Abstract
Limited data on rural Poland's atmospheric ion concentrations exists, with no publicly available monitoring data in urban areas. These knowledge gaps hinder the comparison of concentrations across environments and the identification of their sources. This study examines water-soluble ions across five rural locations in Poland over four years to investigate their concentrations and sources in the atmosphere. This study explores aerosol origins, performing a four-year correlation analysis across five locations to reveal ion relationships. Notably, sulfate (SO₄2⁻), nitrate (NO₃⁻), and ammonium (NH₄⁺) exhibit significant correlations ranging from 0.3 to 0.8, suggesting a common pollution source in all analyzed rural locations. Interestingly, magnesium (Mg2⁺) and sodium (Na⁺) in two locations demonstrated a strong correlation, ranging between 0.4 and 0.9, suggesting the influence of sea spray on these sites. Principal component analysis is used to investigate the factors influencing ion concentrations, revealing distinctive patterns for each location and explaining the total variances ranging from 74.9% to 84.8%. This underscores the significance of geographical and environmental factors. The study's novelty lies in its thorough and long-term analysis of water-soluble ion concentrations across rural Poland, providing an extensive dataset for the region. The study fills a data gap on rural pollution sources and reveals consistent ion patterns across different sites and seasons. The findings emphasize geographical and environmental impacts on aerosol composition and suggest common pollution sources for all areas. This research encourages further investigations into the stability and origins of ions in rural environments, providing valuable insights for local and broader atmospheric studies.
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1 Introduction
The quality of air, both outdoors and indoors, is critical for human health and environmental well-being. Recent studies, such as the one conducted in a higher education institution classroom (Ateş & Khameneh, 2023), underscore the importance of monitoring air temperature, relative humidity, and CO₂ levels to ensure a safe and comfortable environment during educational activities. This study revealed that the air temperature and relative humidity were within acceptable comfort levels, but CO₂ concentrations often exceeded the general limit of 1,000 ppm, highlighting the need for adequate ventilation to maintain air quality. Similar principles apply to outdoor air quality, where the monitoring of water-soluble ions can provide insights into pollution sources and their impacts.
Atmospheric aerosols consist of soluble or insoluble solid and liquid particles suspended in the air, varying in size from a few nanometers to tens of microns (10−9 to 10−5 m). Their significance in the terrestrial climate system cannot be overstated, as they influence air quality and human health. For example, exposure to sulfur dioxide (SO2) and nitrogen dioxide (NO2) has been linked to respiratory problems in children, exacerbating conditions such as asthma and respiratory infections (Loukili et al., 2022). Furthermore, aerosols can scatter and absorb solar radiation and serve as cloud condensation nuclei (CCN), providing surfaces on which water vapor can condense to form cloud droplets. Natural sources of aerosols mainly include dust composed of mineral particles carried from the surface by wind, sea salts produced by sea storms and waves breaking, and organic aerosols originating from biogenic emissions (Deike et al., 2022; Ma et al., 2023; Nascimento et al., 2021). Anthropogenic aerosols, comprising sulfate, nitrate, and carbonaceous particles, primarily originate from fossil fuel combustion. SO2, a sulfate precursor, is formed through gas-phase oxidation in the atmosphere, aqueous-phase oxidation in liquid environments, and heterogeneous oxidation on aerosol surfaces. Nitrogen oxides (NOx) serve as the primary precursors for atmospheric nitrate. They are emitted into the atmosphere and subsequently form nitrate through OH oxidation. Carbonaceous aerosols result from incomplete combustion, with sources including both anthropogenic and natural processes (Bellouin & Haywood, 2020; Cao et al., 2021; Wang et al., 2022; Xin et al., 2023). The complexity of aerosols' chemical makeup arises from their diverse origins. Within these aerosols, there are numerous toxic and harmful substances that are susceptible to diverse physical and chemical transformations when introduced into the atmosphere (Su et al., 2018). Studies show that aerosols have a significant impact on global climate forcing, with their chemical composition playing a crucial role for several reasons. Their composition determines the particles' ability to absorb moisture and dissolve, which affects their size variation with changing relative humidity (RH). It is important to note that the net effect of aerosols on the climate is complex and can depend on various factors. Additionally, while some aerosols contribute to cooling effects, others, such as black carbon (soot), can have a warming influence by absorbing sunlight. Furthermore, the chemical makeup of aerosols influences their optical characteristics by affecting their refractive index (Cotterell et al., 2022; Kreidenweis & Asa-Awuku, 2014; Zhang, 2020). Moreover, the degree of hygroscopicity carries substantial implications for the process of cloud formation, which is closely linked to the indirect consequences of aerosol forcing. The chemical composition of aerosol particles varies depending on their source, making it crucial to assess contributions from different origins. Aerosols are typically categorized as primary or secondary and, as mentioned before, anthropogenic or natural, depending on how they are formed. Particles that are released directly into the atmosphere are called primary aerosols. Natural primary particles, like sea salt and dust, are typically part of the coarser fraction of atmospheric aerosols. Primary anthropogenic particles originate from various sources and can be present in both coarse and fine aerosol modes. Secondary aerosols are produced when gaseous precursors, originating from either natural or anthropogenic sources, transform into condensable material. Most of the mass of secondary aerosols is found in the fine aerosol mode. Interestingly, heterogeneous reactions on coarse particles may lead to the formation of coarse secondary aerosol material. This observation also holds significance in the case of nitrate reacting with sea salt particles and dust, as well as with ammonium. This alteration in composition affects not only the way aerosols are deposited but also their longevity and optical characteristics (Henning et al., 2003).
Environmental studies often focus on the concentration and distribution of contaminants to understand their sources and impacts. For example, a recent study on heavy metals in Ardebil, Iran examined the amount and density of zinc and lead in urban soils and found that their levels were below the Environmental Protection Agency (EPA) standards. This was attributed to the city's low population and limited vehicular use (Mostofi, 2018). Statistical analyses, including the Pearson correlation, revealed no significant relationship between heavy metal concentrations in soils and plants, highlighting the complexity of pollutant interactions in the environment. Similarly, our research aims to analyze the sources of water-soluble ions in rural areas of Poland, employing correlation analysis and principal component analysis (PCA) to identify potential links between ion concentrations and their possible sources. As important components of aerosols, water-soluble ions mainly consist of nitrates, sulfates, and ammonia salts, among others (Wang et al., 2014a, b). According to some studies (Yue et al., 2016), water-soluble ions significantly influence the quantity, size, composition, and lifetime of aerosols by self-hygroscopicity (Chyzhykov et al., 2023). In addition, they affect the formation of cloud condensation nuclei and particle size distributions. The concentration of ions such as chloride (Cl⁻), sulfate (SO₄2⁻), and nitrate (NO₃⁻) impact the acidity of atmospheric precipitation, which subsequently influences the global climate and terrestrial environment. Therefore, it is critical to understand the nature of aerosols and the impact of atmospheric aerosol particles on our environment.
The research is focused on water-soluble ion concentrations present in the atmosphere across five rural locations in Poland. While the study of last year’s water-soluble ions has garnered significant attention (Błaszczak, 2018; Cong et al., 2022; Li et al., 2018; Rogula-Kozlowska et al., 2017; Shen et al., 2012), a comprehensive analysis of atmospheric ion concentrations in Poland is lacking. Ions such as sulfate and nitrate can influence the pH of rainwater; acid rains that contain elevated levels of those ions can cause detrimental effects on ecosystems, soils, and aquatic habitats. High concentrations of water-soluble ions such as SO₄2⁻, NO₃⁻, and ammonium (NH₄⁺) are often associated with poor air quality. These ions, which are major components of particulate matter (PM2.5), can have adverse effects on human health when inhaled (Zhang et al., 2021). The determination of water-soluble ions in the atmosphere can help identify the sources of pollution. For example, elevated sulfate levels may suggest emissions from industrial processes or power plants, while high ammonium concentrations could be linked to agricultural activities or vehicular emissions (Gu et al., 2023; Olson et al., 2021). In this work, analysis of seasonal, location-dependent, and source-dependent variations in PM-bound water-soluble ion concentrations are presented together with long-term trends (four-year time span) to determine emission similarities and discrepancies. To identify their potential sources and better understand their environmental impacts, two complementary analytical methods were employed: correlation analysis and PCA. Correlation analysis was used to investigate potential relationships between different ion concentrations and various environmental factors. This method helps to identify patterns and potential causal links within the data. Principal component analysis, on the other hand, was utilized to reduce the complexity of the data by transforming it into a set of uncorrelated variables. PCA aids in pinpointing the principal sources of ions by grouping them into components based on their variances. By combining these analytical approaches, this study aims to provide a comprehensive overview of the factors influencing ion concentrations in the atmosphere of rural Poland.
This study is novel in its focus on the analysis of water-soluble ions specifically in rural areas of Poland, an area often overlooked in environmental research, which tends to prioritize urban settings. By utilizing correlation analysis and PCA, this research not only identifies potential sources of these ions but also provides a comparative perspective with urban environments. This dual approach helps to fill a significant gap in the literature, offering new insights into the atmospheric chemistry of rural areas and highlighting the differences and similarities with urban pollution patterns. Moreover, this study leverages publicly available data, demonstrating the value of existing resources in environmental monitoring and encouraging further transparency and data sharing. Currently, many studies from around the world observe different climate circumstances, particulate matter, and water-soluble ions and their sources in urban environments. However, there are not many studies that focus on rural areas, likely because data on water-soluble ion concentrations is mostly available for urban areas (Chen et al., 2019; Cheng et al., 2022; Dai et al., 2012; Rogula-Kozlowska et al., 2017; Yin et al., 2023). In Poland, data regarding water-soluble ions is only publicly available for rural areas, whereas this data for urban areas is not accessible. For this reason, it would be interesting to compare water-soluble ion concentrations from different urban locations with those from Polish rural locations.
Understanding the sources and impacts of water-soluble ions in rural areas is crucial for developing effective environmental management strategies. The role of corporate responsibility in environmental disclosure, as highlighted in recent studies, underscores the importance of transparency and stakeholder engagement in addressing environmental challenges. For instance, research by Nirwana and Wedari (2023) has shown that the presence of independent commissioners significantly influences the extent of waste and effluent disclosure by companies, emphasizing the importance of stakeholder-oriented and risk-reducing behaviors. Increasing the availability of air monitoring data regarding water-soluble ions to the public, especially for urban background sites in Poland, could further enhance this transparency and support environmental decision-making.
