区域大气环境中PM2．5／PM10空间分布研究

提出了一种利用移动监测技术研究区域大气环境中PM2.5／PM10空间分布的方法,并在2004年12月进行了宁波市全市域PM2.5／PM10空间分布的研究。数据显示：相同路径所代表的地区PM2.5和PM10具有很好的相关性,多数路径上PM2.5与PM10数据的相关系数平方在0．95以上,而不同路径上PM2.5与PM10的比值不同。文中给出了宁波市PM2.5／PM10污染的空间分布图,直观地显示出PM2.5／PM10污染的空间分布情况,突出了污染的重点点位和地区。     

Spatio-temporal characteristics of PM10 concentration across Malaysia

The recurrence of forest fires in Southeast Asia and associated biomass burning, has contributed markedly to the problem of trans-boundary haze and the long-range movement of pollutants in the region. Air pollutants, specifically particulate matter in the atmosphere, have received extensive attention, mainly because of their adverse effect on people's health. In this study, the spatial and temporal variability of the PM10 concentration across Malaysia was analyzed by means of the rotated principal component analysis. The results suggest that the variability of the PM10 concentration can be decomposed into four dominant modes, each characterizing different spatial and temporal variations. The first mode characterizes the southwest coastal region of the Malaysian Peninsular with the PM10 showing a peak concentration during the summer monsoon i.e. when the winds are predominantly southerlies or southwesterlies, and a minimal concentration during the winter monsoon. The second mode features the region of western Borneo with the PM10 exhibiting a concentration surge in August–September, which is likely to be the result of the northward shift of the Inter Tropical Convergence Zone (ITCZ) and the subsequent rapid arrival of the rainy season. The third mode delineates the northern region of the Malaysian Peninsular with strong bimodality in the PM10 concentration. Seasonally, this component exhibits two concentration maxima during the late winter and summer monsoons, as well as two minima during the inter-monsoon periods. The fourth dominant mode characterizes the northern Borneo region which exhibits weaker seasonality of the PM10 concentration. Generally, the seasonal fluctuation of the PM10 concentration is largely associated with the seasonal variation of rainfall in the country. However, in addition to this, the PM10 concentration also fluctuates markedly in two timescale bands i.e. 10–20 days quasi-biweekly (QBW) and 30–60 days lower frequency (LF) band of the intra-seasonal timescales. These intra-seasonal fluctuations show strong seasonality with the largest fraction of variance occurring during the boreal summer and the weakest variance during the winter. Generally, the LF intra-seasonal oscillation is stronger compared to the QBW intra-seasonal band.     

A new direct thermal desorption-GC/MS method: Organic speciation of ambient particulate matter collected in Golden, BC

Particulate matter having an aerodynamic diameter less than 2.5 μm (PM2.5) is thought to be implicated in a number of medical conditions, including cancer, rheumatoid arthritis, heart attack, and aging. However, very little chemical speciation data is available for the organic fraction of ambient aerosols. A new direct thermal desorption-gas chromatography/mass spectrometry (TD-GC/MS) method was developed for the analysis of the organic fraction of PM2.5. Samples were collected in Golden, British Columbia, over a 15-month period. n-Alkanes constituted 33–98% by mass of the organic compounds identified. PAHs accounted for 1–65% and biomarkers (hopanes and steranes) 1–8% of the organic mass. Annual mean concentrations were: n-alkanes (0.07–1.55 ng m⁻³), 16 PAHs (0.02–1.83 ng m⁻³), and biomarkers (0.02–0.18 ng m⁻³). Daily levels of these organics were 4.89–74.38 ng m⁻³, 0.27–100.24 ng m⁻³, 0.14–4.39 ng m⁻³, respectively. Ratios of organic carbon to elemental carbon (OC/EC) and trends over time were similar to those observed for PM2.5. There was no clear seasonal variation in the distribution of petroleum biomarkers, but elevated levels of other organic species were observed during the winter. Strong correlations between PAHs and EC, and between petroleum biomarkers and EC, suggest a common emission source – most likely motor vehicles and space heating.     

Indoor and outdoor PM mass and number concentrations at schools in the Athens area

