Size distribution of viable, cultivable, airborne microbes and their relationship to particulate matter concentrations and meteorological conditions in a Mediterranean site

The biological loading of viable, cultivable airborne microbes (heterotrophic bacteria, actinobacteria and fungi) in 6 size fractions as well as the three different fractions of respirable particulate matter (PM₁, PM_2.5 and PM₁₀) and their relationship to meteorological conditions were studied in the ambient air due to health-related interests. An Andersen six stage viable particle impactor and a MAS 100 sampler were used for microbial measurements. 82 measurements were performed at three different periods (41 days) at a suburban, residential site in the city of Chania (Crete, Greece) during the period from April 2008 to June 2009. The concentrations of the viable, cultivable airborne microbes (bioaerosols) as well as of the PM₁, PM_2.5 and PM₁₀ were highly variable during the whole measurement period. Among the airborne microbes, fungi presented the most abundant taxonomic group in the ambient air. A characteristic profile of the mean size distribution of biological loading in different PM fractions was obtained for every measured microbial taxonomic group. Although, the highest concentrations of the airborne fungi and actinobacteria were determined at aerodynamic diameters between 2.1 and 3.3 μm, a nearly equal distribution of the mean concentrations of the airborne heterotrophic bacteria was observed in the six different size fractions. However, two small maxima were observed at the airborne heterotrophic bacteria distribution, one at the fraction with aerodynamic diameters between 1.1 and 2.1 μm, and at other at the coarse fraction with aerodynamic diameter larger than 7 μm. A considerable part of the airborne microbes Cycloheximide per mL of growth medium of bacteriwere resistant to drugs. Between 10 and 40 % of the viable, cultivable airborne microbes were resistant to low concentrations of drugs (5–10 μg of Streptomycin or a or fungi, respectively). Furthermore, multiple linear regression of the data showed that the variation in fungi concentrations depends on the variation in PM₁₀ mass concentration, PM₁ number concentration, relative humidity and solar radiation. Likewise, the concentration of heterotrophic bacteria was found proportional to the values of relative humidity and fungal concentration, whereas was negatively correlated to the solar radiation.     

Particle size distribution of cultivable airborne microbes and inhalable particulate matter in a wastewater treatment plant facility

A field study was performed to identify the size distribution characteristics of viable, cultivable airborne microorganisms (heterotrophic bacteria, fungi, and total coliforms) at a municipal wastewater treatment facility, and their association with inhalable particulate matter (PM₁, PM_2.5, and PM₁₀), as well as hydrogen sulfide concentrations and ambient meteorological parameters. The highest concentrations of cultivable, airborne heterotrophic bacteria, total coliforms, mass and number concentration of particulate matter, as well as hydrogen sulfide were observed at the aerated grit removal chambers at the pretreatment stage (3 to 2030 times higher than the values of the background ambient air). In contrast, the mean concentrations of cultivable, airborne mesophilic fungi at the aerated grit chambers were 0.6 time lower than the background site, where fungi presented the most abundant taxonomic group in the ambient air. Although the highest concentrations of the airborne fungi were determined at aerodynamic diameters between 2.1 and 3.3 μm, a nearly equal distribution of the mean concentrations of the cultivable, airborne heterotrophic bacteria were observed in the six different size fractions at the primary settling tanks and in the ambient air. Interestingly, their size distribution profiles at the aerated grit chambers were different and showed a maximum aerodynamic diameter at the size range from 3.3 to 4.7 μm, similar to that of the cultivable, airborne total coliforms. In general, low positive or no significant linear relationships could be found between the cultivable airborne heterotrophic bacteria, total coliforms, or fungi at the two wastewater treatment stages and the ambient background microbial community.     