2 Material and Methods
2.1 Gathering Data
In this study, research data was obtained through yearly archives on the Chief Inspectorate of Environmental Protection (CIEP, GIOŚ—Główny Inspektorat Ochrony Środowiska) website. Chief Inspectorate of Environmental Protection is a Polish governmental organization that was established to ensure compliance with environmental protection regulations and to examine and assess the state of the environment. It consists of the Chief Inspectorate of Environmental Protection itself and 16 voivodeship environmental protection inspectorates. Concentrations for water-soluble ions such as calcium (Ca2⁺), Cl⁻, potassium (K⁺), magnesium (Mg2⁺), sodium (Na⁺), NH₄⁺, NO₃⁻, and SO₄2⁻ were collected from the GIOŚ website (Główny Inspektorat Ochrony Środowiska—GIOŚ, n.d). Ion concentrations in PM2.5 were measured within GIOŚ routine air monitoring across five locations: Osieczów, Bory Tucholskie, Godów, Złoty Potok, and Puszcza Borecka (Fig. 1). The PM2.5 samples for ion analysis were collected using high-volume (HVS) and low-volume (LVS) air samplers positioned at the sampling sites, elevated 1.5 m above ground level to efficiently collect air samples. By location: in Osieczów, samples were collected using HVS produced by Digitel and MCZ; in Bory Tucholskie, using HVS produced by Digitel; in Godów, using HVS produced by Digitel; in Złoty Potok, using LVS produced by MCZ; and in Puszcza Borecka, using HVS produced by Digitel. The ionic composition of PM2.5 was analyzed using the ion chromatography method, in accordance with Polish air quality monitoring standards. Anions were determined using ion chromatography, cations were determined using inductively coupled plasma optical emission spectrometry (ICP-OES) and inductively coupled plasma mass spectrometry (ICP-MS), ammonium ions were determined by continuous flow analysis (CFA).
2.2 Characteristic of the PM2.5-bound Ions Sampling Stations Working within the GIOŚ Air Monitoring Network
The first ion sampling location for this study is situated in the village of Osieczów, Lubusz Voivodeship, Poland (Fig. 2). Osieczów is a small rural settlement renowned for its picturesque countryside, characterized by forests and rolling lowlands with fertile soil, making it a good setting for agricultural activities. Osieczów is strategically located near a facility that utilizes raw quartz to produce quartz sand and quartz powder, while another nearby facility produces silica powder, kaolin, and feldspar (Quartzwerke in Poland, n.d). Aside from quartz production, Osieczów is surrounded by agricultural lands and forests. This geographic proximity is of paramount importance as it allows us to investigate the impact of emissions associated with these activities on the ion composition of the atmosphere. Measuring ions in such proximity will help to elucidate the immediate effects of these emissions on the local environment.
The second ion sampling location for this study is situated within the captivating landscape of Bory Tucholskie, Poland. Bory Tucholskie is a vast and pristine forest complex located in the Kuyavian-Pomeranian Voivodeship of northern Poland (Fig. 3). Renowned for its ecological significance, this natural reserve boasts diverse flora and fauna, with dense forests, crystal-clear lakes, and meandering rivers (Węgrzyn et al., 2020).
Bory Tucholskie is as a forest area with nearby agricultural areas, although it primarily represents an invaluable natural environment relatively untouched by industrial activities and urbanization. This pristine setting serves as an ideal reference point for assessing the baseline ion composition of a minimally-impacted atmosphere.
The third ion sampling location for this study is situated in the charming village of Godów, Poland (Fig. 4). Godów is a picturesque village nestled within the Silesian Voivodeship of southern Poland. The region is characterized by its unique blend of natural beauty and rural tranquility, with rolling hills, agricultural landscapes, and a close-knit community.
Godów and its surrounding areas are predominantly dedicated to agricultural practices, but a large coal power plant is located on the Czech side of the border (CEZ Group, n.d). Overall, the village is ideally located near agricultural activities, including crop fields and orchards, as well as facilities such as power plants, building material manufacturers, and cement producers. Furthermore, a sand pit is located on another side of the border, making it an excellent site to study the potential impact of emissions from agricultural, energy, and raw/building materials production facilities on ion concentrations in the atmosphere (Itahashi et al., 2017; Volná et al., 2022).
Złoty Potok, the fourth ion sampling location for this study, is a village that is nestled within the Silesian Voivodeship of southern Poland (Fig. 5). The region is characterized by its natural beauty, serene forests, and pristine rivers dotted around the landscape.
Złoty Potok and its surrounding areas offer a unique blend of natural landscapes, with dense forests and pristine water bodies, as well as some agricultural activity land close by. The location is quite interesting for its minimal industrial activity and urbanization, providing an ideal setting to study the seasonal changes in ion concentrations of a minimally impacted atmosphere.
Puszcza Borecka is the fifth ion sampling location for this study and it is situated within the pristine Puszcza Borecka forest complex in Poland (Fig. 6). Puszcza Borecka is a vast and ecologically significant forested area located in the Warmian-Masurian Voivodeship of northern Poland. Renowned for its biodiversity and natural beauty, this region encompasses dense forests, tranquil lakes, and a rich variety of flora and fauna.
Puszcza Borecka represents one of the last remaining undisturbed forested areas in Europe, with minimal industrial activities and urbanization. The location is a minimally impacted natural environment, providing a unique opportunity to study the baseline ion composition of an unpolluted atmosphere.
Forested areas like Puszcza Borecka play a critical role in global ecological and climate regulation, acting as carbon sinks and biodiversity hotspots. Investigating ion concentrations here contributes to our understanding of forest-atmosphere interactions, which have implications for global climate modeling.
Work at these measuring stations began on 2010–01-01 in Osieczów, 2004–05-27 in Bory Tucholskie, 2009–09-07 in Godów, 2005–01-01 in Złoty Potok, and 1994–01-01 in Puszcza Borecka. These stations take continuous measurements for each calendar year and provide hourly, daily, and monthly data, depending on the compound measured. For this study, data from the last four years (January 1, 2019 to December 31, 2022) was selected to capture seasonal variations and temporal trends in the concentration of specific ions. This period was chosen to study the seasonal trends, analyzing how meteorological conditions and atmospheric dynamics may affect ion dispersion and concentration levels. In addition, possible influences of the COVID-19 pandemic (Główny Inspektorat Ochrony Środowiska, 2021), impacts driven by energy market fluctuations, and the development and implementation of new air quality standards can be studied.
Data obtained from PM2.5 sampling and ion analyzes in Osieczów, Bory Tucholskie, Godów, Złoty Potok, and Puszcza Borecka by GIOŚ was comprehensively analyzed. This involved data processing steps such as table preparation, seasonal averaging, statistical analysis, and data visualization techniques. The resulting insights were interpreted to discern seasonal variations, ion sources, and their interactions within these unique natural environments.
2.3 Statistical Analysis Techniques Used in the Study
In this study, correlation analysis and PCA statistical techniques were employed to analyze the concentrations of water-soluble ions in five rural locations in Poland to uncover sources, patterns, and trends of the studied ions. Correlation analysis and PCA both offer valuable insights when studying water-soluble ions. Correlation analysis is straightforward and easy to interpret, making it useful for identifying relationships between ion concentrations and environmental factors. It provides quantitative measures of association, suggesting potential causal links. However, it cannot confirm causation and assumes linearity, which may not capture more complex interactions. Additionally, correlation analysis is sensitive to outliers, which can distort results. On the other hand, PCA simplifies complex data by reducing dimensionality and highlighting key patterns and trends. It helps to filter out noise and identify potential sources of ions by grouping related variables. However, interpreting principal components can be challenging, as they are linear combinations of the original variables and may not always align with known processes. Moreover, some information is inevitably lost in the dimensionality reduction process, and PCA also assumes linearity. Despite these limitations, the combined use of correlation analysis and PCA in this study provides a comprehensive understanding of the factors influencing ion concentrations in rural Poland, balancing simplicity with in-depth data analysis (Janse et al., 2021; Karamizadeh et al., 2013).
Correlation analysis was performed on the main inorganic ions, including Ca2⁺, Cl⁻, K⁺, Mg2⁺, Na⁺, NH₄⁺, NO₃⁻, and SO₄2⁻, measured over a four-year period across five distinct rural locations using Statistica software produced by StatSoft, Inc (Statistica StatSoft Polska., n.d). To gain a deeper understanding of the sources, the time variability of multiple ions was analyzed across all five locations.
Furthermore, a source identification study was conducted using PCA, which was also implemented through Statistica software produced by StatSoft, Inc. PCA is a technique employed to reduce the dimensionality of datasets, enhancing interpretability while minimizing information loss. It accomplishes this by generating new uncorrelated variables, known as principal components, that maximize variance successively. Identifying these principal components involves solving an eigenvalue/eigenvector problem, which is determined by the dataset under examination, making PCA an adaptive data analysis technique (Jolliffe & Cadima, 2016). PCA was conducted separately for each location. Eight main inorganic ions were analyzed, with three principal components extracted for each of the studied locations.
3 Results and Discussion
Concentrations of eight specific water-soluble ions in the air, including Ca2⁺, Cl⁻, K⁺, Mg2⁺, Na⁺, NH₄⁺, NO₃⁻, and SO₄2⁻, were assessed by the GIOŚ at five distinct locations across Poland. These locations were Osieczów, Bory Tucholskie, Godów, Złoty Potok, and Puszcza Borecka. Subsequently, these data were subjected to a comprehensive analysis. Interestingly, the data regarding ion concentrations are accessible to the public for only these five locations, even though the GIOŚ maintains a vast archive of data encompassing numerous cities and regions throughout Poland. Around 10,000 GIOŚ measurements were examined and the data was averaged to better illustrate seasonal variations and trends. It is crucial to analyze different seasons to detect distinct patterns of ion concentrations. For example, increased chloride levels in winter may be linked to the application of road salt for snow and ice removal (John et al., 2007), while elevated ammonium and nitrate concentrations in summer can result from agricultural activities and atmospheric reactions (Das et al., 2009; Fung et al., 2022).
The analysis of SO₄2⁻, NO₃⁻, and NH₄⁺ concentrations across multiple measuring locations presented in Figs. 7, 8, 9, 10 and 11 reveal consistent seasonal trends over the span of four years. In all locations, including Osieczów, Bory Tucholskie, Godów, Złoty Potok, and Puszcza Borecka, elevated concentrations of these ions are observed during winter seasons, attributed to increased combustion activities for heating purposes. This trend is particularly pronounced in Osieczów and Godów, where proximity to villages and industrial facilities like quartz and cement production plants, as well as a coal power plant, contributes to heightened pollutant emissions, including SO₂ and NOx. Consequently, sulfate, nitrate, and ammonium ions show peak concentrations during winters, followed by a gradual decline in spring as heating demands decrease. The concentration of these ions reaches their lowest levels in summers, coinciding with reduced heating requirements and increased uptake of ions by vegetation and soil. Autumn seasons see a rise in ion concentrations, potentially influenced by factors such as agricultural activities, including fertilizer application, and crop residue burning, as well as a resurgence of combustion activities. Notably, Godów consistently records the highest concentrations of these ions, likely due to its proximity to significant emission sources.
