Zn/Fe体系湿法催化氧化高效脱除沼气中H2S的研究

提出了Zn/Fe体系湿法催化氧化脱除沼气中H2S新工艺,阐述了反应机理、实验装置和工艺流程,考察了各单因素操作条件对H2S脱除效率的影响,在此基础上进行的综合条件实验,脱硫效率都维持在99.6%以上,净化后沼气中H2S含量低于国家标准。过程不消耗任何化工原料,不产生二次污染,体系无降解问题。     

城市污水厂初沉池的设置方式及运行效果

跟据初沉池在城市污水厂长期的实际运行数据,分析了初沉池去除污水中的悬浮物、有机物、降低能耗、降低水质波动对生化系统的冲击等方面所起的作用,设置初沉池还有利于提高生化系统污泥的活性成份（MLVSS／MLSS）、增强出水效果;同时探讨了初沉池在城市污水处理中的设置方式,通过设置超越管线,在冬、夏季水质波动较大,保持生化系统进水有机负荷的稳定,提出了优化初沉池的处理效果的运行方式。     

Effect of Earthworm(Pheretima sp.) Density on Revegetation of Lead/zinc Metal Mine Tailings Amended with Soil

Abstract

The objective of this study was to investigate the effects of earthworm density on the availability of nutrients and heavy metals in metal contaminated soils. Pb/Zn mine tailings were mixed throughly with a red yellow podzolic soil at the ratio (w/w) of 75:25. Earthworms (Pheretima sp.) were introduced to the mixture at four different densities, zero, three, six and nine individuals per pot planted with ryegrass (Loliun multiflorum). The results indicated that earthworm activity significantly enhanced ryegrass shoot biomass. However, as denser earthworm population was introduced, shoot biomass tended to decrease. Earthworm activity significantly increased soil pH and availability of N, P and K in the tailings and soil mixture. There was a general tendency that uptake of Zn by ryegrass increased after earthworm inoculation, although the increase in extractable Zn in tailings and soil mixture was not significant. On the contrary, there seemed to be a lower uptake of Pb by ryegrass under earthworm inoclation, despite the fact that higher extractable Pb concentrations were observed. The present project indicated that the improved growth of ryegrass was due to improved nutrient availability and other soil conditions, by inoculation of earthworms at an appropriate rate. Further studies are needed to illustrate the relationship between metal availability and earthworm activity in the field.     

钢铁生产行业二英污染特征变化及其排放因子

对我国某省多家钢铁生产企业烧结工序和电炉工序排放烟气中二英（PCDD/Fs）污染水平、排放特征及其排放因子进行了初步研究.结果表明,烧结工序PCDD/Fs毒性当量浓度（以I-TEQ计,下同）为0.003~0.557 ng·m^-3,均值为0.165 ng·m^-3;电炉工序PCDD/Fs毒性当量浓度为0.006~0.057 ng·m^-3,均值为0.025 ng·m^-3.PCDD/Fs毒性当量浓度水平总体较低,较2005~2019年研究报道结果下降1~2个数量级.2005~2020年,钢铁生产行业排放PCDD/Fs毒性当量浓度水平先升高后降低,尤其是新的标准限值实施以及对烟尘等常规污染物进行超低排放控制后,呈现大幅下降.指纹谱图特征显示,所有烟气样品17种PCDD/Fs中最大浓度贡献单体为2,3,7,8-TCDF,与已有研究中以高氯代PCDFs和PCDDs为主不同,且低氯代PCDFs占比有所增加,表明PCDD/Fs生成主要来源有所变化.烧结工序和电炉工序PCDD/Fs同类物指纹分布特征相似,呈现典型的高温热过程特征,两个工序生产过程中PCDD/Fs的生成机制可能均为"从头合成".钢铁生产企业烧结工序PCDD/Fs废气排放因子（以I-TEQ计,下同）为0.003~0.5 μg·t^-1,排放因子平均值为（0.18±0.22）μg·t^-1;电炉工序PCDD/Fs废气排放因子为0.04~0.5 μg·t^-1,排放因子平均值为（0.27±0.23）μg·t^-1;低于UNEP于2013发布的"二英和呋喃排放识别和量化标准工具包"以及2004年我国二英排放清单中的排放因子,建议对我国钢铁生产行业PCDD/Fs排放状况开展调查,更新排放因子.     

