BP网络框架下MODIS气溶胶光学厚度产品估算中国东部PM2.5

近年来随着中国经济的快速发展,中国区域的大气污染情况日趋严重,大气污染监测与治理已刻不容缓.由于卫星遥感具有较广的空间覆盖、成本低等优点,卫星遥感反演气溶胶光学厚度(AOD)产品被普遍认为是地面PM2.5浓度的重要指标,且已被广泛地应用于地面PM2.5遥感监测.利用2007～2008年的MODIS/Terra气溶胶光学厚度产品,考虑中国东部地区5个大气成分站点风速、风向、温度、湿度和边界层高度等气象数据,构建后向(BP)神经网络,提出了基于MODIS AOD产品估算PM2.5的模型.利用5个大气成分站点PM2.5观测数据对模型进行散点拟合和时间序列拟合验证,结果表明:①从PM2.5观测值与估算值的散点回归分析来看,PM2.5估算值与观测值相关系数最好的为庐山站(R=0.6),其它4个站次之,但其相关系数均在0.4(中强相关)以上;②从PM2.5观测值与估算值的时间序列比对分析来看,PM2.5估算值和观测值差值随时间变化而变化,且存在明显的日际振荡现象,但经相邻5 d滑动平均处理,5个站点的PM2.5估算值与观测值相关系数得到普遍提升,滑动后的相关系数RMA均在0.7以上(除郑州外),庐山RMA达到0.83.结果表明在BP网络框架下,基于MODIS AOD产品估算PM2.5的模型能较好地应用于PM2.5监测.     

Study on the optical property and surface morphology of N doped TiO2 film deposited with different N2 flow rates by DCPMS

N doped TiO₂ films were deposited by direct current pulse magnetron sputtering system at room temperature. By using UV-Vis spectrophotometer and atomic force microscope, we studied the influence of N₂ flow rate on the optical property and surface morphology of films. The results indicate that the optical property and surface morphology of N doped TiO₂ film was dominated by the N₂ flow rate. The mean absorbency in visible range of pure TiO₂ films is near to 0%, which means that the pure TiO₂ could hardly display the photocatalytic property in visible range. When N₂ flow rate is 2 sccm, the mean absorbency in visible range of N doped TiO₂ film could reach at 24%. In this case, the film could be used as photocatalyst induced by visible light. While with increasing N₂ flow rate, the mean absorbency in visible range of N doped TiO₂ film decreased abruptly. Especially when N₂ flow rate exceeded 8 sccm, the mean absorbency in visible range of N doped TiO₂ film decreased to about 0%, which is like pure TiO₂ fimls.     

Chemical composition, mass closure and sources of atmospheric PM10 from industrial sites in Shenzhen, China

Concentrations of atmospheric PM10 and chemical components (including twenty-one elements, nine ions, organic carbon (OC) and elemental carbon (EC)) were measured at five sites in a heavily industrial region of Shenzhen, China in 2005. Results showed that PM10 concentrations exhibited the highest values at 264 μg/m3 at the site near a harbor with the influence of harbor activities. Sulfur exhibited the highest concentrations (from 2419 to 3995 ng/m3) of all the studied elements, which may be related to the influence of coal used as fuel in this area for industrial plants. This was verified by the high mass percentages of SO42-, which accounted for 34.3%-39.7% of the total ions. NO3-/SO42- ratios varied from 0.64-0.71, which implies coal combustion was predominant compared with vehicle emission. The anion/cation ratios range was close to 0.95, indicating anion deficiency in this region. The harbor site showed the highest OC and EC concentrations, with the influence of emission from vessels. Secondary organic carbon accounted for about 22.6%-38.7% of OC, with the highest percentage occurring at the site adjacent to a coal-fired power plant and wood plant. The mass closure model performed well in this heavily industrial region, with significant correlation obtained between chemically determined and gravimetrically measured PM10 mass. The main constituents of PM10 were found to be organic materials (30.9%-69.5%), followed by secondary inorganic aerosol (7.9%-25.0%), crustal materials (6.7%-13.8%), elemental carbon (3.5%-10.8%), sea salt (2.4%-6.2%) and trace elements (2.0%-4.9%) in this heavily industrialized region. Principal component analysis indicated that the main sources for particulate matter in this industrial region were crustal materials and coal/wood combustion, oil combustion, secondary aerosols, industrial processes and vehicle emission.     

