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。     

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。     

广州市PM_(2.5)浓度与人群每日死亡风险的空间分布特征

目的了解广州市大气PM_(2.5)暴露对居民每日死亡的影响及其空间分布特征。方法收集2013年1月1日—2014年12月31日期间广州市十二个区(县级市)31个大气监测站点的PM_(2.5)每日数据、气象数据和居民每日死亡数据,采用克里格插值模型和分布滞后非线性模型的时间序列分析方法,分别从全市及12个行政区域的大气PM_(2.5)污染状况及其对居民每日死亡的影响进行评估分析。结果研究期间,全市PM_(2.5)的年平均暴露浓度为49.5±25.6μg/m3,呈西、南部区域PM_(2.5)污染重,东北区域相对较低的区域分布特征;全市范围PM_(2.5)暴露与每日总非意外死亡的滞后累积最大效应RR为1.017(1.001,1.034;95%CI);白云区、从化区、南沙区、越秀区和荔湾区PM_(2.5)暴露与每日总非意外死亡最佳滞后效应RR值范围1.010~1.014(此为各区RR值范围,而非95%CI),滞后累积最大效应RR值范围1.010~1.057(此为各区RR值范围,而非95%CI);从化区、南沙区、越秀区和荔湾区PM_(2.5)暴露与每日心血管系统疾病死亡的最佳滞后效应RR值范围1.006~1.021(此为各区RR值范围,而非95%CI),滞后累积最大效应RR值范围1.017~1.059(此为各区RR值范围,而非95%CI);南沙区和越秀区PM_(2.5)暴露与每日呼吸系统疾病死亡的最佳滞后效应RR值分别为1.004和1.034,滞后累积最大效应RR值分别为1.018和1.110。结论广州市不同区域大气PM_(2.5)暴露对当地居民每日死亡的影响各有不同;呈现南、北两端和西部部分人口密集,交通拥挤的区域风险较高,其他区域风险不明显的空间分布特征。     

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。     

兰州市某办公建筑室内外PM2.5 浓度变化特征及相关性分析

为研究办公建筑室内外细颗粒污染物(PM2.5)质量浓度变化特征,于2019年9月～2020年7月对甘肃省兰州市某办公建筑室内外PM2.5质量浓度、温湿度、风速进行了连续监测.监测结果表明:室内外PM2.5质量浓度水平相关性显著,冬季室内外PM2.5质量浓度水平高于春季和夏季;春、夏季室内外PM2.5质量浓度日小时均值为...     

PM_(2.5)重量法现场测量技术研究

阐述了重量法(DPI)测量原理,分析了适用于现场测试的采样方法和操作流程,并首次利用DPI对燃煤电厂排放PM2.5进行现场测试研究,将测试结果同电荷法(ELPI)测试结果进行比较,研究发现两仪器的测试结果具有较好的一致性。DPI测试方法可为标准测试方法的选取提供参考。     

湖南某大学生态型校园PM_(2.5)浓度调查与分析

通过对湖南某生态性大学校园内的PM2.5浓度进行为期一周的布点监测,获得校园内PM2.5的浓度分布数据,结果表明整个校园内的PM2.5浓度基本超出了国家标准所规定的值。通过分析发现PM2.5超标与城市灰霾天气有很大的关系,灰霾天气是造成其超标的主要原因,其次是校园内施工场地施工的影响。最后,结合数据分析提出了改善校园环境的措施。     

钢铁企业PM_(2.5)污染情况分析及防控措施研究

介绍了PM2.5概念、组成、来源及危害,从太原市的地形、地貌、气象特征对PM2.5的影响方面进行了论述,对钢铁企业排放PM2.5的主要工序进行了分析,并针对太钢当前PM2.5的防控措施提出了一些建议。     

PM_(2.5)对A549细胞IL-1β表达的影响

目的研究6个不同城市大气污染颗粒PM_(2.5)对肺癌A549细胞炎症因子IL-1β的影响,探讨PM_(2.5)成分和炎症因子IL-1β之间的关系。方法采集湛江、广州、武汉、上海、北京和成都6个城市PM_(2.5),测定不同城市PM_(2.5)中金属元素及多环芳烃(PAHs)的含量。将不同城市PM_(2.5)以100μg/m L染毒A549细胞24 h,荧光定量PCR检测不同城市PM_(2.5)染毒细胞后细胞内炎症因子IL-1β基因表达水平。通过线性回归和相关性分析研究PM_(2.5)成分和细胞炎症因子之间的关系。结果 6个城市PM_(2.5)中均含有高浓度的PAHs,其中广州、武汉、上海3个城市PM_(2.5)中PAHs浓度高达900 pg/μg,高于其他3个城市。6个城市PM_(2.5)金属成分中,过渡金属元素Fe、Cu、Ni含量较高。6个城市PM_(2.5)均能够引起A549细胞内IL-1β基因表达水平上调,PM_(2.5)中PAHs和Ni元素含量与细胞内IL-1β表达水平呈显著相关。结论不同城市的PM_(2.5)能上调细胞IL-1β的表达,PM_(2.5)上调细胞内IL-1β的作用与PAHs和Ni元素相关。     

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   

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.     

