Integrated Characterization of Deposited Dust and Atmospheric Particulate as a Micro/Nano Matter Across Urban, Rural, and Industrial Environments in Hillah City, Iraq

INTRODUCTION
Air pollution represents one of the most critical environmental challenges of the twenty-first century, causing approximately seven million premature deaths annually worldwide [1]. Dust is a natural phenomenon significantly affecting climate systems, air quality, and public health [2,3]. In Iraq, prevailing climatic conditions high temperatures, low precipitation, and increased evaporation have made dust a major environmental concern, with drought and soil erosion serving as primary natural sources [4]. Particulate matter (PM), particularly PM₁₀ and PM₂.₅, represents one of the most hazardous air pollutants due to its direct association with respiratory and cardiovascular diseases [5]. Particle size distribution (PSD) determines particle behavior regarding suspension, deposition, and respiratory penetration [6]. Beyond physical characteristics, dust contains heavy metals resistant to biodegradation and bio accessible in the human body, potentially causing neurological disorders, kidney and liver diseases, and cancer [7,8]. These metals originate from both natural sources (dust resuspension) and anthropogenic activities (vehicle emissions, industrial processes) [9,10]. Due to limited studies in Hillah city integrating multiple analytical techniques, this comprehensive investigation aims to: (1) measure PM₁₀ and PM₂.₅ concentrations and dust deposition rates; (2) examine particle morphology using SEM; (3) identify mineral phases using XRD; (4) determine heavy metal concentrations using XRF; and (5) correlate findings with meteorological factors and anthropogenic activities.

MATERIALS AND METHODS
Study Area and Sampling Sites 
Hillah City, the administrative center of Babylon Governorate, is located approximately 100 km south of Baghdad in central Iraq. The city has experienced rapid urban expansion, population growth, and increasing industrial activities. The climate is hot desert, characterized by extremely high summer temperatures, mild winters, and low annual precipitation [11].

Description of Sampling Sites 
An Urban Area (AL-Jam’iya District): This is a specific archetype of an urban dense residential and commercial area having high traffic flow, commercial centers, and daily anthropogenic activities. Coordinates: 32.470653 N, 44.414645 E.
Site 2 — Rural Area (Abu–Khastawi): This site provided a rural and agricultural environment with vegetation cover, farming activities, and very few industries. It’s located away from center. Coordinates: 32.512578 N, 44.398056 E.
Industrial Areas (Industrial zone): This place shows a typical industrial environment with vehicle engine maintenance workshops and other minor industrial activity, which forms a significant source of pollutants emission. Coordinates: 32.470653 N, 44.427247 E (Fig. 1).

Dust Sampling and Deposition Rate
Monthly samples of deposited dust were collected from October 2024 to June 2025 by means of pipe-less cylinders deposited at heights to minimize their direct contamination. The samples were weighed in the laboratory on a digital scale sensitive to micrograms after having also been air-dried. DDR (g m−2 d−1) is a dust deposition rate calculated by equation.

Where, W1 = Weight of the cylinder before collection. W2 = Weight of the cylinder after collection. A = area of the cylinder base (m-2).

Measurement of Particulate Matter (PM10 and PM2.5)
Concentrations of PM10 and PM2.5 were measured at the selected sites using a portable air quality monitoring device (Tem Top). Measurements were conducted at fixed time intervals during the study (from October 2024 to June 2025) to ensure consistency and comparability among the studied areas.

Particle Size Distribution (PSD)
Particle size distribution of the deposited dust samples was analyzed to determine the relative contribution of fine and coarse particles and to evaluate the dominant particle size fractions.
Scanning Electron Microscopy (SEM)
The morphological characteristics of the dust particles, including shape and surface texture, were examined using a scanning electron microscope (SEM) at the laboratories of the University of Babylon. (Device model: ESCAN VEGA 3, Czech Republic). 

X-ray Diffraction (XRD)
The mineralogical composition of the deposited dust samples was identified using X-ray diffraction (XRD) analysis to determine the crystalline phases present. (Device model: XRD-6000, Shimadzu, Japan).

X-ray fluorescence
The X-ray fluorescence (XRF) technique was used to determine the concentrations of heavy metals in the deposited dust samples. After drying and grinding, the samples were placed on a disc-shaped holder with a diameter of about (3 cm). The weight of the analyzed samples ranged from 3 to 5 g. The analysis was carried out at the laboratories of the Scientific Research Authority, Ministry of Higher Education and Scientific Research, Baghdad. (Device model: XEPOS, SPECTRO Analytical Instruments, Germany).

