Dust storms are a common phenomenon that occurs in many dry and arid areas, demonstrates very high levels of particulate matter (PM), can spread significantly further than its origin, affects both outdoor and indoor air quality, and can cause serious health problems although it is a low frequency event. Focus of this study is the prediction of PM (PM.
and PM) infiltration at typical commercial and office building environments during severe dust storms. Therefore, a two-month field campaign was conducted to capture such an event in Doha, Qatar, and a modelling methodology is proposed based on the one-way coupling of a multi-zone and a computational fluid dynamics software. The predicted levels are in fair agreement with the measurements for both the dust storm and typical days, attributed to the accurate estimation of the external wind pressure and representation of the building envelope. The agreement further improves when the efficiency of the ventilation filters is estimated, from the measuremetns, rather than being extracted from specification sheets. Finally, predictions are found to conform with physical reality and to offer useful insights into PM building infiltration during dust storm events when cross examined with measurements.
This study investigates and proposes emission factors (EFs) and models for vehicle-induced exhaust (VEX) and fugitive (VfPM) particulate matter emissions representative of areas with arid climates. Particle number (PNC) and mass (PMC) concentrations and their integrated samples were collected for a period of three months for both PM10 and PM2.5 next to a trafficked road in the city of Doha, Qatar. Using Positive Matrix Factorization (PMF) on the elemental data of the samples, six distinct PM sources were identified: traffic exhaust, dust resuspension, fresh and aged sea salt, secondary aerosols, and fuel oil/shipping. Dispersion modelling and regression analysis were combined to derive EFs (linear analysis) and models (non-linear analysis) for the total traffic fleet (heavy and light duty). The estimated EFs were between 620 and 730 mg VKT?1 (VKT; Vehicle Kilometer Travelled) (adj. R2 ~ 0.84) and between 1080 and 1410 mg VKT?1 (adj. R2 ~ 0.70) for VEX and VfPM, respectively. The integration of field measurements, chemical characterization, and dispersion modelling presented herein is one of the first similar studies conducted in the wider region, identifies the importance of fugitive PM (fPM), and marks the need for further studies to improve emissions modelling of VfPM in arid desert climates.
There is substantial evidence that airborne particulate matter (PM) contributes to haze, acid rain, global climate change, and decreased life expectancy. Many recent studies have reported that a large fraction of airborne PM could be attributed to fugitive PM (fPM). The developing arid and semi-arid regions, in particular, are facing the biggest brunt of fPM usually ascribed to the regionally transported dust. On the other hand, the rapid expansion of their metropolitan cities is contributing a considerable amount of locally induced fPM which makes it a prominent environmental and health stressor in these areas. Based on field measurements and dispersion modelling, this thesis aims to: (i) measure fPM from two common sources (loose soils and non-exhaust traffic) in areas with arid desert climates, (ii) derive representative emission models, and (iii) assess their overall environmental and health impacts.
For this thesis, on site measurements and samples of PM (<10 µm diameter) were collected. Source apportionment was performed to determine the contributions of individual sources. Dispersion modelling and regression analysis were used to derive emission models for loose Calcisols (a prominent soil in the subject areas) and vehicle-induced fPM (VfPM). Finally, our derived models were used along with the state-of-the-art practices (i.e., regional emission models and the World Health Organization?s (WHO) Environmental Burden of Disease (EBD) method) to determine the environmental and health impacts of local fPM. Several important findings were extracted from the above analysis: (i) fPM from different origins contribute more than 60% of the urban PM in arid areas, (ii) power law emission models with wind speed dependence were derived for loose Calcisols soil, (iii) emission factors were derived for VfPM using linear regression and were close to values reported in USA, (iv) EBD estimates found that fPM may lead to ~ 11.0 times higher short-term excess mortalities compared to constant database measurements.