Identification of Fine Particle Sources in Mid-Atlantic US Area

The U.S. Environmental Protection Agency (EPA) designated 20 urban areas including major cities located in mid-Atlantic US area as being in non-attainment of the new national ambient air quality standards for PM_2.5 (particulate matter ≤2.5 μm in aerodynamic diameter). To support the development of effective State Implementation Plans for PM_2.5 in the non-attainment area, 24-h integrated Speciation Trends Networks data collected in the mid-Atlantic US urban area were analyzed through the application of the positive matrix factorization (PMF). A total of 117 to 235 samples and 27 to 29 chemical species collected at the four monitoring sites between 2001 and 2003 were analyzed and six to nine sources were identified. Secondary particles provided the highest contributions to PM_2.5 mass concentrations (38–50% for secondary sulfate; 9–18% for secondary nitrate). Potential source contribution function analyses show the potential source areas and pathways of secondary particles contributing to this region, especially the regional influences of the biogenic as well as anthropogenic secondary particles. Motor vehicle emissions contributed 21–33% to the PM_2.5 mass concentration. In four sites in southern New Jersey and Delaware, gasoline vehicle and diesel emissions were tentatively separated by different abundances of organic and elemental carbons. The compositional profiles for gasoline vehicle and diesel emissions are similar across this area. In addition, other combustion sources, aged sea salt, and intercontinental dust storms were identified.     

大型自然通风奶牛舍空气颗粒物浓度监测方法中测点数和位置优化

对奶牛舍颗粒物浓度和分布进行实时连续监测,是评估其环境风险和制定科学减排措施的前提。随着大型奶牛舍的快速发展,对尽可能少且科学地布置测点数量和位置并能够对舍内颗粒物浓度进行精准监测,提出了新的挑战。为探究测点优化布置方案,该研究基于物联网技术在大型自然通风奶牛舍内3个相邻饲养区域布置17个采样点,对总悬浮颗粒物（total suspended particle, TSP）和细颗粒物（PM_2.5）浓度进行了连续6个月监测,得到舍内浓度平均值（视为“真值”）;利用系统聚类和误差分析方法得到优化的测点方案,并将其颗粒物浓度结果与6种传统测点方案进行对比,以确定最优的测点数量和位置方案。结果表明,舍内3个饲养区域内颗粒物浓度分布均匀,PM_2.5浓度在不同采样高度上无统计差异（P>0.05）,而TSP浓度在屋顶通风口下方（9.0 m）明显低于1.5和2.5 m高度（P<0.05）。与真值相比,优化测点方案的TSP和PM_2.5浓度监测误差绝对值之和分别为6.4%～22.6%和4.7%～14.2%,均低于传统测点方案。综合考虑优化方案的科学性和传统方案的易操作性,确定最优测点方案为：在奶牛舍中央屋顶通风口下方1.0～2.0 m处布置1个测点,在奶牛卧床上方2.5 m高度布置2个测点,上述3个测点按奶牛舍斜对角线进行布置;另外,分别在挤奶通道、饲喂通道、清粪通道上方2.5 m高度处各布置1个测点;共计6个测点。该优化测点方案可满足监测准确性和易操作性要求。     

Source Apportionment of the Atmospheric Aerosol in Lahore, Pakistan

Samples of airborne particulate matter (PM_2.5) were collected at a site in Lahore, Pakistan from November 2005 to January 2006. A total of 129 samples were collected using an Andersen Reference Ambient Air Sampler 2.5-400 sampler and analyzed for major ions, trace metals, and organic and elemental carbon concentrations. The data set was then analyzed by positive matrix factorization (PMF) to identify the possible sources of the atmospheric PM collected in this urban area. Six factors reproduced the PM_2.5 sample compositions with meaningful physical interpretation of the resolved factors. The sources included secondary PM, diesel emissions, biomass burning, coal combustion, two-stroke vehicle exhaust, and industrial sources. Diesel and two-stroke vehicles contributed about 36%, biomass burning about 15%, and coal combustion sources around 13% of the PM_2.5 mass. Nearly two thirds of the PM_2.5 mass is carbonaceous material. Secondary particles contributed about 30% of PM_2.5 mass. The conditional probability function (CPF) was then used to help identify likely locations of the sources present in this area. CPF analysis point to the east and northeast, which are directions of urban and industrial areas located across the border near Amritsar, India as the most probable source for high PM_2.5 concentration from diesel and two-stroke vehicles exhaust in Lahore. Analysis of those days within three different ranges of PM_2.5 concentration shows that most of the measured high PM_2.5 mass concentrations were driven by diesel and two-stroke vehicle emissions including the associated primary sulfate. The use of the potential source contribution function (PSCF) to find the source locations of regionally transported particles is inapplicable in situations when high PM_2.5 concentrations are dominated by local sources and local meteorology.     

