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The study focuses on the application of a dynamic ammonia emission into the Weather Research and Forecasting Chemistry model (WRF-Chem) and the influence on the simulated ammonia concentrations and the overall model performance. We have focused on agricultural ammonia sources and have analysed both hourly and daily patterns of ammonia emissions and concentrations at measurement sites located in agricultural areas or influenced by this activity. For selected episodes, we have also investigated the 3-D patterns of the ammonia concentrations in the atmosphere. The application of the dynamic ammonia emission into the WRF-Chem model (the "DYNAMIC" simulation) results in an improvement of the modelled daily ammonia concentrations in comparison to a static approach (the "BASE" simulation), which is currently widely used in chemical transport models. In the case of hourly resolution, we have observed an improvement for the DYNAMIC approach for the winter and autumn seasons, but for the entire year the modelled hourly ammonia peaks are shifted toward the afternoon hours if compared with measurements. This study indicates that the current description of the diurnal cycle of the ammonia concentration from fields is not accurate and more research is needed in order to improve the processes that describe the emission from fertilised fields. The results suggest that the governing processes in relation to the diurnal cycle are the atmospheric mixing and the emission strength. Therefore, an improved description of the diurnal profile of ammonia concentrations within atmospheric models requires a better description of the planetary boundary layer height and a stronger daily pattern of ammonia emission, e.g. through increased evaporation or increased fluxes from the surface. [ABSTRACT FROM AUTHOR]

A Europe-wide dynamic ammonia (NH3) emissions model has been applied for one of the large agricultural countries in Europe, and its sensitivity on the distribution of emissions among different agricultural functions was analysed by comparing with observed ammonia concentrations and by implementing all scenarios in a chemical transport model (CTM). The results suggest that the dynamic emission model is most sensitive to emission from animal manure, in particular how animal manure and its application on fields is connected to national regulations. In contrast, the model is most robust with respect to emission from buildings and storage. To incorporate the national regulations, we obtained activity information on agricultural operations at the sub-national level for Poland, information about infrastructure on storages, and current regulations on manure practice from Polish authorities. The information was implemented in the existing emission model and was connected directly with the NWP calculations from the Weather Research and Forecasting model (WRF-ARW). The model was used to calculate four emission scenarios with high spatial (5 km x 5 km) and temporal resolution (3 h) for the entire year 2010. In the four scenarios, we have compared the Europe-wide default model settings against (1) a scenario that focuses on emission from agricultural buildings, (2) the existing emission method used in WRF-Chem in Poland, and (3) a scenario that takes into account Polish infrastructure and agricultural regulations. The ammonia emission was implemented into the CTM FRAME and modelled ammonia concentrations was compared with measurements. The results suggest that the default setting in the dynamic model is an improvement compared to a non-dynamical emission profile. The results also show that further improvements can be obtained on the national scale by replacing the default information on manure practice with information that is connected with local practice and national regulations. Implementing a dynamical approach for simulation of ammonia emission is a viable objective for all CTM models that continue to use fixed emission profiles. Such models should handle ammonia emissions in a similar way to other climate-dependent emissions (e.g. biogenic volatile organic compounds). Our results, compared with previous results from the DEHM and the GEOS-CHEM models, suggest that implementing dynamical approaches improves simulations in general, even in areas with limited information about the location of the agricultural fields, livestock and agricultural production methods such as Poland. [ABSTRACT FROM AUTHOR]

The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) has been applied to model the spatial distribution of nitrogen deposition and air concentration over the UK at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1km data. High resolution plots were found to represent a more physically realistic distribution of nitrogen air concentrations and deposition resulting from use of 1km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution. [ABSTRACT FROM AUTHOR]

