集中空调系统积尘理化特征

利用现场采样与实验分析的方法,对集中空调系统内的积尘进行了粒径分布、水溶性碳物质及离子含量的分析,以评估集中空调系统内积尘对微生物滋生的影响.结果表明,集中空调系统除新风段外的6个采样段,积尘平均粒径介于6—20μm之间,新风段积尘平均粒径为41.30μm;沿送风方向,微粒的平均粒径减小,单位积尘量所含的水溶性离子和有...     

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.     

Anomalous Ba/Ca signals associated with low temperature stresses in Porites corals from Daya Bay, northern South China Sea

Barium to calcium (Ba/Ca) ratio in corals has been considered as a useful geochemical proxy for upwelling, river flood and other oceanic processes. However, recent studies indicated that additional environmental or biological factors can influence the incorporation of Ba into coral skeletons. In this study, Ba/Ca ratios of two Porites corals collected from Daya Bay, northern South China Sea were analyzed. Ba/Ca signals in the two corals were ‘anomalous’ in comparison with Ba behaviors seen in other near-shore corals influenced by upwelling or riverine runoff. Our Ba/Ca profiles displayed similar and remarkable patterns characterized by low and randomly fluctuating background signals periodically interrupted by sharp and large synchronous peaks, clearly indicating an environmental forcing. Further analysis indicated that the Ba/Ca profiles were not correlated with previously claimed environmental factors such as precipitation, coastal upwelling, anthropogenic activities or phytoplankton blooms in other areas. The maxima of Ba/Ca appeared to occur in the period of Sr/Ca maxima, coinciding with the winter minimum temperatures, which suggests that the anomalous high Ba/Ca signals were related to winter-time low sea surface temperature. We speculated that the Ba/Ca peaks in corals of the Daya Bay were most likely the results of enrichment of Ba-rich particles in their skeletons when coral polyps retracted under the stresses of anomalous winter low temperatures. In this case, Ba/Ca ratio in relatively high-latitude corals can be a potential proxy for tracing the low temperature stress.     

气相色谱-质谱联用测定水产品中的合成麝香

利用快速溶剂萃取（ASE）和在线吸附净化,气相色谱-质谱（GC/MS）联用测定水产品中8种合成麝香.以正己烷为萃取溶剂,中性氧化铝为吸附剂,在100℃的温度下对水产品进行萃取.实验结果表明,方法的检测限为0.1—0.5 ng·g-1;在浓度1—80 ng·g-1的范围内,峰面积与样品浓度呈良好线性关系;8种合成麝香的回...     

Population viability of the Siberian Tiger in a changing landscape: Going, going and gone?

The Amur tiger (Panthera tigris altaica) is a flagship species of the boreal forest ecosystem in northeastern China and Russia Far East. During the past century, the tiger population has declined sharply from more than 3000 to fewer than 600 individuals, and its habitat has become much smaller and greatly fragmented. Poaching, habitat degradation, habitat loss, and habitat fragmentation have been widely recognized as the primary causes for the observed population decline. Using a population viability analysis tool (RAMAS/GIS), we simulated the effects of poaching, habitat degradation, habitat loss, and habitat fragmentation on the population dynamics and extinction risk of the Amur tiger, and then explored the relative effectiveness of three conservation strategies involving improving habitat quality and establishing movement corridors in China and Russia. A series of controlled simulation experiments were performed based on the current spatial distribution of habitat and field-observed vital rates. Our results showed that the Amur tiger population could be viable for the next 100 years if the current habitat area and quality were well-maintained, with poaching strictly prohibited of the tigers and their main prey species. Poaching and habitat degradation (mainly prey scarcity) had the largest negative impacts on the tiger population persistence. While the effect of habitat loss was also substantial, habitat fragmentation per se had less influence on the long-term fate of the tiger population. However, to sustain the subpopulations in both Russia and China would take much greater conservation efforts. The viability of the Chinese population of tigers would rely heavily on its connectivity with the largest patch on the other side of the border. Improving the habitat quality of small patches only or increasing habitat connectivity through movement corridors alone would not be enough to guarantee the long-term population persistence of the Amur tiger in both Russia and China. The only conservation strategy that allowed for long-term persistence of tigers in both countries required both the improvement of habitat quality and the establishment of a transnational reserve network. Our study provides new insights into the metapopulation dynamics and persistence of the Amur tiger, which should be useful in landscape and conservation planning for protecting the biggest cat species in the world.     

Modelling N mineralization from green manure and farmyard manure from a laboratory incubation study

Predicting N mineralization from organic manures like farmyard manure (FYM) is more difficult than from fresh organic materials like crop residues, as the manures vary greatly in composition. A laboratory incubation experiment was carried out for 98 days at 30 °C under aerobic conditions to study the effects on N dynamics of Gliricidia (Gliricidia sepium, Jacquin) and FYM application to soil at 5 and 10 g kg⁻¹. Application of Gliricidia induced N mineralization from the start of incubation period, with the amount of N mineralized increasing with rate of application. In contrast, application of FYM resulted in immobilization of mineral N in soil, irrespective of the rate of application. The initial net immobilization from FYM was limited by availability of N in the soil for the higher rate of application.We used the APSIM SoilN module to simulate these contrasting patterns of mineralization of N from Gliricidia and from FYM. The prediction of N mineralized from Gliricidia was better than FYM. The default model parameters specify that the fresh organic matter pools (FPOOL1, FPOOL2 and FPOOL3) have the same C:N ratio and this assumption was ineffective in predicting N mineralized from FYM. The predictive ability of the model improved when this default assumption was modified based on the size of the individual pools (FPOOL1, FPOOL2 and FPOOL3), and the pool's C:N ratios. The modelling efficiency, a measure of goodness of fit between the simulated and observed data, improved markedly for the modified model. The discrepancy between the modelled and observed data was a tendency for the model to underestimate the rate of re-mineralization at the lower rate of application of FYM in the later part of incubation. Unfortunately the appropriate modification to the size and C:N ratios of the FPOOLs could not be determined on the basis of chemical analysis alone. Thus, a true predictive application of the model to a new FYM material is not yet possible.