Effect of simulated dust storm conditions on the physiological features of wild pistachio

Abstract

Dust storms are a common natural phenomenon in the world, especially in the arid and semi-arid regions of the world. This phenomenon, like other natural hazards, can have harmful effects on the plants. This study investigates the effects of dust under simulated conditions on the biochemical properties of wild pistachio (Pistacia atlantica). Two-year-old seedlings were provided by a state nursery. As a completely randomized design, seedlings were put in simulated dust chamber. The dust was applied at concentrations of 5000, 7000 and 9000 mg/m³ for 10 weeks with intervals of 12 days. At the same time, ten seedlings were selected as control seedlings. At the end of each dusting period, the leaves of the treated and control seedlings were collected from the middle part of the crowns and stored in the freezer for further analysis. The results showed a decrease in chlorophyll pigments and carotenoids with increasing dust concentration, while carbohydrates and catalase and peroxidase enzymes increased. No significant differences were observed in the proline content of the treated and control seedlings. This could be due to the short time of treatment as well as the intensity of the induced dust storm stress. In conclusion, the results can be considered as basic information on the variations of physiological characteristics of forest trees to natural dust storms and their adaptability to climatic changes.

Keywords:

• Dry sediment
• chlorophyll
• antioxidant enzymes
• proline
• carbohydrate

Introduction

Climate change has become one of the greatest environmental challenges facing the world (Velayatzadeh 2020). Phenomena such as widespread droughts, devastating floods, fires, as well as large-scale dust are the consequences of climate change (Eslami and Ghasemi 2019). The dust phenomenon has been considered a serious threat in recent years. With the increase in earth temperature, decrease in precipitation, increase in evaporation and transpiration, high consumption and misuse of water in many activities by humans, the number of arid and semi-arid areas has increased worldwide (Liu et al. 2003). These conditions have created new sources of dust (Boloorani et al. 2014). Dust storms are triggered by turbulent winds that allow loose sand and dust to be removed from dry topsoil in arid areas, creating sand dunes or dust in the air (Miri et al. 2021).

The western and southwestern parts of Iran are severely affected by dust storms transported from neighboring desert regions, mainly from Iraqi deserts as well as local dust sources (Hossein Hamzeh et al. 2021).

Dust is a general name for solid and air-borne particles having diameters >500 µm, but particles of 2.5 -10 µm in atmospheric are of great concern for the health of organisms (Beckett et al. 1998; Borja-Aburto et al. 1998). Particles are composed of many different organic and inorganic materials of varying shapes and sizes, as fine particles, most of which are smaller than 2.5 micrometers, have effective activities that affect living organisms (Prusty et al. 2005). The deposition of dust particles on the aerial parts leads to disruption of the natural biological processes of the plant (Sharifi et al. 1997; Prajapati and Tripathi 2008; Gupta et al. 2016). The chemical composition of the dust, the size of the particles and the amount of its deposition, as well as its longevity on the trees, determine the effect and toxicity of the dust on the plants (Dang et al. 2022). The amount of dust taken up by plant leaves varies depending on plant species and environmental conditions (Kwon et al. 2021; Ra et al. 2021).

Heavy dust deposition on the aerial parts of the plant causes numerous chemical or biochemical changes (such as alteration of chlorophyll pigments, soluble sugars, and proteins) and ultimately leads to a reduction in primary production (Tripathi and Mukesh 2007; Heydarnezhad and Ranjbar-Fordoie 2014). A large amount of dust on leaves can clog stomatal pores, reduce stomatal conductance and light absorption, and impair photosynthetic rates (Gupta et al. 2016; Popek et al. 2018). When plants are exposed to air pollutants, endogenous reactive oxygen species (ROS) are enhanced, causing oxidation of macromolecules and altering the rate of synthesis of antioxidants (Rai 2016; Kumar et al. 2018). It should be noted that in some cases, the plants compensate the low soil-phosphorus availability by uptake this element from desert dust (Starr et al. 2023).

