Bioaerosols in the atmosphere at two sites in Northern Europe in spring 2021: Outline of an experimental campaign.

A coordinated observational and modelling campaign targeting biogenic aerosols in the air was performed during spring 2021 at two locations in Northern Europe: Helsinki (Finland) and Siauliai (Lithuania), approximately 500 km from each other in north-south direction. The campaign started on March 1, 2021 in Siauliai (12 March in Helsinki) and continued till mid-May in Siauliai (end of May in Helsinki), thus recording the transition of the atmospheric biogenic aerosols profile from winter to summer. The observations included a variety of samplers working on different principles. The core of the program was based on 2- and 2.4--hourly sampling in Helsinki and Siauliai, respectively, with sticky slides (Hirst 24-h trap in Helsinki, Rapid-E slides in Siauliai). The slides were subsequently processed extracting the DNA from the collected aerosols, which was further sequenced using the 3-rd generation sequencing technology. The core sampling was accompanied with daily and daytime sampling using standard filter collectors. The hourly aerosol concentrations at the Helsinki monitoring site were obtained with a Poleno flow cytometer, which could recognize some of the aerosol types. The sampling campaign was supported by numerical modelling. For every sample, SILAM model was applied to calculate its footprint and to predict anthropogenic and natural aerosol concentrations, at both observation sites. The first results confirmed the feasibility of the DNA collection by the applied techniques: all but one delivered sufficient amount of DNA for the following analysis, in over 40% of the cases sufficient for direct DNA sequencing without the PCR step. A substantial variability of the DNA yield has been noticed, generally not following the diurnal variations of the total-aerosol concentrations, which themselves showed variability not related to daytime. An expected upward trend of the biological material amount towards summer was observed but the day-to-day variability was large. The campaign DNA analysis produced the first high-resolution dataset of bioaerosol composition in the North-European spring. It also highlighted the deficiency of generic DNA databases in applications to atmospheric biota: about 40% of samples were not identified with standard bioinformatic methods.

Long-term monitoring of soil bulk density and erosion rates in two Prunus Persica (L) plantations under flood irrigation and glyphosate herbicide treatment in La Ribera district, Spain.

Early season fruit production for the northern European market is highly intensive in fertilization, machinery, irrigation and the use of herbicides. Those conditions increase the soil losses and soil compaction and threaten the Sustainable Goals for Development of the United Nations by 2030. Long-term soil erosion measurements are necessary to determine the sustainability of agriculture managements. Moreover, soil erosion on flood irrigation land is a topic that request more surveys and research as rainfed sloping terrains attracted all the attention of scientists and research investment. Improved Stock Unearthing Method (ISUM) was applied to two 15 years-old herbicide treated fields of Saturn peaches (Prunus persica var. platycarpa) to determine long-term soil erosion rates (2004-2019). Using ISUM, a 1 mm thick nylon rope (700 mm length) was used to connect trees perpendicular to the direction of rows at the height of the graft. To detection soil lowering, the vertical distance of the rope to the soil surface was measured at 10 cm intervals along the rope. The ring method (264 samples at 0-6 cm) was used to determine the soil bulk density, which was in average 1.15 gr cm-3 for both plots. There was found a compaction in the centre of both plots due to the pass of machinery with mean bulk density values of 1.23 gr cm-3, meanwhile underneath of the trees, the soil bulk density was 1.05 gr cm-3. The topography survey carried out with ISUM (2508 sampling points) informed that flood irrigation redistributed the soil from the upper to the lower field position, where a sedimentation layer was measured. We found that the two studied fields showed a contrasted response, with low soil erosion values in Benimodo and high in L'Alcúdia study sites. Soil erosion rates were in average 1.46 Mg ha-1 yr-1 and 8.02 Mg ha-1 yr-1 for Benimodo and L'Alcúdia, respectively. However, the maps development using ISUM allow to inform that the pattern of soil redistribution is similar for both fields as the highest soil lowering was found in the upper field part, where the flood discharge detach soil particles. In the lower field position sedimentation takes place. The dataset allows us to conclude that soil erosion in Saturn peaches fields is non-sustainable and more soil conservation management should be applied to reduce the soil erosion rates due to the bare soils as a consequence of the use of herbicides. This research informs that soil erosion in flood irrigated fields is a relevant process that needs more investigations around the world, where 94% of the irrigated land is under flood or furrow irrigation, and where irrigation is growing year after year.

Analyzing WSTP trend: a new method for global warming assessment.

This paper tries to introduce a time-series of temperature parameters as a potential method for studying the global warming. So, we investigated the spatial-temporal variations of warm-season temperature parameters (WSTP), including start time, end time, length of season, base value, peak time, peak value, amplitude, large integrated value, right drive, and left drive, using a database of 30 years' period in different climates of Iran. We used daily temperature data from 1989 to 2018 over Iran to extract the parameters by TIMESAT software. We studied the trend analysis of WSTP through the Mann-Kendall method. Then, we considered the Pearson correlation coefficient to calculate the correlation between WSTP and time. We assessed the trends of the slope using a simple linear regression method. Then, we compared the results of the WSTP trend analysis in climatic zones. Our results accused the hyper-arid climatic zone has the longest warm season (194.89 days a year). The warm season in this region starts earlier than other regions and increases with moderate speed (left drive, 0.19 °C day-1). Then, it reaches a peak value (31.3 °C) earlier than the different climatic zones. On the other hand, the humid regions' warm season starts with the shortest length and ends later than the other climatic zones (112.1 and 297.5 days a year for start and end times, respectively). We detected that the trend of the start time parameter has decreased by 98.02% of the study area during the last 30 years. The base value, length, and large integrated value parameters have an increasing trend of 66.47%, 80.11%, and 92.95% in Iran. The highest correlation coefficient with time was for start time and large integrated value parameters. Hence, the start time and large integrated value parameters have almost the most negative (< - 0.5) and positive (> 5) trend slope, among other parameters, respectively. In general, these results demonstrate that the studied region has faced global warming impacts over time by increasing the warm season and thermal energy, especially in arid and hyper-arid. We highlight the necessity of planning the land use under the high natural vulnerability of the studied local, especially in this new age of global warming.

Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields.

We consider several approaches to a design of a regional-to-continent-scale automatic pollen monitoring network in Europe. Practical challenges related to the arrangement of such a network limit the range of possible solutions. A hierarchical network is discussed, highlighting the necessity of a few reference sites that follow an extended observations protocol and have corresponding capabilities. Several theoretically rigorous approaches to a network design have been developed so far. However, before starting the process, a network purpose, a criterion of its performance, and a concept of the data usage should be formalized. For atmospheric composition monitoring, developments follow one of the two concepts: a network for direct representation of concentration fields and a network for model-based data assimilation, inverse problem solution, and forecasting. The current paper demonstrates the first approach, whereas the inverse problems are considered in a follow-up paper. We discuss the approaches for the network design from theoretical and practical standpoints, formulate criteria for the network optimality, and consider practical constraints for an automatic pollen network. An application of the methodology is demonstrated for a prominent example of Germany's pollen monitoring network. The multi-step method includes (i) the network representativeness and (ii) redundancy evaluation followed by (iii) fidelity evaluation and improvement using synthetic data.