Forests

Deforestation and degradation of mangrove forests can be categorized as key environmental problems in Indonesia. These problems are majorly driven by overexploitation and the conversion of mangroves into brackish water aquaculture areas. One of the most common aquaculture systems traditionally developed in the coastal areas is the mangrove-fish pond system that combines fish production with existing trees. This study aims to analyze the environmental and economic aspects of mangrove-fish pond aquaculture in different levels of mangrove cover in the coastal area of Subang District, West Java, Indonesia. The spatial analysis method was used to analyze mangrove distribution and identify the current coverage in the aquaculture area. The economic aspect was analyzed, based on the costs and revenue from fish production, while the environmental aspect was represented by carbon storage, which is among the crucial mangrove ecosystem services. This study estimated carbon storage in the four-carbon pools: above- and below-ground biomass, deadwood, and litterfall. Based on the combination of visual interpretation of Sentinel 2A satellite images and field observations, approximately 667 ha of mangrove-fish pond was identified. This study found that there were no significant differences in fish production and net income from mangrove-fish pond aquaculture at various levels of mangrove cover. Meanwhile, the ponds with high mangrove cover stored higher carbon than those with medium and low mangrove covers. This indicates that maintaining carbon storage does not reduce fish production from mangrove-fish pond aquaculture. Full article

The hydroperiod determines the biogeochemical conditions and processes developing in the mangrove soil. Floods control the input of nutrients and the presence of regulators such as salinity and sulfides that, in high concentrations, degrade mangrove vegetation. This work aimed to determine biogeochemical and hydroperiod characteristics in natural and degraded mangrove conditions. Three sampling sites were placed along a spatial gradient, including fringe and basin mangroves with different conditions. Tree characteristics and biogeochemical variables (temperature, salinity, pH, redox potential, sulfides) were measured. The structural analysis indicated two conditions: undisturbed (Rhizophora mangle fringe and Avicennia germinans basin under natural conditions) and disturbed (degraded basin, with standing A. germinans tree trunks). The soil porewater salinity, concentration of sulfides, and temperature were significantly higher, and redox potential lower in the disturbed site. The fringe mangrove was permanently waterlogged with higher tides than the basin mangrove. There were more extended flooding periods on the degraded mangrove due to the loss of hydrological connection with the adjacent water body. Waterlogging in basin mangroves increased soil porewater salinity to 87.8 and sulfides to 153 mg L⁻¹, causing stress and death in A. germinans mangroves. Our results show that the loss of hydraulic connectivity causes the chronic accumulation of salinity and sulfides, with consequences on tree metabolism, ultimately causing its death. It probably also involves the succession in microbial communities. Full article

Tea plant necrotic ring blotch virus (TPNRBV), which carries four positive−sense single−stranded RNA segments, causes discoloration spots and multiple necrotic ring blotches in tea trees. To understand the distribution and transmission of TPNRBV in tea trees and prevent its spread, a SYBR Green real−time quantitative polymerase chain reaction (RT−qPCR) method for detecting the four virus segments was developed. The limit of detection of RT−qPCR was 3.81, 4.73, 3.58, and 4.64 copies/μL for the four strands of TPNRBV, which was 100−fold more sensitive than conventional PCR for RNA1 detection, 10−fold for RNA2 and RNA3, and 1000−fold for RNA4 detection. Visual observation and RT−qPCR of different tea plant tissues showed that symptomatic mature leaves contained the highest TPNRBV load; the concentrations of the four RNAs in other tissues decreased or were undetectable with increasing distances from symptomatic leaves. TPNRBV did not spread efficiently through seeds, cuttings, or mechanical inoculation, but was transmitted to some tea cultivars, particularly light albinistic varieties such as ‘Zhonghuang 1′ and ‘Huangjinya’, under field conditions. Our TPNRBV detection method is useful for determining the distribution and transmission characteristics of TPNRBV and selecting tissues with the highest viral load for early diagnosis, monitoring, and management of the disease. Full article

