2013年冬春季济南市某办公场所室内空气颗粒物质量浓度分析

目的了解冬春季节室内空气颗粒污染物污染水平。方法于2013年1—5月工作日期间在济南市某办公场所采用LD-5C(B)微电脑激光粉尘仪对室内空气颗粒物PM10、PM2.5进行监测。结果济南市冬春季节室内颗粒物PM2.5、PM10平均质量浓度分别为0.082、0.115 mg/m3;采暖期室内PM2.5、PM10的质量浓度(0.152、、0.191 mg/m3)高于非采暖期(0.050、、0.079 mg/m3),差异有统计学意义(P<0.05);采暖期室内PM2.5/PM10为0.807,非采暖期PM2.5/PM10为0.598,差异有统计学意义(Z=4.917,P=0.001);室内外PM2.5相关系数r=0.878,P=0.001;室内外PM10相关系数r=0.701,P=0.001。结论济南市冬春季节室内颗粒物污染较重,室内外颗粒物质量浓度有较好的相关性,采暖对室内细颗粒物浓度影响较大。     

服装市场室内可吸入颗粒物PM10的污染特征

本文采用TSI AM-510型智能防爆粉尘检测仪和TSI Aero Trak TM 8220型激光粒子计数器对北京市西城区三个服装市场的室内、室外PM10的质量浓度和数量浓度进行了现场测试,并评价可吸入颗粒物的浓度水平和污染特征,分析室内外颗粒物之间的相关性及其影响因素。结果表明:1PM10是服装市场室外大气及室内环境的主要污染物。服装市场在室外颗粒物PM10质量浓度超标的情况下(0.15 mg/m~3),室内颗粒物PM10与标准相比的合格率为30%,在室外PM10质量浓度0.15 mg/m~3的情况下,室内PM10的合格率为92.2%。2服装市场室内外颗粒物浓度水平之间存在密切的相关性。室外颗粒物是室内颗粒污染的主要来源,室内颗粒物浓度随室外浓度变化而变化,且吸烟和人员活动是服装市场可吸入颗粒物的重要室内污染源。3对于颗粒物数量浓度比,室内室外PM1/PM10、PM2.5/PM10、PM1/PM2.5的比值都在0.99以上,表明可吸入颗粒物中的绝大部分都是粒径小于2.5μm的可吸入肺颗粒物,对人体健康具有更大危害。     

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。     

西安市某办公建筑室内外颗粒物浓度变化特征分析

本文通过建立质量平衡方程对西安市某办公建筑室内颗粒物浓度进行了理论分析,并对该建筑室内外PM10和PM2.5的质量浓度进行了实时监测。结合线性回归方程、室内外监测浓度线性拟合曲线及室内浓度随时间的指数拟合曲线,对该普通办公房间室内颗粒排放源及室内颗粒浓度变化特征进行了研究。结果表明,该建筑室内PM10的平均发尘为7.93～12.48 mg/h,室内PM2.5的平均发尘为2.89～4.08 mg/h;室内PM10和PM2.5呈现指数变化且随时间呈下降趋势。     

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。     

渗透通风房间室内外颗粒物质量浓度相关性分析

通过某气密性较好的办公房间的渗透通风实验,分析了室内外累积粒径颗粒物和分段粒径颗粒物的逐时质量浓度分布,以及室内外不同粒径颗粒物的质量浓度相关性。研究发现:不同粒径颗粒物的质量浓度相关性差异很大,小粒径颗粒物相关性较强,随着粒径的增大,相关性逐渐降低,当粒径大于5μm时,室内外颗粒物质量浓度无明显相关性;分段粒径颗粒物的室内外质量浓度相关性更能反映建筑围护结构的阻隔性能和室内颗粒物的污染特征。     