The biological response of plants to air pollution depends on some factors such as the growth stage of the plant and environmental conditions (Inglis and Hill 1974). The effects of dust on plants have been investigated in several studies. Najib et al. (2022) reported a significant decrease in stomatal conductance and relative water content and an increase in hydrogen peroxide, proline, and carotenoids at polluted sites compared to the control site in Quercus cerris. Javanmard et al. (2019) found a decrease in total chlorophyll, relative water content, and leaf pH with increasing dust concentration in Fraxinus rotundifolia, Morus alba, Celtis caucasica, and Melia azedarach. In Pistacia vera, dust decreased relative water content, total chlorophyll, and total soluble sugars (Ranjbar-Fordoei 2018). The study by Gupta et al. (2016) showed that with the increase in dust fall fluxes on leaf surfaces, the levels of photosynthetic pigments and soluble sugars decreased, while the levels of ascorbic acid and proline amino acid increased at both sites for Terminalia arjuna and Morus alba plants.

Dust storm is one of the harmful factors affecting Zagros region in the west of Iran with an area of more than five million hectares (Soheili et al. 2023). Wild pistachio tree (Pistacia atlantica) is one of the most important tree species in this forest area due to its compatibility with the local environment as well as its economic value for gum production (Javanmiri Pour et al. 2013). This tree species occupies the largest forest area after Persian oak and grows easily on different soil types, especially poor soils and steep slopes. Therefore, it can be very important in combating desertification, stabilizing the soil, absorbing water from the subsoil, and beautifying the environment (Davarpanah et al. 2009; Sagheb Talebi et al. 2013).

Since the Zagros forest in Iran is frequently affected by dust storms and there is insufficient knowledge about the physiological response of endemic tree seedlings to this devastating phenomenon, we designed this study to investigate the effects of simulated dust deposition in a researcher-made chamber on the physiological parameters of Pistacia atlantica seedlings.

Materials and methods

A total of 30 seedlings of wild pistachio (Pistacia atlantica) at the age of two years old were provided from Eyvan Nursery, a major state seedling supplier in Ilam, Iran. The seedlings were then transported to the Ilam University Research Nursery (33ᵒ21' 30" N, 45ᵒ 41′ 07" E, elevation: 1427 m). The climate in this area is classified as semi-arid according to the De Martonne Aridity Index, with an average annual rainfall of 518 mm. In the state nursery, the seedlings were in small pots (1 kg) as some roots emerged out from the plastic pots. To adopt with beyond environment and appearing the new leaves and reach the maturity, the seedlings were planted in three-kilogram pots filled with a mixture of farmland soil, animal manure, and fine sand (2:1:1 ratio). Then the pots were placed in the yard for three months until the beginning of July for adaptation to the new situation and maturation of the leaves, watered with tap water.

Preparation of soil dust

Considering that dust storms that impact on Ilam province have source within the country and also from the neighboring countries like Iraq. Therefore, to be more similar to the natural conditions, the dust samples were collected in the desert around the town of Dehloran, the southern part of Ilam near the Iraqi border. The mixed soil was passed through the sieves with mesh sizes of 35, 80, 200 and 400 and finally dust with a diameter of about 0.038 mm was collected (Figure 1(A)). A detailed analysis of the soil is found in Table 1.

Figure 1. (A): Dusting chamber in simulated condition showing the dimensions, blowing fans, and holes for ventilation. 1: small fans, 2: ventilations holes; (B): some wild pistachio seedlings treated by dust inside the chamber.

Table 1. Some chemical characteristics of prepared dust.

Sand%	Silt%	pH	EC (ds/m)	CaCO3%	CaCO4 (%)	Cl^-Mg/L	Texture
49.16	39.18	7.36	2.53	51.75	30.10	0.8	Loam

Simulated dust chamber

A plastic covered chamber (200 × 200 × 200cm) was designed to induce dust on the seedlings. After the leaf maturation, the seedlings were placed in the dusting chamber. In order to keep the dust in the chamber for a longer time, three small barbeque fans were placed at different points of the chamber walls. To avoid the adverse effects of wind stress on the leaves from the fans, the wind stream did not come into direct contact with the seedlings’ leaves. The chamber was covered with a polyethylene sheet and small holes were made at the four upper corners of the chamber for better ventilation (Figure 1(A)). To prevent the negative effects of the sun on the seedlings and in order not to increase the chamber temperature, the chamber was placed under a covered yard. Similarly, the same chamber was also provided for the untreated seedlings (control) (Naji and Taherpour 2019).

