Relationship between PM10 and PM2.5 levels in high-traffic area determined using path analysis and linear regression

The objective of this study was to determine the relationship between PM_(10) and PM_(2.5) levels as related to meteorological conditions and traffic flow using both a linear regression analysis and a path analysis. The Particulate matter(PM) samples were collected from Sukhumvit road, Bangkok, Thailand, at both open(104 samples) and covered(92 samples)areas along the road. Fifteen percent of all samples were separated before the statistical models were run and used for model validation. The results from the path analysis were more elaborate than those from the linear regression, thus indicating that meteorological conditions had a direct effect on the particulate levels and that the effects of traffic flow were more variable in open areas. The model also indicated that meteorological conditions had an indirect effect and that traffic flow had a direct effect on particulate levels in covered areas. The model validation results indicated that for open areas, the R~2 values were not very different between the path analysis and the linear regression model, but that the path analysis was more accurate than the linear regression model at very low PM concentrations. At high PM concentrations, the path analysis model also had a better fit than did the linear regression, so the predictions from the path analysis model were more accurate than those from the linear regression.     

以长春为例研究环境空气中TSP、PM_(10)和PM_(2.5)的相关性

选取长春市解放大路与人民大街的交叉口为研究地点,分别进行TSP、PM10和PM2.5的采样和分析.然后利用相关系敷法和t检验对测定结果进行相关性分析,得到备元素的含量在三种污染物中的相关系敖:在TSP与PM10中为0.9349;在PM2.5与PM10中为0.8797;在TSP与PM2.5中为0.7824.得到各元素含量在三种污染物中的T检验统计值,在TSP与PM10中为0.90103;在PM2.5与PM10中为0.04745;在TSP与PM2.5中为0.047986.从分析结果可以看出,各元素含量在TSP与PM10中的相关性最好,在PM2.5与PM10中次之,研究结果为相关环境管理提供科学依据.     

青岛市区春夏季大气能见度与颗粒物的关系

利用青岛市灰霾综合观测站2012年3月2日-2012年6月7日期间的监测数据,分析了青岛市区大气能见度与不同粒径颗粒物质量浓度的日变化特征,比较了各级别大气能见度下不同粒径颗粒物质量浓度及所占比例的相关性,研究了相对湿度对大气能见度和颗粒物质量浓度相关性的影响.结果表明,监测时段大气能见度与颗粒物质量浓度呈现较好的负相关,每天大气能见度最低值出现在早晨07:00--09:00;剔除相对湿度高于90％的前提下,PM2.5是影响大气能见度的主要因子,随着其在PM1o中所占比例上升,大气能见度级别不断下降,相关系数为-0.84;不同相对湿度区间下,PM2.5对大气能见度的影响最明显,其中,相对湿度为60％ ～ 70％,大气能见度与颗粒物质量浓度之间的相关性最好.     

北京市MODIS气溶胶光学厚度与PM_(10)质量浓度的相关性分析

利用北京地区2012年1—12月NASA MODIS气溶胶光学厚度(AOD)和通过空气污染指数(API)转换得到的PM10质量浓度进行了相关性分析.结果发现,二者的直接相关程度较低,在引入季节变化的气溶胶标高且考虑了气溶胶的垂直分布后,进行标高订正,二者的相关系数有所提高;在考虑了湿度影响因子后,进行湿度订正,二者的相关系数显著提高;引入平均风速、平均气温和平均气压等气象因素,进行多元回归分析,相关系数进一步提高.证实了卫星遥感气溶胶光学厚度在经过垂直和湿度订正并考虑气象因素的情况下,可以作为监测北京地区颗粒物污染物地面分布的一个有效手段.     

东营春季PM10中有机碳和元素碳的污染特征及来源

2010年4月采集了东营市大气PM10样品,测定了PM10的浓度,并采用IMPROVE-TOR方法准确测量了样品中的8个碳组分.结果表明,采样期间,东营市大气PM10的平均浓度为(147.02±56.22) μg/m3;PM10中有机碳(0C)、元素碳(EC)浓度平均值分别为11.82、3.68 μg/m 3;PM10中OC和EC显著相关,表明OC、EC的来源相同;所有采样点PM10中OC/EC均大于2.15,表明存在二次有机碳(SOC)的贡献;PM10中SOC平均质量浓度是3.91 μg/m3,占OC质量浓度的33.08％;通过计算PM10中8个碳组分丰度,初步判断东营市颗粒物中碳的主要来源是汽车尾气、道路扬尘和燃煤.     

2002—2012年京津唐PM10变化规律及差异

对2002年6月—2012年5月京津唐城市群大气可吸入颗粒物(PM10)质量浓度的长期监测数据进行分析,结合3市的地理、气候气象条件,分析了京津唐城市群大气颗粒物质量浓度的变化特征;根据3市PM10相互之间的发散系数,定量分析了3市PM10变化的差异。结果表明,2002—2012年北京市的PM10质量浓度变化范围为0.012~0.600 mg/m3,天津、唐山2市的PM10质量浓度变化范围分别为0.014~0.600、0.019~0.452 mg/m3。2008、2011年天津市PM10质量浓度年平均值达到二级标准,唐山市从2008年后PM10质量浓度年平均值达到二级标准;北京市PM10质量浓度总体变化趋势为春季秋季冬季夏季,天津、唐山市均为冬季春季秋季夏季,但不同年份的变化趋势略不同;北京-唐山、北京-天津、天津-唐山之间PM10的月度发散系数范围分别为0.402 7~0.159 2、0.406 8~0.142 9、0.323 1~0.107 8,说明空间距离最近的天津-唐山之间大气污染的相互影响较北京-天津、北京-唐山之间大。     