RESULTS AND DISCUSSION
Dust deposition
The result of dust deposition showed noticeable spatial variation in all sites. Especially in monthly value, since the industrial site recorded the highest dust deposition rate in June (86.70 g/m2) and the lowest value (3.86 g/m2) in January in the same area. (Fig. 2) 
Descriptive statistics indicated that the industrial site exhibited the highest average dust deposition rate (31.77 ± 31.03 g/m2), followed by the rural site (20.06 ± 13.07 g/m2), whereas the urban area recorded the lowest value (18.75 ± 12.21 g/m2). The descriptive statistics of the deposition rates for the studied areas are summarized in Table 1.
Statistical analysis revealed high variability in dust deposition within the industrial area, while relatively stable values were observed in the rural and urban areas. Weak negative correlation was found between dust deposition and relative humidity, whereas weak positive correlation was observed with air temperature and wind speed, with no statistically significant differences. This indicated that meteorological factors played a secondary role in controlling dust deposition during the study period. The elevated dust deposition in the industrial area can be attributed to local anthropogenic activities, such as vehicle movement on unpaved roads and emissions from nearby workshops, which are considered major sources of dust in industrial environments [12]. In contrast. The lower dust levels in the rural area may be associated with vegetation cover and soil moisture, which reduce dust emissions [13]. The urban area recorded the lowest dust deposition rate, likely due to paved roads, urban planning, and limited industrial activities, as well as the presence of green spaces, which contributed to reducing dust emissions [14]. Overall, the results suggest that local anthropogenic sources play a more dominant role in dust accumulation than climatic factors, particularly in the industrial area, consistent with previous studies [12,15].

Particulate matter (PM10 and PM2.5)
The descriptive statistics of PM10 and PM2.5 revealed clear spatial and seasonal variability across the study sites. Higher concentrations were generally recorded during the winter months, while lower values predominated in summer. For PM2.5, the urban area recorded the highest mean concentration. And the recorded concentration ranged from (98.20 to 11.040 µg/m3) in the urban area, at December 2024 and march 2025 respectively, and (83.30 to 27.40 µg/m3) at January 2025 and May 2025 in the rural area, respectively, while (74.10 to14.90 µg/m3) at May 2025 and march 2025 in the industrial area. Respectively, with means (57.64 ±26.92 µg/m3), in urban area, followed by the rural area (53.82 ±20.08 µg/m3), whereas the industrial site showed the lowest mean value (48.06 ±17.47 µg/m3).
The PM10 recorded monthly value ranges were (158.10 to 17.90 µg/m3).  for the urban area at December 2025 and March 2025, respectively, and (125.10 to 41.80 µg/m3) at January 2025 and May 2025, respectively, in the rural area, while in industrial areas (94.10 to 22.80 µg/m3) at November2024 and March 2025, respectively, Similarly, PM10 showed the highest mean concentration in the urban area (92.21 ±42.69 µg/m3), followed by the rural site (82.24 ±30.36 µg/m3). While the industrial area recorded the lowest mean value (72.24 ±24.20 µg/m3). (See Fig. 3).
The result of the particle size distribution of dust particles showed clear differences among the urban agricultural, and industrial areas. The urban area recorded the highest mean particle size, reaching (32.38 ±8.26µm), whereas the industrial area exhibited the lowest mean particle size of (20.01 ±6.06 µm), The agricultural area showed an intermediate value between the two areas with a mean particle size of (27.59 ±13.85 µm). The dominant particle size of deposition dust ranged from 10 µm to 70 µm across the three sites. The objective of analyzing the particle size distribution of dust particles is to clarify the spatial differences in particle sizes among urban, agricultural, and industrial sites and to relate them to the nature of the sources and dominant activities at each site. The particle size distribution in the urban area indicates the dominance of relatively large particles as the distribution curve extends toward higher values, reaching up to 70 µm this reflects the prevalence of coarse particles. This suggests soil particles resulting from dust suspension and daily human activities with traffic movement being the primary source in most cases [16]. In contrast, the industrial area was characterized by the presence of smaller-sized particles compared to the urban and agricultural areas. This can be attributed to the influence of industrial activities, which generated finer and relatively homogeneous particles as a result of combustion processes and mechanical abrasion enabling these particles to remain suspended in the air for longer periods. Meanwhile, the particle size distribution in the agriculture area showed intermediate values between the two areas. This pattern is attributed to soil fragmentation, wind erosion, and agricultural activities, which generated particles of natural origin. The study of Huang illustrate that the wind contributes to an increase in dust particulate size by enhancing emission rates and reducing dust deposition [17].  The analysis of variance concerning standard deviation values confirmed that there were multiple sources of particles at all three sites. The rural area possessed the highest standard deviation, indicating that there were a variety of sources and that there was heterogeneity in soils [18], whereas the industrial site had the lowest standard deviation, indicating that there was homogeneity among the sources due to the industrial process. A characterization of particle sizes revealed that there was a distinct spatial gradient regarding size of particles: the largest sizes were found in the urban area, somewhat smaller in the agricultural area, and then the smallest sizes in the industrial area. These results are consistent with the findings of [15], who found that most of the particles at urban and agricultural locations comprised mostly large particles, whereas the majority of particles found at industrial sites consisted of smaller particles (Fig. 4).