Airborne bacteria, fungi, and endotoxin levels in residential microenvironments: a case study

Limited data are currently available on the concentrations of airborne bacteria, fungi, and endotoxins in indoor environments. The levels of aerial bacteria and fungi were measured at several microenvironments within a well-ventilated residential apartment in Singapore including the living room, kitchen, bedroom, toilet, and at a workplace environment by sampling indoor air onto culture medium plates using the 6-stage Andersen sampler. Total microbial counts were determined by collecting the air samples in water with the Andersen sampler, staining the resultant extracts with a fluorescent dye, acridine orange, and counting the microbes using a fluorescent microscope. The levels of airborne endotoxins were also determined by sampling the airborne microorganisms onto 0.4?μm polycarbonate membrane filter using the MiniVol sampler at 5?l/min for 20?h with a PM_2.5 cut-off device. The aerial bacterial and fungal concentrations were found to be in the ranges of 117–2,873?CFU/m³ and 160–1,897?CFU/m³, respectively. The total microbial levels ranged from 49,000 to 218,000?microbes/m³. The predominant fungi occurring in the apartment were Aspergillus and Penicillium while the predominant bacterial strains appeared to be Staphylococcus and Micrococcus. The average indoor endotoxin level was detectable in the range of 6–39?EU/m³. The amount of ventilation and the types of human activities carried out in the indoor environment appeared to be important factors affecting the level of these airborne biological contaminants.     

Platinum concentration in PM2.5 in the Mexico City Metropolitan Area: relationship to meteorological conditions

Abstract

Platinum (Pt) concentrations in PM_2.5 were evaluated by means of inductively coupled plasma mass spectrometry (ICP-MS) to evaluate the spatial and temporal behavior and to assess trends. Samples were taken from five representative sites in the Mexico City Metropolitan Area (MCMA): Tlalnepantla-northwest (NW), San Agustin-northeast (NE), La Merced -center (C), Coyoacan-southwest (SW), and Universidad Autonoma Metropolitana Iztapalapa-southeast (SE). Under three weather conditions: dry warm (DW-April), rainy (R-August), and dry cold (DC-November) in 2013. We found that the PM_2.5 median mass concentration was 24?μg m^?3?±?15?μg m^?3 while Pt concentration was 55?pg m^?3?±?15?pg m^?3 (median, interquartile range). Seasonal trend was identified: the concentrations decreased significantly in the following order DC?>?R>DW. No spatial distribution was observed. Interestingly, among other meteorically parameters, wind intensity resulted to be the major factor for the dispersion of Pt in PM2.5 in MCMA. Furthermore, we found that Pt concentrations increased significantly by 19.6% between 2011 and 2013. Regardless of the increase in Pt, carbon monoxide (CO) levels decreased opposite to a rise in vehicular fleet. These results urge for environment public policies that address the upward tendency of Pt levels especially in urban areas.     

广州大夫山雨季林内外空气TSP和PM2.5浓度及水溶性离子特征

采用平行同步采样法,于2012年雨季,对广州市大夫山森林公园林内外空气的总悬浮颗粒物(TSP)和细颗粒物(PM_2.5)样品进行了24 h收集,测定了TSP和PM_2.5的质量浓度并分析了样品中水溶性无机离子成分。结果表明:林内外PM_2.5的质量浓度平均值分别为(40.18±10.47)和(55.79±13.01) g/cm³;林内外TSP的质量浓度分别为(101.32 ± 33.19)和(116.61±35.36) g/cm³。林内与林外比,PM_2.5和TSP平均质量浓度都显著减少(P < 0.05),表明森林能显著改善空气环境质量。TSP和PM_2.5中SO₄^2-、Na⁺、NH₄⁺和NO₃^-为水溶性无机离子主要成分,占总离子质量的80%以上,林外这些离子的浓度高于林内(NH₄⁺除外)。这4种离子雨季在空气中的主要存在方式为NaCl、Na₂SO₄、NH₄HSO₄和NH₄NO₃。计算表明,采样期间海盐对大夫山空气TSP和PM_2.5的水溶性组分中Na⁺和Cl^-贡献最大,其它元素主要源自陆地源。林内外TSP和PM_2.5的c(NO₃^-)/c(SO₄^2-)比值在0.3以下,表明固定源是大夫山森林公园空气主要污染贡献者,TSP中c(NO₃^-)/c(SO₄^2-)的比值大于PM_2.5的比值,说明移动源对TSP的贡献大于PM_2.5。     

