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5 results for “Krakow”
Methane isotopes in Krakow, Poland
<p>IRMS measurement time series, CHIMERE modelled time series, sampled source signatures.</p> <p>Please refer to the following article: Menoud, M., van der Veen, C., Necki, J., Bartyzel, J., Szénási, B., Stanisavljević, M., Pison, I., Bousquet, P., Röckmann, T., 2021. Methane (CH4) sources in Krakow, Poland: insights from isotope analysis. Atmos. Chem. Phys. In press.</p>
The Krakow Paradigm - fMRI datasets in BIDS format
<p><strong>Participants</strong></p> <p>Forty-nine participants (mean age, 24.2 ± 3.7 years; 16 males) met the following experiment requirements: no contraindication for MRI scanning; normal or corrected-to-normal vision; no reported physical or psychiatric disorders; drug-free. To ensure sufficient experience in the environment, subjects had to be Krakow residents for at least one year. Subjects lived in Krakow on average 9.1 years (SD 8.1).</p> <p>Participants were informed about the procedure and goals of the study and they gave written consent. The study was approved by the bioethics commission at the Polish Military Institute of Aviation Medicine and was conducted in accordance with ethical standards described in the Declaration of Helsinki. The study was a part of a larger registered project (ISRCTN 18109340). </p> <p><strong>Experimental Task</strong></p> <p>A novel place recognition task, the Krakow Paradigm, was prepared and generated using E-Prime 2.0 (©Psychology Software Tools). The task comprised of two stages: the training session and the fMRI session. Before the training session, subjects were presented with a map of Krakow city on which a thick red line marked the city “center” area and were asked to familiarize with the borders. </p> <p>The trial comprised of the stimulus (4.5 sec duration) and two response screens (each 1.0 sec duration), all separated by the blank screens (each 0.5 sec duration). The stimulus was a photograph taken in the Krakow city (resolution 640 x 428), presenting either characteristic landmarks (e.g. an Old Square) or uncharacteristic outside places (e.g. a playground near an estate community). Photograph was presented centrally on the light-gray background and covered 60% of the screen. On the first response screen, the question “Krakow Center?” occurred with three possible answers (‘yes’, ‘no’, ‘I don’t know’) given by pressing a button on a key-pad with right-hand index, middle, or ring finger respectively. On the second response screen, the question “Have you seen it in real-life?” occurred with two possible answers (‘yes’, ‘no’) given by pressing a button using index or middle finger respectively. For both questions, responses were recorded for 1.5 sec. Between the stimuli, a fixation point (a hash sign) was presented for a varying interval between 2.4 and 6.6 sec every 0.7 sec (on average total trial length = 12 sec). Total scan time was less than 13 minutes.</p> <p>The training session was conducted to ensure timely responses. It was comprised of 7 trials, different than those used in the fMRI session, and was presented on regular computer screen. The fMRI session included 60 trials and was presented using the VisualSystem HD (NordicNeuroLab, Bergen, Norway) binocular apparatus. 50% of the photos were taken in the “center” and 50% outside of it. Characteristic and uncharacteristic places were counterbalanced across both location possibilities. At the end of the task, a feedback information was given to participants informing them the percentage of correctly classified places. Because participants were instructed to wait until the response screen appeared before making a response, reaction times are not informative and were not reported. The rationale for this procedure was to promote accuracy rather than speed, and to encourage response preparation, i.e. memory retrieval, while looking at a photo.</p> <p><strong>MRI Data Acquisition</strong></p> <p>MRI was performed using a 3T scanner (Magnetom Skyra, Siemens) with a 20-channel head/neck coil. High-resolution, whole-brain anatomical images were acquired using a T1-MPRAGE sequence. A total of 176 sagittal slices were obtained (voxel size 1×1×1.1 mm3; TR = 2300 ms, TE = 2.98 ms, flip angle = 9°) for co-registration with the fMRI data. Next, a B0 inhomogeneity gradient fieldmap (magnitude and phase images) was acquired with a dual-echo gradient-echo sequence, matched spatially with fMRI scans (TE1 = 4.92 ms, TE2 = 7.38 ms, TR = 400 ms).</p> <p>Functional T2*-weighted images were acquired using a whole-brain echo planar (EPI) pulse sequence with the following parameters: 3 mm isotropic voxel; TR = 2070 ms; TE = 30 ms; flip angle = 90°; FOV 224 × 224 mm2; GRAPPA acceleration factor 2; and phase encoding A/P. Due to magnetic saturation effects, the first four volumes (dummy scans) of each session were discarded instantly resulting in 360 volumes acquired for each participant.</p>
