南京地区相对湿度对气溶胶含量的影响

为了研究南京地区相对湿度对气溶胶的影响,利用位于南京信息工程大学的拉曼-瑞利-米氏激光雷达,分析湿度廓线对消光系数的影响;利用2014年3月~2015年2月国控点环境监测数据对可吸入颗粒物浓度特征进行统计,并与相对湿度进行逐月和四季对比分析,并计算各参数之间的相关系数,以期为南京市的城市布局与规划、大气污染治理等提供更多参考.结果表明,低空气溶胶的消光系数廓线与相对湿度廓线变化趋势高度一致,地面相对湿度与可吸入颗粒物浓度在一定湿度范围（以不发生重力沉降为界限）内,相对湿度越大越有利于颗粒物的形成,超过这个范围,相对湿度越大,颗粒物浓度越低,在南京地区,对于PM₁₀来说,这个界限在40%~49%,对于PM_2.5来说,这个界限在50%~59%.     

成都冬季一次持续污染过程气象成因及气溶胶垂直结构和演变特征

基于气溶胶激光雷达观测和环境监测站污染物浓度数据、气象观测资料及HYSPLIT后向轨迹模式,分析了2017年12月中下旬,成都市一次本地积累和沙尘输送影响的持续污染过程中污染物浓度、污染物来源、天气系统和气溶胶消光系数的垂直分布及演变.结果表明:①此次污染过程持续时间长,根据气象条件和主要污染物种类,分为本地污染累积、北方沙尘输送和混合影响3个阶段.②本地污染积累阶段,消光系数垂直分布不均匀,受湿度、太阳辐照与逆温层等气象因子的影响,垂直结构变化较大.消光系数最大值多出现在250 m附近,此阶段退偏比数值很小.③沙尘影响阶段,消光系数较前期明显下降,高值区位于250 m及2 km处.退偏比显示沙尘粒子于29日午后开始逐渐抵达成都市2 km高空,并于夜间达到峰值.退偏比相较本地污染累积阶段明显增大,各时段退偏比结构类似,近地面数值略低于高空.④混合影响阶段,消光系数强度小幅回升,退偏比显示有部分沙尘粒子漂浮在1～2 km高度上.     

聊城冬季一重污染过程PM2.5污染特征及成因分析

北方秋冬季为重污染过程频发季节,为了解聊城市冬季重污染过程中PM_(2.5)及化学组分污染特征,于2016年1月7~11日在聊城市区开展PM_(2.5)样品采集并分析了其中水溶性离子、碳成分及无机金属元素这3种化学组分,并对污染特征及成因进行了分析.结果表明,此次污染过程PM_(2.5)浓度呈现明显的倒V字型,平均浓度为238.3μg·m~(-3),超过国家环境空气质量标准(GB 3095-2012)二级浓度限值2.2倍;NH_4~+、NO_3~-和SO_4~(2-)为PM_(2.5)的主要水溶性离子成分;随污染加重或减轻,NH_4~+、SO_4~(2-)、NO_3~-、Cl-和Mg~(2+)浓度呈现增加或降低趋势,而Ca~(2+)变化趋势与之相反.污染鼎盛时,NH_4~+、NO_3~-和SO_4~(2-)浓度分别为48.96、68.45和80.55μg·m~(-3),达到起始阶段的6.29、7.31和7.84倍;过程期间OC和EC的浓度为20.8~60.2μg·m~(-3)和3.0~7.5μg·m~(-3),OC浓度高于EC且变化幅度明显偏大;过程期间各日无机金属元素浓度和分别为10.2、22.4、16.0、19.6和8.2μg·m~(-3),富集因子(EF)结果显示,各元素EF均小于10,未被富集,表明污染过程中其主要来源于地壳等自然源;PM_(2.5)质量浓度重构结果表明,有机物(OM)、SO_4~(2-)和NO_3~-为PM_(2.5)的主要组分,其次为NH_4~+、地壳物质和其他离子,EC和微量元素含量相对较低.随着PM_(2.5)污染加重,二次无机盐(SO_4~(2-)、NO_3~-及NH_4~+)浓度及所占比例均随之增加,OM浓度随之增加但比例有所下降,而地壳物质浓度及比例均下降,表明二次无机转化是此次污染过程的主要原因,主要受燃煤和机动车排放影响.     

