In-vehicle Measurement of Ultrafine Particles on Compressed Natural Gas, Conventional Diesel, and Oxidation-catalyst Diesel Heavy-duty Transit Buses

Many metropolitan transit authorities are considering upgrading transit bus fleets to decrease ambient criteria pollutant levels. Advancements in engine and fuel technology have lead to a generation of lower-emission buses in a variety of fuel types. Dynamometer tests show substantial reductions in particulate mass emissions for younger buses (<10 years) over older models, but particle number reduction has not been verified in the research. Recent studies suggest that particle number is a more important factor than particle mass in determining health effects. In-vehicle particle number concentration measurements on conventional diesel, oxidation-catalyst diesel and compressed natural gas transit buses are compared to estimate relative in-vehicle particulate exposures. Two primary consistencies are observed from the data: the CNG buses have average particle count concentrations near the average concentrations for the oxidation-catalyst diesel buses, and the conventional diesel buses have average particle count concentrations approximately three to four times greater than the CNG buses. Particle number concentrations are also noticeably affected by bus idling behavior and ventilation options, such as, window position and air conditioning.     

Monitoring of heavy metal concentrations in home outdoor air using moss bags

One monitoring station is insufficient to characterize the high spatial variation of traffic-related heavy metals within cities. We tested moss bags (Hylocomium splendens), deployed in a dense network, for the monitoring of metals in outdoor air and characterized metals’ long-term spatial distribution and its determinants in Girona, Spain. Mosses were exposed outside 23 homes for two months; NO₂ was monitored for comparison. Metals were not highly correlated with NO₂ and showed higher spatial variation than NO₂. Regression models explained 61-85% of Cu, Cr, Mo, Pb, Sb, Sn, and Zn and 72% of NO₂ variability. Metals were strongly associated with the number of bus lines in the nearest street. Heavy metals are an alternative traffic-marker to NO₂ given their toxicological relevance, stronger association with local traffic and higher spatial variability. Monitoring heavy metals with mosses is appealing, particularly for long-term exposure assessment, as mosses can remain on site many months without maintenance.     

Binational school-based monitoring of traffic-related air pollutants in El Paso, Texas (USA) and Ciudad Juárez, Chihuahua (México)

Paired indoor and outdoor concentrations of fine and coarse particulate matter (PM), PM2.5 reflectance [black carbon(BC)], and nitrogen dioxide (NO₂) were determined for sixteen weeks in 2008 at four elementary schools (two in high and two in low traffic density zones) in a U.S.-Mexico border community to aid a binational health effects study. Strong spatial heterogeneity was observed for all outdoor pollutant concentrations. Concentrations of all pollutants, except coarse PM, were higher in high traffic zones than in the respective low traffic zones. Black carbon and NO₂ appear to be better traffic indicators than fine PM. Indoor air pollution was found to be well associated with outdoor air pollution, although differences existed due to uncontrollable factors involving student activities and building/ventilation configurations. Results of this study indicate substantial spatial variability of pollutants in the region, suggesting that children’s exposures to these pollutants vary based on the location of their school.     

Pragmatic estimation of a spatio-temporal air quality model with irregular monitoring data

Statistical analyses of health effects of air pollution have increasingly used GIS-based covariates for prediction of ambient air quality in “land use” regression models. More recently these spatial regression models have accounted for spatial correlation structure in combining monitoring data with land use covariates. We present a flexible spatio-temporal modeling framework and pragmatic, multi-step estimation procedure that accommodates essentially arbitrary patterns of missing data with respect to an ideally complete space by time matrix of observations on a network of monitoring sites. The methodology incorporates a model for smooth temporal trends with coefficients varying in space according to Partial Least Squares regressions on a large set of geographic covariates and nonstationary modeling of spatio-temporal residuals from these regressions. This work was developed to provide spatial point predictions of PM_2.5 concentrations for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) using irregular monitoring data derived from the AQS regulatory monitoring network and supplemental short-time scale monitoring campaigns conducted to better predict intra-urban variation in air quality. We demonstrate the interpretation and accuracy of this methodology in modeling data from 2000 through 2006 in six U.S. metropolitan areas and establish a basis for likelihood-based estimation.     

The influence of the North-Föhn on tracer organic compounds in ambient air PM10 at a pre-alpine site in Northern Italy

The ambient air in Northern Italy is characterised by relatively high PAH and PM₁₀ concentrations in relation to calm wind and intensive temperature inversions, especially during cold periods. These stagnant conditions are occasionally interrupted by North-Föhn events, which cause a drop in relative humidity and an increase in O₃ levels, indicating the mixing of local and free troposphere air flows. In this study the influence of the North-Föhn on concentrations of tracer organic compounds, including polycyclic aromatic hydrocarbons (PAHs), PM₁₀, O₃ and black carbon (BC) was studied during a North-Föhn event in November 2007. Large fluctuations in the concentration of these compounds, as well as changes in PM₁₀ composition due to daytime and night-time variations of local source emissions were observed. Although these events occur at low frequencies (6-10%) they can for short periods, strongly affect the regional air quality by quickly decreasing the concentrations of these tracer organic compounds.     