Structural complexity of trees is related to various ecological processes and ecosystem services. To support management for complexity, there is a need to assess the level of structural complexity objectively. The fractal-based box dimension (D_b) provides a holistic measure of the structural complexity of individual trees. This study aimed to compare the structural complexity of Scots pine (Pinus sylvestris L.) trees assessed with D_b that was generated with point cloud data from terrestrial laser scanning (TLS) and aerial imagery acquired with an unmanned aerial vehicle (UAV). UAV imagery was converted into point clouds with structure from motion (SfM) and dense matching techniques. TLS and UAV measured D_b-values were found to differ from each other significantly (TLS: 1.51 ± 0.11, UAV: 1.59 ± 0.15). UAV measured D_b-values were 5% higher, and the range was wider (TLS: 0.81–1.81, UAV: 0.23–1.88). The divergence between TLS and UAV measurements was found to be explained by the differences in the number and distribution of the points and the differences in the estimated tree heights and number of boxes in the D_b-method. The average point density was 15 times higher with TLS than with UAV (TLS: 494,000, UAV 32,000 points/tree), and TLS received more points below the midpoint of tree heights (65% below, 35% above), while UAV did the opposite (22% below, 78% above). Compared to the field measurements, UAV underestimated tree heights more than TLS (TLS: 34 cm, UAV: 54 cm), resulting in more boxes of D_b-method being needed (4–64%, depending on the box size). Forest structure (two thinning intensities, three thinning types, and a control group) significantly affected the variation of both TLS and UAV measured D_b-values. Still, the divergence between the two approaches remained in all treatments. However, TLS and UAV measured D_b-values were consistent, and the correlation between them was 75%. Full article

The mechanism of Picea wilsonii adapting to abiotic stress remains largely unknown. NAC (NAM, ATAF and CUC) transcription factors play significant roles in plant response to adverse environments. In this study, based on our previous RNA-seq, we analyzed the expression patterns of PwNAC38, and revealed its functions in the process of PwNAC38-mediated stress responses. An open-reading frame, encoding PwNAC38 protein with 330 amino acids, was isolated from the cDNA library, a process which can be induced by drought, salt and ABA treatment. Subcellular localization and yeast experiments showed that PwNAC38 was a nuclear-localized transcription factor, and could form homodimers. The full length of PwNAC38 showed transcriptional activity, while the truncated segments, C-PwNAC38 (156–330 aa) and N-PwNAC38 (1–156 aa), did not. The constitutive expression of PwNAC38 (OE lines) in Arabidopsis did not exert influence on the growth of transgenic plants under normal conditions, whereas transgenic seedlings showed higher survival rates, and the seeds had stronger vigor and a higher germination rate under drought and salt stress. The seed germination and root growth of PwNAC38 OE lines were significantly inhibited in the presence of ABA, suggesting the hypersensitivity of PwNAC38 to ABA treatment. Physiological assays showed that the activity of antioxidant enzymes, such as SOD and POD, increased, and that the accumulation of superoxide anion decreased, in OE lines under stress conditions. Moreover, overexpression of PwNAC38 significantly improved drought and salt tolerance in apple calli. A qRT-PCR assay showed that overexpression of PwNAC38 in Arabidopsis promoted the expression of drought or ABA-responsive genes ATHB-7, ANAC019, ERD1, DREB2A, RD29A, ABI5 and NCED3. Taken together, our results revealed that PwNAC38 is positively involved in plants’ response to drought and salt stress by enhancing ROS scavenging efficiency, and is partially dependent on the ABA signaling pathway. Full article

In order to meet the growing demand for raw material of solid biofuels, it is imperative to find alternative materials of low cost, underutilized so far. In this study, wood and bark material of two common cypress species (Mediterranean and Arizona cypress) were chemically characterized through gravimetric and spectroscopic (FTIR) analyses, to assess their potential to be used as raw materials in the production of fuel pellets. Low bark concentrations (0%, 2%, and 7%) were applied, and the mixtures were densified in a flat-die pellet press. The produced pellets were examined in terms of thermal, physical, hygroscopic, and mechanical properties, using standard ISO17225 thresholds as benchmark. The results revealed that the effect of bark presence in low content οn pellet properties and quality was positive. The ash content of both wood species is adequately low for biofuels production, whereas their bark cannot be purely used as feedstock due to the high ash content. By using low bark contents (2% or 7%), the ash content of pellets was kept adequately low to be categorized in the highest quality classes (A1 and A2: for residential applications), while the produced pellets demonstrated improved dimensional stability, mechanical durability, and slightly improved calorific value. The moisture content, dimensions, and bulk density of all the produced pellet categories fulfilled the standard requirements. Even though the pellets of 2% bark share presented much lower ash contents, only the pellets of 7% bark share were proven to have considerably improved mechanical durability, suitable for residential use. The chemical composition of raw materials (especially the extractives and holocellulose) plays a major role in the mechanical durability of pellets. Full article

