PM10冲击采样器切割头设计参数对切割粒径的影响

本文从颗粒在气流中的受力情况分析入手 ,得到冲击采样器中喷嘴喷出后颗粒的运动轨迹方程以及运动轨迹与采样器切割头设计参数的关系式。分析了PM10空气采样器的切割原理 ,并利用数值计算研究颗粒在不同的流量、喷嘴尺寸及喷嘴与冲击板的距离下的运动轨迹 ,从而得到切割头设计参数对切割粒径的影响     

Influence of sulfur dioxide-related interactions on PM2.5 formation in iron ore sintering

The formation of PM_2.5 (aerosol particulate matter less than 2.5 µm in aerodynamic diameter) in association with SO₂ emission during sintering process has been studied by dividing the whole sintering process into six typical sampling stages. A low-pressure cascade impactor was used to collect PM_2.5 by automatically segregating particulates into six sizes. It was found that strong correlation existed between the emission properties of PM_2.5 and SO₂. Wet mixture layer (overwetted layer and raw mixture layer) had the function to simultaneously capture SO₂ and PM_2.5 during the early sintering stages, and released them back into flue gas mainly in the flue gas temperature-rising period. CaSO₄ crystals constituted the main SO₂-related PM_2.5 during the disappearing process of overwetted layer, which was able to form perfect individual crystals or to form particles with complex chemical compositions. Besides the existence of individual CaSO₄ crystals, mixed crystals of K₂SO₄-CaSO₄ in PM_2.5 were also found during the first half of the temperature-rising period of flue gas. The interaction between fine-grained Ca-based fluxes, potassium vapors, and SO₂ was the potential source of SO₂-related PM_2.5.

Implications: The emission property of PM_2.5 and SO₂ throughout the sintering process exhibited well similarity. This phenomenon tightened the relationship between the formation of PM_2.5 and the emission of SO₂. Through revealing the properties of SO₂-related PM_2.5 during sintering process, the potential interaction between fine-grained Ca-based fluxes, potassium vapors, and SO₂ was found to be the source of SO₂-related PM_2.5. This information can serve as the guidance to develop efficient techniques to control the formation and emission of PM_2.5 in practical sintering plants.     

区域大气环境中PM2．5／PM10空间分布研究

提出了一种利用移动监测技术研究区域大气环境中PM2.5／PM10空间分布的方法,并在2004年12月进行了宁波市全市域PM2.5／PM10空间分布的研究。数据显示：相同路径所代表的地区PM2.5和PM10具有很好的相关性,多数路径上PM2.5与PM10数据的相关系数平方在0．95以上,而不同路径上PM2.5与PM10的比值不同。文中给出了宁波市PM2.5／PM10污染的空间分布图,直观地显示出PM2.5／PM10污染的空间分布情况,突出了污染的重点点位和地区。     

Source apportionment of PM10 and PM2.5 in five Chilean cities using factor analysis

Chile is a fast-growing country with important industrial activities near urban areas. In this study, the mass and elemental concentrations of PM10 and PM2.5 were measured in five major Chilean urban areas. Samples of particles with diameter less than 10 microm (PM10) and 2.5 microm (PM2.5) were collected in 1998 in Iquique (northern Chile), Valparaiso, Vi?a del Mar, Rancagua (central Chile), and Temuco (southern Chile). Both PM10 and PM2.5 annual mean concentrations (PM10: 56.9-77.6 microg/m3; PM2.5: 22.4-42.6 microg/m3) were significantly higher than the corresponding European Union (EU) and U.S. Environmental Protection Agency (EPA) air quality standards. Moreover, the 24-hr PM10 and PM2.5 U.S. standards were exceeded infrequently for some of the cities (Rancagua and Valparaiso). Elements ranging from Mg to Pb were detected in the aerosol samples using X-ray fluorescence (XRF). For each of the five cities, factor analysis (FA) was applied to identify and quantify the sources of PM10 and PM2.5. The agreement between calculated and measured mass and elemental concentrations was excellent in most of the cities. Both natural and anthropogenic sources were resolved for all five cities. Soil and sea were the most important contributors to coarse particles (PM10-PM2.5), whereas their contributions to PM2.5 were negligible. Emissions from Cu smelters and oil refineries (and/or diesel combustion) were identified as important sources of PM2.5, particularly in the industrial cities of Rancagua, Valparaiso, and Vi?a del Mar. Finally, motor vehicles and wood burning were significant sources of both PM2.5 and PM10 in most of the cities (wood burning was not identified in Iquique).     