SO₄2⁻, concentrations of which are presented in Appendix 1 Tables 1, 2, 3, 4, 5, can be generated in the atmosphere through the oxidation of SO₂ (Zhou et al., 2023). During winter, heightened heating demands lead to increased combustion of fossil fuels, releasing SO₂ (Yadav et al., 2022). This sulfur dioxide undergoes oxidation, forming sulfate aerosols that contribute to elevated sulfate concentrations. Residential heating with wood or other biomass fuels can also release sulfur compounds and particulate matter into the air, contributing to sulfate aerosol formation (Perumpully et al., 2024; Rickly et al., 2022; Yao et al., 2023). Osieczów and Godów consistently exhibit the highest sulfate ion levels because of combustion activities and nearby industrial operations (CEZ Group, n.d; Winterbone & Turan, 2015). Stable atmospheric conditions in colder seasons trap pollutants near the ground, enhancing sulfate accumulation and leading to elevated sulfate ion concentrations (Beard et al., 2012). In warmer months, agricultural activities release NH₃, which can contribute to the formation of sulfate ions (Fu et al., 2015). Reduced demand for heating, as well as the crop growing season in spring and summer, may lead to lower concentrations. When vegetation is actively consuming nutrients, there may be an increased uptake of sulfate ions from the atmosphere through atmospheric water and then soil, leading to lower concentrations (Takahashi, 2019). A slight rise during autumn may occur because, in some cases, agricultural burning practices, such as crop residue burning, may increase. This can release sulfur compounds into the atmosphere, contributing to an increase in sulfate concentrations (Ni et al., 2017). Autumn is also when fertilizers are applied to winter crops, which can lead to ammonia emissions and subsequent reactions with sulfur dioxide in the atmosphere.
Nitrate ion concentrations (Appendix 1 Tables 1, 2, 3, 4, 5) increase in winter due to heating system emissions and stable atmospheric conditions (Pierce et al., 2019; Song et al., 2023). Fertilizer application in spring and summer emits NH₃, contributing to nitrate ion formation (Das et al., 2009). During the growing season in spring and summer, there may be an increased uptake of nitrate ions washed by rains from the atmosphere to the soil and consumed by vegetation, resulting in decreased concentrations. Along with lower heating demands, this explains lower nitrate ion concentrations in warmer seasons (Stulen & De Kok, 2012). Autumn may see increased nitrate levels due to fertilizer application for winter crops, releasing NH₃ into the atmosphere, which can react with NOx to form nitrate ions (Hertel et al., 2012). Local emissions, such as those from industrial facilities and power plants, also influence nitrate ion concentrations (CEZ Group, n.d; Rogula-Kozłowska et al., 2013a). Examples include Osieczów and Godów, wherein Osieczów has a quartz production facility and Godów has a cement production facility and a power plant. These facilities may influence nitrate ion levels based on their production cycles and seasonal activities, with power plants potentially having a more significant impact during winter seasons.
NH₄⁺ concentrations (Appendix 1 Tables 1, 2, 3, 4, 5) peak in winter due to increased fossil fuel and biomass combustion and stable atmospheric conditions, such as temperature inversions, in winter and autumn (Li et al., 2023; Yi et al., 2017). Agricultural activities contribute to ammonia emissions, impacting concentrations in warmer seasons. This could be influenced by lowered demand for heating, resulting in a drop in concentration, as well as the beginning of active fertilizer applications which, depending on the type of fertilizer used, can lead to NH₃ emissions that release ammonium ions into the atmosphere (Fung et al., 2022; Marais et al., 2021). Given that all locations are surrounded by agricultural lands, the impact of fertilizers on ammonium ion concentrations during the warmer months is significant. Forests and agricultural lands, especially in areas like Złoty Potok, Puszcza Borecka, and Bory Tucholskie, play an active role in absorbing ammonium ions washed by rains from the atmosphere into the soil during the growing season in spring and summer. This means that plants in forests and agricultural lands absorb ammonium ions, reducing levels in spring and summer (Prieto-Blanco et al., 2020; von Wirén et al., 2001). Furthermore, the influence of local emission sources, such as industrial facilities or power plants, can lead to elevated ammonium ion concentrations. In summary, various factors contribute to the fluctuations in the concentration of ammonium ions across the measured areas, with different seasons and local emission sources playing significant roles.
It is worth noting that studies such as Huang et al. (2016) and Chen et al. (2019) revealed similar trends regarding sulfate, nitrate, and ammonia ions (SNA) throughout the year. These ions tend to reach higher concentration levels during the heating season and decrease in non-heating seasons. SNA ions are the predominant inorganic components in PM2.5, constituting 80% or more of all water-soluble ions. The prevalence of SNA is closely linked to the presence of their gaseous precursors, namely NOx, SO2, and NH3, as well as the rates at which these precursors convert in the atmosphere. Additionally, various meteorological factors, such as temperature and humidity, influence the abundance of these ions. To summarize, an increased presence of these ions can serve as an indicator of heavy air pollution, as is often observed during winter seasons, which can be attributed to heightened fossil fuel usage as an energy source (Hong et al., 2022).
The seasonal trends of Na⁺, Mg2⁺, K⁺, Cl⁻, and Ca2⁺ concentrations across five different locations (Osieczów, Bory Tucholskie, Godów, Złoty Potok, and Puszcza Borecka) from 2019 to 2022 are visually presented in Figs. 7, 8, 9, 10 and 11, revealing consistent patterns with some variations. In all locations, the concentration of sodium ions follows a trend of higher levels in winter, declining in spring, reaching the lowest levels in summer, and rising again in autumn. Despite some random elevations, this pattern remains largely consistent across all locations, albeit with minor differences in concentration levels. Similarly, the concentration of magnesium ions exhibits fluctuations across seasons, with winter peaks and varying levels of decline and rise in other seasons. The concentration of potassium ions also displays a consistent pattern, with higher levels in winter followed by a decrease in spring, reaching their lowest levels in summer, and rising again in autumn. The concentration of chloride ions follows a similar seasonal trend across all locations, peaking in winter and reaching their lowest levels in summer. However, the concentration of calcium ions exhibits fluctuations without a clear trend, with elevated concentrations observed in different seasons across all locations.
The concentration of sodium ions (Appendix 1 Tables 1, 2, 3, 4, 5) in the atmosphere is influenced by various sources and activities, with combustion processes, the application of road salt, and dust emissions playing significant roles. Fluctuations in Na⁺ concentrations during different seasons over the four analyzed years are likely associated with combustion sources. However, in Bory Tucholskie and Puszcza Borecka, the influence of sea salt aerosols on the concentration of sodium ions in the atmosphere may be higher due to their proximity to the Baltic Sea (Lewandowska & Falkowska, 2013). The combustion of fossil fuels, biomass, and household waste in residential stoves contributes to sodium emissions, particularly during winter (Rogula-Kozłowska et al., 2013b). The application of road salt during cold seasons for de-icing can also elevate sodium concentrations, especially near highways (Durickovic, 2019). Dust from various sources, including construction activities, unpaved roads, and nearby mining operations like quartz mining and processing facilities (e.g., the one located close to the Osieczów) or cement production facilities near Godów, may contain sodium particles, further contributing to elevated airborne levels, particularly during dry and windy seasons (Cemex, n.d; Wang et al., 2014a, b). Agricultural fertilizers may also introduce sodium compounds into the environment, impacting concentration levels, especially in regions with extensive agricultural activity (Kronzucker et al., 2013). As all measuring sites have agricultural lands located nearby, fertilizer usage may impact concentration levels.
The high concentration of magnesium ions, as presented in Appendix 1 Tables 1, 2, 3, 4, 5, in the atmosphere during winter months is attributed to heating-related combustion, industrial emissions, marine origins, and the application of road salt. Fossil fuel combustion releases magnesium ions, with coal power plants potentially significantly contributing, as observed in Godów (CEZ Group, n.d). Coal combustion generates ash and particulate matter that may contain various elements, including magnesium. If the power plant's emissions control measures are not effectively implemented, these particulates may be released into the atmosphere, potentially contributing to higher magnesium ion levels, especially in winter (Xiao et al., 2021). In Bory Tucholskie and Puszcza Borecka, their proximity to the Baltic Sea can introduce marine-derived magnesium ions (Lewandowska & Falkowska, 2013). Road salt containing magnesium compounds adds to airborne concentrations, particularly in areas with frequent winter de-icing activities, such as highways or villages (Durickovic, 2019; Kotalik et al., 2017). As the warm season begins, the demand for fossil fuel combustion decreases, influencing lower magnesium ion concentrations. Rainfall also reduces magnesium levels by washing particles out of the air, while agricultural activities, such as using magnesium-containing fertilizers and wildfires, can temporarily increase the ion concentration (Agbeshie et al., 2022; Azzouzi et al., 2016; Shen et al., 2012; Zhang et al., 2022). Elevated concentrations in summer are attributed to changing weather conditions, including strong winds and dry periods, leading to increased suspension of dust and particulate matter in the air. These particles may contain magnesium compounds, contributing to higher magnesium ion concentrations. Additionally, summer is a common season for construction and land development activities, which can disturb the soil and release magnesium-containing particles into the air. A decrease in the concentration of magnesium ions during autumn can be attributed to changes in weather patterns, including lower temperatures and increased humidity. These conditions may result in reduced atmospheric turbulence, leading to a reduced suspension of particulate matter containing magnesium ions.
The concentration of potassium ions (Appendix 1 Tables 1, 2, 3, 4, 5) fluctuates because of biomass combustion, agricultural fertilization, and seasonal weather patterns. Winter heating, especially in rural areas, releases particulate matter with potassium ions from wood, biomass burning, and coal combustion (Perumpully et al., 2024). This influence is most pronounced in the Osieczów and Godów measuring stations because of their proximity to villages and, in the case of Godów, its proximity to a coal power plant (CEZ Group, n.d; Li et al., 2003; Yu et al., 2018). Spring sees increased agricultural activity and fertilizer application, contributing to airborne potassium levels. Summer concentrations decrease as vegetation absorbs nutrients from the soil, while autumn witnesses a rise in concentration levels because of agricultural burning and soil disturbance (Ragel et al., 2019; Wang et al., 2014a, b; Yu et al., 2018). Additionally, increased rainfall during autumn can lead to soil erosion, transporting potassium-containing particles into the air, and further contributing to elevated potassium ion concentrations.
