Evaluating Air Pollution in Two Urban Alleys and Comparing Tree Capacity for PM Dust Absorption: A Case Study

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The calculation of PM 2.5 air purification potential is commonly conducted for green spaces and trees within urban areas with models such as I Tee eco, as they play crucial roles in ecosystem functions, including the absorption of various air pollutants, but there is a deficiency of studies verifying the distribution of health-threatening concentrations of this pollutant for urban residents. This study presents the findings of research conducted in Warsaw, the capital of Poland, aiming to assess air pollution levels and compare the dust absorption capabilities of trees in two different alleys. The research comprised two main phases: initially, monitoring the concentration of PM2.5 in urban streets characterized by high and low tree density during peak traffic periods and post-peak traffic periods. Subsequently, the study focused on determining the pollution absorption parameters of trees in selected locations, utilizing the i-Tree Eco tool. The analysis revealed frequent exceedances of air quality standards in Warsaw within isolated time frames. Furthermore, it underscored the dependence of urban forest ecosystem services' efficiency on tree canopy cover (TCC), noting a nearly 14.5-fold lower pollutant uptake in areas with insufficient TCC. This issue warrants serious consideration, particularly as a significant number of samples surpassed the WHO standard of 15 µg/m 3 . Moreover, the study's outcomes emphasized the importance of researching urban trees and air pollution levels using dust sensors. In the case of Warsaw, relying solely on readily available models, commonly utilized in previous studies, may lead to underestimations, failing to accurately represent the actual concentration levels of air pollution. Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Figures Figure 1 Figure 2 Figure 3 Introduction Air pollution is a topic of extensive discourse in both public discourse and scientific circles, owing to the persistent rise in environmental challenges resulting from rapid economic development. While urbanization brings forth numerous social advantages, it also serves as a significant contributor to environmental issues [89, 115]. The widespread conversion of green spaces into concrete structures such as plazas, residential complexes, or shopping centers diminishes the presence of greenery in cities, consequently exacerbating smog formation and urban air pollution. This trend correlates with a multitude of health issues [32, 59, 87]. Expert studies highlight air pollution as a notable concern, with many substances outlined in European Council Directives: 96/62/EC, 1999/30/EC, 2002/3/EC, 2008/50/EC [21, 22, 23, 24] reaching concentrations hazardous to human life and health [4, 127]. The primary sources of pollution include open fires, a high volume of motor vehicles in suboptimal conditions, and outdated industrial facilities [33]. Studies, exemplified by those conducted in China, attribute air pollution primarily to coal combustion and industrial processes during the early stages of economic development [62]. Additionally, exhaust emissions pose a significant concern in urban locales [62]. Hazardous pollutants include carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), lead (Pb), sulfur dioxide (SO2) [30, 36, 39, 74], as well as particulate matter (PM) – dust with an aerodynamic diameter less than 10 microns (PM10) and suspended dust with an aerodynamic diameter less than 2.5 microns [108]. Numerous studies examining air pollution's health impacts have revealed its detrimental effects on respiratory, circulatory, vascular, and neurological systems, leading to declines in overall health [32, 59, 87, 91] As indicated by many researchers, particulate matter (PM) stands out as having the most significant detrimental impact on both public health and the environment [101]. This is primarily due to the size of the particles, making anthropogenic dust the highest risk to human health [14]. Inhaling PM leads to the accumulation of particles in lung tissue and entry into the bloodstream, thereby increasing the risk of circulatory and pulmonary diseases [17], including chronic obstructive pulmonary disease and lung cancer [60]. For instance, studies demonstrate that in Beijing, a 10 µg/m 3 increase in PM2.5 levels corresponded with a rise in lung cancer incidence for both men (1.055) and women (1.149) [46]. In addition to respiratory illnesses like asthma [7, 11], inhaling dust also exacerbates respiratory infections in children [7]. Epidemiological evidence further suggests that particulate matter, particularly PM2.5, may lead to premature death [48]. It's important to note that air pollution adversely affects health not only through inhalation but also through skin absorption resulting from contact with contaminated water or food [25]. Furthermore, the issue of air pollution's impact on health has substantially escalated healthcare costs [53, 76] and continues to pose a significant threat to public health despite advancements in medicine. Anthropogenic pollution sources primarily originate from urban agglomerations [29, 45, 128] characterized by heavy road traffic, high residential density, and large-scale industrial activities [98]. Consequently, the direct influence of air pollution on public health is most pronounced in industrialized and urbanized areas. Estimates project that ongoing migration from rural to urban areas will drive an increase in urban populations, expected to reach 60% by 2030 [12], 70% by 2050 globally [37], and 82% in the EU [124]. While urbanization offers numerous social advantages, it remains a significant contributor to environmental issues such as the Urban Heat Island (UHI) effect [2, 9, 54, 89], primarily driven by land use changes and residential expansion [88, 113]. Research conducted by the WHO confirms that outdoor air pollution has surged by 8% globally in the last five years across more than 3000 cities [122]. The only similar studies we've found so far are those by Riondato et. al. 2020 [94], which examine air quality impacts in Dublin with a link to the i-Tree Eco model. The others mainly analyze model assumptions at the scale of, for example, the city of Warsaw [96], Krakow [95] or macro-regions such as Great Britain [99]. For this reason, we wish to analyze the issue for the local scale in Warsaw. Plants and PM air pollution As urban air pollution escalates, the importance of tree canopy cover (TCC) in urban areas becomes increasingly significant [1], given its provision of numerous ecosystem functions for citizens [34]. Among these functions, trees play a pivotal role in atmospheric air filtration and the retention of toxic substances [43; 104]. Research underscores that plants are among the most effective agents for eliminating suspended particulate matter from the environment [93, 125]. Urban trees enhance air quality by facilitating the deposition of various gases and solid particles, owing to their extensive foliage surface area and their influence on microclimate and air turbulence [44]. Pollution removal by plants occurs via two primary mechanisms: sediment collection on plant surfaces and absorption by stomata [121]. Studies demonstrate that trees in Christchurch, New Zealand, removed approximately 300 tons of air pollutants annually [15]. Similarly, in the UK, planting trees on a quarter of available urban land could potentially decrease PM10 concentrations by 2 to 10% [77]. However, the effectiveness of pollution absorption by trees hinges on three key factors: air movement within the tree crown, air transfer near the tree surface, and surface absorption capacity, dependent on stomatal conductance [120]. The deposition of particulate pollutants primarily occurs on leaf surfaces [44], with the ultra-structures of wax crystals significantly contributing to PM adsorption [118]. Additionally, studies suggest that the stomata of plants can remove soot particles from the environment [129]. Tree species that maintain open stomata longer tend to absorb pollutants more efficiently than isohydrotic species [26]. Despite the pollutant retention properties of tree surfaces [75], the efficacy of this function varies among different tree species [5, 75]. Dust retention efficiency depends on factors such as leaf micromorphology, leaf density, and crown type [6, 13, 40, 66, 92, 98, 100, 102, 106]. Coniferous trees are found to be more effective in PM10 absorption than deciduous trees [5], and among deciduous species, those with rough-surfaced leaves exhibit greater efficiency in PM2.5 absorption [6, 55]. Consequently, the selection of tree species plays a crucial role in maximizing dust absorption efficiency [19]. Furthermore, the absorption of PM2.5 is influenced not only by trees but also by the presence of other specific species in the vicinity [102]. Beyond individual trees, the reduction of dust volume and particle filtration in urban areas can also be attributed to green belts or zones comprising natural or planted greenery. [119]. Research conducted by Yin et al. [126] demonstrated that the concentration of PM2.5 decreased by 9% in forested areas adjacent to urban areas [126]. However, the crucial role of trees may be overlooked in many countries, including Poland, where there's a growing trend of removing greenery from public spaces and replacing it with concrete [78]. Tools used to measure the trees’ capability to remove pollution The Urban Forest Effects (UFORE) tool serves as a valuable instrument for evaluating the efficacy of urban forests, allowing researchers and governing bodies to gauge their functionality and structure based on field data, meteorological observations, and on-site pollution assessments [3, 85]. UFORE's capabilities extend to calculating various parameters, including total stored carbon, net carbon sequestered by urban trees, effects on building energy usage and CO2 emissions, and the estimated impact of tree species on air quality improvement and pollution removal [85]. Additionally, the model features a component for estimating the volume of pollution removed by plants [52]. Derived from the UFORE model, the i-Tree Eco tool, developed