Study of a winter PM episode in Istanbul using the high resolution WRF/CMAQ modeling system

High winter-time PM₁₀, sulfate, nitrate and ammonium levels in Istanbul were investigated using a high resolution WRF/CMAQ mesoscale model system. A model-ready anthropogenic emission inventory on 2 km spatial resolution was developed for the area and the present study is the first attempt to test these emissions. The results suggested that the system was capable of producing the magnitudes. PM₁₀ levels calculated by the model underestimated the observations with an average of 10 per cent at Bogazici University sampling station, whereas an overestimation of 12 per cent is calculated for all stations. High uncertainties, particularly in traffic and coal combustion, led to over estimations around emission hot spots. Base case results together with the sensitivity studies pointed significant contribution of local sources, pointing to the need of control strategies focusing on primary particulate emissions.     

PM10-PM2.5冲击采样器的研制与开发

在颗粒物研究中,分级采样是一种常用的监测方法,而冲击采样器是颗粒物分级采样的重要仪器.根据斯托克斯数,对PM10-PM2.5冲击采样器设计参数进行了详细分析,并对PM10-PM2.5的捕集效率特征进行了分析.结果表明,PM10-PM2.5冲击采样器具备理想的PM10和PM2.5捕集效率,PM10冲击采样器、PM2.5冲击采样器切割粒径分别为9.94、2.43μm,均在其允许误差范围内.     

Identification of the sources of PM10 in a subway tunnel using positive matrix factorization

The level of particulate matter of less than 10 μm diameter (PM₁₀) at subway platforms can be significantly reduced by installing a platform screen-door system. However, both workers and passengers might be exposed to higher PM₁₀ levels while the cars are within the tunnel because it is a more confined environment. This study determined the PM₁₀ levels in a subway tunnel, and identified the sources of PM₁₀ using elemental analysis and receptor modeling. Forty-four PM₁₀ samples were collected in the tunnel between the Gireum and Mia stations on Line 4 in metropolitan Seoul and analyzed using inductively coupled plasma–atomic emission spectrometry and ion chromatography. The major PM₁₀ sources were identified using positive matrix factorization (PMF). The average PM₁₀ concentration in the tunnels was 200.8 ± 22.0 μg/m³. Elemental analysis indicated that the PM₁₀ consisted of 40.4% inorganic species, 9.1% anions, 4.9% cations, and 45.6% other materials. Iron was the most abundant element, with an average concentration of 72.5 ± 10.4 μg/m³. The PM₁₀ sources characterized by PMF included rail, wheel, and brake wear (59.6%), soil combustion (17.0%), secondary aerosols (10.0%), electric cable wear (8.1%), and soil and road dust (5.4%). Internal sources comprising rail, wheel, brake, and electric cable wear made the greatest contribution to the PM₁₀ (67.7%) in tunnel air.

ImplicationsWith installation of a platform screen door, PM₁₀ levels in subway tunnels were higher than those on platforms. Tunnel PM₁₀ levels exceeded 150 μg/m³ of the Korean standard for subway platform. Elemental analysis of PM₁₀ in a tunnel showed that Fe was the most abundant element. Five PM₁₀ sources in tunnel were identified by positive matrix factorization. Railroad-related sources contributed 68% of PM₁₀ in the subway tunnel.     

Numerical study on adjusting and controlling effect of forest cover on PM10 and O3

A new-coupled air quality numerical modeling system has been developed and applied to the study on the adjusting and controlling effect of forest cover on air quality. The modeling system is composed of Plant Canopy Layer Model (PCLM), Urban Scale Meteorological Model (USMM), and High-Resolution Chemical Model (HRCM). The system was applied to the study on the ecological adjusting and controlling effects on PM₁₀ and O₃ in Jinan City, China. The results show that the forest cover can adjust and control PM₁₀ and O₃ significantly by reducing the concentrations of PM₁₀ while increasing the concentrations of O₃ with the increase of forest cover.     

Prediction of ambient PM10 and toxic metals using artificial neural networks

In this study, an artificial neural network is employed to predict the concentration of ambient respirable particulate matter (PM10) and toxic metals observed in the city of Jaipur, India. A feed-forward network with a back-propagation learning algorithm is used to train the neural network the behavior of the data patterns. The meteorological variables of wind speed, wind direction, relative humidity, temperature, and time are taken as input to the network. The results indicate that the network is able to predict concentrations of PM10 and toxic metals quite accurately.     