Study on the optical property and surface morphology of N doped TiO2 film deposited with different N2 flow rates by DCPMS

N doped TiO₂ films were deposited by direct current pulse magnetron sputtering system at room temperature. By using UV-Vis spectrophotometer and atomic force microscope, we studied the influence of N₂ flow rate on the optical property and surface morphology of films. The results indicate that the optical property and surface morphology of N doped TiO₂ film was dominated by the N₂ flow rate. The mean absorbency in visible range of pure TiO₂ films is near to 0%, which means that the pure TiO₂ could hardly display the photocatalytic property in visible range. When N₂ flow rate is 2 sccm, the mean absorbency in visible range of N doped TiO₂ film could reach at 24%. In this case, the film could be used as photocatalyst induced by visible light. While with increasing N₂ flow rate, the mean absorbency in visible range of N doped TiO₂ film decreased abruptly. Especially when N₂ flow rate exceeded 8 sccm, the mean absorbency in visible range of N doped TiO₂ film decreased to about 0%, which is like pure TiO₂ fimls.     

基于光学在线监测及形态学研究的絮凝体强度分析方法

以PDA在线监测混凝过程和絮凝体形态学分析为基础,建立了絮凝体强度的分析评价方法.为了计算某一特定絮凝条件下形成絮凝体的黏结力,进行混凝实验并运用图像解析法及粒子图像测速技术研究絮凝体形态学特征.实验过程中将水样引入与光散射颗粒分析仪(PDA2000)相连的透明橡胶管内,并通过准确控制橡胶管内的水流速度梯度来改变作用于絮凝体上的剪切力,这样就可以在线监测絮体的破碎情况,然后根据PDA输出的FI曲线来确定絮凝体的临界破碎条件.根据临界破碎条件下剪切力、破碎力和黏结力的等量关系,确定黏结力系数k1,进而计算出可以表征絮凝体强度的黏结力B.该方法的有效性已经被大量以硫酸铝为混凝剂的腐殖酸混凝实验所证实.     

基于地基遥感的杭州地区气溶胶光学特性

利用2012年杭州、桐庐、建德、淳安CE-318太阳光度计的观测资料,反演获得了气溶胶光学厚度（AOD）、Ångström波长指数（AE）、单次散射反照率（SSA）和气溶胶粒子谱（ASD）等参数,分析了杭州地区气溶胶光学特性的变化规律.结果表明,2012年杭州、桐庐、建德、淳安AOD_440nm年均值分别为0.94±0.16、0.84±0.17、0.82±0.22、0.71±0.20,呈现出自东北向西南逐渐下降的变化趋势,是长三角地区AOD高值地区之一.AE_440-870nm年均值分别为1.24±0.12、1.19±0.17、1.06±0.04、1.04±0.10,表明杭州地区以半径较小的气溶胶粒子为主控模态.3~4月AE相对偏低与来自北方的沙尘粒子远距离输送有关.除淳安外,杭州、桐庐和建德AOD有明显的日变化特征.不同地区细模态粒子峰值半径春季、秋季和冬季均在0.15 μm左右,由于气溶胶粒子的吸湿增加导致夏季细模态粒子的峰值半径在0.25 μm左右;粗模态粒子峰值半径夏季、秋季和冬季均在2.94 μm左右,高于春季（1.7~2.2 μm）.SSA_440nm年均值分别为0.91±0.01、0.92±0.03、0.92±0.02、0.93±0.02,说明杭州地区气溶胶粒子为中等强度吸收性气溶胶.对气溶胶类型进行分类表明,杭州以生物质燃烧/城市工业型为主,而桐庐、建德和淳安以混合型为主.     

生态净化系统中DOM光学特性及影响因素分析:以盐龙湖春季为例

为了探究生态净化系统中溶解性有机物（DOM）的光学特性、空间分布特征及主要影响因子.以盐龙湖生态净化系统为例,取2017、2018年春季数据进行研究.结果表明,盐龙湖春季总磷、总氮、高锰酸盐指数浓度变化范围分别为0.05~0.25、1.25~2.75、3.99~7.17 mg·L^-1,出水溶解氧升高至（11.93±1.31）mg·L^-1、浊度降低至（13.23±2.24）NTU,而高锰酸盐指数变化不显著.主成分分析（PCA）表明盐龙湖原水、预处理区水质与外源汇入有关;而沉水植物区和深度净化区水质依赖于内源影响.荧光指数、腐殖化指数及生物源指数分析综合发现水体中DOM主要是源于陆生植物与土壤输入,腐殖化程度较低且新生的自生源DOM较多.PARAFAC模型将DOM可分为紫外光区类富里酸（239 nm,304 nm/407 nm）,可见光区类富里酸（256 nm,352 nm/439 nm）,色氨酸类蛋白质（276 nm/327 nm）和胡敏酸（292 nm,395 nm/491 nm）.紫外吸收指数表明盐龙湖原水、预处理单元、挺水植物区DOM光谱强度波动较大,沉水植物区、深度净化区DOM光谱强度较稳定.水质参数中对DOM光学特性有影响的因素主要是透明度、溶解氧、电导率、总氮和藻细胞数.     