A Study of PM2.5 and PM2.5-Associated Polycyclic Aromatic Hydrocarbons at an Urban Site in the Po Valley (Bologna, Italy)

PM_2.5 and PAHs bound to PM_2.5 were investigated in downtown Bologna, from January to June 2003, in order to determine the burden of the fine fraction in the aerosol of a typical urban environment of the Po Valley, a critical area in Northern Italy in terms of atmospheric pollution. The sampling campaign was divided into three parts: a winter sub-campaign, an intermediate campaign where PM_2.5 and PM₁₀ were simultaneously sampled and which identified PM_2.5 as the major component of PM₁₀, and a summer sub-campaign. Critical concentrations of both PM_2.5 and PAHs were observed in winter time; for example, in January 2003 the mean value for the 24-h average PM_2.5 concentration was 58 μg/m³, much higher than the annual arithmetic mean of 15 μg/m³ established by the US ambient air quality standard (NAAQS). Correspondingly, the mean value for benzo[a]pyrene (BAP) in PM_2.5 was 1.79 ng/m³, again higher than the annual mean of 1 ng/m³, required by European regulations for BAP in PM₁₀. In summer time the BAP concentration considerably decreases to 0.10 ng/m³ as the likely effect of photolysis and dilution on a higher boundary layer; PM_2.5 decreases too, but the mean concentration (22 μg/m³) is still higher than the NAAQS value. Further analysis included TEM microscopy of collected particles and correlations between PM_2.5, PAHs and gases (benzene, O₃, CO, NO₂, SO₂). All these observations identified on-road mobile sources as the main source of emissions and, in general, of the poor air quality level in the city of Bologna.     

Measuring air particulate matter in large urban areas for health effect assessment

This study deals with Particle Matter (PM) levels in the metropolitan area of Lisbon and shows that EU directive is exceeded in a systematic way, mainly due to the inner city traffic. Results show that it is important to develop an epidemiological study in Lisbon to find a possible association between PM levels, sources and morbidity. Some important issues related with a monitor's representation of regional, sub-regional, and local air pollution exposures to the population in the metropolitan area are highlighted. PM_2.5 and PM₁₀ total mass concentration measured in several places located in both centre of Lisbon and the outskirts are quite well correlated, mainly considering that two measuring methodologies (automatic and gravimetric) were used and areas with different classifications (urban and suburban) were analysed. However, the results imply that a source-oriented evaluation of PM health effects needs to take into account the uncertainty associated with spatial representativity of the species measured at a single sampling station. Temporal correlation across sampling stations, within relatively short separation distances, varied considerably for some important elements (Zn, Sb, Cu, As and Br), indicating that the precision of population exposure estimates for specific elements can vary depending on the species.     

PM10 and PM2.5 Levels in the Eastern Mediterranean (Akrotiri Research Station, Crete, Greece)