PM2.5 Spatiotemporal Variations and the Relationship with Meteorological Factors during 2013-2014 in Beijing,China

Objective

Limited information is available regarding spatiotemporal variations of particles with median aerodynamic diameter < 2.5 μm (PM_2.5) at high resolutions, and their relationships with meteorological factors in Beijing, China. This study aimed to detect spatiotemporal change patterns of PM_2.5 from August 2013 to July 2014 in Beijing, and to assess the relationship between PM_2.5 and meteorological factors.

Methods

Daily and hourly PM_2.5 data from the Beijing Environmental Protection Bureau (BJEPB) were analyzed separately. Ordinary kriging (OK) interpolation, time-series graphs, Spearman correlation coefficient and coefficient of divergence (COD) were used to describe the spatiotemporal variations of PM_2.5. The Kruskal-Wallis H test, Bonferroni correction, and Mann-Whitney U test were used to assess differences in PM_2.5 levels associated with spatial and temporal factors including season, region, daytime and day of week. Relationships between daily PM_2.5 and meteorological variables were analyzed using the generalized additive mixed model (GAMM).

Results

Annual mean and median of PM_2.5 concentrations were 88.07 μg/m³ and 71.00 μg/m³, respectively, from August 2013 to July 2014. PM_2.5 concentration was significantly higher in winter (P < 0.0083) and in the southern part of the city (P < 0.0167). Day to day variation of PM_2.5 showed a long-term trend of fluctuations, with 2–6 peaks each month. PM_2.5 concentration was significantly higher in the night than day (P < 0.0167). Meteorological factors were associated with daily PM_2.5 concentration using the GAMM model (R ² = 0.59, AIC = 7373.84).

Conclusion

PM_2.5 pollution in Beijing shows strong spatiotemporal variations. Meteorological factors influence the PM_2.5 concentration with certain patterns. Generally, prior day wind speed, sunlight hours and precipitation are negatively correlated with PM_2.5, whereas relative humidity and air pressure three days earlier are positively correlated with PM_2.5.     

Aerobiological study in the Mexico City subway system

Monitoring campaigns in two different seasons were carried out at two underground stations (Tacubaya and Azcapotzalco) of the subway of Mexico City, in order to assess airborne bacterial and fungi concentrations, as well as their relationship with several factors, such as depth of the station, sampling site, temperature, and relative humidity. Sixteen sampling sites were selected according to the depth of the lines and the transit of passengers in the corridors, concourses, and platforms. In addition, samples were also collected in the carriages when they were in movement. Outdoor samples were taken at the two stations for comparison. Two-stage multi-orifice cascade impactors were used to collect aerobiological particles, and with the aid of macroscopic and microscopic characterization were found 57 fungi and 61 bacteria colonies. Outdoor bacteria concentrations ranged from 1 to 68 CFU m^?3, while fungi concentrations varied from 6 to 80 CFU m^?3. The indoor concentration levels of bacteria and fungi ranged from 1 to 484 CFU m^?3 and from 51 to 715 CFU m^?3, respectively. Fungi and bacteria indoor concentrations in the subway were higher than outdoor, up to 8 times. Most of bacteria were identified as Gram-positive nonsporulating short bacillus, while the most abundant fungi genera identified were Aspergillus, Penicillium, and Alternaria in that order of frequency. Statistical analysis showed significant differences between the stations and the lines of different depths, showing a greater microorganisms’ concentration with a greater depth. Although bacteria and fungi concentrations were higher in the spring than in winter, this difference was not significant. Even if indoor microbiological pollution in underground stations was higher than outdoor, the concentrations found in this study were lower than indoor air international standards.     