Chloride ions (Cl⁻) in the atmosphere vary with fossil fuel combustion, the application of road salt, and agricultural practices (Appendix 1 Tables 1, 2, 3, 4, 5). During winter, fossil fuel combustion, especially in locations with prevalent combustion sources like Osieczów and Godów, contributes the most to the chloride ion concentration levels. Moreover, the elevated concentrations of magnesium ions observed in Godów can be attributed to the nearby coal power plant, as also confirmed by the study conducted by Wang et al., (2014a, b). Road maintenance that involves the application of de-icing agents like road salt, which contains chloride ions, contributes to higher concentrations during cold months (John et al., 2007). Spring sees increased agricultural activity and fertilizer use, adding to airborne chloride concentrations (Wang et al., 2023). During summer, lower chloride ion concentrations can be attributed to reduced combustion usage and rainfall, which helps leach chloride ions from the air. In autumn, concentrations may rise again because of agricultural burning and vegetation decomposition (Svensson et al., 2021).
Calcium ion concentrations (Appendix 1 Tables 1, 2, 3, 4, 5) in the atmosphere are influenced by various sources, including biomass burning, road maintenance, agricultural activities, wildfires, and industrial processes. Winter heating and the application of road salt, which contains calcium chloride (CaCl₂) as a de-icing agent to melt ice and snow, contribute to elevated calcium ion levels (Bulkfinechem, n.d.). Additionally, at the onset of warmer months, snowmelt can lead to the resuspension of soil particles and dust from the ground. These particles may contain calcium ions and their suspension in air can increase airborne calcium concentrations. Spring fertilization and agricultural activities release calcium ions. Additionally, temporary increases are seen during summer because of farming practices and wildfires (Agbeshie et al., 2022; Kibet et al., 2023). Autumn brings additional rises from agricultural activities and soil disturbance. Seasonal construction, road maintenance, and other local activities can lead to the release of dust and particulate matter, which may contain calcium ions (Wang et al., 2014a, b). Industrial processes like mining and processing may also release calcium-containing dust into the air, impacting concentrations seasonally. For example, quartz mining and processing located in Osieczów can generate dust emissions due to the mechanical crushing and grinding of quartz-rich rocks. While the primary components of this dust are typically silica particles, there may be trace amounts of other minerals in the rock that contain calcium ions, which could potentially become airborne as dust (Li et al., 2018).
It is worth noting that for the water-soluble ions analyzed in this study, neither the regulations governing air quality standards in the European Union (EU) nor those in the United States establish specific limits for these ions in the air. Of course, according to the EU air quality standards and United States EPA (USEPA) standards, some of the presented ions are regulated indirectly, such as SO2. According to EU air quality standards, the average SO2 concentration limit is 350 µg/m3 per hour and 125 µg/m3 per 24 h (EU, 2008). According to the USEPA established in 2010, the regulatory standard for SO2 is 75 parts per billion (ppb) based on a 3-year average of the 99th percentile of 1-h maximum concentration (USEPA, 2019). It is known that SO₄2⁻ can form in the atmosphere from the oxidation of SO2, thus demonstrating how the concentration of sulfate ions can be regulated indirectly. EU and US regulations primarily focus on traditional air pollutants and do not typically set specific limits for ions in the air. Ions are generally not considered primary air pollutants; their concentrations in the atmosphere are often a result of natural processes or emissions from other pollutants, such as sulfur dioxide or nitrogen oxides, which can form ions when they react with atmospheric components.
To conclude, the current absence of well-defined, direct limits for water-soluble ion emissions in the EU and USA does not diminish the importance of this topic; rather, it underscores the critical need for further research and a more comprehensive understanding of this issue. It is imperative to continue scientific investigations and perform robust data collection to establish effective guidelines for managing these emissions and develop new advanced techniques for tracing these emissions, thereby safeguarding our environment. A commitment to knowledge and proactive measures is essential in addressing this environmental challenge.
3.1 Correlation Analysis of Multiple Water-Soluble Ions
The composition of PM in the atmosphere plays a pivotal role in shaping air quality and its subsequent impacts on public health and the environment. Within the vast spectrum of PM constituents, water-soluble ions emerge as critical markers, reflecting both natural and anthropogenic contributions to atmospheric aerosols.
Correlation analysis was performed to gain a better understanding of the time variability of multiple ions together, revealing their correlations and shedding light on the dynamic sources that govern their presence. The investigation spanned four years and encompassed five distinct locations, providing a nuanced understanding of how these ions evolve both temporally and spatially. Pearson correlation coefficients were obtained, revealing notable associations between various ions over the observed four-year period across five generally rural locations. The highest coefficients were observed between the following pairs of ions: SO₄2⁻ and NH₄⁺, NO₃⁻ and NH₄⁺, SO₄2⁻ and NO₃⁻, NH₄⁺ and Cl⁻, NO₃⁻ and Cl⁻, SO₄2⁻ and K⁺, Cl⁻ and K⁺, Mg2⁺ and Na⁺, and Mg2⁺ and Ca2⁺ (Fig. 12). These results contribute to the analysis of potential sources of these ions.
A strong correlation was consistently observed for SO₄2⁻ and NH₄⁺ across all locations throughout almost every studied year, with correlation coefficients ranging between 0.8 and 0.9. Similarly, a strong correlation between NO₃⁻ and NH₄⁺ ions was observed overall, with correlation coefficients also between 0.8 and 0.9. Regarding SO₄2⁻ and NO₃⁻, it was noted that the correlation is generally lower across all locations, with some locations and years recording a correlation level as low as 0.3, as seen in Osieczów. However, these values still indicate a significant correlation, ranging from 0.3 to 0.8. This suggests that sulfate, nitrate, and ammonium ions may share a common pollution source, exhibiting close resemblances in their molecular structures. A study performed by Hong et al. (2022), wherein data was analyzed for Beijing, China, reported a correlation coefficient of approximately 0.9 between SO₄2⁻ and NO₃⁻ and between NO₃⁻ and NH₄⁺. These correlations support the assumption that SNA ions originate from the same pollution source and share similar molecular morphologies.
Furthermore, interesting results emerged regarding the correlation coefficients for NH₄⁺ and Cl⁻ and for NO₃⁻ and Cl⁻. For instance, in Osieczów, the correlation coefficient between NH₄⁺ and Cl⁻ was insignificant in 2019. However, in 2020 and 2021, it reached significant levels of 0.5 and 0.7, respectively. In 2022, it returned to being insignificant. On the other hand, in Bory Tucholskie, Godów, and Złoty Potok, correlations were consistently significant, showing a growing trend year by year, with correlation coefficients ranging from 0.5 to 0.9.
In Puszcza Borecka, the correlation was insignificant in 2019 and 2020. However, in 2021 and 2022, it grew to significant levels of 0.6 and 0.3, respectively. This may be attributed to the influence of a particular source of ions beginning to emerge in these years. For NO₃⁻ and Cl⁻, it was observed that the correlation was consistently significant in all locations and across all years, ranging from 0.4 to 0.9. The correlation analysis results for NH₄⁺ and Cl⁻, as well as for NO₃⁻ and Cl⁻, suggest that sulfate, nitrate, and ammonium ions may have similar origins and are related in their molecular morphologies. According to a study by Cheng et al. (2022) performed in Lanzhou, China, NH₄⁺ demonstrated a positive correlation with Cl⁻ and NO₃⁻, indicating that ammonium salts were mainly present in the form of NH₄Cl and NH₄NO₃. Similarly, a study by Hong et al. (2022) showed a strong correlation between NO₃⁻ and Cl⁻, suggesting that SNA ions share a common pollution source.
The investigation of SO₄2⁻ and K⁺, along with Cl⁻ and K⁺, also revealed significant correlations. Notably, for SO₄2⁻ and K⁺ in Bory Tucholskie, Złoty Potok, and Puszcza Borecka—locations characterized as entirely rural with no major villages in close proximity—the correlation remained consistently strong throughout all analyzed years. However, in Osieczów and Godow, where there is a larger influence from villages near the measuring stations, the correlation coefficients varied. In Osieczów, the correlation between SO₄2⁻ and K⁺ was insignificant in 2021 and 2022, while in 2020 and 2019 correlation coefficients of 0.5 and 0.4 were observed, respectively. Similarly, in Godow, while the correlation was insignificant in 2022, in the other years, it ranged between 0.5 and 0.7.
The relationship between Cl⁻ and K⁺ revealed consistent and significant correlations across the majority of locations and years, ranging between 0.3 and 0.8. The only exception was in Godow in 2022, where the correlation was insignificant. A similar situation was observed for SO₄2⁻ and K⁺ ions in Godow in 2022, suggesting that these ions have similar pollution sources.
According to a study performed by Dai et al. (2012), a good correlation was observed for SO₄2⁻ and K⁺. This was reported to likely be a result of emissions from combustion processes, such as vehicle exhausts, along with fossil fuel and biomass burning. In their study, Cl⁻ and K⁺ ions were assumed to originate from sea salts. This might be the case for the Bory Tucholskie and Puszcza Borecka locations, which can be influenced by sea spray from the Baltic Sea. However, in other cases, the reasons for such correlations could be related to combustion and agricultural activities.
Furthermore, interesting results were observed for Mg2⁺ and Na⁺ ions, with correlation coefficients being significant overall but exhibiting some fluctuations over the years in certain locations. For example, in Osieczów, the correlation coefficients for 2019 and 2022 were 0.4 and 0.7, respectively. However, in 2020, the correlation was insignificant, while in 2021, it was negative. Similarly, in Złoty Potok, correlation coefficients were 0.7 and 0.8 for the years 2019 and 2020, but in the other two years, the correlation was insignificant. Generally, in Godow these ions demonstrated good correlations across all four years, ranging from 0.3 to 0.6.
The most interesting results were observed for Bory Tucholskie and Puszcza Borecka, where the highest correlations were consistently observed in all years for both locations, ranging between 0.5 and 0.7 for Bory Tucholskie and from 0.4 to 0.9 for Puszcza Borecka. For the other three locations, the major influence may be from resuspension. Cesari et al. (2019) also found a strong correlation between Mg2⁺ and Na⁺ through correlation analysis. The authors suggest that this correlation indicates the presence of a contribution from marine aerosols in PM2.5, which aligns with the proximity of the measurement site to the coast (approximately 15 km). Given these results, which indicate that Mg2⁺ and Na⁺ ions can serve as tracers for sea spray and considering that Bory Tucholskie and Puszcza Borecka are much closer to the Baltic Sea than the other three locations, it suggests that the influence of the sea as a possible source is significant. Good correlations between Mg2⁺ and Ca2⁺ were observed in all locations and years, albeit with a couple of exceptions, with correlation coefficients ranging from 0.3 to 0.9. It is thought that these results suggest potential influence from dust events (Cheng et al., 2022; Choi et al., 2001).
In summary, when comparing results from rural areas with those from urban sites, it becomes evident that similar pollution sources are influencing both sites. This includes rural sites that are located deep in the countryside, suggesting that pollution dispersal mechanisms and the reach of industrial activities extend far beyond urban boundaries. However, as there is no public data available for urban areas, it is hard to assess the full scale of this impact in Poland.
