Removal of fine particulate matter (PM2.5) via atmospheric humidity caused by evapotranspiration

Impact of urban tree arrangement on pedestrian exposure to the size-fractional particulate matter in a city boulevard

Trees act as natural filters that mitigate roadside air pollution. However, the filtration impact of different tree arrangements on traffic pollutants with different particle diameters has rarely been analysed in real street canyon environments. To quantify how roadside tree arrangements impact pedestrian exposure to particle number concentrations (PNCs) of different diameters (0.25-32 μm), in situ field measurements were carried out in a boulevard-type street canyon in the city of Xi'an, China. This study analysed the experimental data of PNCs collected along segments of a pedestrian lane under four typical tree arrangements: open space without trees, a sparse-spaced tree arrangement, a medium-spaced tree arrangement, and a dense-spaced tree arrangement in a street canyon. Our results reveal that the effect of tree arrangement on PNCs depended on the particle diameter. In general, trees can significantly reduce coarse PNC (particles with diameters >2.5 μm) but not the fine PNC. Quantitative analysis showed that a medium-spaced tree arrangement, in which tree crowns are adjacent to each other but do not overlap, is the most capable of reducing PNC, followed by a sparse-spaced tree arrangement, while a the dense-spaced tree arrangement has the least impact. The attenuation effect of trees on the PNCs increased with increasing particle diameter. Moreover, the presence of trees altered the local microclimate, which also affected how exposure to PNCs changed. Our empirical findings further highlight the complexity of how trees affect particulate pollutants in street canyons and provide timely insights for enhancing tree-planning management in cities from the perspective of air quality improvement.

Sansevieria trifasciata's specific metabolite improves tolerance and efficiency for particulate matter and volatile organic compound removal

Phytoremediation has become famous for removing particulate matter (PM) and volatile organic compounds (VOCs), but the ability is affected by plant health. Lately, the priming technique was a simple approach to studying improving plant tolerance against abiotic stress by specific metabolites that accumulated, known as "memory", but the mechanism underlying this mechanism and how long this "memory" was retained in the plant was a lack of study. Sansevieria trifasciata was primed for one week for PM and VOC stress to improve plant efficiency on PM and VOC. After that, the plant was recovered for two- or five-weeks, then re-exposed to the same stress with similar PM and VOC concentrations from cigarette smoke. Primed S. trifasciata showed improved removal of PMs entirely within 2 h and VOC within 24 h. The primed plant can maintain a malondialdehyde (MDA) level and retain the "memory" for two weeks. Metabolomics analysis showed that an ornithine-related compound was accumulated as a responsive metabolite under exposure to PM and VOC stress. Exogenous ornithine can maintain plant efficiency and prevent stress by increasing proline and antioxidant enzymes. This study is the first to demonstrate plant "memory" mechanisms under PM and VOC stress.

Quantitative evaluation of the impact of indoor relative humidity on deposition of aerosols generated during tooth grinding in a real-world clinical setting

OBJECTIVES

Exposure to aerosol particles generated from tooth grinding has a negative impact on the health of dental personnel. The aim of this study was to quantitatively analyze the impact of indoor relative humidity (IRH) on the deposition of these suspended particles in a well-controlled dental environment.

MATERIALS AND METHODS

In this study, a humidity control system was employed to effectively regulate and maintain indoor relative humidity (IRH). A novel computer-assisted numerical control system was developed to pre-treat the molar specimens, and accurately simulate clinical tooth grinding procedures. Each procedure was performed in triplicate, with an online real-time particle counter (ORPC; TR-8301, TongrenCo.) measuring aerosol production. All testing devices were controlled remotely. The data obtained were statistically analyzed using descriptive statistics and non-parametric tests (Kruskal-Wallis/ Dunn's post hoc test with Bonferroni correction, p < 0.05).

RESULTS

The findings showed that with increasing IRH, the maximum peak concentration of aerosol particles decreased by 397% from 6.51 × 107 particles/m3 at 30% to 1.64 × 107 particles/m3 at 80%. The Kruskal-Wallis test results indicated a statistically significant effect of IRH on the aerosol increment (p < 0.05).

CONCLUSIONS

Increasing the IRH level can effectively promote the deposition of aerosol particles, with a return to baseline within 15 min after reaching 60% or above.