Particle size distribution of the major Alternaria alternata allergen,Alt a 1, derived from airborne spores and subspore fragments

Fungal fragments are abundant immunoreactive bioaerosols that may outnumber the concentrations of intact spores in the air. To investigate the importance of Alternaria fragments as sources of allergens compared to Alternaria spores, we determined the levels of Alternaria spores and Alt a 1 (the major allergen in Alternaria alternata spores) collected on filters within three fractions of particulate matter (PM) of different aerodynamic diameter: (1) PM_>10, (diameter>10 μm); (2) PM_2.5-10 (2.5–10μm); (3) PM_2.5 (0.12–2.5 μm). The airborne particles were collected using a three stage high-volume ChemVol cascade impactor during the Alternaria sporulation season in Poznań, Poland (30 d between 6 July and 22 September 2016). The quantification of Alt a 1 was performed using the enzyme-linked immunosorbent assay. High concentrations of Alt a 1 were recorded during warm and dry d characterized by high sunshine duration, lack of clouds and high dew point values. Atmospheric concentrations of Alternaria spores correlated significantly (r = 0.930, p < 0.001) with Alt a 1 levels. The highest Alt a 1 was recorded in PM_2.5-10 (66.8 % of total Alt a 1), while the lowest in PM_2.5 (<1.0 %). Significantly more Alt a 1 per spore (>30 %) was observed in PM_2.5-10 than in PM_>10. This Alt a 1 excess may be derived from sources other than spores, e.g. hyphal fragments. Overall, in outdoor air the major source of Alt a 1 are intact Alternaria spores, but the impact of other fungal fragments (hyphal parts, broken spores, conidiophores) cannot be neglected, as they may increase the total atmospheric Alt a 1 concentration.     

Airborne concentrations of bacteria and fungi in Thailand border market

Thailand border market is where the local Thais, Cambodians, Laotians, and Burmeses exchange their goods and culture at the border checkpoints. It is considered to be the source of aerial disease transmission especially for foreigners because it is always very crowded with people from all walks of life. Unhealthy air quality makes this area high risk of spread of airborne diseases. This study assessed airborne concentrations of bacteria and fungi in a border market to improve exposure estimates and develop efficient control strategies to reduce health risk. The density and distribution of airborne bacteria and fungi were investigated in the Chong Chom border market in Surin Province, Thailand. Eighteen air sampling sites were taken from outdoors and various work environments including indoor footpaths, wooden handicraft shops, electronic shops, the secondhand clothing shops, and fruit market areas. Exposed Petri plate method and liquid impinger sampler were used for sampling at the breathing zone, 1.5 m above the floor level, during weekend and holiday. Meteorological factors such as relative humidity, temperature, and light intensity were collected by portable data logger. The relative humidity was 67–73%, and temperature 29–33°C, and light varied between 18 and 270 Lux m⁻². Gram-positive and Gram-negative bacteria were found at a mean value of 10⁴ CFU m⁻³, and airborne fungi of 10³ CFU m⁻³ were recorded. The highest concentration of culturable airborne microorganisms was found along the indoor footpath (9.62 × 10⁴ CFU m⁻³ and 750.00 CFU/plate/h for impingement and sedimentation methods, respectively), the fruit market area (7.86 × 10⁴ CFU m⁻³ and 592.42 CFU/plate/h for impingement and sedimentation methods, respectively), and the secondhand clothing shop (4.59 × 10³ CFU m⁻³ and 335.42 CFU/plate/h for impingement and sedimentation methods, respectively) for Gram-positive bacteria, Gram-negative bacteria, and fungi, respectively. The lowest concentration of Gram-positive bacteria, Gram-negative bacteria, and fungi was found only at the outdoor area at 1.53 × 10⁴ CFU m⁻³, 0.93 × 10⁴ CFU m⁻³ and 0.80 × 10³ CFU m⁻³ by means of impingement method and 136.67 CFU/plate/h, 69.25 CFU/plate/h, and 62.00 CFU/plate/h by means of sedimentation methods for Gram-positive bacteria, Gram-negative bacteria, and fungi, respectively. The most frequently present airborne bacteria were identified as Bacillus, Corynebacteria, Diplococcus, Micrococcus, Acinetobacter, Alcaligenes, Enterobacter, and spore former rods. Acremonium, Aspergillus, Cladosporium, Penicillium, and Sporotrichum were the most frequently found aerosol fungi genera. The distribution of airborne microorganisms correlated with relative humidity and light factors based on principal component analysis. In conclusion, the border market is a potential source of aerial disease transmission and a various hazards of bioaerosols for workers, consumers, sellers, and tourists. The bioaerosol concentration exceeded the standard of occupational exposure limit. Many major indicators of allergenic and toxigenic airborne bacteria and fungi, Acinetobacter, Enterobacter, Pseudomonas, Cladosporium, Alternaria, Aspergillus, and Penicillium, were found in the various market environments.     