Dusting process

Dust concentrations for dusting processes were 5000, 7000, and 9000 mg/m³, respectively. Each chamber contained 10 seedlings (Figure 1). In addition to these seedlings, ten seedlings were selected as control seedlings. Dusting process was carried out during the June. The dust was applied on seedlings in three different days with considering an interval of 12 days between each period. The dusting process started at 09:00 am and lasted until 18:00 pm in each day using a dust simulator (Dustin-mizer Model 1212). The dust can attach and deposit on the wall sheet as well as on the floor. The simulator and fans were not merely able to keep the dust concentration in chamber space at the target concentrations. Therefore, we sometimes added some extra dust (g/m³) to the chamber based on the chamber volume (m³).

The seedlings were irrigated as needed. Calibration of dust chambers for the concentration and method of particle size distribution in the air was conducted by the dust monitor (model 176000 A Microdust Pro Dust Monitoring). At the end of the experiment, leaf samples (from each dusting level) were randomly collected from the middle part of the crown of both treated and control seedlings. Leaves were individually placed in plastic bags and placed in a freezer at −80 °C for further study.

Measuring biochemical Features

Leaf extract pH

The pH of the leaf extract was determined according to the protocol of Cornelissen et al. (2006). Approximately 0.5 g of leaf powder was homogenized with 4 ml of deionized water. To mix the samples completely, the next step was to shake them in a shaker at a speed of 250 rpm for one hour. They were then centrifuged at 4,000 rpm for 5 min (Hermle model, Z300, Labortechnic; made in Germany). The pH of the solution was measured using a digital pH meter (Clean pH-200 L, China).

Electrolyte leakage (EL)

Electrolyte leakage was determined according to Bajji et al. (2001). Some fully mature leaves were collected from the middle part of the crown (for each treatment). The leaves were then rinsed and cut into 1 cm long segments. The segments, which were from the same leaf, were placed in 10 ml of deionized water in a plastic jar. The samples were stored at 30 °C for 3 h before measuring conductivity (EC1). The tubes were then placed in a hot water bath (100 Cᵒ) for 2 min, cooled to room temperature, and conductivity was again measured (EC2). The EL was calculated according to the following formula: $$\text{EL }\left(\%\right)=\left(\text{EC}1/\text{EC}2\right)\times \text{1}00.$$

Relative water content (RWC)

​RWC of the leaf was assessed according to Yang et al. (2007). To measure the fresh weight of leaves, three samples of fully mature leaves were taken from each seedling and weighed (FW) using a digital balance (Acculab Sartorius Group; Germany). Then, the leaves were placed in a Petri dish filled with water overnight (24 h) in the refrigerator. After the free water was removed from the leaves with filter paper, the leaves were weighed again to obtain their saturation weight (TW). Finally, the saturated sample was placed in an oven at 70 °C for 48 h and the dry weight (DW) was measured. The RWC was calculated by: $$\text{RWC}=\left[\left(\text{FW }-\text{ DW}\right)/\left(\text{TW }-\text{ DW}\right)\times \text{ 1}00\right]$$

Photosynthetic pigments concentration

The content of chlorophyll a (Chl a), chlorophyll b (Chl b), and carotenoids (Car) in fully developed leaves was calculated according to the method described by Lichtenthaler & Wellburn (1985). Approximately 0.1 g of leaf powder was homogenized with 10 ml of acetone (80% v/v) and centrifuged at 2500 rpm for 10 min. Absorbance was then measured at 662 nm (chlorophyll a), 645 (chlorophyll b), and 470 nm (carotenoids) using a spectrophotometer (Analytikjena, Specord 50n, Germany). The photosynthetic pigment content was calculated according to the formula: $${\text{Chl a}}^{}=\text{ 11}.{\text{75A}}_{662}–\text{ 2}.{\text{35A}}_{645}$$ $${\text{Chl b}}^{}=\text{ 18}.{\text{61A}}_{645}–\text{ 3}.960{\mathrm{A}}_{662}$$ $${\text{Car}}^{}=\left(1000{\mathrm{A}}_{470}–\text{ 2}.270\text{ Chl a }–\text{ 81}.\text{4 Chl b}\right)/227$$ $$\text{Chl T }=\left(\text{Chla }+\text{ Chlb}\right)$$

