区域PM2.5污染特征及影响因素研究

通过对区域环境空气中PM2.5的采样监测,分析了区域PM2.5的时间变化特征及温度、湿度、风速对其质量浓度产生的影响,并对PM2.5与PM10污染水平及关系进行了研究,得出了一些有意义的结论。     

杭州沿河住宅小区冬季室外PM2.5实测与分析

杭州市气象台天气统计数据显示,杭州市雾霾天气季节性特征明显,在冬半年出现雾霾天气的频率越来越高,恶劣的空气环境影响着城市居民的健康和生活.PM2.5浓度的升高则是形成雾霾天的直接原因.文章选取杭州主城区运河段一个典型沿河住宅小区,通过实测住宅小区居住环境中PM2.5浓度及室外气象参数(如空气温度、相对湿度、风速),探索PM2.5浓度与室外气象参数变化之间的关系,为后续模拟研究掌握沿河住宅小区PM2.5浓度分布及变化规律提供依据,为改善沿河住宅小区空气环境质量提供参考.     

不同建筑环境空气中颗粒物PM1.0、PM2.5和PM10的污染水平及对比研究

为了解人们常停留的建筑室内空气中不同粒径段颗粒物的污染水平,本文对写字楼、地铁站台、餐饮环境、大学教室和宿舍等不同类型建筑室内和室外空气中的颗粒物PM10、PM2.5和PM10的质量浓度水平进行了测试、统计分析和对比研究,同时对不同建筑环境内不同粒径段颗粒物的浓度大小、占比情况和主要来源进行了分析探讨.结果 表明:1)对PM10,不同建筑环境空气中PM10平均质量浓度均未超过标准限值0.150 mg/m3;对PM2.5,写字楼A中70％的房间PM2.5质量浓度超出标准限值(0.075 mg/m3)7.69％～ 18.53％,餐饮环境PM2.5平均质量浓度(0.130 mg/m3)超出标准限值73.33％;2)除地铁站台稍有差异,测试的建筑环境中PM10/PM2.5浓度比值均在90％以上.对不同粒径段颗粒物PM1.0、PM1.0-2.5和PM2.5.10,餐饮、写字楼和大学宿舍内PM10在PM10中占比最大,分别为90.97％、65.28％和63.73％.大学教室和地铁站台环境内PM2.5-10在PM10中占比最大,分别为50.98％和44.16％;3)写字楼内的吸烟、打印机和电脑等办公设备主要产生细微颗粒物PM1.0和细颗粒物PM2.5;大学教室内人员活动、地铁站台人员流动以及列车进出站主要产生PM2.5-10;餐饮环境中不同燃烧源、烹饪过程主要产生细微颗粒物PM1.0;4)根据研究结果,对不同类型建筑,针对细微颗粒物PM1.0占比较大、对人体健康影响更大、更易携带细菌和病毒的特点,迫切需要在今后加强不同类型建筑环境PM1.0浓度水平限值的研究,并制定相关标准规范,且针对不同类型建筑应采取不同通风净化措施来保证PM10满足人体健康需求.     

公园绿地不同景观空间PM2.5分布特征及其影响因素研究

研究选取城市公园中6个由不同景观要素构成的空间,通过监测不同空间内PM2.5浓度、空气温度、相对湿度及风速风向,分析不同空间景观要素组成与PM2.5浓度之间的关系,探讨不同空间气象因子变化与PM2.5浓度的相关性。研究结论如下,1）不同景观要素构成的空间中PM2.5浓度存在显著差异（P< 0.05）。2）PM2.5浓度与绿量（D）呈显著负相关（R=－0.966）, 当113.57 m2相似文献   

某宿舍开关窗条件下室内外PM2.5浓度变化分析

由于雾霾的影响,PM2.5受到越来越多的关注。文章介绍了在不同天气以及开关窗条件下测试室内外PM2.5浓度随时间变化的情况。室外的PM2.5浓度受天气影响较大。雾霾天气情况下的PM2.5浓度明显高于下雨和晴朗天气下的PM2.5浓度。同时,在开窗和关窗条件下,室内外的PM2.5浓度随时间的变化具有较强的跟随性。室内外的PM2.5浓度最大值常出现在8:00~10:00时间段左右。为研究室内外PM2.5浓度提供一定参考。     

北京市某办公建筑夏冬季室内外PM_(2.5)浓度变化特征

为了把握雾霾天气大气环境细颗粒物PM2.5浓度变化对室内环境的影响规律,项目组先后于2013年6月~8月(夏季)和2013年12月~2014年2月(冬季)对北京地区一办公建筑室内外细颗粒物(PM2.5)质量浓度及I/O比值变化规律进行了实时监测。实测结果表明:1)在建筑外窗关闭、室内无其他污染源且机械通风系统关闭条件下,夏、冬季室内外PM2.5质量浓度的日变化规律均为夜间高白天低,周变化规律为周一~周五呈逐渐上升趋势;2)冬季各月的室内外PM2.5质量浓度水平均高于夏季各月的,对应的室内外PM2.5质量浓度I/O比值也是冬季高于夏季;3)室外风速和空气相对湿度与室内外PM2.5质量浓度存在明显的负相关,而室外空气温度与室内外PM2.5质量浓度水平的变化相关性不明显。     