3.2 Sources investigation using principal component analysis
All five locations—Osieczów, Bory Tucholskie, Godów, Złoty Potok, and Puszcza Borecka—were analyzed for water-soluble ions, including Ca2⁺, Cl⁻, K⁺, Mg2⁺, Na⁺, NH₄⁺, NO₃⁻, and SO₄2⁻, using Statistica software. In the case of Osieczów, the results explained factors accounting for 75.4% of the total variance.
As illustrated in Fig. 13, for Osieczów, Factor 1 accounts for 40.9% of the total variance covered, showing elevated load values of SO₄2⁻, NO₃⁻, NH₄⁺, K⁺, and Cl⁻. This combination indicates typical secondary ions originating from agricultural activities and biomass burning, with Cl⁻ being a tracer of coal combustion. Thus, Factor 1 represents the secondary transformation of gaseous precursors and combustion.
Regarding Factor 2 for Osieczów (Fig. 13), it accounted for 20% of the total variance and exhibited elevated loadings of Na⁺, Mg2⁺, and Ca2⁺. These elements are most likely from natural and construction dust, with Mg2⁺ and Ca2⁺ primarily coming from soil particles, building materials, and road dust, while Na⁺ likely originated from soil. This implies that Factor 2 is associated with soil and various construction sources.
Factor 3 accounts for 14.3% of the total variance and was significantly loaded by Ca2⁺. This is indicative of natural and construction dust contributions, possibly resulting from wind and weathering processes leading to the resuspension of calcium-rich particles.
The results for Bory Tucholskie explain factors accounting for 74.9% of the total variance. As illustrated in Fig. 14, Factor 1 covers 40.9% of the total variance and exhibits elevated load values of SO₄2⁻, NO₃⁻, NH₄⁺, K⁺, and Cl⁻. This is similar to what was observed for Osieczów, indicating once again that Factor 1 represents the secondary transformation of gaseous precursors and combustion.
Factor 2 for Bory Tucholskie (Fig. 14) accounts for 23.5% of the total variance and displays elevated loadings of Na⁺, Mg2⁺, and Ca2⁺. Considering that the Bory Tucholskie sampling station is relatively close to the Baltic Sea and noting that Na⁺ is a tracer of sea salt aerosols and Mg2⁺ primarily originates from marine and crustal origins, the fingerprint of this factor may have marine origins. Therefore, this suggests that the likely sources of Factor 2 are sea spray and soil.
Factor 3 accounted for 11.6% of the total variance and showed a significant loading of Na⁺, suggesting that some Na⁺ ions may originate from soil particles.
The results for Godów explain factors accounting for 82% of the total variance. Factor 1, presented in Fig. 15, covers 52% of the total variance. Similar to previously observed results, it shows elevated loadings of SO₄2⁻, NO₃⁻, NH₄⁺, K⁺, and Cl⁻. Notably, Na⁺ is also included in this group. Thus, Factor 1 can be recognized as typical secondary ions, with Cl⁻ serving as a tracer for coal combustion. Considering the proximity of a coal power plant near the sampling point, this is highly probable. A good correlation between Na⁺ and Cl⁻ indicates their similar origins or coexistence in aerosols. Factor 2 covers 18.4% of the total variance, displaying elevated loadings of Mg2⁺ and Ca2⁺, suggesting natural and construction dust origins. Regarding Factor 3, 11.5% of the total variance is covered and, similarly to Bory Tucholskie, it is loaded with Na⁺, suggesting natural dust as the origin.
The results obtained for Złoty Potok explain factors accounting for 76.8% of the total variance. Factor 1, graphically presented in Fig. 16, covers 42.5% of the total variance. Loaded with SO₄2⁻, NO₃⁻, NH₄⁺, K⁺, and Cl⁻—similar to what was observed for Bory Tucholskie and Osieczów—these ions most probably originate from the secondary transformation of gaseous precursors and combustion. Factor 2 covers 22.8% of the total variance, presenting elevated load values of Na⁺, Mg2⁺, and Ca2⁺, suggesting natural and construction dust origins. Similar results were observed for Bory Tucholskie, where Na⁺ and Mg2⁺ were presumed to have marine origins because of the close proximity to the Baltic Sea. However, Złoty Potok's sampling point is located quite far from the sea, approximately 500 km away, thus possible marine influence must be further investigated. Factor 3 accounts for 11.5% of the total variance and shows a significant loading of Ca2⁺, most probably originating from the resuspension of calcium-rich soil particles. The obtained results align closely with prior studies conducted by Błaszczak (2018) for the same rural location (Złoty Potok).
Results for Puszcza Borecka explain factors accounting for 84.8% of the total variance. Factor 1, presented in Fig. 17, covers 44.6% of the total variance and is loaded with SO₄2⁻, NO₃⁻, NH₄⁺, K⁺, and Cl⁻. This is generally similar to previous observations in all sampling locations, albeit with some differences. This factor indicates that the secondary transformation of gaseous precursors and combustion significantly influenced the concentration levels of SO₄2⁻, NO₃⁻, NH₄⁺, K⁺, and Cl⁻. In Factor 2, 26% of the total variance displays elevated loadings of Na⁺, Mg2⁺, and Ca2⁺, with Ca2⁺ most probably coming from natural dust. Puszcza Borecka and Bory Tucholskie, both of which are located relatively close to the Baltic Sea, demonstrated similar levels of Na⁺ and Mg2⁺, proving that the fingerprint of these factors may have marine origins. Factor 3 covers 14.1% of the total variance and shows a significant loading with Ca2⁺, which is indicative of particles from natural origin.
In a previous study conducted by Chen et al. (2019), some similarities between urban and rural sites in water-soluble ion sources were demonstrated. Researchers performed PCA analyses on data measured in the urban area of Chengdu, China. Interestingly, Factor 1 in both urban (Chengdu) and rural (Osieczów, Bory Tucholskie, Godów, Złoty Potok, Puszcza Borecka) areas exhibited elevated load values of typical secondary ions, such as SO₄2⁻, NO₃⁻, NH₄⁺, and Cl⁻, indicating a common influence of secondary aerosols and combustion processes on aerosol compositions across different environments. Cl⁻ was consistently identified as a tracer for coal combustion in Factor 1 across all locations, highlighting the impact of coal-related emissions on air quality in both rural and urban environments. While Factor 1 in urban Chengdu is also influenced by Na⁺, Factor 1 in rural areas does not consistently include Na⁺. In fact, Na⁺ was only included in Factor 1 for Godów, which can be considered a small city, indicating their similar source of origin. Considering that Godów is located near a coal power station, this is highly possible. In terms of differences, the variance of Factor 1 varies between locations, with Chengdu accounting for 61.1% of the total variance, while rural areas such as Osieczów, Bory Tucholskie, Godów, Złoty Potok, and Puszcza Borecka account for percentages ranging from 40.9% to 52%. This suggests potential differences in the dominant sources and processes influencing aerosol compositions between urban and rural environments. Factors 2 and 3 obtained by Chen et al. (2019) in Chengdu slightly differ from the results presented in this study (Osieczów, Bory Tucholskie, Godów, Złoty Potok, and Puszcza Borecka), although they also suggest the influence of construction and natural dust resuspension. Similar PCA results were observed for Na⁺, Mg2⁺, and Ca2⁺ ions in studies performed by Li et al. (2018) and Błaszczak (2018), wherein high load values for Mg2⁺ and Ca2⁺ were attributed to dust resuspension in urban background locations. For example, in Godów, Factor 2 represents Mg2⁺ and Ca2⁺. As Godów can be treated as a small city, it is clear that the major influence is road dust resuspension and construction activities. In contrast, for the other four rural locations, Na⁺ is included in Factor 2, which can be explained by the addition of mineral dust. A study performed by Li et al. (2018) in the Beibei District in Chongqing, China, which is located inland, suggested that the Na⁺ observed in Factor 3, similar to Godów and Bory Tucholskie, mainly originates from soil and dust. However, considering that the Bory Tucholskie sampling site is relatively close to the Baltic Sea, sea spray may also be an influencing factor. Regarding Ca2⁺ ions, a study performed by Błaszczak (2018), which analyzed data from the Trzebinia (urban background) site, reported the presence of Ca2⁺, along with (secondary organic carbon, SOC), Na⁺, Cl⁻, K⁺, and Mg2⁺, highlighting the role of municipal combustion sources. This is indicated by the presence of fly ash particles that are typically enriched in alkaline metals. In the case of rural sites, including Osieczów, Złoty Potok, and Puszcza Borecka, Ca2⁺ most likely comes from natural origins, such as resuspension.
To conclude the PCA section, potential sources of the observed ions were successfully identified and discussed based on the results of this study's analysis. The study by Chen et al. (2019) and other supporting research highlights significant similarities in the sources of water-soluble ions between urban and rural sites. Both environments exhibit elevated levels of secondary ions, such as SO₄2⁻, NO₃⁻, NH₄⁺, and Cl⁻, indicating the widespread influence of secondary aerosols and combustion processes. Cl⁻ consistently serves as a marker for coal combustion across all locations, underscoring the pervasive impact of coal-related emissions on air quality. Despite some differences, such as the inclusion of Na⁺ in urban areas but not consistently in rural areas for Factor 1, the overall variance explained by common factors suggests similar pollution influences. This convergence points to the significant reach of pollution dispersal mechanisms, extending the impact of urban pollution sources into rural areas.
Additionally, informative box plots that complement the content of this paper have been prepared and are available in Appendix 2 (Figures 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37). The box plot analysis revealed consistency in ion concentrations across various sites and years, irrespective of seasonal variations. This notable consistency implies a stable trend in ion sourcing, suggesting that the origins of these ions remain relatively unchanged throughout the studied period. This could be due to consistent anthropogenic or natural factors contributing to the ion concentrations in all the observed rural locations. Such uniformity across diverse rural sites, whether in small villages or agricultural lands and forests, in different parts of the country and timeframes prompts a closer examination of potential sources. This comprehensive analysis and visualization serve as valuable contributions to our understanding of ion sources and seasonal concentration fluctuations in the context of this study.
4 Conclusion
This study provides a comprehensive analysis of water-soluble ions in the PM from rural parts of Poland, highlighting both temporal and spatial variations. Utilizing correlation analysis and PCA, significant relationships between various ions and their potential sources were identified. The correlation analysis revealed strong associations between ions such as SO₄2⁻ and NH₄⁺, NO₃⁻ and NH₄⁺, and SO₄2⁻ and NO₃⁻, suggesting common pollution sources and similar molecular morphologies. The observed high correlations indicate that these ions likely originate from similar pollution sources, namely primarily secondary aerosols and combustion processes.