Proline content

The free proline content of the leaves was quantified based on Bates et al. (1973). About 0.2 g of powdered leaves were mixed with 10 mL of aqueous sulfosalicylic acid 3% (w/v), and the homogenate was centrifuged at 10,000 rpm for 5 min. Approximately 2 mL of this extract was mixed with 2 mL glacial acetic acid and 2 mL acidic ninhydrin reagent and placed in an oven at 100 °C for 1 h. The reaction was placed in an ice bath and the reaction mixture was extracted with 5 mL of toluene followed by vortexing for 20 s. Finally, the toluene phase was separated and the absorbance was measured using a spectrophotometer at 520 nm. The concentration of proline was then determined from a calibration curve.

Total soluble carbohydrate contents (TSC)

Total sugar content was determined in mature leaves according to DuBois et al. (1956). About 0.2 g of powdered leaf was mixed with 10 mL of 95% ethanol in test tubes and placed in a hot water bath at 80 °C for one hour. Then, 1 mL of the extract was mixed with 1 mL of 5% phenol and 5 mL of 98% sulfuric acid. Finally, the absorbance was measured at 490 nm using a UV spectrophotometer and the total sugar content was calculated using a standard curve developed and constructed with glucose.

Enzyme activities

Approximately 0.1 g of the frozen material was homogenized in potassium phosphate buffer 100 mM (pH 7.0) containing 5% polyvinylpyrrolidine (PVP) and 1 mM EDTA. The homogenates were filtered through four layers of gauze cloth and then centrifuged at 4 °C for 20 min at 15000 rpm. The homogenates were filtered through four layers of gauze cloth and then centrifuged at 4 °C for 30 min at 14000 rpm. The supernatant was collected and used for determination of enzymatic activities. All steps to prepare the enzyme extract were performed at 4 °C (Bradford 1976).

The enzyme catalase was measured according to the method of Aebi (1984). About 50 mL of the enzyme extract was added to 3 mL of phosphate buffer and 4.51 μl of mM H2O2. The decrease in absorbance at 240 nm was monitored for 1 min, and the enzyme activity was determined by calculating the amount of H₂O₂ decomposed.

The enzyme guaiacol peroxidase was measured according to the method of Tang and Newton (2005). About 50 mM phosphate buffer (pH 6.1), 16 mM guaiacol, 2 mM H2O2, and 0.1 mL enzyme extract were mixed in the reaction mixture. The mixture was diluted with distilled water to reach the final volume of 3.0 mL. Enzyme specific activity is expressed as µmol of tetra-guaiacol formed per minute and mg of protein.

Statistical analysis

​ Experiments were performed in a completely randomized design with three replicates. Before analysis of variance, Shapiro-Wilk and Leven’s tests were used to assess normality and homogeneity of variance, respectively. ANOVA and LSD tests were used to compare the different treatments, with significance at p = 0.05. All statistical analyses were performed using SAS software 9.4 (SAS Institute, Cary, NC, USA). Excel software was used to draw graphs.

Results

The results of the analysis of variance on physiological traits of Pistacia atlantica species showed that dust stress had a significant effect on most physiological traits, except for pH, relative leaf water content (RWC), and proline. The dusting periods had significant effects on EL, chlorophyll (Chl a, b and t), total soluble carbohydrate (TSC), and the enzymes catalase and guaiacol peroxidase (Cat and Gpx) (Table 2).

Table 2. The results of the variance analysis of the effect of different dust concentration treatments on the physiological characteristics of wild pistachio leaves.