CLINICAL RELEVANCE

Our study suggested that maintaining IRH above 70% during the cleaning process, allowing natural recovery to ambient humidity levels within 15 min after cleaning, and taking basic precautions, may lead to an adequate reduction in the possible health risks of aerosol contamination.

Exogenous of different elicitors: proline and ornithine on Sansevieria trifasciata under particulate matter (PM) and volatile organic compounds (VOC)

Phytoremediation has become famous for removing particulate matter (PM) and volatile organic compounds (VOC) in situ. Plants for removing PM and VOC were associated with botanical biofilters to attract pollution to the plant. On the other hand, persistent pollution exposure can lower plant health and phytoremediation effectiveness; therefore, improving plant tolerance against stress is necessary. Various elicitors can enhance plant tolerance to certain stressors. This study aims to investigate different elicitors to maintain plant health and improve the use of plants in phytoremediation for PM and VOC pollution. This experiment used Sansevieria trifasciata hort. ex Prain under PM and VOC stress. Exogenous elicitors, such as proline, ornithine, and a commercial product, were applied to the leaf parts before exposure to PM and VOC stress. The initial concentrations of PM1, PM2.5, and PM10 were 300-350, 350-450, and 400-500 µg m-3, respectively, while the VOC concentration was 2.5-3.0 mg m-3. The plant was stressed for 7 days. The result indicated that ornithine 10 mM is vital in improving plant tolerance and inducing antioxidant enzymes against PM and VOC, while proline 50 mM and a commercial product could not reduce plant stress. This study suggests that ornithine might be an important metabolite to improve plant tolerance to PM and VOC.

Study of summer microclimate and PM2.5 concentration in campus plant communities

Understanding the influencing effect of meteorological factors and air pollutants in the campus plot and the relationship between them is an important topic in the planning and design of campus green space. The changes of pollutant concentrations and meteorological factors in campus green space have certain patterns and specific influencing factors. In this study, we selected four sample plots in Nanjing Forestry University as the research objects, and collected various environmental parameters of the four plots on July 25, 2022. The results showed that the main influences of meteorological factors are the type of the underlying surface of the site, the degree of plant canopy density and the shade coverage area of the building. These factors mainly have a great influence on the value of temperature and humidity. The comprehensive influencing factors can be concluded that the cooling and humidifying effect of the site is ranked as follows: forest > lawn > asphalt road > concrete Square. The main influencing factors of pollutants are: illumination, wind speed, temperature and relative humidity. Among them, illumination and temperature have a negative correlation with PM2.5, wind speed and relative humidity have a positive correlation with PM2.5. Our research shows that the adjustment of campus green space factors can reduce the concentration of pollutants by changing the meteorological factors.

Quantitative assessment of aerosol contamination generated during tooth grinding with a speed-increasing handpiece

OBJECTIVES

Tooth grinding produces a significant amount of aerosol particles. The aim of this study was to quantitatively assess particle contamination produced from tooth grinding with a speed-increasing handpiece across a real-world clinical setting.

METHODS

All molar crowns were pretreated into cylinders with a uniform size. A novel computer-assisted numerical control system was used to parametrically study the bur speed: from 20,000 (20 K) to 200 K rpm at 20 K rpm intervals. 5-minute tooth grinding was performed in triplicate at each speed setting. Three online real-time particle counters (ORPC; TR-8301, TongrenCo.) were placed at 3 positions (0.5, 1, and 1.5 m) to evaluate particle production. All experimental instruments were controlled remotely. The data obtained were statistically analyzed using descriptive statistics and non-parametric tests (Scheirer-Ray-Hare and Kruskal-Wallis/ Dunn-Bonferroni tests, p < 0.05).

RESULTS

The concentration level of aerosol particles production during the grinding experiment was elevated above the control group for all conditions, and increased with bur speed at any location (the maximum peak, reaching 5.59 × 107 particles/m3, at 200 K and 1 m), with differences between conditions. The effect of speed on the increment of particles across different channels compared to the control group was statistically significant among locations (p < 0.001).

CONCLUSIONS

Statistically significant particle contamination was produced using a speed-increasing handpiece, but the contamination level for each experimental condition was reduced to baseline within 30 min, and most particles with a diameter greater than 1üm produced at low speeds (80 K or lower) tended to settle within 1 m.

