An air quality forecasting system in Beijing - Application to the study of dust storm events in China in May 2008

An air pollution forecast system, ARIA Regional, was implemented in 2007-2008 at the Beijing Municipality Environmental Monitoring Center, providing daily forecast of main pollutant concentrations. The chemistry-transport model CHIMERE was coupled with the dust emission model MB95 for restituting dust storm events in springtime so as to improve forecast results. Dust storm events were sporadic but could be extremely intense and then control air quality indexes close to the source areas but also far in the Beijing area. A dust episode having occurred at the end of May 2008 was analyzed in this article, and its impact of particulate matter on the Chinese air pollution index (API) was evaluated. Following our estimation, about 23 Tg of dust were emitted from source areas in Mongolia and in the Inner Mongolia of China, transporting towards southeast. This episode of dust storm influenced a large part of North China and East China, and also South Korea. The model result was then evaluated using satellite observations and in situ data. The simulated daily concentrations of total suspended particulate at 6:00 UTC had a similar spatial pattern with respect to OMI satellite aerosol index. Temporal evolution of dust plume was evaluated by comparing dust aerosol optical depth (AOD) calculated from the simulations with AOD derived from MODIS satellite products. Finally, the comparison of reported Chinese API in Beijing with API calculated from the simulation including dust emissions had showed the significant improvement of the model results taking into account mineral dust correctly.     

Three-dimensional hydrodynamic and water quality model for TMDL development of Lake Fuxian, China

Lake Fuxian is the largest deep freshwater lake in China. Although its average water quality meets Class I of the China National Water Quality Standard (CNWQS), i.e., GB3838-2002, monitoring data indicate that the water quality approaches the Class II threshold in some areas. Thus it is urgent to reduce the watershed load through the total maximum daily load (TMDL) program. A three-dimensional hydrodynamic and water quality model was developed for Lake Fuxian, simulating flow circulation and pollutant fate and transport. The model development process consists of several steps, including grid generation, initial and boundary condition configurations, and model calibration processes. The model accurately reproduced the observed water surface elevation, spatiotemporal variations in temperature, and total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) concentrations, suggesting a reasonable numerical representation of the prototype system for further TMDL analyses. The TMDL was calculated using two interpretations of the water quality standards for Class I of the CNWQS based on the maximum instantaneous surface and annual average surface water concentrations. Analysis of the first scenario indicated that the TN, TP and COD loads should be reduced by 66%, 68% and 57%, respectively. Water quality was the highest priority; however, local economic development and cost feasibility for load reduction can pose significant issues. In the second interpretation, the model results showed that, under the existing conditions, the average water quality meets the Class I standard and therefore load reduction is unnecessary. Future studies are needed to conduct risk and cost assessments for realistic decision-making.     

模糊标识指数与对应分析法在水质评价中的联合应用

水质评价对判断水体的污染状况,了解其污染程度和成因有重要的意义,并可为水资源管理及水污染控制提供科学依据,而适当的评价方法是保证评价结果科学合理的关键.因此,本文以青山湖流域为例,在单因子指数法、综合指数法、灰色关联法、改进的模糊层次分析法、水质指数评价法、综合水质标识指数法6种常用水质评价法的结果对比分析的基础上,提出了一种新的模糊标识指数法.该方法结合了改进的模糊层次分析法和综合水质标识法的优点,不仅给出水质级别和水功能区达标程度,而且克服了以往模糊层次分析法存在的低估污染的严重性及不能评价劣Ⅴ类水质的缺点,更加适用于水质状况的评价.同时,在模糊标准化处理基础上,采用对应分析法,将采样点与变量有机地结合起来进行分析.结果表明,青山湖流域的总体水质状况以劣Ⅴ类为主,总体水功能区达标率仅10.34%,流域根据受污染情况被分为3个区,Ⅰ区、Ⅱ区、Ⅲ区的主要污染因子分别是TN、NH4+-N与COD、TP.模糊标识指数法与对应分析法的联合应用可以全面分析流域水质状况,给出科学合理的评价结果.     

1980—2010年温榆河的水环境质量时空演变特征

以温榆河流域的主要超标污染物 COD 和氨氮为研究对象,通过历史数据和现场调查,系统研究了1980—2010年间温榆河的水环境质量时空演变特征.结果表明,温榆河流域水环境质量经历了清洁-污染-重度污染-污染遏制的过程,但水质现状均不达标;温榆河流域水环境质量好坏依次是上段>下段,温榆河>坝河>清河,并且Pearson相关分析表明,温榆河下段COD和NH+4-N浓度主要受清河影响;温榆河流域COD污染逐步遏制(超标倍数<1)、NH+4-N污染凸显(超标倍数8～20),耗氧物质处于从COD为主向NH+4-N为主转换的阶段;支流清河和坝河不仅是温榆河干流入河污染负荷的首要输入途径,而且支流上污水集中处理设施的排水是温榆河干流的首要补给来源(70.1%),其运行状况与升级改造对改善温榆河水环境质量至关重要.     

