Commuting by subway? What you need to know about air quality

Internationally, more than 120 million people commute by subway every day, and this number will keep increasing in the future as the United Nations predicts that 75% of the world’s population will be urban by 2050. On top of being crucial to the mobility of city dwellers, subway systems can also play a pivotal role in reducing outdoor air pollution in large metropolises by helping to reduce motor-vehicle use. However, in response to increasing scientific and public awareness regarding the importance of clean air to human health, several studies have revealed unacceptably high levels of inhalable particulate matter (PM) in some subway systems. This article reviews some of these studies and puts their results in perspective, given World Health Organisation (WHO) guidelines concerning safe concentrations of particulate matter in the air. Following on from this, the authors identify some of the key factors influencing subway air pollution and put forward a number of recommendations to help city planners improve air quality in subway systems, as well as commuters protect themselves from the brunt of air pollution in the subway environment

Concentrations, sources and geochemistry of airborne particulate matter at a major European airport

9 pages, 9 figures, 2 tables.-- PMID: 20383366 [PubMed]Monitoring of aerosol particle concentrations (PM10, PM2.5, PM1) and chemical analysis (PM10) was undertaken at a major European airport (El Prat, Barcelona) for a whole month during autumn 2007. Concentrations of airborne PM at the airport were close to those at road traffic hotspots in the nearby Barcelona city, with means measuring 48 g PM10/m3, 21 g PM2.5/m3 and 17 g PM1/m3. Meteorological controls on PM at El Prat are identified as cleansing daytime sea breezes with abundant coarse salt particles, alternating with nocturnal land-sourced winds which channel air polluted by industry and traffic (PM1/PM10 ratios > 0.5) SE down the Llobregat Valley. Chemical analyses of the PM10 samples show that crustal PM is dominant (38% of PM10), followed by total carbon (OC + EC, 25%), secondary inorganic aerosols (SIA, 20%), and sea salt (6%). Local construction work for a new airport terminal was an important contributor to PM10 crustal levels. Source apportionment modelling PCA-MLRA identifies five factors: industrial/traffic, crustal, sea salt, SIA, and K+ likely derived from agricultural biomass burning. Whereas most of the atmospheric contamination concerning ambient air PM10 levels at El Prat is not attributable directly to aircraft movement, levels of carbon are unusually high (especially organic carbon), as are metals possibly sourced from tyre detritus/smoke in runway dust (Ba, Zn, Mo) and from brake dust in ambient PM10 (Cu, Sb), especially when the airport is at its most busy. We identify microflakes of aluminous alloys in ambient PM10 filters derived from corroded fuselage and wings as an unequivocal and highly distinctive tracer for aircraft movement.This work was supported by research projects from the Spanish Ministry of Environment (MMA 2006_EG0X2006-M-PARTICULADO- M1) (CALIOPE, 441/2006/3-12.1), the Spanish Ministry of Sciences and Innovation (GRACCIE-CSD2007- 00067, DOASUR CGL2007-62505/CLI) and a fellowship from the Spanish Council of Research (CSIC).Peer reviewe

Characteristics of ash and particle emissions during bubbling fluidised bed combustion of three types of residual forest biomass

Combustion of residual forest biomass (RFB) derived from eucalypt (Eucalyptus globulus), pine (Pinus pinaster) and golden wattle (Acacia longifolia) was evaluated in a pilot-scale bubbling fluidised bed reactor (BFBR). During the combustion experiments, monitoring of temperature, pressure and exhaust gas composition has been made. Ash samples were collected at several locations along the furnace and flue gas treatment devices (cyclone and bag filter) after each combustion experiment and were analysed for their unburnt carbon content and chemical composition. Total suspended particles (TSP) in the combustion flue gas were evaluated at the inlet and outlet of cyclone and baghouse filter and further analysed for organic and elemental carbon, carbonates and 57 chemical elements. High particulate matter collection efficiencies in the range of 94-99% were observed for the baghouse, while removal rates of only 1.4-17% were registered for the cyclone. Due to the sand bed, Si was the major element in bottom ashes. Fly ashes, in particular those from eucalypt combustion, were especially rich in CaO, followed by relevant amounts of SiO2, MgO and K2O. Ash characteristics varied among experiments, showing that their inorganic composition strongly depends on both the biomass composition and combustion conditions. Inorganic constituents accounted for TSP mass fractions up to 40 wt%. Elemental carbon, organic matter and carbonates contributed to TSP mass fractions in the ranges 0.58-44%, 0.79-78% and 0.01-1.7%, respectively.publishe

