Link between precipitations and air quality in Bucharest Greater Area, Romania

<p>Air pollution and climate change represent today key environmental issues. They are highly linked each other through various ways. Pollutant emission reductions can improve both air quality and mitigate the climate changes. On the other hand, heavy precipitations and/or an increased frequency of their occurrence (climate change) might help to clean the air from pollutants. Despite of the scientific progress, the understanding of atmospheric pollutant wet removal in urban and peri-urban areas is still subject to a large uncertainty. Among factors of uncertainties are aerosol large variability, different sources, aerosol-cloud processing.</p><p>This study examines how the concentrations of particulate matter with an aerodynamic diameter below 10 μm (PM<sub>10</sub>) and below 2.5 μm (PM<sub>2.5</sub>) might be linked with precipitation characteristics using an observational data set for three years (2015-2017) in Bucharest metropolitan area. Particulate matter data and meteorological parameters at each site (atmospheric pressure, relative humidity, temperature, global solar radiation, wind speed and direction) were extracted from the public available Romanian National Air Quality Database. Meteorology was complemented with radar products (images, reflectivity, echotops) from the C-band meteorological radar from National Meteorological Administration in Bucharest. Change of aerosol mass concentration during the evolution of the precipitation events was investigated. The aerosol scavenging coefficients were estimated and compared with those in scientific literature. Correlations between meteorological parameters and ambient PM<sub>10</sub> and PM<sub>2.5</sub> levels were analyzed. Connection of meteorological phenomena occurrence and air mass origin was investigated by computing air mass backward trajectories using the HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) model for 72 hours back.</p><p>It was found that heavy precipitations have a strong influence on the atmospheric aerosol concentrations, determining an increased value of scavenging coefficient with up to one order of magnitude higher than in case of a moderate precipitation. Higher values of scavenging coefficient than in literature reveals a good capability of the convective precipitating systems to clear the atmosphere from aerosol and pollutant species.</p><p>The obtained results are important for modeling of air quality and for investigations of aerosol wet deposition processes.</p><p><strong>Acknowledgement:</strong></p><p>The authors thank the financial support from UB198/Int project and to National Meteorological Administration for access to the RADAR database. The data regarding ground-based air pollution and meteorology by site was extracted from the public available Romanian National Air Quality Database, www.calitateaer.ro, last accessed in December 2019.</p>

Review and uncertainty assessment of size-resolved scavenging coefficient formulations for below-cloud snow scavenging of atmospheric aerosols

Theoretical parameterizations for the size-resolved scavenging coefficient for atmospheric aerosol particles scavenged by snow (Λsnow) need assumptions regarding (i) snow particle–aerosol particle collection efficiency E, (ii) snow-particle size distribution N(Dp), (iii) snow-particle terminal velocity VD, and (iv) snow-particle cross-sectional area A. Existing formulas for these parameters are reviewed in the present study, and uncertainties in Λsnow caused by various combinations of these parameters are assessed. Different formulations of E can cause uncertainties in Λsnow of more than one order of magnitude for all aerosol sizes for typical snowfall intensities. E is the largest source of uncertainty among all the input parameters, similar to rain scavenging of atmospheric aerosols (Λrain) as was found in a previous study by Wang et al. (2010). However, other parameters can also cause significant uncertainties in Λsnow, and the uncertainties from these parameters are much larger than for Λrain. Specifically, different N(Dp) formulations can cause one-order-of-magnitude uncertainties in Λsnow for all aerosol sizes, as is also the case for a combination of uncertainties from both VD and A. Assumptions about dominant snow-particle shape (and thus different VD and A) will cause an uncertainty of up to one order of magnitude in the calculated scavenging coefficient. In comparison, uncertainties in Λrain from N(Dp) are smaller than a factor of 5, and those from VD are smaller than a factor of 2. As expected, Λsnow estimated from empirical formulas generated from field measurements falls in the upper range of, or is higher than, the theoretically estimated values, which can be explained by additional processes/mechanisms that influence field-derived Λsnow but that are not considered in the theoretical Λsnow formulas. Predicted aerosol concentrations obtained by using upper range vs. lower range of Λsnow values (a difference of around two orders of magnitude in Λsnow) can differ by a factor of 2 for just a one-centimetre snowfall (liquid water equivalent of approximately 1 mm). Based on the median and upper range of theoretically generated Λsnow and Λsnow values, it is likely that, for typical rain and snow events, the removal of atmospheric aerosol particles by snow is more effective than removal by rain for equivalent precipitation amounts, although a firm conclusion requires much more evidence.

