Crude oil pollution is a global environmental concern since it persists in the environment longer than most conventional carbon sources. In December 2014, the hyper-arid Evrona Nature Reserve, Israel, experienced large-scale contamination when crude oil spilled. The overarching goal of the study was to investigate the possible changes, caused by an accidental crude oil spill, in the leaf reflectance and biochemical composition of four natural habitat desert shrubs. The specific objectives were (1) to monitor the biochemical properties of dominant shrub species in the polluted and control areas; (2) to study the long-term consequences of the contamination; (3) to provide information that will assist in planning rehabilitation actions; and (4) to explore the feasibility of vegetation indices (VIs), along with the machine learning (ML) technique, for detecting stressed shrubs based on the full spectral range. Four measurement campaigns were conducted in 2018 and 2019. Along with the various stress indicators, field spectral measurements were performed in the range of 350–2500 nm. A regression analysis to examine the relation of leaf reflectance to biochemical contents was carried out, to reveal the relevant wavelengths in which polluted and control plants differ. Vegetation indices applied in previous studies were found to be less sensitive for indirect detection of long-term oil contamination. A novel spectral index, based on indicative spectral bands, named the “normalized blue-green stress index” (NBGSI), was established. The NBGSI distinguished significantly between shrubs located in the polluted and in the control areas. The NBGSI showed a strong linear correlation with pheophytin a. Machine learning classification algorithms obtained high overall prediction accuracy in distinguishing between shrubs located in the oil-polluted and the control sites, indicating internal component differences. The findings of this study demonstrate the efficacy of indirect and non-destructive spectral tools for detecting and monitoring oil pollution stress in shrubs.

The presence of plant leaves has been shown to lower the risks of health problems by reducing atmospheric particulate matter (PM). Leaf PM accumulation capacity will saturate in the absence of runoff. Rainfall is an effective way for PM to “wash off” into the soil and renew leaf PM accumulation. However, little is known about how PM wash-off varies with PM size and health problems caused by particulate pollution vary with PM size. This study thus used artificial rainfall with six plant species to find out how size-fractioned PM are washed off during rain processes. Total wash-off masses in fine, coarse and large fractions were 0.6–10.3 μg/cm2, 1.0–18.8 μg/cm2 and 4.5–60.1 μg/cm2 respectively. P. orientalis (cypress) and E. japonicus (evergreen broadleaved shrub) had the largest wash-off masses in each fraction during rainfall. P. cerasifera (deciduous broadleaved shrub) had the largest cumulative wash-off rates in each fraction. Rainfall intensity had more influence on wash-off masses and rates of large particles for six species and for small particles in evergreen species, but limited effect on wash-off proportions. Wash-off proportions decreased in large particles and increased in small particles along with rainfall. The results provide information for PM accumulation renewal of plants used for urban greening.

Studies focused on pollutants deposition on vegetation surfaces or aerodynamics of vegetation space conflict in whether vegetation planting can effectively reduce airborne particulate matter (PM) pollution. To achieve a more comprehensive understanding of the conflict, we conducted experiments during 2013 and 2014 in Beijing, China to evaluate the importance of vegetation species, planting configurations and wind in influencing PM concentration at urban and street scales. Results showed that wind field prevailed over the purification function by vegetation at urban scale. All six examined planting configurations reduced total suspended particle along horizontal but not vertical direction. Shrubs and trees–grass configurations performed most effectively for horizontal PM2.5 reduction, but adversely for vertical attenuation. Trapping capacity of PMs was species-specific, but species selection criteria could hardly be generalized for practical use. Therefore, design of planting configuration is practically more effective than tree species selection in attenuating the ambient PM concentrations in urban settings.

This study investigated changes in diversity of shrub-tree layer, leaf decomposition rates, nutrient release and soil NO fluxes of a Brazilian savanna (cerrado sensu stricto) under N, P and N plus P additions. Simultaneous addition of N and P affected density, dominance, richness and diversity patterns more significantly than addition of N or P separately. Leaf litter decomposition rates increased in P and NP plots but did not differ in N plots in comparison to control plots. N addition increased N mass loss, while the combined addition of N and P resulted in an immobilization of N in leaf litter. Soil NO emissions were also higher when N was applied without P. The results indicate that if the availability of P is not increased proportionally to the availability of N, the losses of N are intensified.