The identification of wildfires is a very complex task due to their different shapes, textures, and colours. Traditional image processing methods need to manually design feature extraction algorithms based on prior knowledge, and because fires at different stages have different characteristics, manually designed feature extraction algorithms often have insufficient generalization capabilities. A convolutional neural network (CNN) can automatically extract the deeper features of an image, avoiding the complexity and blindness of the feature extraction phase. Therefore, a wildfire identification method based on an improved two-channel CNN is proposed in this paper. Firstly, in order to solve the problem of the insufficient dataset, the dataset is processed by using PCA_Jittering, transfer learning is used to train the model and then the accuracy of the model is improved by using segmented training. Secondly, in order to achieve the effective coverage of the model for fire scenes of different sizes, a two-channel CNN based on feature fusion is designed, in which the fully connected layers are replaced by a support vector machine (SVM). Finally, in order to reduce the delay time of the model, Lasso_SVM is designed to replace the SVM in the original model. The results show that the method has the advantages of high accuracy and low latency. The accuracy of wildfire identification is 98.47% and the average delay time of fire identification is 0.051 s/frame. The wildfire identification method designed in this paper improves the accuracy of identifying wildfires and reduces the delay time in identifying them. Full article

The occurrence of forest fires causes serious damage to ecological diversity and the safety of people’s property and life. However, due to the complex forest environment, the changeable shape of forest fires, and the uncertainty of flame color and texture, forest fire detection becomes very difficult. Traditional image processing methods rely heavily on artificial features and are not generally applicable to different forest fire scenes. In order to solve the problem of inaccurate forest fire recognition caused by the manual extraction of features, some scholars use deep learning technology to adaptively learn and extract forest fire features, but they often use a single target detection model, and their lack of learning and perception makes it difficult for them to accurately identify forest fires in a complex forest fire environment. Therefore, in order to overcome the shortcomings of the manual extraction of features and achieve a higher accuracy of forest fire recognition, this paper proposes an algorithm based on weighted fusion to identify forest fire sources in different scenarios, fuses two independent weakly supervised models Yolov5 and EfficientDet, completes the training and prediction of data sets in parallel, and uses the weighted boxes fusion algorithm (WBF) to process the prediction results to obtain the fusion frame. Finally, the model is evaluated by Microsoft COCO standard. Experimental results show that compared with Yolov5 and EfficientDet, the proposed Y4SED improves the detection performance by 2.5% to 4.5%. The fused algorithm proposed in this paper has better feature extraction ability, can extract more forest fire feature information, and better balances the recognition accuracy and complexity of the model, which provides a reference for forest fire target detection in the real environment. Full article

Abiotic stress is one of the environmental conditions that effects plant survival and growth. As a vital model plant and papermaking raw material, it is very important to identify the differentially expressed genes of Populus trichocarpa Torr. & A.Gray ex Hook under abiotic stress in order to cultivate stress-tolerant plants. We analyzed the whole transcription spectrum and potential differentially expressed genes of 54 groups of roots and stem-xylem sequencing sample data under cold, drought, heat and salt stress for different durations. Gene Ontology (GO) enrichment analysis showed that molecular function played a stronger role in stems’ response to abiotic stress, and genes in roots could barely respond to both cold stress and heat stress. Degree and betweenness centrality were used to identify transcription factors. It was considered that intermediate centrality is more suitable to determine whether the transcription factor is a hub gene. DNA binding was the biggest enrichment, while transcription factors responded to the abiotic stress. The multipronged approach identified in the roots and stems provides a genetic basis for resistance and more targeted genetic improvement of Populus trichocarpa. The comparison of two centralities can more effectively analyze the importance of complex gene network nodes in plants under corresponding abiotic stresses. Full article