Air pollution poses a significant risk to both human health and the environment in the contemporary world. Among the various pollutants, particulate matter with a diameter <2.5 μm (PM 2.5 ) is regarded as the most hazardous. It has been implicated in over four million global fatalities in 2019 alone. This research paper divulges the outcomes of modelling the spatial-temporal fluctuations of PM 2.5 concentrations within the confines of Wroclaw, a city situated in Poland, Central Europe. The model's output was evaluated through comparison with collected data from two government-operated monitoring stations within the city. For this study, we used the ADMS-Urban model and tested two different sources of background data (low-cost sensors and the EMEP MSC-W atmospheric chemistry transport model). The statistical analysis conducted in the paper indicates that the model reproduces the temporal variability of PM 2.5 . The conclusions from this research indicate that the average annual PM 2.5 concentration within Wroclaw is 13.8 μg/m 3 , with the concentration peaking in the month of March. The spatial distribution reveals the highest PM 2.5 concentrations primarily in the southern and western zones of the city, with additional elevated concentrations observed sporadically throughout the city. The study unveils that 1.3 % of Wroclaw's area experiences PM 2.5 concentrations exceeding the EU's annual limit of 20 μg/m 3 . When considered in relation to the WHO's suggested annual average level of 5 μg/m 3 , Wroclaw city experiences exceedances throughout. When background concentrations are excluded from the model, the annual average PM2.5 concentration across the city is noted to be reduced by >50 %. A thorough investigation of the city's emission structure, taking into account only emissions from the city without background, indicates that the residential sector contributes about 77.3 % of the total annual average PM 2.5 concentration in Wroclaw. The transportation and industrial sectors account for nearly 19.5 % and 3.2 %, respectively., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Air pollution originating from the household presents a significant burden to public health, especially during the wintertime in countries, such as Poland, where coal substantially contributes to the energy market. One of the most hazardous components of particulate matter is benzo(a)pyrene (BaP). This study focusses on the impact of different meteorological conditions on BaP concentrations in Poland and associated impacts on human health and economic burdens. For this study, we used the EMEP MSC-W atmospheric chemistry transport model with meteorological data from the Weather Research and Forecasting model to analyze the spatial and temporal distribution of BaP over Central Europe. The model setup has two nested domains, with the inner domain at 4 km × 4 km over Poland, which is a hotspot for BaP concentrations. The outer domain covers countries surrounding Poland in coarser resolution (12 × 812 km), to ensure that transboundary pollution is properly characterized in the modelling. We investigated the sensitivity to variability in winter meteorological conditions on BaP levels and impacts using data from 3 years: 1) 2018, which represents average meteorological conditions during the winter season (BASE run), 2) 2010 with a cold winter (COLD), and 3) 2020 with a warm winter (WARM). The ALPHA-RiskPoll model was used to analyze the lung cancer cases and associated economic costs. The results show that the majority of Poland exceeds the target level of benzo(a)pyrene (1 ng m -3 ) mainly due to high concentrations during the cold months. High concentrations of BaP have serious health implications and the number of lung cancers in Poland due to BaP exposure varies from 57 to 77 cases for the WARM and COLD years, respectively. It is reflected in the economic costs, which ranged from 136, through 174 to 185 million euros/year for the WARM, BASE and COLD model runs, respectively., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

We analyse the impact of ground-based data assimilation to the Weather Research and Forecasting (WRF) meteorological model on parameters relevant for birch pollen emission calculations. Then, we use two different emission databases (BASE - no data assimilation, OBSNUD - data assimilation for the meteorological model) in the chemical transport model and evaluate birch pollen concentrations. Finally, we apply a scaling factor for the emissions (BASE and OBSNUD), based on the ratio between simulated and observed seasonal pollen integral (SPIn) to analyse its impact on birch concentrations over Central Europe. Assimilation of observational data significantly reduces model overestimation of air temperature, which is the main parameter responsible for the start of pollen emission and amount of released pollen. The results also show that a relatively small bias in air temperature from the model can lead to significant differences in heating degree days (HDD) value. This may cause the HDD threshold to be attained several days earlier/later than indicated from observational data which has further impact on the start of pollen emission. Even though the bias for air temperature was reduced for OBSNUD, the model indicates a start for the birch pollen season that is too early compared to observations. The start date of the season was improved at two of the 11 stations in Poland. Data assimilation does not have a significant impact on the season's end or SPIn value. The application of the SPIn factor for the emissions results in a much closer birch pollen concentration level to observations even though the factor does not improve the start or end of the pollen season. The post-processing of modelled meteorological fields, such as the application of bias correction, can be considered as a way to further improve the pollen emission modelling., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