办公建筑中空调形式对室内外PM2.5浓度相关性的影响

室外PM2.5可通过新风及围护结构缝隙渗透至室内,室外PM2.5较高时尤为明显,结果导致室内空气中的PM2.5浓度上升。为了研究空调形式对室内外PM2.5浓度相关性的影响,在2015年夏季对重庆某办公建筑中采用不同空调形式的室内外PM2.5浓度进行了实测。实测结果发现:集中式空调、分体式空调和非空调房间室内外PM2.5浓度比变化范围分别为0.59~0.76、0.47~0.76、0.71~0.91。室内外PM2.5浓度相关性系数的排序为:集中式空调环境(0.94)非空调环境(0.92)分体式空调环境(0.77),研究结果表明,办公建筑的空调形式,对室内外PM2.5浓度的相关性有影响。     

不同住所室内PM2.5的浓度变化规律及温湿度对室内颗粒物影响的初探

为深入探究不同住所室内颗粒物PM_(2.5)的浓度水平随室外颗粒物及室内污染源的变化规律,于2017年1月-2018年1月对北京城区4户居民住宅、2个学生宿舍和1户农村住宅的室内PM_(1.0)、PM_(2.5)及PM_(10)浓度、室外PM_(2.5)浓度及室内外温湿度变化进行了逐时测试,并对测试分析结果进行了差异性检验。结果表明:①城市住户室内污染源对室内PM_(2.5)浓度的影响程度为:吸烟烹饪清洁。农户污染源对室内PM_(2.5)的影响顺序为:燃煤燃烧薪柴吸烟清洁人员活动。②当住所门窗关闭室外雾霾开始或结束后,室内PM_(2.5)浓度的升高或降低均延迟于室外PM_(2.5)的变化。③城市住宅与学生宿舍的平均I/O小于1,农村住户的平均I/O大于1,且不同住所之间的I/O差异性显著(P0.05)。④住户相对湿度在10%～50%时(冬季采暖),室内颗粒物PM_(1.0)/PM_(2.5)及PM_(2.5)/PM_(10)的比值随相对湿度增加而增加,室内细颗粒PM_(2.5)的主要占比为细微颗粒物PM_(1.0);住户相对湿度在50%～80%时(秋季实测),室内颗粒物PM_(1.0)、PM_(2.5)和PM_(10)平均浓度随相对湿度增加而下降。⑥Spearman相关分析得到室内外温差与室内PM_(10)浓度和PM_(2.5)浓度呈现显著性负相关,与室内PM_(1.0)浓度无明显相关性。研究成果可为室内颗粒物控制提供理论依据并对改善住所环境和保护人体健康具有重要意义。     

一般办公环境粉尘污染特征分析

对典型办公室内的粉尘颗粒分布特征及室内外颗粒浓度比值进行了实验研究,结果表明,室内外的粉尘以小颗粒为主,1.0～3.0μm粒径的颗粒分别占室内、外总悬浮颗粒物TSP质量的46.70%和45.06%;所有测试房间室内外TSP的I/O比值为0.61～0.72,PM10的I/O比值为0.64～0.74;I/O比值随粒径的增大而减小,变化范围为0.406～0.995,但与纯自然通风条件下不同,变化趋势为较小粒径时下降迅速,之后趋于平缓。     

基于典型城市气象参数的建筑通风用新风所含污染物统计分析

选取我国5个气候分区的12个典型城市,用SPSS软件统计分析了2012—2017年PM2.5,PM10,SO_2,NO_2及温度和相对湿度的分布特征,以及各气象要素之间的关联性。结果表明:PM2.5,PM10,SO_2,NO_2日均浓度的变化趋势呈现冬高夏低,年内单峰型、年间双峰型正弦分布的规律,且温湿度变化趋势与空气污染物质量浓度相似;雾霾综合污染指数F存在地区差异性,季节性特征明显且冬季峰值最大;空气污染物的主成分为PM2.5和PM10(累计贡献率大于90%),PM2.5和PM10与温度和相对湿度的线性相关性明显(相关系数大于0.5),SO_2和NO_2与温度和相对湿度的线性相关性不明显(相关系数小于0.3);用考虑温湿度的优化后的雾霾综合污染指数分析空气污染因素时,方差数值小,数值离散程度小,分析结果更精确。     

