沉淀净化理论分析

含有害金属废水溶液的中和沉淀净化过程受诸多因素的影响,其中,最重要的有溶液中金属的价态和形态,溶液的离子强度,沉淀物的组成,结构和表面效应等,本文对上述问题作了较全面的理论分析。     

RAINGAGE NETWORK DESIGN USING NEXRAD PRECIPITATION ESTIMATES1

ABSTRACT: A general framework is proposed for using precipitation estimates from NEXRAD weather radars in raingage network design. NEXRAD precipitation products are used to represent space time rainfall fields, which can be sampled by hypothetical raingage networks. A stochastic model is used to simulate gage observations based on the areal average precipitation for radar grid cells. The stochastic model accounts for subgrid variability of precipitation within the cell and gage measurement errors. The approach is ideally suited to raingage network design in regions with strong climatic variations in rainfall where conventional methods are sometimes lacking. A case study example involving the estimation of areal average precipitation for catchments in the Catskill Mountains illustrates the approach. The case study shows how the simulation approach can be used to quantify the effects of gage density, basin size, spatial variation of precipitation, and gage measurement error, on network estimates of areal average precipitation. Although the quality of NEXRAD precipitation products imposes limitations on their use in network design, weather radars can provide valuable information for empirical assessment of rain‐gage network estimation errors. Still, the biggest challenge in quantifying estimation errors is understanding subgrid spatial variability. The results from the case study show that the spatial correlation of precipitation at subgrid scales (4 km and less) is difficult to quantify, especially for short sampling durations. Network estimation errors for hourly precipitation are extremely sensitive to the uncertainty in subgrid spatial variability, although for storm total accumulation, they are much less sensitive.     

PRECIPITATION CHANGES FROM 1956 TO 1996 ON THE WALNUT GULCH EXPERIMENTAL WATERSHED1

ABSTRACT: The climate of Southern Arizona is dominated by summer precipitation, which accounts for over 60 percent of the annual total. Summer and non‐summer precipitation data from the USDA‐ARS Walnut Gulch Experimental Watershed are analyzed to identify trends in precipitation characteristics from 1956 to 1996. During this period, annual precipitation increased. The annual precipitation increase can be attributed to an increase in precipitation during non‐summer months, and is paralleled by an increase in the proportion of annual precipitation contributed during non‐summer months. This finding is consistent with previously reported increases in non‐summer precipitation in the southwestern United States. Detailed event data were analyzed to provide insight into the characteristics of precipitation events during this time period. Precipitation event data were characterized based on the number of events, event precipitation amount, 30‐minute event intensity, and event duration. The trend in non‐summer precipitation appears to be a result of increased event frequency since the number of events increased during nonsummer months, although the average amount per event, average event intensity, and average event duration did not. During the summer “monsoon” season, the frequency of recorded precipitation events increased but the average precipitation amount per event decreased. Knowledge of precipitation trends and the characteristics of events that make up a precipitation time series is a critical first step in understanding and managing water resources in semiarid ecosystems.     

SPATIAL VARIATIONS OF WATER LOSS DURING DROUGH A CASE STUDY1

ABSTRACT: A regional water conservation system for drought management involves many uncertain factors. Water received from precipitation may stay on the ground surface, evaporate back into the atmosphere, or infiltrate into the ground. Reliable estimates of the amount of evapotranspiration and infiltration are not available for a large basin, especially during periods of drought. By applying a geographic information system, this study develops procedures to investigate spatial variations of unavailable water for given levels of drought severity. Levels of drought severity are defined by truncated values of monthly precipitation and daily streamflow to reflect levels of water availability. The greater the truncation level, the lower the precipitation or streamflow. Truncation levels of monthly precipitation are recorded in depth of water while those of daily streamflow are converted into monthly equivalent water depths. Truncation levels of precipitation and streamflow treated as regionalized variables are spatially interpolated by the unbiased minimum variance estimation. The interpolated results are vector values of precipitation and streamflow at a grid of points covering the studied basin. They are then converted into raster‐based values and expressed graphically. The image subtraction operation is used to subtract the image of streamflow from that of precipitation at their corresponding level of drought severity. It is done on a cell‐by‐cell basis resulting in new attribute values to form the spatial image representing a spatial distribution of potential water loss at a given level of drought severity.     

1961—2008年新疆阿克苏地区降水、温度变化特征

利用阿克苏地区5个气象站1961—2008年的降水和温度资料,对近50 a来该地区气候变化及其趋势进行了分析。各气象站年降水量变化趋势基本一致,总体上都呈增加趋势。除库车县气象站年平均温度呈降低趋势外,其余呈上升趋势。总体上,阿克苏地区年降水量和年平均温度均呈上升趋势。     

Application of Wavelet Coherence Method to Investigate Karst Spring Discharge Response to Climate Teleconnection Patterns

