Forescasting chemical recovery from acidification

预测酸化中的化学品回收率

• 批准号: 327208-2006
• 负责人: Aherne, Julian
• 金额: $ 1.35万
• 依托单位: Trent University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=361195
• 关键词: Forescasting; chemical; recovery; acidification

Acid deposition is recognised as a major regional pollutant that has had negative impacts on sensitive terrestrial and aquatic ecosystems across eastern North America. Deposition of strong acids has accelerated base cation leaching from soils, and there is increasing concern that declining soil base saturation could result in a decline in forest health and productivity. Acidic deposition to base poor soils has resulted also in decreases in surface water pH and increases in the concentration of inorganic monomeric aluminium. A number of dynamic process-oriented models have been developed to investigate the response of surface waters to acid deposition. Dynamic acidification models can be readily used to provide an estimate of the future soil or surface water chemistry. As such, dynamic models are being increasingly applied on a regional basis to assess the benefits of reduced acid deposition and predict times to recovery. The proposed research program will contribute to the better prediction of the future chemical status of soils and waters under proposed future emission reductions. The research is innovative and novel in that predictive modelling tools will be developed to determine environmental risk from anthropogenic impacts. The research will principally focus on acid deposition, although the influence of land-use change and climate will be considered. The methodology will focus on linking or nesting existing biogeochemical and hydrological models. Novel statistical and modelling techniques will be utilised to quantify uncertainty in model predictions. The research program will focus principally on established long-term monitoring sites. Existing information for these sites will be supplemented with measurements of additional state variables with the objective to develop an integrated monitoring network for the application of computer models. This type of network approach is essential for synthesising the results of individual sites and for providing a coherent message to policy makers. It is anticipated that the results of the research program will provide the scientific underpinning for the development and implementation of future emission reduction polices.

酸沉降被认为是一种主要的区域污染物，对北美东部敏感的陆地和水生生态系统产生了负面影响。强酸的沉积加速了土壤中阳离子的流失，人们越来越担心土壤碱饱和度的下降会导致森林健康和生产力的下降。酸沉降到贫碱土壤也导致地表水pH值下降和无机单体铝浓度增加。为了研究地表沃茨对酸沉降的响应，已经开发了许多面向动态过程的模型。动态酸化模型可以很容易地用于提供未来土壤或地表水化学的估计。因此，在区域基础上越来越多地应用动态模型来评估减少酸沉降的好处和预测恢复时间。拟议的研究计划将有助于更好地预测土壤和沃茨的未来化学状态下拟议的未来减排。该研究具有创新性和新颖性，因为将开发预测建模工具，以确定人为影响的环境风险。研究将主要集中在酸沉降，虽然土地使用变化和气候的影响将被考虑。该方法将侧重于连接或嵌套现有的地球化学和水文模型。新的统计和建模技术将用于量化模型预测的不确定性。该研究计划将主要集中在已建立的长期监测点。这些场址的现有资料将以其他状态变量的测量数据加以补充，目的是建立一个综合监测网络，以应用计算机模型。这种网络办法对于综合各个地点的结果和向决策者提供连贯一致的信息至关重要。预计研究结果将为未来减排政策的制定和实施提供科学依据。