空调办公室热环境的数值模拟

建立办公室的CFD模型,以雷诺平均方程和k-ε两方程紊流模型为基础,应用Monte Carlo法,考虑太阳辐射产生附加热流的影响,研究了室内速度分布、温度场、PMV值及PM2.5浓度场。计算结果和实验数据表明:该仿真模型能准确计算室内热环境,散流器送风不合理,风速分布不均,导致PMV值偏大,人体会感觉较热,需要进一步优化送风口的风速或开度大小;室内温度均值在26.15 ℃,上下浮动不超过±2 ℃,温度分布均匀,但电脑、人体和荧光灯散热对其附近温度场分布有影响;PM2.5含量为良,室内物品表面细微颗粒对PM2.5的浓度有一定影响。     

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。     

Small-scale spatial variability of particle concentrations and traffic levels in Montreal: a pilot study

Little is known about the particulate exposure of populations living along major urban roads. The objective of this pilot study was to explore the small-scale spatial and temporal variability of the absorption coefficient of PM2.5 filters, as a surrogate for elemental carbon, in relation to levels of PM2.5, at residential sites with varying traffic densities in a large Canadian city. Concurrent 24-h measurements were performed at four residential sites during 7 weeks. A gradient existed across all four sites for the absorption coefficient of the filters (and NO2 levels). In contrast, the levels of PM2.5 were quite similar at all sites. The difference in the filter absorption coefficient of PM2.5 filters, between an urban background and a residential traffic site (with about 30000 vehicles/day), expressed as a percentage of the background site, was 40%. These results indicate that spatial variability in PM2.5 absorption coefficient can be observed with traffic intensity on a small scale within a North American city and suggests that regression modelling approaches similar to those used in European studies could be used to estimate exposure of the general population to traffic-related particles on a local scale in North America.     

Spatial heterogeneity of personal exposure to airborne metals in French urban areas

The spatial distribution of urban population exposures to ambient air particles was investigated as part of the Genotox'ER study conducted in four metropolitan areas (Grenoble, Paris, Rouen and Strasbourg) in France. In each city, 60 to 90 non-smoking adult and children volunteers were selected. Subjects lived in three different urban sectors: one highly exposed to traffic emissions, one influenced by local industrial sources, and a background urban environment. The Harvard Chempass multi-pollutant personal sampler was used to sample PM10 and PM2.5 particles during 48 h during two different seasons ('hot' and 'cold'). The elemental composition of the filters was analysed by Particle-Induced X-ray Emission (PIXE). Sixteen elements were found to be over the method detection limits: Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn and Pb. The relative concentrations of elements of crustal origin (Si, Al, Ca) were higher in the coarse fraction of PM10 filters, while elements associated with combustion processes (traffic emissions or industrial combustion) presented higher relative concentrations in the PM2.5 fraction (S, Ni, V, Pb). Spatial heterogeneity of elemental exposures by urban sector is substantial for some metals of health concern, with 20% to 90% greater exposure values, on average, in the traffic proximity or industrial sectors, compared to the background sector, for Fe, Zn, Cu, V and Cr. This spatial heterogeneity should not be overlooked in epidemiological or risk assessment studies.     

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。     

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.     

Dispersion of particles from vehicle emissions around high- and low-rise buildings

Understanding the distribution of outdoor pollutants around a building envelope, generated by sources located in its vicinity, is important when choosing the location of building ventilation system intakes, as well as for quantifying the exposure of people living or working in the building. A systematic experimental characterisation of the number concentration of submicrometre particles was undertaken around the envelope of six buildings (both low- and high-rise) at different distances from a road (the main pollution source). The concentrations were measured using two TSI Scanning Mobility Particle Sizers. PM2.5 concentrations were also monitored around the low-rise buildings using two TSI DustTraks. For the three high rise buildings the concentration of fine and ultra-fine particles decreased in most cases to about 50-60% from the approximate ground level readings (between heights of 0 to 6 m), to full building height (from 24 to 33 m above the ground). Measurements of submicrometre particle number concentrations as well as PM2.5 fraction in the envelope around low-rise isolated buildings did not show any significant trends from the front to the rear of the building. The sensitivity of PM2.5 measurements to a small number of larger particles, possibly from sources other than vehicle emissions, was observed.     

城市街区形态对PM10、PM2.5的影响研究——以武汉为例

构成城市肌理的普遍街区的空间形态与颗粒物浓度存在显著差异。基于武汉市18个空气质量监测点的PM_(10)、PM_(2.5)数据与二维、三维街区形态指标,揭示不同街区形态与PM_(10)、PM_(2.5)之间的深层关系规律,以期为城市规划管控提供参考。双变量相关分析与一元回归分析揭示了街区形态与PM_(10)、PM_(2.5)的相关性及其影响规律,多元线性回归分析揭示不同街区形态对PM_(10)、PM_(2.5)变化的贡献度。结果表明,街区之间的平均PM_(10)、PM_(2.5)浓度分别在城市平均水平55%～106%、59%～117%之间浮动,绿化覆盖率、道路面积率和相对高程对PM_(10)、PM_(2.5)具有显著影响,相对高程与绿化覆盖率对PM_(10)变化的贡献度达83.0%,绿化覆盖率对PM_(2.5)变化的贡献度达72.5%,道路面积率对PM_(10)、PM_(2.5)变化的贡献度分别为17.0%、27.5%。     