Particulate matter measurements (PM₁₀, PM_2.5) using a beta radiation attenuation monitor were performed at the Akrotiri research station (May 2003–March 2006) on the island of Crete (Greece). The mean PM₁₀ concentration during the measuring period (05/02/03–03/09/04) was equal to 35.0?±?17.7 μg/m³ whereas the mean PM_2.5 concentration (03/10/04–04/02/06) was equal to 25.4?±?16.5 μg/m³. The aerosol concentration at the Akrotiri station shows a large variability during the year. Mean concentrations of particulate matter undergo a seasonal change characterised by higher concentrations during summer [PM₁₀, 38.7?±?10.8 μg/m³ (2003); PM_2.5, 27.9?±?8.7 μg/m³ (2004) and 27.8?±?9.7 μg/m³ (2005)] and lower concentrations during winter [PM₁₀, 28.7?±?22.5 μg/m³ (2003/2004); PM_2.5, 21.0?±?13.0 μg/m³ (2004/2005) and 21.4?±?21.9 μg/m³ (2005/2006)]. Comparative measurements of the PM₁₀ concentration between the beta radiation attenuation monitor, a standardized low volume gravimetric reference sampler and a low volume sequential particulate sampler showed that PM₁₀ concentrations measured by the beta radiation attenuation monitor were higher than values given by the gravimetric samplers (mean ratio 1.17?±?0.11 and 1.21?±?0.08, respectively). Statistical and back trajectory analysis showed that elevated PM concentrations (PM₁₀, 93.8?±?49.1 μg/m³; PM_2.5: 102.9?±?59.9 μg/m³) are associated to desert dust events. In addition regional transport contributes significantly to the aerosol concentration levels whereas low aerosol concentrations were observed during storm episodes.     

Concentration and Sources of PM10 and its Constituents in Alsasua, Spain

Ambient concentrations of PM₁₀ were measured every fifteen minutes from November 2002 to October 2003 at Alsasua (Northern Spain) using a laser particle counter. A high volume sampler was also used to collect 24-h integrated PM₁₀ samples at a frequency of three running days per week (i.e. three consecutive PM₁₀ samples followed by five days without sampling) for gravimetric determination of PM₁₀ mass concentrations followed by chemical analysis of its chemical components. The annual mean PM₁₀ concentration obtained using the laser particle counter with gravimetric correction was 22.7 μg m^?3 (365 days), while the mean for the gravimetric samples was 29.5 μg m^?3 (134 days). A total of 94 integrated PM₁₀ samples were analyzed for 60 chemical species using a combination of inductively coupled plasma spectrometry (ICP) and ion chromatography (IC). The concentrations of the main PM₁₀ components were found to be generally in agreement with the values reported for other Spanish cities. Bilinear Positive Matrix Factorization (PMF2) was used to study the sources of PM₁₀ and its constituents. Six main sources of PM₁₀ were identified (average contribution to total PM₁₀ mass in parentheses): crustal material (35%), secondary sulfate (21%), secondary nitrate (14%), motor vehicles (12%), sea-salt aerosol (12%) and metallurgical industries (3%).     

Influence of the 23 October 2002 Dust Storm on the Air Quality of Four Australian Cities

Widespread drought and record maximum temperatures in eastern Australia produced a large dust storm on 23 October, 2002 which traversed a large proportion of eastern Australia and engulfed communities along a 2000 km stretch of coastline from south of Sydney (NSW) to north of Mackay (Queensland). This event provided an opportunity for a study of the impacts of rural dust upon the air quality of four Australian cities. A simple model is used to predict dust concentrations, dust deposition rates and particle size characteristics of the airborne dust in the cities. The total dust load of the plume was 3.35 to 4.85 million tones, and assuming a (conservative) plume height of 1500 m, 62–90% of this dust load was deposited in-transit to the coast. It is conservatively estimated that 3.5, 12.0, 2.1 and 1.7 kilotonnes of dust were deposited during the event in Sydney, Brisbane, Gladstone and Mackay, respectively. In the South East Queensland region, this deposition is equivalent to 40% of the total annual TSP emissions for the region. The event increased TSP, PM₁₀ and PM_2.5 concentrations and reduced the visibility beyond the health and amenity guidelines in the four cities. For example, the 24-h average PM₁₀ concentrations in Brisbane and Mackay, were 161 and 475 μg m^?3 respectively, compared with the Australian national ambient air quality standard of 50 μg m^?3. The 24-h average PM_2.5 concentration in Brisbane was 42 μg m^?3, compared with the national advisory standard of 25 μg m^?3. These rural dusts significantly increased PM₁₀/TSP ratios and decreased PM_2.5/PM₁₀ ratios, indicating that most of the particles were between PM_2.5 and PM₁₀.     

