Integrated analysis of the effects of agricultural management on nitrogen fluxes at landscape scale

The integrated modelling system INITIATOR was applied to a landscape in the northern part of the Netherlands to assess current nitrogen fluxes to air and water and the impact of various agricultural measures on these fluxes, using spatially explicit input data on animal numbers, land use, agricultural management, meteorology and soil. Average model results on NH₃ deposition and N concentrations in surface water appear to be comparable to observations, but the deviation can be large at local scale, despite the use of high resolution data. Evaluated measures include: air scrubbers reducing NH₃ emissions from poultry and pig housing systems, low protein feeding, reduced fertilizer amounts and low-emission stables for cattle. Low protein feeding and restrictive fertilizer application had the largest effect on both N inputs and N losses, resulting in N deposition reductions on Natura 2000 sites of 10% and 12%, respectively.     

Polybrominated diphenyl ethers (PBDEs) and indicator polychlorinated biphenyls (PCBs) in marine fish from four areas of China

The levels of polybrominated diphenyl ethers (PBDEs) and indicator polychlorinated biphenyls (PCBs) were determined in marine fish from four areas of China (South China Sea, Bohai Sea, East China Sea, and Yellow Sea) using GC/NCI-MS and GC/ITMS, respectively. Total concentrations of eight PBDEs (BDE-28, 47, 99, 100, 153, 154, 183 and 209) in all samples ranged from 0.3 ng g⁻¹ ww (wet weight) to 700 ng g⁻¹ ww, with median and mean values of 85 ng g⁻¹ ww and 200 ng g⁻¹ ww, respectively. BDE-209 and BDE-47 were the major congeners in all samples, contributing 54% and 19% to the total concentration, respectively. The sum of seven indicator PCB levels (CB-28, 52, 101, 118, 138, 153, and 180) ranged from 0.3 ng g⁻¹ ww to 3.1 μg g⁻¹ ww, with median and mean values of 6.4 ng g⁻¹ ww and 398 ng g⁻¹ ww, respectively. High contributions of CB-138 (32%) and CB-153 (25%) were found in all samples. In general, pollutants measured in this study were at high levels when compared with previous studies from other regions in the world. The relative abundance of BDE-209 may suggest that deca-BDE sources existed in studied area. And principal component analysis (PCA) showed that there were other PBDE sources in Yellow Sea. The pattern and PCA showed that PCB pollutions came from similar sources in the studied areas. In addition, concentrations of ∑₇PBDEs (u/209) were strongly correlated with those of ∑₇PCBs in all fish (r = 0.907, n = 44).     

Redistribution of free tropospheric chemical species over West Africa: radicals (OH and HO₂), peroxide (H₂O₂) and acids (HNO₃ and H₂SO₄)

The purpose of this paper is to study the redistribution of chemical species (OH, HO₂, H₂O₂, HNO₃ and H₂SO₄) over West Africa, where the cloud cover is ubiquitously present, and where deep convection often develops. In this area, because of these cloud systems, chemical species are redistributed by the ascending and descending flow, or leached if they are soluble. So, we carry out a mesoscale study using the Regional Atmospheric Modelling System (RAMS) coupled to a code of gas and aqueous chemistry (RAMS_Chemistry). It takes into account all processes under mesh. We examine several cases following the period (November and July), with inputs emissions (anthropogenic, biogenic and biomass burning). The radicals OH and HO₂ are an indicator of possibilities for chemical activity. They characterize the oxidizing power of the atmosphere and are very strong oxidants. The acids HNO₃ and H₂SO₄ are interesting in their transformation into nitrates and sulfates in precipitation. In November, when photochemistry is active during an event of biomass burning, concentrations of chemical species are higher than those of November in the absence of biomass burning. The concentrations of nitric acid double and sulfuric acid increases 70 times. In addition, the concentrations are even lower in July if there is a deep convection. Compared to measures of the African Monsoon Multidisciplinary Analysis (AMMA), the results and observations of radicals OH and HO₂ are the same order of magnitude. Emissions from biomass burning increase the concentrations of acid and peroxide, and a deep convection cloud allows the solubility and the washing out of species, reducing their concentration. Rainfalls play a major role in solubility and washing out acids, peroxides and radicals in this region.     