The modeling and health risk assessment of PM2.5 from Tema Oil Refinery

Fine particulate matters (PM_2.5) are known to pose serious health problems compared to other air pollutants. The current study employed air dispersion modeling system (AERMOD) to simulate the concentration of PM_2.5 from Tema Oil Refinery (TOR) and to assess the non-cancer risk and mortalities of the exposed population. In addition, the effects of local climatic factors on the distribution and concentration of PM_2.5 within the three main seasons (Major Raining Season (MRS), Low Raining Season (LRS) and Dry Season (DS)) were investigated. The AERMOD results showed that both 24-h (38.8 µg m^?3) and annual (12.6 µg m^?3) PM_2.5 concentration levels were in exceedance of the international limits. However, a decreasing trend in seasonal PM_2.5 concentrations was observed. Health risk assessment (HRA), indicated by hazard index (HI), revealed that the amount of Al₂O₃ present in the PM_2.5 caused a significant non-carcinogenic health risk to the exposed population (both adults and children) within the Metropolis (HI = 2.4 for adults and HI = 1.5 for children). Additionally, cardiopulmonary disease related mortalities due to PM_2.5 exposure (181 deaths for adults and 24 deaths for children) were found high compared to deaths caused by lung cancer (137 deaths for adults and 16 deaths for children).     

Spatio-temporal air quality analysis and PM2.5 prediction over Hyderabad City,India using artificial intelligence techniques

Air pollution is one of the most serious environmental issues faced by humans, and it affects the quality of life in cities. PM_2.5 forecasting models can be used to create strategies for assessing and warning the public about anticipated harmful levels of air pollution. Accurate pollutant concentration measurements and forecasting are critical criteria for assessing air quality and are the foundation for making the right strategic decisions. Data-driven machine learning models for PM_2.5 forecasting have gained attention in the recent past. In this study, PM_2.5 prediction for Hyderabad city was carried out using various machine learning models viz. Multi-Linear Regression (MLR), decision tree (DT), K-Nearest Neighbors (KNN), Random Forest (RF), and XGBoost. A deep learning model, the Long Short-Term Memory (LSTM) model, was also used in this study. The results obtained were finally compared based on error and R² value. The best model was selected based on its maximum R² value and minimal error. The model's performance was further improved using the randomized search CV hyperparameter optimization technique. Spatio-temporal air quality analysis was initially conducted, and it was found that the average winter PM_2.5 concentrations were 68% higher than the concentrations in summer. The analysis revealed that XGBoost regression was the best-performing machine learning model with an R² value of 0.82 and a Mean Absolute Error (MAE) of 7.01 μg/ m³, whereas the LSTM deep learning model performed better than XGBoost regression for PM_2.5 modeling with an R² value of 0.89 and an MAE of 5.78 μg/ m³.     