by the United States Forest Service (USFS), offers a comprehensive analysis of urban tree structure, species, and health status to assess the ecosystem services provided by trees [85]. Studies utilizing i-Tree Eco have revealed that factors such as planting density, total leaf surface area, phenology, and spatial arrangement contribute to pollution removal at the tree group level [10; 47; 83]. At the individual tree level, leaf characteristics and growth patterns play significant roles in PM2.5 removal efficiency, with optimal environmental benefits observed when crown density and leaf area index (LAI) are approximately 50–60% and 1.5-2.0, respectively. With over half of the global population residing in urban areas according to the United Nations (UN), there is a pressing need to conduct studies involving real measurements of air pollution and to explore commonly used tools for measuring urban air quality (United Nations, n.d.). While analyses employing dust sensors necessitate specialized equipment and advanced analytical methods, the i-Tree Eco model offers a readily accessible and free-of-charge alternative. However, the accuracy of the i-Tree Eco model, particularly in comparing dust concentrations in vegetated versus non-vegetated areas, warrants further investigation, as empirical validation studies remain scarce. Our study aims to address this gap by innovatively calibrating low and high canopy coverage streets for air particulate matter concentrations using a combination of field measurements and i-Tree Eco simulations, thus providing valuable insights into ecosystem services assessment opportunities, especially concerning tree canopy cover (TCC) variances. Therefore, our research was designed to examine the potential impact of urban vegetation on air pollutant concentrations at the local scale, considering that some studies suggest urban vegetation may inadvertently elevate air pollutant levels. Our aim was to uncover the true extent of this issue and assess the associated human health risks posed by inadequate vegetation, particularly trees, in urban environments amidst prevailing air pollution challenges. Materials & Methods Case study area description Warsaw, the capital of Poland and the largest city in the country, situated at the heart of Europe, was chosen as the research area (Figure 1). With a surface area of 517.2 km 2 and a population of 1,792,718 (Poland in numbers, 2020), Warsaw, like many other Polish cities, grapples with severe air quality issues on a global scale. In January 2017, the city experienced one of its most severe smog episodes, with pollution levels exceeding air quality standards across much of Poland. During this period, the permissible average concentrations of PM10 were surpassed on 19-22 days, accounting for 60-70% of the month, while PM2.5 concentrations exceeded standards on 25-28 days, covering 80-90% of the month [65]. In January 2021, Warsaw ranked 6th among cities with the lowest air quality according to the Air Quality Index [72]. Additionally, the World Air Quality Ranking in February 2021 identified Warsaw as the city with the second-worst air quality globally, with PM10 concentrations exceeding by 232% and PM2.5 levels by a staggering 364% [70]. Subsequently, in March, Warsaw topped the IQAir ranking as the most polluted major city in the world [57], underscoring its selection as the research focus. The average daily lowest temperature was recorded at 8.2°C, and the average daily highest temperature reached 15.9°. The average daily lowest humidity rate was 71.9%, the recorded highest daily humidity rate was 90.1%. Wind speed during the analyzed period ranged from 2 to 7 m/s with gusts of 4 to 16 m/s occurring. Precipitation occurred 3 times - 2.4 mm of rain fell on September 23, 0.4 mm of rain on September 24 and 4 mm of rain on September 30. There were no sudden changes in atmospheric conditions during the analyzed period. The tree inventory was conducted along two 500-meter sections in Warsaw, Poland, chosen for their varied tree canopy cover and essential role in city communication (Table 4), experiencing heavy traffic throughout the day, with an average of 1070 cars per hour on Marszałkowska Street and 1049 cars per hour on Żwirki i Wigury Street during rush hour [80]. Traffic measurement points coincided with the tree inventory locations at spot 2307 on Marszałkowska Street and spot 1306 on Żwirki i Wigury Street [80]. Both streets feature similar geometry, minimizing variability in pollution level measurements, as they lack bends or curves. Traffic characteristics (heavy traffic lane) at both studied locations and the characteristics of the tree system - a linear alley system, and the way the measurements has been carried out - measurements recorded along the alley, have registered the linear characteristics of air purification in the studied alley sections. Both of these streets, as shown by the orthophoto (Figure 1) are not canyons according to the accepted definition ( H / W ⩾1) [117]. None of the industrial emitters of pollution were located near the surveyed street sections [130]. The trees along these streets grow in public areas and are easily accessible. Marszałkowska Street predominantly features concrete squares, wide pavements, and commercial buildings, with minimal surrounding shrubbery (Figure 2). The street accommodates three traffic lanes in each direction, with a tree alley mostly comprising small-leaved linden trees (Tilia cordata Mill) planted in designated spaces between the pavement and the road. The surveyed section boasts a 6% tree canopy cover, with 59 trees averaging 18.05 cm in diameter and 5 meters in height. In contrast, Żwirki i Wigury Street (Figure 3), a primary thoroughfare bordered by four rows of trees, benefits from closer proximity to allotment gardens, resulting in a greater abundance of trees and other vegetation. With two traffic lanes in each direction separated by small-leaved linden trees, the surveyed section hosts 142 trees averaging 11 meters in height and boasting a 31% tree canopy cover (Table 4). Tree canopy cover was determined using QGIS. Methodology The principal sources of data utilized in the research included monitoring the PM2.5 concentration levels in urban streets with differing tree canopy cover (TCC) densities [65] during peak traffic periods and post-peak traffic periods. Additionally, tree inventory was conducted in selected locations, and the i-Tree Eco tool was employed to calculate the pollution removal capacity. Through data collected from these sources, the authors aim to assess the impact of trees on air quality in two distinct locations, identify statistically significant differences, and analyze the measurement findings of actual pollution levels alongside estimates provided by the i-Tree Eco model. Air quality monitoring Air quality monitoring was conducted at two locations: Marszałkowska Street and Żwirki i Wigury Street. Air quality sensors were strategically placed in central areas of one alley covered by trees and another devoid of tree cover, positioned 3 meters away from the edge of the road. Temtop M2000 sensors, versatile air quality meters capable of measuring PM2.5, PM10, CO2, HCHO, temperature, and humidity, were utilized for this purpose. Equipped with PM laser sensors and Non-Dispersive Infrared (NDIR) CO2 sensor, the Temtop M2000 meter offers measurements with an accuracy of 0.1 µg/m3 for PM2.5 dust, within a measurement range of 0-999 µg/m3 [111]. Air pollution concentration levels were recorded every minute during the monitoring period, spanning from 24th September 2021 to 8th October 2021, across two distinct time intervals: during rush hour and post-rush hour. Each sensor was stationed at the testing sites for 60 minutes during each period. Rush hour was defined as the timeframe between 4:00 p.m. and 6:00 p.m. on Mondays through Fridays, while non-rush hour periods encompassed the remaining time, excluding the hours between 8:00 a.m. and 10:00 a.m. Pollution measurements were taken at a consistent height of 1 meter, directly adjacent to vehicular traffic, at the edge of the sidewalk and roadway. The i-Tree Eco model The i-Tree Eco model guided the collection of field data following its prescribed protocols, as outlined in the i-Tree Eco User Manual [56]. Following the software's recommendations, one of the two tree sample selection options was employed, entailing a comprehensive survey of trees within the designated area. A thorough examination of trees in the research area was conducted, with data collection performed as per established procedures [64]. This encompassed documenting tree species and locations, alongside dendrometric measurements including trunk diameter (DBH), total tree height, live tree height, crown base, North-South crown width, East-West crown width, crown loss percentage, crown health, and crown light exposure. DBH measurements were obtained using a caliper at 130 cm above ground level, while measurements for other parameters were acquired utilizing a Bosch GLM120c laser measure with up to 0.5 m accuracy. Additionally, weather details and air quality data sourced from the i-Tree database, including PM2.5 concentration levels measured by PM level monitors positioned in Warsaw, were incorporated into the model. The i-Tree database facilitated access to meteorological data and air quality information. Subsequently, upon inputting all requisite data, the model was activated to generate estimates regarding the pollution removal efficacy of trees along Marszałkowska Street and Żwirki i Wigury Street. Furthermore, to ascertain the statistical significance of air quality measurement disparities between tree-covered and low tree cover segments, an analysis of PM2.5 concentration level differences was conducted utilizing R software. Statistics To illustrate the PM2.5 air pollution levels on Żwirki i Wigury Street and Marszałkowska Street, a comparison of average air pollution and the duration of recorded pollution levels (in minutes) in two categories: below 15 µg/m3 and above 15 µg/m3 was conducted. Both sets of data were presented by date and measurement time (high traffic or after the peak traffic). The results were analyzed using the pivot table tool in Microsoft Excel spreadsheet software. Additionally, line