Organic aerosol sources in Krakow, Poland, before implementation of a solid fuel residential heating ban
<p>Krakow is a pollution hot-spot in Europe which is thought to be caused mainly by a high use of coal combustion (power plants, residential heating). Here, we quantify the impact of coal burning on air quality in the city of Krakow before the use of solid fuels for residential heating was banned within the city of Krakow. The particulate matter (PM) was collected on 126 24-hour filter samples (January to September, both PM<sub>1</sub> and PM<sub>10</sub>, i.e., with an aerodynamic diameter smaller than 1 µm and 10 µm, respectively) and analyzed with an aerosol mass spectrometer and the sources of the organic aerosol (OA) quantified. Secondary OA (SOA) likely from residential heating was the main contributor to winter-time OA (78% in PM<sub>1</sub>, 57% in PM<sub>10</sub>) and was composed of equal parts of fossil and non-fossil emissions. Additionally, fresh solid fuel combustion emissions from residential heating contribute to OA during winter (coal combustion OA (CCOA): 12%, biomass burning OA (BBOA): 3%). While BBOA contributed substantially to water-soluble OA, COOA was found to be water-insoluble and thus not identified as part of water-soluble OA. Together with the fairly low water-solubility of WOOA (29%), this leads to a low overall water-solubility of organic carbon during winter (35%). In contrast, spring and summer were characterized by more soluble organic carbon (71% in PM<sub>1</sub>, 55% in PM­<sub>10</sub>) which was dominated by biogenic sources (non-fossil), i.e., fine biogenic secondary oxygenated OA (summer oxygenated OA (SOOA): 35% in PM<sub>1</sub>) and coarse primary biological OA (PBOA: 54% in PM<sub>10</sub>). Overall, here we provide information on OA’s sources needed to evaluate the success of mentioned efforts to improve air quality in Krakow in future studies.</p>
Highly time-resolved measurements of element concentrations in PM10 and PM2.5: Comparison of Delhi, Beijing, London, and Krakow
<p>Data presented in the manuscript "Highly time-resolved measurements of element concentrations in PM10 and PM2.5: Comparison of Delhi, Beijing, London, and Krakow" (https://doi.org/10.5194/acp-2020-618) by Rai et al. (2020).</p>
Characterization of NR-PM1 and source apportionment of organic aerosol in Krakow, Poland
<p>Krakow is routinely affected by very high air pollution levels, especially during the winter months. Although a lot of effort has been done on characterization of ambient aerosols, there is a lack of online and long-term measurements of non-refractory aerosols. Our measurements at AGH University provide online long-term chemical composition of ambient submicron particulate matter (PM<sub>1</sub>) between January 2018 and April 2019. Here we report the chemical characterization of non-refractory submicron aerosols and source apportionment of the organic fraction by positive matrix factorization (PMF). In contrast to other long-term source apportionment studies, we let a small PMF window roll over the dataset instead of performing PMF over the full dataset or on separate seasons. In this way, the seasonal variation of the source profiles can be captured. The uncertainties of the PMF solutions are addressed by the bootstrap resampling strategy and the random <em>a</em>-value approach for constrained factors.</p> <p>We observe clear seasonal patterns in concentration and composition of PM<sub>1</sub>, with high concentrations during the winter months and lower concentrations during the summer months. Organics are the dominant species throughout the campaign. Five organic aerosol (OA) factors are resolved, of which three are of primary nature (hydrocarbon-like OA (HOA), biomass burning OA (BBOA) and coal combustion OA (CCOA)) and two are of secondary nature (more oxidized oxygenated OA (MO-OOA) and less oxidized oxygenated OA (LO-OOA)). While HOA contributes on average 8.6 % ± 2.3 % throughout the campaign, the solid fuel combustion related BBOA and CCOA show a clear seasonal trend with average contributions of 10.4 % ± 2.7 % and 14.1 %, ± 2.1 % respectively. Not only BBOA but also CCOA is associated with residential heating because of the pronounced yearly cycle where the highest contributions are observed during wintertime. Throughout the campaign, the OOA can be separated into MO-OOA and LO-OOA with average contribution of 38.4 % ± 8.4 % and 28.5 % ± 11.2 %, respectively. </p>
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