TY  - JOUR
AB  - Due to their affinity to water, physical-chemical properties of aerosol particles depend highly on the ambient relative humidity (RH). Aerosol drying below 40% RH is recommended to minimize measurement artifacts, increase data quality, and make results from different environments comparable. Diffusion dryers (DD) are one of the most frequently used tools to lower RH in sampled air. This work presents a custom-built DD, its design, construction, and application. By using readily available materials and 3D printing, we were able to manufacture a high-quality, cost-effective DD that can be used in various measurement scenarios (e.g., long-term measurements, intensive field campaigns, laboratory studies, and applications with low-cost sensors). The DD is equipped with ports for desiccant regeneration using clean and dry air, eliminating the need for desiccant removal from the dryer. The field tests of the proposed DD showed that it could reduce RH from ambient 65% to < 5 and 15% at flow rates of 2.5 and 8.0 L min–1, respectively. The transmission efficiency (TE) of 10–20 nm and > 20 nm aerosol particles is between 60–80% and > 80%, respectively. The presented DD is easily scalable, thus, can be adapted for multiple applications at a low cost without compromising the data quality.
AU  - Kecorius, S.
AU  - Madueno, L.*
AU  - Sues, S.
AU  - Cyrys, J.
AU  - Lovrić, M.*
AU  - Pöhlker, M.*
AU  - Plauškaite, K.*
AU  - Davulienė, L.*
AU  - Minderytė, A.*
AU  - Byčenkiene, S.*
C1  - 70166
C2  - 55222
CY  - Chaoyang Univ Tech, Dept Env Eng & Mgmt, Prod Ctr Aaqr, No 168, Jifong E Rd, Wufong Township, Taichung County, 41349, Taiwan
TI  - Development of a cost-effective adsorption dryer for high-quality aerosol sampling.
JO  - Aerosol Air Qual. Res.
VL  - 24
IS  - 3
PB  - Taiwan Assoc Aerosol Res-taar
PY  - 2024
SN  - 1680-8584
ER  - 

TY  - JOUR
AB  - This study aims to improve the generalisation capabilities of machine learning models for modelling hourly air pollutant concentrations in scenarios where access to high-quality data is limited. A diverse set of techniques was implemented to tackle this challenge, encompassing the utilisation of the prophet, random forest, and three different deep learning architectures: long short-term memory networks, convolutional neural networks, and multilayer perceptrons. A hybrid model of random forest and prophet was also tested. The role of the hybrid model was to combine the forecasting strengths of the Prophet model with the predictive power of the Random Forest model to better capture complex temporal patterns in the data. After testing, the hybrid model demonstrated improved generalization capabilities, achieving statistically significant improvements in R 2 for hourly concentrations of NO (improving by 26%), NO2 (enhancing by 18%), PM10 (with changes ranging from an 8% decline to a 35% improvement), and O3 (showcasing R 2 coefficients ranging from 0.83 to 0.87) at five sites in Graz, Austria. The utilisation of surface atmospheric ERA5-Land datasets within the models as model features showed high feature post hoc importance in the best (hybrid) models per pollutant and site. Furthermore, error analysis was performed to understand better the conditions under which these models might fail. The results showed that despite the expectations for models to fail with an increasing timeframe (the test set) from March 2019 to March 2020, the models were sufficiently stable for long-term prediction and thus can be used to forecast and predict air pollution.
AU  - Petric, V.*
AU  - Hussain, H.*
AU  - Casni, K.*
AU  - Vuckovic, M.*
AU  - Schopper, A.*
AU  - Andrijic, Z.U.*
AU  - Kecorius, S.
AU  - Madueno, L.*
AU  - Kern, R.*
AU  - Lovrić, M.*
C1  - 73265
C2  - 56820
CY  - Chaoyang Univ Tech, Dept Env Eng & Mgmt, Prod Ctr Aaqr, No 168, Jifong E Rd, Wufong Township, Taichung County, 41349, Taiwan
TI  - Ensemble machine learning, deep learning, and time series forecasting: Improving prediction accuracy for hourly concentrations of ambient air pollutants.
JO  - Aerosol Air Qual. Res.
VL  - 24
IS  - 12
PB  - Taiwan Assoc Aerosol Res-taar
PY  - 2024
SN  - 1680-8584
ER  - 