graphs were generated to depict the pollution levels on both streets throughout the entire study period. Results Air quality measurement The research yielded data on pollution concentration levels in two locations: Marszałkowska Street and Żwirki i Wigury Street (Tables 2 and 3). Pollution level measurements were conducted over 9 consecutive days, totaling 1074 minutes at a road segment with low tree density (Marszałkowska Street) and 1189 minutes in a tree-lined alley at Żwirki i Wigury Street. An overview of concentration levels in both locations is provided in histograms (Figures 2 and 3), while the average pollution levels at each street are shown in the tables. Monitoring was simultaneous in both locations, and any discrepancies may result from occasional failure to register current pollution concentration readings. Tables 2 and 3 depict exceedances of PM2.5 levels by peak hour, post-peak time, and total exceedance time by street. PM2.5 limits exceeded by values higher than 15 µg/m 3 were recorded 1.5 times more frequently on the street with low tree cover. Furthermore, PM2.5 limits exceeded by values higher than 15 µg/m 3 occurred 3.5 times more frequently in the same area, and limits exceeded by values higher than 25 µg/m 3 happened 14 times more frequently. Dust concentrations are also illustrated in the graphs (Figs. 2 and 3). Considering a similar level of traffic congestion and the same tree species in both locations, it can be inferred that the main reason for the difference in pollution concentration levels is the poorer condition of trees at Marszałkowska Street. The trees there grow in designated spaces cut out in the pavement (1,9x1,9m), resulting in inadequate access to water and insufficient space for root system growth. As a consequence of these harsh site conditions (high concentration of paved areas), tree canopy cover is only 6% in that area. Statistical analysis was conducted based on the collected data on PM concentration levels. A Shapiro-Wilk distribution test, covering PM2.5 concentration levels at roads with low and high tree canopy cover, revealed significantly different distribution patterns from the norm (p < 0.05). Additionally, a parametric Mann-Whitney test was performed to assess the sum of ranks. The resulting sum provided the rank difference, aiding in categorizing groups into two separate populations. This test showed a significant difference (W = 341450, p < 0.05) between concentration levels in a street covered with trees and a street with low tree cover. The median for PM2.5 concentration levels was 14 µg/m 3 in the segment of the street with low tree canopy cover and 10 µg/m 3 in the tree-covered alley. Additionally, an ANOVA table test was performed. The ANOVA table tests the overall significance of the model. The F-statistic of 120.103 with a p-value less than 0.001 indicates that the model is statistically significant, meaning at least one of the predictors has a significant impact on PM 2.5 removal value levels (Table 4). The multiple linear regression model demonstrates a strong relationship between the predictors (Crown % Miss, Total Tree Height, and Diameter) and the dependent variable (PM 2.5 removal value. The R-value of 0.837 suggests a high correlation between the predictors and the dependent variable. The model explains 70.1% of the variance in PM 2.5 removal value, as indicated by the R² value of 0.701. The adjusted R² is 0.695, meaning that the model maintains its explanatory power even when adjusting for the number of predictors. The table of coefficients provides insights into the individual contributions of each predictor: Diameter: The coefficient is 0.244 (p < 0.001), indicating a positive relationship between tree diameter and PM 2.5 removal value. A one-unit increase in Diameter is associated with a 0.244 increase in PM 2.5 removal value, holding other variables constant. Total Tree Height: The coefficient is 1.142 (p < 0.001), showing a strong positive impact on PM 2.5 removal value. An increase in tree height by one unit results in a 1.142 increase in PM 2.5 removal value. Crown % Miss: The coefficient is -0.148 (p < 0.001), meaning that a higher percentage of missing crown coverage reduces PM 2.5 removal value. For every 1% increase in Crown % Miss, PM 2.5 removal value decreases by 0.148. All predictors are statistically significant at the 0.001 level, confirming their strong contribution to the model. The i-Tree Eco model To prepare the model using the i-Tree Eco tool, a tree inventory was conducted at Marszałkowska Street (a segment with low TCC) and at Żwirki i Wigury Street (a segment with high TCC). The analysis of the tree inventory revealed that there were 59 trees along Marszałkowska Street, with the dominant species being Tilia cordata Mill. The diameter of the trees at Marszałkowska Street ranged mainly between 7.6 cm and 15.2 cm. Along the tree alley at Żwirki i Wigury Street, there were 142 trees, also predominantly Tilia cordata Mill., with diameters mainly between 30.5 cm and 45.7 cm [Table 1]. According to the i-Tree Eco report, the research was conducted on 500-meter-long street segments. After inputting the data, a model was launched using current data in the i-Tree Eco database on air pollution and meteorological conditions. The i-Tree Eco model assessed that the tree stand at Marszałkowska was capable of removing approximately 105.7 g of PM2.5 over the course of a year, while the tree stands at Żwirki i Wigury had the capacity to remove 1.52 kg of PM2 in a year. The highest value of PM2.5 absorption for a single tree at Żwirki i Wigury was 24 g over the whole year, while the result for Marszałkowska was 19.9 g. Tables 2 and 3 show average values of PM2.5 absorption for a single tree over the course of a year, indicating the variability of dust absorption throughout the year and in specific months in both locations. The average value of PM2.5 absorption for a single tree at Marszałkowska was 0.009 g, while the result for Żwirki i Wigury was 0.12 g. The highest capabilities of PM2.5 pollution absorption at Żwirki i Wigury were recorded in September and October, while records for Marszałkowska indicate the highest results in May, September, and October. The observed differences in the test results for average pollutant uptake by a single tree may be attributed to the smaller canopy cover of the trees at Marszałkowska and their limited growing conditions, as they were planted in small pits with restricted access to soil, which affected their health. Discussion As awareness of the impact of pollution on human health and the environment grows, measures to reduce urban air pollution are gaining prominence. Among these measures, planting trees has been identified as one of the most effective ways to mitigate dust and other pollutants [ 93 ]. Encouraging activities aimed at expanding wooded areas is therefore reasonable. Previous research conducted in Warsaw demonstrated that trees have the capacity to absorb significant amounts of air pollutants annually [ 64 ]. The study found that one tree on Marszalkowska Street absorbs an average of 89.38 grams of pollution per year, while a tree located on Zvirki i Wigury Street absorbs 390.39 grams of pollution per year. The result for individual trees was on average 4.5 times higher at Żwirki i Wigury Street. Our research confirms the finding that tree planting is an effective means of absorbing particulate matter. According to i-Tree Eco model estimates, an avenue with large, mature trees absorbs 1.52 kg of PM2.5 per year, while an avenue with small trees planted in tree pits set in the sidewalk absorbs only 105.7 g of PM2.5 per year. Annual PM exposure map prepared by Fisher et. al. [ 38 ] shoved that around 10% of the central city were those with pollutants concentration above the 20 µg/m 3 i.e. exceeding national annual guidelines. In our study, we found that even areas placed close to each other but differing by TCC could have different pollutant absorption - PM2.5 limits exceeded by values higher than 15 µg/m 3 were recorded 1.5 times more frequently on the street with low tree cover. Furthermore, PM2.5 limits exceeded by values higher than 15 µg/m 3 occurred 3.5 times more frequently in the same area, and limits exceeded by values higher than 25 µg/m 3 happened 14 times more frequently, which indicates the importance of detailed empirical analyses to complement the results obtained with the i-Tree model, essential in the decison-making process concerning urban forest planting and maintaining polices. In New Zealand, over a year trees have been removed approx. 300 tons of air pollutants in the area of Christchurch [ 15 ] but according to our results the same size of the studied area could have significantly different air pollution removal potential. It was found in the UK that planting trees on a quarter of the available urban area may lead to a decrease in PM10 concentration by 2 to 10% [ 77 ] in our study potential of mature and in good vitality trees was more than 14 times higher in comparison to trees growing in poor site condition in the empirical study. Considering similar levels of traffic volume and the same tree species in both locations, the median for PM2.5 concentration levels was 14 µg/m 3 in the segment of the street with low tree canopy cover and 10 µg/m 3 in the tree-covered alley. Our results point to the potential of high-quality green infrastructure for the well-being of city dwellers, especially those living in high PM2,5 concentration areas. The accepted daily standard for PM 2.5 is 25ug/m3. In our study, we checked the actual concentrations of PM 2.5. Marszalkowska Street recorded 28 exceedances above the specified level during peak hours, while Żwirki i Wigury Street recorded 2 exceedances. As research specifies, particulate matter (PM) has the most detrimental effect on public health and the environment [ 38 , 101 ]. It is due to the size of the particles - hence anthropogenic dust is considered the highest risk to human health [ 14 ]. Inhaling PM causes the particles to accumulate in lung tissue and enter the bloodstream, which in turn leads to a higher risk of circulatory and pulmonary illnesses [ 17 ], chronic obstructive pulmonary disease, and lung cancer [ 60 ]. Research shows that lung cancer incidence in