A modelling study of OH, NO3 and H2SO4 in 2007-2018 at SMEAR II, Finland: analysis of long-term trends.

Major atmospheric oxidants (OH, O3 and NO3) dominate the atmospheric oxidation capacity, while H2SO4 is considered as a main driver for new particle formation. Although numerous studies have investigated the long-term trend of ozone in Europe, the trends of OH, NO3 and H2SO4 at specific sites are to a large extent unknown. The one-dimensional model SOSAA has been applied in several studies at the SMEAR II station and has been validated by measurements in several projects. Here, we applied the SOSAA model for the years 2007-2018 to simulate the atmospheric chemical components, especially the atmospheric oxidants OH and NO3, as well as H2SO4 at SMEAR II. The simulations were evaluated with observations from several shorter and longer campaigns at SMEAR II. Our results show that daily OH increased by 2.39% per year and NO3 decreased by 3.41% per year, with different trends of these oxidants during day and night. On the contrary, daytime sulfuric acid concentrations decreased by 2.78% per year, which correlated with the observed decreasing concentration of newly formed particles in the size range of 3-25 nm with 1.4% per year at SMEAR II during the years 1997-2012. Additionally, we compared our simulated OH, NO3 and H2SO4 concentrations with proxies, which are commonly applied in case a limited number of parameters are measured and no detailed model simulations are available.

Evaluation of impact of residential heating on air quality of megacity Istanbul by CMAQ.

Residential heating is one of the major sectors that contribute to emissions of harmful air pollutants in urban areas. In Istanbul, local sources are the main contributors of particulate matter levels. To quantify the contributions of residential heating sector to ambient particulate matter concentrations, we have developed an up to date spatially distributed high-resolution emissions inventory based on local activity data. The air quality simulations were conducted using the CMAQ (version 5.2). Our study results showed that our high-resolution emissions of the residential heating sector significantly improve the spatial distribution and concentration of air pollutants (SO2, PM10, PM2.5) for Istanbul. Air quality model simulations with our high-resolution emissions underestimated PM10 concentrations throughout the study episode on average by only 4.16% with a mean bias of 2.23 µg/m-3 while base inventory underestimated PM10 concentrations on average by 35.1% with a mean bias of 18.91 µg/m-3. Results show that our spatially distributed high-resolution emissions inventory produces more realistic results for Istanbul during wintertime when residential heating has the most influence on local air pollution.