Experimental and modelling studies of the adsorption of acetone on ice surfaces at temperatures around 200 K

The thermodynamics and kinetics of the adsorption of acetone on ice films as well as their dependence on ice film thickness and ice age have been studied in the temperature range T= 190 – 220 K using a coated wall flow tube reactor (CWFT) coupled with QMS detection. A kinetic model has been developed in order to describe the adsorption and desorption kinetics of acetone on ice surfaces in tubular flow reactors. The rate coefficients for adsorption and desorption as well as adsorption isotherms have been derived by applying the model to the temporal profiles of the gas phase concentration at the exit of the flow reactor. It was found that acetone adsorption is entirely reversible and that the adsorption capacity depends on temperature and film thickness and decreases with the age of the ice film. The time constant of the ageing effect depends on the ice mass and is most pronounced at low acetone gas phase concentrations ( 2.0 x 1011 molecules/cm3) and at low temperatures. It is suggested that under these conditions acetone is initially adsorbed with a high rate and high surface coverage on cubic ice (Ic) adsorption sites. Upon ageing cubic ice is converted into hexagonal ice (Ih) for which the rate of adsorption and the surface coverage are lower. Using two-site dynamic modelling the rate coefficients for adsorption (kads) and desorption (kdes) as well as the Langmuir constant (KL) and the maximum number of adsorption sites (cs,max) as obtained for the adsorption of acetone on each of these ice phases in the respective temperature range are kads(Ic) = 3.8 x 10-14 T0.5 cm3s-1, kdes(Ic) = 4.0x1011 exp(-5773/T) s-1, KL(Ic) = 6.3x10-25 exp(5893/T) cm3, cs,max(Ic) 1014 cm-2 and kads(Ih) = 2.9 x 10-15 T0.5 cm3s-1, kdes(Ih) = 1.5x107 exp(-3488/T) s-1, KL(Ih) = 5.0x10-22 exp(3849/T) cm3, cs,max(Ih) = 6.0x1014 cm-2, respectively. The cs,max (Ih) and cs,max (Ic) were found to be dependent on ice thickness, however cs,max (Ic) is relative lab time and temperature dependent as well

METER.AC: Live Open Access Atmospheric Monitoring Data for Bulgaria with High Spatiotemporal Resolution

Detailed atmospheric monitoring data are notoriously difficult to obtain for some geographic regions, while they are of paramount importance in scientific research, forecasting, emergency response, policy making, etc. We describe a continuously updated dataset, METER.AC, consisting of raw measurements of atmospheric pressure, temperature, relative humidity, particulate matter, and background radiation in about 100 locations in Bulgaria, as well as some derived values such as sea-level atmospheric pressure, dew/frost point, and hourly trends. The measurements are performed by low-power maintenance-free nodes with common hardware and software, which are specifically designed and optimized for this purpose. The time resolution of the measurements is 5 min. The short-term aim is to deploy at least one node per 100 km2, while uniformly covering altitudes between 0 and 3000 m asl with a special emphasis on remote mountainous areas. A full history of all raw measurements (non-aggregated in time and space) is publicly available, starting from September 2018. We describe the basic technical characteristics of our in-house developed equipment, data organization, and communication protocols as well as present some use case examples. The METER.AC network relies on the paradigm of the Internet of Things (IoT), by collecting data from various gauges. A guiding principle in this work is the provision of findable, accessible, interoperable, and reusable (FAIR) data. The dataset is in the public domain, and it provides resources and tools enabling citizen science development in the context of sustainable development

Architecture and Data Knowledge of the Regional Data Center for Intelligent Agriculture

The main task of the National Research Program “Smart crop production”, supported by the Ministry of Education and Science of Bulgaria and approved by the Council of Ministers, is the development of a regional data center to facilitate the work of farmers. The regional data center is part of the implementation of a smart crop production environment called ZEMEL which provides personal assistants supporting the work of farmers. The environment provides intelligent services for crop analysis and prevention and assists farmers in performing basic tasks related to crop production. The objective of the proposed article is to present the implementation of the architecture, infrastructure, and data architecture of a regional data center in the Plovdiv region. In order to clearly present the results of this work, which are the architectural and physical implementations of a regional data center and the storage of dynamic data and background knowledge, a methodology consisting of several steps is followed: the system infrastructure of the data center and the data architecture are discussed; one of the local pieces of infrastructure, implemented in the Institute of Plant Genetic Resources (IPGR) in the town of Sadovo in the Plovdiv region, is presented in detail, including the different types of sensors and their connection to the data center in wheat cultivation; the data repositories are discussed where dynamic data and background knowledge are stored. The paper pays special attention to background knowledge developed as ontologies for winter wheat cultivation. The results are summarized by drawing some conclusions and recommendations for the design of the local infrastructure of the center and the stored data to improve its performance