Quantifying the characteristics of particulate matters captured by urban plants using an automatic approach

Microscopic characteristics and sources of atmospheric dustfall in open-pit mining coal resource-based city in the arid desert area of Northwest China

Atmospheric dustfall is solid air pollutant, has a major impact on the environment and human health. The objective of this study was to investigate the microscopic characteristics and sources of atmospheric dustfall in open-pit mining coal resource-based city in the arid desert area of Northwest China. The characteristics of size and shape factors, variation of shape factors with size distribution, types of individual particles, and sources of atmospheric dustfall, which were collected in the open-pit mining area and surrounding areas, were analyzed by X-ray diffraction (XRD) and scanning electron microscopy coupled with an energy dispersive spectrometer (SEM-EDS) combined with graphical method and shape factors. The results showed that the atmospheric dustfall in all functional areas was dominated by coarse-grained particles. The shape of the atmospheric dustfall deviated from spherical shape, and with decreasing particle size, the difference in shape factors increased in each functional area. The EDS and XRD analyses indicated the presence of 13 types of particles. The sources were mainly local and included soil dust from each functional area; industrial dust, construction dust, biogenic impurities, fossil fuel combustion, wear products of motor vehicle parts, motor vehicle exhaust emissions, and emission and excreta from biological activities in each functional area except the desert area; emissions from a steel plant in the industrial area; coal-associated ore, coal dust, coal gangue emissions, and emissions from the spontaneous combustion of coal gangue in the open-pit mining area; secondary chemical crystallization products in the industrial area and the open-pit mining area; dust generated by vehicles abrading the surface of the off-mine coal road and in the open-pit mining area.

Differences in particulate matter retention and leaf microstructures of 10 plants in different urban environments in Lanzhou City

Particulate matter (PM) is a major primary environmental air pollutant and poses a threat to human health. Differences in the environment and leaf microstructures of plants will result in varying abilities to retain PM, but the effects of changes in these factors on PM retention are not yet well understood. This study selected 10 plant species in four urban areas (sports field, park, residential green space, and greenway) as the study objects. The amount of retained PM by the different species was measured, and the leaf microstructures were observed. It was found that the environment significantly affected both PM retention and leaf microstructure. The ranking of PM retention in the 10 species in four areas was greenway > residential green space > park > sports field. The ranking of average stomatal width and length was park > sports field > residential green space > greenway, while that of average stomatal density was greenway > residential green space > park > sports field. Different environments affected the length and density of trichomes in the leaves. These changes represented the adaptation of plant species to the growth environment. The stomata and grooves of the leaf surface significantly affected the ability of plants to retain PM. The amount of PM retained by different species varied. In all four urban areas, Prunus × cistena N. E. Hansen ex Koehne (purple leaf sand cherry), Prunus cerasifera Ehrhart f. atropurpurea (Jacq.) Rehd. (cherry plum), Buxus sinica var. parvifolia M. Cheng (common boxwood), and Ligustrum × vicaryi Rehder (golden privet) showed strong PM retention. The results of this study will provide information for planners and urban managers for the selection of plant species.

Experimental Characterization of Particulate and Gaseous Emissions from Biomass Burning of Six Mediterranean Species and Litter

Wildfires across the Mediterranean ecosystems are associated with safety concerns due to their emissions. The type of biomass determines the composition of particulate matter (PM) and gaseous compounds emitted during the fire event. This study investigated simulated fire events and analysed biomass samples of six Mediterranean species and litter in a combustion chamber. The main aims are the characterization of PM realized through scanning electron microscopy (SEM/EDX), the quantification of gaseous emissions through gas chromatography (GC-MS) and, consequently, identification of the species that are potentially more dangerous. For PM, three size fractions were considered (PM10, 2.5 and 1), and their chemical composition was used for particle source-apportionment. For gaseous components, the CO, CO2, benzene, toluene and xylene (BTXs) emitted were quantified. All samples were described and compared based on their peculiar particulate and gaseous emissions. The primary results show that (a) Acacia saligna was noticeable for the highest number of particles emitted and remarkable values of KCl; (b) tree species were related to the fine windblown particles as canopies intercept PM10 and reemit it during burning; (c) shrub species were related to the particles resuspended from soil; and (d) benzene and toluene were the dominant aromatic compounds emitted. Finally, the most dangerous species identified during burning were Acacia saligna, for the highest number of particles emitted, and Pistacia lentiscus for its high density of particles, the presence of anthropogenic markers, and the highest emissions of all gaseous compounds.

