Water quality evaluation based on improved fuzzy matter-element method

For natural water, method of water quality evaluation based on improved fuzzy matter-element evaluation method is presented. Two important parts are improved, the weights determining and fuzzy membership functions. The coefficient of variation of each indicator is used to determine the weight instead of traditional calculating superscales method. On the other hand, fuzzy matter-elements are constructed, and normal membership degrees are used instead of traditional trapezoidal ones. The composite fuzzy matter-elements with associated coefficient are constructed through associated transformation. The levels of natural water quality are determined according to the principle of maximum correlation. The improved fuzzy matter-element evaluation method is applied to evaluate water quality of the Luokou mainstream estuary at the first ten weeks in 2011 with the coefficient of variation method determining the weights. Water quality of Luokou mainstream estuary is dropping from level I to level II. The results of the improved evaluation method are basically the same as the official water quality. The variation coefficient method can reduce the workload, and overcome the adverse effects from abnormal values, compared with the traditional calculating superscales method. The results of improved fuzzy matter-element evaluation method are more credible than the ones of the traditional evaluation method. The improved evaluation method can use information of monitoring data more scientifically and comprehensively, and broaden a new evaluation method for water quality assessment.     

上海市大气总汞季节变化特征及与气象条件的关系

2008年到2010年对上海市西南部大气中总汞(TGM———Total Gaseous Mercury)的污染水平进行监测,结果表明TGM日均浓度为ND~57.23ng/m(3(7.79±3.29)ng/m)3。TGM呈现出一定的季节性变化特征,浓度最高的是秋季,然后依次是冬季、春季、夏季,平均浓度分别为(9.30±2.48)、(8.32±2.79)、(7.78±2.33)、(2.16±3.29)ng/m3。TGM浓度受东南风向影响最大,其次为西北和东北风向。在置信水平为95%的情况下,TGM浓度与日平均温度呈正相关性,而与日温差、相对湿度、日相对湿度差、风速无显著相关性。但TGM浓度分别与日均O3浓度和NO2浓度均呈显著正相关。利用HYSPLIT_4模型对TGM浓度高值与低值几天的空气气团来源轨迹进行反演,结果发现高低浓度日的气团来源略有差别,总体上看,冬季、春季和秋季受北方气团影响较大,夏季则受我国东部海域影响,具体的局部和长距离输送的贡献需要进一步研究。     

污水处理厂不同工艺的污泥脱水效能分析及其影响因素研究

污泥脱水是污泥减量的主要手段,直接影响到后续污泥处理处置.本研究以北京某大型污水处理厂A2/O工艺和A2/O-MBR工艺污泥脱水为对象,基于2013年全年的运行数据,分析不同工艺的污泥脱水效果、絮凝剂投配率、污泥脱水电耗和污泥脱水成本,并通过冗余分析(RDA)研究了不同污水处理工艺污泥脱水性能的影响因素.结果表明,污泥脱水性能和絮凝剂投配率均呈现季节性变化特征,冬季污泥较难脱水,絮凝剂消耗大.A2/O-MBR工艺的脱水污泥含水率年均值为(81.92±1.64)%,A2/O工艺为(82.56±1.35)%,污泥脱水絮凝剂消耗(以DS计,下同)分别为(8.70±7.25)kg·t-1和(7.42±2.96)kg·t-1,电耗(以DS计,下同)分别为331.82 k W·h·t-1和121.57 k W·h·t-1.A2/O-MBR工艺的污泥脱水絮凝剂成本(以DS计,下同)为204.76元·t-1,用电成本为231.61元·t-1;A2/O工艺的污泥脱水絮凝剂成本为175.00元·t-1,用电成本为84.86元·t-1.RDA分析表明,水温等季节性因素引起污泥有机质变化是影响污泥脱水性能的关键因素之一,此外,污泥龄也与污泥脱水性能有一定相关性.     

三峡库区回水区营养盐和叶绿素a的时空变化及其相互关系

为探讨三峡水库调度运行背景下,库区回水区营养盐和叶绿素a时空变化及其相互关系,于2013年5月~2014年5月在三峡库区北岸最大、也是库区水华频发的支流——澎溪河的回水区高阳平湖进行了定点和高频监测.结果表明水体热分层是高阳平湖水华发生的诱导因素.高阳平湖水体热分层发生于春季(3月初),消亡于夏末(9月中旬),冬季没有分层.2014年春季,随着水体分层的发生和发展,表层叶绿素a在69 d内从14.92μg·L-1骤增至183.73μg·L-1,并暴发水华,之后叶绿素a随着混合层深度增加而下降.水体没有分层时,表、中和底层营养盐浓度相近;水体分层之后,各层磷浓度有了明显差异,表层和底层总磷浓度相差(0.18±0.04)mg·L-1.高水位期(9月至次年4月),高阳平湖硝氮和溶解性磷高于低水位期(5~8月)的含量,分别占总氮、总磷浓度的71.4%~95.4%和42.7%~94.4%,是总氮和总磷的主要组成部分,干流倒灌输入的硝氮和溶解性磷是其主要来源.     