Objectives and Design of Central California's 1995 Integrated Monitoring Study of the California Regional PM10/PM2.5 Air Quality Study

ABSTRACT

The 1995 Integrated Monitoring Study (IMS95) is part of the Phase 1 planning efforts for the California Regional PM_10/PM_2.5 Air Quality Study. Thus, the overall objectives of IMS95 are to (1) fill information gaps needed for planning an effective field program later this decade; (2) develop an improved conceptual model for pollution buildup (PM10, PM2.5, and aerosol precursors) in the San Joaquin Valley; (3) develop a uniform air quality, meteorological, and emissions database that can be used to perform initial evaluations of aerosol and fog air quality models; and (4) provide early products that can be used to help with the development of State Implementation Plans for PM_10. Consideration of the new particulate matter standards were also included in the planning and design of IMS95, although they were proposed standards when IMS95 was in the planning process.     

An hourly PM10 diagnosis model for the Bilbao metropolitan area using a linear regression methodology

There is extensive evidence of the negative impacts on health linked to the rise of the regional background of particulate matter (PM) 10 levels. These levels are often increased over urban areas becoming one of the main air pollution concerns. This is the case on the Bilbao metropolitan area, Spain. This study describes a data-driven model to diagnose PM10 levels in Bilbao at hourly intervals. The model is built with a training period of 7-year historical data covering different urban environments (inland, city centre and coastal sites). The explanatory variables are quantitative—log [NO₂], temperature, short-wave incoming radiation, wind speed and direction, specific humidity, hour and vehicle intensity—and qualitative—working days/weekends, season (winter/summer), the hour (from 00 to 23 UTC) and precipitation/no precipitation. Three different linear regression models are compared: simple linear regression; linear regression with interaction terms (INT); and linear regression with interaction terms following the Sawa’s Bayesian Information Criteria (INT-BIC). Each type of model is calculated selecting two different periods: the training (it consists of 6 years) and the testing dataset (it consists of 1 year). The results of each type of model show that the INT-BIC-based model (R ²?=?0.42) is the best. Results were R of 0.65, 0.63 and 0.60 for the city centre, inland and coastal sites, respectively, a level of confidence similar to the state-of-the art methodology. The related error calculated for longer time intervals (monthly or seasonal means) diminished significantly (R of 0.75–0.80 for monthly means and R of 0.80 to 0.98 at seasonally means) with respect to shorter periods.     

Analysis of long-range transport influences on urban PM10 using two-stage atmospheric trajectory clusters

There is evidence that long-range transport of natural and/or anthropogenic particles can have a negative impact on urban air quality. Certain European cities may fail to comply with the currently implemented 24-h PM₁₀ limit value due to the additional impact of remote sources of particles, which are not controllable at local level. For that reason, reliable methodologies identifying long-range transport patterns and quantifying their contribution to urban PM₁₀ levels are required. In this study, a two-stage clustering methodology was developed and applied to back trajectories arriving in three European cities: Athens, Madrid and Birmingham, which experience large, moderate and small numbers of daily PM₁₀ episodes, respectively. The atmospheric trajectories used in this analysis were computed with HYSPLIT model (NOAA) for a 3-year period. The two-stage cluster analysis has the advantage of providing highly disaggregated trajectory clusters, which proved to correspond to significantly different PM₁₀ levels. In the case of Madrid and Birmingham, clusters of trajectories originating from North Africa and continental Europe, respectively, were strongly associated with the highest PM₁₀ levels recorded in selected monitoring stations. In Athens, long-range transport patterns and trans-boundary influences were less evident, which highlighted the more substantial impact of local emission sources. Finally, two simple statistical indexes were proposed for assessing PM₁₀ episodes associated with different clusters of trajectories. This study has established a practical methodology for examining the impact of long-range atmospheric transport on local air quality, without resorting to high resource-demanding source apportionment techniques.     

Quantifying the effect of urban tree planting on concentrations and depositions of PM10 in two UK conurbations

Trees are efficient scavengers of particulate matter and are characterised by higher rates of dry deposition than other land types. To estimate the potential of urban tree planting for the mitigation of urban PM₁₀ concentrations, an atmospheric transport model was used to simulate the transport and deposition of PM₁₀ across two UK conurbations (the West Midlands and Glasgow). Tree planting was simulated by modifying the land cover database, using GIS techniques and field surveys to estimate reasonable planting potentials. The model predicts that increasing total tree cover in West Midlands from 3.7% to 16.5% reduces average primary PM₁₀ concentrations by 10% from 2.3 to 2.1 μg m⁻³ removing 110 ton per year of primary PM₁₀ from the atmosphere. Increasing tree cover of the West Midlands to a theoretical maximum of 54% by planting all available green space would reduce the average PM₁₀ concentration by 26%, removing 200 ton of primary PM₁₀ per year. Similarly, for Glasgow, increasing tree cover from 3.6% to 8% reduces primary PM₁₀ concentrations by 2%, removing 4 ton of primary PM₁₀ per year. Increasing tree cover to 21% would reduce primary PM₁₀ air concentrations by 7%, removing 13 ton of primary PM₁₀ per year.     