The impact of climate teleconnections on the regional hydrometeorology has been well studied, but very little effort has been made to relate climate teleconnections with groundwater flow variation. In this study, we used a wavelet coherence method to analyze monthly climate indices, precipitation, and spring discharge data, and investigated the relation between major teleconnection patterns (the Arctic Oscillation, North Atlantic Oscillation, Pacific Decadal Oscillation, El Niño‐Southern Oscillation, and Indian Ocean Dipole) and karst hydrological process in Niangziguan Springs Basin, China. The results indicate precipitation and spring discharges correlate well with climate indices at intra‐ and inter‐annual time scales. Further, the climate indices are mainly correlated with precipitation at shorter periodicities, but correlated with spring discharge at longer scales. The difference reflects the modulation of karst aquifers on precipitation‐spring discharge during the processes of precipitation infiltration into the ground, and subsequent transformation into spring discharge. When teleconnection signals are transmitted into spring discharge via precipitation infiltration and groundwater propagation, some high‐frequency climatic signals are likely to be filtered, attenuated, and delayed, thus only low‐frequency climatic signals are preserved in spring discharge.     

MEAN AREAL PRECIPITATION FOR DAILY HYDROLOGIC MODELING IN MOUNTAINOUS REGIONS1

ABSTRACT: A procedure using detrended kriging has been developed to calculate daily values of mean areal precipitation (MAP) for input to hydrologic models. The important features of this procedure that overcome weaknesses in existing MAP procedures are: (1) specific precipitation-elevation relationships are determined for each time period as opposed to using relationships based on climatological averages, (2) spatial variability is incorporated by estimating precipitation for each grid cell over a watershed, (3) the spatial correlation structure of precipitation is explicitly modeled, and (4) station weights for precipitation estimates are determined objectively and optimally. Detailed cross-validation testing of the procedure was done for the Reynolds Creek research watershed in southwestern Idaho. The procedure is suitable for use in operational streamflow forecasting.     

ON PRECIPITATION SENSOR NETWORK DENSITIES FOR EVALUATING WINTERTIME OROGRAPHIC CLOUD SEEDING EXPERIMENTS1

Principal component analysis is used to investigate density requirements of wintertime orographic cloud seeding experiment precipitation sensor networks. Three passes in the vicinity of Climax, Colorado are studied. The eighteen or more evenly spaced precipitation sensors of each pass are almost completely described by three principal components. These three principal components appear to represent (i) mean precipitation, (ii) slope orientation to storm systems, and (iii) elevation. Evaluation of these principal components is implemented with two distribution-free tests, a proportionality test and the runs test. The results of this study suggest that the loss of experimental information caused by low density precipitation sensor networks may be of little consequence.     

PRECIPITATION RETENTION AND SOIL EROSION UNDER VARYING CLIMATE,LAND USE,AND TILLAGE AND CROPPING SYSTEMS1

ABSTRACT: Nonirrigated crop yields and forage production are limited by low and variable precipitation in the southern Great Plains. Precipitation variation involves production risks, which can be reduced by considering probability of precipitation, precipitation retention, and soil erosion under various production systems. The objective of this study was to probabilistically quantify the impact of precipitation variations, land use, cropping, and tillage systems on precipitation retention and soil erosion. Five 1.6 ha watersheds that had 3 to 4 percent slopes, and similar silt loam soils were selected. One was kept in native grass, and the others were planted into winter wheat (Triticum aestivum L.) under different cropping and tillage systems. Daily runoff and soil erosion were measured at the outlet of each watershed. Precipitation distributions exhibited great seasonal and interannual variations, and precipitation retention distributions resembled those of precipitation. Cropping and tillage systems affected precipitation retention but much less than did precipitation variations. Available soil water storage, which was largely controlled by ET, played an important role in retaining precipitation. This indicates that cropping systems should be adjusted to precipitation patterns, if predictable, for better soil water use. Land use and cropping and tillage systems had a much greater impact on soil erosion than on precipitation retention. Soil erosion risks, which were proportional to the levels of tillage disturbance, were mainly caused by a few large storms in summer, when surface cover was low. This study explored a novel approach for evaluating production risks associated with insufficient precipitation retention and excessive soil erosion for certain crops or cropping systems under assumed precipitation conditions.     

VARIABILITY CHARACTERISTICS OF MONTHLY PRECIPITATION IN CENTRAL OKLAHOMA1

ABSTRACT: To fully take advantage of regional climate forecast information for agricultural applications, the relationship between divisional and station scale precipitation characteristics must be quantified. The spatial variability of monthly precipitation is assumed to consist of two components: a systematic and a random component. The systematic component is defined by differences in long-term mean precipitation between stations within a climate division, and the random component by differences between station and divisional standardized values. For the Central Climate Division of Oklahoma, the systematic component has a positive precipitation gradient from west to east with a slope ranging between 3 to 16 mm of precipitation per 100 km depending on the month of the year. On the other hand, the random component ranges between 27 to 48 percent of the mean temporal variation of the monthly precipitation. This significant random spatial variability leads to large localized departures from divisional values, and clearly demonstrates the critical influence of the random component in the utilization of divisional climate forecasts for local agricultural applications. The results of this study also provide an uncertainty range for local monthly precipitation projections that are derived from divisional climate information.