PCA further elucidated the sources of these ions, attributing significant loadings of SO₄2⁻, NO₃⁻, NH₄⁺, K⁺, and Cl⁻ to secondary transformations of gaseous precursors and combustion activities. Factors such as Na⁺, Mg2⁺, and Ca2⁺ were linked to natural and construction dust, with indications of marine aerosol influences, particularly in locations closer to the Baltic Sea. The consistency of these findings across various rural locations underscores the pervasive nature of pollution dispersal mechanisms, which extend the impact of typical urban emissions on rural environments as well.
Our study highlights the importance of understanding PM composition in rural areas, which are often understudied compared to urban environments. The identified correlations and sources provide crucial insights into the mechanisms influencing air quality in rural settings, emphasizing the need for continued monitoring and analysis. This research contributes to a broader understanding of how both natural and anthropogenic activities affect atmospheric composition, with implications for environmental policy and public health strategies. Further studies should aim to compare these rural findings with urban data, which is currently lacking in public databases in Poland, to fully grasp the scale and impact of particulate matter pollution across different environments in Poland.
Data Availability
The authors declare that the data supporting the findings of this study are available within the paper and its Appendix files. Should any raw data files be needed in another format they are available from the corresponding author upon reasonable request.
References
Agbeshie, A. A., Abugre, S., Atta-Darkwa, T., & Awuah, R. (2022). A review of the effects of forest fire on soil properties. Journal of Forestry Research, 33(5), 1419–1441. https://doi.org/10.1007/s11676-022-01475-4
Ateş, E., & Khameneh, E. T. (2023). Effects of the number of people, temperature, relative humidity, and CO2 parameters on indoor air quality in higher education institution classrooms. Edelweiss Applied Science and Technology, 7(2), 164–181. https://doi.org/10.55214/25768484.v7i2.406
Azzouzi, H., Ouzaouit, K., Aboulaich, A., Dali, Y., Kaddami, A., & Akalay, I. (2016). Managem products potentially used in fertilizers industry. Symphos 2015 - 3rd International Symposium on Innovation and Technology in the Phosphate Industry, 138, 302–307. https://doi.org/10.1016/j.proeng.2016.02.088
Beard, J. D., Beck, C., Graham, R., Packham, S. C., Traphagan, M., Giles, R. T., & Morgan, J. G. (2012). Winter Temperature Inversions and Emergency Department Visits for Asthma in Salt Lake County, Utah, 2003–2008. Environmental Health Perspectives, 120(10), 1385–1390. https://doi.org/10.1289/ehp.1104349
Bellouin, N., & Haywood, J. (2020). Climatology of Tropospheric Aerosols. Earth Systems and Environmental Sciences. https://doi.org/10.1016/B978-0-12-409548-9.12436-4
Blaszczak, B. (2018). The use of principal component analysis for source identification of PM from selected urban and regional background sites in Poland. X-Th Scientific Conference Air Protection in Theory and Practice, 28. https://doi.org/10.1051/e3sconf/20182801001
Bulkfinechem, (n.d). Calcium Chloride. Bulkfinechem.com. Retrieved September 26, 2023, from https://bulkfinechem.com/product/calcium-chloride/
Cao, J., Qiu, X., Gao, J., Wang, F., Wang, J., Wu, J., & Peng, L. (2021). Significant decrease in SO2 emission and enhanced atmospheric oxidation trigger changes in sulfate formation pathways in China during 2008–2016. Journal of Cleaner Production, 326, 129396. https://doi.org/10.1016/j.jclepro.2021.129396
Cemex, (n.d). Betonárna Dětmarovice (Dětmarovice concrete plant). Cemex. Retrieved September 27, 2023, from https://www.cemex.cz/-/betonarna-detmarovice
Cesari, D., Merico, E., Grasso, F. M., Decesari, S., Belosi, F., Manarini, F., De Nuntiis, P., Rinaldi, M., Volpi, F., Gambaro, A., Morabito, E., & Contini, D. (2019). Source apportionment of PM2.5 and of its oxidative potential in an industrial suburban site in South Italy. Atmosphere, 10(12), 758. https://doi.org/10.3390/atmos10120758
CEZ Group. (n.d). Elektrárna Dětmarovice (Dětmarovice Power Plant). CEZ Group. Retrieved September 25, 2023, from https://www.cez.cz/cs/o-cez/vyrobni-zdroje/uhelne-elektrarny-a-teplarny/uhelne-elektrarny-a-teplarny-cez-v-cr/elektrarna-detmarovice-58185
Chen, Y., Xie, S. D., Luo, B., & Zhai, C. Z. (2019). Characteristics and Sources of Water-Soluble Ions in PM in the Sichuan Basin, China. Atmosphere, 10(2). https://doi.org/10.3390/atmos10020078
Cheng, B., Ma, Y., Li, H., Feng, F., Zhang, Y., & Qin, P. (2022). Water-soluble ions and source apportionment of PM2.5 depending on synoptic weather patterns in an urban environment in spring dust season. Scientific Reports, 12(1), 21953. https://doi.org/10.1038/s41598-022-26615-y
Choi, J. C., Lee, M., Chun, Y., Kim, J., & Oh, S. (2001). Chemical composition and source signature of spring aerosol in Seoul, Korea. Journal of Geophysical Research: Atmospheres, 106(D16), 18067–18074. https://doi.org/10.1029/2001jd900090
Chyzhykov, D., Widziewicz-Rzońca, K., Błaszczak, M., Rogula-Kopiec, P., & Słaby, K. (2023). Automatic weighing system vs. manual weighing precision comparison in PM-loaded filter measurements under different humidity conditions. Environmental Monitoring and Assessment, 195, 1393. https://doi.org/10.1007/s10661-023-11939-7
Cong, L., Zhou, S. J., Liu, Y., Zhang, Z. M., & Zhang, M. X. (2022). Rainfall characteristics significantly affect the scavenging of water-soluble ions attached to leaves. Ecotoxicology and Environmental Safety, 247. https://doi.org/10.1016/j.ecoenv.2022.114238
Cotterell, M. I., Knight, J. W., Reid, J. P., & Orr-Ewing, A. J. (2022). Accurate Measurement of the Optical Properties of Single Aerosol Particles Using Cavity Ring-Down Spectroscopy. The Journal of Physical Chemistry. A, 126(17), 2619–2631. https://doi.org/10.1021/acs.jpca.2c01246
Dai, W., Gao, J. Q., Wang, B., & Ouyang, F. (2012). Characterization and Identification of Inorganic Water-Soluble Ions in PM2.5. Applied Mechanics and Materials, 260–261, 748–753. https://doi.org/10.4028/www.scientific.net/amm.260-261.748
Das, P., Sa, J. H., Kim, K. H., & Jeon, E. C. (2009). Effect of fertilizer application on ammonia emission and concentration levels of ammonium, nitrate, and nitrite ions in a rice field. Environmental Monitoring and Assessment, 154(1–4), 275–282. https://doi.org/10.1007/s10661-008-0395-2
Deike, L., Reichl, B. G., & Paulot, F. (2022). A mechanistic sea spray generation function based on the sea state and the physics of bubble bursting. AGU Advances, 3, e2022AV000750. https://doi.org/10.1029/2022AV000750
Durickovic, I. (2019). NaCl Material for Winter Maintenance and Its Environmental Effect. In Ç. Mualla Cengiz & K. Savas (Eds.), Salt in the Earth (pp. Ch. 6). IntechOpen. https://doi.org/10.5772/intechopen.86907
EU. (2008). Air quality standards. European Union: Energy, Climate change, Environment. Retrieved September 25, 2023, from https://environment.ec.europa.eu/topics/air/air-quality/eu-air-quality-standards_en
Fu, X., Wang, S. X., Ran, L. M., Pleim, J. E., Cooter, E., Bash, J. O., Benson, V., & Hao, J. M. (2015). Estimating NH emissions from agricultural fertilizer application in China using the bi-directional CMAQ model coupled to an agro-ecosystem model. Atmospheric Chemistry and Physics, 15(12), 6637–6649. https://doi.org/10.5194/acp-15-6637-2015
Fung, K. M., Martin, M. V., & Tai, A. P. K. (2022). Modeling the interinfluence of fertilizer-induced NH emission, nitrogen deposition, and aerosol radiative effects using modified CESM2. Biogeosciences, 19(6), 1635–1655. https://doi.org/10.5194/bg-19-1635-2022
Główny Inspektorat Ochrony Środowiska—GIOS. (2021). Wpływ ograniczeń gospodarczych związanych z pandemią Covid-19 na wysokość stężeń zanieczyszczeń powietrza w 2020 roku (Impact of economic restrictions associated with the Covid-19 pandemic on the level of air pollutant concentrations in 2020). Departament Monitoringu Środowiska (Department of Environmental Monitoring). Retreived September 20, 2023, from https://powietrze.gios.gov.pl/pjp/documents/download/108628
Główny Inspektorat Ochrony Środowiska—GIOS. (n.d). Bank danych pomiarowych (Measurement data bank). Chief Inspectorate of Environmental Protection. Retrieved September 20, 2023, from https://powietrze.gios.gov.pl/pjp/archives
Gu, C., Wang, S., Zhu, J., Dai, W., Liu, J., Xue, R., Che, X., Lin, Y., Duan, Y., Wenig, M. O., & Zhou, B. (2023). Underestimated ammonia vehicular emissions in Metropolitan City revealed by On-Road Mobile Measurement. Environmental Research Letters, 18(10), 104040. https://doi.org/10.1088/1748-9326/acf94a
Henning, S., Weingartner, E., Schwikowski, M., Gäggeler, H. W., Gehrig, R., Hinz, K.-P., Trimborn, A., Spengler, B., & Baltensperger, U. (2003). Seasonal variation of water-soluble ions of the aerosol at the high-alpine site Jungfraujoch (3580 m asl). Journal of Geophysical Research: Atmospheres, 108(D1), ACH 8–1–ACH 8–10. https://doi.org/10.1029/2002JD002439
Hertel, O., Skjoth, C. A., Reis, S., Bleeker, A., Harrison, R. M., Cape, J. N., Fowler, D., Skiba, U., Simpson, D., Jickells, T., Kulmala, M., Gyldenkærne, S., Sorensen, L. L., Erisman, J. W., & Sutton, M. A. (2012). Governing processes for reactive nitrogen compounds in the European atmosphere. Biogeosciences, 9(12), 4921–4954. https://doi.org/10.5194/bg-9-4921-2012