TY  - JOUR
AB  - In the complex situation with the plurality of emissions, the important research task of assessing the air quality and potential sources through aerosol composition analyses remains for Moscow's megacity environment. The light absorption, PM10 mass concentration, aerosol composition, and meteorological parameters in this urban background were measured during spring 2017, a period characterized by significant changes in the air temperature, mass advection, and solar radiation. The organic and elemental carbon (OC and EC) and 76 organic compounds, e.g., alkanes, polycyclic aromatic hydrocarbons (PAHs), oxidized PAHs, hopanes, anhydrosugars, polyols, primary and secondary saccharides, and HULIS, as well as 13 ions, including K+, a marker of biomass burning, have been quantified to determine the carbonaceous and inorganic chemical profiles of the aerosol. The correlation between the absorption Angstrom exponent (AAE) and the levoglucosan concentration reveals the relative contributions of agricultural fires and residential biomass burning (BB) nearby to the urban aerosol composition. Combining detailed analytical and statistical approaches, we have identified and analyzed the specific chemical compounds that most accurately represent the variability of the aerosol composition. Principal component analysis (PCA) highlights the main factors for marker species related to gasoline/diesel traffic, BB, biogenic activity, and secondary formation in the atmosphere. Distinguishing the BB-affected periods allows us to evaluate daily changes in the aerosol composition in relation to the transported air masses and detected fires in the areas surrounding Moscow.
AU  - Popovicheva, O.*
AU  - Padoan, S.
AU  - Schnelle-Kreis, J.
AU  - Nguyen, D.-L.
AU  - Adam, T.
AU  - Kistler, M.*
AU  - Steinkogler, T.*
AU  - Kasper-Giebl, A.*
AU  - Zimmermann, R.
AU  - Chubarova, N.*
C1  - 58848
C2  - 48387
CY  - Chaoyang Univ Tech, Dept Env Eng & Mgmt, Prod Ctr Aaqr, No 168, Jifong E Rd, Wufong Township, Taichung County, 41349, Taiwan
SP  - 702-719
TI  - Spring aerosol in the urban atmosphere of a megacity: Analytical and statistical assessment for source impacts.
JO  - Aerosol Air Qual. Res.
VL  - 20
IS  - 4
PB  - Taiwan Assoc Aerosol Res-taar
PY  - 2020
SN  - 1680-8584
ER  - 

TY  - JOUR
AB  - In 2014, Pha Din (1466 m a.s.l.) was established as a Global Atmosphere Watch (GAW) regional station for aerosol and trace gas measurements in northwestern Vietnam. This study presents a five-year climatology of aerosol optical properties derived from nephelometer and aethalometer measurements and a comparison with ground-based remote sensing measurements at the nearby AERONET station Son La. The annual variations of the aerosol measurements at Pha Din are clearly dominated by annually recurring periods with high biomass burning activity in northern Southeast Asia (February– May). During these periods, the majority of air masses arriving at Pha Din originate from the southwest (northern Thailand, Laos and Myanmar). Both the meteorological conditions and the aerosol optical properties are very similar during the individual high biomass burning periods (increased temperature: > 20°C; moderate ambient relative humidity: 60–70%; decreased single scattering albedo: 0.8–0.9; increased absorption Ångström exponent: 1.6–2.0; and scattering Ångström exponent significantly larger than 1). Prior to the biomass burning season (October–January), the meteorological conditions at Pha Din are influenced by the SE Asian monsoon, leading to a frequent transport of air masses from SW China with moderate aerosol loadings. The lowest pollution levels are observed from June to September, which represents the wet season.
AU  - Bukowiecki, N.*
AU  - Steinbacher, M.*
AU  - Henne, S.*
AU  - Nguyen, N.A.*
AU  - Nguyen, X.A.*
AU  - Hoang, A.L.*
AU  - Nguyen, D.-L.
AU  - Long, H.L.*
AU  - Engling, G.*
AU  - Wehrle, G.*
AU  - Gysel, M.*
AU  - Baltenspergeri, U.*
C1  - 56074
C2  - 46811
CY  - Chaoyang Univ Tech, Dept Env Eng & Mgmt, Prod Ctr Aaqr, No 168, Jifong E Rd, Wufong Township, Taichung County, 41349, Taiwan
SP  - 1172-1187
TI  - Effect of large-scale biomass burning on aerosol optical properties at the GAW regional station pha din, Vietnam.
JO  - Aerosol Air Qual. Res.
VL  - 19
IS  - 5
PB  - Taiwan Assoc Aerosol Res-taar
PY  - 2019
SN  - 1680-8584
ER  - 