Source of changes	MS	F	ρ
pH	0.03768	2.07	0.1509 ^ns
RWC	38.1197	2.53	0.0993 ^ns
EL	155.319	4.71	0.0178**
Chl a	6.16749	23.67	0.0000***
Chl b	2.95042	9.80	0.0010***
Chl t	17.6026	18.64	0.0000***
Car	0.81593	23.24	0.0000***
TSC	1.92520	12.71	0.0003***
Prolin	2.355	3.28	0.0525 ^ns
Cat	0.29820	40.08	0.0000***
Gpx	0.51685	484.29	0.0000***

DC: dust concentration; RWC: Relative leaf water content; EL: electrolyte leakage; Chl a, b and t: chlorophyll a, b and total; Car: carotenoids; TSC: total soluble carbohydrate; Cat: Catalase and Gpx: Glutathione peroxidase enzyme; Significance indicated as follows: *p < .05; **p < .01; ***p < .001.

The results of mean comparison showed that the values pH, EL, Chl a, b and t, Car, TSC, and values of Cat and Gpx enzymes were significantly different in the treated seedlings compared to the control seedlings. The pH of leaf extract of seedlings increased when subjected to the increased dust concentrations. The lowest and highest pH values in the control treatment and at 5000 mg/m³ dust concentrations were 4.25 and 4.47, respectively. There was no statistically significant difference in the pH values among the treated seedlings (Table 2). The increase in the dust concentration was associated with an obvious increase in the EL values. The lowest and highest EL values in the control treatment and at 9000 mg/m³ dust concentrations were 39.15% and 50.48%, respectively. The average EL in the treated seedlings was not statistically different (Figure 2(B)).

Figure 2. Effect of different levels of dust treatment on (A) relative water content (RWC); (B) electrolyte leakage (EL); (C) chlorophyll a (Chl a); (D) chlorophyll b (Chl b); (E) total chlorophyll (Chl t); (F) carotenoid (Car); (G) total soluble carbohydrate content (TSC); (H) enzyme catalase (Cat) and, (I) guaiacol peroxidase (Gpx).

The levels of foliar pigments (Chl a, b and t) and Car significantly decreased with increasing dust concentrations (Figure 2(C–E)). The lobwest and highest values were determined in the control treatment and at 9000 mg/m³ level of dust. However, no significant differences were observed between seedlings at 5000 and 7000 mg/m³ of dust level. The lowest amount of them at 9000 mg/m³ of dust levels were 4.85, 1.59, 6.44 and 1.09 (μg/g FW), and the highest in the control treatment were 7.41, 3.37, 10.78 and 2.02 (μg/g FW), respectively.

TSC and activity of Cat and Gpx enzymes increased with increase in dust levels. The lowest value in the control treatment were 2.95 (μg/g FW), 0.32 and 0.19 (μmol⁻¹min⁻¹ g-1 FW⁻¹), respectively, and the highest amount at 9000 mg/m³ of dust levels was 4.47 (μg/g FW), 0.90 and 0.96 (μmol⁻¹min⁻¹ g⁻¹ FW⁻¹), respectively (Figure 2(G–I)).

Discussion

According to the Department of Environment of Ilam (Department of Environment of Ilam 2017), dust concentrations in the air of Ilam on the most polluted days (more than 50 days from April to November) were about 5000 mg/m³ and above. The concentrations of dust in the air of Ilam province in different parts during the dust storms were averagely 15 to 67 times higher than the normal amount. Accordingly, the above-mentioned concentrations were selected for the study. In the present study, dust stress significantly affected most physiological traits of Pistacia atlantica seedlings. Leaf pH is an indicator of the detoxification mechanism in plants, which increases tolerance to stress factors such as air pollution (Ninave et al. 2001). In the current study, increase in dust stress led to a significant Increase in pH of leaves Pistacia atlantica species, which was consistent with the results in Quercus cerris (Najib et al. 2022). Many studies have found that deposition of alkaline dust with pH values above 9 can lead to direct leaf damage (Prajapati 2012; Chaturvedi et al. 2013). In this study, the dust induced had about 52% lime (Table 1). Therefore, the increase in pH can be attributed to the dissolution of dust particles in the cell sap (Lohe et al. 2015).