常州夏冬季PM2.5中无机组分昼夜变化特征与来源解析

为探讨常州大气气溶胶中无机组分的昼夜变化特征,在夏冬两季分别连续采集1个月的PM2.5样品,对比分析了11种水溶性离子和13种重金属元素的昼夜特征和来源.结果表明,夏冬两季PM2.5平均质量浓度白天高于夜间,水溶性离子占比夜间稍高于白天.冬季水溶性离子占PM2.5的比例(44%~45%)高于夏季(31%~36%),而重金属元素呈现相反的季节性特征(冬季白天3.03%,夜间2.29%;夏季白天4.40%,夜间4.51%).SO_4~(2-)、NO_3~-、NH_4~+是主要的二次离子,占总水溶性离子77%~85%,说明常州市大气污染呈二次污染为主的复合污染特征.夏季强太阳辐射的光化学反应导致白天SO_4~(2-)占比(49.0%)稍高于夜间(41.1%),而白天高温NH_4NO_3分解,使NO_3~-浓度白天(1.98μg·m-3)远低于夜间(5.10μg·m-3).NH_4~+与SO_4~(2-)、NO_3~-之间好的线性相关性及预测NH_4~+与实测NH_4~+的比值接近1,表明NH_4~+主要以(NH4)2SO4,NH_4NO_3和NH4Cl形态存在.离子平衡表明夏季颗粒物呈弱碱性,冬季呈中性.Fe、Al和Zn这3种重金属元素占比最大,Fe和Al元素白天占比明显高于夜间,Zn正好相反.无机组分相关性及主成分分析表明,无机组分都来自二次生成、扬尘和交通等排放源,表现一定的季节性和昼夜变化特征.     

烟台市环境受体PM2.5四季污染特征与来源解析

于2016～2017年四季在烟台市3个点位采集了PM_(2.5)样品,分析了其质量浓度和化学组分特征.利用CMB模型对受体进行解析,并利用后向轨迹和PSCF对传输气流和潜在源区进行了分析.结果表明,烟台市监测点位冬季、春季、夏季和秋季的PM_(2.5)平均质量浓度分别为(89. 45±56. 80)、(76. 78±28. 44)、(32. 65±17. 92)和(57. 32±24. 60)μg·m~(-3). PM_(2.5)浓度表现出明显的季节变化特征(P 0. 01).全年PM_(2.5)各源类分担率大小依次为:二次硝酸盐源(20. 3%)城市扬尘源(15. 7%)机动车排放源(14. 9%)燃煤源(13. 8%)二次硫酸盐源(12. 8%) SOC(6. 1%)建筑水泥尘源(5. 5%)海盐源(2. 9%),可以看到烟台市以二次源、扬尘、机动车排放源和燃煤源为主要污染源.春季硝酸盐源和城市扬尘源是重要贡献源类,夏季硫酸盐源贡献突出,燃煤源在秋冬季占比突出.烟台市气流输送和潜在源区也呈现出明显的季节变化:冬季主要受烟台市短距离输送的影响;夏季主要受烟台东部沿海和本地的影响;春秋季主要受山东东北部和东部沿海地区的区域传输和烟台市本地源的影响.     

乌鲁木齐河源区黑碳气溶胶浓度特征及其来源分析

利用七波段黑碳仪对2016年8月—2017年7月乌鲁木齐河源区大气中黑碳气溶胶进行了实时监测,并结合同时期气象资料对该区域黑碳气溶胶浓度变化特征、影响因子和可能来源进行了分析.结果表明,观测期间乌鲁木齐河源区黑碳浓度在102～1525 ng·m~(-3)之间变化,均值为520 ng·m~(-3).春季、夏季、秋季和冬季的浓度分别为425、536、686和427 ng·m~(-3),呈秋季最高,夏季次之,冬、春季低的季节变化特点.日内变化具有明显的双峰双谷特征,在当地时间8:00—9:00(与北京时间的时差为2小时,即为北京时间10:00—11:00,下同)和16:00—19:00有两个明显的峰值,可能与当地的排放和气象因素有关.乌鲁木齐河源区黑碳的本底浓度在春季、夏季和秋季分别为253、271和290 ng·m~(-3),而冬季黑碳的本底浓度仅为162 ng·m~(-3).与其他偏远地区相比,乌鲁木齐河源区因受较多排放源影响,黑碳浓度本底值较高.黑碳气溶胶浓度与气象因素相关性显著,当风速小于2 m·s~(-1)时,黑碳的平均浓度明显偏高,当相对湿度大于55%时,黑碳浓度明显偏低.由浓度权重轨迹分析和波长吸收指数(AAE)可知,乌鲁木齐河源区的黑碳浓度,除了受本地化石燃料燃烧和生物质燃烧排放的影响以外,还可能受到中亚地区远距离传输的影响.     