In recent years, allergies due to airborne pollen allergens have shown an increasing trend, along with the severity of allergic symptoms in most industrialized countries, while synergism with other common atmospheric pollutants has also been identified as affecting the overall quality of citizenly life. In this study, we propose the state-of-the-art WRF-Chem model, which is a complex Eulerian meteorological model integrated on-line with atmospheric chemistry. We used a combination of the WRF-Chem extended towards birch pollen, and the emission module based on heating degree days, which has not been tested before. The simulations were run for the moderate season in terms of birch pollen concentrations (year 2015) and high season (year 2016) over Central Europe, which were validated against 11 observational stations located in Poland. The results show that there is a big difference in the model's performance for the two modelled years. In general, the model overestimates birch pollen concentrations for the moderate season and highly underestimates birch pollen concentrations for the year 2016. The model was able to predict birch pollen concentrations for first allergy symptoms (above 20 pollen m -3 ) as well as for severe symptoms (above 90 pollen m -3 ) with probability of detection at 0.78 and 0.68 and success ratio at 0.75 and 0.57, respectively for the year 2015. However, the model failed to reproduce these parameters for the year 2016. The results indicate the potential role of correcting the total seasonal pollen emission in improving the model's performance, especially for specific years in terms of pollen productivity. The application of chemical transport models such as WRF-Chem for pollen modelling provides a great opportunity for simultaneous simulations of chemical air pollution and allergic pollen with one goal, which is a step forward for studying and understanding the co-exposure of these particles in the air.

Large-scale synoptic conditions are able to transport considerable amounts of airborne particles over entire continents by creating substantial air mass movement. This phenomenon is observed in Europe in relation to highly allergenic ragweed (Ambrosia L.) pollen grains that are transported from populations in Central Europe (mainly the Pannonian Plain and Balkans) to the North. The path taken by atmospheric ragweed pollen often passes through the highly industrialised mining region of Silesia in Southern Poland, considered to be one of the most polluted areas in the EU. It is hypothesized that chemical air pollutants released over Silesia could become mixed with biological material and be transported to less polluted regions further North. We analysed levels of air pollution during episodes of long-distance transport (LDT) of ragweed pollen to Poland. Results show that, concomitantly with pollen, the concentration of air pollutants with potential health-risk, i.e. SO 2 , and PM 10 , have also significantly increased (by 104% and 37%, respectively) in the receptor area (Western Poland). Chemical transport modelling (EMEP) and air mass back-trajectory analysis (HYSPLIT) showed that potential sources of PM 10 include Silesia, as well as mineral dust from the Ukrainian steppe and the Sahara Desert. In addition, atmospheric concentrations of other allergenic biological particles, i.e. Alternaria Nees ex Fr. spores, also increased markedly (by 115%) during LDT episodes. We suggest that the LDT episodes of ragweed pollen over Europe are not a "one-component" phenomenon, but are often related to elevated levels of chemical air pollutants and other biotic and abiotic components (fungal spores and desert dust)., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The objective of this paper is to empirically show that estimates of wind speed and wind direction based on measurements carried out using the Pitot tubes and GNSS receivers, mounted on consumer-grade unmanned aerial vehicles (UAVs), may accurately approximate true wind parameters. The motivation for the study is that a growing number of commercial and scientific UAV operations may soon become a new source of data on wind speed and wind direction, with unprecedented spatial and temporal resolution. The feasibility study was carried out within an isolated mountain meadow of Polana Izerska located in the Izera Mountains (SW Poland) during an experiment which aimed to compare wind characteristics measured by several instruments: three UAVs (swinglet CAM, eBee, Maja) equipped with the Pitot tubes and GNSS receivers, wind speed and direction meters mounted at 2.5 and 10 m (mast), conventional weather station and vertical sodar. The three UAVs performed seven missions along spiral-like trajectories, most reaching 130 m above take-off location. The estimates of wind speed and wind direction were found to agree between UAVs. The time series of wind speed measured at 10 m were extrapolated to flight altitudes recorded at a given time so that a comparison was made feasible. It was found that the wind speed estimates provided by the UAVs on a basis of the Pitot tube/GNSS data are in agreement with measurements carried out using dedicated meteorological instruments. The discrepancies were recorded in the first and last phases of UAV flights.

We have investigated the relationship between the inflow of air masses and the ragweed pollen concentration in SW Poland (Wrocław) for a 10-year period of 2005-2014. The HYSPLIT trajectory model was used to verify whether episodes of high concentrations can be related to regions outside of the main known ragweed centres in Europe, like Pannonian Plain, northern Italy and Ukraine. Furthermore, we used two different meteorological data sets (the global GDAS data set and from the WRF mesoscale model; the meteorological parameters were: U and V wind components, temperature and relative humidity) into HYSPLIT to evaluate the influence of meteorological input on calculated trajectories for high concentration ragweed episodes. The results show that the episodes of high pollen concentration (above 20 pm -3 ) represent a great part of total recorded ragweed pollen in Wrocław, but occur rarely and not in all years. High pollen episodes are connected with air masses coming from south and south-west Europe, which confirms the existence of expected ragweed centres but showed that other centres near Wrocław are not present. The HYSPLIT simulations with two different meteorological inputs indicated that footprint studies on ragweed benefit from a higher resolution meteorological data sets.