Diversity Monitoring of Coexisting Birds in Urban Forests by Integrating Spectrograms and Object-Based Image Analysis

In the context of rapid urbanization, urban foresters are actively seeking management monitoring programs that address the challenges of urban biodiversity loss. Passive acoustic monitoring (PAM) has attracted attention because it allows for the collection of data passively, objectively, and continuously across large areas and for extended periods. However, it continues to be a difficult subject due to the massive amount of information that audio recordings contain. Most existing automated analysis methods have limitations in their application in urban areas, with unclear ecological relevance and efficacy. To better support urban forest biodiversity monitoring, we present a novel methodology for automatically extracting bird vocalizations from spectrograms of field audio recordings, integrating object-based classification. We applied this approach to acoustic data from an urban forest in Beijing and achieved an accuracy of 93.55% (±4.78%) in vocalization recognition while requiring less than ⅛ of the time needed for traditional inspection. The difference in efficiency would become more significant as the data size increases because object-based classification allows for batch processing of spectrograms. Using the extracted vocalizations, a series of acoustic and morphological features of bird-vocalization syllables (syllable feature metrics, SFMs) could be calculated to better quantify acoustic events and describe the soundscape. A significant correlation between the SFMs and biodiversity indices was found, with 57% of the variance in species richness, 41% in Shannon’s diversity index and 38% in Simpson’s diversity index being explained by SFMs. Therefore, our proposed method provides an effective complementary tool to existing automated methods for long-term urban forest biodiversity monitoring and conservation.

Macro and trace elements in the black pine needles as inorganic indicators of urban traffic emissions

Urban activities intensify air pollution by increasing the amount of particulate matter (PM). The trees collect PM by adsorption on the leaf surface and simultaneously absorb inorganic components. In this research, we investigated the potential of the black pine as bioindicator of road traffic emissions in Cluj-Napoca (Romania). We defined three sites types with different exposure to the road traffic (streets, outskirts, parks) and a control site far from the city. We quantified 17 inorganic components (Al, B, Ba, Ca, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, P, Pb, Sr, Zn) by MP-AES (microwave-plasma atomic emission spectroscopy) technique in the one-year-old needles and we identified the best candidates for biomonitoring purposes. The concentration of Ba, Cr, Cu and Fe showed the most sensitive variations with the road traffic intensity. While in the streets the Ba, Cu and Fe increased by 2.8-3.5 times in relation to the control site, the Cr varied in the highest degree exhibiting ratios of 2.2 (parks), 3.3 (outskirts) and 6.3 (streets). The success of these elements lies in several characteristics: they are closely related to non-exhaust emissions, they are readily absorbed through the leaves rather than the roots, and they tend to accumulate in the needles instead of being relocated to other organs. The street maintenance activities caused considerable accumulation of Na in the trees from the roadsides, but had no impact over the trees from the parks. The elements originating mainly in the re-suspended urban dust (Ni, Pb, Sr) equally affected the pines from the streets and parks.

Monitoring of particulate matter (PM2.5 and PM10) in San Juan city, Argentina, using active samplers and the species Tillandsia capillaris

The concentration of particulate matter (PM2.5 and PM10) was studied in San Juan city, Argentina, during winter and spring of 2017. Samplers of particulate matter (PM) and individuals of the plant species Tillandsia capillaris were placed in the centre of the city to be used as a biomonitors of atmospheric particulate matter. The PM filters and PM deposited in T. capillaris leaves were analysed to measure particle concentration and concentrations of elements (K, Ca, Mn, Fe, Cu, Zn, Br, Sr, Ba and Pb) using X-ray fluorescence by synchrotron radiation (SR-XRF). Linear regression analysis showed significant positive correlations between PM concentration in the atmosphere and the particles deposited on T. capillaris leaves. The elements quantified in PM2.5 and PM10 filters were subjected to a principal component analysis, which showed the presence of three emission sources in the study area (soil, vehicular traffic and industry) in both fractions. It was not possible to conduct this analysis with the elements obtained from the extraction of T. capillaris leaves, since most of them are solubilised at the moment of extraction. Biomonitoring with T. capillaris might be used to estimate the concentration of particulate matter in large areas or in remote sites with no electrical power supply to run active samplers. Further studies should be carried out in other regions, and more variables should be incorporated to obtain increasingly deterministic models.

Coagulation effect of aero submicron particles on plant leaves: Measuring methods and potential mechanisms

Aero submicron particles (d < 1 μm) have attracted widely attention due to their difficulty in removal from the air and serious threat to human health. Leaves are considered as important organs to purify particulate matter and alleviate air pollution. However, the current research mainly focuses on the removal capacity of particulate matter by urban plants at different scales, there are relatively few studies on the change of particle diameter at the air-leaf interface during this process. This study is one of the first to propose the existence of coagulation effect of aero submicron particles on the leaves, and a sweep-resuspension method and X-ray microscope were used to measure such size changes of two typical subtropical broad-leaf plants. The results showed that the size of submicron particles increased significantly during the migration from atmosphere to leaf surface: the average particle size increased from 0.48 μm at emission to 3.40 μm on the leaf surface, while the proportion of submicron particles decreased from 95% to less than 20%. The sweep-resuspension method was easy to implement, the data was easy to obtain, and the cost was low, therefore it could be widely used in the determination of the coagulation effect. The coagulation effect was also inferred as an important mechanism used by plants to reduce particulate matter. In the process of particulate removal: coagulation effect and dry deposition are actually two steps that occur simultaneously and interact. This finding refined the understanding of particulate removal processing, and laid a foundation for further research on factors affecting coagulation, which can be helpful for optimizing tree species selection and plant arrangement.

