A critical appraisal of epidemiological studies investigating the effects of ultrafine particles on human health

Maudgalya, Tushyati; Genaidy, Ash; Weckman, Gary R.; Shell, Richard; Karwowski, Waldemar; Wallace, Scott A.

doi:10.1002/hfm.20115

Cited by 13 publications

(9 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…those of less than 100 nm in size. These are present in very large numbers in urban environments and are potentially very important because they are small enough to penetrate deep into the lungs and additionally, have the potential to transfer into tissues beyond the lungs and cause more physiological damage (Ibald-Mulli et al, 2002;Maudgalya et al, 2008;Kreyling et al, 2006). The transport sector is known to be a major source of primary organic aerosols (POA) in urban environments (Colvile et al, 2001), but others such as cooking (Robinson et al, 2006) and the burning of solid fuels such as biomass (Simoneit, 2002) are also known to be significant in some locations.…”

Section: Introductionmentioning

confidence: 99%

Contributions from transport, solid fuel burning and cooking to primary organic aerosols in two UK cities

Allan¹,

Morgan²,

Martin³

et al. 2009

Preprint

View full text Add to dashboard Cite

Abstract. Organic matter frequently represents the single largest fraction of fine particulates in urban environments and yet the exact contributions from different sources and processes remain uncertain, owing in part to its substantial chemical complexity. Positive Matrix Factorisation (PMF) has recently proved to be a powerful tool for the purposes of source attribution and profiling when applied to ambient organic aerosol data from the Aerodyne Aerosol Mass Spectrometer (AMS). Here we present PMF analysis applied to AMS data from UK cities for the first time. Three datasets are analysed, with the focus on objectivity and consistency. The data were collected in London during the Regent's Park and Tower Environmental Experiment (REPARTEE) intensives and Manchester. These occurred during the autumn and wintertime, such that the primary fraction would be prominent. Ambiguities associated with rotationality within sets of potential solutions are explored and the most appropriate solution sets selected based on comparisons with external data. In addition to secondary organic aerosols, three candidate sources of primary organic aerosol (POA) were identified according to mass spectral and diurnal profiles; traffic emissions, cooking and solid fuel burning. Traffic represented, on average, 40% of POA during colder conditions and exhibited a hydrocarbon-like mass spectrum similar to those previously reported. Cooking aerosols represented 34% of POA and through laboratory work, their profile was matched with that sampled from the heating of seed oils, rather than previously-published spectra derived from charbroiling. This suggests that in these locations, oil from frying may have contributed more to the particulate than the meat itself. Solid fuel aerosols represented 26% of POA during cold weather conditions but were not discernable during the first REPARTEE experiment, when conditions were warmer than the other campaigns. This factor showed features associated with biomass burning and occurred mainly at night. Grid-scale emission factors of the combustion aerosols suitable for use in chemical transport models were derived relative to CO and NOx. The traffic aerosols were found to be 14.4 μg m−3 ppm−1 relative to CO for Manchester and 28 μg m−3 ppm−1 relative to NOx for London. Solid fuel emissions were derived as 17.3 μg m−3 ppm−1 relative to CO for Manchester. These correspond to mass emission ratios of 0.012, 0.021 (as NO) and 0.014 respectively and are of a similar order to previously published estimates, derived from other regions or using other approaches.

show abstract

Section: Introductionmentioning

confidence: 99%

Contributions from transport, solid fuel burning and cooking to primary organic aerosols in two UK cities

Allan¹,

Morgan²,

Martin³

et al. 2009

Preprint

View full text Add to dashboard Cite

show abstract

“…Epidemiological evidence for these health effects is robust, even though there are still knowledge gaps regarding the exact mechanisms by which air pollutants affect human health (including the effects of pollutant mixtures), and which pollutants should be tackled with priority (EEA, 2013;EPA, 2012;Maudgalya et al, 2008;WHO, 2012WHO, , 2013a. Controlling air pollution not only directly reduces adverse health effects, but increases general well-being, quality of life, improves public health and can have positive impacts on ecosystem services.…”

mentioning

confidence: 99%

Personal exposure monitoring of PM 2.5 in indoor and outdoor microenvironments

Steinle

Reis

Sabel

et al. 2015

Science of The Total Environment

279

178

View full text Add to dashboard Cite

Adverse health effects from exposure to air pollution are a global challenge and of widespread concern. Recent high ambient concentration episodes of air pollutants in European cities highlighted the dynamic nature of human exposure and the gaps in data and knowledge about exposure patterns. In order to support health impact assessment it is essential to develop a better understanding of individual exposure pathways in people's everyday lives by taking account of all environments in which people spend time. Here we describe the development, validation and results of an exposure method applied in a study conducted in Scotland. A low-cost particle counter based on light-scattering technology - the Dylos 1700 was used. Its performance was validated in comparison with equivalent instruments (TEOM-FDMS) at two national monitoring network sites (R(2)=0.9 at a rural background site, R(2)=0.7 at an urban background site). This validation also provided two functions to convert measured PNCs into calculated particle mass concentrations for direct comparison of concentrations with equivalent monitoring instruments and air quality limit values. This study also used contextual and time-based activity data to define six microenvironments (MEs) to assess everyday exposure of individuals to short-term PM2.5 concentrations. The Dylos was combined with a GPS receiver to track movement and exposure of individuals across the MEs. Seventeen volunteers collected 35 profiles. Profiles may have a different overall duration and structure with respect to times spent in different MEs and activities undertaken. Results indicate that due to the substantial variability across and between MEs, it is essential to measure near-complete exposure pathways to allow for a comprehensive assessment of the exposure risk a person encounters on a daily basis. Taking into account the information gained through personal exposure measurements, this work demonstrates the added value of data generated by the application of low-cost monitors.

show abstract

“…Because of their small size, nanoparticles can deposit throughout the respiratory tract, transport into cells, or traverse the skin and enter into the bloodstream or elsewhere in the body (Oberdorster et al, 2005). For these reasons, it is not surprising that elevated exposure to ultrafine aerosol has been associated with higher incidences of adverse cardiopulmonary effects (Gong et al, 2008;Maudgalya et al, 2008;Politis et al, 2008;Knibbs et al, 2011).…”

mentioning

confidence: 95%