Sorption of selenate on soils and pure phases: kinetic parameters and stabilisation

This study was conducted to identify the principle selenate carrier phases for two selected soils, by comparing their reactivity with selenate to that of pure phases of the solids. Silica, calcium carbonate, aluminium hydroxide, goethite, bentonite and humic acid were selected as the main soil carrier phases. Comparisons were made first on the parameter values obtained with the best fit of a kinetic sorption model which can discriminate instantaneous sorption from kinetically limited sorption. Then comparisons were made of the ability for each solid to stabilise selenate by measuring the ratio of the partition coefficient for sorption (Kd_sorption) over that of the desorption (Kd_desorption). Kinetics and stabilisation were used to help elucidate the nature of interactions with the test solid phases for a large range of selenate concentrations. The experiments were conducted over 165 h in batch reactors, the solid being isolated from the solution by dialysis tubing, at two pH (5.4 and 8) and three selenate concentrations (1 × 10⁻³, 1 × 10⁻⁶ and 1 × 10⁻⁸ mol L⁻¹). The results obtained showed that only aluminium hydroxide can sorb selenate throughout the studied pH range (pH 5.4 to 8.0). The sorption capacity on this mineral was high (Kd_sorption > 100 to 1 × 10⁴ L kg⁻¹) and the selenate was mainly stabilized by the formation of inner sphere complexes. The sorption on goethite occurred at pH 5.4 (Kd_sorption 52 L kg⁻¹), mainly as outer sphere complexes, and was null at pH 8. On silica, a weak sorption was observed only at pH 5.4 and at 165 h (Kd_sorption 4 L kg⁻¹). On bentonite, calcium carbonate and humic acid no significant sorption was observed. Concerning the two soils studied, different behaviours were observed for selenate. For soil Ro (pH 5.4), Kd_sorption was low (8 L kg⁻¹) compared to soil Bu (pH 8) (70 L kg⁻¹). The sorption behaviour of selenate on soil Ro was mainly due to outer sphere complexes, as for goethite, whereas for soil Bu the sorption was mainly attributed to inner sphere complexes followed by reduction mechanisms, probably initiated by microorganisms, in which no steady state was reached at the end of the 165 h experiments. The sorption of selenate decreased when concentrations reached 1 × 10⁻³ mol L⁻¹, due to solid saturation, except for aluminium hydroxide. Reduction of selenate seemed also to occur on goethite and soil Ro, for the same concentration, but without preventing a decrease in sorption. Thus, this work shows that the comparison of selenate behaviour between soil and pure phases helps to elucidate the main carrier phases and sorption mechanisms in soil.     

Assessing and testing prediction uncertainty for single tree-based models: A case study applied to northern hardwood stands in southern Québec, Canada

Estimating prediction uncertainty for a single tree-based model is hindered by the complex structure of these models. In this paper, we addressed this issue with a case study applied to northern hardwood stands in Québec, Canada. SaMARE is a stochastic single tree-based model that was designed for these types of stands. Using a Monte Carlo approach, the model can provide a mean predicted value and its confidence limits for some plot-level attributes.The mean predicted values were compared to observed values in terms of bias and accuracy. In addition to these common statistics, we compared nominal coverage of Monte Carlo-simulated confidence intervals with real (observed) coverage to verify the adequacy of the simulated uncertainty. A comparison was made using several plot-level attributes, which exhibited an increasing discriminative complexity. This complexity ranges from coarse attributes, such as all-species basal area, up to more complex ones, such as basal area for stems of a particular species and with sawlog potential.The results showed that in terms of absolute value, biases were small, but could be relatively high with respect to the average observed value when the discriminative complexity of the attribute increased. The comparison between nominal and real coverage of confidence intervals gave satisfactory results for all-species plot-level attributes. However, for some species-specific attributes, the Monte Carlo-simulated confidence intervals overestimated the real coverage.     