成都市冬季大气消光系数及其组成的特征研究

由于气溶胶吸湿增长的复杂性和不确定性,大气消光的演化机理至今尚不十分清晰.为此,利用成都市2017年12月浊度仪和黑碳仪的逐时观测资料,结合同时次的环境气象监测数据,系统研究了该区域冬季对应550 nm大气消光系数及其组成的特征.结果表明:①观测期间大气消光系数为(1173.42±641.21) Mm~(-1),其中"干"气溶胶散射系数、"干"气溶胶吸收系数、干洁大气散射系数、气态污染物吸收系数和气溶胶吸湿性消光系数对其平均贡献率分别是53.02%、6.54%、1.50%、1.65%和37.29%.②大气消光系数、"干"气溶胶散射系数和气溶胶吸湿性消光系数的日变化为"单峰单谷型",而"干"气溶胶吸收系数和气态污染物吸收系数的日变化则分别表现为"单谷型"和"双峰双谷型".③明确了单位质量大气消光系数及其组成随相对湿度的变化特征,并就其各自成因进行了分析.     

Characteristics of volatile organic compounds, NO2, and effects on ozone formation at a site with high ozone level in Chengdu

Chengdu is a megacity in the southwest of China with high ozone (O₃) mixing ratio. Observation of volatile organic compounds (VOCs), NO₂ and O₃ with high temporal resolution was conducted in Chengdu to investigate the chemical processes and causes of high O₃ levels. The hourly mixing ratios of VOCs, NO₂, and O₃ were monitored by an online system from 28 August to 7 October, 2016. According to meteorological conditions, Chengdu, with relative warm weather and low wind speed, is favorable to O₃ formation. Part of the O₃ in Chengdu may be transported from the downtown area. In O₃ episodes, the average mixing ratios of NO₂ and O₃ were 20.20?ppbv and 47.95?ppbv, respectively. In non-O₃ episodes, the average mixing ratios of NO₂ and O₃ were 16.38?ppbv and 35.15?ppbv, respectively. The average mixing ratio of total VOCs (TVOCs) was 40.29?ppbv in non-O₃ episodes, which was lower than that in O₃ episodes (53.19?ppbv). Alkenes comprised 51.7% of the total O₃ formation potential (OFP) in Chengdu, followed by aromatics which accounted for 24.2%. Ethylene, trans-pentene, propene, and BTEX (benzene, ethylbenzene, toluene, m/p-xylene, o-xylene) were also major contributors to the OFP in Chengdu. In O₃ episodes, intensive secondary formations were observed during the campaign. Oxygenated VOCs (OVOCs), such as acetone, Methylethylketone (MEK), and Methylvinylketone (MVK) were abundant. Isoprene rapidly converted to MVK and Methacrolein (MACR) during O₃ episodes. Acetone was mainly the oxidant of C3-C5 hydrocarbons.     

Air pollution characteristics and their relationship with emissions and meteorology in the Yangtze River Delta region during 2014–2016

With rapid economic growth and urbanization, the Yangtze River Delta(YRD) region in China has experienced serious air pollution challenges. In this study, we analyzed the air pollution characteristics and their relationship with emissions and meteorology in the YRD region during 2014–2016. In recent years, the concentrations of all air pollutants, except O_3,decreased. Spatially, the PM_(2.5), PM_(10), SO_2, and CO concentrations were higher in the northern YRD region, and NO_2 and O_3 were higher in the central YRD region. Based on the number of non-attainment days(i.e., days with air quality index greater than 100), PM_(2.5) was the largest contributor to air pollution in the YRD region, followed by O_3, PM_(10), and NO_2.However, particulate matter pollution has declined gradually, while O_3 pollution worsened.Meteorological conditions mainly influenced day-to-day variations in pollutant concentrations. PM_(2.5) concentration was inversely related to wind speed, while O_3 concentration was positively correlated with temperature and negatively correlated with relative humidity.The air quality improvement in recent years was mainly attributed to emission reductions.During 2014–2016, PM_(2.5), PM_(10), SO_2, NO_x, CO, NH_3, and volatile organic compound(VOC)emissions in the YRD region were reduced by 26.3%, 29.2%, 32.4%, 8.1%, 15.9%, 4.5%, and0.3%, respectively. Regional transport also contributed to the air pollution. During regional haze periods, pollutants from North China and East China aggravated the pollution in the YRD region. Our findings suggest that emission reduction and regional joint prevention and control helped to improve the air quality in the YRD region.