Huvudinnehåll

Cecilia Bennet

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Researcher Air Quality, Ph. D.

Porträtt på Cecilia Bennet.

Cecilia Bennet

  • Dispersion modelling
  • Aerosol modelling
  • Exposure modelling for epidemiological research
  • Bilateral cooperation in air quality
  • Ph. D. thesis - Regional air quality modelling over south-east Asia

Latest publications

High-resolution dispersion modelling of PM<sub>2.5</sub>, PM<sub>10</sub>, NO<sub>x</sub> and NO<sub>2</sub> exposure in metropolitan areas in Sweden 2000-2018-large health gains due to decreased population exposure

Karl Kilbo Edlund, Marta A. Kisiel, Christian Asker, David Segersson, Cecilia Bennet, Marten Spanne, Susanna Gustafsson, Jenny Lindvall, Kristina Eneroth, Martin Tondel, Petter Ljungman, Leo Stockfelt, Goeran Pershagen, Peter Molnar

In: Air quality, atmosphere and health

2024

DOI: 10.1007/s11869-024-01535-0

Quantification of population exposure to PM10, PM2.5 and NO2 and estimated health impacts for 2019 and 2030

Helene Alpfjord Wylde, Christian Asker, Cecilia Bennet, David Segersson

2023

Concentrations of NO2, PM10 and PM2.5 have been calculated for the whole of Sweden for the year 2019 as well as two scenarios for 2030 in this study. Calculations have been performed using a new methodology, allowing almost seam-less combination of dispersion modelling at regional and urban scale without double-counting emissions. The concentrations have been calculated at 250x250 m2 resolution, producing a uniquely complete and detailed dataset at national scale. The  methodology used can well reproduce the measured pollution levels at most urban background stations in the modelling domain. The spatial resolution of 250 m captures concentration gradients that are of importance for exposure calculations. An important strength of using dispersion modelling to calculate concentrations is the direct relation with emission inventories, allowing for source attribution and scenario evaluation that is consistent with emission inventories and projections. 

The modelled concentrations are used together with gridded population data in order to calculate exposure. The annual average population weighted exposure is 5.08 µg/m3 for NO2, 9.95 µg/m3 for PM10 and 5.21 µg/m3 for PM2.5 in 2019. A large decrease, by approximately 2 µg/m3, is seen for exposure to NO2 in 2030 compared to 2019. The exposure to PM10 and PM2.5 is also decreasing in 2030, but not as drastically, by about 0.2 µg/m3.   

A general conclusion is that exposure is higher in the age span of 21-50 years. An explanation is that these age groups more often live in urban areas, where there are more emissions and higher concentrations of pollution.    

Zero percent of the population is exposed to levels above the annual air quality standards for NO2, PM10 and PM2.5 for 2019 and 2030.  It is to be noted that the model results represent annual averaged urban background concentrations, not local hotspot concentrations. 

The modelled exposures to PM2.5 and urban NO2 have been used for a national health impact assessment. The health impact assessment is similar to an earlier study of premature deaths and incident cases of mainly chronic diseases. Our results differ to a varying degree from similar impact assessments. Most important among the complicated reasons for differences in the estimated health impacts are the assumed exposure-response functions for the specific exposures, the slope and if there is a lower threshold below which no association exists. We have in this study decided to follow the strong evidence from high quality epidemiological studies that the exposure-response relationship between long-term exposure to PM2.5 and total mortality in adults is supra-linear with a much steeper slope at the lower end, with stronger effects of near source exposure, and no evidence of a threshold level below which no effects are observed. When adding the yearly number of premature deaths attributed to the regional background PM2.5 levels and the deaths associated with PM2.5 exposure from local sources, the total number becomes 4 264 deaths related to the fine particle exposure situation in 2019. At the same time, the urban contribution of NO2 is estimated to result in additional 428 premature deaths per year. 

In 2030 the population exposure to PM2.5 from the regional background is expected to be about 2% lower and from urban sources 22% lower compared to 2019, which indicates how much the attributed number of preterm deaths would change if everything else stays the same. 

MATCH-SALSA - Multi-scale Atmospheric Transport and CHemistry model coupled to the SALSA aerosol microphysics model - Part 1

Camilla Andersson, Robert Bergström, Cecilia Bennet, Lennart Robertson, Manu Thomas, H. Korhonen, K. E. J. Lehtinen, H. Kokkola

In: Geoscientific Model Development, Vol. 8, No. 2

2015

DOI: 10.5194/gmd-8-171-2015

We have implemented the sectional aerosol dynamics model SALSA (Sectional Aerosol module for Large Scale Applications) in the European-scale chemistry-transport model MATCH (Multi-scale Atmospheric Transport and Chemistry). The new model is called MATCH-SALSA. It includes aerosol microphysics, with several formulations for nucleation, wet scavenging and condensation. The model reproduces observed higher particle number concentration (PNC) in central Europe and lower concentrations in remote regions. The modeled PNC size distribution peak occurs at the same or smaller particle size as the observed peak at four measurement sites spread across Europe. Total PNC is underestimated at northern and central European sites and accumulation-mode PNC is underestimated at all investigated sites. The low nucleation rate coefficient used in this study is an important reason for the underestimation. On the other hand, the model performs well for particle mass (including secondary inorganic aerosol components), while elemental and organic carbon concentrations are underestimated at many of the sites. Further development is needed, primarily for treatment of secondary organic aerosol, in terms of biogenic emissions and chemical transformation. Updating the biogenic secondary organic aerosol (SOA) scheme will likely have a large impact on modeled PM2.5 and also affect the model performance for PNC through impacts on nucleation and condensation.