CLINICAL RELEVANCE

Our study suggested that the use of a speed-increasing handpiece below 80 K and 30 min of fallow time may lead to an adequate reduction in the health effects of particle contamination.

Foliar particulate matter retention and toxic trace element accumulation of six roadside plant species in a subtropical city

As a major source of air pollution, particulate matter (PM) and associated toxic trace elements pose potentially serious threats to human health and environmental safety. As is known that plants can reduce air PM pollution. However, the relationship between PM of different sizes and toxic trace elements in foliar PM is still unclear. This study was performed to explore the association between PM of different sizes (PM2.5, PM10, PM>10) and toxic trace elements (As, Al, Cu, Zn, Cd, Fe, Pb) as well as the correlation among toxic trace elements of six roadside plant species (Cinnamomum camphora, Osmanthus fragrans, Magnolia grandiflora, Podocarpus macrophyllus, Loropetalum chinense var. rubrum and Pittosporum tobira) in Changsha, Hunan Province, China. Results showed that P. macrophyllus had the highest ability to retain PM, and C. camphora excelled in retaining PM2.5. The combination of P. macrophyllus and C. camphora was highly recommended to be planted in the subtropical city to effectively reduce PM. The toxic trace elements accumulated in foliar PM varied with plant species and PM size. Two-way ANOVA showed that most of the toxic trace elements were significantly influenced by plant species, PM size, and their interactions (P < 0.05). Additionally, linear regression and correlation analyses further demonstrated the homology of most toxic trace elements in foliar PM, i.e., confirming plants as predictors of PM sources as well as environmental monitoring. These findings contribute to urban air pollution control and landscape configuration optimization.

Quantitative estimation of the PM2.5 removal capacity and influencing factors of urban green infrastructure

Long-term exposure to PM_2.5 (fine particulate matter with an aerodynamic diameter <2.5 μm) could cause great harm to human health and sustainable development. It remains a challenge to estimate the long-term PM_2.5 removal capacity of nature-based green infrastructure in urban areas. In this paper, the annual PM_2.5 removal capacity of urban green infrastructure (UGI) from 2000 to 2019 in Shenyang was estimated based on the PM2.5 dry deposition model. The spatial heterogeneity of annual PM_2.5 removal capacity were detected Sen-MK test and local spatial autocorrelations analysis. Then the effects of landscape patterns and socioeconomic variables on PM_2.5 removal capacity were explored based on linear regression model. The results illustrated that the PM_2.5 removal capacity of UGI increased significantly from 2000 to 2019 in Shenyang, with the amount of PM_2.5 removal, PM_2.5 removal flux and removal rate increasing by 20.64 Mg/a, 0.0258 g/m²/a, and 0.377 %/a, respectively. The PM_2.5 removal capacity of UGI exhibited spatial heterogeneity in the study area. Specifically, the regions experiencing the increase in PM_2.5 removal capacity of UGI accounted for majority of the old urban area of Shenyang City during the study period; the lower PM_2.5 removal capacity clustered in the center urban area, in which high density impervious surfaces distributed, while the higher PM_2.5 removal capacity mainly gathered in the area with large scale green space; PM_2.5 removal capacity were significantly higher in urban functional zones with a high proportion of green spaces. The landscape metrics representing fragmentation and shape complexity positively affected the annual PM_2.5 removal flux and removal rate, while the aggregation metrics had significantly negative correlations with the PM_2.5 removal flux and removal rate. Moreover, it was also found that population density and GDP negatively affected the PM_2.5 removal capacity of UGI. This study provides a methodological reference and some new insights for future urban landscape planning and air pollution purification.

From Raising Awareness to a Behavioural Change: A Case Study of Indoor Air Quality Improvement Using IoT and COM-B Model

The topic of indoor air pollution has yet to receive the same level of attention as ambient pollution. We spend considerable time indoors, and poorer indoor air quality affects most of us, particularly people with respiratory and other health conditions. There is a pressing need for methodological case studies focusing on informing households about the causes and harms of indoor air pollution and supporting changes in behaviour around different indoor activities that cause it. The use of indoor air quality (IAQ) sensor data to support behaviour change is the focus of our research in this paper. We have conducted two studies-first, to evaluate the effectiveness of the IAQ data visualisation as a trigger for the natural reflection capability of human beings to raise awareness. This study was performed without the scaffolding of a formal behaviour change model. In the second study, we showcase how a behaviour psychology model, COM-B (Capability, Opportunity, and Motivation-Behaviour), can be operationalised as a means of digital intervention to support behaviour change. We have developed four digital interventions manifested through a digital platform. We have demonstrated that it is possible to change behaviour concerning indoor activities using the COM-B model. We have also observed a measurable change in indoor air quality. In addition, qualitative analysis has shown that the awareness level among occupants has improved due to our approach of utilising IoT sensor data with COM-B-based digital interventions.