The relationship between climate data and tick questing activity is crucial for estimation of the spatial and temporal distribution of the risk of ticks and tick-borne diseases. This study establishes correlations between selected meteorological variables provided by the Weather Research and Forecasting model (WRF) and the questing activity of Ixodes ricinus nymphs and adults on a regional scale across Lower Silesia, Poland. Application of Generalized Linear Mixed Models (GLMM), built separately for adults and nymphs, showed that solar radiation, air temperature, and saturation deficit appeared to be the meteorological variables of prime importance, whereas the wind speed was less important. However, the effect of meteorological parameters was different for adults and nymphs. The adults are also more influenced by forest cover and the percentage of forest type if compared to nymphs. The WRF model providing meteorological variables separately for each location and day of tick sampling can be useful in studies of questing activity of ticks on a regional scale., (© 2014 The Society for Vector Ecology.)

An atmospheric chemical transport model was adapted to simulate the concentration and deposition of heavy metals (arsenic, cadmium, chromium, copper, lead, nickel, selenium, vanadium, and zinc) in the United Kingdom. The model showed that wet deposition was the most important process for the transfer of metals from the atmosphere to the land surface. The model achieved a good correlation with annually averaged measurements of metal concentrations in air. The correlation with measurements of wet deposition was less strong due to the complexity of the atmospheric processes involved in the washout of particulate matter which were not fully captured by the model. The measured wet deposition and air concentration of heavy metals were significantly underestimated by the model for all metals (except vanadium) by factors between 2 and 10. These results suggest major missing sources of annual heavy metal emissions which are currently not included in the official inventory. Primary emissions were able to account for only 9%, 21%, 29%, 21%, 36%, 7% and 23% of the measured concentrations for As, Cd, Cr, Cu, Ni, Pb and Zn. A likely additional contribution to atmospheric heavy metal concentrations is the wind driven re-suspension of surface dust still present in the environment from the legacy of much higher historic emissions. Inclusion of two independent estimates of emissions from re-suspension in the model was found to give an improved agreement with measurements. However, an accurate estimate of the magnitude of re-suspended emissions is restricted by the lack of measurements of metal concentrations in the re-suspended surface dust layer., (Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.)

Integrated assessment modelling has evolved to support policy development in relation to air pollutants and greenhouse gases by providing integrated simulation tools able to produce quick and realistic representations of emission scenarios and their environmental impacts without the need to re-run complex atmospheric dispersion models. The UK Integrated Assessment Model (UKIAM) has been developed to investigate strategies for reducing UK emissions by bringing together information on projected UK emissions of SO2, NOx, NH3, PM10 and PM2.5, atmospheric dispersion, criteria for protection of ecosystems, urban air quality and human health, and data on potential abatement measures to reduce emissions, which may subsequently be linked to associated analyses of costs and benefits. We describe the multi-scale model structure ranging from continental to roadside, UK emission sources, atmospheric dispersion of emissions, implementation of abatement measures, integration with European-scale modelling, and environmental impacts. The model generates outputs from a national perspective which are used to evaluate alternative strategies in relation to emissions, deposition patterns, air quality metrics and ecosystem critical load exceedance. We present a selection of scenarios in relation to the 2020 Business-As-Usual projections and identify potential further reductions beyond those currently being planned., (© 2013.)