Comparison between a personal PM10 sampling head and the tapered element oscillating microbalance (TEOM) system

A new personal PM₁₀ sampling head has been developed by the Institute of Occupational Medicine (IOM), Edinburgh. The purpose of this study was to compare its performance in the field with the accepted fixed-location PM₁₀ sampler, the tapered element oscillating microbalance (TEOM). The comparisons were carried out on three separate occasions during 1997 at each of two city centre locations in the UK. On each occasion two personal IOM PM₁₀ sampling heads were located adjacent to a TEOM monitor and four successive sets of 24-h filter samples were collected. The data was compared with 24-h average TEOM concentrations, calculated as the arithmetic mean of the recorded hourly averages. There was a statistically significant linear relationship between the two types of monitor, although the concentrations from the IOM PM₁₀ samplers were consistently higher than the TEOM data. It is therefore possible to use the regression equations presented in this paper to correct ambient PM₁₀ concentrations measured by either method to equivalent values. Further research is needed to properly understand the reason for the difference between the TEOM and filter samplers.     

PM2.5 and PM10: The influence of sugarcane burning on potential cancer risk

In Brazil, sugarcane fields are often burned to facilitate manual harvesting, and this burning causes environmental pollution from the large amounts of soot released into the atmosphere. This material contains numerous organic compounds such as PAHs. In this study, the concentrations of PAHs in two particulate-matter fractions (PM_2.5 and PM₁₀) in the city of Araraquara (SE Brazil, with around 200,000 inhabitants and surrounded by sugarcane plantations) were determined during the sugarcane harvest (HV) and non-harvest (NHV) seasons in 2008 and 2009. The sampling strategy included four campaigns, with 60 samples in the NHV season and 220 samples in the HV season. The PM_2.5 and PM₁₀ fractions were collected using a dichotomous sampler (10 L min^?1, 24 h) with Teflon? filters. The filter sets were extracted (ultrasonic bath with hexane/acetone (1:1 v/v)) and analyzed by HPLC/Fluorescence. The median concentration for total PAHs (PM_2.5 in 2009) was 0.99 ng m^?3 (NHV) and 3.3 ng m^?3 (HV). In the HV season, the total concentration of carcinogenic PAHs (benz(a)anthracene, benzo(b)fluoranthene, benzo(k)fluoranthene, and benzo(a)pyrene) was 5 times higher than in the NHV season. B(a)P median concentrations were 0.017 ng m^?3 and 0.12 ng m^?3 for the NHV and HV seasons, respectively. The potential cancer risk associated with exposure through inhalation of these compounds was estimated based on the benzo[a]pyrene toxic equivalence (BaP_eq), where the overall toxicity of a PAH mixture is defined by the concentration of each compound multiplied by its relative toxic equivalence factor (TEF). BaP_eq median (2008 and 2009 years) ranged between 0.65 and 1.0 ng m^?3 and 1.2–1.4 ng m^?3 for the NHV and HV seasons, respectively. Considering that the maximum permissible BaP_eq in ambient air is 1 ng m^?3, related to the increased carcinogenic risk, our data suggest that the level of human exposure to PAHs in cities surrounded by sugarcane crops where the burning process is used is cause for concern.     

Influence of tobacco smoke on carcinogenic PAH composition in indoor PM10 and PM2.5

