Use of native mosses as biomonitors of heavy metals and nitrogen deposition in the surroundings of two steel works

A biomonitoring survey using the moss species Hypnum cupressiforme Hedw. was conducted in the surroundings of two steel plants located in the North of Spain. Levels of V, Cr, Ni, Cu, Zn, As, Cd, Hg, Pb and N were determined. Very high concentrations in the areas of study were detected when compared to nearby unaffected regions. Similar trends were observed for all the elements in the differently orientated transects, showing an appreciable influence of the NW prevailing winds of the region in the dispersion of pollutants, as well as a clear decreasing gradient in the concentrations of metals in mosses within a distance of 1500 meters from the facilities. A differentiation between the elements emitted by the chimney as result of the industrial activity (V, Cr, Ni, Cu and As) and those with a high presence in steel slag deposits (Zn, Cd, Hg and Pb) was observed. The range of contamination was also established by means of the Contamination Factor, indicating a category 4 out of 6 categories, which shows the high levels reported in the areas of study. A different dynamic was registered for nitrogen regarding the rest of the heavy metals analysed except for Hg, probably due to the elevated volatility and mobility of both elements, as well as their high persistence in the atmosphere.     

Response of Ceriodaphnia dubia to ionic silver: discrepancies among model predictions, measured concentrations and mortality

Silver thiosulfate, often a waste product of photoprocessing, is less bioavailable or toxic to aquatic organisms than is ionic silver. We conducted duplicate 48-h Ceriodaphnia dubia tests in reconstituted laboratory water using treatments of 92.7 nM Ag+ with various concentrations of thiosulfate. Expected Ag+ concentrations were generated for thiosulfate treatment levels using MINEQL + chemical equilibrium modeling. Ag+ concentrations in treatments were determined using a novel silicon-based sensor. Based on predicted Ag+ and published 48-h LC50 values for C. dubia, we did not expect to observe adverse effects. Yet, 100% mortality was observed at low thiosulfate treatments, whereas > 85% and > 95% survival was observed at higher thiosulfate treatment levels, respectively. Our results indicate that biotic responses match the sensor-based Ag+ concentrations. However, there is a discrepancy between these empirical results and responses expected to occur with Ag+ concentrations as predicted by MINEQL + chemical modeling. By correlating silicon sensor data with toxicity results obtained from our laboratory, our work clearly relates a specific chemical form (Ag+) to toxicity results.     

Multiple regression models for the lower heating value of municipal solid waste in Taiwan

A multiple regression analysis was used to develop two predictive models of lower heating value (LHV) for municipal solid waste (MSW), using 180 samples gathered from cities and counties in Taiwan during 2001-2002. These models are referred to as the original proposed model (OPM) and the simplified model (SM). The coefficients of multiple determinations for the OPM and SM were 0.983 and 0.975, respectively. To verify the feasibility of the models, a demonstration program based on sampling of MSW in Kaohsiung City was conducted. As a result, the OPM showed superior precision in terms of relative percentage deviation (RPD) and mean absolute percentage error (MAPE), when compared to the conventional models based on the proximate analysis, physical composition and ultimate analysis. The SM was derived by neglecting the three minor physical components used in the OPM. The resulting SM was less precise when compared to the OPM, but it was still acceptable, with a precision level better than the conventional models. It was concluded that the predictability of empirical models could be improved significantly through selection of the appropriate physical components and multiple regression analysis.     

Estimation and projection of nitrous oxide (N2O) emissions from anthropogenic sources in Taiwan

Taiwan is a densely populated and developed country with more than 97% of energy consumption supplied by imported fuels. Greenhouse gas emissions are thus becoming significant environmental issues in the country. Using the Intergovernmental Panel on Climate Change (IPCC) recommended methodologies, anthropogenic emissions of nitrous oxide (N2O) in Taiwan during 2000-2003 were estimated to be around 41 thousand metric tons annually. About 87% of N2O emissions come from agriculture, 7% from the energy sector, 3% from industrial processes sector, 3% from waste sector. On the basis of N2O emissions in 2000, projections for the year 2010 show that emissions were estimated to decline by about 6% mainly due to agricultural changes in response to the entry of WTO in 2002. In contrast to projections for the year 2020, N2O emissions were projected to grow by about 17%. This is based on the reasonable scenario that a new adipic acid/nitric acid plant will be probably started after 2010.     

Swift model for a lower heating value prediction based on wet-based physical components of municipal solid waste

To establish an empirical model for predicting a lower heating value (LHV) easily and economically by multiple regression analysis. A wet-based physical components model (WBPCM) was developed and based on physical component analysis without dewatering. Based on 497 samples of municipal solid waste (MSW) gathered from 14 incinerators in western parts of Taiwan from 2002 to 2009. The proposed model was verified by independent samples from other incinerators through parameters multiple correlation coefficients (R), relative percentage deviation (RPD) and mean absolute percentage error (MAPE). Experimental results indicated that R, RPD and MAPE were 0.976, 17.1 and 17.7, respectively. This finding implies that LHV predicted by the WBPCM could well explain the LHV characteristics of MSW. The WBPCM was also compared with existing prediction models of LHV on a dry basis. While more accurately predicting LHV predicting than those models based on proximate analysis, the WBPCM was comparable with models based on physical component analysis in term of RPD and MAPE. Experimental results further indicated that the prediction accuracy of the WBPCM varied with MSW moisture parabolically. No specific relation was observed in the results of the previous prediction model. The accuracy of the WBPCM was almost approached to that of ultimate analysis in moisture ranging from 40% to 55%. The model was applicable within this moisture range. We conclude that the WBPCM is a faster and more economical model for LHV predictions with comparable accuracy than those models based on physical component analysis. The proposed WBPCM is highly promising for use in designing and operating incinerators.     

粘性泥石流体应力本构关系的试验研究

为了能直接测定含有粗颗粒砾石的粘性泥石流体原样的流变特性，专门研制了大型泥石流流变仪，利用该仪器测试的结果分析研究了粘性泥石流体的应力本构关系。分析研究表明：粘性泥石流体在低速率区启动初始段，颗粒间的作用以接触挤压和滑动摩擦为主，其应力本构关系可用剪切稀化的幂定理方程来描述；在剪切速率区流动剪切段的应力本构关系，包含滑动摩擦作用的零次项和反映惯性碰撞的平方项，具有屈服应力和剪切膨胀的流变特征。     

The development and application of remote sensing to monitor sand dune habitats

Sand dunes are complex systems that contain several habitats, often as mosaics or transitions between types. Several of these habitats are afforded protection under European Legislation and in the UK nationally within Special Areas of Conservation (SAC) and Sites of Special Scientific Interest (SSSI). Natural England has a statutory duty to report to Europe on the conservation status and condition of sand dunes; and is required to report to the UK Government on designated sites. To achieve this we have sought ways of capturing, analysing and interpreting data on the extent and location of sand dune habitats. This requires an ability to be able to obtain data over large areas of coastline in an efficient way. Natural England and Environment Agency Geomatics have worked collaboratively for over 16 years, sharing data and ecological knowledge. In 2012 work started to evaluate the use of remote sensing to map UK BAP and Annex I sand dune habitats. A methodology has now been developed and tested to map sand dune habitats. The key objective was to provide an operational tool that will help to map these habitats and understand change on sites around England. This has been achieved through analysis of LIDAR and Compact Airborne Spectrographic Imager (CASI) data using Object Orientated Image Analysis. Quality Control (QC) and accuracy assessments have shown this approach to be successful and 11 sites have been mapped to date. These techniques are providing a new approach to monitoring change in coastal vegetation communities and informing management of protected sites.