Foliar dust retention capability and source identification of atmospheric particulates in local urban environments of Xuzhou, China

Plants effectively filter ambient air by adsorbing particulate matter. The correct selection of landscape plants can exert greater dust retention benefits in different polluted areas. However, few studies have focused on the dust retention ability and related physiological responses of plants under continuous dust pollution from different dust sources. Here, we assessed the particle retention dynamics and plant physiology (chlorophyll content, soluble protein content, soluble sugar content, and peroxidase activity) of six shrubs (Berberis thunbergii var. atropurpurea, Ligustrum vicaryi, Rosa multiflora, Sorbaria sorbifolia, Swida alba, and Syzyga oblata) under continuous dust pollution from different dust sources (industrial sources: area below the direction of the coal-fired thermal power plant in Chengyang District, Qingdao, China; traffic sources: both sides of the road in each direction at the intersection of Great Wall Road and Zhengyang Road, Chengyang District, Qingdao, China; clean sources: Qingdao Agricultural University Campus, Qingdao Olympic Sculpture Park). The results showed that R. multiflora had the highest dust retention per unit leaf area of 3.27 ± 0.018g·m-2 and 2.886 ± 0.02g·m-2 in the experimental treatments of fuel source dust and clean source dust, respectively. The chlorophyll content of the tested shrubs significantly decreased due to the influence of dust treatment time, the range of cellular osmoregulatory substances (soluble sugars, soluble proteins, proline) tended to first increase and then decrease, and the antioxidant enzyme activities (superoxide dismutase, peroxidase) tended to increase and then decrease after continuous dust treatment. The greatest physiological changes were observed in plants within the industrial dust treatment area. The peroxidase activity and chlorophyll could be used as sensitive indicators of dust pollution in plants. R. multiflora showed better resistance to dust and had a greater dust retention capacity than other shrubs, making it more suitable for planting as a greening tree in industrial and traffic-polluted areas. S. alba and S. sorbifolia are sensitive to dust pollution, so they can be used as sensitive tree species to indicate atmospheric dust pollution. Our results may help design a feasible approach for urban shrub greening.

Aeolian mineral dust is an important component of the Earth’s environmental systems, playing roles in the planetary radiation balance, as a source of fertilizer for biota in both terrestrial and marine realms and as an archive for understanding atmospheric circulation and paleoclimate in the geologic past. Crucial to understanding all of these roles of dust is the identification of dust sources. Here we review the methods used to identify dust sources active at present and in the past. Contemporary dust sources, produced by both glaciogenic and non-glaciogenic processes, can be readily identified by the use of Earth-orbiting satellites. These data show that present dust sources are concentrated in a global dust belt that encompasses large topographic basins in low-latitude arid and semiarid regions. Geomorphic studies indicate that specific point sources for dust in this zone include dry or ephemeral lakes, intermittent stream courses, dune fields, and some bedrock surfaces. Back-trajectory analyses are also used to identify dust sources, through modeling of wind fields and the movement of air parcels over periods of several days. Identification of dust sources from the past requires novel approaches that are part of the geologic toolbox of provenance studies. Identification of most dust sources of the past requires the use of physical, mineralogical, geochemical, and isotopic analyses of dust deposits. Physical properties include systematic spatial changes in dust deposit thickness and particle size away from a source. Mineralogy and geochemistry can pinpoint dust sources by clay mineral ratios and Sc-Th-La abundances, respectively. The most commonly used isotopic methods utilize isotopes of Nd, Sr, and Pb and have been applied extensively in dust archives of deep-sea cores, ice cores, and loess. All these methods have shown that dust sources have changed over time, with far more abundant dust supplies existing during glacial periods. Greater dust supplies in glacial periods are likely due to greater production of glaciogenic dust particles from expanded ice sheets and mountain glaciers, but could also include dust inputs from exposed continental and insular shelves now submerged. Future dust sources are difficult to assess, but will likely differ from those of the present because of global warming. Global warming could bring about shifts in dust sources by changes in degree or type of vegetation cover, changes in wind strength, and increases or decreases in the size of water bodies. A major uncertainty in assessing dust sources of the future is related to changes in human land use, which could affect land surface cover, particularly due to increased agricultural endeavors and water usage.

This paper compares and evaluates four principal methods of dust source and plume identification using MODIS data. The four MODIS methods used here are: (i) Roskovensky and Liou's dust identification algorithm, (ii) Ackerman's model, (iii) Normalized Difference Dust Index (NDDI), and (iv) Deep Blue algorithm. These techniques were applied to three recent significant events in the Middle East region. In addition, true color images and the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model were used to evaluate the result of each technique. To optimize the result of dust detection for each technique, the published dust–nondust thresholds had to be considerably adjusted on an event-by-event basis. Results show that techniques that use brightness temperature (BT) difference are the most reliable techniques for dust source detection in several situations such as multiplume and multimineralogical conditions (unlike the NDDI index and other optical based algorithms). However, these techniques cannot effectively differentiate dust plume from the bright desert surfaces (due to the same thermal behavior of dust and desert surfaces in both BT31 and BT32). This weakness impelled us to develop a new model based on Ackerman's technique because of its more precise results in dust source identification. In this new presented model called Middle East Dust Index (MEDI), BT29 was involved to highlight the difference between dust and desert surfaces as the [(BT31–BT29)/(BT32–BT29)] equation. In this equation, the values of dusty pixels are less than 0.6 while nondusty pixels are greater than 0.6. Results indicate that the MEDI model is ideal in both identifying dust plume and sources and desert surfaces. Finally, due to some misclassification of the MEDI model in differentiating cirrus clouds from dust plumes, the NDDI index was added to the initial model to distinguish them more accurately.