天津市区夏季碳气溶胶特征及改进的二次有机碳估算方法

为更加准确地估算环境受体PM_2.5中SOC（二次有机碳）的质量浓度,于2015年6-8月利用在线监测仪器同步采集小时分辨率的PM_2.5及OC（有机碳）和EC（元素碳）样品数据,分析碳气溶胶的变化特征,并尝试运用改进的EC示踪法估算ρ（SOC）.结果表明:天津市区夏季ρ（PM_2.5）为（70.9±46.0）μg/m3,ρ（OC）和ρ（EC）分别为（7.6±3.1）（2.2±1.5）μg/m3,占ρ（PM_2.5）的11.8%±4.6%和3.1%±1.4%,OC/EC（质量浓度之比,下同）的平均值为4.0±2.0.ρ（OC）与ρ（EC）之间的Pearson相关系数（R）仅为0.66,说明OC和EC的来源较为复杂,SOC的产生可能是重要影响因素.ρ（NO₂）与OC/EC呈显著负相关（R=-0.47,P < 0.01）,并且OC/EC（4.0）相对较低,说明天津市区机动车可能对碳气溶胶具有重要影响.ρ（SO₂）与ρ（OC）、ρ（EC）的相关性较低（R均为0.33,P均小于0.01）,说明天津市区碳气溶胶可能受燃煤源的影响较低.改进的EC示踪法主要是利用O₃和CO、EC作为光化学反应和一次源排放的指标,并结合ρ（OC）、ρ（EC）和OC/EC的变化特征,逐步筛选一次排放源主导的时间段的ρ（OC）和ρ（EC）数据,然后利用最小二乘法拟合获得ρ（OC）和ρ（EC）的线性方程,最后进行ρ（SOC）和ρ（POC）（POC为一次有机碳）的估算.天津市区夏季ρ（SOC）的平均值为（2.5±2.0）μg/m3,分别占ρ（OC）和ρ（PM_2.5）的28.8%±15.0%和3.7%±3.6%;ρ（POC）的平均值为（5.2±1.7）μg/m3,分别占ρ（OC）和ρ（PM_2.5）的71.2%±15.0%和8.1%±5.2%,说明天津市区夏季有机碳的主要来源是一次排放源.研究显示,相比于EC示踪法,改进的EC示踪法估算的ρ（SOC）明显降低,ρ（POC）明显升高.AT（大气温度）对ρ（SOC）的影响较为显著,而WS（风速）对ρ（POC）的影响较为显著.      

Insights into the formation of secondary organic carbon in the summertime in urban Shanghai

To investigate formation mechanisms of secondary organic carbon(SOC) in Eastern China,measurements were conducted in an urban site in Shanghai in the summer of 2015. A period of high O_3 concentrations(daily peak 120 ppb) was observed, during which daily maximum SOC concentrations exceeding 9.0 μg/(C·m~3). Diurnal variations of SOC concentration and SOC/organic carbon(OC) ratio exhibited both daytime and nighttime peaks. The SOC concentrations correlated well with O_x(= O_3+ NO_2) and relative humidity in the daytime and nighttime, respectively, suggesting that secondary organic aerosol formation in Shanghai is driven by both photochemical production and aqueous phase reactions. Single particle mass spectrometry was used to examine the formation pathways of SOC. Along with the daytime increase of SOC, the number fraction of elemental carbon(EC) particles coated with OC quickly increased from 38.1% to 61.9% in the size range of 250–2000 nm, which was likely due to gas-to-particle partitioning of photochemically generated semi-volatile organic compounds onto EC particles. In the nighttime, particles rich in OC components were highly hygroscopic, and number fraction of these particles correlated well with relative humidity and SOC/OC nocturnal peaks. Meanwhile, as an aqueous-phase SOC tracer, particles that contained oxalate-Fe(III) complex also peaked at night. These observations suggested that aqueous-phase processes had an important contribution to the SOC nighttime formation. The influence of aerosol acidity on SOC formation was studied by both bulk and single particle level measurements, suggesting that the aqueous-phase formation of SOC was enhanced by particle acidity.     