Particle concentrations in data centers

Cooling buildings with large airflow rates of outside air when temperatures are favorable is an established energy-saving measure. In data centers, this strategy is not widely used, owing to concerns that it would cause increased indoor levels of particles of outdoor origin, which could damage electronic equipment. However, environmental conditions typical of data centers and the associated potential for equipment failure are not well characterized. This study presents the first published measurements of particle concentrations in operating data centers. Indoor and outdoor particle measurements were taken at eight different sites in northern California for particulate matter 0.3–5.0 μm in diameter. One of the data centers has an energy-efficient design that employs outside air for cooling, while the rest use conventional cooling methods. Ratios of measured particle concentrations in the conventional data centers to the corresponding outside concentrations were significantly lower than those typically found in office or residential buildings. Estimates using a material-balance model match well with empirical results, indicating that the dominant particle sources and losses have been identified. Measurements taken at the more energy-efficient site show nearly an order of magnitude increase in particle concentration when ventilation rates were high. The model indicates that this increase may be even higher when including particles smaller than the monitoring-equipment size limitation. Even with the increases, the measured particle concentrations are still below concentration limits recommended in industry standards.     

Modelling the Removal of Gaseous Pollutants and Particulate Matters from the Atmosphere of a City by Rain: Effect of Cloud Density

In this paper, an original nonlinear mathematical model for the removal of gaseous pollutants and particulate matters from the atmosphere of an industrial city by rain is proposed and analyzed. It is assumed that five interacting phases in the atmosphere of the city exist, i.e., cloud droplets phase, raindrops phase, gaseous pollutants phase, particulate matters phase, and the phase of absorbed gaseous pollutants in raindrops. It is assumed further that these phases undergo nonlinear interactions in the atmosphere, while gaseous pollutant interacts with cloud droplets as well as with raindrops but particulate matters interact only with raindrops. The gravitational settling and reversible reaction processes have also been considered appropriately in the model. By analyzing the model, it is shown that both the gaseous pollutants and particulate matters may be removed from the atmosphere under certain conditions, provided the rates of formation of cloud droplets and raindrops are sufficiently large. It is noted that under unfavorable atmospheric conditions, rain does not occur and pollutants are not removed from the atmosphere.     

颗粒物激光雷达在大气复合污染立体监测中的应用

针对由于局地污染、沙尘输入、外源性输入与局地污染物相互叠加所导致的3种灰霾污染发生过程,分别选取3个典型案例,采用颗粒物激光雷达对污染物的时空分布特征进行解析。研究发现,在局地污染发生时,污染物从地面开始垂直向上扩散,扩散高度约1 km。重度污染过程中,气溶胶的日均垂直消光系数随高度的变化背离指数衰减特征,800 m高度处出现消光系数的极大值层,极大值超过2.5 km-1,800 m以下消光系数近乎常数,约为0.3 km-1。这说明,重污染过程中,有一层较厚重的颗粒物分布,使近地面污染物在垂直方向的扩散能力减弱,形成积累效应,造成大面积空气混浊。当有外源性沙尘输入时,激光雷达能够清晰地监测到污染团输入的全过程。沙团突然出现在高空2~3 km。污染团退偏振度较大,超过0.3。随着沙尘粒子的重力沉降,沙团的轮廓在垂直方向上不断地增大。沙团的输入,导致近地面粗颗粒质量浓度的增加幅度明显大于细颗粒。在第3个案例中,激光雷达清晰地监测到高空1.8~3 km突然出现含有大量球形细颗粒的污染团,同时还发现此污染团与近地面的污染物有不同的演化特征。近地面污染物随时间垂直向上扩散,12:00左右扩散高度超过1.8 km。而高空的污染团逐渐沉降进入边界层内,与近地面扩散的污染物相互混合,共同导致本地的灰霾天气。综上所述,激光雷达可以清晰地捕获污染物的垂直结构特征,对不同的致霾过程进行立体解析,实现对大气复合污染的监测和机理研判。     

广州地区大气能见度与颗粒物关系的初探

采用番禺大气成分站2007—2013年的能见度、颗粒物(PM1、PM2.5、PM10)及番禺气象局站的相对湿度(RH)资料,对颗粒物7年来的变化状况进行了分析。以RH为标准,将能见度和颗粒物数据分为RH≥90%、80%RH90%和RH≤80%3个部分,并以相关系数(R2)为判断标准,分别对其之间的相关性进行了分析。结果表明,PM10、PM2.5、PM1多年日平均值分别为56.6、43.0、38.5μg/m3,颗粒物值旱季高于雨季。当RH≤80%时,颗粒物与能见度的相关性最好,R2大小顺序为:PM10(0.47)PM2.5(0.57)PM1(0.58);当80%RH90%时,颗粒物与能见度的相关性次之,分别为PM10(0.4)PM2.5(0.46)PM1(0.49);当RH≥90%时,颗粒物与能见度的相关性较差。     

扩散管在大气汞分析中的应用

本文叙述一种分离大气中气态汞和颗粒态汞的扩散管采样方法 ,将它与传统的滤膜过滤法测得的结果进行比较。当使用 6 0 0 mm长的扩散管 ,采样流速为 1L· m in-1时 ,它对气态汞的采样效率可达 99%以上