Influence of Saharan Dust Transport Events on PM2.5 Concentrations and Composition over Athens

The evaluation of the contribution of natural sources to PM₁₀ and PM_2.5 concentrations is a priority especially for the countries of European south strongly influenced by Saharan dust transport events. Daily PM_2.5 concentrations and composition were monitored at an urban site at 14 m above ground level, at the National Technical University of Athens campus from February to December 2010. The typical dust constituents Si, Al, Fe, K, Ca, Mg, and Ti were determined by wavelength dispersive X-ray fluorescence spectrometry (WDXRF). Sulfur, a tracer of anthropogenic origin and major constituent of PM_2.5, was determined by both WDXRF and ionic chromatography. The contribution of dust and sulfates in PM_2.5 was calculated from the analytical determinations. An annual mean of 20 μg/m³ was calculated from the mean daily PM_2.5 concentrations data. Twenty-two per cent of daily concentrations of PM_2.5 reached or exceeded the EU annual target concentration of 25 μg/m³. The exceedances occurred during 13 short periods of 1–4 days. Back-trajectory analysis was performed for these periods in order to identify the air masses origin. From these periods, ten periods were associated to Saharan dust transport events. The most intense dust transport event occurred between February 17th and 20th and was responsible for the highest recorded PM_2.5 concentration of 100 μg/m³ where the dust contribution in PM_2.5 reached 96 %. The other dust transport events were less intense and corresponded to less pronounced enhancements of PM_2.5 concentrations, and their contribution ranged from 15 to 39 % in PM_2.5 concentrations. Air masses originated from northwest Africa while the influence of central Sahara was quite smaller.     

Diurnal Characteristics of Suspended Particulate Matter and PM<Subscript>2.5</Subscript> in the Urban and Suburban Atmosphere of the Kanto Plain,Japan

Suspended particulate matter (SPM) and PM_2.5 in the urban and suburban atmosphere of the Kanto Plain of Japan, which includes the Tokyo metropolitan area, during the period 22–26 July 2002 were characterized. Samples of SPM and PM_2.5 were collected by low-volume samplers at 6-h intervals at Suginami, Saitama, and Kisai. At all the sites, the major components of SPM and PM_2.5 were organic carbon (OC), elemental carbon (EC), and sulfate. The ion balance, the size distributions of the ionic species, and the high correlation between SO₄ ^2? and NH₄ ⁺ indicated that the main chemical form of sulfate was (NH₄)₂SO₄. The OC/EC ratios were larger in the daytime than in the nighttime. The correlation coefficients of OC, OC/EC, and SO₄ ^2? with ozone concentrations at inland sites (Saitama, Kisai) were higher than those at the coastal site (Suginami). Bound water and hydrogen and oxygen atoms associated with OC, the amounts of which were estimated with a mass closure model, contributed substantially to the total particle mass. The chemical characteristics of the particles indicated that two mechanisms led to high concentrations of SPM and PM_2.5: (i) an active photochemical process produced high concentrations of OC and sulfate, leading to a high concentration of (NH₄)₂SO₄ in the particles and to production of secondary organic aerosols; (ii) stable meteorological conditions resulted in accumulation of primary particles, mainly emitted from vehicle exhaust, resulting in high concentrations of OC and EC.     

Effects of biochar and poultry manure on soil properties,growth, yield and quality of cocoyam (Xanthosoma sagittifolium Schott) grown in sandy soil

ABSTRACT

Field experiments were conducted during the 2017 and 2018 cropping seasons, to evaluate the effects of biochar (B) and poultry manure (PM) on soil physical and chemical properties, leaf nutrient concentrations, growth, mineral composition and corm and cormel yield of cocoyam. The experiment each year consisted of 4 × 2 factorial combinations of B (0, 10, 20 and 30 t ha^?1) and PM (0 and 7.5 t ha^?1). Results of the study indicated that in both years, the application of B and PM alone, and in combination, improved soil physical and chemical properties, leaf nutrient concentrations, growth, mineral composition and corm and cormel yield of cocoyam. There was a significant interaction effect of B and PM (B x PM) which was adduced to the ability of the B to increase PM-use efficiency and promote better use of the nutrients in the PM. It was found that combination of 30 t ha^?1 B and 7.5 t ha^?1 PM (B₃₀+ PM_7.5) gave the highest corm and cormel yield of cocoyam compared with other treatments. The combination of 30 t ha^?1 B and 7.5 t ha^?1 PM (B₃₀+ PM_7.5) exhibited the highest impact and is therefore recommended for soil sustainability and cocoyam productivity on sandy soil.     