Implementation of road dust resuspension in air quality simulations of particulate matter in Madrid (Spain)

An evaluation of the concentration levels of Particulate Matter (PM) was carried out in Madrid (Spain) by introducing the emissions from road dust resuspension. Road dust resuspension emission factors (EF) for different types of vehicles were calculated from EPA-AP42, a global resuspension factor of 0.097 g veh−1 km−1 as described in Amato et al. (2010) and a rain-dependent correction factor. With these resuspension EFs, a simulation at street canyon level was performed with the OSPM model without rainfall. Subsequently, a simulation using the CMAQ model was implemented adding resuspension emissions affected by the rain. These data were compared with monitored data obtained from air quality stations. OSPM model simulations with resuspension EFs but without the effect of rainfall improve the PM estimates in about 20 μg m−3 compared to the simulation with default EFs. Total emissions were calculated by adding the emissions estimated with resuspension EFs to the default PM emissions to be used by CMAQ. For the study in the Madrid Area, resuspension emissions are approximately of the same order of magnitude as inventoried emissions. On a monthly scale, rain effects are negligible for resuspension emissions due to the dry weather conditions of Spain. With the exception of April and May, the decrease in resuspension emissions is not >3%. The predicted PM10 concentration increases up to 9 μg m−3 on annual average for each station compared to the same scenario without resuspension. However, in both cases, PM10 estimates with resuspension are still underestimating observations. It should be noted that although that accounting for resuspension improves the quality of model predictions, other PM sources (e.g., Saharan dust) were not considered in this study.This project was partially financed by the Spanish Ministry of the Environment (SERCA-058/PC08/3-18.1).Peer reviewedPeer Reviewe

Effects of Road Dust Suppressants on PM Levels in a Mediterranean Urban Area

The abatement of road dust emissions is currently a major challenge for sustainable transportation, causing exceedances of limits on particulate matter (PM) and high population exposures to mineral dust and metals. Mitigation measures have been proposed such as improved street cleaning and the use of dust suppressants. This study evaluated, for the first time, the effectiveness of calcium-magnesium acetate (CMA) and MgCl2 in reducing road dust emissions in a Mediterranean city. During a two-month campaign, a typical urban road in the city of Barcelona was sprayed, and changes in PMx levels and components were monitored at four traffic sites and one background monitoring sites. The integrated results indicate no statistically significant effectiveness of dust suppressants on PM10 and PM2.5-10 levels. Episodic reductions of Al, K, Mg, Cr, Li, Cu, and Zn were observed during CMA applications, but they were not systematically statistically significant over different stations and spreading days. MgCl2 days showed lower PM10 mean concentrations, but these reductions were not statistically significant and were not supported by significant drops in mineral and brake-wear metals. Based on our literature review, it can be postulated that the higher the road dust loading, the higher the dust suppressant effectiveness

Implementation of road dust resuspension in air quality simulations of particulate matter in Madrid (Spain)

An evaluation of the concentration levels of Particulate Matter (PM) was carried out in Madrid (Spain) by introducing the emissions from road dust resuspension. Road dust resuspension emission factors (EF) for different types of vehicles were calculated from EPA-AP42, a global resuspension factor of 0.097 g veh−1km−1 as described in Amato et al. (2010) and a rain-dependent correction factor. With these resuspension EFs, a simulation at street canyon level was performed with the OSPM model without rainfall. Subsequently, a simulation using the CMAQ model was implemented adding resuspension emissions affected by the rain. These data were compared with monitored data obtained from air quality stations. OSPM model simulations with resuspension EFs but without the effect of rainfall improve the PM estimates in about 20gm−3μ compared to the simulation with default EFs. Total emissions were calculated by adding the emissions estimated with resuspension EFs to the default PM emissions to be used by CMAQ. For the study in the Madrid Area, resuspension emissions are approximately of the same order of magnitude as inventoried emissions. On a monthly scale, rain effects are negligible for resuspension emissions due to the dry weather conditions of Spain. With the exception of April and May, the decrease in resuspension emissions is not >3%. The predicted PM10 concentration increases up to 9μ gm−3 on annual average for each station compared to the same scenario without resuspension. However, in both cases, PM 10 estimates with resuspension are still underestimating observations. It should be noted that although that accounting for resuspension improves the quality of model predictions, other PM sources (e.g., Saharan dust) were not considered in this study