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。     

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。     

哈尔滨典型街谷空间PM2.5分布场与绿色界面指数相关性研究

在城市化快速进程的背景下,城市街区PM2.5污染日益严重,本文选取哈尔滨在不同季节的典型街谷空间,对以叶面积密度（LA D）、叶面积指数（LAI）为实测要素的绿色界面指数以及PM2.5浓度进行实测对比研究。通过对实测数据的分析和挖掘,最终得出如下结论：首先,典型街谷空间PM2.5时段浓度呈现上午比下午平均高37.75%,冬季比夏季高4.7倍的特征;其次,街谷空间的灌木界面对PM2.5浓度场平均积极贡献率为18.62%;最后,对PM2.5的衰减率与实测街谷绿色界面的叶面积密度（LAD）与叶面积指数（LAI）进行相关性分析,结果显示街谷绿色界面对PM2.5浓度的衰减作用与叶面积密度（LAD）呈显著负相关关系,与叶面积指数（LAI）的相关性程度较弱。     

Functional group characterization of indoor, outdoor, and personal PM: results from RIOPA

Fourier transform infrared (FTIR) spectra of outdoor, indoor, and personal fine particulate matter (PM(2.5)) samples were collected during the Relationship of Indoor, Outdoor, and Personal Air (RIOPA) study. FTIR spectroscopy provides functional group information about the entire PM(2.5) sample without any chemical preparation. It is particularly important to characterizing the poorly understood organic fraction of PM(2.5). To our knowledge this is the first time that FTIR spectroscopy has been applied to a PM(2.5) exposure study. The results were used to chemically characterize indoor air and personal exposure. Sulfate was strongest in outdoor samples, which is consistent with the generally accepted understanding that sulfate is of outdoor origin. Absorbances attributed to soil dust were also seen in many outdoor and some indoor and personal samples. Inorganic nitrate absorbances were a common feature of many California and some New Jersey samples. Carbonyl absorbances showed substantial variation in strength, number of peaks, and wave number shift between samples, indicating variability in composition and sources. Absorbances attributed to aliphatic hydrocarbon and amide functional groups were enhanced in many personal and indoor samples, which suggested the influence of indoor sources in these homes. We speculate that meat cooking is one possible source of particulate amides. PRACTICAL IMPLICATIONS: To our knowledge this is the first time that FTIR spectroscopy has been used to characterize the composition of indoor and personal PM(2.5). The presence of sulfate, nitrate, ammonium, soil dust and a number of organic functional groups are all detected in one analysis on filter samples without extraction or other sample preparation. Differences between indoor and outdoor spectra are used to identify spectral features due to indoor-generated PM(2.5). Particularly interesting are the much larger aliphatic absorbances, shifts in carbonyl absorbances, and occasional small amide absorbances found in indoor and personal spectra but rarely in outdoor spectra. These observations are important because organics make up a large portion of PM(2.5) mass and their composition and properties are poorly characterized. The properties and behavior of organic compounds in airborne particles are often predicted based on their functional group composition. This analysis begins the development of a better understanding of the functional group composition of indoor and personal PM(2.5) and how it differs from that of outdoor PM(2.5). Eventually this will lead to an improved understanding of the properties, behavior and effects of PM(2.5) of indoor and outdoor origin.     

城市绿地空间形态对PM2.5的消减影响——以武汉市为例

缓解大气颗粒物污染、营造清洁健康的城市环境是中国绝大部分城市须解决的问题之一。城市绿地能有效缓解PM_(2.5),然而当前对绿地空间形态的研究不足,导致能在规划设计中直接应用的成果不多。基于武汉市9个城市绿地空间形态要素量化差异与实地测量的PM_(2.5)浓度大小,探索二者深层的量化关系规律。结果显示:1)PM_(2.5)消减量随绿地规模的增加呈增长趋势,当规模大于5～10 hm~2消减量减缓;2)绿地面积、周长及形状指数与PM_(2.5)的消减量显著正相关,分维指数与近圆形形状指数相关性不显著;3)PM_(2.5)的消减效率随绿地规模的增加急剧下降,当绿地规模超过5～10 hm~2,消减效率变化不明显。通过量化分析,揭示对PM_(2.5)消减具有显著影响的城市绿地空间形态指标,提出适当的规模、不规则或复杂的绿地形态及分散式的布局等绿地优化策略。     

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。