Beijing was 1.055 for men and 1.149 for women and the increase in incidence was caused by the increase of PM2.5 levels by 10 mg -3 [ 46 ]. Inhaling dust also causes deterioration of health in respiratory illnesses such as asthma [ 7 , 11 ] and leads to respiratory infections in children [ 7 ]. The iTree data shows that the absorption of pollutants in the low-density tree canopy cower area is 14 times lower but does not show how often pollution exceeds levels dangerous to the health of city dwellers, so the novelty of our study is to provide new information illustrating the risks to human health and life and to determine periods of time when the health risk is significant. This knowledge allows countermeasures to be taken, ranging from alerting residents to taking action to improve the quality of green infrastructure, for example through efforts to increase tree canopy cover and as a result risk mitigating. Studies using models like the i-Tree Eco model in Barcelona and the UFORE model in Perth have quantified the removal of air pollutants by urban forests. The survey was conducted for the entire city area, where tree canopy coverage is 22%. In the case of the study from Australia, the amount of PM10 removed was converted to m2 and was 16.0 g/year/m2. However, there is a need for tools that are validated with actual pollution data, as many studies rely on models. The i-Tree Eco model, while widely available, lacks studies verifying its accuracy, especially regarding comparisons of dust concentrations in areas with varying vegetation cover. Our study aimed to address this gap by comparing actual pollution measurements with i-Tree Eco model estimates in areas with different tree canopy cover. Although the results of analyses using the model for cities have been conducted [ 96 ] but there is a lack of verification using empirical methods that provide data on the specifics of pollution distribution. From the results of our study, it can be concluded that urban trees contribute to improving urban air quality and human health. However, there are uncertainties regarding the accuracy of tools like the i-Tree Eco model in estimating pollutant absorption. Further research is needed to validate and refine these models. Studies conducted in various locations, including Warsaw, Shanghai, New Zealand, and China, have shown that trees are effective in reducing air pollution levels. However, the effectiveness of trees in absorbing pollutants may vary depending on habitat conditions and tree canopy cover. Our study highlights the importance of adequate tree canopy cover in urban areas for maximizing the benefits of air pollutant removal crucial for the prevention of human health toxicity from exceeding air pollution norms. The analysis of air quality standards in Warsaw indicates that exceedances of these standards are frequent, particularly during peak hours. This underscores the need for further research on urban trees and air pollution using dust sensors, as most studies to date have relied on models rather than experimental data [ 64 , 96 ]. Holnicki et. al. [ 131 ] conducted a study that consisted of running a model in the CALMET/CALPUFF tool. Based on the model, they determined the most polluted places in Warsaw. Work with the execution of generalized regression models (GRM) was also carried out by Majewski et. al. [132]. The impact of air pollution on visibility in the Warsaw metropolitan area, which was determined based on the aforementioned model, was investigated. Despite the conclusions of King et. al. [ 68 ] that who suggested that tree canopy cover likely has at most a small impact on neighborhood air quality visible in PM2.5 concentration and represents a lack of pollution sources rather than active pollution removal we have found that on the same type of urban site and location in the city center, but with low tree canopy cover – 6% TCC (Marszałkowska Street), PM 2,5 absorption was found to be almost 14.5 times lower than on area with tree canopy cover meeting the assumptions of optimal green infrastructure density – 31% (Żwirki and Wigury Street). We assumed rather than the habitat conditions of the trees at Żwirki i Wigury Street positively affect the possibility of greater absorption of pollutants through greater opportunities for tree growth. According to Urban [ 114 ] and Trowbridge et. al. [ 114 ], trees need a suitable rooting space to develop properly and at the same time maximize ecosystem services. In the case of studied trees (average DBH is 18,05 cm) recommended soil volume for rooting is 13 m 3 [ 114 ] in reality, tree pits provide 3,6 m 3 for rooting. Difficult habitat conditions (isolated tree pits) on Marszalkowska Street resulting in poor tree health, limit the ability of trees to absorb air pollutants. Maximizing ecosystem services in this area requires modifying (improving) habitat conditions. A study by Warsaw scientists [ 86 ] showed that trees with limited rooting areas have more difficult conditions to develop than trees growing in the reserve. The differences associated with the number of mycorrhizal tops and mycorrhizal species were related to organic matter levels and soil chemical parameters, which were less favorable for root development in the rooting space limited by paving. Moreover, 25 years long research was conducted on the average life span of trees in roadside greenery zones [ 27 ]), which showed that the average life expectancy of trees growing in small tree pits along Marszałkowska Street was 10–12 years. This indicates that it is not possible for a tree to reach full maturity and therefore high ecosystem service provision in excessively limited rooting space, common in urban locations. Conclusions In conclusion, while there is growing public awareness of the importance of addressing urban air pollution, further research is needed to inform evidence-based decision-making in this area. The use of the potential of urban areas, expressed in the availability of optimal site conditions for the healthy growth of trees resulted, in our study, in more than 14 times greater effectiveness of trees in cleaning the air from PM 2.5. Our study contributes to this effort by providing empirical data on the effectiveness of trees in mitigating air pollution, but more research is warranted to fully understand the complexities of this issue. Declarations Author Contribution All authors wrote the main text of the manuscript. KK prepared the drawings.MG has prepared tables. Data Availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. References Akbari, H., Pomerantz, M., & Taha, H. (2001). Cool surfaces and shade trees to reduce energy use and improve air quality in urban areas. 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Environmental Pollution , 159 (8–9), 2155–2163. https://doi.org/10.1016/J.ENVPOL.2011.03.009 Zanobetti, A., & Schwartz, J. (2012). Mortality Displacement in the Association of Ozone with Mortality. American Journal of Respiratory and Critical Care Medicine , 177 (2), 184–189. https://doi.org/10.1164/RCCM.200706-823OC Zhang, S., & Witlox, F. (2020). Analyzing the impact of different transport governance strategies on climate change. Sustainability (Switzerland) , 12 (1), 200. https://doi.org/10.3390/su12010200Tao, Miaomiao & Xu, Ying & Liu, Qingyang & Liu, Yanju & Tian, Shili & Schauer, James. (2023). Penetration of submicron amino‑functionalized graphene quantum dots in plant stomata, implication for the depollution of atmospheric soot particles. Environmental Chemistry Letters. 1281-1286. 10.1007/s10311-022-01535-5. Spatial Information System (2022). https://geoportal.gov.pl Holnicki, P., Kałuszko, A., Nahorski, Z., Stankiewicz, K., Trapp, W. (2017). Air quality modeling for Warsaw agglomeration. 42-64, DOI 10.1515/aep-2017-0005 Majewski, G., Czechowski, P., Badyda, A., Brandyk, A. (2014). Effect of air pollution on visibility in urban conditions. Warsaw Case Study. Environment Protection Engineering. DOI: 10.5277/epe140204 Tables Tables 1 to 4 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.docx Table2.docx Table3.docx Table4.doc Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5461393","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":441071360,"identity":"fc982869-9bd9-41df-989d-4ec474a72f15","order_by":0,"name":"Karolina 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22:59:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":18129,"visible":true,"origin":"","legend":"\u003cp\u003eŻwirki I Wigury Street – PM 2.5 pollution level\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5461393/v1/717a014f719f9a639a1a4d97.png"},{"id":80579015,"identity":"8c65e46f-9138-42ab-9f91-1b21a2be21c5","added_by":"auto","created_at":"2025-04-14 23:07:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":26231,"visible":true,"origin":"","legend":"\u003cp\u003eMarszałkowska Street – PM 2.5 pollution level\u003c/p\u003e\n\u003cp\u003eX-axis: Date of the test\u003c/p\u003e\n\u003cp\u003eY-axis concentration of air 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23:23:05","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":16290,"visible":true,"origin":"","legend":"","description":"","filename":"Table3.docx","url":"https://assets-eu.researchsquare.com/files/rs-5461393/v1/aad476cdd19d3553a0ccaedc.docx"},{"id":80579016,"identity":"ba460122-f96c-49bf-ada1-d5374d10268c","added_by":"auto","created_at":"2025-04-14 23:07:05","extension":"doc","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":15360,"visible":true,"origin":"","legend":"","description":"","filename":"Table4.doc","url":"https://assets-eu.researchsquare.com/files/rs-5461393/v1/8f4ddd3dcb13096a5284670c.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluating Air Pollution in Two Urban Alleys and Comparing Tree Capacity for PM Dust Absorption: A Case Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAir pollution is a topic of extensive discourse in both public discourse and scientific circles, owing to the persistent rise in environmental challenges resulting from rapid economic development. While urbanization brings forth numerous social advantages, it also serves as a significant contributor to environmental issues [89, 115]. The widespread conversion of green spaces into concrete structures such as plazas, residential complexes, or shopping centers diminishes the presence of greenery in cities, consequently exacerbating smog formation and urban air pollution.