Applying indoor and outdoor modeling techniques to estimate individual exposure to PM2.5 from personal GPS profiles and diaries: A pilot study

Impacts of individual behavior on personal exposure to particulate matter (PM) and the associated individual health effects are still not well understood. As outdoor PM concentrations exhibit highly temporal and spatial variations, personal PM exposure depends strongly on individual trajectories and activities. Furthermore, indoor environments deserve special attention due to the large fraction of the day people spend indoors. The indoor PM concentration in turn depends on infiltrated outdoor PM and indoor particle sources, partially caused by the activities of people indoor.We present an approach to estimate PM2.5 exposure levels for individuals based upon existing data sources and models. For this pilot study, six persons kept 24-hour diaries and GPS tracks for at least one working day and one weekend day, providing their daily activity profiles and the associated geographical locations. The survey took place in the city of Münster, Germany in the winter period between October 2006 and January 2007. Environmental PM2.5 exposure was estimated by using two different models for outdoor and indoor concentrations, respectively. For the outdoor distribution, a dispersion model was used and extended by actual ambient fixed site measurements. Indoor concentrations were modeled using a simple mass balance model with the estimated outdoor concentration fraction infiltrated and indoor activities estimated from the diaries. A limited number of three 24-hour indoor measurements series for PM were performed to test the model performance.The resulting average daily exposure of the 14 collected profiles ranged from 21 to 198 µg m^− 3 and showed a high variability over the day as affected by personal behavior. Due to the large contribution of indoor particle sources, the mean 24-hour exposure was in most cases higher than the daily means of the respective outdoor fixed site monitors.This feasibility study is a first step towards a more comprehensive modeling approach for personal exposure, and therefore restricted to limited data resources. In future, this model framework not only could be of use for epidemiological research, but also of public interest. Any individual operating a GPS capable device may become able to obtain an estimate of its personal exposure along its trajectory in time and space. This could provide individuals a new insight into the influence of personal habits on their exposure to air pollution and may result in the adaptation of personal behavior to minimize risks.     

西安市调整供暖措施后颗粒物浓度污染状况分析

通过对2017年西安市采暖期采用煤改气、煤改电措施后大气颗粒物(包括PM10和PM2.5)的污染状况进行研究分析。结果表明:改变采暖措施后,西安大气中颗粒物的浓度有所下降,其中PM10的浓度范围34.9~374μg/m^3,平均浓度为153.9μg/m^3。PM2.5的浓度范围20.2~307.5μg/m^3,平均浓度为99.1μg/m3,PM2.5占PM10的平均比例为64.4%。典型日的污染仍较为严重。在测试范围内,PM10和PM2.5的质量浓度日变化呈双峰分布特征,在凌晨2:00出现浓度极值,16:30以后可以看出颗粒物浓度有上升的趋势。总体来说,西安治霾仍然还有很长路要走。     

不同城市绿地类型对PM 2.5 、PM 10 以及TSP的消减效应研究

一直以来,绿地系统都是城市户外公共活动、文化展示、景观美化等功能的重要载体。此外,基于景观生态学的绿地系统研究使其生态调节功能进一步强化。作为城市的主要户外公共空间,城市绿地的空气质量关乎整个城市居民的健康,虽然已有部分研究开始初步探索城市绿地在消减空气颗粒物上的作用,但仍缺乏更加系统性的对比研究,以揭示不同绿地类型中绿地率、植物群落结构等特征对空气颗粒物的不同消减效应。本文采用定量测定的方法,对重庆市典型的绿地类型进行全年的测试分析。研究表明：绿地率最高的公园绿地对于空气颗粒物的消减率最明显;在一年四季中,TSP在夏季的消减率最高,PM 10 的消减率春季最高,PM 2.5 的消减率冬季最高;在不同空气颗粒物的消减率对比分析中,各种城市绿地对TSP的消减率最高,能达到15%以上,对PM 2.5 的消减率最低,在夏季甚至出现负值。由此可见,城市绿地对总悬浮颗粒物（TSP）和粗颗粒物（PM 10 ）都具有很好的消减效果,但是在对细颗粒物(PM 2.5 )的消减效果则不明显。     

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.     

风机盘管加新风系统室内PM2.5污染控制

在对民用建筑通风系统常用过滤器滤料性能测试基础上,建立了常规风机盘管加新风系统空调房间室内颗粒物浓度集总参数模型,讨论了回风过滤段和新风过滤段过滤器效率的设计选型方法。以西安市某空调系统为例,为满足室内PM2.5污染控制标准,基于室外PM2.5浓度\"不保证10d\"取值计算,结果表明,余压为50~80Pa的机组回风过滤器效率选用G3、G4型过滤器,余压为30~50Pa的机组回风过滤器效率选用初效G2、G3型过滤器,同时,室内设置等效过滤效率的空气净化器,新风选用初效G4加中效F7或F8两级过滤。