TY  - JOUR
AB  - Nanjing has areas with different degrees of pollution and is therefore predestined for the analysis of particle phase polycyclic aromatic hydrocarbons (P-PAHs) in different functional areas and their correlation with the latter. The functional sites include a background area (BGA), an industrial area (IDA), a traffic area (TFA), a business area (BNA) and a residential area (RDA), where parameters such as PAH composition, content, carcinogenic and mutagenic potencies were analyzed. The results revealed increasing P-PAH contents (PM2.5, PM10) in the following order: BGA (14.02 ng m–3, 38.45 ng m–3) < BNA (16.33 ng m–3, 44.13 ng m–3) < TFA (17.13 ng m–3, 48.31 ng m–3) < RDA (21.11 ng m–3, 61.03 ng m–3) < IDA (50.00 ng m–3, 93.08 ng m–3). Thereby, the P-PAH content in the industrial area was significantly higher than in the other functional zones (P < 0.01). Furthermore, the gas phase PAH concentrations were also estimated by the G/P partitioning model and the total PAH toxicity was assessed applying toxicity equivalent factors (∑BaPTEF) and mutagenicity equivalent factors (∑BaPMEF). Finally, the incremental lifetime cancer risk (ILCR) value of children and adolescents in Nanjing was higher than that of adults.
AU  - Liu, X.
AU  - Schnelle-Kreis, J.
AU  - Schloter-Hai, B.
AU  - Ma, L.*
AU  - Tai, P.*
AU  - Cao, X.
AU  - Yu, C.*
AU  - Adam, T.
AU  - Zimmermann, R.
C1  - 57133
C2  - 47566
CY  - Chaoyang Univ Tech, Dept Env Eng & Mgmt, Prod Ctr Aaqr, No 168, Jifong E Rd, Wufong Township, Taichung County, 41349, Taiwan
SP  - 2294-2307
TI  - Analysis of PAHs associated with PM10 and PM2.5 from different districts in Nanjing.
JO  - Aerosol Air Qual. Res.
VL  - 19
IS  - 10
PB  - Taiwan Assoc Aerosol Res-taar
PY  - 2019
SN  - 1680-8584
ER  - 

TY  - JOUR
AB  - Many persistent organic pollutants (POPs) such as organochlorine pesticides (OCPs), which are emitted into air, occur ubiquitously in different environmental compartments worldwide. OCPs are measurable in conspicuous concentrations in the air not only near emission regions but also in background areas, as in the Alps. In the present study, we analyzed OCPs in air samples between 2005 and 2013 at three high Alpine stations (Weißfluhjoch, Switzerland: 2663 m a s l.; Sonnblick, Austria: 3106 m a s l.; and Schneefernerhaus, Germany: 2650 m a s l.). The air concentrations of OCPs at these stations were lower than those in source regions but higher than those in the Arctic region. Concentration differences between sites were found to be relatively small. To distinguish the influences from different European source regions, four filters of low- volume active air samplers were operated alternately according to a trajectory prediction method. Air masses from the northeast (i.e., Bavaria and Eastern Central Europe) and the south (i.e., Mediterranean countries) were characterized by higher concentrations of OCPs (e.g., pentachlorobenzene and hexachlorobenzene) compared with those arriving from the Atlantic Ocean. Additionally, we evaluated the temporal trend of the single compounds; only a few compounds such as endosulfan exhibited a clear decreasing trend.
AU  - Kirchner, M.
AU  - Jakobi, G.
AU  - Körner, W.*
AU  - Levy, W.
AU  - Moche, W.*
AU  - Niedermoser, B.*
AU  - Schaub, M.*
AU  - Ries, L.*
AU  - Weiss, P.*
AU  - Antritter, F.
AU  - Fischer, N.
AU  - Henkelmann, B.
AU  - Schramm, K.-W.
C1  - 48079
C2  - 39904
CY  - Taichung County
SP  - 738-751
TI  - Ambient air levels of organochlorine pesticides at three high alpine monitoring stations: Trends and dependencies on geographical origin.
JO  - Aerosol Air Qual. Res.
VL  - 16
IS  - 3
PB  - Taiwan Assoc Aerosol Res-taar
PY  - 2016
SN  - 1680-8584
ER  -