天气因数对PM2.5浓度的影响

PM2.5浓度是衡量环境质量的一项重要指标,随着人们环保意识的进一步增强越来越被社会各界所重视。PM2.5浓度很容易受外界因素影响而发生变化,本文着重研究了天气因素对它的影响,先后分析了温度,风力大小,天气情况对PM2.5浓度的影响。根据特定的数据对象,讨论了杭州地区PM2.5浓度变化的情况。     

南京某幼儿园室内外细颗粒物(PM2.5)质量浓度调查及影响因素分析

于2015年4—12月(除7,8月外,每月一周)实测了该幼儿园室内外PM2.5浓度,结果显示:室外PM2.5质量浓度中位值为60.6μg/m~3,室内PM2.5质量浓度中位值为32.5μg/m~3;室内外PM2.5浓度相关系数达0.74,检测期间平均约有52%的室外PM2.5通过建筑围护结构进入室内,室内55%的PM2.5变化由室外颗粒物源导致;实测期间,时均I/O值为0.69,变化范围为0.1~5.46;I/O值受室外PM2.5质量浓度的影响,随室外PM2.5质量浓度升高呈下降趋势,室外PM2.5浓度较高时,I/O值随换气次数减小而减小,室外PM2.5浓度较低时,I/O值随换气次数减小而增大;室外空气湿度与室内外PM2.5浓度正相关,室外风速与室内外PM2.5浓度负相关,而室外温度对室内外PM2.5浓度影响有限,但与I/O值正相关。     

地铁车站PM2.5和PM10颗粒物浓度实测及分析

为了进一步了解地铁车站内环境中的颗粒物浓度分布情况,在2015年11月对上海市A、B两个地铁车站进行了实地监测,分析了PM2.5和PM10颗粒物浓度在一天中的变化规律及其影响因素.测试结果显示站厅公共区,站台公共区与轨行区的PM2.5浓度在监测时段内逐时变化规律相似.站厅公共区,站台公共区PM10与PM2.5在监测时段内逐时变化规律相似.地铁车站站台内PM2.5/PM10质量浓度比值平均值为0.65～0.93,颗粒物污染主要为细颗粒物.     

冬季雾霾期间中学教室室内污染物测量与分析

北方地区中小学教室冬季多采用集中供暖或分体空调,教室长时间密闭,室内空气质量对学生学习效率影响较大。本文以济南某中学教室为例,通过对教室和室外大气中二氧化碳浓度、PM2.5浓度、温度以及相对湿度等连续一周的测试,给出了室内外二氧化碳浓度、PM2.5浓度、温度以及相对湿度等参数的相关性变化规律,为雾霾条件下教室内新风量的确定提供了基础数据。     

The PM2.5 and PM10 particles in urban areas of Taiwan

This study conducted an atmospheric aerosol sampling to measure the PM10 (particles < 10 microns in aerodynamic diameter) and PM2.5 (particles < 2.5 microns in aerodynamic diameter) mass concentrations from October 1996 to June 1997 in northern (Taipei), central (Taichung) and southern (Kaohsiung), the three largest cities of Taiwan. Seventy-eight samples were obtained to measure the mass concentrations of PM10 and PM2.5 from nine sampling sites. According to those results, the PM10 mass concentrations in Taipei, Taichung and Kaohsiung were 42.19, 60.99 and 77.10 micrograms/m3, respectively. The corresponding PM2.5 mass concentrations were 23.09, 39.97 and 48.47 micrograms/m3, respectively. The PM2.5 fraction accounted for 61-67% of the PM10 mass in central and southern Taiwan, but was lower (54-59%) in northern Taiwan. Some samples in which the PM2.5 fraction was overwhelmingly dominant could reach as high as 80-95% of the PM10 mass. In addition, the PM2.5, PM10 levels and PM2.5/PM10-2.5 (particles with aerodynamic diameters ranging from 2.5 to 10 microns) ratios in metropolitan Taiwan significantly fluctuated from site-to-site and over time. Moreover, ambient daily PM2.5 and PM10-2.5 mass concentrations did not correlate well with each other at most of the sampling sites, indicated that they originated from different kinds of sources and emitted variedly over time.     