Atmospheric circulation and rainfall are important factors controlling the deposition of atmospheric pollutants. This paper aims to quantify the role of these factors in the deposition of sulphur and nitrogen compounds, using case studies in the United Kingdom and Poland. The FRAME model has been applied to calculate deposition for the base year (2005), dry and wet years (2003 and 2000 for the UK and 2003 and 1974 for Poland, respectively), and for years with contrasting annual wind patterns (1986 and 1996 for the UK, and 1998 and 1996 for Poland). Variation in annual wind and rainfall resulted in statistically significant changes in spatial patterns of deposition and the national deposition budget of sulphur and nitrogen compounds in both countries. The deposition budgets of S and N are 5% lower than for the reference year if the dry year is considered in both countries. For the wet year, there is an increase in country total deposition by up to 17%. Years with an increased frequency of eastern winds are associated with an increase in deposition of up to 14% in Poland and 8% in the UK. The national deposition budget is below the average for the years with high frequencies of W winds, especially for the UK (up to 13%). Wet deposition varies due to meteorological factors to a larger extent than dry deposition. In Poland, the changes in national deposition budget due to meteorological factors exceed the changes resulting from emission abatements in years 2000-2009 for nitrogen compounds. In the UK, emission abatements influence the national deposition budget to a larger extent than meteorological changes (except for NH(x)). The findings are important in relation to future climate changes, especially considering the potential increase in annual precipitation. This may lead to an increase in deposition over mountainous areas with sensitive ecosystems, where annual rainfall brings significant load of S and N. Changes in annual wind speed and frequency can modify the spatial pattern of deposition. An increased frequency of W winds will benefit both countries through reduced S and N deposition. NW areas of Poland and the UK will suffer from above-average deposition during years with enhanced easterly flow, and this may result in critical loads for acid and nitrogen deposition being exceeded over the areas that are at present sufficiently protected from acidification and eutrophication, despite the ongoing emission abatements., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Alternate forms of neuropsychological instruments are often made parallel by developing tests with similar numbers of items, formats, and psychometric properties. The present study offers an alternative approach by examining three different trail-making tests that could potentially be used as alternate forms. Over a 3-week period, the Trail Making Test of the Delis-Kaplan Executive Functioning System (DK-TMT), Comprehensive Trail Making Test (CTMT), and Connections Task (CT) were individually administered to 154 undergraduate psychology students in each of six possible orders. Consistent with hypotheses, the three tests share the same underlying factors of sequencing and shifting as alternatives to one- and three-factor models; statistical evidence is provided to support that the two-factor solution is invariant regardless of test order. These findings support the notion that three different trail-making tests can be administered without discernable practice effects, increasing the flexibility of a serial neuropsychological assessment battery.

The relative contribution of reduced nitrogen to acid and eutrophic deposition in Europe has increased recently as a result of European policies which have been successful in reducing SO(2) and NO(x) emissions but have had smaller impacts on ammonia (NH(3)) emissions. In this paper the Fine Resolution Atmospheric Multi-pollutant Exchange (FRAME) model was used to calculate the spatial patterns of annual average ammonia and ammonium (NH(4)(+)) air concentrations and reduced nitrogen (NH(x)) dry and wet deposition with a 5 km × 5 km grid for years 2002-2005. The modelled air concentrations of NH(3) and dry deposition of NH(x) show similar spatial patterns for all years considered. The largest year to year changes were found for wet deposition, which vary considerably with precipitation amount. The FRAME modelled air concentrations and wet deposition are in reasonable agreement with available measurements (Pearson's correlation coefficients above 0.6 for years 2002-2005), and with spatial patterns of concentrations and deposition of NH(x) reported with the EMEP results, but show larger spatial gradients. The error statistics show that the FRAME model results are in better agreement with measurements if compared with EMEP estimates. The differences in deposition budgets calculated with FRAME and EMEP do not exceed 17% for wet and 6% for dry deposition, with FRAME estimates higher than for EMEP wet deposition for modelled period and lower or equal for dry deposition. The FRAME estimates of wet deposition budget are lower than the measurement-based values reported by the Chief Inspectorate of Environmental Protection of Poland, with the differences by approximately 3%. Up to 93% of dry and 53% of wet deposition of NH(x) in Poland originates from national sources. Over the western part of Poland and mountainous areas in the south, transboundary transport can contribute over 80% of total (dry + wet) NH(x) deposition. The spatial pattern of the relative contribution of national sources to total deposition of NH(x) may change significantly due to the general circulation of air., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Poland has one of the largest sulfur and nitrogen emissions in Europe. This is mainly because coal is a main fuel in industrial and nonindustrial combustion. The aim of this paper is to assess the amount of sulfur and nitrogen deposited from SNAP sector 02 (nonindustrial sources) coal combustion. To assess this issue, the Fine Resolution Atmospheric Multipollutant Exchange (FRAME) model was used. The results suggest that industrial combustion has the largest impact on deposition of oxidized sulfur, whereas the oxidized nitrogen national deposition budget is dominated by transboundary transport. The total mass of pollutants deposited in Poland, originating from nonindustrial coal combustion, is 45 Gg of sulfur and 2.5 Gg of nitrogen, which is over 18% of oxidized sulfur and nearly 2% of oxidized nitrogen deposited. SNAP 02 is responsible for up to 80% of dry-deposited sulfur and 11% of nitrogen. The contribution to wet deposition is largest in central Poland in the case of sulfur and in some areas can exceed 11%. For oxidized nitrogen, nonindustrial emissions contribute less than 1% over the whole area of Poland. The switch from coal to gas fuel in this sector will result in benefits in sulfur and nitrogen deposition reduction.