Hong, X., Yang, K., Liang, H., & Shi, Y. (2022). Characteristics of water-soluble inorganic ions in pm2.5 in typical urban areas of Beijing. China. ACS Omega, 7(40), 35575–35585. https://doi.org/10.1021/acsomega.2c02919
Huang, T., Chen, J., Zhao, W., Cheng, J., & Cheng, S. (2016). Seasonal variations and correlation analysis of water-soluble inorganic ions in PM2.5 in Wuhan, 2013. Atmosphere, 7(4), 49. https://doi.org/10.3390/atmos7040049
Itahashi, S., Uno, I., Osada, K., Kamiguchi, Y., Yamamoto, S., Tamura, K., Wang, Z., Kurosaki, Y., & Kanaya, Y. (2017). Nitrate transboundary heavy pollution over East Asia in Winter. Atmospheric Chemistry and Physics, 17(6), 3823–3843. https://doi.org/10.5194/acp-17-3823-2017
Janse, R. J., Hoekstra, T., Jager, K. J., Zoccali, C., Tripepi, G., Dekker, F. W., & van Diepen, M. (2021). Conducting correlation analysis: Important limitations and Pitfalls. Clinical Kidney Journal, 14(11), 2332–2337. https://doi.org/10.1093/ckj/sfab085
John, K., Karnae, S., Crist, K., Kim, M., & Kulkarni, A. (2007). Analysis of Trace Elements and Ions in Ambient Fine Particulate Matter at Three Elementary Schools in Ohio. Journal of the Air & Waste Management Association, 57(4), 394–406. https://doi.org/10.3155/1047-3289.57.4.394
Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: a review and recent developments. Philosophical Transactions of the Royal Society a-Mathematical Physical and Engineering Sciences, 374(2065). https://doi.org/10.1098/rsta.2015.0202
Karamizadeh, S., Abdullah, S. M., Manaf, A. A., Zamani, M., & Hooman, A. (2013). An overview of principal component analysis. Journal of Signal and Information Processing, 04(03), 173–175. https://doi.org/10.4236/jsip.2013.43b031
Kibet, P & Mugwe, Jayne & Korir, Nicholas & Mucheru-Muna, Monicah & Ngetich, Felix & Mugendi, Daniel. (2023). Granular and powdered lime improves soil properties and maize (Zea mays l.) performance in humic Nitisols of central highlands in Kenya. Heliyon, 9(6), E17286.https://doi.org/10.1016/j.heliyon.2023.e17286
Kotalik, C. J., Clements, W. H., & Cadmus, P. (2017). Effects of magnesium chloride road deicer on montane stream benthic communities. Hydrobiologia, 799(1), 193–202. https://doi.org/10.1007/s10750-017-3212-5
Kreidenweis, S. M., & Asa-Awuku, A. (2014). Aerosol hygroscopicity: Particle water content and its role in atmospheric processes. Treatise on Geochemistry, 5, 331–361. https://doi.org/10.1016/b978-0-08-095975-7.00418-6
Kronzucker, H. J., Coskun, D., Schulze, L. M., Wong, J. R., & Britto, D. T. (2013). Sodium as nutrient and toxicant. Plant and Soil, 369(1), 1–23. https://doi.org/10.1007/s11104-013-1801-2
Lewandowska, A. U., & Falkowska, L. M. (2013). Sea salt in aerosols over the southern Baltic. part 1. the generation and transportation of Marine particles. Oceanologia, 55(2), 279–298. https://doi.org/10.5697/oc.55-2.279
Li, Y. P., Hao, Q. J., Wen, T. X., Ji, D. S., Liu, Z. R., Wang, Y. S., Li, X. X., He, X. H., & Jiang, C. S. (2018). Pollution Characteristics of Water-soluble Ions in Aerosols in the Urban Area in Beibei of Chongqing. Aerosol and Air Quality Research, 18(7), 1531–1544. https://doi.org/10.4209/aaqr.2017.11.0500
Li, Q., Gao, Y., & Yang, A. (2020). Sulfur Homeostasis in Plants. International Journal of Molecular Sciences, 21(23), 8926. https://doi.org/10.3390/ijms21238926
Li, T. T., Li, J., Sun, Z. Y., Jiang, H. X., Tian, C. G., & Zhang, G. (2023). High contribution of anthropogenic combustion sources to atmosphericinorganic reactive nitrogen in South China evidenced by isotopes. Atmospheric Chemistry and Physics, 23(11), 6395–6407. https://doi.org/10.5194/acp-23-6395-2023
Li, J., Posfai, M., Hobbs, P. V., & Buseck, P. R. (2003). Individual aerosol particles from biomass burning in southern Africa: 2, Compositions and aging of inorganic particles. Journal of Geophysical Research-Atmospheres, 108(D13), SAF 20–1–SAF 20–12. https://doi.org/10.1029/2002JD002310
Loukili, H., Anouzla, A., Jioui, I., Achiou, B., Alami Younssi, S., Azoulay, K., Bencheikh, I., Mabrouki, J., Abrouki, Y., Sebbahi, S., Bourais, I., Sabbar, A., Labjar, N., Hajjaji, S. E., Azzallou, R., Azrour, M., El Ghanjaoui, M. A., Salah, M., Tahiri, S., & Riadi, Y. (2022). Combining multiple regression and principal component analysis to evaluate the effects of ambient air pollution on children’s respiratory diseases. International Journal of Information Technology, 14(3), 1305–1310. https://doi.org/10.1007/s41870-022-00906-z
Ma, X., Gao, Q., Jiang, X., Chen, S., Gan, Y., Zhang, T., et al. (2023). Direct effects of air humidity on dust aerosol production: Evidences for the surprising role of electrostatic forces. Geophysical Research Letters, 50, e2023GL103639. https://doi.org/10.1029/2023GL103639
Marais, E. A., Pandey, A. K., Van Damme, M., Clarisse, L., Coheur, P. F., Shephard, M. W., Cady-Pereira, K. E., Misselbrook, T., Zhu, L., Luo, G., & Yu, F. Q. (2021). UK Ammonia Emissions Estimated With Satellite Observations and GEOS-Chem. Journal of Geophysical Research-Atmospheres, 126(18), e2021JD035237. https://doi.org/10.1029/2021JD035237
Mostofi, F. (2018). Heavy metal contamination of zinc and lead in Region 1 and 2 of the main city of Ardabil. Journal of Research in Science, Engineering and Technology, 6(04), 14–20.
Nascimento, J. P., Bela, M. M., Meller, B. B., Banducci, A. L., Rizzo, L. V., Vara-Vela, A. L., Barbosa, H. M. J., Gomes, H., Rafee, S. A. A., Franco, M. A., Carbone, S., Cirino, G. G., Souza, R. A. F., McKeen, S. A., & Artaxo, P. (2021). Aerosols from anthropogenic and biogenic sources and their interactions – modeling aerosol formation, optical properties, and impacts over the central Amazon basin. Atmospheric Chemistry and Physics, 21, 6755–6779. https://doi.org/10.5194/acp-21-6755-2021
Ni, H., Tian, J., Wang, X., Wang, Q., Han, Y., Cao, J., Long, X., Chen, L. W. A., Chow, J. C., Watson, J. G., Huang, R.-J., & Dusek, U. (2017). PM2.5 emissions and source profiles from open burning of crop residues. Atmospheric Environment, 169, 229–237. https://doi.org/10.1016/j.atmosenv.2017.08.063
Nirwana, J. T., & Wedari, L. K. (2023). The impact of corporate governance and firm performance on waste and effluent disclosure: Evidence from polluting industries in Indonesia. International Journal of Management and Sustainability, 12(2), 189–203. https://doi.org/10.18488/11.v12i2.3345
Olson, E., Michalski, G., Welp, L., Larrea Valdivia, A. E., Reyes Larico, J., Salcedo Peña, J., Fang, H., Magara Gomez, K., & Li, J. (2021). Mineral dust and fossil fuel combustion dominate sources of aerosol sulfate in urban Peru identified by sulfur stable isotopes and water-soluble ions. Atmospheric Environment, 260, 118482. https://doi.org/10.1016/j.atmosenv.2021.118482
Perumpully, S. J., Gautam, S., J., J. P., & M., S. (2024). Evaluating the impact of personal exposure to emissions from sustainable commercial heating and cooking fuels on women in rural southern India and their alignment with Sustainable Development Goals. Water, Air, & Soil Pollution, 235(1), 54.https://doi.org/10.1007/s11270-023-06854-z
Pierce, A. M., Loría-Salazar, S. M., Holmes, H. A., & Gustin, M. S. (2019). Investigating horizontal and vertical pollution gradients in the atmosphere associated with an urban location in complex terrain, Reno, Nevada, USA. Atmospheric Environment, 196, 103–117. https://doi.org/10.1016/j.atmosenv.2018.09.063
Prieto-Blanco, M. C., Ballester-Caudet, A., Souto-Varela, F. J., López-Mahía, P., & Campíns-Falcó, P. (2020). Rapid evaluation of ammonium in different rain events minimizing needed volume by a cost-effective and sustainable PDMS supported solid sensor. Environmental Pollution, 265(Pt A), 114911. ARTN 114911. https://doi.org/10.1016/j.envpol.2020.114911
Quartzwerke in Poland. (n.d). About. Retrieved September 26, 2023, from https://quarzwerke.pl/en/company/about-us/
Ragel, P., Raddatz, N., Leidi, E. O., Quintero, F. J., & Pardo, J. M. (2019). Regulation of K Nutrition in Plants. Frontiers in Plant Science, 10, 281. ARTN 281. https://doi.org/10.3389/fpls.2019.00281
Rickly, P. S., Guo, H. Y., Campuzano-Jost, P., Jimenez, J. L., Wolfe, G. M., Bennett, R., Bourgeois, I., Crounse, J. D., Dibb, J. E., DiGangi, J. P., Diskin, G. S., Dollner, M., Gargulinski, E. M., Hall, S. R., Halliday, H. S., Hanisco, T. F., Hannun, R. A., Liao, J., Moore, R., . . . Rollins, A. W. (2022). Emission factors and evolution of SO measured from biomass burning in wildfires and agricultural fires. Atmospheric Chemistry and Physics, 22(23), 15603–15620. https://doi.org/10.5194/acp-22-15603-2022
Rogula-Kozłowska, W., Sówka, I., Mathews, B., Klejnowski, K., Zwoździak, A., & Kwiecińska, K. (2013a). Sizeresolved water-soluble ionic composition of ambient particles in an urban area in southern Poland. Journal of Environmental Protection, 4(04), 371–379. https://doi.org/10.4236/jep.2013.44044
Rogula-Kozłowska, W., Klejnowski, K., Rogula-Kopiec, P., Ośródka, L., Krajny, E., Błaszczak, B., & Mathews, B. (2013b). Spatial and seasonal variability of the mass concentration and chemical composition of PM2.5 in Poland. Air Quality, Atmosphere & Health, 7(1), 41–58. https://doi.org/10.1007/s11869-013-0222-y