镇江市综合防灾系统中消防信息的输入与管理

本文以镇江市消防地图及其相关信息为对象,分析了消防信息的特点和现有的输入方法,以及作者在设计与建造镇江市消防信息数据库的实践中采用的技术路线和具体方法。     

提高交通安全——实现智能汽车的研究

主要介绍了通过智能汽车的研究 ,提高城市交通安全的必要性 ;综述了发达国家关于智能汽车研究的现状与趋势 ,并通过国外智能汽车发展的趋势 ;进一步论证智能汽车的研究是汽车工业发展的方向 ,也是提高交通安全的重要手段之一。此外 ,论文提出利用模式识别技术的智能汽车的结构框架 ;指出神经网络方法应用与模式识别技术结合的优势。最后 ,论文在阐述我国需要发展智能汽车的同时 ,提出应结合中国国情相应研究相关理论 ,为今后的实施奠定基础的近期目标 ,并提出展望     

鄱阳湖典型湿地沉水植物的分布格局及其水环境影响因子

沉水植物是湖泊湿地生态系统中关键组分,调查研究沉水植物分布格局及其水环境影响因子,对于沉水植被的恢复与重建具有重要的指导意义。2013年5月初期分别对鄱阳湖典型湿地区域中有沉水植物的25个样地进行群落结构调查,采用系统取样方法对沉水植物进行调查采样并监测水环境因子,在野外调查的基础上运用GIS软件制作鄱阳湖典型区域沉水植物的生物量分布图,并采用主成分分析(PCA)和典范对应分析(CCA)方法分析其主要影响因子。结果表明:鄱阳湖湿地沉水植物以苦草(Vallisneria natans)为广布种,其中蚌湖及白沙湖以黑藻(Hydrilla verticillata)为优势种,白沙洲及乐安河龙口段以苦草为优势种,伴生种主要有金鱼藻(Ceratophyllum demersum)、马来眼子菜(Potamogeton malaianus)、菹草(P.crispus)、小茨藻(Najas minor)、大茨藻(N.marina)、刺苦草(V.spinulosa)和水车前(Ottelia alismoides)等。采用双向指示种分析法将研究区沉水植物分为6个群落;5月初大部分沉水植物尚处于生长季初期,生物量相对较低,仅菹草的生物量较大;沉水植物与浮叶植物共存现象明显。主成分分析(PCA)结果显示,第一主成分中水深、总磷和溶解氧等因子的系数值较大,第二主成分中pH值、化学需氧量和水体透明度等因子的系数值较大,是影响沉水植物分布的关键因子;典范对应分析(CCA)结果显示,水深、总磷和总氮对苦草和黑藻的影响显著,水体透明度是马来眼子菜的主要影响因子。     

A novel approach for VOC source apportionment combining characteristic factor and pattern recognition technology in a Chinese industrial area

Volatile organic compound (VOC) emission control and source apportionment in small-scale industrial areas have become key topics of air pollution control in China. This study proposed a novel characteristic factor and pattern recognition (CF-PR) model for VOC source apportionment based on the similarity of characteristic factors between sources and receptors. A simulation was carried out in a typical industrial area with the CF-PR model involving simulated receptor samples. Refined and accurate source profiles were constructed through in situ sampling and analysis, covering rubber, chemicals, coating, electronics, plastics, printing, incubation and medical treatment industries. Characteristic factors of n-undecane, styrene, o-xylene and propane were identified. The source apportionment simulation results indicated that the predicted contribution rate was basically consistent with the real contribution rate. Compared to traditional receptor models, this method achieves notable advantages in terms of refinement and timeliness at similar accuracy, which is more suitable for VOC source identification and apportionment in small-scale industrial areas.