The Air Quality Standards for Particulate Matter (PM) at high altitude urban areas in different countries, must consider the pressure and temperature due to the effect that these parameters have on the breath volume.This paper shows the importance to correct Air Quality Standards for PM considering pressure and temperature at different altitudes. Specific factors were suggested to convert the information concerning PM, from local to standard conditions, and adjust the Air Quality Standards for different high altitudes cities. The correction factors ranged from: 1.03 for Santiago de Chile to 1.47 for El Alto Bolivia. Other cities in this study include: Mexico City, México; La Paz, Bolivia; Bogota, Cali and Medellin, Colombia; Quito, Ecuador and Cuzco, Peru.If these corrections are not considered, the atmospheric concentrations will be underestimated.

A new methodology has been developed for the determination of secondary alkane sulfonates (SAS), an anionic surfactant, in environmental matrices. Sediment and sludge samples were extracted using pressurized liquid extraction and sonication, whereas wastewater and surface water samples were processed using solid-phase extraction. Extraction recoveries were acceptable for both aqueous (78–120%) and solid samples (83–100%). Determination of SAS was carried out by high or ultra performance liquid chromatography – mass spectrometry using ion trap and time-of-flight detectors. The methodology was applied to samples from Guadalete River (SW Spain), where SAS concentrations below 1 μg L−1 were measured in surface water, and from 72 to 9737 μg kg−1 in sediments. Differential partitioning was observed for SAS homologues as those having a longer hydrocarbon chain which preferentially sorbed onto particulate matter. A preliminary environmental risk assessment also showed that SAS measured levels were not harmful to the aquatic community in the sampling area.

The toxicity of atmospheric fine particulate matter (PM2.5) in Atlanta is assessed using freshwater rotifers (Brachionus calyciflorus). The PM-laden quartz filters were extracted in both water and methanol. Aerosol extracts were passed through a C-18 column to separate the PM components into hydrophobic and hydrophilic fractions. Toxicity data reported in the units of LC50 (concentration that kills 50% of the test population in 24 h) shows that ambient particles are toxic to the rotifers with LC50 values ranging from 5 to 400 μg of PM. The methanol extract of the aerosols was substantially more toxic (8 ± 6 times) to the rotifers compared to the water extracts. A sizeable fraction (>70%) of toxicity was found to be associated with the hydrophobic fraction of PM. However, none of the bulk aerosol species was strongly correlated with the LC50 values suggesting a complicated mechanism of toxicity probably involving synergistic interactions of various PM components.

Satellite observations may improve the areal coverage of particulate matter (PM) air quality data that nowadays is based on surface measurements. Three statistical methods for retrieving daily PM2.5 concentrations from satellite products (MODIS-AOD, OMI-AAI) over the San Joaquin Valley (CA) are compared – Linear Regression (LR), Generalized Additive Models (GAM), and Multivariate Adaptive Regression Splines (MARS). Simple LRs show poor correlations in the western USA (R2 ≅ 0.2). Both GAM and MARS were found to perform better than the simple LRs, with a slight advantage to the MARS over the GAM (R2 = 0.71 and R2 = 0.61, respectively). Since MARS is also characterized by a better computational efficiency than GAM, it can be used for improving PM2.5 retrievals from satellite aerosol products. Reliable PM2.5 retrievals can fill in missing surface measurements in areas with sparse ground monitoring coverage and be used for evaluating air quality models and as exposure metrics in epidemiological studies.

Particulate matter (PM), a complex mix of chemical compounds, results to be associated with various health effects. However there is still lack of information on the impact of its different components. PM2.5 and PM1 samples, collected during the different seasons at an urban, rural and remote site, were chemically characterized and the biological effects induced on A549 cells were assessed. A Partial Least Square Discriminant Analysis has been performed to relate PM chemical composition to the toxic effects observed. Results show that PM-induced biological effects changed with the seasons and sites, and such variations may be explained by chemical constituents of PM, derived both from primary and secondary sources. The first-time here reported biological responses induced by PM from a remote site at high altitude were associated with the high concentrations of metals and secondary species typical of the free tropospheric aerosol, influenced by long range transports and aging.