Because of the mutagenic and/or carcinogenic properties, Polycyclic Aromatic Hydrocarbons (PAH), have a direct impact on human population. Consequently, there is a widespread interest in analysing and evaluating the exposure to PAH in different indoor environments, influenced by different emission sources. The information on indoor PAH is still limited, mainly in terms of PAH distribution in indoor particles of different sizes; thus, this study evaluated the influence of tobacco smoke on PM₁₀ and PM_2.5 characteristics, namely on their PAH compositions, with further aim to understand the negative impact of tobacco smoke on human health. Samples were collected at one site influenced by tobacco smoke and at one reference (non-smoking) site using low-volume samplers; the analyses of 17 PAH were performed by Microwave Assisted Extraction combined with Liquid Chromatography (MAE–LC). At the site influenced by tobacco smoke PM concentrations were higher 650% for PM₁₀, and 720% for PM_2.5. When influenced by smoking, 4 ring PAH (fluoranthene, pyrene, and chrysene) were the most abundant PAH, with concentrations 4600–21 000% and 5100–20 800% higher than at the reference site for PM₁₀ and PM_2.5, respectively, accounting for 49% of total PAH (Σ_PAH). Higher molecular weight PAH (5–6 rings) reached concentrations 300–1300% and 140–1700% higher for PM₁₀ and PM_2.5, respectively, at the site influenced by tobacco smoke. Considering 9 carcinogenic PAH this increase was 780% and 760% in PM₁₀ and PM_2.5, respectively, indicating the strong potential risk for human health. As different composition profiles of PAH in indoor PM were obtained for reference and smoking sites, those 9 carcinogens represented at the reference site 84% and 86% of Σ_PAH in PM₁₀ and PM_2.5, respectively, and at the smoking site 56% and 55% of Σ_PAH in PM₁₀ and PM_2.5, respectively. All PAH (including the carcinogenic ones) were mainly present in fine particles, which corresponds to a strong risk for cardiopulmonary disease and lung cancer; thus, these conclusions are relevant for the development of strategies to protect public health.     

Elemental characterization of PM10, PM2.5 and PM1 in the town of Genoa (Italy)

The particulate matter (PM) concentration and composition, the PM10, PM2.5, PM1 fractions, were studied in the urban area of Genoa, a coastal town in the northwest of Italy. Two instruments, the continuous monitor TEOM and the sequential sampler PARTISOL, were operated almost continuously on the same site from July 2001 to September 2004. Samples collected by PARTISOL were weighted to obtain PM concentration and then analysed by PIXE (particle induced X-ray emission) and by ED-XRF (energy dispersion X-ray fluorescence), obtaining concentrations for elements from Na to Pb. Some of the filters used in the TEOM microbalance were analysed by ED-XRF to calculate Pb concentration values averaged over 7-30 d periods.     

Temporal Variations of PM2.5, PM10, and Gaseous Precursors during the 1995 Integrated Monitoring Study in Central California

ABSTRACT

The spatial and temporal distributions of particle mass and its chemical constituents are essential for understanding the source-receptor relationships as well as the chemical, physical, and meteorological processes that result in elevated particulate concentrations in California’s San Joaquin Valley (SJV). Fine particulate matter ₍PM_2.5), coarse particulate matter (PM₁₀), and aerosol precursor gases were sampled on a 3-hr time base at two urban (Bakersfield and Fresno) and two non-urban (Kern Wildlife Refuge and Chowchilla) core sites in the SJV during the winter of 1995–1996.

Day-to-day variations of PM_2.5 and PM₁₀ and their chemical constituents were influenced by the synoptic-scale meteorology and were coherent among the four core sites. Under non-rainy conditions, similar diurnal variations of PM_2.5 and coarse aerosol were found at the two urban sites, with concentrations peaking during the nighttime hours. Conversely, PM_2.5 and coarse aerosol peaked during the morning and afternoon hours at the two non-urban sites. Under rainy and foggy conditions, these diurnal patterns were absent or greatly suppressed.

In the urban areas, elevated concentrations of primary pollutants (e.g., organic and elemental carbons) during the late afternoon and nighttime hours reflected the impact from residential wood combustion and motor vehicle exhaust. During the daytime, these concentrations decreased as the mixed layer deepened. Increases of secondary nitrate and sulfate concentrations were found during the daylight hours as a result of photochemical reactions. At the non-urban sites, the same increases in secondary aerosol concentrations occurred during the daylight hours but with a discernable lag time. Concentrations of the primary pollutants also increased at the non-urban sites during the daytime. These observations are attributed to mixing aloft of primary aerosols and secondary precursor gases in urban areas followed by rapid transport aloft to non-urban areas coupled with photochemical conversion.     

Patterns and concentrations of PM10 in a mountainous basin region

In this study, continuous data of PM10 (particles with aerodynamic diameter < 10 microns) concentration measurements for a 4-yr period were analyzed. These measurements have been carried out in the Eordea Basin, an industrial area in the northwestern mountainous region of Greece. The annual, monthly, and diurnal patterns are presented and investigated regarding the prevailing meteorological conditions and atmospheric processes that affect the ambient concentrations of PM10. The effect of wind on controlling PM10 concentration is also discussed. Based on the data analysis, an attempt is made to provide useful information about air quality levels, taking into account U.S. Environmental Protection Agency air quality standards.