How does the composition of atmospheric aerosol particles affect PM2.5 toxicity?

Thomson, Steven (2022). How does the composition of atmospheric aerosol particles affect PM2.5 toxicity? University of Birmingham. Ph.D.

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Abstract

Epidemiological studies have shown that exposure to PM2.5 increases the chance of mortality or morbidity due to respiratory and cardiovascular diseases. The causes for this are not completely understood yet, however, one widely proposed biochemical pathway is PM2.5-induced oxidative stress.
This study aims to determine the impact of PM2.5 concentration on the oxidative potential (OP) of the air mass, and the effect of PM chemical composition on the intrinsic OP of PM2.5 particles. These factors were investigated through several intensive periods of PM2.5 measurement across different seasons in Beijing and Delhi, with a shorter campaign in Birmingham, followed by detailed laboratory chemical analysis, and application of an OP assay to the collected PM samples.
The dithiothreitol (DTT) assay was chosen as the method for OP determination and a laboratory protocol was developed, meeting the requirements and limitations of the project and available laboratories. This protocol was validated using PM2.5 samples collected during a short sampling campaign in Birmingham.
PM2.5 concentration was found to be strongly correlated with air mass OP (DTTv, nmol DTT min-1 m-3) at lower PM¬2.5 concentrations (r = 0.85 at < 110.6 µg m-3, being the median concentration), however, at higher concentrations a non-linear relationship formed (r = 0.41 at > 110.6 µg m-3). This was due to an inverse relationship between PM2.5 concentration and intrinsic toxicity (DTTm, pmol DTT min-1 µg-1 PM2.5) at higher PM2.5 concentrations (r = -0.47). During some extreme PM2.5 pollution events DTTv values were lower than those seen during much lower PM2.5 concentration days, demonstrating the importance of intrinsic PM OP to human exposure (DTTv) and consequent health effects.
The relative impact of different PM chemical components on DTTm was determined through various correlation, multiple linear regression, and t-test analyses performed on composition measurements within PM, and meteorological and gas-phase data for the Beijing and Delhi campaigns. The impact of these species and meteorological conditions on DTTm was determined by the gradient of their correlation with DTTm, the gradient for each species was denoted by DTTmspecie (i.e. DTTmFe representing pmol DTT min-1 ng-1 Fe).
Data from all campaigns showed significant correlations between vehicle related emissions and DTTm. Crustal material, re-suspended road dust, and non-exhaust vehicle emissions were also significantly correlated with DTTm during the Beijing winter and all Delhi campaigns. Species most commonly associated with these sources consistently showed the highest gradients such as Ce, Cr, Ni, and Sr.
During the Delhi autumn campaign biomass burning is the dominant source of PM2.5. Biomass associated species such as OC and K showed a weaker effect on OP assessed as DTTm values, compared with non-exhaust vehicle emissions and crustal materials i.e. 0.153 ± 0.023 DTTmOC compared to 358 ± 34 DTTmCe. Multiple linear regression analysis showed that 78 % of DTTm variance was accounted for by non-exhaust vehicle emissions in this campaign. This study shows that PM2.5 concentration is key in determining the overall oxidative potential of the air, however, it is not sufficient to solely predict this oxidative potential. The sources and composition of the particulate matter must also be considered to better predict the health effects of particulate matter oxidative potential.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):