Determination of asbestos cement rooftop surface composition using regression analysis and hyper-spectral reflectance data in the visible and near-infrared ranges.

The effects of asbestos on human health have spurred numerous studies examining its risks in urban environments. Recent works have shifted towards less-invasive techniques for remote detection and classification of asbestos-cement. In this context, this study combines visible (VIS) and near-infrared (NIR) reflectance data collected in-situ with reference signals from the USGS spectral library, utilizing optimized regression analysis to determine the surface composition of corrugated asbestos-cement rooftops. An outlier filter was successfully implemented to enhance the accuracy of regression calculations, achieving a high level of agreement with actual field observations. The regression analysis revealed varying proportions of weathered cement, hazardous asbestos fibers (specifically chrysotile and cummingtonite), and biological growth (such as lichens and moss). These results are consistent with previous research on the composition of asbestos-cement rooftops, including a comparable field study and XRD analysis conducted in 2019. This underscores the importance of using regression analysis, preceded by an outlier filtering step, on VIS and NIR reflectance data to ascertain the surface composition of asbestos-cement rooftops. This methodology holds potential for application to larger hyperspectral datasets across more extensive sample surfaces and areas.

PM2.5 characterization of primary and secondary organic aerosols in two urban-industrial areas in the East Mediterranean.

Primary and secondary organic aerosols in PM2.5 were investigated over a one-year campaign at Zouk Mikael and Fiaa, Lebanon. The n-alkanes concentrations were quite similar at both sites (26-29 ng/m3) and mainly explained by anthropogenic emissions rather than natural ones. The concentrations of total Polycyclic Aromatic Hydrocarbons (PAHs) were nearly three times higher at Zouk Mikael (2.56 ng/m3) compared to Fiaa (0.95 ng/m3), especially for indeno[1,2,3-c,d]pyrene linked to the presence of the power plant. A characteristic indeno[1,2,3-c,d]pyrene/(indeno[1,2,3-c,d]pyrene + benzo[g,h,i]perylene) ratio in the range 0.8-1.0 was determined for heavy fuel oil combustion from the power plant. Fatty acids and hopanes were also investigated and were assigned to cooking activities and vehicular emissions respectively. Phthalates were identified for the first time in Lebanon with high concentrations at Zouk and Fiaa (106.88 and 97.68 ng/m3 respectively). Moreover, the biogenic secondary aerosols revealed higher concentrations in summer. The total terpene concentration varied between 131 ng/m3 at Zouk Mikael in winter to 469 ng/m3 at Fiaa in summer. Additionnally, the concentrations of the dicarboxylic acids especially for adipic and phthalic acids were more influenced by anthropogenic sources.The analysis of molecular markers and diagnostic ratios indicated that the sites were strongly affected by anthropogenic sources such as waste open burning, diesel private generators, cooking activities, road transport, power plant, and industrial emissions. Moreover, results showed different pattern during winter and summer seasons. Whereas, higher concentrations of biogenic markers were clearly encountered during the summer period.

Risk assessment of asbestos-cement roof sheets in Chekka, North Lebanon.

Asbestos-cement was manufactured and used in Lebanon since the early 1950s. Corrugated rooftops of asbestos-cement were mostly spread within residential areas throughout the country. These rooftops are subject to weathering factors which are known to increase friability and risk of hazardous fiber release. This study aimed at assessing the asbestos-cement rooftop friability and the possible emerging risks in the urban-industrial city of Chekka, North Lebanon. The evaluation of the asbestos-cement included two field assessment algorithms and a standardized pull-up test. Hazard of fiber emissions was assessed by a pull-up test method, whereas vulnerability was determined by a level of interaction between people and the rooftops. Geographic object-based image analysis was used to map hazard, vulnerability, and risk of asbestos rooftops in the study area. The field algorithms classified most rooftops in a bad state compared with the pull-up test which ranked most of them as good. The X-ray diffraction analysis showed the presence of serpentine and amphibole fibers, except for crocidolite, in some rooftop samples. Hazard, vulnerability, and risk maps of the sampled area showed how hazard potential was amplified by vulnerability of population to possible fiber emission.

Contributions of local and regional anthropogenic sources of metals in PM2.5 at an urban site in northern France.