\u003c/p\u003e\n\u003cp\u003eThis trend correlates with a multitude of health issues [32, 59, 87]. Expert studies highlight air pollution as a notable concern, with many substances outlined in European Council Directives: 96/62/EC, 1999/30/EC, 2002/3/EC, 2008/50/EC [21, 22, 23, 24] reaching concentrations hazardous to human life and health [4, 127]. The primary sources of pollution include open fires, a high volume of motor vehicles in suboptimal conditions, and outdated industrial facilities [33]. Studies, exemplified by those conducted in China, attribute air pollution primarily to coal combustion and industrial processes during the early stages of economic development [62]. Additionally, exhaust emissions pose a significant concern in urban locales [62]. Hazardous pollutants include carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), lead (Pb), sulfur dioxide (SO2) [30, 36, 39, 74], as well as particulate matter (PM) \u0026ndash; dust with an aerodynamic diameter less than 10 microns (PM10) and suspended dust with an aerodynamic diameter less than 2.5 microns [108]. Numerous studies examining air pollution\u0026apos;s health impacts have revealed its detrimental effects on respiratory, circulatory, vascular, and neurological systems, leading to declines in overall health [32, 59, 87, 91]\u003c/p\u003e\n\u003cp\u003eAs indicated by many researchers, particulate matter (PM) stands out as having the most significant detrimental impact on both public health and the environment [101]. This is primarily due to the size of the particles, making anthropogenic dust the highest risk to human health [14]. Inhaling PM leads to the accumulation of particles in lung tissue and entry into the bloodstream, thereby increasing the risk of circulatory and pulmonary diseases [17], including chronic obstructive pulmonary disease and lung cancer [60]. For instance, studies demonstrate that in Beijing, a 10 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e increase in PM2.5 levels corresponded with a rise in lung cancer incidence for both men (1.055) and women (1.149) [46]. In addition to respiratory illnesses like asthma [7, 11], inhaling dust also exacerbates respiratory infections in children [7]. Epidemiological evidence further suggests that particulate matter, particularly PM2.5, may lead to premature death [48]. It\u0026apos;s important to note that air pollution adversely affects health not only through inhalation but also through skin absorption resulting from contact with contaminated water or food [25]. Furthermore, the issue of air pollution\u0026apos;s impact on health has substantially escalated healthcare costs [53, 76] and continues to pose a significant threat to public health despite advancements in medicine.\u003c/p\u003e\n\u003cp\u003eAnthropogenic pollution sources primarily originate from urban agglomerations [29, 45, 128] characterized by heavy road traffic, high residential density, and large-scale industrial activities [98]. Consequently, the direct influence of air pollution on public health is most pronounced in industrialized and urbanized areas.\u003c/p\u003e\n\u003cp\u003eEstimates project that ongoing migration from rural to urban areas will drive an increase in urban populations, expected to reach 60% by 2030 [12], 70% by 2050 globally [37], and 82% in the EU [124]. While urbanization offers numerous social advantages, it remains a significant contributor to environmental issues such as the Urban Heat Island (UHI) effect [2, 9, 54, 89], primarily driven by land use changes and residential expansion [88, 113]. Research conducted by the WHO confirms that outdoor air pollution has surged by 8% globally in the last five years across more than 3000 cities [122].\u003c/p\u003e\n\u003cp\u003eThe only similar studies we\u0026apos;ve found so far are those by Riondato et. al. 2020 [94], which examine air quality impacts in Dublin with a link to the i-Tree Eco model. The others mainly analyze model assumptions at the scale of, for example, the city of Warsaw [96], Krakow [95] or macro-regions such as Great Britain [99]. For this reason, we wish to analyze the issue for the local scale in Warsaw.\u003c/p\u003e\n\u003ch3\u003ePlants and PM air pollution\u003c/h3\u003e\n\u003cp\u003eAs urban air pollution escalates, the importance of tree canopy cover (TCC) in urban areas becomes increasingly significant [1], given its provision of numerous ecosystem functions for citizens [34]. Among these functions, trees play a pivotal role in atmospheric air filtration and the retention of toxic substances [43; 104]. Research underscores that plants are among the most effective agents for eliminating suspended particulate matter from the environment [93, 125]. Urban trees enhance air quality by facilitating the deposition of various gases and solid particles, owing to their extensive foliage surface area and their influence on microclimate and air turbulence [44].\u003c/p\u003e\n\u003cp\u003ePollution removal by plants occurs via two primary mechanisms: sediment collection on plant surfaces and absorption by stomata [121]. Studies demonstrate that trees in Christchurch, New Zealand, removed approximately 300 tons of air pollutants annually [15]. Similarly, in the UK, planting trees on a quarter of available urban land could potentially decrease PM10 concentrations by 2 to 10% [77]. However, the effectiveness of pollution absorption by trees hinges on three key factors: air movement within the tree crown, air transfer near the tree surface, and surface absorption capacity, dependent on stomatal conductance [120].\u003c/p\u003e\n\u003cp\u003eThe deposition of particulate pollutants primarily occurs on leaf surfaces [44], with the ultra-structures of wax crystals significantly contributing to PM adsorption [118]. Additionally, studies suggest that the stomata of plants can remove soot particles from the environment [129]. Tree species that maintain open stomata longer tend to absorb pollutants more efficiently than isohydrotic species [26].\u003c/p\u003e\n\u003cp\u003eDespite the pollutant retention properties of tree surfaces [75], the efficacy of this function varies among different tree species [5, 75]. Dust retention efficiency depends on factors such as leaf micromorphology, leaf density, and crown type [6, 13, 40, 66, 92, 98, 100, 102, 106]. Coniferous trees are found to be more effective in PM10 absorption than deciduous trees [5], and among deciduous species, those with rough-surfaced leaves exhibit greater efficiency in PM2.5 absorption [6, 55]. Consequently, the selection of tree species plays a crucial role in maximizing dust absorption efficiency [19].\u003c/p\u003e\n\u003cp\u003eFurthermore, the absorption of PM2.5 is influenced not only by trees but also by the presence of other specific species in the vicinity [102]. Beyond individual trees, the reduction of dust volume and particle filtration in urban areas can also be attributed to green belts or zones comprising natural or planted greenery. [119]. Research conducted by Yin et al. [126] demonstrated that the concentration of PM2.5 decreased by 9% in forested areas adjacent to urban areas [126]. However, the crucial role of trees may be overlooked in many countries, including Poland, where there\u0026apos;s a growing trend of removing greenery from public spaces and replacing it with concrete [78].\u003c/p\u003e\n\u003cdiv id=\"Sec3\"\u003e\n \u003ch2\u003eTools used to measure the trees\u0026rsquo; capability to remove pollution\u003c/h2\u003e\n \u003cp\u003eThe Urban Forest Effects (UFORE) tool serves as a valuable instrument for evaluating the efficacy of urban forests, allowing researchers and governing bodies to gauge their functionality and structure based on field data, meteorological observations, and on-site pollution assessments [3, 85]. UFORE\u0026apos;s capabilities extend to calculating various parameters, including total stored carbon, net carbon sequestered by urban trees, effects on building energy usage and CO2 emissions, and the estimated impact of tree species on air quality improvement and pollution removal [85]. Additionally, the model features a component for estimating the volume of pollution removed by plants [52].\u003c/p\u003e\n \u003cp\u003eDerived from the UFORE model, the i-Tree Eco tool, developed by the United States Forest Service (USFS), offers a comprehensive analysis of urban tree structure, species, and health status to assess the ecosystem services provided by trees [85]. Studies utilizing i-Tree Eco have revealed that factors such as planting density, total leaf surface area, phenology, and spatial arrangement contribute to pollution removal at the tree group level [10; 47; 83]. At the individual tree level, leaf characteristics and growth patterns play significant roles in PM2.5 removal efficiency, with optimal environmental benefits observed when crown density and leaf area index (LAI) are approximately 50\u0026ndash;60% and 1.5-2.0, respectively.\u003c/p\u003e\n \u003cp\u003eWith over half of the global population residing in urban areas according to the United Nations (UN), there is a pressing need to conduct studies involving real measurements of air pollution and to explore commonly used tools for measuring urban air quality (United Nations, n.d.). While analyses employing dust sensors necessitate specialized equipment and advanced analytical methods, the i-Tree Eco model offers a readily accessible and free-of-charge alternative. However, the accuracy of the i-Tree Eco model, particularly in comparing dust concentrations in vegetated versus non-vegetated areas, warrants further investigation, as empirical validation studies remain scarce. Our study aims to address this gap by innovatively calibrating low and high canopy coverage streets for air particulate matter concentrations using a combination of field measurements and i-Tree Eco simulations, thus providing valuable insights into ecosystem services assessment opportunities, especially concerning tree canopy cover (TCC) variances.