Chemical speciation and health risks of airborne heavy metals around an industrial community in Nigeria

Abstract

Quantification of PM_2.5 (particulate matter <2.5?µm) bound heavy metals and their potential health risks were carried out around a cement manufacturing company in Ewekoro, Nigeria. The PM_2.5 samples were collected using Environtech gravimetric sampler. A four-staged sequential extraction procedure was used to fractionate PM_2.5 bound chromium (Cr), lead (Pb), aluminum (Al), copper (Cu), and silver (Ag), and further analyzed using inductively coupled plasma mass spectrometry. Chemical speciation results reveal bioavailable levels of Pb (4.05?µg/m³), Cr (10.75?µg/m³), Al (16.47?µg/m³), Cu (4.38E-01?µg/m³), and Ag (1.22E-02?µg/m³) in the airborne particulates. Pb and Cr levels exceeded the World Health Organization allowable limit of 0.5 and 2.5E-05?µg/m³, respectively. The labile phases showed strong indication of the presence of Cr and Cu metal. Excess cancer risks exposure for adults, outdoor workers and children were higher than the acceptable risk target level of 1E-06. Non-carcinogenic health risk estimated using hazard quotients (HQs) and hazard indices (HIs) showed ingestion route within the safe level of HI <1 implying no adverse effect while inhalation route exceeded the safe level for all receptors. Enforcement of pollution control by authorized agencies, and screening of greenbelts as sinks for air pollutants is strongly recommended.     

Spatio-temporal modelling of particulate matter concentrations using satellite derived aerosol optical depth over coastal region of Chennai in India

The present study primarily focuses on describing aerosol optical depth (AOD), its distribution pattern and seasonal variation, and modelling Particulate Matter Concentrations in Chennai. The frequency distribution of AOD and PM_2.5 demonstrates that AOD can be used as a proxy for estimating PM_2.5 in the study region as the occurrence of AOD almost resonates with that of PM_2.5. The seasonal variation of AOD and PM_2.5 revealed that during the winter (October–January) and summer (February–May) seasons, AOD reasonably followed the trend of PM_2.5. However, during the monsoon period, AOD showed random variations. Different models like linear and non-linear regression models and machine learning models such as random forest (RF) have been developed for PM_2.5 estimation. The model's performance in different stations and seasons has been assessed. The effect of meteorology and other factors in the model has also been assessed. From linear and non-linear model analysis, AOD was a significant parameter in estimating PM_2.5. The Random Forest model was the stable model for the study region, with a model R² of 0.53 and an RMSE of 15.89 μg/m³. The inclusion of meteorological parameters like relative humidity, wind speed, and wind direction decreased the error in prediction by 17.45 μg/m³. The seasonal and spatial analysis indicates that the prediction capability of models varies with stations and seasons. The best performing model was found to be Model RF, and the model could explain about 53.14% of the variability in PM_2.5 concentration occurrence in the study region with a prediction error of 15.89 μg/m³.     

Estimating PM2.5 concentrations with statistical distribution techniques for health risk assessment in Bangkok

Abstract

Ambient PM_2.5 data in the Central Business District (CBD) of Bangkok monitored by Pollution Control Department and Bangkok Metropolitan Administration were collected over three years in Bangkok from 2015 to 2017. The other air pollutions data were used as the dependent variables to develop mathematic models with statistical distribution technique. Multiple linear regression technique was selected as the main statistical distribution methodology for estimating PM_2.5 concentrations in non-monitored areas. The predicted PM_2.5 concentrations were validated against the measured PM_2.5 concentrations by various statistical techniques. The validation found that the model had strong significant correlations for ambient and roadside area with R ²?=?0.88 and 0.96, respectively. The non-carcinogenic health risk assessment of PM_2.5 was quantified as the hazard quotient (HQ) from both the measured and predicted data. The risk areas and HQ were compared using the inverse distance weighting interpolation technique and illustrated as GIS-based maps. During December to February, the HQ values of PM_2.5 were exceed 1 (HQs?>?1) at all area of CBD; however, the highest HQ was found in the southern part of CBD. The finding could be used for residential health awareness in that area.     