Measurements of children's exposures to particles and nitrogen dioxide in Santiago, Chile

An exposure study of children (aged 10-12 years) living in Santiago, Chile, was conducted. Personal, indoor and outdoor fine and inhalable particulate matter (< 2.5 .m in diameter, PM2.5 and < 10 microm in diameter, PM10, respectively), and nitrogen dioxide (NO2) were measured during pilot (N = 8) and main (N = 20) studies, which were conducted during the winters of 1998 and 1999, respectively. For the main study, personal, indoor and outdoor 24-h samples were collected for five consecutive days. Similar mean personal, indoor and outdoor PM2.5 concentrations (69.5, 68.5 and 68.1 microg/m3, respectively) were found. However, for coarse particles (calculated as the difference between measured PM10 and PM2.5, PM2.5-10), indoor and outdoor levels (35.4 and 47.4 microg/m3) were lower than their corresponding personal exposures (76.3 microg/m3). Indoor and outdoor NO2 concentrations were comparable (35.8 and 36.9 ppb) and higher than personal exposures (25.9 ppb). Very low ambient indoor and personal O3 levels were found, which were mostly below the method's limit of detection (LOD). Outdoor particles contributed significantly to indoor concentrations, with effective penetration efficiencies of 0.61 and 0.30 for PM2.5 and PM2.5-10, respectively. Personal exposures were strongly associated with indoor and outdoor concentrations for PM2.5, but weakly associated for PM2.5-10. For NO2, weak associations were obtained for indoor-outdoor and personal-outdoor relationships. This is probably a result of the presence of gas cooking stoves in all the homes. Median I/O, P/I and P/O ratios for PM2.5 were close to unity, and for NO2 they ranged between 0.64 and 0.95. These ratios were probably due to high ambient PM2.5 and NO2 levels in Santiago, which diminished the relative contribution of indoor sources and subjects' activities to indoor and personal PM2.5 and NO2 levels.     

Characterizing ultrafine particles and other air pollutants at five schools in South Texas

This study examined five schools with different ventilation systems in both urban and rural areas in South Texas. Total particle number concentration, ultrafine particle (UFP, diameter < 100 nm) size distribution, PM(2.5) , and CO(2) were measured simultaneously inside and outside of various school microenvironments. Human activities, ventilation settings, and occupancy were recorded. The study found a greater variation of indoor particle number concentration (0.6 × 10(3) -29.3 × 10(3) #/cm(3) ) than of outdoor (1.6 × 10(3) -16.0 × 10(3) #/cm(3) ). The most important factors affecting indoor UFP levels were related to various indoor sources. Gas fan heaters increased the indoor-to-outdoor ratio (I/O ratio) of total particle number concentrations to 30.0. Food-related activities, cleaning, and painting also contributed to the increased indoor particle number concentration with I/O ratios larger than 1.0. Without indoor sources, the I/O ratios for total particles varied from 0.12 to 0.66 for the five ventilation systems studied. The I/O ratio decreased when the outdoor total particle number concentration increased. Particles with diameters <60 nm were less likely to penetrate and stay airborne in indoor environments than larger particles and were measured with smaller I/O ratios. PRACTICAL IMPLICATIONS: From an exposure assessment perspective, schools are important and little-studied microenvironments where students congregate and spend a large proportion of their active time. This study provides information for indoor and outdoor ultrafine particle concentrations at different types of school microenvironments. These data may allow future epidemiological studies to better estimate exposure and assess ultrafine particles health effects among students.     