Rogula-Kozlowska, W., Majewski, G., Czechowski, P. O., & Rogula-Kopiec, P. (2017). Analysis of the Data Set from a Two-Year Observation of the Ambient Water-Soluble Ions Bound to Four Particulate Matter Fractions in an Urban Background Site in Southern Poland. Environment Protection Engineering, 43(1), 137–149. https://doi.org/10.5277/epe170111
Shen, Z. X., Zhang, L. M., Cao, J. J., Tian, J., Liu, L., Wang, G. H., Zhao, Z. Z., Wang, X., Zhang, R. J., & Liu, S. X. (2012). Chemical composition, sources, and deposition fluxes of water-soluble inorganic ions obtained from precipitation chemistry measurements collected at an urban site in northwest China. Journal of Environmental Monitoring, 14(11), 3000–3008. https://doi.org/10.1039/c2em30457k
Song, W., Chen, Z. L., Yin, Y. M., & Liu, X. Y. (2023). Primary nitrate from combustion-related sources biases the Δ O differentiation of formation pathway contributions of atmospheric secondary nitrate. Atmospheric Environment, 296, 119574. ARTN 119574. https://doi.org/10.1016/j.atmosenv.2022.119574
Statistica. StatSoft Polska. (n.d). Retrieved on 2024, June 1 from https://www.statsoft.pl/Programy/Ogolnacharakterystyka/Rodzaje-dokumentow-STATISTICA/
Stulen, I., & De Kok, L. J. (2012). Foreword: Exploring Interactions Between Sulfate and Nitrate Uptake at a Whole Plant Level. Sulfur Metabolism in Plants: Mechanisms and Applications to Food Security and Responses to Climate Change, 1–8. https://doi.org/10.1007/978-94-007-4450-9_1
Su, J., Zhao, P. S., & Dong, Q. (2018). Chemical compositions and liquid water content of size-resolved aerosol in Beijing. Aerosol and Air Quality Research, 18(3), 680–692. https://doi.org/10.4209/aaqr.2017.03.0122
Svensson, T., Kylin, H., Montelius, M., Sandén, P., & Bastviken, D. (2021). Chlorine cycling and the fate of Cl in terrestrial environments. Environmental Science and Pollution Research, 28(7), 7691–7709. https://doi.org/10.1007/s11356-020-12144-6
Takahashi, H. (2019). Sulfate transport systems in plants: Functional diversity and molecular mechanisms underlying regulatory coordination. Journal of Experimental Botany, 70(16), 4075–4087. https://doi.org/10.1093/jxb/erz132
USEPA. (2019). Primary National Ambient Air Quality Standard (NAAQS) for Sulfur Dioxide. USEPA. Retrieved September 20, 2023, from https://www.epa.gov/so2-pollution/primary-national-ambient-air-quality-standard-naaqs-sulfur-dioxide
Volná, V., Hladký, D., Seibert, R., & Krejčí, B. (2022). Transboundary air pollution transport of PM10 and benzo[a]pyrene in the Czech–polish border region. Atmosphere, 13(2), 341. https://doi.org/10.3390/atmos13020341
von Wirén, N., Gojon, A., Chaillou, S., & Raper, D. (2001). Mechanisms and Regulation of Ammonium Uptake in Higher Plants. In P. J. Lea & J.-F. Morot-Gaudry (Eds.), Plant Nitrogen (pp. 61–77). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-04064-5_3
Wang, F., Chen, Q., Zhang, W. Y., Guo, Y. T., & Zhao, L. B. (2014a). Effect of sand dust weather on major water-soluble ions in PM10 in Lanzhou. China. Huan Jing Ke Xue, 35(7), 2477–2482.
Wang, W., Maenhaut, W., Yang, W., Liu, X. D., Bai, Z. P., Zhang, T., Claeys, M., Cachier, H., Dong, S. P., & Wang, Y. L. (2014b). One-year aerosol characterization study for PM and PM in Beijing. Atmospheric Pollution Research, 5(3), 554–562. https://doi.org/10.5094/Apr.2014.064
Wang, T., Liu, Y., Cheng, H., Wang, Z., Fu, H., Chen, J., & Zhang, L. (2022). Significant formation of sulfate aerosols contributed by the heterogeneous drivers of Dust Surface. Atmospheric Chemistry and Physics, 22(20), 13467–13493. https://doi.org/10.5194/acp-22-13467-2022
Wang, Y., Liu, X. B., Wang, L. X., Li, H. T., Zhang, S. Y., Yang, J. F., Liu, N., & Han, X. R. (2023). Effects of Long-Term Application of Cl-Containing Fertilizers on Chloride Content and Acidification in Brown Soil. Sustainability, 15(11), 8801. ARTN 8801. https://doi.org/10.3390/su15118801
Węgrzyn, M. H., Kołodziejczyk, J., Fałowska, P., Wężyk, P., Zięba-Kulawik, K., Szostak, M., Turowska, A., Grzesiak, B., & Wietrzyk-Pełka, P. (2020). Influence of the environmental factors on the species composition of Lichen Scots pine forests as a guide to maintain the community (Bory Tucholskie National Park, Poland). Global Ecology and Conservation, 22, e01017. https://doi.org/10.1016/j.gecco.2020.e01017
Winterbone, D. E., & Turan, A. (2015). Chapter 14 - Chemical Kinetics. In D. E. Winterbone & A. Turan (Eds.), Advanced Thermodynamics for Engineers (2nd Ed., pp. 307–322). Butterworth-Heinemann. https://doi.org/10.1016/B978-0-444-63373-6.00014-9
Xiao, K., Wang, Q. Y., Lin, Y. C., Wang, W. Q., Lu, S. L., & Yonemochi, S. (2021). Approval Research for Carcinogen Humic-Like Substances (HULIS) Emitted from Residential Coal Combustion in High Lung Cancer Incidence Areas of China. Processes, 9(7), 1254. ARTN 1254. https://doi.org/10.3390/pr9071254
Xin, K., Chen, J., & Soyol-Erdene, T. (2023). Formation mechanism and source apportionment of nitrate in atmospheric aerosols. APN Science Bulletin, 13(1). https://doi.org/10.30852/sb.2023.2225
Yadav, P., Usha, K., & Singh, B. (2022). Air Pollution Mitigation and Global Dimming: A Challenge to agriculture under changing climate. Climate Change and Crop Stress, 271–298. https://doi.org/10.1016/b978-0-12-816091-6.00015-8
Yao, W., Zhao, Y., Chen, R., Wang, M., Song, W., & Yu, D. (2023). Emissions of Toxic Substances from Biomass Burning: A Review of Methods and Technical Influencing Factors. Processes, 11(3), 853. https://doi.org/10.3390/pr11030853
Yi, L., Thompson, T. M., Van Damme, M., Chen, X., Benedict, K. B., Shao, Y., Day, D., Boris, A., Sullivan, A. P., Ham, J., Whitburn, S., Clarisse, L., Coheur, P.-F., & Collett, J. L., Jr. (2017). Temporal and spatial variability of ammonia in urban and agricultural regions of northern Colorado United States. Atmospheric Chemistry and Physics, 17, 6197–6213. https://doi.org/10.5194/acp-17-6197-2017
Yin, Z., Liu, Z., Liu, X., Zheng, W., & Yin, L. (2023). Urban heat islands and their effects on thermal comfort in the US: New York and New Jersey. Ecological Indicators, 154, 110765. https://doi.org/10.1016/j.ecolind.2023.110765
Yu, J. T., Yan, C. Q., Liu, Y., Li, X. Y., Zhou, T., & Zheng, M. (2018). Potassium: A Tracer for Biomass Burning in Beijing? Aerosol and Air Quality Research, 18(9), 2447–2459. https://doi.org/10.4209/aaqr.2017.11.0536
Yue, D. L., Zhong, L. J., Zhang, T., Shen, J., Yuan, L., Ye, S. Q., Zhou, Y., & Zeng, L. M. (2016). Particle Growth and Variation of Cloud Condensation Nucleus Activity on Polluted Days with New Particle Formation: A Case Study for Regional Air Pollution in the PRD Region, China. Aerosol and Air Quality Research, 16(2), 323–335. https://doi.org/10.4209/aaqr.2015.06.0381
Zhang, B. (2020). The Effect of Aerosols to Climate Change and Society. Journal of Geoscience and Environment Protection, 8, 55–78. https://doi.org/10.4236/gep.2020.88006
Zhang, J., Cheng, H., Wang, D., Zhu, Y., Yang, C., Shen, Y., Yu, J., Li, Y., Xu, S., Zhang, S., Song, X., Zhou, Y., Chen, J., Jiang, J., Fan, L., Wang, C., & Hao, K. (2021). Chronic Exposure to PM2.5 Nitrate, Sulfate, and Ammonium Causes Respiratory System Impairments in Mice. Environmental science & technology, 55(5), 3081–3090. https://doi.org/10.1021/acs.est.0c05814
Zhang, W. Q., Liu, Y., Muneer, M. A., Jin, D. A., Zhang, H., Cai, Y. Y., Ma, C. C., Wang, C. S., Chen, X. H., Huang, C. D., Tang, Y. F., & Wu, L. Q. (2022). Characterization of Different Magnesium Fertilizers and Their Effect on Yield and Quality of Soybean and Pomelo. Agronomy, 12(11), 2693. ARTN 2693. https://doi.org/10.3390/agronomy12112693
Zhou, L. Y., Liang, Z. C., Mabato, B. R. G., Cuevas, R. A. I., Tang, R. Z., Li, M., Cheng, C. L., & Chan, C. K. (2023). Sulfate formation via aerosol-phase SO oxidation by model biomass burning photosensitizers: 3,4-dimethoxybenzaldehyde, vanillin andsyringaldehyde using single-particle mixing-state analysis. Atmospheric Chemistry and Physics, 23(9), 5251–5261. https://doi.org/10.5194/acp-23-5251-2023
Acknowledgements
We would like to extend our deepest gratitude to Kamila Widziewicz-Rzońca. Her knowledge and exacting attention to detail, along with her helpful advice regarding data analysis and comments on the manuscript, have been an inspiration and kept our work on track.
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The research was financed from the statutory research: Differentiation of the physicochemical composition of atmospheric pollutants in urban and non-urban areas on the example of the Silesian metropolis and the Polish-Czech borderland 1a-146/24/25/26.
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Dmytro Chyzhykov: conceptualization, formal analysis, investigation, methodology, writing original draft, visualization, data analysis, reviewing and editing. Barbara Mathews: editing and reviewing.
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Figures 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36 and 37.
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Chyzhykov, D., Mathews, B. Measurements of Water-Soluble Ions in Particulate Matter 2.5 in Polish Rural Areas: Identifying Possible Sources. Water Air Soil Pollut 235, 467 (2024). https://doi.org/10.1007/s11270-024-07265-4
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DOI: https://doi.org/10.1007/s11270-024-07265-4