环渤海地区持久性有机污染物空间多介质迁移模拟

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题名	环渤海地区持久性有机污染物空间多介质迁移模拟
作者	刘世杰
学位类别	博士
答辩日期	2014-05
授予单位	中国科学院研究生院
授予地点	北京
导师	吕永龙
关键词	逸度 BETR模型苯并[a]芘（BaP）全氟辛烷磺酸（PFOS）软件开发 Fugacity BETR model Benzo[a]pyrene (BaP) Perfluorooctane sulfonate (PFOS) Software development
其他题名	Simulation of Spatial Explicit Multimedia Fate of POPs in Bohai Rim
学位专业	环境科学
中文摘要	利用空间多介质模型模拟分析区域内持久性有机污染物（Persistent Organic Pollutants，POPs）的分布和迁移状况，是进行 POPs生态风险评价研究的重要内容，也是环境科学的重要前沿方向。本文以环渤海地区为研究区域，以苯并 [a]芘（BaP）和全氟辛烷磺酸（PFOS）为目标物质，基于逸度模型原理构建了区域尺度上的 POPs空间多介质迁移模型，收集了模型所需的化学品性质和环境参数数据，估算了其在环渤海地区的空间排放，在稳态条件下模拟其在环渤海地区大气、植被、淡水、淡水沉积物、海水和土壤中的浓度及迁移扩散特征，根据模型结果分析了污染物在环渤海地区的介质分配、相间及空间迁移过程，通过与实测值进行对比、参数敏感性分析及不确定性分析等方法对模型的可靠性进行验证，初步分析了其在环渤海地区的风险，最后对模型进行了重新设计和二次开发，使其具有图形化用户界面。根据排放估算的结果，2008年环渤海地区 BaP总排放量为 112.12吨，炼焦用煤、生物质燃烧和生活燃煤为排放最高的三类排放源，北京 -天津-唐山地区、沈阳-营口地区及济南-淄博-潍坊地区是研究区域内的三个高排放区域；根据模型结果，BaP的高浓度区主要分布在高排放及其周围一定范围内的区域；生物相中的 BaP浓度远高于其他环境介质，存在很高的人体健康风险；土壤中 BaP的储量占其在环境中总量的 94.53%，是 BaP在该地区环境中的最主要的“汇”；在相间迁移过程中，大气向其他环境介质的迁移是 BaP在该地区主要相间迁移过程；大气是环渤海地区 BaP入海和空间迁移的最主要驱动力，较大河流对于 BaP在环境中的迁移同样具有重要贡献；与平流过程相比，降解过程是环渤海地区 BaP从环境系统中移除的主要过程；模拟值与实测值浓度对比表明模型模拟效果较好，实测数据的代表性不足可能是造成部分区域模拟值和实测值产生差异的主要原因；上游区域的大量排放也可能导致模拟值整体偏低；参数敏感性分析结果表明，部分与 BaP排放速率、介质规模、迁移速率以及污染物持久性相关的参数是对模型结果影响最显著的敏感性参数；不确定性分析结果表明 BaP在大气和土壤中的浓度分布都符合对数正态分布，其变异系数分别为 0.46和 1.53。环渤海地区 PFOS四种排放场景下排放总量分别为 471.52 kg/a、542.09 kg/a、540.19 kg/a和 529.69 kg/a；淡水是 PFOS排放的主要受体；不同介质中 PFOS排放的空间分布基本类似，潍坊、青岛、北京、天津和大连的排放量明显高于其他地区；模型结果表明，高浓度地区主要包括高排放区域以及由于河流的传输作用导致的河流下游区域；场景 2中 PFOS浓度比其他场景略高，但差别并不显著；土壤是 PFOS在该地区环境中的最主要储库，占环境总储量的 52.96%；在土壤中 PFOS的三种来源中，直接排放是其在土壤中的主要来源；PFOS在淡水、淡水沉积物和海水中储量的比例比 BaP等典型 POPs相比要高出许多，水环境也是PFOS重要的“汇”；通过入海河流的传输是该地区海水中 PFOS的主要输入途径；水是环渤海地区中 PFOS空间迁移的主要驱动力；与降解相比，平流流出是 PFOS 从环境中移除的主要途径；在仅考虑淡水流量季节性变化的条件下，冬、春两季淡水中 PFOS浓度较高，而夏、秋两季浓度较低，且 PFOS浓度季节性差异程度与河流总流量成负相关关系，这主要是受到河流水量稀释作用的影响；与 PFOS在淡水中浓度季节性变化趋势相反，PFOS入海通量在夏、秋两季较高，而在冬、春两季较低，水量的增加导致河流对 PFOS整体运移量的增加；对研究区域 PFOS淡水中暴露风险的分析表明，整体来讲目前环渤海地区 PFOS淡水中的 PFOS暴露的生态风险较低，但部分地区河流水量的季节性变化很有可能会引起河流中PFOS浓度的显著升高，并有一定的生态风险。模型模拟值和实测值基本处于同一浓度区间内，吻合较好，但由于化学品性质数据和排放估算的不确定性、模型中对部分小河的忽略以及沿海工业源直接排放入海所导致的对排放的高估等原因，模型模拟值与实测值相比整体略偏高。基于一致性、标准化和可拓展的原则，本研究对模型进行了重新设计和二次开发，使其成为一个有图形化用户界面的软件。软件主要功能包括对污染物空间多介质迁移进行静态和动态模拟、参数敏感性分析以及对结果进行空间展示，针对每种功能分别对软件界面进行了详细设计。
英文摘要	Simulating the distribution and fate of Persistent Organic Pollutants (POPs) using a spatially environmental multimedia fate model is an essential step in environmental risk assessment. In this study, a grid based multimedia fugacity model on regional scale was developed for Bohai coastal region, together with case studies modeling the fate and transfer of Benzo[a]pyrene (BaP) and perfluorooctane sulfonate (PFOS). Physical-chemical properties of chemicals and environmental characterastics were collected for the model. Based on the estimated emissions, concentrations of the chemicals in air, vegetation, soil, fresh water, fresh water sediment and coastal water as well as the transferfluxes were derived under the steady-state assumption. Inventories in multimedia and tranferring processeses were analyzed according to the model results. The reliability of model results was assessed through comparison between the measured and modeled concentrations, sensitivity analysis and uncertainty analysis. Preliminary risk assessment was carried out for the chemicals in Bohai coastal region. The model was also redesigned and redeveloped to have a visualized user interface. The total BaP emssion in Bohai coastal region was estimated to be 112.12 tons in 2008. Coking coal combustion, biomass burning and domestic coal bombustion were major emission sources of BaP. Emissions in the region of Beijing-Tianjin-Tangshan, Shenyang-Yingkou and Jinan-Zibo-Weifang were much higher than those in other regions. In comparison, the spatial distribution of BaP concentrations was almost the same as that of the emissions with a few diffusion effect. Concentrations of BaP in biota were much higher than those in other environmental compartments, which had the highest risk to human health. 