Particulate matter resuspension from simulated urban green floors using a wind tunnel-mounted closed chamber

Background

Green areas are thought to reduce particulate matter (PM) concentrations in urban environments. Plants are the key to PM reduction via various mechanisms, although most mechanisms do not lead to the complete removal of PM. Ultimately, PM falls into the soil via wind and rainfall. However, the fallen PM can re-entrain the atmosphere, which can affect plants capacity to reduce PM. In this study, we simulated an urban green floor and measured the resuspension of PM from the surface using a new experimental system, a wind tunnel-mounted closed chamber.

Methods

The developed system is capable of quantifying the resuspension rate at the millimeter scale, which is measured by using the 1 mm node chain. This is adequate for simulating in situ green floors, including fallen branches and leaves. This addressed limitations from previous studies which focused on micrometer-scale surfaces. In this study, the surfaces consisted of three types: bare sand soil, broadleaves, and coniferous leaves. The resuspended PM was measured using a light-scattering dust detector.

Results

The resuspension rate was highest of 14.45×10^-4 s^-1 on broad-leaved surfaces and lowest on coniferous surfaces of 5.35×10^-4 s^-1 (p < 0.05) and was not proportional to the millimeter-scale surface roughness measured by the roller chain method. This might be due to the lower roughness density of the broad-leaved surface, which can cause more turbulence for PM resuspension. Moreover, the size distribution of the resuspended PM indicated that the particles tended to agglomerate at 2.5 µm after resuspension.

Conclusion

Our findings suggest that the management of fallen leaves on the urban green floor is important in controlling PM concentrations and that the coniferous floor is more effective than the broadleaved floor in reducing PM resuspension. Future studies using the new system can be expanded to derive PM management strategies by diversifying the PM types, surfaces, and atmospheric conditions.

Effect of flow structures on natural ventilation performance in office model

The recent Coronavirus Disease 2019 pandemic has highlighted the importance of indoor ventilation. In particular, ventilation is crucial in residential spaces and workspaces, where people spent most of their day. Natural ventilation is a cost-effective method for improving indoor ventilation. It can provide safe and comfortable residential and working environments without additional energy consumption. In this study, the ventilation performance was experimentally studied by measuring the concentration of ultrafine particulate matter according to the opening conditions of the windows and door of an office model in a wind tunnel. Furthermore, the internal flow structure in the office model was quantitatively analyzed through particle image velocimetry to determine the factors that affected the ventilation performance. The mean velocity inside the model and the ventilation performance increased with the opening angle of the windows. In particular, the opening condition of the door strongly affected the ventilation performance. This study is expected to provide a guideline for effectively improving the ventilation performance in indoor spaces.

Graphical abstract

Short-term effect of meteorological factors on the risk of rheumatoid arthritis hospital admissions: A distributed lag non-linear analysis in Hefei, China

Rheumatoid arthritis (RA) is an autoimmune disease, mainly characterized by erosional arthritis. The proportion of adults suffering from RA is about 0.5%-1%. There have been reports on the association of rainfall and traffic-related air pollutants with RA hospitalization rates. However, there have been no studies on the association of diurnal temperature range (DTR) and relative humidity (RH) with RA hospitalization rates. This study aimed to examine the short-term association of DTR, RH and other meteorological factors with the hospital admission rate of RA patients, while excluding the interference of PM_2.5, SO₂, NO₂, CO and O₃ atmospheric pollutants. We collected daily RA occupancy rate and meteorological factor data in Hefei city from 2015 to 2018 and used the generalized additive model (GAM) combined with the distributed lag nonlinear model (DLNM) for time series analysis, and further stratified analysis by gender and age. Single-day and cumulative-day risk estimates of RA admissions were expressed as relative risk (RR) and its 95% confidence interval (95% CI). For the cumulative-day lag model, high RH was statistically significant after cumulative lag 0-8 days, and the effect gradually increases. Stratified analysis shows that females seem to be more susceptible to high or extremely high DTR and RH exposure, and extremely high DTR exposure may increase the risk of RA admission in all populations. In conclusion, this study found that high DTR and high RH exposure increased the risk of hospitalization in RA patients and provided clues to the potential association between other meteorological factors and RA.