\u003c/p\u003e\n \u003cp\u003eTherefore, our research was designed to examine the potential impact of urban vegetation on air pollutant concentrations at the local scale, considering that some studies suggest urban vegetation may inadvertently elevate air pollutant levels. Our aim was to uncover the true extent of this issue and assess the associated human health risks posed by inadequate vegetation, particularly trees, in urban environments amidst prevailing air pollution challenges.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Materials \u0026 Methods","content":"\u003cp\u003e\u003cstrong\u003eCase study area description\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWarsaw, the capital of Poland and the largest city in the country, situated at the heart of Europe, was chosen as the research area (Figure 1). With a surface area of 517.2 km\u003csup\u003e2\u003c/sup\u003e and a population of 1,792,718 (Poland in numbers, 2020), Warsaw, like many other Polish cities, grapples with severe air quality issues on a global scale. In January 2017, the city experienced one of its most severe smog episodes, with pollution levels exceeding air quality standards across much of Poland. During this period, the permissible average concentrations of PM10 were surpassed on 19-22 days, accounting for 60-70% of the month, while PM2.5 concentrations exceeded standards on 25-28 days, covering 80-90% of the month [65]. In January 2021, Warsaw ranked 6th among cities with the lowest air quality according to the Air Quality Index [72]. Additionally, the World Air Quality Ranking in February 2021 identified Warsaw as the city with the second-worst air quality globally, with PM10 concentrations exceeding by 232% and PM2.5 levels by a staggering 364% [70]. Subsequently, in March, Warsaw topped the IQAir ranking as the most polluted major city in the world [57], underscoring its selection as the research focus. The average daily lowest temperature was recorded at 8.2°C, and the average daily highest temperature reached 15.9°. The average daily lowest humidity rate was 71.9%, the recorded highest daily humidity rate was 90.1%. Wind speed during the analyzed period ranged from 2 to 7 m/s with gusts of 4 to 16 m/s occurring. \u0026nbsp;Precipitation occurred 3 times - 2.4 mm of rain fell on September 23, 0.4 mm of rain on September 24 and 4 mm of rain on September 30. There were no sudden changes in atmospheric conditions during the analyzed period.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe tree inventory was conducted along two 500-meter sections in Warsaw, Poland, chosen for their varied tree canopy cover and essential role in city communication (Table 4), experiencing heavy traffic throughout the day, with an average of 1070 cars per hour on Marszałkowska Street and 1049 cars per hour on Żwirki i Wigury Street during rush hour [80]. Traffic measurement points coincided with the tree inventory locations at spot 2307 on Marszałkowska Street and spot 1306 on Żwirki i Wigury Street [80]. Both streets feature similar geometry, minimizing variability in pollution level measurements, as they lack bends or curves. Traffic characteristics (heavy traffic lane) at both studied locations and the characteristics of the tree system - a linear alley system, and the way the measurements has been carried out - measurements recorded along the alley, have registered the linear characteristics of air purification in the studied alley sections. Both of these streets, as shown by the orthophoto (Figure 1) are not canyons according to the accepted definition ( H / W ⩾1) [117]. None of the industrial emitters of pollution were located near the surveyed street sections [130]. The trees along these streets grow in public areas and are easily accessible. Marszałkowska Street predominantly features concrete squares, wide pavements, and commercial buildings, with minimal surrounding shrubbery (Figure 2). The street accommodates three traffic lanes in each direction, with a tree alley mostly comprising small-leaved linden trees (Tilia cordata Mill) planted in designated spaces between the pavement and the road. The surveyed section boasts a 6% tree canopy cover, with 59 trees averaging 18.05 cm in diameter and 5 meters in height. In contrast, Żwirki i Wigury Street (Figure 3), a primary thoroughfare bordered by four rows of trees, benefits from closer proximity to allotment gardens, resulting in a greater abundance of trees and other vegetation. With two traffic lanes in each direction separated by small-leaved linden trees, the surveyed section hosts 142 trees averaging 11 meters in height and boasting a 31% tree canopy cover (Table 4). Tree canopy cover was determined using QGIS.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe principal sources of data utilized in the research included monitoring the PM2.5 concentration levels in urban streets with differing tree canopy cover (TCC) densities [65] during peak traffic periods and post-peak traffic periods. Additionally, tree inventory was conducted in selected locations, and the i-Tree Eco tool was employed to calculate the pollution removal capacity. Through data collected from these sources, the authors aim to assess the impact of trees on air quality in two distinct locations, identify statistically significant differences, and analyze the measurement findings of actual pollution levels alongside estimates provided by the i-Tree Eco model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAir quality monitoring\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAir quality monitoring was conducted at two locations: Marszałkowska Street and Żwirki i Wigury Street. Air quality sensors were strategically placed in central areas of one alley covered by trees and another devoid of tree cover, positioned 3 meters away from the edge of the road. Temtop M2000 sensors, versatile air quality meters capable of measuring PM2.5, PM10, CO2, HCHO, temperature, and humidity, were utilized for this purpose. Equipped with PM laser sensors and Non-Dispersive Infrared (NDIR) CO2 sensor, the Temtop M2000 meter offers measurements with an accuracy of 0.1 µg/m3 for PM2.5 dust, within a measurement range of 0-999 µg/m3 [111]. Air pollution concentration levels were recorded every minute during the monitoring period, spanning from 24th September 2021 to 8th October 2021, across two distinct time intervals: during rush hour and post-rush hour. Each sensor was stationed at the testing sites for 60 minutes during each period. Rush hour was defined as the timeframe between 4:00 p.m. and 6:00 p.m. on Mondays through Fridays, while non-rush hour periods encompassed the remaining time, excluding the hours between 8:00 a.m. and 10:00 a.m. Pollution measurements were taken at a consistent height of 1 meter, directly adjacent to vehicular traffic, at the edge of the sidewalk and roadway.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe i-Tree Eco model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe i-Tree Eco model guided the collection of field data following its prescribed protocols, as outlined in the i-Tree Eco User Manual [56]. Following the software's recommendations, one of the two tree sample selection options was employed, entailing a comprehensive survey of trees within the designated area. A thorough examination of trees in the research area was conducted, with data collection performed as per established procedures [64]. This encompassed documenting tree species and locations, alongside dendrometric measurements including trunk diameter (DBH), total tree height, live tree height, crown base, North-South crown width, East-West crown width, crown loss percentage, crown health, and crown light exposure. DBH measurements were obtained using a caliper at 130 cm above ground level, while measurements for other parameters were acquired utilizing a Bosch GLM120c laser measure with up to 0.5 m accuracy. Additionally, weather details and air quality data sourced from the i-Tree database, including PM2.5 concentration levels measured by PM level monitors positioned in Warsaw, were incorporated into the model. The i-Tree database facilitated access to meteorological data and air quality information. Subsequently, upon inputting all requisite data, the model was activated to generate estimates regarding the pollution removal efficacy of trees along Marszałkowska Street and Żwirki i Wigury Street. Furthermore, to ascertain the statistical significance of air quality measurement disparities between tree-covered and low tree cover segments, an analysis of PM2.5 concentration level differences was conducted utilizing R software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo illustrate the PM2.5 air pollution levels on Żwirki i Wigury Street and Marszałkowska Street, a comparison of average air pollution and the duration of recorded pollution levels (in minutes) in two categories: below 15 µg/m3 and above 15 µg/m3 was conducted. Both sets of data were presented by date and measurement time (high traffic or after the peak traffic). The results were analyzed using the pivot table tool in Microsoft Excel spreadsheet software. Additionally, line graphs were generated to depict the pollution levels on both streets throughout the entire study period.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eAir quality measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research yielded data on pollution concentration levels in two locations: Marszałkowska Street and Żwirki i Wigury Street (Tables 2 and 3). Pollution level measurements were conducted over 9 consecutive days, totaling 1074 minutes at a road segment with low tree density (Marszałkowska Street) and 1189 minutes in a tree-lined alley at Żwirki i Wigury Street. An overview of concentration levels in both locations is provided in histograms (Figures 2 and 3), while the average pollution levels at each street are shown in the tables. Monitoring was simultaneous in both locations, and any discrepancies may result from occasional failure to register current pollution concentration readings. Tables 2 and 3 depict exceedances of PM2.5 levels by peak hour, post-peak time, and total exceedance time by street. PM2.5 limits exceeded by values higher than 15 µg/m\u003csup\u003e3\u003c/sup\u003e were recorded 1.5 times more frequently on the street with low tree cover. Furthermore, PM2.5 limits exceeded by values higher than 15 µg/m\u003csup\u003e3\u003c/sup\u003e occurred 3.5 times more frequently in the same area, and limits exceeded by values higher than 25 µg/m\u003csup\u003e3\u003c/sup\u003e happened 14 times more frequently. Dust concentrations are also illustrated in the graphs (Figs. 2 and 3). Considering a similar level of traffic congestion and the same tree species in both locations, it can be inferred that the main reason for the difference in pollution concentration levels is the poorer condition of trees at Marszałkowska Street. The trees there grow in designated spaces cut out in the pavement (1,9x1,9m), resulting in inadequate access to water and insufficient space for root system growth. As a consequence of these harsh site conditions (high concentration of paved areas), tree canopy cover is only 6% in that area.