Aerosol-Radiation Feedback and PM10 Air Concentrations Over Poland

We have implemented the WRF-Chem model version 3.5 over Poland to quantify the direct and indirect feedback effects of aerosols on simulated meteorology and aerosol concentrations. Observations were compared with results from three simulations at high spatial resolutions of 5 × 5 km: (1) BASE—without any aerosol feedback effects; (2) DIR—with direct aerosol-radiative effects (3) INDIR—with direct and indirect aerosol-radiative effects. We study the overall effect during January 2011 as well as selected episodes of the highest differences in PM10 concentrations between the three simulations. For the DIR simulation, the decrease in monthly mean incoming solar radiation (SWDOWN) appears for the entire study area. It changes geographically, from about −8.0 to −2.0 W m−2, respectively for the southern and northern parts of the country. The highest changes do not correspond to the highest PM10 concentration. Due to the solar radiation changes, the surface mean monthly temperature (T2) decreases for 96 % of the area of Poland, but not more than 1.0 °C. Monthly mean PBLH changes by more than ±5 m for 53 % of the domain. Locally the differences in PBLH between the DIR and BASE are higher than ± 20 m. Due to the direct effect, for 84 % of the domain, the mean monthly PM10 concentrations increase by up to 1.9 µg m−3. For the INDIR simulation the spatial distribution of changes in incoming solar radiation as well as air temperature is similar to the DIR simulation. The decrease of SWDOWN is noticed for the entire domain and for 23 % of the domain is higher than −5.0 W m−2. The absolute differences of PBLH are slightly higher for INDIR than DIR but similarly distributed spatially. For daily episodes, the differences between the simulations are higher, both for meteorology and PM10 concentrations, and the pattern of changes is usually more complex. The results indicate the potential importance of the aerosol feedback effects on modelled meteorology and PM10 concentrations.

Application of WRF-Chem to Forecasting PM10 Concentration over Poland

The meteorological and chemical transport model WRF-Chem was implemented to forecast PM10 concentrations over Poland. WRF-Chem version 3.5 was configured with three one way nested domains using the GFS meteorological data and the TNO MACC II emissions. Forecasts, with 48h lead time, were run for a winter and summer period 2014. WRF-Chem in general captures the variability in observed PM10 concentrations, but underestimates some peak concentrations during winter-time. The peaks coincide with either stable atmospheric condition during nighttime in the lower part of the planetary boundary layer or on days with very low surface temperatures. Such episodes lead to increased combustion in residential heating, where hard coal is the main fuel in Poland. This suggests that a key to improvement in the model performance for the peak concentrations is to focus on the simulation of PBL processes and the distribution of emissions with high resolution in WRF-Chem.

Application of WRF-Chem to Forecasting PM10 Concentration Over Poland

The meteorological and chemical transport model WRF-Chem was implemented to forecast PM10 concentrations over Poland. WRF-Chem version 3.5 was configured with three one-way nested domains using the GFS meteorological data and the TNO MACC II emissions. The 48 hour forecasts were run for each day of the winter and summer period of 2014 and there is only a small decrease in model performance for winter with respect to forecast lead time. The model in general captures the variability in observed PM10 concentrations for most of the stations. However, for some locations and specific episodes, the model performance is poor and the results cannot yet be used by official authorities. We argue that a higher resolution sector-based emission data will be helpful for this analysis in connection with a focus on planetary boundary layer processes in WRF-Chem and their impact on the initial distribution of emissions on both time and space.