Effect of airflow pattern and distance on removal of particulate matters and volatile organic compounds from cigarette smoke using Sansevieria trifasciata botanical biofilter

Botanical biofilters can effectively remove indoor air pollution. However, to apply botanical biofilters in situ, the distance of botanical biofilter to the pollutants and airflow pattern can be important factors impacting efficiency. This study examined the removal efficiency of particulate matters (PMs) and volatile organic compounds (VOCs) from cigarette smoke, such as formaldehyde and acetone, at various distances (100 cm, 175 cm, 240 cm, and 315 cm) using a Sansevieria trifasciata botanical biofilter. The botanical biofilter was placed inside a testing room (24 m³) and exposed to cigarette smoke. The pollutants removal efficiency was evaluated for six cycles (24 h/cycle) and one cycle as a recovery period where botanical biofilter was placed under normal conditions for 30 days. Results showed that the botanical biofilter could remove 140-250 μg m^-3, 147-257 μg m^-3, 212-455 μg m^-3 for PM₁, PM_2.5, and PM₁₀, respectively, at 8 h. Total VOCs, formaldehyde, and acetone removal were 40%-65%, 46%-69%, and 31%-61% at 24 h. PMs and VOCs removal efficiency can be affected by both distance and pattern of airflow in the testing room. The highest PM₁ and PM_2.5 elimination appeared at 240 cm and 315 cm, while VOCs removal was high at 100 cm. Botanical biofilter creates airflow vortices around 100 cm, indicating low removal of PMs. This is the first study that demonstrated the effect of airflow patterns on different pollutants removal efficiency.

Plant-based remediation of air pollution: A review

Humans face threats from air pollutants present in both indoor and outdoor environments. The emerging role of plants in remediating the atmospheric environment is now being actively investigated as a possible solution for this problem. Foliar surfaces of plants (e.g., the leaves of cotton) can absorb a variety of airborne pollutants (e.g., formaldehyde, benzene, trimethylamine, and xylene), thereby reducing their concentrations in indoor environments. Recently, theoretical and experimental studies have been conducted to offer better insights into the interactions between plants and the surrounding air. In our research, an overview on the role of plants in reducing air pollution (often referred to as phytoremediation) is provided based on a comprehensive literature survey. The major issues for plant-based research for the reduction of air pollution in both outdoor and indoor environments are discussed in depth along with future challenges. Analysis of the existing data confirms the effectiveness of phytoremediation in terms of the absorption and purification of pollutants (e.g., by the leaves and roots of plants and trees), while being controlled by different variables (e.g., pore characteristics and planting patterns). Although most lab-scale studies have shown that plants can effectively absorb pollutants, it is important for such studies to reflect the real-world conditions, especially with the influence of human activities. Under such conditions, pollutants are to be replenished continually while the plant surface area to ambient atmosphere volume ratio vastly decreases (e.g., relative to lab-based experiments). The replication of such experimental conditions is the key challenge in this field of research. This review is expected to offer valuable insights into the innate ability of various plants in removing diverse pollutants (such as formaldehyde, benzene, and particulate matter) under different environmental settings.

Particulate Matter (PM) Adsorption and Leaf Characteristics of Ornamental Sweet Potato (Ipomoea batatas L.) Cultivars and Two Common Indoor Plants (Hedera helix L. and Epipremnum aureum Lindl. & Andre)

