西安地铁一、二号线环境空气品质调查分析

本文对西安地铁已投入运营的一、二号线各车站的站台、站厅、车厢内PM10、PM2.5、CO2、TVOC及氡浓度进行监测。结果表明,现有的机械通风系统可以较好地控制地铁环境中的颗粒物、CO2和氡的浓度,但是对于运行初期环境中的TVOC,通风换气量不够,浓度普遍超标。两条线站厅、站台和车厢的PM10浓度均未超标;二号线个别站点站台PM2.5平均浓度不同程度超标。两条线站台、站厅CO2平均浓度最高值均出现在人流密度较高的站点。一号线站台、站厅、车厢TVOC浓度普遍超标,二号线只有车厢内超标。两条线的氡浓度均未超标,但站台高于站厅。相关性分析表明,站台PM10浓度与室外相关性较强,而站台和车厢内PM2.5浓度与室外相关性均较弱。     

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)...     

上海市一号线地铁站空气质量调研分析

本文以上海地铁1号线部分地下车站为研究对象,通过调研与实测的方式研究了地铁站内的环境状况。实验结果表明:地铁站台内以温湿度为代表的微气候能够满足乘客的需求。CO_2的浓度水平略高于0.10%的标准值,换乘站的浓度比非换乘站的浓度明显高出很多。在地铁站内,颗粒物浓度过高,PM10的平均浓度范围为200～800μg/m~3,超标比较严重,晴天的站台内颗粒物浓度普遍高于雨天的站台内颗粒物浓度,特别是细颗粒物PM2.5的浓度所占比例很大。     

环境空气PM2.5和PM10自动监测相关问题分析

在公众对改善环境空气质量需求的推动下,大气细颗粒物PM2.5作为基本监测项目纳入《环境空气质量标准》（GB3095-2012）, 肇庆市已完成PM2.5的监测能力建设和实时发布。根据2012年6月5日城市大气颗粒物（PM2.5和PM10）监测数据,出现了城市大气颗粒物（PM2.5和PM10）监测因为仪器方法技术局限而出现负值和“倒挂”（PM2.5监测浓度高于PM10）的现象,对该现象的研究分析对将来的自动监测工作极为重要。     

冬季高校教室温湿度及PM2.5、PM10变化规律研究

以西安某高校教室为研究目标,运用相关仪器进行实地监测及数据分析的方法,研究了教室内温湿度变化及PM2.5、P M10的变化规律.结果表明:冬季教室内温度的变化与上课时间的安排及课间人员的流动密切相关,冬季节正常天气下教室内湿度与温度两者之间的变化呈现出显著的负相关关系,降雨降雪天气教室内相对湿度变化受室外湿度影响波动较大.室外PM2.5及PM10浓度与室内两者的浓度均有显著正相关性,教室朝向对PM2.5及PM10浓度有较大影响.     

武汉地铁2号线空气质量调查分析

为调研武汉市地铁的乘车环境,对地铁2号线出口处、地下站台及车厢进行空气污染物浓度的监测与分析。结果表明:地铁站台及车厢环境内温湿度状况良好,CO浓度较低。但苯、TVOC浓度总体偏高,颗粒物PM2.5、PM10浓度超标较为严重。其中,高人群密度车厢内的空气质量最差,PM2.5、CO2、TVOC的浓度平均值分别达到0.198 mg/m3、1326 ppm、2.050 ppm,均超过国家相关标准。此外,地铁站台出入口处的PM2.5平均浓度最高,达到0.49 mg/m3,超过国家标准5.5倍,出入口处的颗粒物浓度过高会加重站内颗粒物污染。通过结果分析,车厢内合理加大通风量和出入口处安置风幕有利于改善地铁环境。     

广州地铁五号线车站空气质量状况调查与分析

目的了解广州地铁五号线车站空气质量现状,为地铁卫生管理和疾病预防控制等工作的开展提供科学依据及合理建议。方法对广州地铁五号线全线24个车站的站台、站厅各取5个点进行监测。监测指标包括温度、相对湿度、风速、照度、噪声、一氧化碳(CO)、二氧化碳(CO2)、可吸入颗粒物(PM10)、甲醛、空气细菌总数。结果 21个车站噪声监测均值超过卫生标准(超标率为87.50%)。3个车站甲醛监测均值超过卫生标准(超标率为12.50%)。站台CO2的监测均值高于站厅,相对湿度、PM10、照度低于站厅(P<0.05)。换乘车站CO2、甲醛、空气细菌总数、照度的监测均值高于非换乘车站,风速低于非换乘车站(P<0.05)。高架车站温度、CO、PM10的监测均值高于站厅,CO2、甲醛低于站厅(P<0.05)。结论噪声、甲醛是地铁需要重视的空气卫生学问题。换乘车站是地铁改善空气的重点场所。适当增加新风供给、加强新风过滤,对提高地铁空气质量有积极意义。     

唐山市细颗粒物PM_(2.5)污染特征分析

根据2013年1⁹月唐山市城市空气质量PM2.5监测资料进行统计分析,表明PM2.5污染具有季节性,冬季污染严重,春夏季较低。PM2.5浓度日变化则呈双峰状态,高峰出现在上午89月唐山市城市空气质量PM2.5监测资料进行统计分析,表明PM2.5污染具有季节性,冬季污染严重,春夏季较低。PM2.5浓度日变化则呈双峰状态,高峰出现在上午8⁹时,次高峰出现在晚上219时,次高峰出现在晚上21²2时。地域分布则呈现出越靠近市中心PM2.5浓度越高的特征。PM2.5/PM10的比值为0.606,表明唐山市区空气中细颗粒物PM2.5在PM10中的比重大于粗颗粒物,细颗粒物PM2.5污染严重。     

地铁站厅至站台楼梯口风速对火灾烟气运动的影响

地铁车站站台发生火灾,连接站厅与站台的楼梯口保持一定风速,可阻挡烟气向站厅蔓延并为人员疏散提供诱导气流。为研究楼梯口风速对车站火灾烟气运动的影响,试验对不同排烟模式下楼梯口风速进行测量,建立数值计算模型进行模拟。结果表明：火灾场景下楼梯口风速大于无火源场景下风速,因此常规楼梯口风速校核设计方法由于没考虑真实火灾情况下各种因素的复杂作用,需进一步改进;楼梯口附近起火,烟气易从挡烟垂壁溢出向站厅层蔓延,站台火灾时站厅层为送风状态,存在溢出烟气时站厅层烟浓度可增至大于站台层;站台公共区着火,增开隧道风机,能够增     

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。     

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.     

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。     

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).     

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.     

内置式永磁同步曳引机的设计

列举了永磁同步曳引机的优点，提出了一种内置式、低转矩脉动、低成本永磁同步曳引机的设计方案，并采用Ansoft磁场分析软件进行分析，试验表明该设计方案的合理性。     

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。