δ¹³C and δ¹⁵N were analyzed in the leaves of Pinus sylvestris L. and Betula spp. under the conditions of severe heavy metal (Zn, Cu, Cd, and Pb) contamination. Twenty-seven plots located near the Karabash copper smelter (Russia) were studied. No reliable correlation of ¹³C in tree leaves with the level of pollution was observed. δ¹⁵N, both in Pinus sylvestris and Betula spp., increased similarly in polluted areas. δ¹⁵N was increased by 2.3‰ in the needles of Pinus sylvestris and by 1.6‰ in the leaves of Betula spp. in polluted plots compared to the background ones. The probable reasons for the increase in δ¹⁵N were estimated using multiple regression. The regression model, which includes two predictors: δ¹⁵N in the humus horizon and the occurrence of roots in the litter, explains 33% of the total variability of δ¹⁵N in leaves. Thus, in ecosystems polluted with heavy metals, the state of trees is determined not only by the direct toxic effects of heavy metals but also by indirect ones associated with the features of plant mineral nutrition. This fact opens the way to the search for opportunities to control the state of plants in disturbed ecosystems by regulating the content of mineral nutrition elements. Full article

Hurricanes often devastate trees throughout coastal China; accordingly, developing a method to quantitatively evaluate the changes in tree phenotypic characteristics under continuous strong winds is of great significance for guiding forest cultivation practices and mitigating wind hazards. For this research, we built a lifting steel truss carrying a large forced draft fan near a rubber plantation on Hainan Island, and we aligned three selected small rubber trees in a row in front of the fan (with separation distances from the forced draft fan outlet of approximately 1.3, 3.3, and 5.3 m) to explore the susceptibility of rubber trees to the mechanical loading of hurricane-level winds. By adjusting the power of the forced draft fan, four wind speeds were emitted: 0 m/s, 10.5 m/s, 13.5 m/s, and 17.5 m/s. Meanwhile, point clouds of the three rubber trees under different continuous wind speeds were acquired using two terrestrial laser scanners. Computer algorithms were applied to derive the key parameters of the three rubber trees, namely, the zenith and azimuth angles of each leaf, effective leaf area index (LAI), windward area of each tree, volume of the tree canopy, and trunk tilt angle, from these point clouds under all four wind speeds. The results show that by increasing the wind speed from 0 m/s to 17.5 m/s, the leaf zenith angles of the three rubber trees were unimodally distributed with the peak concentrated at 0°, while the leaf azimuth angles were bimodally distributed with the peaks concentrated at 0° and 360°. The effective LAI values of the three trees increased from 2.97, 4.77, and 3.63 (no wind) to 3.84, 5.9, and 4.29 (wind speed of 17.5 m/s), respectively, due to a decrease in the vertical crown projection area caused by the compression of the tree canopy. We also found that the effective LAI, windward area, and canopy volume of the third rubber tree (the tree farthest from the forced draft fan) varied less than those of the other two trees, reflecting the attenuation of the wind speed by the crowns of the two trees closer to the fan. The experimental results also indicate that the joint use of light detection and ranging (LiDAR) data with computer graphics algorithms to analyse the dynamic changes in tree phenotypic characteristics during the passage of a hurricane is promising, enabling the development of a novel strategy for mitigating wind hazards. The proposed method with the designed device capable of producing an adjustable wind speed also has the potential to study the impacts of wind damage under various forest conditions by further modifying the tree spacing and tree species. Full article

(1) Background: The destruction of peatlands caused by forest fire can significantly damage the ecosystems, flora, and fauna found in forests. Swamp jelutung (Dyera polyphylla) is a tree species that can be planted on peatland and combined with seasonal plants to provide multiple economic and environmental benefits. The aim of this study is to analyze the biomass and carbon stocks above and belowground in stands of swamp jelutung of an age class of 10, 13, and 17 years. (2) Methods: Observation plots were determined based on the age classes of D. polyphylla plants. The plots were determined using a purposive sampling method with a size of 20 m × 5 m with two sample plots in each class of plant age. The biomass calculation measured the diameters of living trees without causing any damage. The understory biomass was obtained by cutting and then placing in a container before weighing and recording the wet weight. The necromass was determined by measuring the diameter and length of all the wood. (3) Results: The amount of aboveground biomass (trees) was divided into 111.73 ton/ha (17 years), 55.96 ton/ha (13 years), and 50.08 ton/ha (10 years) age classes. The root biomass had the highest values of 18.36 ton/ha (17 years), 9.45 ton/ha (13 years), and 9.07 ton/ha (10 years). Meanwhile, the organic C contents in peat soil under stands of D. polyphylla were 33.45% (13 years), 31.32% (17 years), and 26.14% (10 years). (4) Conclusions: D. polyphylla trees play a role in restoring forest ecosystems on peatlands and absorb more CO₂ as the trees age. Therefore, they are useful in dealing with climate change. Full article