Evaluation of Spatial Variability of PM10 Concentrations in London

This study aims to apply principal component analysis (PCA) to identify monitoring sites with similar variations of PM₁₀ concentrations in the London Air Quality Monitoring Network. This statistical methodology was applied to hourly average concentrations measured at 27 monitoring sites during the period from January 2000 to December 2009. The monitoring sites were selected according their efficiency in the study period (greater than 75% for each year). It was observed that the hourly average PM₁₀ concentrations were decreasing along the selected period at almost all monitoring sites. PCA was performed for each year, selecting the number of principal components (PCs) that had at least 95% of the original data variance. Analysing the frequency with which each pair of monitoring sites gave a significant contribution to the same PC, nine city areas with specific PM₁₀ behaviour were identified. Thus, monitoring sites with redundant measurements during the studied period were identified, being possible to remove them to decrease the costs relative to their maintenance or replace them to increase the monitored area.     

A Morphometric and Compositional Approach to the Study of Ambient Aerosol in a Medium Industrial Town of Italy

Morphometric and compositional studies have been performed on both PM_10–2.5 and PM_2.5 aerosol collected in the city of Prato, Italy. Chemical analysis has been carried out using PIXE technique and factor analysis was applied for the source apportionment process. Industrial emissions, vehicular traffic as well as crustal dust and marine aerosol were the sources identified. SEM-EDS analysis has been employed to individually characterize particles collected during a week of the sampling campaign. The morphometric study, performed on 43,671 particles, revealed that, for both the fine and coarse fraction, about 2/3 of particles display a high roundness coefficient, 1/3 of them a medium value, while only a small number of particles (from silicates and organics) exhibits a low roundness coefficient. Similarly, particles with small surface area represent the greater portion in both fractions. Particles classified as organics, metals and oxides, chlorides, carbonates, phosphates, sulphates and silicates have been detected in the PM_10–2.5 while in the PM_2.5 chlorides and phosphates are lacking. Silicates are about the same percentage, by concentration number, in the coarse and fine fraction (20.7% and 20.5% respectively) showing that this material, at least one fifth of the total PM, might be the result of crustal erosion and anthropic activities. The purpose of this work has been that of providing a contribution to the study of particulate matter and took an effort for relating morphometric and compositional features of urban aerosol collected in a medium size industrial city.     

Human Health Impact of Exposure to Airborne Particulate Matter in Pearl River Delta, China

To evaluate the potential public health impact of exposure to airborne particulate matter, concentrations of PM₁₀ and PM_2.5 were measured at 16 monitoring stations in Pearl River Delta. Epidemiological studies were collected, and meta-analysis method was used to get the exposure-response functions for health effects on mortality of residents in China. Chinese studies reported somewhat lower exposure-response coefficients as compared with studies abroad. Both Poisson model and life-table approach were used to estimate the health effects including acute effects and chronic effects. For short-term exposure, 2,700 (95% confidence interval (CI), 2,200?C3,400) premature deaths would be prevented annually if PM₁₀ daily concentrations reduced to below World Health Organization (WHO) guideline value. Much more benefits would be gained for long-term exposure. The annual avoidable deaths would be 42,000 (95% CI, 28,000?C55,000) and 40,000 (95% CI, 23,000?C54,000) for PM₁₀ and PM_2.5, respectively, if the particulate matter annual concentrations were reduced to below WHO guideline values. And the average lifespan of residents would prolong 2.57?years for PM₁₀ and 2.38?years for PM_2.5 if reducing the PM annual concentrations. The benefits varied greatly in different areas and different manage strategies should be carried out to protect human health effectively.     

Monitoring of Submicron Particulate Matter Concentrations in the Air of Turin City, Italy. Influence of Traffic-limitations