Simultaneous indoor and outdoor PM₁₀ and PM_2.5 concentration measurements were conducted in seven primary schools in the Athens area. Both gravimetric samplers and continuous monitors were used. Filters were subsequently analyzed for anion species. Moreover ultrafine particles number concentration was monitored continuously indoors and outdoors. Mean 8-hr PM₁₀ concentration was measured equal to 229 ± 182 μg/m³ indoors and 166 ± 133 μg/m³ outdoors. The respective PM_2.5 concentrations were 82 ± 56 μg/m³ indoors and 56 ± 26 μg/m³ outdoors. Ultrafine particles 8-h mean number concentration was measured equal to 24,000 ± 17,900 particles/cm³ indoors and 32,000 ± 14,200 particles/cm³ outdoors. PM₁₀ outdoor concentrations exhibited a greater spatial variability than the corresponding PM_2.5 ones. I/O ratios were close or above 1.00 for PM₁₀ and PM_2.5 and smaller than 1.00 for ultrafine particles. Very high I/O ratios were observed when intense activities took place. The initial results of the chemical analysis showed that accounts for the 6.6 ± 3.5% of the PM₁₀ and for the 3.1 ± 1.4%.The corresponding results for PM_2.5 are 12.0 ± 7.7% for and 3.1 ± 1.9% for . PM_2.5 indoor concentrations were highly correlated with outdoor ones and the regression line had the largest slope and a very low intercept, indicative of no indoor sources of fine particulate . The results of the statistical analysis of indoor and outdoor concentration data support the use of as a proper surrogate for indoor PM of outdoor origin.     

空间分辨率与精度协同改进的卫星AOD产品降尺度模型

针对现有卫星气溶胶光学厚度(AOD)产品空间分辨率和精度往往难以满足大气污染精细治理实际需求,提出了一种耦合偏差校正的统计降尺度改进模型(SDBC).该模型基于“空间尺度不变性假设”引入相关驱动因子的额外空间信息实现AOD降尺度,并在此基础上通过偏差校正进一步提升降尺度产品的精度.以1km分辨率MAIAC AOD产品为例,在北京、大湾区、台湾岛3个典型地区开展模型验证.结果表明:(1)DEM、NDVI、人口数量和土地覆盖是影响AOD变化的细节因子,在SDBC空间降尺度过程中引入可将AOD产品的空间分辨率有效提升至500m,且降尺度产品验证R2最高可达0.88;(2)顾及卫星观测几何、质量标识、大气水蒸气柱、气溶胶模式等因子的偏差校正则可进一步提升降尺度AOD产品的精度,3个地区的验证R2均在0.85以上,最高可达0.93;(3)信息熵评估结果显示SDBC模型生成的500m AOD产品提高了原始MAIAC AOD产品的空间信息量.在保留了公里级产品AOD的空间分布格局的基础上,SDBC产品也增强了细节和纹理特征、改善了边界现象和马赛克效应.研究结果证实SDBC模型能有效协同改进现有卫星A...     

郑州市 PM2．5和 PM10质量浓度变化特征分析

根据郑州市2013年PM2．5和PM10颗粒物连续自动监测数据,对郑州市各国控站点的PM2．5和PM10的达标情况、变化趋势等进行探讨分析。结果表明：2013年郑州市PM10和PM2．5的年均质量浓度均超过了新标准规定的年均值二级标准限值。 PM10和PM2．5月均值峰值出现在1月和10月,谷值出现在8月,各月PM2．5的超标天数都大于PM10。PM10和PM2．5冬季的日均值浓度明显高于其他季节,呈双峰型,夜晚浓度整体高于白天;PM2．5春、夏、秋三季日变化呈单峰型,PM10夏季和秋季呈单峰型,春季呈双峰型。 PM2．5和PM10日均值有着非常显著的线性相关关系,PM2．5和PM10浓度的比值（p）10月最高。     

机动车排放颗粒物成分谱对比研究

对深圳、无锡、济南和美国EPA建立的机动车排放颗粒物成分谱进行对比研究,建立的成分谱中各组分含量存在较大差别原因为使用了不同的采样方法。     

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.     

南京市冬季大气颗粒态汞的分布特征

采集了南京市2012年冬季4个功能区的PM2．5、PM10、TSP样品,对不同粒径大气颗粒物中的颗粒态汞测试。结果表明,南京冬季大气颗粒物TSP中汞的质量浓度为49．26 pg/m3～257．14 pg/m3,平均质量浓度为161．27 pg/m3;PM10中汞的质量浓度为44．82 pg/m3～228．29 pg/m3,平均质量浓度为147．38 pg/m3;PM2．5中汞的质量浓度为35．98 pg/m3～178．58 pg/m3,平均质量浓度为104．10 pg/m3。不同功能区大气颗粒态汞质量浓度的分布趋势为：交通综合区＞旅游区＞住宿综合区＞商业区。大气颗粒态汞60％以上存在于可吸入肺的PM2．5中,细颗粒物富集汞的能力比粗颗粒物强。     

我国居住建筑室内PM_(2.5)研究现状及进展

分析了我国居住建筑室内PM_(2.5)污染水平,总结了现阶段PM_(2.5)的研究方法,主要包括理论分析法、数值模拟法和实验测试法。指出室外源是室内PM_(2.5)的主要污染来源,而室内烟草烟雾、烹饪及人员活动也会严重影响室内PM_(2.5)浓度。针对目前研究中存在的问题,提出了标定典型建筑在不同影响因素下的I/O比范围、研究家具和家电的颗粒物释放状况、加强农村室内外空气颗粒物污染调查等建议。