群体感应淬灭菌的分离及其膜污染控制性能

通过淬灭细菌的群体感应系统来抑制生物膜形成、防止膜生物污染的方法近年来受到广泛关注.本实验从实际运行污水处理厂活性污泥中分离出5株具有群体感应淬灭功能的菌株,其中菌株HG10对信号分子N-乙酰高丝氨酸环内酯(C6-HSL)分解能力最强.经16S rRNA基因序列比对,初步鉴定为蜡样芽孢杆菌(Bacillus cereus).用海藻酸钠将菌株HG10进行包埋固定,以探究其在膜过滤系统中对膜污染防治的效果.结果表明,经过8 d培养,添加细菌包埋珠(SA-HG10)的实验组B中膜通量为181.29 L·(m~2·h)~(-1),未投加包埋珠的对照组A膜通量为110.64 L·(m~2·h)~(-1),B组膜通量比A组高出63.86%;对微滤膜片上生物膜中EPS含量测定表明,实验组B中EPS多糖和蛋白质含量较对照组A分别减少了29%和48%,疏水性蛋白质含量的大量减少是造成膜污染减弱的主要原因;膜表面胞外聚合物(EPS)总含量减少了43%,表明投放SA-HG10细菌包埋珠对过滤膜片上生物膜形成具有明显抑制作用,改善了膜过滤性能.     

苯酚对两种微囊藻生长的作用效应

用不同浓度的苯酚处理无毒铜绿微囊藻和有毒铜绿微囊藻。结果显示不加苯酚处理时，有毒藻生长量明显高于无毒藻；100μg／mL的苯酚促进无毒藻生长而抑制有毒藻的生长；苯酚浓度增至200μg／mL，无毒藻的生长才受到抑制。高浓度苯酚胁迫下的藻细胞：光合速率大幅度降低；可溶性蛋白含量减少；细胞膜透性增大；超氧阴离子(O2^-)产生速率和丙二醛(MDA)相对含量升高；超氧化物歧化酶(SOD)活性降低。这些变化有毒藻较无毒藻更显著。表明：有毒微囊藻是水华中的优势种群；两种藻中有毒藻对苯酚的敏感性更大。     

Particle emissions of a railway line determined by detailed single particle analysis

The goal of this study was to identify and quantify particles emitted from railway traffic. For that purpose PM10 samples were collected near a busy railway line using a wind direction and speed controlled sampling equipment consisting of five devices. Measurements taken perpendicular to the railway lines at 10, 36 and 120 m distance enable an identification and separation of particles caused by the railway traffic from background particles. Morphology and chemistry of more than 11,000 particles were analysed by computer controlled scanning electron microscopy (CCSEM). Based on chemical composition five particle classes are defined and assigned to their sources. The mass of the individual particles is determined by multiplying their volumes, calculated based on their morphology with a density assigned specifically to each particle class. The density of the particle classes is derived from their chemical composition. To estimate the PM10 contributions of the railway lines, the mass of PM10 at 120 m (background, not influenced by the railway lines) is subtracted from the mass of PM10 at 10 m. The emissions of the railway lines are dominated by ‘iron’ particles, which contribute 2.9 μg m⁻³ or 67% to the railway related PM10. In addition, ‘aluminium’ and ‘calcium’ particles contribute also to the railway related PM10 (1.0 μg m⁻³ or 23% for the ‘aluminium’ and 0.4 μg m⁻³ or 10% for the ‘calcium’ particles). These particles are assigned to abrasion of the gravel bed and re-suspension of mineral dust.Long-term gravimetric results of the contribution of iron to the mass of railway related PM10 from a study performed earlier at the same site are in good agreement with the data presented in this study.     

(M)VOC and composting facilities. Part 2: (M)VOC dispersal in the environment

BACKGROUND, AIMS AND SCOPE: Composting facilities are known to release odorous volatiles due to biodegradation of municipal waste and plant residues. Although odour perception and its grading is influenced by experience, attitude and adaptation, these emissions have created a lack of acceptance for residents in the vicinity of composting facilities. Enclosure of compost pile halls, ventilation systems and biofilters are often insufficient to minimise the burden of compost-derived compounds in the air. Moreover, economic considerations forced smaller communities to establish less sophisticated facilities with open storage areas and other relevant sources for wind-borne dispersal of bioaerosols. Aim of the present study was to characterise the immission and dispersal of microbial volatiles (MVOC) and, besides, to find coincidences between MVOC and compost odour. METHODS: In the course of this study, the surroundings of two composting facilities, differing in their type of process engineering, were investigated for emission of volatiles in the environment. Both microbially and plant-derived substances were assessed, several of which have low odour thresholds. Air samples were taken in distances ranging from 50 to 800 m in a downwind direction from each facility. RESULTS AND DISCUSSION: Compost-derived and microbial volatile organic compounds (MVOC) were found at distances of up to 800 m from the composting facilities. Terpenes like alpha-pinene, camphene and camphor were the dominant compounds and coincided with typical compost odour, whereas several typical MVOC were not found at greater distances. The terpenes in combination with certain MVOC may play an important role in the perception of compost odour. Exposure concentrations were not of toxicological relevance, but sensory irritation and psychohygienic effects due to an annoyance potential of such compounds should not be dismissed. RECOMMENDATIONS AND OUTLOOK: Although terpenes are generally associated with pleasant odour characteristics, they seemed to contribute to malodours in a mixture with other VOC, in this context of volatile waste from compost facilities. Malodorous emissions from biowaste have to be considered as sources of health complaints and the investigation of mixtures of compost-derived volatiles is still inevitable. Exposure levels have to be discussed taking VOC mixtures into account. Within composting facilities, technical devices have to be improved to minimise dispersal of volatiles to prevent residents from immissions eventually causing health complaints.