冬季南京城市大气气溶胶吸湿性观测研究

气溶胶吸湿性不仅影响颗粒物非均相化学反应过程和大气能见度,且对云凝结核形成起决定性作用.本研究运用加湿串联拆分迁移分析仪(H-TDMA)对冬季南京城市大气气溶胶吸湿性进行外场观测研究.结果表明:吸湿增长因子概率分布函数(GF-PDF)呈双峰分布,峰值分别为1.000±0.010(弱吸湿峰)和1.400±0.035(强吸湿峰);在85%相对湿度条件下,不同粒径段(40、80、110、150、200 nm)弱吸湿组粒子数目占比(NFLH)随粒径的增大从40%降低至20%,而强吸湿组粒子数目占比(NFMH)却从60%增加到80%.弱吸湿组GF-PDF离散程度(σLH)在0.04~0.05之间,而强吸湿组GF-PDF离散程度(σMH)0.1,说明强吸湿组粒子化学成分较复杂,外混合程度较高.对比各粒径段气溶胶吸湿性日变化规律发现,平均吸湿增长因子(GFmean)和NFMH均呈双峰特征,峰值分别出现在7:00和17:00左右.受夜晚边界层降低、强吸湿性组分非均相转化生成等影响,GFmean和NFMH夜间数值整体大于白天;受降水等气象条件影响,污染时段所有粒径段气溶胶的GFmean和NFMH均高于清洁时段.     

邯郸市黑碳气溶胶浓度变化及影响因素分析

根据2013年3月—2017年2月邯郸市河北工程大学站点的黑碳气溶胶、PM2.5、大气污染物的小时浓度数据及常规气象数据,对邯郸市黑碳浓度的时间变化特征及影响因素进行分析.结果表明,4年来邯郸市黑碳浓度呈逐年下降的趋势:与2013年相比,2014—2016年黑碳气溶胶浓度分别下降了5%、16%、24%;邯郸市黑碳气溶胶浓度的季节变化趋势基本一致且季节变化特征明显,冬季黑碳气溶胶浓度最高,秋季次之,春夏两季最低,其中,冬季平均浓度分别是春、夏、秋季的2.07、2.77、1.49倍;其日变化呈单峰单谷状,且4个季节的日变化趋势相同,峰值均出现在6:00—8:00,谷值均出现在14:00—15:00.黑碳与PM2.5的相关系数r为0.860,相关性显著,说明黑碳气溶胶和PM2.5的来源大部分是一致的;风速和风向对黑碳气溶胶浓度也有影响,黑碳气溶胶浓度随风速增加而降低;4个季节高频风向为南-西南方向,且该风向下黑碳气溶胶浓度均较高,冬季南-西南风向下的黑碳浓度最高;应用后向轨迹对研究时段内4段重污染期间的气流轨迹进行模拟发现,邯郸市黑碳气溶胶浓度较高的主要原因是本地源排放和近距离传输,远距离传输贡献较小.     

强化混凝和改性活性炭对二级出水DON的作用机制

探讨强化混凝和改性活性炭对城市污水厂二级出水中溶解性有机氮（DON）作用机制,分析相对分子量以及亲疏水组分变化,并考察氯化消毒副产物生成势变化特征,结合三维荧光（3DEEM）光谱分析手段,对强化混凝和活性炭吸附前后DON组成,化学结构特征进行研究.结果表明：强化混凝可以明显提高DON的去除效果,DON去除率通过pH值强化混凝提高到1.45倍,臭氧强化混凝提高到2.06倍,PAC强化混凝提高到2.09倍,PAM强化混凝提高到1.96倍.活性炭对DON吸附过程更符合准二级动力学模型.DON吸附过程中,酸改性活性炭表面主要是π-π色散力作用机理,而碱改性活性炭表面主要是给电子-受电子复合物形成机制.在强化混凝和活性炭吸附作用下,DON的相对分子量和组分发生较大变化,而消毒副产物的生成势大幅下降.经3DEEM和光谱区域体积积分法（FRI）分析,在强化混凝和活性炭吸附过程中DON及消毒副产物生成潜势与荧光区域Ⅱ和区域Ⅳ所代表物质有关.     

