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Modeling the effects of acid deposition and natural organic acids on surface waters.

机译：模拟酸沉降和天然有机酸对地表水的影响。

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摘要

Atmospheric deposition of sulfuric and nitric acids has impacted surface waters in the eastern U.S. Controls on anthropogenic S and NOx emissions have resulted in a substantial decrease in acid deposition. Long-term measurements of surface water chemistry indicate contrasting responses of surface waters to this deposition reduction. Streams in Great Smoky Mountain National Park (GRSM), in Tennessee and North Carolina, generally show a delayed response in contrast to lakes in the Adirondacks in New York State which are responding relatively rapidly to decreases in acid deposition. In this dissertation, I used a biogeochemical model, PnET-BGC, as a tool to investigate the influence of acid deposition and watershed characteristics on the extent and rate of surface water response to changes in atmospheric deposition. I applied PnET-BGC model to surface waters in two regions of the eastern US: the Adirondacks and the GRSM. These regions are both highly impacted from acid deposition, but have different watershed characteristics, which results in contrasting responses of surface waters. The focus of my analysis was on surface waters that have been identified by their respective states as acid-impaired. In addition to these impaired waters, I applied the model to other sites where data were available through intensive monitoring programs for the purpose of calibration, confirmation, or extrapolation. In the Adirondacks, 128 lakes have been identified as impaired and 12 streams in the GRSM. Simulation results indicate that surface waters in the Adirondacks are more responsive to controls on SO42- deposition than on NO3 - and NH4+, while streams in the GRSM are more responsive to NH4+ rather than SO4 2- and NO3-. This contrasting response is most likely due to the higher SO42- adsorption capacity of the soil and the lower N retention of the ecosystems in the GRSM, compared to the Adirondacks. I used the critical loads (CLs) and Total Maximum Daily Loads (TMDLs) to project reductions in atmospheric deposition loads that would provide healthy conditions for the fisheries of surface waters in these regions. These concepts are commonly used as tools for communication between scientists and policy makers. In this study, acid neutralizing capacity (ANC) was used as an indicator of the health of surface waters.;I performed a sensitivity analysis of the model for applications to both regions; I found that model simulation of ANC is most sensitive to the model inputs of Ca2+ and Na+ weathering rates, precipitation, maximum air temperature, and SO42- wet deposition. In the Adirondacks, the model simulating ANC was also sensitive to the parameters which were used in an algorithm depicting the acid-base behavior of naturally occurring organic acids. Model sensitivity to organic acid parameters along with the findings from recent studies, which indicate that following control on acid deposition, the acidity of surface waters is shifting from inorganic to organics acids, encouraged me to improve the parameterization of the acid-base characteristics of the naturally occurring organic acids.;To accomplish this, I used long-term data from two intensive sites in the northeastern U.S.: the Adirondacks and the Hubbard Brook Experimental Forest in New Hampshire. Combining a chemical equilibrium model and an optimization algorithm, I generated a modeling framework to parameterize organic acids in order to provide the best predictions for pH, ANC and inorganic monomeric Al, given the observations of other major solutes. Model parameterization is proposed for application in biogeochemical models such as PnET-BGC. The parameterization of organic acids showed that about 5% of the dissolved organic carbon consists of associated reactive functional groups, with both strong and weak acid characteristics. The parameterization of the organic acids, made using two temporal intervals of surface water data (i.e., 1993-2001 and 2003-2012 time intervals), indicate that the charge density of organic acids increased over time. This pattern suggests that dissolved organic matter recently (i.e., 2003-2012) draining from soil has a different quality, with more acidic characteristics and a greater relative contribution to the acidity of surface waters than dissolved organic matter from an earlier period (i.e., 1993-2001).
机译：硫酸和硝酸的大气沉积影响了美国东部的地表水。人为控制的S和NOx排放量的控制导致酸沉降的大幅下降。地表水化学的长期测量表明，地表水对此沉积减少的响应不同。田纳西州和北卡罗来纳州的大烟山国家公园（GRSM）的溪流通常显示出延迟的响应，这与纽约州阿迪朗达克山脉的湖泊对酸沉降减少的响应相对较快。本文以生物地球化学模型PnET-BGC为工具，研究了酸沉降和分水岭特征对地表水对大气沉降变化的响应程度和速率的影响。我将PnET-BGC模型应用于美国东部两个地区的地表水：阿迪朗达克山脉和GRSM。这些地区都受到酸沉降的强烈影响，但具有不同的分水岭特征，这导致地表水的响应形成对比。我的分析重点是地表水，这些水已被各自的状态识别为弱酸。除了这些受损的水域外，我还将模型应用到其他站点，这些站点可以通过密集的监视程序获得数据，以进行校准，确认或外推。在阿迪朗达克山脉，GRSM中已确认有128个湖泊受损，有12条溪流。模拟结果表明，阿迪朗达克山脉的地表水对SO42沉积的控制比对NO3-和NH4 +的响应更敏感，而GRSM中的水流对NH4 +的响应比对SO4 2-和NO3-的响应更敏感。与阿地伦达山脉相比，这种不同的响应很可能是由于土壤中SO42的较高吸附能力和GRSM中生态系统的氮保留较低。我使用了临界负荷（CL）和总最大每日负荷（TMDL）来预测大气沉积负荷的减少，这将为这些地区的地表水域渔业提供健康的条件。这些概念通常用作科学家与决策者之间交流的工具。在这项研究中，酸中和能力（ANC）被用作指示地表水健康的指标。我发现ANC的模型仿真对Ca2 +和Na +的风化速率，降水，最高气温和SO42-湿沉降的模型输入最为敏感。在阿迪朗达克山脉，模拟ANC的模型对描述自然存在的有机酸的酸碱行为的算法中使用的参数也很敏感。模型对有机酸参数的敏感性以及最近的研究结果表明，在控制了酸沉积之后，地表水的酸度正在从无机酸转变为有机酸，这促使我改善了有机酸参数的参数化为此，我使用了来自美国东北部两个集约化地点的长期数据：阿迪朗达克山脉和新罕布什尔州的哈伯德布鲁克实验森林。结合化学平衡模型和优化算法，我给出了对有机酸进行参数化的建模框架，以便在观察到其他主要溶质的情况下提供对pH，ANC和无机单体Al的最佳预测。提出将模型参数化应用于生物地球化学模型（如​​PnET-BGC）中。有机酸的参数化表明，约5％的溶解有机碳由相关的反应性官能团组成，具有强酸和弱酸特性。使用两个时间间隔的地表水数据（即1993-2001年和2003-2012年时间间隔）对有机酸进行参数化处理，表明有机酸的电荷密度随时间增加。这种模式表明，与早期（1993年）溶解有机物相比，最近（2003-2012年）从土壤中排出的溶解有机物具有不同的质量，具有更强的酸性特征，对地表水酸度的相对贡献更大。 -2001）。

著录项

  • 作者

    Fakhraei, Habibollah.;

  • 作者单位

    Syracuse University.;

  • 授予单位 Syracuse University.;
  • 学科 Civil engineering.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 249 p.
  • 总页数 249
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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