Particulate matter (PM) is a serious threat to human health, climate, and ecosystems. Furthermore, owing to the combined influence of indoor and outdoor particles, indoor PM can pose a greater threat than urban PM. Plants can help to reduce PM pollution by acting as biofilters. Plants with different leaf characteristics have varying capacities to capture PM. However, the PM mitigation effects of plants and their primary factors are unclear. In this study, we investigated the PM adsorption and leaf characteristics of five ornamental sweet potato (Ipomea batatas L.) cultivars and two common indoor plants (Hedera helix L. and Epipremnum aureum Lindl. & Andre) exposed to approximately 300 μg m−3 of fly ash particles to assess the factors influencing PM adsorption on leaves and to understand the effects of PM pollution on the leaf characteristics of plants. We analyzed the correlation between PM adsorption and photosynthetic rate (Pn), stomatal conductance (gs), transpiration rate (Tr), leaf area (LA), leaf width/length ratio (W/L), stomatal density (SD), and stomatal pore size (SP). A Pearson’s correlation analysis and a principal component analysis (PCA) were used to evaluate the effects of different leaf characteristics on PM adsorption. The analysis indicated that leaf gas exchange factors, such as Pn and Tr, and morphological factors, such as W/L and LA, were the primary parameters influencing PM adsorption in all cultivars and species tested. Pn, Tr, and W/L showed a positive correlation with PM accumulation, whereas LA was negatively correlated.

Screening of Particulate Matter Reduction Ability of 21 Indigenous Korean Evergreen Species for Indoor Use

The formation and pollution of particulate matter (PM), a side effect of rapid industrialization and urbanization, is considered a global issue. However, various plant species are able to effectively capture and reduce atmospheric PM concentrations. We investigated the indoor growth and morphology of 21 indigenous Korean evergreen species at low light intensities to ascertain their ability to reduce PM of aerosol particles in a closed acrylic chamber. The decrease in PM mass concentration differed significantly across species, with a significant correlation (8 h; p < 0.001). The reduction in the mass concentration of PM differed with particle size and across species. The highest reduction of PM_2.5 occurred after 8 h with Dryopteris lacera (86.8%), Ilex × wandoensis (84.9%), Machilus thunbergii (84.3%), and Rhododendron brachycarpum (84.0%). Reduction of PM₁₀ after 8 h was highest with Cephalotaxus harringtonii (98.3%), I. × wandoensis (98.5%), M. thunbergii (98.5%), and R. brachycarpum (98.3%). Plant morphological characteristics (category, plant height, leaf shape, leaf area) and relative humidity were closely related to the decrease in PM mass concentration. In conclusion, our findings can be used to identify Korean plant species that can reduce PM concentration and are suitable for indoor use.

Health-Related Benefits of Different Indoor Plant Species in a School Setting

Humans spend more than 80% of their lives indoors resulting in an increased demand for high indoor air quality (IAQ). At the same time, indoor air tends to be at least twice as polluted as outdoor air, and health threats caused by long-term exposure to indoor air pollution are rising. Few experiments under real-life conditions have demonstrated positive effects of indoor plants on parameters related to IAQ, resulting in improved humidity and temperature, reduced particulate matter concentration and CO2 levels. Indoor living walls allow the presence of many plants—without taking up valuable floor area. This article presents the results of conducted measurements on four do-it-yourself green walls planted with different plant species that are typically used for vertical indoor greenery (golden pothos, Boston fern, spider plant and a combination of plants) in a school setting. Besides the parameters of air humidity and temperature, CO2, mold spore and particulate matter levels, influences on room acoustics were investigated. Based on a custom-developed evaluation matrix, the plants were compared with each other and a reference without plants. The results show that no species led to deterioration of IAQ. Golden pothos had the most substantial effect and delivered improvements in all examined parameters.

Adsorption of nanoparticles suspended in a drop on a leaf surface of Perilla frutescens and their infiltration through stomatal pathway

Particulate matter (PM) has become a severe environmental issue, and ultrafine PM particles such as PM2.5 or PM1 can cause various complications and respiratory diseases to human beings. In particular, heavy metals contained in PM particles can contaminate edible plants; for example, plant leaves are exposed to PM particle-laden raindrops. The contaminated edible plants can injure the human health by ingestion, so a detailed understanding on the accumulation of PM particles inside edible plants is essential. In this study, we investigate the infiltration of PM particles in plant tissues with a hypothesis that ultrafine PM particles are absorbed through stomatal pathways. As an edible test plant, Perilla frutescens is selected. Drops of gold nanoparticle (AuNP) suspension are deposited on a leaf of P. frutescens to simulate the scenario where PM particle-laden raindrops fall on patulous stomata of the test plant. To examine AuNP adsorption on the P. frutescens foliar surface and diffusional AuNP absorption through stomatal apertures, we investigate three physical dynamics of AuNPs suspended in a sessile drop: sedimentation, evaporation-driven convective flow, and shrinkage of the drop interface. Quantitative information on the 3D spatial distribution of AuNPs in plant tissues was measured by X-ray imaging and two-photon excitation microscopy.