Scanning Electron Microscope (SEM)
The result of the (SEM) showed the presence of various shapes of deposited dust particulate, including spherical (rounded), flat, elongated, and irregular particles with sharp edges and metallic flakes. This indicates that the deposition dust particles consist of a heterogeneous mixture of different morphologies as shown in Figs. 5-7.
Dust particle morphology analysis using SEM by site has shown different morphological characteristics. The morphology of dust particles was irregular and heterogeneous due to different sources, meteorological conditions, the length of time the particles spent in the atmosphere, and the elemental make-up of the particles [18,19]. The irregular platy-shaped particles that had sharp edges and rough surfaces were primarily attributed to weathering of the primary crust and the effects of weathering from wind erosion [20] and the effects of human activities, including construction sites and road dust from vehicles [21]. Very small round, smooth spherical-shaped particulate matter was found to be representative of soot from the emission of vehicles and combustion [22,23]. Highly porous particles containing carbon from agricultural or waste burning have high adsorption capacity and ability to aggregate over large areas [24,25] were also seen SEM analysis from the industrial sites identified metal particles and broken particles produced from mechanical processes that are produced through diligence in the Workshop. The results of this research identified two major categories of particles, anthropogenic round shiny particles created from combustion and natural irregular rough surface particles that have been formed from geological and biological sources [26] and corroborates with the findings of [20], that particle morphology represents the characteristics and origin of the source of the particle. 

Mineralogical identification of deposited dust particles
X-ray diffraction (XRD) analysis was conducted on the total deposited dust samples from the three study sites to identify the mineralogical composition. Calcite (CaCO3) and Quartz (SiO2) were identified in all sites. In contrast, less common phases in the atmospheric dust were preliminarily identified based on peak matching according to standard reference, (ICDD reference patterns) (Table 2).
X-ray diffraction (XRD) tests indicated all locations had calcite and quartz indicating that there are natural crustal components present in the atmospheric dust as shown in Fig. 8.

Calcite is the major mineral within carbonate-rich soils, so the presence of this mineral in atmospheric dust is not abnormal; however, its presence may also be attributed to cement-related pollution since it is widely used in many industries, and its environmental effects through chemical weathering [27,28]. Quartz is resistant to physical and chemical weathering and is therefore used as a reliable index to identify crustal dust from natural sources including soil re-suspension, dust storms, and vehicular activity, but peak intensity can vary by site [29]. The feldspar phase, Albite Calcine Low (Al1.16Ca0.16Na0.84O8Si2.84), was discovered as a result of soil re-suspension and rock fragmentation. Lead Calcium Zirconium Oxide (Ca0.3O3Pb0.65Zr), which served as an indicator of anthropogenic pollution caused by vehicle emissions and brake operations [30,31], was detected in urban samples Molybdenum nitride (Mo2N) was present in industrial dust samples, indicating a chemical or thermal interaction resulted from molybdenum sources with nitrogen-containing gases from industrial workshop processes such as welding, polishing, or thermal spraying [32]. An intermetallic alloy phase (GaMnNi2), which was formed under high vacuum at elevated temperatures, also appeared in industrial samples, confirming that anthropogenic industrial emissions are likely causing the presence of this alloy or suspending metallic particles. In rural areas, rubidium iodate (RbIO3) was found which is uncommon and forms through the adsorption of rubidium that occurs naturally in clay-rich soils and of mobile iodate anions by wind re-suspension of soil particles into the atmosphere [33-35]. In addition to rubidium iodate, strontium chromate (Sr2CrO4), which is known to be a carcinogen, was identified as a result of aerosolized dispersal of paint particles through the air during the process of painting as a means of providing protection from corrosion by using corrosion resistant paint [36,37]. The results of this study are consistent with the work of [38], who reported that calcite, quartz, albite, and dolomite were sourced from natural geological processes associated with rock weathering and that illite, hematite, and montmorillonite were sourced from anthropogenic activities such as construction and industrial emissions. 

