TY - JOUR AB - The COVID-19 pandemic in Germany in 2020 brought many regulations to impede its transmission such as lockdown. Hence, in this study, we compared the annual air pollutants (CO, NO, NO2, O3, PM10, PM2.5, and BC) in Augsburg in 2020 to the record data in 2010–2019. The annual air pollutants in 2020 were significantly (p < 0.001) lower than that in 2010–2019 except O3, which was significantly (p = 0.02) higher than that in 2010–2019. In a depth perspective, we explored how lockdown impacted air pollutants in Augsburg. We simulated air pollutants based on the meteorological data, traffic density, and weekday and weekend/holiday by using four different models (i.e. Random Forest, K-nearest Neighbors, Linear Regression, and Lasso Regression). According to the best fitting effects, Random Forest was used to predict air pollutants during two lockdown periods (16/03/2020–19/04/2020, 1st lockdown and 02/11/2020–31/12/2020, 2nd lockdown) to explore how lockdown measures impacted air pollutants. Compared to the predicted values, the measured CO, NO2, and BC significantly reduced 18.21%, 21.75%, and 48.92% in the 1st lockdown as well as 7.67%, 32.28%, and 79.08% in the 2nd lockdown. It could be owing to the reduction of traffic and industrial activities. O3 significantly increased 15.62% in the 1st lockdown but decreased 40.39% in the 2nd lockdown, which may have relations with the fluctuations the NO titration effect and photochemistry effect. PM10 and PM2.5 were significantly increased 18.23% an 10.06% in the 1st lockdown but reduced 34.37% and 30.62% in the 2nd lockdown, which could be owing to their complex generation mechanisms. AU - Cao, X. AU - Liu, X.* AU - Hadiatullah, H.* AU - Xu, Y.* AU - Zhang, X.* AU - Bendl, J.* AU - Cyrys, J.* AU - Zimmermann, R. AU - Adam, T. C1 - 66043 C2 - 52599 TI - Investigation of COVID-19-related lockdowns on the air pollution changes in augsburg in 2020, Germany. JO - Atmos. Pollut. Res. VL - 13 IS - 9 PY - 2022 ER - TY - JOUR AB - Fireworks have been shown to contribute short-term but potent source of ambient particulate matter (PM). Here we present a source apportionment-based approach to estimate the quantitative contributions of fireworks in releasing black carbon (eBC), polycyclic aromatic hydrocarbons (PAHs) and metals into urban ambient air on six New Year's Day fireworks events from the period 2010 to 2021. Simplified PMF analyses were performed to assign PAHs, eBCs, and metals to major contributors (building heating, traffic, and fireworks) of ambient PM. The trends of PM10 and PM2.5 concentrations clearly showed the drastic increase of the concentrations on New Year's Days. The PMF analyses showed that, on average, about 35% (20–80% for individual years) of the PAHs and about 45% of eBC (10–100%) were associated with the fireworks. Metals presented in high concentrations in pyrotechnic sets, namely Ba, Cu, K, Mg, and Sr were attributed to fireworks about 90%, while Al was attributed to fireworks by 86%. Other metals (Ca, Cr, Fe, Na, Pb, Ti, and Zn) were attributed to fireworks by variable proportions averaging at 67%, 77%, 44%, 59%, 64%, 75%, and 33%, respectively. Overall, these findings complement future monitoring programs and regulations for fireworks emissions. AU - Khedr, M. AU - Liu, X. AU - Hadiatullah, H.* AU - Orasche, J. AU - Zhang, X.* AU - Cyrys, J. AU - Michalke, B. AU - Zimmermann, R. AU - Schnelle-Kreis, J. C1 - 64206 C2 - 51985 CY - Dokuz Eylul Univ, Dept Environmental Engineering, Tinaztepe Campus, Buca, Izmir 35160, Turkey TI - Influence of New Year's fireworks on air quality – A case study from 2010 to 2021 in Augsburg, Germany. JO - Atmos. Pollut. Res. VL - 13 IS - 3 PB - Turkish Natl Committee Air Pollution Res & Control-tuncap PY - 2022 ER - TY - JOUR AB - In this study, the exposure to ambient particulate matter metrics (PM1, PM2.5, PM10, black carbon (BC), brown carbon (BrC), ultraviolet particulate matter (UVPM), particle number concentration (PNC), and lung deposited surface area (LDSA)) were measured along a fixed walking route with specific focus on three typical micro-environments (park, central business district (CBD), and traffic) in different time of day during the non-heating (May–Oct.) and heating (Nov.–Apr.2nd year) periods from 2018 to 2020 in the downtown Augsburg, Germany. The spatio-temporal exposure to ambient PM metrics exhibited substantial heterogeneity during the observation period, with park environment having lowest exposure and traffic area having the highest exposure. Generally, the higher LDSA concentrations were found in traffic area and CBD during the observation periods, while the lower concentrations were found in the park, which is similar with other ambient PM metrics (PMX, eUVPM, eBC, and PNC). The correlations between LDSA and other ambient PM metrics were higher during the heating than non-heating period in most of investigated environments, indicating the different PM sources. Overall, this study provides a comprehensive assessment of personal exposure that complements fixed-site ambient PM metrics measurements in the context of health risk assessment and epidemiological studies. AU - Liu, X.