A practical real option methodology for the evaluation of farm-in/out joint venture agreements in mineral exploration

Although the “real option valuation” (ROV) methodology offers extremely valuable insights in optimising investment decisions in the face of uncertainty, its practical acceptance in the mining industry has until recently been slow because of its perceived computational complexity. Recent conceptual advances in the use of binomial lattices and software developments in the areas of decision trees and dynamic programming, have significantly simplified ROV analysis and made it of practical application in day-to-day financial evaluations and decisions involving uncertainty. This paper provides general background on the ROV methodology and an example of how a typical farm-in/out agreement, as a preliminary to the establishment of a joint venture (JV), can be valued as a series of sequential and compound real options. For illustrative and quality assurance purposes, a simple farm-in/out agreement is valued from the point of view of the party acquiring equity in the project (the farm-inee) using two distinct methods, i.e. (a) a binomial lattice and (b) a decision tree in combination with binomial stochastic processes, in both cases neutralising risk using the user-friendly “risk-neutral probability”. The fact that exactly the same ROV is obtained by both methods provides confidence in the modified decision tree approach, which opens up the capacity to value the more complex sequential/compound real options inherent in real-life farm-in/out agreements. The model is then modified to incorporate a number of realistic contractual conditions often encountered in typical exploration and mining farm-in/out deals. The paper demonstrates how the increased complexity of the model can be relatively easily addressed using a decision tree with dynamic programming capability.     

Optimizing model for land use/land cover retrieval from remote sensing imagery based on variable precision rough sets

The suitable spectral mode in remote sensing is often desirable to facilitate the inversion of ecological environment and landscape. This paper put forward an optimizing model based on variable precision rough sets (VPRS) for the land cover discrimination in wetland inventory. In the case study of Lake Baiyangdian which has important ecological functions to the northern China, this model is established successfully according to the domain-experts knowledge. The procedure is as follows. First step is data collection, including remote-sensing data (e.g., Landsat-5 TM bands), the digitized relief maps, and statistical yearbooks. Second, the remote sensing imagery (RSI) and relief maps are co-registered into the same resolution. Third, a condition set, including various attributes is derived from spectral bands, band math or ratio indices based on previous studies, at the same time, the decision set is derived from true land types after investigation and validation. Then, the remote sensing decision table (RSDT) is constructed by linking condition set with decision set according to the sequential pixels in RSI. Fourth, we create one forward greedy searching algorithm based on VPRS to handle this RSDT. After adjusting parameters such as β and knowledge granularity diameter (KGD), we obtain the stable optimized results. Comparative experiments and evaluation show that the discrimination or retrieval accuracy of VPRS model is satisfying (overall accuracy: 87.32% and KHAT: 0.84) and better than original data. Moreover, data dimension has been decreased dramatically (from 12 to 3) and key attributes found by the model may be useful for specific retrieval in wetland inventories.     

A Multi‐Agency Nutrient Dataset Used to Estimate Loads,Improve Monitoring Design,and Calibrate Regional Nutrient SPARROW Models1

Saad, David A., Gregory E. Schwarz, Dale M. Robertson, and Nathaniel L. Booth, 2011. A Multi‐Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models. Journal of the American Water Resources Association (JAWRA) 47(5):933‐949. DOI: 10.1111/j.1752‐1688. 2011.00575.x Abstract: Stream‐loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long‐term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water‐quality model, the flow‐bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water‐quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.     

Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States1

Preston, Stephen D., Richard B. Alexander, Gregory E. Schwarz, and Charles G. Crawford, 2011. Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States. Journal of the American Water Resources Association (JAWRA) 47(5):891‐915. DOI: 10.1111/j.1752‐1688.2011.00577.x Abstract: We compared the results of 12 recently calibrated regional SPARROW (SPAtially Referenced Regressions On Watershed attributes) models covering most of the continental United States to evaluate the consistency and regional differences in factors affecting stream nutrient loads. The models – 6 for total nitrogen and 6 for total phosphorus – all provide similar levels of prediction accuracy, but those for major river basins in the eastern half of the country were somewhat more accurate. The models simulate long‐term mean annual stream nutrient loads as a function of a wide range of known sources and climatic (precipitation, temperature), landscape (e.g., soils, geology), and aquatic factors affecting nutrient fate and transport. The results confirm the dominant effects of urban and agricultural sources on stream nutrient loads nationally and regionally, but reveal considerable spatial variability in the specific types of sources that control water quality. These include regional differences in the relative importance of different types of urban (municipal and industrial point vs. diffuse urban runoff) and agriculture (crop cultivation vs. animal waste) sources, as well as the effects of atmospheric deposition, mining, and background (e.g., soil phosphorus) sources on stream nutrients. Overall, we found that the SPARROW model results provide a consistent set of information for identifying the major sources and environmental factors affecting nutrient fate and transport in United States watersheds at regional and subregional scales.     

A Perspective on Nonstationarity and Water Management1

Hirsch, Robert M., 2011. A Perspective on Nonstationarity and Water Management. Journal of the American Water Resources Association (JAWRA) 47(3):436‐446. DOI: 10.1111/j.1752‐1688.2011.00539.x Abstract: This essay offers some perspectives on climate‐related nonstationarity and water resources. Hydrologists must not lose sight of the many sources of nonstationarity, recognizing that many of them may be of much greater magnitude than those that may arise from climate change. It is paradoxical that statistical and deterministic approaches give us better insights about changes in mean conditions than about the tails of probability distributions, and yet the tails are very important to water management. Another paradox is that it is difficult to distinguish between long‐term hydrologic persistence and trend. Using very long hydrologic records is helpful in mitigating this problem, but does not guarantee success. Empirical approaches, using long‐term hydrologic records, should be an important part of the portfolio of research being applied to understand the hydrologic response to climate change. An example presented here shows very mixed results for trends in the size of the annual floods, with some strong clusters of positive trends and a strong cluster of negative trends. The potential for nonstationarity highlights the importance of the continuity of hydrologic records, the need for repeated analysis of the data as the time series grow, and the need for a well‐trained cadre of scientists and engineers, ready to interpret the data and use those analyses to help adjust the management of our water resources.     

Examining Flood Frequency Distributions in the Midwest U.S.1

Villarini, Gabriele, James A. Smith, Mary Lynn Baeck, and Witold F. Krajewski, 2011. Examining Flood Frequency Distributions in the Midwest U.S. Journal of the American Water Resources Association (JAWRA) 47(3):447‐463. DOI: 10.1111/j.1752‐1688.2011.00540.x Abstract: Annual maximum peak discharge time series from 196 stream gage stations with a record of at least 75 years from the Midwest United States is examined to study flood peak distributions from a regional point of view. The focus of this study is to evaluate: (1) “mixtures” of flood peak distributions, (2) upper tail and scaling properties of the flood peak distributions, and (3) presence of temporal nonstationarities in the flood peak records. Warm season convective systems are responsible for some of the largest floods in the area, in particular in Nebraska, Kansas, and Iowa. Spring events associated with snowmelt and rain‐on‐snow are common in the northern part of the study domain. Nonparametric tests are used to investigate the presence of abrupt and slowly varying changes. Change‐points rather than monotonic trends are responsible for most violations of the stationarity assumption. The abrupt changes in flood peaks can be associated with anthropogenic changes, such as changes in land use/land cover, agricultural practice, and construction of dams. The trend analyses do not suggest an increase in the flood peak distribution due to anthropogenic climate change. Examination of the upper tail and scaling properties of the flood peak distributions are examined by means of the location, scale, and shape parameters of the Generalized Extreme Value distribution.