Review and uncertainty assessment of size-resolved scavenging coefficient formulations for snow scavenging of atmospheric aerosols

Theoretical parameterizations for the size-resolved scavenging coefficient for atmospheric aerosol particles scavenged by snow (Λsnow) need assumptions regarding (i) snow particle–aerosol particle collection efficiency E, (ii) snow particle size distribution N(Dp), (iii) snow particle terminal velocity VD, and (iv) snow particle cross-sectional area A. Existing formulas for these parameters are reviewed in the present study and uncertainties in Λsnow caused by various combinations of these parameters are assessed. Different formulations of E can cause uncertainties in Λsnow of more than one order of magnitude for all aerosol sizes for typical snowfall intensities. E is the largest source of uncertainty among all the input parameters, similar to rain scavenging of atmospheric aerosols (Λrain) as was found in a previous study by Wang et al. (2010). However, other parameters can also cause significant uncertainties in Λsnow, and the uncertainties from these parameters are much larger than for Λrain. Specifically, different N(Dp) formulations can cause one-order-of-magnitude uncertainties in Λsnow for all aerosol sizes, as is also the case for a combination of uncertainties from both VD and A. In comparison, uncertainties in Λrain from N(Dp) are smaller than a factor of 5 and those from VD are smaller than a factor of 2. Λsnow estimated from one empirical formula generated from field measurements falls in the upper range of, or is slightly higher than, theoretically estimated values. The predicted aerosol concentrations obtained using different Λsnow formulas can differ by a factor of two for just a one-centimeter snowfall (liquid water equivalent of approximately 1 mm). It is likely that, for typical rain and snow event the removal of atmospheric aerosol particles by snow is more effective than removal by rain for equivalent precipitation amounts, although a firm conclusion requires much more evidence.

Effect of Rain on Evolution of Distribution of Soluble Gaseous Pollutants in the Atmosphere

We suggest a model of rain scavenging of soluble gaseous pollutants in the atmosphere. It is shown that below-cloud gas scavenging is determined by non-stationary convective diffusion equation with the effective Peclet number. The obtained equation was analyzed numerically in the case of log-normal droplet size distribution. Calculations of scavenging coefficient and the rates of precipitation scavenging are performed for wet removal of ammonia (NH3) and sulfur dioxide (SO2) from the atmosphere. It is shown that scavenging coefficient is non-stationary and height-dependent. It is found also that the scavenging coefficient strongly depends on initial concentration distribution of soluble gaseous pollutants in the atmosphere. It is shown that in the case of linear distribution of the initial concentration of gaseous pollutants whereby the initial concentration of gaseous pollutants decreases with altitude, the scavenging coefficient increases with height in the beginning of rainfall. At the later stage of the rain scavenging coefficient decreases with height in the upper below-cloud layers of the atmosphere.

Scavenging of ultrafine particles by rainfall at a boreal site: observations and model estimations

Values of the scavenging coefficient determined from observations of ultrafine particles (with diameters in the range 10–510 nm) during rain events at a boreal forest site in Southern Finland between 1996 and 2001 were reported by Laakso et al. (2003a). The estimated range of the median values of the scavenging coefficient was [7×10−6–4×10−5] s−1, which is generally higher than model calculations based only on below-cloud processes (Brownian diffusion, interception, and typical phoretic and charge effects). In the present study, in order to interpret these observed data on scavenging coefficients from Laakso et al. (2003a), we use a model that includes below-cloud scavenging processes, mixing of ultrafine particles from the boundary layer (BL) into cloud, followed by cloud condensation nuclei activation and in-cloud removal by rainfall. The range of effective scavenging coefficient predicted by the new model, corresponding to wide ranges of values of its input parameters, are compared with observations. Results show that ultrafine particle removal by rain depends on aerosol size, rainfall intensity, mixing processes between BL and cloud elements, in-cloud scavenged fraction, in-cloud collection efficiency, and in-cloud coagulation with cloud droplets. The scavenging coefficients predicted by the new model are found to be significantly sensitive to the choice of representation of: (1) mixing processes; (2) raindrop size distribution; (3) phoretic effects in aerosol-raindrop collisions; and (4) cloud droplet activation. Implications for future studies of BL ultrafine particles scavenging are discussed.

Scavenging of ultrafine particles by rainfall at a boreal site: observations and model estimations

Values of the scavenging coefficient were determined from observations of ultrafine particles (with diameters in the range 10–510 nm) during rain events at a boreal forest site in Southern Finland between 1996 and 2001. The estimated range of values of the scavenging coefficient was [7×10−6–4×10−5] s−1, which is generally higher than model calculations based only on below-cloud processes (Brownian diffusion, interception, and typical charge effects). A new model that includes below-cloud scavenging processes, mixing of ultrafine particles from the boundary layer (BL) into cloud, followed by cloud condensation nuclei activation and in-cloud removal by rainfall, is presented. The effective scavenging coefficients estimated from this new model have values comparable with those obtained from observations. Results show that ultrafine particle removal by rain depends on aerosol size, rainfall intensity, mixing processes between BL and cloud elements, in-cloud scavenged fraction, in-cloud collection efficiency, and in-cloud coagulation with cloud droplets. Implications for the treatment of scavenging of BL ultrafine particles in numerical models are discussed.