长治市社会经济发展与环境质量变化相关趋势分析

系统阐述了长治市的社会经济发展及主要环境污染指标的变化趋势,利用库兹涅茨曲线对二者相互关系进行了相关性分析。     

关于我国环境空气质量监测点位设置的思考

设置各种空气质量监测点位时,应以监测网络的监测目的为根本出发点,并同时考虑点位功能和空间代表尺度、点位环境条件以及实际经济技术条件等因素。一个完整的环境空气质量监测网络应涵盖各类功能的监测点位,从而达到监测网络建设的多目标要求,然而空气质量监测点位的建设是一个不断发展和完善的过程。目前我国城市空气质量监测点以空气质量评价点为主,其目的是掌握城市整体空气质量状况和长期变化趋势,为环境管理和污染防治提供决策依据,但这类监测点位的功能相对单一,难以满足公众了解详尽的空气质量状况信息的需求。未来,随着监测投入的增加,我国应进一步完善地方监测网络建设,使之涵盖不同功能的监测点位,从而更好地为公众提供空气质量预警信息和健康指引。     

北湖流域水质改善系统动力学研究

利用系统动力学擅长研究动态、非线性复杂系统的特点,将其应用于北湖水质改善分析,构建了系统动力学-水质耦合模型,可实现长时间序列的连续模拟和水环境管理的情景分析。文章定量分析了三产比例调整、城镇化率提高与污水集中处理等因素对流域纳污控制及水质改善的影响,推演出可协调经济发展-水环境保护-污水治理资金三方矛盾的合理方案,为类似小城镇的发展提供可借鉴的思路和方法。     

R型聚类对辽河不同断面水质指标相关性分析

河流水质监测中许多指标常常存在着一定的相关性,通过对水质指标相关性研究,可了解水质指标间影响关系及河流污染物的特点,指导河流水污染治理,提高水质量标准。以辽河为例,采用R型聚类方法对辽河不同断面水质指标的相关性进行分析,应用DPS统计软件,通过计算机对监测数据进行运算得出相关系数矩阵和变量的分类树形图。通过分析可看出化学需氧量与五日生化需氧量、高锰酸盐指数与氨氮相关密切。文中对各种水质指标相关关系的内在关联进行深入研究,分析相关指标间的相互作用,以期达到对影响因子的全方位监测与控制,实现对辽河水污染治理及水环境监测评价的作用。     

成都市大气水汽与空气质量关系的研究

为深入分析大气水汽对空气质量的影响,基于2016年成都温江国家气候观象台的气象观测资料和成都市环境监测中心的环境空气质量指数(AQI),首先利用地面气象要素估算出逐时的大气可降水量(PWV),继而结合空气质量指数资料研究了成都地区降水、静稳天气、太阳辐射强度等气象条件对空气质量及其与大气水汽关系的影响.结果表明:在降水条件下,臭氧(O_3)浓度随着PWV的增大而显著减小,PWV与PM_(2.5)、PM_(10)浓度的正相关系数减小,其中对PWV与PM_(10)浓度的相关性影响最大,相关系数减小47.62%.PWV与O_3的负相关系数在春季增大、夏季减小;PWV与PM_(2.5)的正相关系数在秋、冬季减小.当天气处于高静稳指数时,PWV变化对污染物浓度变化的影响更为显著.不同太阳辐射强度下,PWV与O_3的相关性也不同,随着太阳辐射增强,PWV与PM_(2.5)、PM_(10)的相关性从正相关转变为负相关.     

基于数据分解的AQI的CEEMD-Elman神经网络预测研究

针对Elman神经网络在预测空气质量指数（AQI）时易受到数据非平稳性的影响导致预测趋势良好但准确度较低的问题,提出以互补集合经验模态分解（Complementary Ensemble Empirical Mode Decomposition,CEEMD）为基础的CEEMD-Elman模型.应用CEEMD对AQI序列分解成不同时间尺度上的本征模态函数分量和剩余分量,进而首次将对非平稳的AQI序列的预测研究转化为对多个平稳的本征模态函数分量的研究.分别与Elman单一模型、EMD-Elman模型、BP单一模型及CEEMD-BP模型进行实验对比.结果表明：应用该方法建立的模型的均方误差、平均绝对误差和平均绝对百分比误差分别为4.80、0.71、1.84%,均小于其他模型结果;对应空气质量等级预报正确天数的频率为94.12%.该模型能有效的降低非平稳性对实验预测结果的影响,实现对空气质量等级的准确预报;该研究为进一步预测AQI的走向提供了有效依据,也为政府决策和管理部门制定空气污染控制提供了更充分的参考.