Characterization of indoor air quality in primary schools in Antwerp, Belgium

The indoor air quality of 27 primary schools located in the city centre and suburbs of Antwerp, Belgium, was assessed. The primary aim was to obtain correlations between the various pollutant levels. Indoor:outdoor ratios and the building and classroom characteristics of each school were investigated. This paper presents results on indoor and local outdoor PM2.5 mass concentrations, its elemental composition in terms of K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Pb, Al, Si, S, and Cl, and its black smoke content. In addition, indoor and local outdoor levels of the gases NO2, SO2, O3, and BTEX (benzene, toluene, ethyl benzene, and xylene isomers) were determined. Black smoke, NO2, SO2 and O3, occurred at indoor:outdoor ratios below unity, indicating their significant outdoor sources. No linear correlation was established between indoor and outdoor levels for PM2.5 mass concentrations and BTEX; their indoor:outdoor ratios exceeded unity except for benzene. Classroom PM2.5 occurred with a different elemental composition than local outdoor PM2.5. The re-suspension of dust because of room occupation is probably the main contributor for the I/O ratios higher than 1 reported for elements typically constituting dust particles. Finally, increased benzene concentrations were reported for classrooms located at the lower levels. PRACTICAL IMPLICATIONS: The elevated indoor PM2.5, and BTEX concentrations in primary school classrooms, exceeding the ambient concentrations, raise concerns about possible adverse health effects on susceptible children. This is aggravated by the presence of carpets and in the case of classrooms at lower levels. Analysis of PM2.5's elemental composition indicated a considerable contribution of soil dust to indoor PM2.5 mass. In order to set adequate threshold values and guidelines, detailed information on the health impact of specific PM2.5 composites is needed. The results suggest that local outdoor air concentrations measurements do not provide an accurate estimation of children's personal exposures to the identified air pollutants inside classrooms.     

Indoor/outdoor relationships for PM2.5 and associated carbonaceous pollutants at residential homes in Hong Kong - case study

Six residences were selected (two roadside, two urban, and two rural) to evaluate the indoor-outdoor characteristics of PM(2.5) (aerodynamic diameter <2.5 microm) carbonaceous species in Hong Kong during March and April 2004. Twenty-minute-averaged indoor and outdoor PM(2.5) concentrations were recorded by DustTrak samplers simultaneously at each site for 3 days to examine diurnal variability of PM(2.5) mass concentrations and their indoor-to-outdoor (I/O) ratios. Daily (24-h average) indoor/outdoor PM(2.5) samples were collected on pre-fired quartz-fiber filters with battery-powered portable mini-volume samplers and analyzed for organic and elemental carbon (OC, EC) by thermal/optical reflectance (TOR) following the Interagency Monitoring of Protected Visual Environments (IMPROVE) protocol. The average indoor and outdoor concentrations of 24 h PM(2.5) were 56.7 and 43.8 microg/m(3), respectively. The short-term PM(2.5) profiles indicated that the penetration of outdoor particles was an important contributor to indoor PM(2.5), and a household survey indicated that daily activities were also sources of episodic peaks in indoor PM(2.5). The average indoor OC and EC concentrations of 17.1 and 2.8 microg/m(3), respectively, accounted for an average of 29.5 and 5.2%, respectively, of indoor PM(2.5) mass. The average indoor OC/EC ratios were 5.8, 9.1, and 5.0 in roadside, urban, and rural areas, respectively; while average outdoor OC/EC ratios were 4.0, 4.3, and 4.0, respectively. The average I/O ratios of 24 h PM(2.5), OC, and EC were 1.4, 1.8, and 1.2, respectively. High indoor-outdoor correlations (r(2)) were found for PM(2.5) EC (0.96) and mass (0.81), and low correlations were found for OC (0.55), indicative of different organic carbon sources indoors. A simple model implied that about two-thirds of carbonaceous particles in indoor air are originated from outdoor sources. PRACTICAL IMPLICATIONS: Indoor particulate pollution has received more attentions in Asia. This study presents a case study regarding the fine particulate matter and its carbonaceous compositions at six residential homes in Hong Kong. The characteristics and relationship of atmospheric organic and elemental carbon were discussed indoors and outdoors. The distribution of eight carbon fractions was first reported in indoor samples to interpret potential sources of indoor carbonaceous particles. The data set can provide significant scientific basis for indoor air quality and epidemiology study in Hong Kong and China.     