Heavy Metal Interpretation (XRF Analysis) 
Spatial Variation 
Results of the analysis of spatial statistics showed a clearly defined variation in concentrations of heavy metals amongst the various measurement sites included in this study. The urban area had the greatest mean concentration at 110.91 + 195.33 with the industrial area second at 93.28 + 150.10. In contrast, the rural location had the lowest average concentration at 88.43 + 176.98. The high standard deviation values indicate significant heterogeneity of heavy metal concentration across each site, most likely due to the non-uniform distributions of heavy metals and differing emission sources from anthropogenic activities rather than consistent and continuous background sources.
The results depicted in Fig. 9 show significant differences in heavy metal concentrations between study locations and are consistent with descriptive statistics. This demonstrates non-uniform (anisotropic) heavy metal concentration distribution in deposited dust, especially in urban settings, where there’s considerable variability of heavy metal concentrations spatially. 
The boxplot demonstrates how there is a lot of variability amongst samples due to the wide range of concentrations in each region, as well as due to outlying data points. The boxplot indicates that the boxplot shows some level of uniformity across the sample regions while also exemplifying variabilities through the heavy metal distributions which are indicative of anthropogenic sources, as they originate from a large number of direct and highly varied location sources. Examples of differences that occur between sample locations are also visible on the boxplot through the differences in sample population variability.

Seasonal Variations
Lastly, with respect to seasonal variation in heavy metal concentrations found in deposited dust samples collected during the summer (96.83 ± 180.11) and winter (98.25 ± 169.57) seasons, only minor differences have been observed. In general, the mean concentrations between seasons were relatively equal, however, there is a large amount of variability as indicated by the high standard deviation values. Given that there is so much variability in the heavy metal concentration samples collected between seasons, the probability of significant seasonal variations resulting is very low, as is demonstrated by the data presented in Fig. 10.
Statistical analysis showed differential seasonal behavior of heavy metals in each of the study areas. Higher mean concentrations were recorded for winter (101.16) than for summer (85.40) in the case of industrial areas, which possibly reflects higher industrial activity or less atmospheric dispersion in winter. In urban regions, mean concentrations showed comparatively little difference between summer (113.01) and winter (108.82), indicating stability of the source of emission. On the other hand, the rural region found that summer concentrations were slightly increased (92.09) compared to winter (84.77), which may be related to agricultural activities. This suggests that season effects differ across regions but are minor in comparison to the combined variation in a single season, thus confirming the idea that direct local sources control heavy metal concentration in deposited dust. 
There was also no statistically significant difference in mean heavy metal concentration between the three regions according to the Two-Way ANOVA (Region x Season) (Sig =0.757, F=0.279) No significant differences were also seen between summer and winter (Sig = 0.956, F = 0.003). There was also no significant interaction between region × season (Sig = 0.925, F = 0.078). Region, season, and the interaction of region and season had no statistically significant effect of heavy metal concentrations (Sig = 0.982) in the corrected model. The R2 (coefficient of determinant) was limited (0.004). These results suggest that spatial and seasonal characteristics account for only a quite minimal part of the variation in heavy metal concentrations, suggesting that the levels of heavy metals in deposited dust are more likely driven by nearby local sources or other unexplored variables than by location and season.  
The heavy metals concentrated and subjected to mean concentrations show variation in deposited dust samples. The mean concentrations of the elements Mg, Mn, Sr, Ba, and Cr were relatively high, while the mean concentrations of Na, Hg, Cd, Sb, and Sn were extremely low.
The heavy metals distribution in reveals high and low mean concentrations of elements, which confirm the differences in the abundance of the elements. And as further evidence of the statistical analysis results, within dust samples. Certain heavy metals had high standard deviation values (indicating large variation in concentration) and others demonstrated low standard deviation values (indicating relatively stable concentrations) within the time interval between measurements.
As shown in the box plot, heavy metals are exhibited to high dispersion, where most with wide range and some with outliers, confirming high dispersion. Variability with dust samples. Standard error analysis was conducted as a follow-up to assess the accuracy of mean concentrations. Centering and spread are described with mean, and error bars represent standard deviation, respectively (Fig. 11) this file is in the first Proceedings Data.