* AU - Hadiatullah, H.* AU - Khedr, M. AU - Zhang, X.* AU - Schnelle-Kreis, J. AU - Zimmermann, R. AU - Adam, T. C1 - 65567 C2 - 52384 TI - Personal exposure to various size fractions of ambient particulate matter during the heating and non-heating periods using mobile monitoring approach: A case study in Augsburg, Germany. JO - Atmos. Pollut. Res. VL - 13 IS - 7 PY - 2022 ER - TY - JOUR AB - Haze pollution by anthropogenic emitted particles is a frequent challenge for Beijing air quality in addition to the well-known dust storm events. Man-made air pollution is able to cause hazy conditions reducing the sight range. Since those air quality conditions became more and more frequent in Beijing recently, this paper focuses on the seasonal variability of the air quality during such haze episodes in relation to clear air situations. In order to find out the characteristics of airborne PM during haze episodes in different seasons as well as of the corresponding PM sources or air flow influences, a continuous one-year daily PM sampling from June 2010 till June 2011 was performed at the campus of the China University of Geoscience (Beijing). The inorganic elements, water-soluble ions, element carbon and organic carbon as well as levoglucosan, hopanes and PAHs were analyzed, respectively. Positive matrix factorization and back trajectory cluster analyses were applied and combined to identify and apportion sources. The results show that the main sources of particles during haze are secondary inorganic ions formations. Beyond that, different sources from season to season are obvious: biomass burning derived particles have high impact on summer and autumn haze, coal combustion is a major source for winter haze whereas mineral dust emissions are most prominent in spring haze. The sources of PM during clear days were dominated by mineral dust emissions and traffic. Nearby southerly industrial regions were found to be the main source areas of particles during haze in Beijing. AU - Shen, R.* AU - Schäfer, K.* AU - Schnelle-Kreis, J. AU - Shao, L.* AU - Norra, S.* AU - Kramar, U.* AU - Michalke, B. AU - Abbaszade, G. AU - Streibel, T.* AU - Zimmermann, R. AU - Emeis, S.* C1 - 52748 C2 - 44433 CY - Dokuz Eylul Univ, Dept Environmental Engineering, Tinaztepe Campus, Buca, Izmir 35160, Turkey SP - 627-633 TI - Seasonal variability and source distribution of haze particles from a continuous one-year study in Beijing. JO - Atmos. Pollut. Res. VL - 9 IS - 4 PB - Turkish Natl Committee Air Pollution Res & Control-tuncap PY - 2018 ER - TY - JOUR AB - Daily mass concentrations and chemical compositions (elemental carbon, organic carbon, water soluble ions, chemical elements and organic species) of PM were measured continuously in Beijing for one year from June 2010 to June 2011 (365 samples). The seasonal variation of PM mass concentration followed the order of spring 2011 > winter 2010 > summer 2010 > autumn 2010. Organic matter (OM) and secondary inorganic aerosol components (SNA: SO42-, NO3- and NH4+) were the two major fractions of PM during the whole year. Source apportionment by PMF performed on the basis of a full year of data, including both inorganic and organic species, showed that biomass burning, secondary sulfate and nitrate formation, mineral dust, industry, coal combustion and traffic were the main sources of PM in Beijing during 2010-2011. Specifically, comparison among the four seasons shows that the contribution of secondary sulfate and biomass burning, secondary nitrate formation, mineral dust, and coal combustion were the dominating sources of PM in summer, autumn, spring and winter, respectively. The contributions of industry to PM was distributed evenly in four seasons, while traffic contributed more in summer and autumn than in winter and spring. Backward trajectory analysis was applied in combination with PMF and showed that air flow from the South contributed mostly to high PM mass concentrations in Beijing. Meteorological parameters (temperature, wind speed, wind direction, precipitation and mixing layer height) influence such a variation. In general, high relative humidity and low mixing layer height can raise PM mass concentration, while high wind speed and precipitation can reduce pollutants. In addition, wind direction also plays a key role in influencing PM because different wind directions can bring different pollutants to Beijing from different regions. AU - Shen, R.* AU - Schaefer, K.* AU - Schnelle-Kreis, J. AU - Shao, L.* AU - Norra, S.* AU - Kramar, U.* AU - Michalke, B. AU - Abbaszade, G. AU - Streibel, T.* AU - Fricker, M.* AU - Chen, Y.* AU - Zimmermann, R. AU - Emeis, S.* AU - Schmid, H.P.* C1 - 48402 C2 - 41076 CY - Buca SP - 235-248 TI - Characteristics and sources of PM in seasonal perspective - a case study from one year continuously sampling in Beijing. JO - Atmos. Pollut. Res. VL - 7 IS - 2 PB - Turkish Natl Committee Air Pollution Res & Control-tuncap PY - 2016 ER -