大气颗粒物(PM2.5、PM10)对地表景观结构的响应研究进展

颗粒物PM_(2.5)、PM_(10)是近年来我国大气首要污染物,威胁环境和人类健康。地表景观结构直接或间接影响PM_(2.5)、PM_(10)浓度,了解其影响过程和机理对于改善生态环境具有重要意义。系统总结了国内外关于PM_(2.5)、PM_(10)对地表景观结构响应的研究成果,指出研究中出现不确定性的可能影响因素,并对今后的发展方向进行展望。得出基本结论:(1)地表景观类型的构成及其格局显著影响大气颗粒物浓度,对PM_(2.5)、PM_(10)起到"源"和"汇"的作用。(2)地表景观结构引起局地气候变化并影响颗粒物的迁移转化,但其影响过程和机理复杂,研究结论并不明确。(3)颗粒物浓度和地表景观数据主要通过实际监测或遥感处理方法获得,但因为获取方法、监测点微观环境及遥感影像等因素影响,导致数据具有不确定性,加上时空尺度相对应的复杂性,大大限制了地表景观结构与PM_(2.5)、PM_(10)响应关系的研究进展,是未来要突破的难点。(4)PM_(2.5)、PM_(10)对地表景观结构响应的区域时空差异及过程,局地小气候变化对颗粒物浓度的影响过程和强度,主要景观类型尤其是水体、湿地景观对大气颗粒物浓度的影响过程、机理与贡献程度等是未来需要关注的方向。     

The Impact of Winter Heating on Air Pollution in China

Fossil-fuel combustion related winter heating has become a major air quality and public health concern in northern China recently. We analyzed the impact of winter heating on aerosol loadings over China using the MODIS-Aqua Collection 6 aerosol product from 2004–2012. Absolute humidity (AH) and planetary boundary layer height (PBL) -adjusted aerosol optical depth (AOD^*) was constructed to reflect ground-level PM_2.5 concentrations. GIS analysis, standard statistical tests, and statistical modeling indicate that winter heating is an important factor causing increased PM_2.5 levels in more than three-quarters of central and eastern China. The heating season AOD^* was more than five times higher as the non-heating season AOD^*, and the increase in AOD^* in the heating areas was greater than in the non-heating areas. Finally, central heating tend to contribute less to air pollution relative to other means of household heating.     

Particulate matter and bacteria characteristics of the Middle East Dust (MED) storms over Ahvaz,Iran

The Middle East Dust storms have greatly affected the south and west parts of Iran during the last decade. The main purpose of this study was to examine and compare culturable airborne bacteria concentration in particulate matter (PM) during normal, semi-dust, and dust event days in different places and seasons in Ahvaz from November 2011 to May 2012. Sampling was performed every 6 days and on dust event days at different sampling stations. The overall mean concentrations of PM₁₀, PM_2.5, and PM₁ for the entire study period were 598.92, 114.8, and 34.5 μg/m³, respectively. The PM concentrations during the dust event days were much higher than normal and semi-dust event days. The highest mean PM concentrations were observed in March 2011. The low PM_2.5/PM₁₀ ratios indicate that these PM are mostly originating from natural sources such as dust storms. The overall mean concentration of total bacteria during the study period was 620.6 CFU/m³. The greatest bacterial concentrations were observed during dust event days and at areas with high traffic and more human activities compared with normal days and greener areas. The percentage of gram-positive bacteria was significantly higher than that during the study period (89 vs 11 %). During this study, 26 genera of culturable bacteria were identified from all the sampling stations. The most dominant genera in all sampling stations were Streptomyces, Bacillus, Kocuria, Corynebacterium, and Paenibacillus. The results also showed that there were positive correlations between PM and bacterial concentrations during the study period (p < 0.05).     