Three-dimensional volumetric monitoring of settling particulate matters on a leaf using digital in-line holographic microscopy

Plants are considered as a possible modality to reduce particulate matter (PM) particles from ambient air in an ecofriendly manner. A new precise monitoring technique that can explore interactions between individual PM particles and a leaf surface is necessary to understand the underlying mechanisms of PM removal of plant leaves. In this study, a digital in-line holographic microscopy (DIHM) was employed to experimentally investigate the settling motions of PM particles over the leaf surface. The in-plane positions and sizes of opaque PMs with irregular shapes were obtained from the projection images of numerically reconstructed holographic images. The depth positions of PMs were determined by using proper selection of an autofocusing criterion with automatic segmentation method. The edge of a hairy Perilla frutescens leaf was detected by adopting several digital imaging processing techniques. The DIHM technique was applied in this study to accurately detect 3D settling trajectories of PMs with velocity information of PMs in the midair and near leaf surface, simultaneously.

Effect of trichome structure of Tillandsia usneoides on deposition of particulate matter under flow conditions

The removal of particulate matters (PM) has emerged as one of the most significant issues in public health and environment worldwide. Environmentalists have proposed the use of indoor air-purifying plants as an eco-friendly strategy to resolve PM-related problems and effectively remove fine particulate matter (PM_2.5). Among air-purifying plants, Tillandsia usneoides (L.) L. (T. usneoides) has been used as a biomonitor for heavy metals and air pollutants. However, the PM removal effect of T. usneoides and its primary mechanism remain unclear. Here, we investigated the PM removal performance of T. usneoides in a closed chamber under flow conditions, the effects of trichomes, and the array density according to the different types of PM. The chamber with bulk T. usneoides under flow conditions exhibited 16.5 % and 9.2 % higher removal efficiency in PM_2.5T. usneoides for incense and A1 rigid PM, respectively, than that without T. usneoides. T. usneoides with trichome structure exhibited larger removal efficiencies of 7% and 2% in PM_2.5 and PM₁₀, respectively, than without trichome for incense particles. In addition, the increase in total effective surface was effective for the deposition of both PM types. The increase in effective surface area by trichome structure and array density of T. usneoides is a crucial factor for the deposition of PM.

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.

Effect of flow and humidity on indoor deposition of particulate matter

The removal of particulate matter (PM) is an important issue in public health and the global atmospheric environment. Various PM removal methods have been suggested to effectively remove PM particles. However, the effects of various factors on PM deposition are not completely clear. We quantitatively investigated the effects of flow and humidity difference in a closed chamber on PM deposition. To elucidate the parameters affecting the deposition of PM particles, PM removal efficiency and deposition constant were examined at different flow rates, flow directions, and relative humidity (RH) inside the closed system. The highest PM deposition rate was achieved under humid condition with the upward direction flow at a fan speed of RPM = 150. Mean velocity fields inside the test chamber were obtained by a particle image velocimetry (PIV) technique to quantitatively examine the effect of flow conditions on the PM deposition. The flow structure and RH inside the closed chamber have significant influence on PM deposition.

Highly accurate particulate matter detection assisted by an air heater based on a silver nanowire film

Recently, many studies have been carried out to solve the particulate matter pollution problem. However, the detection accuracy for particulate matter in the atmosphere remains unsatisfactory due to the influence of the air relative humidity. Herein, we report a Ag nanowire film air heater to enhance the detection accuracy through internal heating. From air temperature and air relative humidity relationship analysis, it has been found that the Ag nanowire film air heater can form the most suitable air relative humidity in the detection system, thereby enhancing the detection accuracy. Consequently, the Ag nanowire film air heater-assisted light scattering particulate matter detector has achieved tremendous enhancement in its detection accuracy, which is comparable with the data obtained by the beta gauge method. Film resistance plays a key role in internal air temperature distribution and the resultant air relative humidity at given voltages. To achieve the most suitable air relative humidity for continuous online monitoring, response time and power consumption should be balanced. Therefore, guidance for designing Ag nanowire films with proper resistance used in an optional-sized detector has been given for quick response, high accuracy and low power consumption. This work is of significance for providing insight for future studies in particulate matter detection and pollution remediation.