Chemical composition of PM2.5 and PM10 in Mexico City during winter 1997

PM2.5 and PM10 were measured over 24-h intervals at six core sites and at 25 satellite sites in and around Mexico City from 23 February to 22 March 1997. In addition, four 6-h samples were taken each day at three of the core sites. Sampling locations were selected to represent regional, central city, commercial, residential, and industrial portions of the city. Mass and light transmission concentrations were determined on all of the samples, while elements, ions and carbon were measured on approximately two-thirds of the samples. PM10 concentrations were highly variable, with almost three-fold differences between the highest and lowest concentrations. Fugitive dust was the major cause of PM10 differences, although carbon concentrations were also highly variable among the sampling sites. Approximately 50% of PM10 was in the PM2.5 fraction. The majority of PM mass was comprised of carbon, sulfate, nitrate, ammonium and crustal components, but in different proportions on different days and at different sites. The largest fine-particle components were carbonaceous aerosols, constituting approximately 50% of PM2.5 mass, followed by approximately 30% secondary inorganic aerosols and approximately 15% geological material. Geological material is the largest component of PM10, constituting approximately 50% of PM10 mass, followed by approximately 32% carbonaceous aerosols and approximately 17% secondary inorganic aerosols. Sulfate concentrations were twice as high as nitrate concentrations. Sulfate and nitrate were present as ammonium sulfate and ammonium nitrate. Approximately two-thirds of the ammonium sulfate measured in urban areas appears to have been transported from regions outside of the study domain, rather than formed from emissions in the urban area. Diurnal variations are apparent, with two-fold increases in concentration from night-time to daytime. Morning samples had the highest PM2.5 and PM10 mass, secondary inorganic aerosols and carbon concentrations, probably due to a shallow surface inversion and rush-hour traffic.     

Hospital indoor PM10/PM2.5 and associated trace elements in Guangzhou, China

PM10 and PM2.5 samples were collected in the indoor environments of four hospitals and their adjacent outdoor environments in Guangzhou, China during the summertime. The concentrations of 18 target elements in particles were also quantified. The results showed that indoor PM2.5 levels with an average of 99 microg m(-3) were significantly higher than outdoor PM2.5 standard of 65 microg m(-3) recommended by USEPA [United States Environmental Protection Agency. Office of Air and Radiation, Office of Air Quality Planning and Standards, Fact Sheet. EPA's Revised Particulate Matter Standards, 17, July 1997] and PM2.5 constituted a large fraction of indoor respirable particles (PM10) by an average of 78% in four hospitals. High correlation between PM2.5 and PM10 (R(2) of 0.87 for indoors and 0.90 for outdoors) suggested that PM2.5 and PM10 came from similar particulate emission sources. The indoor particulate levels were correlated with the corresponding outdoors (R(2) of 0.78 for PM2.5 and 0.67 for PM10), demonstrating that outdoor infiltration could lead to direct transportation into indoors. In addition to outdoor infiltration, human activities and ventilation types could also influence indoor particulate levels in four hospitals. Total target elements accounted for 3.18-5.56% of PM2.5 and 4.38-9.20% of PM10 by mass, respectively. Na, Al, Ca, Fe, Mg, Mn and Ti were found in the coarse particles, while K, V, Cr, Ni, Cu, Zn, Cd, Sn, Pb, As and Se existed more in the fine particles. The average indoor concentrations of total elements were lower than those measured outdoors, suggesting that indoor elements originated mainly from outdoor emission sources. Enrichment factors (EF) for trace element were calculated to show that elements of anthropogenic origins (Zn, Pb, As, Se, V, Ni, Cu and Cd) were highly enriched with respect to crustal composition (Al, Fe, Ca, Ti and Mn). Factor analysis was used to identify possible pollution source-types, namely street dust, road traffic and combustion processes.     

Temporal variations and spatial distribution of ambient PM2.2 and PM10 concentrations in Dhaka, Bangladesh

Concentrations and characteristics of airborne particulate matter (PM(10), PM(2.2) and BC) on air quality have been studied at two air quality-monitoring stations in Dhaka, the capital of Bangladesh. One site is at the Farm Gate area, a hot spot with very high pollutant concentrations because of its proximity to major roadways. The other site is at a semi-residential area located at the Atomic Energy Centre, Dhaka Campus, (AECD) with relatively less traffic. The samples were collected using a 'Gent' stacked filter unit in two fractions of 0-2.2 mum and 2.2-10 mum sizes. Samples of fine (PM(2.2)) and coarse (PM(2.2-10)) airborne particulate matter fractions collected from 2000 to 2003 were studied. It has been observed that fine particulate matter has a decreasing trend, from prior year measurements, because of Government policy interventions like phase-wise plans to take two-stroke three-wheelers off the roads in Dhaka and finally banned from January 1, 2003. Other policy interventions were banning of old buses and trucks to ply on Dhaka city promotion of the using compressed natural gas (CNG), introducing air pollution control devices in vehicles, etc. It was found that both local (mostly from vehicular emissions) and possibly some regional emission sources are responsible for high PM(2.2) and BC concentrations in Dhaka. PM(2.2), PM(2.2-10) and black carbon concentration levels depend on the season, wind direction and wind speed. Transport related emissions are the major source of BC and long-range transportation from fossil fuel related sources and biomass burning could be another substantial source of BC.     