阴离子对Acidithiobacillus ferrooxidans氧化活性及次生铁矿物形成影响

酸性矿山废水（AMD）具有酸度高并含有大量可溶性Fe、硫酸根及重（类）金属的特点,采用生物矿化方法促使AMD中Fe向羟基硫酸铁次生矿物转变,对AMD后期石灰中和减少氢氧化铁和废石膏的产生,提高中和效率具有实际意义.通过模拟酸性矿山废水,考察了Cl^-、NO₃^-、PO₄^3-3种阴离子对嗜酸性氧化亚铁硫杆菌（A.ferrooxidans）体系中pH值、Fe²⁺氧化率、总Fe沉淀率、次生铁矿物矿相的影响.结果表明,高浓度阴离子对A.ferrooxidans氧化Fe²⁺能力具有抑制作用.A.ferrooxidans对阴离子的耐受性依次为PO₄^3- > NO₃^- > Cl^-.阴离子浓度在A.ferrooxidans耐受范围内时,其对Fe²⁺的生物氧化速率基本没有影响.但高浓度阴离子会通过抑制A.ferrooxidans的氧化活性,从而间接影响Fe³⁺的水解成矿过程,导致培养终点时总Fe沉淀率降低和次生铁矿物产量减少.受Fe³⁺供应速率降低的影响,次生铁矿物的合成途径易向施氏矿物转变.     

Sensitivity evaluation of the visual,tactile, and auditory detection response task method while driving

Objectives: In this article, we evaluate the sensitivity to cognitive load of 3 versions of the Detection Response Task method (DRT), proposed in ISO Draft Standard DIS-17488.

Methods: We present a user study with 30 participants in which we compared the sensitivity to cognitive load of visual, audio, and tactile DRT in a simulated driving environment. The amount of cognitive load was manipulated with secondary n-back tasks at 2 levels of difficulty (0-back and 1-back). We also explored whether the DRT method is least sensitive to cognitive load when the stimuli and secondary task are of the same modality. For this purpose, we used 3 forms to present the n-back task stimuli: visual, audio, and tactile. Responses to the task were always vocal. The experiment was based on a between-subject design (the DRT modalities) with 2 levels of within-subject design study (modalities and difficulty of the secondary n-back tasks). The participants' primary task in the study was to drive safely, and a second priority was to answer to DRT stimuli and perform secondary tasks.

Results: The results indicate that all 3 versions of the DRT tested were sensitive to detecting the difference in cognitive load between the reference driving period and driving and engaging in the secondary tasks. Only the visual DRT discriminated between the 0-back and 1-back conditions on mean response time. Contrary to expectations, no interaction was observed between DRT modality and the stimuli modality used for presentation of the secondary tasks.

Conclusions: None of the 3 methods of presenting DRT stimuli showed a consistent advantage in sensitivity in differentiating multiple levels of cognitive load if all response times, hit rates, and secondary task performance are considered. If only response time is considered, the visual presentation of the DRT stimulus used in this study showed some advantages. In interpreting these data, it should be noted that the methods of DRT stimulus presentation varied somewhat from the currently proposed draft ISO standard and it is possible that the relative salience level of the visual DRT stimulus influenced the findings. It is further suggested that more than 2 levels of difficulty of the n-back task should be considered for further investigation of the relative sensitivity of different DRT stimuli modalities. Parameters that indicate change in cognitive load (response time, hit rate, task performance) should be analyzed together in assessing the overall impact on the driver and not individually, in order to obtain a fuller insight of the assessed cognitive load.