Potential Environmental Benefits from Increased Use of Bioenergy in China

Because of its large population and rapidly growing economy, China is confronting a serious energy shortage and daunting environmental problems. An increased use of fuels derived from biomass could relieve some demand for nonrenewable sources of energy while providing environmental benefits in terms of cleaner air and reduced emissions of greenhouse gases. In 2003, China generated about 25.9 × 10⁸ metric tons of industrial waste (liquid + solid), 14.7 × 10⁸ metric tons/year (t/y) of manure (livestock + human), 7.1 × 10⁸ t/y of crop residues and food-processing byproducts, 2 × 10⁸ t/y of fuelwood and wood manufacturing residues, and 1.5 × 10⁸ t/y of municipal waste. Biofuels derived from these materials could potentially displace the use of about 4.12 × 10⁸ t/y of coal and 3.75 × 10⁶ t/y of petroleum. An increased bioenergy use of this magnitude would help to reduce the emissions of key air pollutants: SO₂ by 11.6 × 10⁶ t/y, NO_X by 1.48 × 10⁶ t/y, CO₂ by 1.07 × 10⁹ t/y, and CH₄ by 50 × 10⁶ t/y. The reduced SO₂ emissions would be equivalent to 54% of the national emissions in 2003, whereas those for CO₂ are 30%. It is important to recognize, however, that large increases in the use of biomass fuels also could result in socioeconomic and environmental problems such as less production of food and damage caused to natural habitats.     

Environmental sub models for a macroeconomic model: agricultural contribution to climate change and acidification in Denmark

Integrated modelling of the interaction between environmental pressure and economic development is a useful tool to evaluate environmental consequences of policy initiatives. However, the usefulness of such models is often restricted by the fact that these models only include a limited set of environmental impacts, which are often energy-related emissions. In order to evaluate the development in the overall environmental pressure correctly, these model systems must be extended. In this article an integrated macroeconomic model system of the Danish economy with environmental modules of energy related emissions is extended to include the agricultural contribution to climate change and acidification. Next to the energy sector, the agricultural sector is the most important contributor to these environmental themes and subsequently the extended model complex calculates more than 99% of the contribution to both climate change and acidification. Environmental sub-models are developed for agriculture-related emissions of CH(4), N(2)O and NH(3). Agricultural emission sources related to the production specific activity variables are mapped and emission dependent parameters are identified in order to calculate emission coefficients. The emission coefficients are linked to the economic activity variables of the Danish agricultural production. The model system is demonstrated by projections of agriculture-related emissions in Denmark under two alternative sets of assumptions: a baseline projection of the general economic development and a policy scenario for changes in the husbandry sector within the agricultural sector.     

土壤镉胁迫下菲降解菌的筛选及其降解特性研究

以菲和镉为供试物,对沈抚灌区土壤中土著菌进行筛选试验,筛选出一株菲降解菌,命名为W.J,同时测定在不同浓度镉胁迫下,菲为单一碳源时W.J的生长情况.结果表明,在镉胁迫下W.J对菲具有一定的降解能力,镉30 mg/L时,60 h时菲降解率在65%以上.16s rDNA测序比对发现,W.J与Alcaligenes(产碱杆菌属)同源性最高,为99%.通过对W.J生长曲线的测定,发现其对数生长期为0～20 h,这为W.J菌株保存提供了一定的前提条件.高浓度镉在W.J的生长后期对其有明显的毒理效应.     

基于可拓方法的职业危害控制水平预警模型

为了量化职业危害发生的可能性，并为职业病防治提供依据，利用物元分析方法，建立了高危作业有害因素控制水平的综合预警模型。为了避免人为主观因素的影响，采用简单可拓关联函数确定模型中指标权重，并以定量结果确定预警级别。实例验证表明，该模型可用于对职业危害的控制水平做出综合评价，并提供定量的预警信息。     

土壤pH值与土壤养分有效态关系探讨——以内江市白马镇为例

本文探讨了小区域范围内土壤pH值与土壤主要肥力指标N、P、K有效态的关系，结果表明土壤pH值与土壤速效P含量呈极显著负相关，相关系数为-0．498；与土壤缓效K呈显著正相关，相关系数为0．352；与水解性N和速效K含量相关性不明显。     

Mathematical Modeling of Leachates from Ash Ponds of Thermal Power Plants

The present study describes the development of empirical models for the prediction of various trace metals i.e., Mn, Cu, Fe, Zn and Pb found in the leachates generated from the ash ponds of various thermal power plants. The dispersion phenomenon of these trace metals followed first order reaction rate kinetics. The empirical models for individual trace metals derived from the lab scale models data correlate well with the real field data with regression coefficients varying from 0.93 to 0.98. The predicted concentrations of the trace metals varied within ±3% of the observed values in the leachates generated from the ash ponds of four thermal power plants with standard deviation varying from 0.001 to 0.032. The empirical models derived from the study can be applied for prediction of trace metals in leachates generated from similar thermal power plants.