Ultrasound is a reliable non-destructive method commonly used to evaluate the state of a piece of wood. The effect of the moisture content (MC) on the timber wave velocity, which is different depending on the wood species, must be considered. MC adjustment factors are important if accurate and comparable results are to be achieved. Thus, the goal of this study is to define a model that allows obtaining the adjustment factor to predict the standard velocity (12% of MC (V₁₂) from velocity obtained at different MC for two Costa Rican commercial species: Tectona grandis L.F (teak) and Cupressus lusitanica M. (cypress). This effect was studied on small clean specimens during the desorption stages, from the fiber saturation point to the oven-dry state, controlling the specimen’s mass and MC on 62 specimens. With this data, the rate of change in ultrasound velocity per MC was modeled. Thus, the applicability of already published moisture adjustment models for conifers and hardwood tropical species was proved. The results showed that the proposed model coefficients adjust better than the ones obtained from the wood science literature, which makes them suitable to describe ultrasound velocity in different moisture conditions (V_H). Full article

The Brazilian Cerrado biome is a hotspot due to its ecological importance and high diversity of fauna and flora. We aimed to develop statistical models to predict the crown diameter of open-growing trees using several forest attributes. Potential crown diameter trends in the measured trees were determined by quantile regression. Crown diameter models were developed by regression analyses, artificial neural networks, support vector machine, and random forest techniques. We evaluated 200 trees characterized into 60 species belonging to 30 botanical families. Our equation for potential crown diameter predicts the derived basal area, number of trees, and the necessary growth space of crown diameter at breast height. Artificial neural networks (with the following validation statistics: R² = 0.90, RMSE = 1.21, MAE = 0.93, and MAPE = 16.25) predicted crown diameter more accurately than the other evaluated techniques. Modeling crown diameter via machine learning represents an important step toward the assessment of crown dynamics by species and can support the decision making of silvicultural practices and other related activities in several rural properties within the Cerrado biome. Full article

Productivity assessment studies are essential in forest operations, mainly because their results enable operational planning and rate setting, the development of equitable payment systems, the assessment of environmental performance, the assessment of improvements brought by technology development, and the optimization of larger forest-based systems. This study examines productive performance and fuel consumption in farm-tractor based skidding operations implemented in flat terrain oak harvesting by developing detailed statistics and predictive models on skidding performance. Two felling areas were selected to monitor the operations, and detailed statistics and predictive models were developed at two resolutions by an end-to-end assessment. Based on 56 observed work cycles, and for average values of the number of logs, payload volume, winching distance and extraction distance of 4.96, 1.81 m³, 14.43 m, 177.3 m, respectively, the net efficiency and productivity rates of skidding operations were estimated at 0.125 h/m³ and 8.03 m³/h, respectively. At the resolution of piece-by-piece winching, winching time depended only on the winching distance. At the resolution of overall skidding operations, the skidding time depended on the number of logs in a payload and average winching and extraction distances. The same predictors were relevant in explaining the fuel consumption in skidding operations, which accounted for 3.72 L/h or 0.46 L/m³, while there was a variation in fuel consumption induced by the type of operation. Both efficiency and productivity were found to be highly sensitive to the operational distances, as the main factors affecting them. Nevertheless, significant improvements in efficiency, productivity, and fuel consumption may be achieved when dealing with fewer logs per turn and higher volumes per piece, since the models indicated no effects brought in fuel and time consumption by the log size, and the technical limits of the used winched reached 8.5 tons. Full article

Moso bamboo (Phyllostachys edulis) is a critical forest resource in subtropical China, and reasonable cutting management of moso bamboo forests is essential for improving the productivity of bamboo forests, increasing the income of farmers, and improving the ecological environment. Therefore, we set up sample plots with different cutting widths at the Yixing Forest Farm in Jiangsu Province in December 2017. Moso bamboo growth surveys and soil sampling were conducted in May 2018 to study the effects of different cutting widths on the growth and nutrient content of moso bamboo forests. Our results indicate that strip cutting had significant effects on degraded bamboo shoots, the number of new bamboos, and their ratios. Soil elements showed surface aggregation, and cutting increased the soil nutrient content. Principal component analysis showed that stand characteristics (diameter at breast height and number of new bamboo shoots) were positively associated with total phosphorus and available phosphorus but negatively correlated with available potassium, total potassium, and soil organic carbon. A cutting width of 8 m resulted in rich nutrient content, which is suitable for bamboo cultivation. These results will provide theoretical guidance for the formulation of scientific and reasonable strip cutting methods for moso bamboo forests. Full article