Electrolyte leakage is a good indicator of stress response in plant cells (Dehghan et al. 2015). Increase in dust concentration resulted in an increasing trend of EL across the examined species, which is in line with studies on Ficus religiosa, Azadirachta indica, and Cassia fistula (Chaudhary and Rathore 2019). Closure of plant leaf stomata by dust particles readily occurs under dust stress, causing an increase in reactive oxygen species (ROS) (Shahbazi et al. 2016). The increase in ROS leads to lipid peroxidation in the membranes of cells and organelles, increased membrane permeability, and consequently increased electrolyte loss leakage (Shen et al. 2010).

The RWC of a leaf is an index that indicates the amount of water in the plant organ, which shows the plant’s ability to retain water under stress conditions (Sharifi Rad et al. 2014). The large amount of water (RWC) in a tree helps maintain its physiological balance under stress conditions (Seyyednjad et al. 2011). At 5000 mg/m³ of dust level, a simultaneous decrease in RWC with an increase in ion leakage was observed, which is consistent with the study on Pistacia vera (Ranjbar-Fordoei 2018). In the control treatment and 9000 mg/m³ of dust level, dust stress had no significant effect on RWC, which is in agreement with Shahbazi et al. (2016). This could be related to the regular irrigation of the seedlings. Therefore, there was always enough water for seedlings and roots. One of the factors that reduce the relative content of leaf water in different species is the unavailability of water in the soil or root system (Kaya et al. 2007). Increasing dust levels can increase cell permeability, resulting in loss of water and dissolved nutrients (Tak and Kakde 2020). Plants that maintain high RWC in polluted environments are considered tolerant to air pollutants (Agbaire and Akporhonor 2014).

Chlorophyll pigments are one of the most important biological factors that decrease under environmental stress. An increase in dust concentration was associated with a significant decrease in chlorophyll pigments of Pistacia atlantica species compared to untreated species. A similar trend of decrease in chlorophyll pigments (Chl a, b, and t) in response to dust concentration was also observed in Quercus brantii (Roushani Nia et al. 2018), Pistacia vera (Ranjbar-Fordoei 2018), Ligustrum ovalifolium (Taheri Analojeh et al. 2016), and on Haloxylon aphyllum (Heydarnezhad and Ranjbar-Fordoie 2014).

The deposition of dust on leaf surfaces can lead to stomata clogging, reducing the uptake of CO₂ by leaves which ultimately leads to a significant reduction in photosynthesis. Closure of stomata leads to increased oxygen demand (Shahbazi et al. 2016), peroxidation of membrane lipids, and consequent degradation of chlorophyll (Gong et al. 2003). In addition to affecting gas exchange, dust deposited on leaves can decrease sunlight penetration, increase leaf temperature, and consequently affect photosynthetic rate. Taheri Analojeh et al. (2016) found that the amount of chlorophyll in new leaves increased under fine dust exposure, which is in contrast to the results of this study. In that study, the dust was applied vertically and from top to bottom of the plant and only the upper leaf surface was affected. Because of the open stomata on the lower surface, the plant was able to photosynthesize and exchange oxygen and Co₂. In this study, fans were installed in the three down parts of the dust simulator chamber, which generated airflow so that dust particles were swirled in all directions of the chamber. Therefore, the stomata on the abaxial and adaxial sides of the blade were affected by the dusting process. The results showed that there is a negative and significant correlation between photosynthetic pigments and antioxidant enzymes, it seems due to the increased activity of chlorophyllase enzyme and also, the proper activity of the protective system (antioxidant enzymes and osmotic activity) is more affected by stress (Sharafi et al. 2017: Hu et al. 2021) (Table 3).

Table 3. Correlation results of physiological characteristics of wild pistachio leaves under different dust concentrations.

