Human health risks brought by fine atmospheric particles raise scholarly and policy awareness about the role of urban trees as bio-filters of air pollution. While a large number of empirical studies have focused on the characteristics of vegetation leaves and their effects on atmospheric particle retention, the dry deposition of particles on branches, which plays a significant role in capturing and retaining particles during the defoliation period and contributes substantially to total removal of atmospheric particles, is under-investigated. To fill in this knowledge gap, this case study examined the dry deposition velocities (Vd) of submicron particulate matters (PM₁) on the branches of six common deciduous species in Shanghai (China) using laboratory experiments. And the association between Vd and key branch anatomical traits (including surface roughness, perimeter, rind width proportion, lenticel density, peeling, and groove/ridge characteristics) was explored. It was found that surface roughness would increase Vd, as a rougher surface significantly increases turbulence, which is conducive to particle diffusion. By contrast, peeling, branch perimeter, and lenticel density would decrease Vd. Peeling represents the exfoliated remains on the branch surfaces which may flutter considerably with airflow, leading to particle resuspension and low Vd. When branch perimeter increases, the boundary layer of branches thickens and a wake area appears, increasing the difficulty of particles to reach branch surface, and reducing Vd. While lenticels can increase the roughness of branch surface, their pointy shape would uplift airflow and cause a leeward wake area, lowering Vd. This finely wrought study contributes to a better understanding of branch dry deposition during leaf-off seasons and potential of deciduous trees serving as nature-based air filters all year round in urban environments.

Exposure to suspended particulate matter (PM), found in the air, is one of the most acute environmental problems that affect the health of modern society. Among the different airborne pollutants, heavy metals (HMs) are particularly relevant because they are bioaccumulated, impairing the functions of living beings. This study aimed to establish a method to predict heavy metal concentrations in leaves and road dust, through their magnetic properties measurements. For this purpose, machine learning, automatic linear regression (MLR), and support vector machine (SVM) were used to establish models for the prediction of airborne heavy metals based on leaves and road dust magnetic properties. Road dust samples and leaves of two common evergreen species (Cupressus lusitanica/Casuarina equisetifolia) were sampled simultaneously during two different years in the Great Metropolitan Area (GMA) of Costa Rica. MLR and SVM algorithms were used to establish the relationship between airborne heavy metal concentrations based on single (χlf) and multiple (χlf y χdf) leaf magnetic properties and road dust. Results showed that Fe, Cu, Cr, V, and Zn concentrations were well-simulated by SVM prediction models, with adjusted R² values ≥ 0.7 in both training and test stages. By contrast, the concentrations of Pb and Ni were not well-simulated, with adjusted R² values < 0.7 in both training and test stages. Heavy metal predicción models using magnetic properties of leaves from Casuarina equisetifolia, as collectors, yielded better prediction results than those based on the leaves of Cupressus lusitanica and road dust, showing relatively higher adjusted R² values and lower errors (MAE and RMSE) in both training and test stages. SVM proved to be the best prediction model with variations between single (χlf) and multiple (χlf y χdf) magnetic properties depending on the element studied.

Airborne fine particles can affect climate change and human health; moreover, they can be transported over significant distances. However, studies on characteristics of individual particles and their morphology, elemental composition, aging processes, and spatial distribution after long-range transport over the Yellow Sea are limited. Therefore, in this study, we conducted shipborne measurements of fine particulate matter of less than 2.5 μm in diameter (PM₂.₅) over the Yellow Sea and classified the individual particles into seven types based on their morphology and composition. Overall, the percentage of organic-rich particles was the highest, followed by that of sea spray, sulfur-rich, dust, metals, fly ash, soot, and other particles. Near Shandong, China, the percentage of fly ash and sulfur-rich particles increased, while an increased percentage of only sulfur-rich particles was observed near the Korean Peninsula. In the open sea, the PM₂.₅ concentrations were the lowest, and sea spray particles predominated. During the cruises, three types (Types 1, 2, and 3) of events with substantially increased PM₂.₅ concentrations occurred, each with different dominant particles. Type 1 events frequently featured air masses from northern China and Mongolia with high wind speeds and increased dust particles. Type 2 events involved air masses from China with high wind speeds; fly ash, soot, organic-rich particles, and the sulfate percentage in PM₂.₅ increased. Type 3 events displayed stagnant conditions and local transport (from Korea); soot, dust particles, and the secondary sulfate and nitrate percentages in PM₂.₅ increased. Thus, different types of transport affected concentrations and dominant types of fine particles over the Yellow Sea during spring.