Assessing the Impact of Advected African Dust on Air Quality and Health in the Eastern United States

Large quantities of African dust are carried into the southeastern United States each summer with concentrations typically in the range of 10 to 100?µg m^?3. Because approximately one-third to one-half of the dust mass is in the size range under 2.5?µm diameter, the advection of African dust has implications for the EPA's newly implemented standard for PM_2.5 particulate matter and for the assessment of human health effects. It will be difficult to assess the impact of African dust events on air quality because they occur during the summer (maximum in July) when photochemical pollution events are frequent and intense in the eastern United States. Indeed, the presence of dust could affect the evolution of photochemical dust events. In order to assess the role of African dust in air quality in the United States, it will be necessary to develop a set of diagnostic indicators; it appears that dust mineralogy and elemental composition might be useful for this purpose. Various satellite products can be used to characterize the spatial coverage of dust events and, when coupled with meteorological tools, to predict impact regions.     

Bioaerosol emissions in a poultry litter burning plant

This study investigates the exposure of workers to biological particles in a poultry litter burning plant in operation. The microorganism concentrations were examined at different workplaces during procedures leading to increased emissions. The concentrations of culturable airborne mesophilic, xerophilic and thermophilic microorganisms in the ambient air were tested inside and outside of the burning plant using two different methods of measuring. The focus of this study was on the quantitative evaluation of culturable bacteria as well as the quantitative and qualitative evaluation of gram-negative bacteria, fungi and thermophilic actinomycetes. The maximum airborne concentrations were found in the delivery hall. Mesophilic bacteria concentrations reached up to 1.7 × 10⁶ CFU/m³; gram-negative bacteria up to 9.1 × 10² CFU/m³. Fungal propagule concentrations for xerophilic fungi were between 1.2 × 10³ and 2.9 × 10⁴ CFU/m³ and for mesophilic fungi between 4.4 × 10² and 2.9 × 10⁴ CFU/m³. Among fungi, Aspergillus niger, Eurotium herbariorum and Scopulariopsis brevicaulis species were dominant. Thermophilic actinomycetes reached airborne concentrations of 8.7 × 10⁴ CFU/m³, with increased concentrations of the pathogens causing extrinsic allergic alveolitis. The high concentrations of airborne microorganisms in poultry litter burning plants and the potential hazard of the intake of microorganisms including potential pathogens require the introduction of consistent measures in both technical areas and personnel management.     

The effects of transported Asian dust on the composition and concentration of ambient fungi in Taiwan

This study was conducted to evaluate the effects of transported Asian dust and other environmental parameters on the levels and compositions of ambient fungi in the atmosphere of northern Taiwan. We monitored Asian dust events in Taipei County, Taiwan from January 2003 to June 2004. We used duplicate Burkard portable air samplers to collect ambient fungi before, during, and after dust events. Six transported Asian dust events were monitored during the study period. Elevated concentrations of Aspergillus (A. niger, specifically), Coelomycetes, Rhinocladiella, Sporothrix and Verticillium were noted (p < 0.05) during Asian dust periods. Botryosporium and Trichothecium were only recovered during dust event days. Multiple regression analysis showed that fungal levels were positively associated with temperature, wind speed, rainfall, non-methane hydrocarbons and particulates with aerodynamic diameters ≤10 μm (PM₁₀), and negatively correlated with relative humidity and ozone. Our results demonstrated that Asian dust events affected ambient fungal concentrations and compositions in northern Taiwan. Ambient fungi also had complex dynamics with air pollutants and meteorological factors. Future studies should explore the health impacts of ambient fungi during Asian dust events, adjusting for the synergistic/antagonistic effects of weather and air pollutants.