京津冀内陆平原区PM2.5浓度时空变化定量模拟

近年来我国京津冀地区霾污染日趋严重,为揭示该地区PM_2.5时空变化特征,以京津冀内陆平原为研究区,以MODIS AOD数据作为主要预测因子,采用混合效应模型建立研究区2013~2014年AOD-PM_2.5逐日变化的关系模型.利用十折交叉验证法对模型拟合进行验证.结果表明,采用混合效应模型对AOD-PM_2.5进行时间上的校准能够提高二者间的相关性,模型拟合的PM_2.5质量浓度与地面实测值间的R²为0.78,经过交叉验证后R²为0.70,RMSE、RPE分别为20.80 μg·m^-3、28.76%.针对研究区冬季AOD有效值非随机性缺失带来的采样偏差,用校正因子对模型预测的2013~2014年间PM_2.5平均浓度进行校正,结果表明研究区内PM_2.5平均浓度均高于75 μg·m^-3,南部和西部地区的PM_2.5浓度相对较高,北部和东部地区PM_2.5浓度相对较低,呈现出"南高北低、西高东低"的分布趋势.研究结果表明混合效应模型能够适用于近地面PM_2.5监测,也为该区域大气颗粒物污染治理提供了科学依据.     

基于气溶胶光学特性的颗粒物来源分析

为初步探讨利用气溶胶光学指标判别污染物来源的适用性,选取天津市冬季一次重污染过程（2017年11月17—21日）,对气溶胶的七波段吸收系数、三波段散射系数及其化学组分进行在线观测及分析,研究气溶胶光学特性的变化,并结合化学组分定性分析污染过程不同阶段的污染来源.结果表明:SSA（单散射反照率）可以从散射性组分和吸光性组分对消光贡献的变化判断污染来源.污染积累期,颗粒物中散射性组分（SO₄2-、NO₃-、NH₄+）的增幅高于吸光性组分EC（元素碳）,导致污染积累期的SSA值高于污染前期和污染消散期,说明污染积累期存在较明显的二次转化过程.SAE（散射波长指数）可以从粒径角度推断污染来源.此次观测的污染积累期SAE值呈较明显的下降趋势,说明在细粒径段（2.5 μm以下）颗粒物粒径有增大的趋势,这主要与颗粒物中无机盐的吸湿增长及颗粒物之间的碰并有关.AAE（吸收波长指数）在一定程度上可以指示吸光颗粒物的类型.污染前期,BrC（棕色碳）在370、470 nm处对光吸收的贡献率分别为50.7%、33.8%;同期PM_2.5中ρ（Cl-）、ρ（K+）同步升高,卫星遥感显示,观测点周围有大量火点出现,推测主要受祭祖活动的影响.研究显示,气溶胶光学指标能够从散射性组分和吸光性组分对消光贡献变化、粒径变化、吸光颗粒物类型角度定性解析一部分污染来源,但其对于燃煤源和机动车等重要源类的指示作用还有待进一步研究.      

新疆奎独乌区域冬季大气重污染过程PM2.5组成特征及来源解析

为研究新疆奎独乌（奎屯、独山子、乌苏）区域冬季大气重污染过程的PM_2.5污染特征及其成因,于2015年2月4-10日在奎屯、独山子和乌苏三地开展PM_2.5样品采集,并对其中的元素、水溶性离子及碳组分进行测试,分析不同污染水平下PM_2.5中化学组分的变化规律.结果表明,采样期间奎独乌区域ρ（PM_2.5）日均值均超过GB 3095-2012《环境空气质量标准》二级标准（75 μg/m3）,2月9日ρ（PM_2.5）最高（298.58 μg/m3）,超标2.98倍.通过比较PM_2.5载带化学组分质量百分比发现,随着污染等级加剧,SO₄2-、NO₃-质量百分比呈逐渐增加的趋势,严重污染时SO₄2-、NO₃-质量百分比分别较轻度污染时增长11.7%、5.5%;NH₄+、碳组分及元素组分质量百分比则呈下降趋势,严重污染较轻度污染时分别下降0.7%、9.5%、2.4%;结合采样期间静稳及高湿的气象条件,说明此次重污染由本地污染物累积及二次颗粒物生成所致.随着污染水平的加重,SOR（硫氧化率）及NOR（氮氧化率）的值也在随之增大,说明污染越重大气二次转化程度越高,进一步验证了二次颗粒物是导致此次重污染的原因之一.对不同污染等级PM_2.5进行质量重构发现,PM_2.5中主要组分均为硫酸盐和OM（有机物）,硫酸盐和OM的质量百分比分别在23.0%~34.7%、16.4%~28.7%之间,说明此次重污染过程的主要污染源为燃煤及机动车尾气.