In April 2023, a major dust storm event in Lanzhou attracted widespread attention. This study provides a comprehensive analysis of the causes, progression, and dust sources of this event using multiple data sources and methods. Backward trajectory analysis using the HYSPLIT model was employed to trace the origins of the dust, while FY-2H satellite data provided high-resolution dust distribution patterns. Additionally, the MAIAC AOD product was used to analyze Aerosol Optical Depth, and concentration-weighted trajectory (CWT) analysis was used to identify key dust source regions. The study found that PM10 played a dominant role in the storm, and the AOD values during the storm in Lanzhou were significantly higher than the annual average, highlighting the severe impact on regional air quality. Key meteorological conditions influencing the storm's occurrence were analyzed, including the formation and eastward movement of a high-potential ridge, convection driven by diurnal temperature variations, and surface temperature increases coupled with decreased relative humidity, which together promoted the generation and development of dust. Backward trajectory and dust distribution analyses revealed that the dust primarily originated from Central Asia, western Mongolia, Xinjiang, and Gansu. From the 19th to the 21st, the dust distribution showed similarities between day and night, with a noticeable increase in dust concentration from night to day due to strong vertical atmospheric mixing. To mitigate the impacts of future dust storms, this study highlights both short-term and long-term strategies, including enhanced monitoring systems, public health advisories, and vegetation restoration in key source regions. Strengthening regional and international cooperation for transboundary dust management is also emphasized as critical for sustainable mitigation efforts. These findings are significant for understanding and predicting the causes, characteristics, and environmental impacts of dust storms in Lanzhou and the Northwestern region.

Identification and characterization of sources of atmospheric mineral dust in East Asia

Assessment of foliar dust particle retention and toxic metal accumulation ability of fifteen roadside tree species: Relationship and mechanism

ABSTRACTThe present study was carried out to assess and understand the potential health risk, level of contamination, composition pattern, and sources of urban foliar dust in Nanjing City with respect to polycyclic aromatic hydrocarbons (PAHs). Five urban functional areas of foliar dust were analysed and the contents of 16 priority PAHs were determined. Total PAH concentrations in foliar dust ranged from 1.77 to 19.02 μg·g−1, with an average value of 6.98 μg·g−1. The PAH pattern was dominated by four and five-ring PAHs (contributing > 38% of total PAHs) in all of the five functional areas. The results indicated that the combustion of fossil fuel, coal, and biomass, as well as vehicle traffic emissions were the major sources of PAHs. The estimated incremental lifetime cancer risk due to PAHs in foliar dust were 8.19 × 10−6, 6.63 × 10−6, and 9.65 × 10−6 for childhood, adolescence and adulthood, respectively, indicating a high risk of cancer from exposure to foliar dust in Nanjing. Our results indicated that foliar dust might be a useful indicator of atmospheric PAH pollution.

Application of remote sensing techniques and machine learning algorithms in dust source detection and dust source susceptibility mapping

Identification of dust sources using long term satellite and climatic data: A case study of Tigris and Euphrates basin

In recent years, dust events in Iraq become very frequent due to its emission from active local dust sources or transportation from abroad. This study aims to identify dust sources in Iraq for the period (1st January, 2005 to 31 December, 2016) using mean of monthly mean of the aerosol optical properties including Deep Blue Aerosol Optical Depth(DB-AOD), Deep Blue Angstrom Exponent(DB-AE) and UV Positive Absorption Aerosol Index(AAI) acquired from space borne instruments including MODerate resolution Imaging Spectroradiometer (MODIS) for both Aqua and Terra, Multiangle Imaging SpectroRadiometer (MISR) and Ozone Monitoring Instrument (OMI), considering the dust aerosols having values of AOD>0.5, AE<0.5 and AI>0.7 based on the predefined thresholds. The results show that Al-Jazira and the southern region of Iraq considered as significant dust sources most of the year, with the absence of active dust sources in December, January, October and November. While spring and summer months show many active dust sources in the Alluvial plain, western plateau, southern and southeastern parts of Iraq with high AOD, low AE and high AAI especially in April, May, June and July. MISR/AOD shows lower values of MODIS-DB in Iraq along months of the years, which could be due to the insufficient coverage over dust regional sources compared to MODIS.