\u003c/p\u003e\n\u003cp\u003eStatistical analysis was conducted based on the collected data on PM concentration levels. A Shapiro-Wilk distribution test, covering PM2.5 concentration levels at roads with low and high tree canopy cover, revealed significantly different distribution patterns from the norm (p \u0026lt; 0.05). Additionally, a parametric Mann-Whitney test was performed to assess the sum of ranks. The resulting sum provided the rank difference, aiding in categorizing groups into two separate populations. This test showed a significant difference (W = 341450, p \u0026lt; 0.05) between concentration levels in a street covered with trees and a street with low tree cover. The median for PM2.5 concentration levels was 14 µg/m\u003csup\u003e3\u003c/sup\u003e in the segment of the street with low tree canopy cover and 10 µg/m\u003csup\u003e3\u003c/sup\u003e in the tree-covered alley. Additionally, an ANOVA table test was performed. The ANOVA table tests the overall significance of the model. The F-statistic of 120.103 with a p-value less than 0.001 indicates that the model is statistically significant, meaning at least one of the predictors has a significant impact on PM 2.5 removal value levels (Table 4). The multiple linear regression model demonstrates a strong relationship between the predictors (Crown % Miss, Total Tree Height, and Diameter) and the dependent variable (PM 2.5 removal value. The R-value of 0.837 suggests a high correlation between the predictors and the dependent variable. The model explains 70.1% of the variance in PM 2.5 removal value, as indicated by the R² value of 0.701. The adjusted R² is 0.695, meaning that the model maintains its explanatory power even when adjusting for the number of predictors. The table of coefficients provides insights into the individual contributions of each predictor: Diameter: The coefficient is 0.244 (p \u0026lt; 0.001), indicating a positive relationship between tree diameter and PM 2.5 removal value. A one-unit increase in Diameter is associated with a 0.244 increase in PM 2.5 removal value, holding other variables constant. Total Tree Height: The coefficient is 1.142 (p \u0026lt; 0.001), showing a strong positive impact on PM 2.5 removal value. An increase in tree height by one unit results in a 1.142 increase in PM 2.5 removal value. Crown % Miss: The coefficient is -0.148 (p \u0026lt; 0.001), meaning that a higher percentage of missing crown coverage reduces PM 2.5 removal value. For every 1% increase in Crown % Miss, PM 2.5 removal value decreases by 0.148. All predictors are statistically significant at the 0.001 level, confirming their strong contribution to the model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe i-Tree Eco model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo prepare the model using the i-Tree Eco tool, a tree inventory was conducted at Marszałkowska Street (a segment with low TCC) and at Żwirki i Wigury Street (a segment with high TCC). The analysis of the tree inventory revealed that there were 59 trees along Marszałkowska Street, with the dominant species being Tilia cordata Mill. The diameter of the trees at Marszałkowska Street ranged mainly between 7.6 cm and 15.2 cm. Along the tree alley at Żwirki i Wigury Street, there were 142 trees, also predominantly Tilia cordata Mill., with diameters mainly between 30.5 cm and 45.7 cm [Table 1]. According to the i-Tree Eco report, the research was conducted on 500-meter-long street segments. After inputting the data, a model was launched using current data in the i-Tree Eco database on air pollution and meteorological conditions. The i-Tree Eco model assessed that the tree stand at Marszałkowska was capable of removing approximately 105.7 g of PM2.5 over the course of a year, while the tree stands at Żwirki i Wigury had the capacity to remove 1.52 kg of PM2 in a year. The highest value of PM2.5 absorption for a single tree at Żwirki i Wigury was 24 g over the whole year, while the result for Marszałkowska was 19.9 g. Tables 2 and 3 show average values of PM2.5 absorption for a single tree over the course of a year, indicating the variability of dust absorption throughout the year and in specific months in both locations. The average value of PM2.5 absorption for a single tree at Marszałkowska was 0.009 g, while the result for Żwirki i Wigury was 0.12 g. The highest capabilities of PM2.5 pollution absorption at Żwirki i Wigury were recorded in September and October, while records for Marszałkowska indicate the highest results in May, September, and October. The observed differences in the test results for average pollutant uptake by a single tree may be attributed to the smaller canopy cover of the trees at Marszałkowska and their limited growing conditions, as they were planted in small pits with restricted access to soil, which affected their health.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAs awareness of the impact of pollution on human health and the environment grows, measures to reduce urban air pollution are gaining prominence. Among these measures, planting trees has been identified as one of the most effective ways to mitigate dust and other pollutants [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e]. Encouraging activities aimed at expanding wooded areas is therefore reasonable. Previous research conducted in Warsaw demonstrated that trees have the capacity to absorb significant amounts of air pollutants annually [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. The study found that one tree on Marszalkowska Street absorbs an average of 89.38 grams of pollution per year, while a tree located on Zvirki i Wigury Street absorbs 390.39 grams of pollution per year. The result for individual trees was on average 4.5 times higher at Żwirki i Wigury Street. Our research confirms the finding that tree planting is an effective means of absorbing particulate matter. According to i-Tree Eco model estimates, an avenue with large, mature trees absorbs 1.52 kg of PM2.5 per year, while an avenue with small trees planted in tree pits set in the sidewalk absorbs only 105.7 g of PM2.5 per year.\u003c/p\u003e \u003cp\u003eAnnual PM exposure map prepared by Fisher et. al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] shoved that around 10% of the central city were those with pollutants concentration above the 20 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e i.e. exceeding national annual guidelines. In our study, we found that even areas placed close to each other but differing by TCC could have different pollutant absorption - PM2.5 limits exceeded by values higher than 15 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e were recorded 1.5 times more frequently on the street with low tree cover. Furthermore, PM2.5 limits exceeded by values higher than 15 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e occurred 3.5 times more frequently in the same area, and limits exceeded by values higher than 25 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e happened 14 times more frequently, which indicates the importance of detailed empirical analyses to complement the results obtained with the i-Tree model, essential in the decison-making process concerning urban forest planting and maintaining polices. In New Zealand, over a year trees have been removed approx. 300 tons of air pollutants in the area of Christchurch [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] but according to our results the same size of the studied area could have significantly different air pollution removal potential. It was found in the UK that planting trees on a quarter of the available urban area may lead to a decrease in PM10 concentration by 2 to 10% [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e] in our study potential of mature and in good vitality trees was more than 14 times higher in comparison to trees growing in poor site condition in the empirical study. Considering similar levels of traffic volume and the same tree species in both locations, the median for PM2.5 concentration levels was 14 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e in the segment of the street with low tree canopy cover and 10 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e in the tree-covered alley. Our results point to the potential of high-quality green infrastructure for the well-being of city dwellers, especially those living in high PM2,5 concentration areas. The accepted daily standard for PM 2.5 is 25ug/m3. In our study, we checked the actual concentrations of PM 2.5. Marszalkowska Street recorded 28 exceedances above the specified level during peak hours, while Żwirki i Wigury Street recorded 2 exceedances. As research specifies, particulate matter (PM) has the most detrimental effect on public health and the environment [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e]. It is due to the size of the particles - hence anthropogenic dust is considered the highest risk to human health [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Inhaling PM causes the particles to accumulate in lung tissue and enter the bloodstream, which in turn leads to a higher risk of circulatory and pulmonary illnesses [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], chronic obstructive pulmonary disease, and lung cancer [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Research shows that lung cancer incidence in Beijing was 1.055 for men and 1.149 for women and the increase in incidence was caused by the increase of PM2.5 levels