Several studies have shown the association between ambient particulate matter (PM) and adverse health effects, thus highlighting the need to limit the anthropogenic sources of PM, especially motor vehicle emissions. PM exposure is commonly monitored as mass concentration of PM10 or PM2.5, although increasing toxicity with decreasing aerodynamic diameter has been reported. In the present study an analysis was performed of the concentration and size distribution of airborne PM fractions collected at street level in the city center of Turin, Italy, to verify the usefulness of “ecological” days with traffic limitations. PM levels were determined daily at five different outdoor sites, from Thursday to Tuesday for 7 weeks (five with “ecological” Sunday, two with normal traffic density). Air sampling was performed using a six-channel laser particle counter to determine the number of particles (n°/l) in six size ranges between 0.3 and 10 μm. Climatic conditions and indoor PM levels were also monitored. The PM size distribution was constant for all the samples tested, with the 90% of the particles smaller than 0.5 μm, suggesting that measurements for count are needed in addition to the traditional ones based on the mass. The total number of particles was highly variable comparing days or weeks of monitoring, but much less among the sites of air sampling. The restriction of motor vehicle circulation has not determined any significant effect on PM levels and, in the winter period, PM0.5 peak concentrations were measured also on the ecological days.     

GIS-Based Emission Inventory, Dispersion Modeling, and Assessment for Source Contributions of Particulate Matter in an Urban Environment

The Industrial Source Complex Short Term (ISCST3) model was used to discern the sources responsible for high PM₁₀ levels in Kanpur City, a typical urban area in the Ganga basin, India. A systematic geographic information system-based emission inventory was developed for PM₁₀ in each of 85 grids of 2?×?2 km. The total emission of PM₁₀ was estimated at 11 t day^?1 with an overall breakup as follows: (a) industrial point sources, 2.9 t day^?1 (26%); (b) vehicles, 2.3 t day^?1 (21%); (c) domestic fuel burning, 2.1 t day^?1 (19%); (d) paved and unpaved road dust, 1.6 t day^?1 (15%); and the rest as other sources. To validate the ISCST3 model and to assess air-quality status, sampling was done in summer and winter at seven sampling sites for over 85 days; PM₁₀ levels were very high (89?C632 ??g m^?3). The results show that the model-predicted concentrations are in good agreement with observed values, and the model performance was found satisfactory. The validated model was run for each source on each day of sampling. The overall source contribution to ambient air pollution was as follows: vehicular traffic (16%), domestic fuel uses (16%), paved and unpaved road dust (14%), and industries (7%). Interestingly, the largest point source (coal-based power plant) did not contribute significantly to ambient air pollution. The reason might be due to release of pollutant at high stack height. The ISCST3 model was shown to produce source apportionment results like receptor modeling that could generate source apportionment results at any desired time and space resolution.     

A Comparison of Trace Gases and Particulate Matter over Beijing (China) and Delhi (India)

Air pollution represents a significant fraction of the total mortality estimated by the World Health Organization (WHO) global burden of disease projec?t (GBD). The present paper discusses the characteristics of trace gases (O₃, NO, NO₂, and CO) and particulate matter (PM₁₀ and PM_2.5) in two Asian megacities, Delhi (India) and Beijing (China). A continuous measurement of trace gases and particulate matter are considered from 12 measuring sites in Beijing and 8 sites in Delhi. Over Beijing, the annual average of PM_2.5, PM₁₀, O₃, NO₂, and CO is, respectively, 85.3, 112.8, 58.7, and 53.4 μg/m³ and 1.4 mg/m³, and, respectively, over Delhi 146.5, 264.3, 24.7,and 19.8 μg/m³ and 1.73 mg/m³. From the spatial variations of pollutants, the concentrations of particulate matter and trace gases are observed to be much higher in the urban areas compared to the suburban areas. The higher average concentrations of PM₁₀ and PM_2.5 over Delhi and Beijing are observed during winter season compared with other seasons. The maximum diurnal variation of PM₁₀ concentration is observed during winter season over Beijing and Delhi. The comparison of trace gases shows that the O₃ concentrations during daytime are obviously higher compared with nighttime, and the highest diurnal variation of O₃ is observed during summer. The concentrations of CO are highest during winter season, and higher concentrations are observed during nighttime compared to daytime. The O₃ and CO show negative correlation over Beijing and Delhi. The negative correlation between O₃ and NO₂ is merely observed over Beijing, while CO and NO₂ concentrations, in contrast, show positive correlation over Beijing.     