Although mineral dust plays a key role in the Earth’s climate system and in climate and weather prediction, models still have difficulties in predicting the amount and distribution of mineral dust in the atmosphere. One reason for this is the limited understanding of the distribution of dust sources and their behavior with respect to their spatiotemporal variability in activity. For a better estimation of the atmospheric dust load, this paper presents an approach to localize dust sources and thereby estimate the sediment supply for a study area centered on the Aïr Massif in Niger with a north–south extent of 16 ∘ –22 ∘ N and an east–west extent of 4 ∘ –12 ∘ E. This approach uses optical Sentinel-2 data at visible and near infrared wavelengths together with HydroSHEDS flow accumulation data to localize ephemeral riverbeds. Visible channels from Sentinel-2 data are used to detect sand sheets and dunes. The identified sediment supply map was compared to the dust source activation frequency derived from the analysis of Desert-Dust-RGB imagery from the Meteosat Second Generation series of satellites. This comparison reveals the strong connection between dust activity, prevailing meteorology and sediment supply. In a second step, the sediment supply information was implemented in a dust-emission model. The simulated emission flux shows how much the model results benefit from the updated sediment supply information in localizing the main dust sources and in retrieving the seasonality of dust activity from these sources. The described approach to characterize dust sources can be implemented in other regional model studies, or even globally, and can thereby help to get a more accurate picture of dust source distribution and a more realistic estimation of the atmospheric dust load.

Concentrations of 19 elements (Al, Fe, Ca, K, Mg, Na, S, Ti, Ba, Sr, Zn, V, Cu, Mn, Cr, Pb, Ni, Co, and Cd) in foliar dust samples were determined from 6 different roadside locations of Bilaspur city (Chhattisgarh), India. Principal component analysis (PCA) indicated the significance of vehicular activities followed by sources such as firework events and other industrial/regional/transboundary sources in foliar dust in the area of study. Risk assessment of metal levels in foliar dust was performed using several indices based on the data collected from different sites. The geo-accumulation index (Igeo) analysis indicated foliar dust was moderately and extremely polluted with S and Cd, respectively, while practically unpolluted with most other elements (Al, Fe, Ca, K, Mg, Na, Ti, Ba, Sr, Zn, V, Cu, Mn, Cr, Pb, Ni, and Co). The values of pollution (IPOLL) index and contamination factor (CF) of Cd indicated a high pollution level. Comparable results were found for the ecological risk (Eri) of Cd (above 320) with a very high Eri at all sites. In addition, the overall Eri index (RI) of foliar dust at all sites was very high due to a greater Cd contribution.

Environmental context Exploring the characterisation and sources of the chemical composition of fine particulate matter in the atmosphere is critical to human health. The main sources of PM2.5 in Lanzhou City are dust, secondary pollution, industry, biomass burning, traffic and coal combustion. In Chengguan District, dust sources are the most significant contributors, whereas secondary pollution sources are dominant in Xigu District. This provides directions and ideas for future local ecological environment management, especially air pollution. Rationale The characterisation and sources of the chemical composition of fine particulate matter in the atmosphere are of critical importance to the environment and human health. As the capital of Gansu Province with a population of more than 4 million people, and being one of important industrial cities in western China, it is of importance to study the characterisation and sources of atmospheric fine particulate matter chemical constituents in Lanzhou City. Methodology In this study, monitoring was carried out from January 2018 to June 2022 in Chengguan and Xigu Districts, and a total of 702 valid samples were collected. Measurements included PM2.5 mass concentrations, water-soluble ions, metals, metalloids and polycyclic aromatic hydrocarbons (PAHs) in both districts. Results The results showed that PM2.5 mass concentrations in both districts exhibited a decreasing trend throughout the study period, with seasonal variations characterised as high in winter and spring, and low in summer and autumn. The concentration of water-soluble ions follows the order of SO42− &gt; NO3− &gt; NH4+ &gt; Cl−, with a seasonal distribution pattern of winter &gt; autumn &gt; spring &gt; summer (P &lt; 0.05). The concentrations of metals and metalloids were higher in Xigu District than in Chengguan District, following a seasonal pattern of spring &gt; winter &gt; autumn &gt; summer (P &lt; 0.05). PAHs concentrations were significantly higher in Chengguan District than in Xigu District (P &lt; 0.05), with a seasonal pattern of being high in winter and low in summer (P &lt; 0.05). Discussion The main sources of PM2.5 in Lanzhou City comes from dust, secondary pollution, industry, biomass burning, traffic and coal combustion. Dust sources were the most significant contributors in Chengguan District (37.6%), whereas secondary pollution sources were predominant in Xigu District (40.9%). This provides the latest research evidence exploring feasible pollution reduction pathways for Lanzhou to achieve cleaner skies. The results provide valuable insights and a scientific basis for the prevention and control of atmospheric PM2.5 pollution in Lanzhou City.

Feasibility studies for a dust observatory between earth and the asteroid belt

Introducing a novel dust source identification method based on edge points and paths extracted from integration of time-series MODIS products