Source Classification of Heavy Metals
Lithogenic (Natural) Elements 
The high concentrations of some elements deposited dust include: Mg, Mn, Sr, Ba, Fe, Ca and Si and SiO2. This elevation should be normal based on the crustal origin of these elements and their abundance in adsorption-based raser within prophylytic surface soils that were enriched through weathering and erosion of rocks and soils rather than being industrial or anthropogenic polluted [39] [40]. Low average concentrations were recorded for Mn with the exception of the mining regions, and also for two elements, Cu and Ca, which were expected to show a relatively higher mean concentration, which is due to their general abundance in the study areas, except for the mining regions. High standard deviation values relative to each other indicate variation in concentrations, potentially due to climatic factors like wind and dust resuspension. As long as they do not exceed the environmental safety limits, the crustal heavy metals that originate from dust are treated as natural background instead of environmental pollution.

Anthropogenic Elements 
Contrarily, anthropogenic variables, exhibiting different concentrations   include Pb, Zn, Cu, Ni, Mo, Cd, Sb, Hg, As, Sn, and Co, and their concentrations are significantly controlled by human activities (industrial, traffic, combustion, and construction). The mean concentrations of many elements recorded relatively high variability revealed in the high standard deviation (a huge fluctuations of samples). Such irregularity is associated with temporally and spatially variable emissions from human activities and is reflected as variability in total columns of Co [41]. Box plot depicted wide ranges and outliers present, which is a hallmark of anthropogenic nature, where emissions tend to be local and sporadic rather than uniform sources [42]. These factors have no national or seasonal pattern and instead rely on local customs. The increased concentrations of these species in settled dust signifies a direct effect of human activities on air quality and the regional environment, which may be of anthropogenic and not geological origin and could contribute to the environmental burden by continued deposition if they are not addressed.
These results are in agreement with [43] who established that Fe, Mn, Co, and Ni in deposited dust are mainly of natural origin, while Pb, Zn, Cd and Cu are closely related to anthropogenic input. Likewise, [44] stated that changes in heavy metal concentrations in Baghdad could be due to environmental fluctuations and several origins such as dust storms and patchy plant distribution.

CONCLUSION
This research shows the primary cause of particulate pollution in Hillah City is local source emissions while there is greater spatial than seasonal or meteorological variability. The principal means of depositing these particles are industrial areas due to mechanical processes, unpaved surfaces, and localized emissions. The majority of particulate matter (PM) concentration is found in urban areas with PM₂.₅ and PM₁₀ being primarily caused by vehicle emissions/transportation and urban activity. The close relationship between PM₂.₅ and PM₁₀ indicates that the two particle sizes come from similar areas and both types have a common atmospheric mechanism for distribution. The particle size distribution has clear environmental separation where the larger particles are derived from resuspension of dust within the urban areas and the smaller ones are from industrial processes. While there are some elemental or chemical composition similarities in the aggregate groups, one can distinguish between sorts of morphologies based on particle characteristics. There are heterogeneities in dust-morphology due to differing mechanical activity of the source in origin, as well as, due to different media/locations of production: natural surfaces (desert) or man-made (urban). Mineralogical study indicates predominantly quartz and calcite, implying natural soil resuspension is a major source, additional minerals representing anthropogenic impact. Heavy metal distribution exhibits significant spatial heterogeneity and anisotropy in urban settings, indicating irregular and localized sources of emissions. A lack of significant seasonal variability and lack of correlation with climatic variables indicate an anthropogenic influence on heavy metals rather than environmental control factors. Lithogenic elements have a natural geological source, whereas trace metals like Pb, Zn, and Cu are closely associated with human activity from sources such as vehicular traffic and industrial emissions. This study shows that the quality of air in arid environments is a product of the relationship between natural dust and anthropogenic emissions, and anthropogenic sources increase the amount of air contamination.

ACKNOWLEDGMENTS
We thank Al-Qasim Green University for the support.

CONFLICT OF INTEREST
The authors declare that there is no conflict of interests regarding the publication of this manuscript.