Attributes	pH	EL	RWC	Chl a	Chl b	Chl T	Car	TSC	Prolin	Cat
EL	0.186 ^ns
RWC	−0.161 ^ns	−0.198 ^ns
Chl a	−0.394 ^ns	−0.923 ^ns	−0.091 ^ns
Chl b	−0.360 ^ns	−0.934 ^ns	−0.085 ^ns	0.999*
Chl T	−0.380 ^ns	−0.928 ^ns	−0.089 ^ns	1.000**	1.000***
Car	−0.320 ^ns	−0.944 ^ns	−0.080 ^ns	0.996*	0.999**	0.998**
TSC	−0.167 ^ns	0.780 ^ns	0.410 ^ns	−0.816 ^ns	−0.832 ^ns	−0.823 ^ns	−0.848 ^ns
Prolin	−0.578 ^ns	0.694 ^ns	−0.030 ^ns	−0.483 ^ns	−0.517 ^ns	−0.497 ^ns	−0.555 ^ns	0.779 ^ns
Cat	0.230 ^ns	0.944 ^ns	0.120 ^ns	−0.985*	−0.991**	−0.988*	−0.995**	0.893 ^ns	0.621 ^ns
Gpx	0.194 ^ns	0.931 ^ns	0.166 ^ns	−0.978*	−0.984*	−0.981*	−0.990*	0.916 ^ns	0.637 ^ns	0.999**

Significance indicated as follows: *p < .05; **p < .01; ***p < .001.

Carotenoids play a role as accessory light-collecting pigments and also protect photosynthetic systems against reactive oxygen species (Young 1991). Our study showed that an increase in dust concentration caused a descending trend in carotenoid content in P. atlantica leaves, which is in line with previous studies on Quercus brantii (Roushani Nia et al. 2018) and Haloxylon aphyllum (Heydarnezhad and Ranjbar-Fordoie 2014). Dust deposition on the leaf surface may reduce carotenoid content due to shading effects (Soheili et al. 2023). Due to the positive and significant correlation of carotenoid content with the content of photosynthetic pigments, the protective role of carotenoid is considered more (Table 3).

Carbohydrates are main storage and structural component of plants. An increase in dust concentration was associated with an increase in TSC concentration. The results of this study are in agreement with the result of Roushani Nia et al. (2018), in which dust stress increased TSC content in Quercus brantii. The increase in soluble carbohydrates may be caused by the decrease in the need for photosynthetic substances due to reduced growth, synthesis of these compounds from non-photosynthetic pathways, and destruction of insoluble carbohydrates (Ehdaie et al. 2006).

Proline is a stress indicator that plays an important role in plant defense mechanisms, especially oxidative damage, and is more accumulated in stressed plants (Sinha and Saxena 2006). It seems that the dust stress in this study was not so great that it could increase the amount of proline. Our result is consistent with previous studies on Quercus brantii (Roushani Nia et al. 2018), Pinus eldarica, and Cupressus sempervirens (Taheri Analojeh et al. 2016).

Oxidative stress can be alleviated by CAT and PRO enzymes that decompose H₂O₂ into water and oxygen to reduce toxic levels of hydrogen peroxide and prevent damage to plant tissue (Foyer and Shigeoka 2011). Increase in dust concentration was associated with a marked increase in the activities of antioxidant enzymes. According to our findings, an increase in the activity of antioxidant enzymes in response to dust was also observed in Eucalyptus camaldulensis, Conocarpus erectus, and Bombax ceiba (Nawaz et al. 2022).

Conclusions

Dust is one of the most important atmospheric pollution phenomena in arid areas. In Iran, the western and southern regions are not exempt from this occurrence. The results of this study suggest that the remaining dust particles on leaf surfaces can affect the gas exchange (photosynthesis and respiration) of the plant, leading to significant changes in its physiological behavior. With the increasing of dust concentration, a decreasing trend was observed in the amount of chlorophyll pigments, as well as an increasing trend in the pH, carbohydrates, and the enzymes. On the other hand, no clear trend was observed on the characteristics of electrolyte leakage and the relative water content of the leaves. The study of variations in impacted trees contributes to a better understanding of the forest environment, how trees respond, and issues related to the management of different forest stands whether to continue planting this tree seedling in natural area with problems related to the management of diverse forests in natural areas.

Consent to participate

All participants in this study consented voluntarily to participate in this research study.

Consent to publish

The authors declare that they agree with the publication of this paper in this journal.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data available on request.