An ultra-spatially resolved method to quali-quantitative monitor particulate matter in urban environment

Monitoring the amount and composition of airborne particulate matter (PM) in the urban environment is a crucial aspect to guarantee citizen health. To focus the action of stakeholders in limiting air pollution, fast and highly spatially resolved methods for monitoring PM are required. Recently, the trees' capability in capturing PM inspired the development of several methods intended to use trees as biomonitors; this results in the potential of having an ultra-spatially resolved network of low-cost PM monitoring stations throughout cities, without the needing of on-site stations. Within this context, we propose a fast and reliable method to qualitatively and quantitatively characterize the PM present in urban air based on the analysis of tree leaves by scanning electron microscopy combined with X-ray spectroscopy (SEM/EDX). We have tested our method in the Real Bosco di Capodimonte urban park (Naples, Italy), by collecting leaves from Quercus ilex trees along transects parallel to the main wind directions. The coarse (PM_10-2.5) and fine (PM_2.5) amounts obtained per unit leaf area have been validated by weighting the PM washed from leaves belonging to the same sample sets. PM size distribution and elemental composition match appropriately with the known pollution sources in the sample sites (i.e., traffic and marine aerosol). The proposed methodology will then allow the use of the urban forest as an ultra-spatially resolved PM monitoring network, also supporting the work of urban green planners and stakeholders.

Quantification of the traffic-generated particulate matter capture by plant species in a living wall and evaluation of the important leaf characteristics

Traffic-generated particulate matter (PM) is a significant fraction of urban PM pollution and little is known about the use of living walls as a short-term strategy to reduce this pollution. The present study evaluated the potential of twenty living wall plants to reduce traffic-based PM using a living wall system located along a busy road in Stoke-on-Trent, UK. An Environmental Scanning Electron Microscope (ESEM) and ImageJ software were employed to quantify PM accumulation on leaves (PM₁, PM_2.5 and PM₁₀) and their elemental composition was determined using Energy Dispersive X-ray (EDX). Inter-species variation in leaf-PM accumulation was evaluated using a Generalized Linear Mixed-effect Model (GLMM) using time as a factor; any differential PM accumulation due to specific leaf characteristics (stomatal density, hair/trichomes, ridges and grooves) was identified. The study showed a promising potential for living wall plants to remove atmospheric PM; an estimated average number of 122.08 ± 6.9 × 10⁷ PM₁, 8.24 ± 0.72 × 10⁷ PM_2.5 and 4.45 ± 0.33 × 10⁷ PM₁₀ were captured on 100 cm² of the living wall used in this study. Different species captured significantly different quantities of all particle sizes; the highest amount of all particle sizes was found on the leaf-needles of Juniperus chinensis L., followed by smaller-leaved species. In the absence of an apparent pattern in correlation between PM accumulation and leaf surface characteristics, the study highlighted the importance of individual leaf size in PM capture irrespective of their variable micro-morphology. The elemental composition of the captured particles showed a strong correlation with traffic-based PM and a wide range of important heavy metals. We conclude that the use of living walls that consist largely of smaller-leaved species and conifers can potentially have a significant impact in ameliorating air quality by removing traffic-generated PM pollution to improve the wellbeing of urban dwellers.

Determining the Contribution of Nearby Power Plants to Deposited Foliar Dust: A Case Study of BTPS, Bokaro

Deposition of dust particles on foliage surfaces helps to filter airborne dust particles that occur predominantly in areas near thermal power plants (TPPs). Highly dust-laden foliage surrounding TPPs is a serious issue affecting the vegetation and façade greening adversely. Fly ash (FA) generated by TPPs have an adverse impact on the growth and development of flora. Therefore, identification of their percentage contribution on foliar dust (FD) is of utmost importance. The present study attempted to identify all the contributing sources to FD. Morphological and chemical characterization of FD, FA, and road dust (RD) has been evaluated, followed by their multivariate statistical analysis. Contamination of FD from different sources was estimated by using field emission scanning electron microscope (FE-SEM) coupled with energy dispersive X-ray technique (EDX), Fourier transform infrared spectroscope (FTIR), and atomic absorption spectrophotometer techniques. Particle size distribution of FD revealed that the major portion of FD was <2 µm. FE-SEM and EDX analysis confirmed contamination of FD by FA, resuspension of RD, and local sources. FTIR peaks depicted the presence of different functional groups, including silica from nearby roads, saturated-nonsaturated, and aromatic organic functional groups originating predominantly from different activities of TPPs and traffic. Results of IR were in agreement with results obtained in physicochemical analyses. Heavy metals analysis of FA demonstrated high concentration of carcinogens Cr, Cu, Cd, and Ni and could be considered a marker to them. Certain heavy metals (Fe, Co, Mn, Pb, and Zn) were found to be in the order RD > FA > FD. This explores the necessity for considering other sources other than TPP sources. Principal component analysis (PCA) of heavy metals present in FD revealed that the sampling area was chiefly influenced from three sources: Bokaro thermal power station (55 %), RD (18 %), and local sources (27 %). Cluster analysis complemented the results of Pearson correlation matrix and PCA. Analyses illustrated the substantial influence of TPPs along with other source's significance in contamination of FD.