95% of the total BaP amount was found in soil in Bohai coastal region, which implies that soil serves as the predominant sink of BaP. Fluxes from air to other compartments were major pathways of BaP inter-media transport. Most of the BaP entering the sea were transferred by airflow, which was also the crucial driving force in the spatial distribution processes of BaP. The Yellow River, Liaohe River and Daliao River played an important role in the spatial transformation processes of BaP. Compared with advection outflow, degradation was more important in removal processes of BaP. The model results indicated that the predicted concentrations of BaP in air, fresh water, soil and sediment generally agreed with field observations. The individual differences between model outputs and measured data could be attributed to the under-representation of the measured data. The modeled concentrations were generally lower than the observed values, probably due to the influence of emission from the surrounding area. According to the result of sensitivity analysis, emission rates, compartment dimensions, transport velocity and chemical persistence were the most influential parameters for the model output. The distributions of BaP concentration in air and soil were fitted well with lognormal distributions, and the coefficients of variances (CVs) were 0.46 and 1.53, respectively. The total emission of PFOS in Bohai costal region in 2010 were estimated to be 471.52 kg/a, 542.09 kg/a, 540.19 kg/a and 529.69 kg/a for the four emission scenarios separately, and fresh water was the main receptor of PFOS. Spatial distributions of the emssions in different scenarios were similar to each other, and emisisons in Weifang, Qingdao, Beijing, Tianjin and Dalian were significantly higher that those in other regions. The model result showed that regions with higher PFOS concentration were mainly distributed in the regions with heavy emission, and also extended to estuaries due to the transportation by river flow. Concentrations of PFOS in scenario 1, 3 and 4 were basically at the same level, while those in scenario 2 were slightly higher than the others. 52.96% of the total amount of PFOS accumulated in soil, which was the most important sink in Bohai coastal region. Direct emission was the main source of PFOS in soil. Compared with typical POPs such as BaP, much more PFOS were stored in aquatic envrionment. Flow of fresh water was the primary pathway for PFOS to enter the sea, and also the most important driving force for the spatial transportation of PFOS. Advection was the dominant removing process for PFOS in environmental system. Given the seasonal variance of fresh water flow rate, concentrations of PFOS in winter and spring were higher than those in summer and autumn, which might be due to the dilution effect of river water. The degree of variance displayed a negative correlation with the total flow rate of fresh water. In contrast to the concentrations, fluxes of PFOS into the sea in summer and autumn were higher than those in winter and spring. The increase of fresh water flow enhanced the overall transfer of PFOS. Generally, the ecological risk of PFOS in fresh water was fairly low in Bohai coastal region. However, the risk might increase significantly because of the seasonal change of fresh water flow rate in some regions. The values of modeled concentration fell in the same range of measured data, while the model output was slightly higher, which might be attributed to the uncertainty of model input, consideration of some rivers in the model and direct emission into the sea from some industrial sources along the coast. With consistency, standardization and extensibility, the model was redesigned and redeveloped into a user-friendly software. The softwater has three main functions, including simulating the fate of pollutants in steady and dynamic state, analyzing the sensitivity of model input and displaying the spatial distribution of model results. Detailed design was carried out for each function of the software.
公开日期	2015-07-07
内容类型	学位论文
源URL	[http://ir.rcees.ac.cn/handle/311016/15635]
专题	生态环境研究中心_城市与区域生态国家重点实验室
推荐引用方式 GB/T 7714	刘世杰. 环渤海地区持久性有机污染物空间多介质迁移模拟[D]. 北京. 中国科学院研究生院. 2014.