PM2.5 have been related to various adverse health effects, mainly due to their ability to penetrate deeply and to convey harmful chemical components, such as metals inside the body. In this work, PM2.5 were sampled at Saint-Omer, a medium-sized city located in northern France, in March-April 2011 and analyzed for their total carbon, water-soluble ions, major and trace elements. More specifically, the origin of 15 selected elements was examined using different tools including enrichment factors, conditional bivariate probability function (CBPF) representations, diagnostic ratios and receptor modelling. The results indicated that PM2.5 metal composition is affected by both emissions of a local glassmaking factory and an integrated steelworks located at a distance of 35 km from the sampling site. For the first time, diagnostic ratios were proposed for the glassmaking activity. Therefore, metals in PM2.5 could be attributed to the following anthropogenic sources: (i) local glassmaking industry for Sn, As, Cu and Cr, (ii) distant integrated steelworks for Ag, Fe, Cd, Mn, Rb and Pb, (iii) heavy fuel oil combustion for Ni, V and Co and (iv) non-exhaust traffic for Zn, Pb, Mn, Sb, and Cu. The impact of such sources on metal concentrations in PM2.5 was assessed using a constrained receptor model. Despite their low participation to PM2.5 concentration (2.7%), the latter sources were found as the main contributors (80%) to the overall concentration levels of the 15 selected elements in PM2.5.

PM2.5 source apportionment in a French urban coastal site under steelworks emission influences using constrained non-negative matrix factorization receptor model.

The constrained weighted-non-negative matrix factorization (CW-NMF) hybrid receptor model was applied to study the influence of steelmaking activities on PM2.5 (particulate matter with equivalent aerodynamic diameter less than 2.5 µm) composition in Dunkerque, Northern France. Semi-diurnal PM2.5 samples were collected using a high volume sampler in winter 2010 and spring 2011 and were analyzed for trace metals, water-soluble ions, and total carbon using inductively coupled plasma--atomic emission spectrometry (ICP-AES), ICP--mass spectrometry (ICP-MS), ionic chromatography and micro elemental carbon analyzer. The elemental composition shows that NO3(-), SO4(2-), NH4(+) and total carbon are the main PM2.5 constituents. Trace metals data were interpreted using concentration roses and both influences of integrated steelworks and electric steel plant were evidenced. The distinction between the two sources is made possible by the use Zn/Fe and Zn/Mn diagnostic ratios. Moreover Rb/Cr, Pb/Cr and Cu/Cd combination ratio are proposed to distinguish the ISW-sintering stack from the ISW-fugitive emissions. The a priori knowledge on the influencing source was introduced in the CW-NMF to guide the calculation. Eleven source profiles with various contributions were identified: 8 are characteristics of coastal urban background site profiles and 3 are related to the steelmaking activities. Between them, secondary nitrates, secondary sulfates and combustion profiles give the highest contributions and account for 93% of the PM2.5 concentration. The steelwork facilities contribute in about 2% of the total PM2.5 concentration and appear to be the main source of Cr, Cu, Fe, Mn, Zn.

Chemical profile identification of fugitive and confined particle emissions from an integrated iron and steelmaking plant.

The aim of this study is to obtain the characteristic inorganic chemical profile of important particle sources identified in the integrated iron and steel process: sintering, blast furnace, steelmaking and desulfurization slag processing. A complete chemical and physical characterization program was developed: particle size distribution, chemical analysis, XRD, SEM-EDX and TGA/DTA. The sample collected from the sinter stack showed high levels of K and Cl(-), followed by Fe, NH4(+), Ca, Na and Pb. The profile of the dust samples taken from the sinter cake discharge zone was quite different, showing higher amounts of Fe, Ca and Al, and lower amounts of K, Cl(-), Na and Pb. Dust samples collected from the blast furnace (BF) and steelmaking cast house may be distinguished from each other based on the higher levels of Fe (hematite and magnetite) and lower levels of Ca, Zn and C (graphite) found in BF dust. High levels of Ca and Fe were found in samples taken from the desulfurization slag processing area. Such information can be useful for source apportionment studies at receptor sites that could be influenced by iron and steelmaking plant emissions.