The UK implemented a lockdown in Spring (2020) to curtail the person-to-person transmission of the SARS-CoV-2 virus. Measures restricted movements to one outing per day for exercise and shopping, otherwise most people were restricted to their dwelling except for key workers (e.g. medical, supermarkets, and transport). In this study, we quantified changes to air quality across the United Kingdom from 30/03/2020 to 03/05/2020 (weeks 14–18), the period of most stringent travel restrictions. Daily pollutant measurements of NO₂, O₃ and PM₂.₅ from the national network of monitoring sites during this period were compared with measurements over the same period during 2017–19. Comparisons were also made with predicted concentrations for the 2020 period from business-as-usual (BAU) modelling, where the contributions of normal anthropogenic activities were estimated under the observed meteorological conditions. During the lockdown study period there was a 69% reduction in traffic overall (74% reduction in light and 35% in heavy vehicles). Measurements from 129 monitoring stations, identified mean reductions in NO₂ of 38.3% (−8.8 μg/m³) and PM₂.₅ of 16.5% (−2.2 μg/m³). Improvements in NO₂ and PM₂.₅ were largest at urban traffic sites and more modest at background locations where a large proportion of the population live. In contrast, O₃ concentrations on average increased by 7.6% (+4.8 μg/m³) with the largest increases at roadside sites due to reductions in local emissions of NO. A lack of VOC monitoring limited our capacity to interpret changes in O₃ at urban background locations. BAU models predicted comparable NO₂ reductions and O₃ gains, although PM₂.₅ episodes would have been more prominent without lockdown. Results demonstrate the relatively modest contribution of traffic to air quality, suggesting that sustained improvements in air quality require actions across various sectors, including working with international and European initiatives on long-range transport air pollutants, especially PM₂.₅ and O₃.

Cadmium (Cd) is a heavy metal toxicant as a common pollutant derived from many agricultural and industrial sources. The absorption of Cd takes place primarily through Cd-contaminated food and water and, to a significant extent, via inhalation of Cd-contaminated air and cigarette smoking. Epidemiological data suggest that occupational or environmental exposure to Cd increases the health risk for osteoporosis and spontaneous fracture such as itai-itai disease. However, the direct effects and underlying mechanism(s) of Cd exposure on bone damage are largely unknown. We used primary bone marrow-derived mesenchymal stromal cells (BMMSCs) and found that Cd significantly induced BMMSC cellular senescence through over-activation of NF-κB signaling pathway. Increased cell senescence was determined by production of senescence-associated secretory phenotype (SASP), cell cycle arrest and upregulation of p21/p53/p16ᴵᴺᴷ⁴ᵃ protein expression. Additionally, Cd impaired osteogenic differentiation and increased adipogenesis of BMMSCs, and significantly induced cellular senescence-associated defects such as mitochondrial dysfunction and DNA damage. Sprague-Dawley (SD) rats were chronically exposed to Cd to verify that Cd significantly increased adipocyte number, and decreased mineralization tissues of bone marrow in vivo. Interestingly, we observed that Cd exposure remarkably retarded bone repair and regeneration after operation of skull defect. Notably, pretreatment of melatonin is able to partially prevent Cd-induced some senescence-associated defects of BMMSCs including mitochondrial dysfunction and DNA damage. Although Cd activated mammalian target of rapamycin (mTOR) pathway, rapamycin only partially ameliorated Cd-induced cell apoptosis rather than cellular senescence phenotypes of BMMSCs. In addition, a selective NF-κB inhibitor moderately alleviated Cd-caused the senescence-related defects of the BMMSCs. The study shed light on the action and mechanism of Cd on osteoporosis and bone ageing, and may provide a novel option to ameliorate the harmful effects of Cd exposure.

Japan receives nitrogenous air pollutants via long-range transport from China. However, emissions of nitrogenous air pollutants in China have stabilized or decreased in recent years. This study examined both the long-term trends in atmospheric nitrogen (N) deposition from the 1990s to the 2010s and the response of stream water nitrate (NO₃⁻) leaching from forested areas in western Japan. A long-term (1992–2018) temporal analysis of atmospheric N deposition in Fukuoka (western Japan) was conducted. Atmospheric bulk N deposition was collected at forested sites in a suburban forest (Swₑₛₜ) and a rural forest (Rwₑₛₜ) in western Japan during 2009–2018. Stream water samples were also collected from four locations at sites Swₑₛₜ and Rwₑₛₜ during the same period. Results showed that atmospheric N deposition in Fukuoka started to decrease from the mid-2000s at an annual rate of −2.5% yr⁻¹. The decrease in atmospheric N deposition was attributable mainly to decreased atmospheric ammonium (NH₄⁺) deposition, which caused greater contribution of NO₃⁻ deposition to atmospheric N deposition. Concentrations of NO₃⁻ in the stream water samples from three of the four locations decreased significantly at an annual rate of −3.7 to −0.7% yr⁻¹. However, stream water NO₃⁻ concentrations increased in one watershed where understory vegetation has been deteriorating owing to the increased deer population. This might weaken the recovery of N leaching from forested areas.