Forest harvesting and fire are major disturbances in boreal forests. Forest harvesting has modified stand successional pathways, which has led to compositional changes from the original conifer-dominated forests to predominantly mixed and hardwood forests. Boreal fire regimes are expected to change with future climate change. Using the LANDIS-II spatially explicit landscape model, we evaluated the effects of forest management scenarios and projected fire regimes under climate change in northeastern Canadian boreal forests, and we determined the subsequent alteration in stand- and landscape-level composition, succession, and spatial configuration of boreal forests. We observed that, in contrast to successional pathways that followed fire, successional pathways that followed forest harvesting favored mixed forests with a prevalence of shade-intolerant hardwoods for up to 300 y after harvesting. This trend was exacerbated under climate change scenarios where forests became dominated by hardwood species, particularly in ecoregions where these species were found currently in low abundance. Our results highlight the failure of existing forest management regimes to emulate the effects of natural disturbance regimes on boreal forest composition and configuration. This illustrates the risks to maintaining ecosystem goods and services over the long term and the exacerbation of this trend in the context of future climate change. Full article

Acid forest soils in South China experience a chronically elevated input of atmospheric nitrogen (N), turning them into hot spots for gaseous N emissions. Soil moisture is known to be a major controller for the partitioning of gaseous N loss to nitric (NO) and nitrous oxide (N₂O), which may be of particular relevance in the monsoonal climate of South China. To study this partitioning in more detail, we determined gas phase kinetics of NO and N₂O release during laboratory dry-out of acidic surface soils from the headwater catchment TieShanPing (TSP), situated close to Chongqing, SW China. Soils were sampled from two hydrologically distinct environments, a well-drained hill slope (HS), and a periodically flooded groundwater discharge zone (GDZ). Production and consumption of NO were studied in an automated flow-through system purged with NO-free or NO-spiked air. Production rates peaked at 21% and 18% water filled pore space (WFPS) in HS and GDZ soils, respectively, suggesting nitrification as the dominant process of NO formation in both landscape units. In HS soils, maximum production and consumption occurred at the same WFPS, whereas GDZ soils displayed maximum NO consumption at higher WFPS than maximum production, suggesting that denitrification is an important NO sink in GDZ soils. Net N₂O release was largest at 100% WFPS and declined steadily during drying. Integrated over the entire range of soil moisture, potential NO-N loss outweighed potential N₂O-N loss, suggesting that N-saturated, acid forest soil is an important NO source. Full article

The auto exhaust and dust derived from increased traffic volumes have led to an increasing level of atmospheric particulates in urban areas, which have become a primary pollutant of ambient air in urban zones. Roadside plants can effectively retain atmospheric particulates and clean the urban air via foliar capture of road dust. Five common roadside plants in Hangzhou were selected to evaluate their capacity for the retention of particulate matter (PM) and the accumulation of metals. The results showed that the PM retention capacity of the different plants varied greatly, as was the case with Loropetalum chinense var. rubrum Yieh, Osmanthus fragrans (Thunb.) Loureiro, Pittosporum tobira (Thunb.) Ait, Photinia × fraseri Dress and Cinnamomum camphora (L.) Presl. In addition, the amounts of particles retained by the plants varied among seasons, with the highest retention in winter (12.19 g·m⁻²) and the lowest retention in spring (6.89 g·m⁻²). The solids on the leaf surface were mainly irregular particles, such as mineral fragments, soot aggregates, and fly ash particles. Meanwhile, these plant species can effectively accumulate heavy metals that attached to the particles. The leaves of the five tree species had the highest amounts of copper (Cu) and the lowest amounts of cadmium (Cd). Among species, L. chinense and P. tobira had the strongest comprehensive capacity to adsorb particulate matter and heavy metals. The results shed light on the rational selection of road plants, both as ornaments and to purify air via dust suppression in subtropical zones. Full article