Mineralogy of Inhalable Particulate Matter (PM10) in the Atmosphere of Beijing, China

The study of mineral components in respirable particles (particulate matter with diameter less than 10 μm, PM₁₀) in ambient air is important in understanding and improving air quality. In this study, PM₁₀ samples were collected in various areas around Beijing during 2002～2003, including an urban setting, a satellite city and a rural area. The mineralogical composition of these PM₁₀ samples was studied by X-ray diffraction (XRD), environmental scanning electron microscopy / and energy-dispersive X-ray analyzer (ESEM/EDX). The results indicated that mineral composition of PM₁₀ in different seasons and in different region varied significantly. Mineral mass concentration in Beijing PM₁₀ reached the highest percentage in the spring and fell to the lowest level in the autumn. The minerals in the spring PM₁₀ were dominated by clay minerals and quartz, followed by plagioclase, K-feldspar, calcite, dolomite, hematite, pyrite, magnesite, gypsum and laumontite as well as some unidentified materials. Fewer mineral types were collected in summer, however some new components, including K(NH₄)Ca(SO4)₂·H₂O, NH₄Cl and As₂O₃·SO₃ were noted to be present, suggesting that atmospheric chemical reaction in Beijing air were more active in summer than in other seasons. Mineral components in Beijing urban air were at a higher percentage with fewer phases than that in satellite city air. In conclusion, there was considerable variation in mineral components in PM₁₀ samples collected in different seasons and areas, which reflects the related air quality of sampling areas.     

Association of IL-6 with PM<Subscript>2.5</Subscript> Components: Importance of Characterizing Filter-Based PM<Subscript>2.5</Subscript> Following Extraction

Filter-based toxicology studies are conducted to establish the biological plausibility of the well-established health impacts associated with fine particulate matter (PM_2.5) exposure. Ambient PM_2.5 collected on filters is extracted into solution for toxicology applications, but frequently, characterization is nonexistent or only performed on filter-based PM_2.5, without consideration of compositional differences that occur during the extraction processes. To date, the impact of making associations to measured components in ambient instead of extracted PM_2.5 has not been investigated. Filter-based PM_2.5 was collected at locations (n?=?5) and detailed characterization of both ambient and extracted PM_2.5 was performed. Alveolar macrophages (AMJ2-C11) were exposed (3, 24, and 48 h) to PM_2.5 and the pro-inflammatory cytokine interleukin (IL)-6 was measured. IL-6 release differed significantly between PM_2.5 collected from different locations; surprisingly, IL-6 release was highest following treatment with PM_2.5 from the lowest ambient concentration location. IL-6 was negatively correlated with the sum of ambient metals analyzed, as well as with concentrations of specific constituents which have been previously associated with respiratory health effects. However, positive correlations of IL-6 with extracted concentrations indicated that the negative associations between IL-6 and ambient concentrations do not accurately represent the relationship between inflammation and PM_2.5 exposure. Additionally, seven organic compounds had significant associations with IL-6 release when considering ambient concentrations, but they were not detected in the extracted solution. Basing inflammatory associations on ambient concentrations that are not necessarily representative of in vitro exposures creates misleading results; this study highlights the importance of characterizing extraction solutions to conduct accurate health impact research.     

辽宁西北部主要绿化树种对空气颗粒物滞留能力研究

采用洗脱法测定了辽西北地区阜新市15种常见绿化树种单位叶面积滞留粗颗粒物(TSP)及细颗粒物(PM_(2.5))的质量,分析比较了15种树种叶片去除TSP和PM_(2.5)能力以及随着空间变化的规律。结果表明:(1)不同树种单位叶面积TSP和PM_(2.5)滞留量均存在显著差异,变化范围分别为3.68~5.94g/m~2和0.47~0.92g/m~2,树种间滞留能力的差值可达2倍左右。(2)在同一个功能区不同树种滞留TSP和PM_(2.5)的差异由树冠高度(绿篱灌木乔木)和叶表面粗糙度(叶表面沟槽宽度的不同可能是沟槽宽度过宽和过窄均不利于叶片捕集颗粒物,且颗粒物滞留量随沟槽深度增加而增大)以及叶片比叶重(比叶重大的滞尘量大)等所引起。(3)在不同功能区同一树种单位叶面积滞留TSP量的排序为工业区商业交通区露天矿区清洁区,而PM_(2.5)滞留量则无明显差异。乔木中新疆杨、灌木中紫丁香的单位叶面积滞留量与单株滞留量都较高,起到明显的降尘作用,是沙尘频发的辽西北地区城市绿化树种的优先之选。