两典型办公室室内颗粒物浓度监测与分析

对一普通办公楼及甲级办公楼办公室内、外颗粒物浓度进行监测。监测结果显示建筑室外颗粒物污染严重;普通办公楼室内颗粒物污染严重,甲级办公楼室内颗粒物浓度较低;甲级办公楼室内外颗粒物浓度I／O比值较普通办公楼小;两办公楼室内、外的PM2．5污染均较PMIO污染频繁;室内人和物的剧烈活动、吸烟等活动会造成严重的室内颗粒物污染。     

Hospital indoor respirable particles and carbonaceous composition

Indoor air PM2.5 and PM10 samples were collected at the different types of indoor enviornment in the four hospitals and their adjacent outdoor environments in Guangzhou, China, during the summertime. The objectives of this study were (1) to characterize the indoor PM concentrations and associated carbonaceous species in hospitals, (2) to investigate the potential indoor sources and (3) to reconstruct carbonaceous composition in PM. Additionally, regression analysis was made to evaluate effect of outdoor sources to indoor PM levels and comparison was made between I/O levels in different types of indoor environment to evaluate effects of human activities and ventilation types to indoor PM levels.     

Fine particle number and mass concentration measurements in urban Indian households

Fine particle number concentration (D(p)>10 nm, cm(-3)), mass concentrations (approximation of PM(2.5), microg m(-3)) and indoor/outdoor number concentration ratio (I/O) measurements have been conducted for the first time in 11 urban households in India, 2002. The results indicate remarkable high indoor number and mass concentrations and I/O number concentration ratios caused by cooking. Besides cooking stoves that used liquefied petroleum gas (LPG) or kerosene as the main fuel, high indoor concentrations can be explained by poor ventilation systems. Particle number concentrations of more than 300,000 cm(-3) and mass concentrations of more than 1000 microg m(-3) were detected in some cases. When the number and mass concentrations during cooking times were statistically compared, a correlation coefficient r>0.50 was observed in 63% of the households. Some households used other fuels like wood and dung cakes along with the main fuel, but also other living activities influenced the concentrations. In some areas, outdoor combustion processes had a negative impact on indoor air quality. The maximum concentrations observed in most cases were due to indoor combustion sources. Reduction of exposure risk and health effects caused by poor indoor air in urban Indian households is possible by improving indoor ventilation and reducing penetration of outdoor particles.     

The analysis of PM2.5 and associated elements and their indoor/outdoor pollution status in an urban area

In this study, elemental composition of PM2.5 and the status of indoor/outdoor pollution were investigated in a commercial building near a roadside area in Daejeon, Korea. A total of 60 parallel PM2.5 samples were collected both on the roof (outdoor) and in an indoor office of a building near a highly congested road during the spring and fall of 2008. The concentrations of 23 elements were analysed from these PM2.5 samples using instrumental neutron activation analysis. PM2.5 levels in indoor environment (47.6 ± 16.5 μg/m(3)) were noticeably higher than the outdoor levels (37.7 ± 17.2 μg/m(3)) with the I/O concentration ratio of 1.37 ± 0.33 [correlation coefficient (r) = 0.89, P < 0.001]. Principal component analysis results coincidently showed the predominance of sources such as soil dust, traffic, oil/coal combustion and road dust for both indoor and outdoor microenvironments. An isolated source in the indoor environment was assigned to environmental tobacco smoke (ETS) with high factor loading of Ce, Cl, I, K, La and Zn. The overall results of our study indicate that the sources of indoor constituents were strongly dependent on outdoor processes except for the ones affected by independent sources such as ETS. PRACTICAL IMPLICATIONS: An improved understanding of the factors affecting the indoor PM2.5 concentration levels can lead to the development of an efficient management strategy to control health risks from exposure to indoor PM2.5 and related toxic components. A comparison of our comprehensive data sets indicated that most indoor PM2.5 and associated elemental species were strongly enriched by indoor source activities along with infiltration of ambient outdoor air for a naturally ventilated building.     

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.