by 10 mg -3 [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Inhaling dust also causes deterioration of health in respiratory illnesses such as asthma [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and leads to respiratory infections in children [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The iTree data shows that the absorption of pollutants in the low-density tree canopy cower area is 14 times lower but does not show how often pollution exceeds levels dangerous to the health of city dwellers, so the novelty of our study is to provide new information illustrating the risks to human health and life and to determine periods of time when the health risk is significant. This knowledge allows countermeasures to be taken, ranging from alerting residents to taking action to improve the quality of green infrastructure, for example through efforts to increase tree canopy cover and as a result risk mitigating. Studies using models like the i-Tree Eco model in Barcelona and the UFORE model in Perth have quantified the removal of air pollutants by urban forests. The survey was conducted for the entire city area, where tree canopy coverage is 22%. In the case of the study from Australia, the amount of PM10 removed was converted to m2 and was 16.0 g/year/m2. However, there is a need for tools that are validated with actual pollution data, as many studies rely on models. The i-Tree Eco model, while widely available, lacks studies verifying its accuracy, especially regarding comparisons of dust concentrations in areas with varying vegetation cover. Our study aimed to address this gap by comparing actual pollution measurements with i-Tree Eco model estimates in areas with different tree canopy cover. Although the results of analyses using the model for cities have been conducted [\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e] but there is a lack of verification using empirical methods that provide data on the specifics of pollution distribution. From the results of our study, it can be concluded that urban trees contribute to improving urban air quality and human health. However, there are uncertainties regarding the accuracy of tools like the i-Tree Eco model in estimating pollutant absorption. Further research is needed to validate and refine these models.\u003c/p\u003e \u003cp\u003eStudies conducted in various locations, including Warsaw, Shanghai, New Zealand, and China, have shown that trees are effective in reducing air pollution levels. However, the effectiveness of trees in absorbing pollutants may vary depending on habitat conditions and tree canopy cover. Our study highlights the importance of adequate tree canopy cover in urban areas for maximizing the benefits of air pollutant removal crucial for the prevention of human health toxicity from exceeding air pollution norms. The analysis of air quality standards in Warsaw indicates that exceedances of these standards are frequent, particularly during peak hours. This underscores the need for further research on urban trees and air pollution using dust sensors, as most studies to date have relied on models rather than experimental data [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e]. Holnicki et. al. [\u003cspan citationid=\"CR131\" class=\"CitationRef\"\u003e131\u003c/span\u003e] conducted a study that consisted of running a model in the CALMET/CALPUFF tool. Based on the model, they determined the most polluted places in Warsaw. Work with the execution of generalized regression models (GRM) was also carried out by Majewski et. al. [132]. The impact of air pollution on visibility in the Warsaw metropolitan area, which was determined based on the aforementioned model, was investigated.\u003c/p\u003e \u003cp\u003eDespite the conclusions of King et. al. [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e] that who suggested that tree canopy cover likely has at most a small impact on neighborhood air quality visible in PM2.5 concentration and represents a lack of pollution sources rather than active pollution removal we have found that on the same type of urban site and location in the city center, but with low tree canopy cover \u0026ndash; 6% TCC (Marszałkowska Street), PM 2,5 absorption was found to be almost 14.5 times lower than on area with tree canopy cover meeting the assumptions of optimal green infrastructure density \u0026ndash; 31% (Żwirki and Wigury Street). We assumed rather than the habitat conditions of the trees at Żwirki i Wigury Street positively affect the possibility of greater absorption of pollutants through greater opportunities for tree growth. According to Urban [\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e] and Trowbridge et. al. [\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e], trees need a suitable rooting space to develop properly and at the same time maximize ecosystem services. In the case of studied trees (average DBH is 18,05 cm) recommended soil volume for rooting is 13 m\u003csup\u003e3\u003c/sup\u003e [\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e] in reality, tree pits provide 3,6 m\u003csup\u003e3\u003c/sup\u003e for rooting. Difficult habitat conditions (isolated tree pits) on Marszalkowska Street resulting in poor tree health, limit the ability of trees to absorb air pollutants. Maximizing ecosystem services in this area requires modifying (improving) habitat conditions. A study by Warsaw scientists [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e] showed that trees with limited rooting areas have more difficult conditions to develop than trees growing in the reserve. The differences associated with the number of mycorrhizal tops and mycorrhizal species were related to organic matter levels and soil chemical parameters, which were less favorable for root development in the rooting space limited by paving. Moreover, 25 years long research was conducted on the average life span of trees in roadside greenery zones [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]), which showed that the average life expectancy of trees growing in small tree pits along Marszałkowska Street was 10\u0026ndash;12 years. This indicates that it is not possible for a tree to reach full maturity and therefore high ecosystem service provision in excessively limited rooting space, common in urban locations.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, while there is growing public awareness of the importance of addressing urban air pollution, further research is needed to inform evidence-based decision-making in this area. The use of the potential of urban areas, expressed in the availability of optimal site conditions for the healthy growth of trees resulted, in our study, in more than 14 times greater effectiveness of trees in cleaning the air from PM 2.5. Our study contributes to this effort by providing empirical data on the effectiveness of trees in mitigating air pollution, but more research is warranted to fully understand the complexities of this issue.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors wrote the main text of the manuscript. KK prepared the drawings.MG has prepared tables.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAkbari, H., Pomerantz, M., \u0026amp; Taha, H. (2001). 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DOI: 10.5277/epe140204 \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5461393/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5461393/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe ongoing urbanization of cities worldwide contributes to escalating levels of air pollution, posing significant environmental and health concerns. The calculation of PM 2.5 air purification potential is commonly conducted for green spaces and trees within urban areas with models such as I Tee eco, as they play crucial roles in ecosystem functions, including the absorption of various air pollutants, but there is a deficiency of studies verifying the distribution of health-threatening concentrations of this pollutant for urban residents. This study presents the findings of research conducted in Warsaw, the capital of Poland, aiming to assess air pollution levels and compare the dust absorption capabilities of trees in two different alleys. The research comprised two main phases: initially, monitoring the concentration of PM2.5 in urban streets characterized by high and low tree density during peak traffic periods and post-peak traffic periods. Subsequently, the study focused on determining the pollution absorption parameters of trees in selected locations, utilizing the i-Tree Eco tool. The analysis revealed frequent exceedances of air quality standards in Warsaw within isolated time frames. Furthermore, it underscored the dependence of urban forest ecosystem services' efficiency on tree canopy cover (TCC), noting a nearly 14.5-fold lower pollutant uptake in areas with insufficient TCC. This issue warrants serious consideration, particularly as a significant number of samples surpassed the WHO standard of 15 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e. Moreover, the study's outcomes emphasized the importance of researching urban trees and air pollution levels using dust sensors. In the case of Warsaw, relying solely on readily available models, commonly utilized in previous studies, may lead to underestimations, failing to accurately represent the actual concentration levels of air pollution.\u003c/p\u003e","manuscriptTitle":"Evaluating Air Pollution in Two Urban Alleys and Comparing Tree Capacity for PM Dust Absorption: A Case Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-14 22:59:00","doi":"10.21203/rs.3.rs-5461393/v1","editorialEvents":[{"type":"communityComments","content":1}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"204c8c8a-414c-42b9-a94f-698b9c1f26b9","owner":[],"postedDate":"April 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":46961611,"name":"Earth and environmental sciences/Ecology"},{"id":46961612,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2025-05-08T04:08:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-14 22:59:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5461393","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5461393","identity":"rs-5461393","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}