The total PAH associated to the airborne particulate matter (PM10) was apportioned by one receptor model based on positive matrix factorization (PMF) in an urban environment (Zaragoza city, Spain) during February 2010–January 2011. Four sources associated with coal combustion, gasoline, vehicular and stationary emissions were identified, allowing a good modelling of the total PAH (R2 = 0.99). A seasonal behaviour of the four factors was obtained with higher concentrations in the cold season. The NE direction was one of the predominant directions showing the negative impact of industrial parks, a paper factory and a highway located in that direction. Samples were classified according to hierarchical cluster analysis obtaining that, episodes with the most negative impact on human health (the highest lifetime cancer risk concentrations), were produced by a higher contribution of stationary and vehicular emissions in winter season favoured by high relative humidity, low temperature and low wind speed.

Recently, biomagnetic monitoring of tree leaves has proven to be a good estimator for ambient particulate concentration. This paper investigates the usefulness of biomagnetic leaf monitoring of crown deposited particles to assess the spatial PM distribution inside individual tree crowns and an urban street canyon in Ghent (Belgium). Results demonstrate that biomagnetic monitoring can be used to assess spatial PM variations, even within single tree crowns. SIRM values decrease exponentially with height and azimuthal effects are obtained for wind exposed sides of the street canyon. Edge and canyon trees seem to be exposed differently. As far as we know, this study is the first to present biomagnetic monitoring results of different trees within a single street canyon. The results not only give valuable insights into the spatial distribution of particulate matter inside tree crowns and a street canyon, but also offer a great potential as validation tool for air quality modelling.

This study combines the methods of observation statistics and remote sensing retrieval, using remote sensing information including the urban heat island (UHI) intensity index, the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), and the difference vegetation index (DVI) to analyze the correlation between the urban heat island effect and the spatial and temporal concentration distributions of atmospheric particulates in Beijing. The analysis establishes (1) a direct correlation between UHI and DVI; (2) an indirect correlation among UHI, NDWI and DVI; and (3) an indirect correlation among UHI, NDVI, and DVI. The results proved the existence of three correlation types with regional and seasonal effects and revealed an interesting correlation between UHI and DVI, that is, if UHI is below 0.1, then DVI increases with the increase in UHI, and vice versa. Also, DVI changes more with UHI in the two middle zones of Beijing.

Cerebrovascular accidents, or strokes, are the second leading cause of mortality and the leading cause of morbidity in both Chile and the rest of the world. However, the relationship between particulate matter pollution and strokes is not well characterized. The association between fine particle concentration and stroke admissions was studied. Data on hospital admissions due to cerebrovascular accidents were collected from the Ministry of Health. Air quality and meteorological data were taken from the Air Quality database of the Santiago Metropolitan Area. Santiago reported 33,624 stroke admissions between January 1, 2002 and December 30, 2006. PM2.5 concentration was markedly seasonal, increasing during the winter. This study found an association between PM2.5 exposure and hospital admissions for stroke; for every PM2.5 concentration increase of 10 μg m−3, the risk of emergency hospital admissions for cerebrovascular causes increased by 1.29% (95% CI 0.552%–2.03%).

Concerns over exposure to airborne particulate matter (PM) are on the rise. Currently monitoring of PM is done on the basis of interpolating a mass of PM by volume (μg/m3) but has the drawback of not taking the chemical nature of PM into account. Here we propose a method of collecting PM at its emission source and employing automated analysis with scanning electron microscopy associated with EDS-analysis together with light scattering to discern the chemical composition, size distribution, and time and space resolved structure of PM emissions in a heavily trafficated roundabout in Sweden. Multivariate methods (PCA, ANOVA) indicate that the technogenic marker Fe follows roadside dust in spreading from the road, and depending on time and location of collection, a statistically significant difference can be seen, adding a useful tool to the repertoiré of detailed PM monitoring and risk assessment of local emission sources.