Source apportionment of PM10 and PM2.5 in Milan (Italy) using receptor modelling

In this paper a source apportionment of particulate matter pollution in the urban area of Milan (Italy) is given. Results of PM10 and PM2.5 mass and elemental concentrations from a 1-year monitoring campaign are presented. Mean annual and daily PM10 levels are compared with the limits of the EU Air Quality Directive EC/30/1999 and the results show that the limit values established would not be met in the urban area of Milan or the large surrounding area. Moreover, high levels of PM2.5 are registered and this fraction constitutes a high portion of the PM10 mass. In Milan the winter period is characterised by a high degree of air pollution due to a greater contribution of emissions and to adverse meteorological and thermodynamic conditions of the atmosphere. The application of multivariate techniques and receptor modelling (PCFA, APCFA) to the whole data-set led to the identification of the main emitting sources and to the source apportionment of PM10 and PM2.5 in Milan. The most important sources were identified as 'soil dust', 'traffic', 'industry' and 'secondary compounds' for PM10 and as 'soil dust', 'anthropogenic' and 'secondary compounds' for PM2.5, explaining the greatest part of the total variance (91% and 75%, respectively).     

Characterization of chemical species in PM2.5 and PM10 aerosols in suburban and rural sites of central Taiwan.

Aerosol samples for PM2.5 (particulate matter with aerodynamic diameters less than 2.5 microns), PM2.5-10 (particulate matter with aerodynamic diameters between 2.5 and 10 microns) and TSP were collected from June to September 1998 at THU (suburban) and HKIT (rural) sites in central Taiwan. The ratios of PM2.5/PM10 averaged 0.70 for the daytime and 0.63 for the nighttime at THU, respectively. At HKIT, the PM2.5/PM10 ratios averaged 0.56 for the daytime and 0.72 in the nighttime, respectively. These results indicated that the PM2.5 concentrations contribute the majority of the PM10 concentration and PM10 concentrations contribute the majority of the TSP at both sites. The averaged PM2.5 concentrations at THU are higher than those measured at HKIT during the daytime period. However, the average PM2.5-10 concentrations in THU are lower than those measured at HKIT during nighttime. The samples collected were also analyzed by atomic absorption spectrophotometry for the elemental analysis of Ca, Fe, Pb, Zn, Cu, Mn and Cr. Meanwhile ion chromatography was used to analyze for the water-soluble ions: sulphate, nitrate and chloride in the Universal samples. The concentrations of heavy metals in PM10 during daytime were all higher than nighttime at THU. However, the averaged concentrations of metal elements in PM10 during day and night period were distributed irregularly at HKIT. The results indicated that for metal elements collected at HKIT have different emission sources. The concentrations of metal elements during daytime in PM10 at THU were generally higher than HKIT. The phenomena owing to the averaged PM2.5 particle concentrations at THU (suburban) were higher than those measured at HKIT (rural) and PM2.5 occupied the major portions of PM10 for both sites during the day period. For anion species, there are no significant differences between day and night period in PM10 concentrations at both suburban and rural sites.     

浅谈PM2.5

通过对能见度和PM2.5的有关介绍,指出PM2.5给人们健康带来的危害以及对环境造成的污染,并提出了PM2.5的检测技术和预防方法。     

居住区室外开敞空间PM2.5、PM10时空 分布特征及居民暴露风险评估

研究利用Reynolds Averaged Navier-Stokes Model与Revised Drift Flux Model模拟分析了居住区室外开敞空间中PM_(2.5)、PM_(10)浓度的时空分布,利用行为制图建立场地中居民活动与PM2.5、PM_(10)浓度分布的时空映射,并依据世界卫生组织的空气质量标准(IT-1)评估了典型场地中居民活动的暴露风险。结果表明:1)居住区室外开敞空间居民访问的主要时段是10:30—12:30及15:00—18:00,其活动范围集中在基础设施附近的热点区域;2)倾斜风向下,4个典型活动场地的PM_(2.5)、PM_(10)浓度更高,位于居住区边缘的场地更容易暴露于较高的浓度中。由植物围合的铺装场地容易富集颗粒物,提升了场地内的PM_(2.5)、PM_(10)浓度;3)场地热点平均浓度指标可用于准确评估居民室外开敞空间暴露的风险(R~20.99)。研究结果为公共健康视角下居住区室外开敞空间景观设计提供了理论依据与设计思路。