It is widely recognized that green infrastructures in urban ecosystems provides important ecosystem services, including air purification. The potential absorption of nitrogen oxides (NOₓ) by urban trees has not been fully quantified, although it is important for air pollution mitigation and the well-being of urban residents. In this study, four common tree species (Sophora japonica L., Fraxinus chinensis Roxb., Populus tomentosa Carrière, Sabina chinensis (L.)) in Beijing, China, were studied. The dual stable isotopes (¹⁵N and ¹⁸O) and a Bayesian isotope mixing model were applied to estimate the sources contributions of potential nitrogen sources to the roadside trees based on leaf and soil sampling in urban regions. The following order of sources contributions was determined: soil > dry deposition > traffic-related NOₓ. The capacity of urban trees for NOₓ removal in the city was estimated using a remote sensing and GIS approach, and the removal capacity was found to range from 0.79 to 1.11 g m⁻² a⁻¹ across administrative regions, indicating that 1304 tons of NOₓ could be potentially removed by urban trees in 2019. Our finding qualified the potential NOₓ removal by urban trees in terms of atmospheric pollution mitigation, highlighting the role of green infrastructure in air purification, which should be taken into account by stakeholders to manage green infrastructure as the basis of a nature-based approach.

The limited evidence available suggests that the interaction between chemical pollutants and biological particles may intensify respiratory diseases caused by air pollution in urban areas. Unlike air pollutants, which are routinely measured, records of biotic component are scarce. While pollen concentrations are daily surveyed in most cities, data related to airborne bacteria or fungi are not usually available. This work presents the first effort to understand atmospheric pollution integrating both biotic and abiotic agents, trying to identify relationships among the Proteobacteria, Actinobacteria and Ascomycota phyla with palynological, meteorological and air quality variables using all biological historical records available in the Madrid Greater Region. The tools employed involve statistical hypothesis contrast tests such as Kruskal-Wallis and machine learning algorithms. A cluster analysis was performed to analyse which abiotic variables were able to separate the biotic variables into groups. Significant relationships were found for temperature and relative humidity. In addition, the relative abundance of the biological phyla studied was affected by PM₁₀ and O₃ ambient concentration. Preliminary Generalized Additive Models (GAMs) to predict the biotic relative abundances based on these atmospheric variables were developed. The results (r = 0.70) were acceptable taking into account the scarcity of the available data. These models can be used as an indication of the biotic composition when no measurements are available. They are also a good starting point to continue working in the development of more accurate models and to investigate causal relationships.

The development of urbanised areas together with the growing transport infrastructure and traffic volume are the main cause of air quality deterioration due to the increasing concentrations of particulate matter. Dust pollution is a threat to human health. It can cause the development of lung, larynx or circulatory system cancer. Due to the ability to accumulate dust particles on the leaf surface, the contribution of trees in the process of phytoremediation of air pollution has started to be appreciated. An analysis of the elemental composition of particulate matter (PM) stored on the leaves surface was also carried out, which showed high average concentration of: C > O > Si > Fe (above 8wt.%). It was also observed single particles with a high concentration of heavy metals: Ti, Mn, Ba, Zn, Cr, Pb, Sn, Ni and REE (rare earth elements). The major origin of PM are vehicular emissions, soil and re-suspended road dust. This paper presents also a comparison of selected tree, shrub and vine species differing in their ability to accumulate particulate matter. It was experimentally determined the average leaf surface of individual plant species and established the amount of particulate matter with aerodynamic diameter between 10 and 100 μm, 2.5 and 10 μm, and 0.2 and 2.5 μm deposited on the leaf surface and in waxes.Some species of vines (Parthenocissus quinquefolia), shrubs (Forsythia x intermediata) and coniferous trees, such as Betula pendula ‘Youngii’, Quercus rubra, Cratageus monogyna, Acer pseduoplatanus, Tilia cordata Mill. or Platanus orientalis turned out to be the most efficient in the process of phylloremediation.

Cadmium (Cd) is a toxic metal found in tobacco, air and food. Recent cross-sectional studies have suggested that Cd negatively impacts physical performance, but the prospective association is uncertain.We used data from 2548 older adults from the Seniors-ENRICA II cohort in Madrid, Spain. Whole blood Cd levels were measured at baseline using inductively coupled plasma-mass spectrometry. At baseline (2017) and follow-up (2019), overall physical function was evaluated using the physical component summary (PCS) of the SF 12-Item Health questionnaire, lower-extremity performance with the Short Physical Performance Battery (SPPB), muscle weakness with a hand dynamometer, and frailty with a Deficit Accumulation index. Mobility limitations and disability in instrumental activities of daily living (IADL) were ascertained with standardized questionnaires. Analyses were adjusted for relevant confounders, including tobacco smoke, number of cigarettes smoked per day and time since cessation in former smokers.In cross-sectional analyses, odds ratios (95% confidence interval) per two-fold increase in blood Cd were 1.16 (1.03; 1.31) for low PCS scores, 1.08 (0.97; 1.20) for impaired lower-extremity performance, 1.10 (0.98; 1.23) for low grip strength, 1.11 (1.02; 1.20) for mobility limitations, 1.16 (1.02; 1.31) for frailty, and 1.26 (1.08; 1.47) for IADL disability. In longitudinal analyses, corresponding hazard ratios were 1.25 (1.03; 1.51) for low PCS scores, 1.14 (1.03; 1.27) for impaired lower-extremity performance, 1.02 (0.92; 1.13) for low grip strength, 1.03 (0.91; 1.16) for mobility limitations, and 1.16 (1.00; 1.35) for frailty. All the associations where consistent when current smokers were excluded from the analyses.Our results support the role of Cd as a risk factor for physical function impairments in older adults.