Exploring the Spatial Variation Characteristics and Influencing Factors of PM2.5 Pollution in China: Evidence from 289 Chinese Cities

Haze pollution has become an urgent environmental problem due to its impact on the environment as well as human health. PM2.5 is one of the core pollutants which cause haze pollution in China. Existing studies have rarely taken a comprehensive view of natural environmental conditions and socio-economic factors to figure out the cause and diffusion mechanism of PM2.5 pollution. This paper selected both natural environmental conditions (precipitation (PRE), wind speed (WIN), and terrain relief (TR)) and socio-economic factors (human activity intensity of land surface (HAILS), the secondary industry's proportion (SEC), and the total particulate matter emissions of motor vehicles (VE)) to analyze the effects on the spatial variation of PM2.5 concentrations. Based on the spatial panel data of 289 cities in China in 2015, we used spatial statistical methods to visually describe the spatial distribution characteristics of PM2.5 pollution; secondly, the spatial agglomeration state of PM2.5 pollution was characterized by Moran’s I; finally, several regression models were used to quantitatively analyze the correlation between PM2.5 pollution and the selected explanatory variables. Results from this paper confirm that in 2015, most cities in China suffered from severe PM2.5 pollution, and only 17.6% of the sample cities were up to standard. The spatial agglomeration characteristics of PM2.5 pollution in China were particularly significant in the Beijing–Tianjin–Hebei region. Results from the global regression models suggest that WIN exerts the most significant effects on decreasing PM2.5 concentration (p < 0.01), while VE is the most critical driver of increasing PM2.5 concentration (p < 0.01). Results from the local regression model show reliable evidence that the relation between PM2.5 concentrations and the explanatory variables varied differently over space. VE is the most critical factor that influences PM2.5 concentrations, which means controlling motor vehicle pollutant emissions is an effective measure to reduce PM2.5 pollution in Chinese cities.

Assisted Deposition of PM2.5 from Indoor Air by Ornamental Potted Plants

This study clarifies whether vegetation can promote the decrease of indoor PM2.5 concentration. The indoor PM2.5 concentration in two periods of 2013 in Wuhan city was simulated by cigarette burning in a series of sealed chambers. Six common indoor potted plants were selected as samples to investigate the effect of plants on PM2.5 decline. The effects of potted plants on PM2.5 decline were analyzed from three aspects: plant species, leaf characteristics and relative humidity. The results show that the presence of potted plants accelerated the decline of PM2.5. The additional removal rates (excluding gravity sedimentation of PM2.5 itself) for Aloe vera and Epipremnum aureum were 5.2% and 30% respectively, when the initial PM2.5 concentration was around 200 μg/m3. The corresponding values were 0% and 17.2%, respectively, when the initial PM2.5 was around 300 μg/m3. Epipremnum aureum was the optimum potted plant for PM2.5 sedimentation, due to its rough and groove leaf surface, highest LAI (leaf area index, 2.27), and strong humidifying capacity (i.e., can promote chamber humidity to 65% in 30–60 minutes.). Actual indoor studies have also confirmed that a certain amount of Epipremnum aureum can promote the decrease of indoor PM2.5. This paper provides insights on reducing the concentration of fine particulate matter by indoor greening efforts.

Primary Pollutants and Air Quality Analysis for Urban Air in China: Evidence from Shanghai

In recent years, China's urban air pollution has caused widespread concern in the academic world. As one of China's economic and financial centers and one of the most densely populated cities, Shanghai ranks among the top in China in terms of per capita energy consumption per unit area. Based on the Shanghai Energy Statistical Yearbook and Shanghai Air Pollution Statistics, we have systematically analyzed Shanghai’s atmospheric pollutants from three aspects: Primary pollutants, pollutants changing trends, and fine particulate matter. The comprehensive pollution index analysis method, the grey correlation analysis method, and the Euclid approach degree method are used to evaluate and analyze the air quality in Shanghai. The results have shown that Shanghai's primary pollutants are PM2.5 and O3, and the most serious air pollution happens during the first half of the year, particularly in the winter. This is because it is the peak period of industrial energy use, and residential heating will also lead to an increase in energy consumption. Furthermore, by studying the particulate pollutants of PM2.5 and PM10, we clearly disclosed the linear correlation between PM2.5 and PM10 concentrations in Shanghai which varies seasonally.