The effects of atmospheric pollution on plant species richness (nₛₚ) are of widespread concern. We carried out a modelling exercise to estimate how nₛₚ in British semi-natural ecosystems responded to atmospheric deposition of nitrogen (Ndₑₚ) and sulphur (Sdₑₚ) between 1800 and 2010. We derived a simple four-parameter equation relating nₛₚ to measured soil pH, and to net primary productivity (NPP), calculated with the N14CP ecosystem model. Parameters were estimated from a large data set (n = 1156) of species richness in four vegetation classes, unimproved grassland, dwarf shrub heath, peatland, and broadleaved woodland, obtained in 2007. The equation performed reasonably well in comparisons with independent observations of nₛₚ. We used the equation, in combination with modelled estimates of NPP (from N14CP) and soil pH (from the CHUM-AM hydrochemical model), to calculate changes in average nₛₚ over time at seven sites across Britain, assuming that variations in nₛₚ were due only to variations in atmospheric deposition. At two of the sites, two vegetation classes were present, making a total of nine site/vegetation combinations. In four cases, nₛₚ was affected about equally by pH and NPP, while in another four the effect of pH was dominant. The ninth site, a chalk grassland, was affected only by NPP, since soil pH was assumed constant. Our analysis suggests that the combination of increased NPP, due to fertilization by Ndₑₚ, and decreased soil pH, primarily due to Sdₑₚ, caused an average species loss of 39% (range 23–100%) between 1800 and the late 20th Century. The modelling suggests that in recent years nₛₚ has begun to increase, almost entirely due to reductions in Sdₑₚ and consequent increases in soil pH, but there are also indications of recent slight recovery from the eutrophying effects of Ndₑₚ.

Humic-like substances (HULIS) are complex mixtures that are highly associated with brown carbon (BrC) and are important components of biomass burning (BB) emissions. In this study, we investigated the light absorption, emission factors (EFs), and amounts of HULIS emitted from the simulated burning of 27 types of regionally important rainforest biomass in Southeast Asia. We observed that HULIS had a high mass absorption efficiency at 365 nm (MAE₃₆₅), with an average value of 2.6 ± 0.83 m² g⁻¹ C. HULIS emitted from BB accounted for 65% ± 13% of the amount of water-soluble organic carbon (WSOC) and 85% ± 10% of the light absorption of WSOC at 365 nm. The EFs of HULIS from BB averaged 2.3 ± 2.1 g kg⁻¹ fuel, and the burning of the four vegetation subtypes (herbaceous plants, shrubs, evergreen trees, and deciduous trees) exhibited different characteristics. The differences in EFs among the subtypes were likely due to differences in lignin content in the vegetation, the burning conditions, or other factors. The light absorption characteristics of HULIS were strongly associated with the EFs. The annual emissions (minimum–maximum) of HULIS from BB in this region in 2016 were 200–371 Gg. Furthermore, the emissions from January to April accounted for 99% of the total annual emissions of HULIS, which is likely the result of the burning activities during this season. The most significant emission regions were Cambodia, Burma, Thailand, and Laos. This study, which evaluated emissions of HULIS by simulating open BB, contributes to a better understanding of the light-absorbing properties and regional budgets of BrC in this region.

Particulate matter (PM) deposited on canopy surfaces could be washed off and carried in throughfall to the ground. This would help plants recapture airborne PM on their canopy surfaces and then develop a PM purification capacity. Sixteen commonly greening plant species in north China (including 13 arbor species and 3 shrub species) were selected to investigate the washing process of plant-deposited PM during precipitation events. We measured the PM wash-off mass in throughfall under canopies of 16 plant species and in atmospheric precipitation during 14 precipitation events through field positioning experiments in 2015, compared the seasonal changes and species differences in PM wash-off mass, and discussed the predominant factors resulting in the variation. The results showed that plant-deposited PM was largely washed off by precipitation. The average wash-off mass of total suspended particulate (TSP) in throughfall was 1.3 times higher than that in precipitation, at 18.3 ± 0.7 kg hm−2 and 7.9 ± 0.9 kg hm−2, respectively. There were significant seasonal differences in TSP wash-off mass. The value was higher in summer at 22.3 ± 1.0 kg hm−2, followed by that of winter (10.8 ± 0.6 kg hm−2) and spring (8.9 ± 1.0 kg hm−2). TSP wash-off mass in throughfall greatly varied among plant species (F = 9.542, n = 627, p < 0.001). Of the 16 selected species, Platanus acerifolia (38.0 ± 5.8 kg hm−2) showed the largest difference from that of Liriodendron chinese (8.9 ± 0.6 kg hm−2) (n = 80, p < 0.001). PM wash-off mass of different particle sizes in throughfall increased with the increase of event-based precipitation. This study enhanced the quantitative understanding of plant-deposited PM washed-off by natural precipitation among plant species and seasons. The results could provide significant guidelines for the selection and allocation of plant species to improve the PM retention capacity of urban greening plants.

Outdoor air pollution is considered as the most serious environmental problem for human health, associated with some million deaths worldwide per year. Cities have to cope with the challenges due to poor air quality impacting human health and citizen well-being. According to an analysis in the framework of this study, the annual mean concentrations of tropospheric ozone (O₃) have been increasing by on average 0.16 ppb year⁻¹ in cities across the globe over the time period 1995–2014. Green urban infrastructure can improve air quality by removing O₃. To efficiently reduce O₃ in cities, it is important to define suitable urban forest management, including proper species selection, with focus on the removal ability of O₃ and other air pollutants, biogenic emission rates, allergenic effects and maintenance requirements. This study reanalyzes the literature to i) quantify O₃ removal by urban vegetation categorized into trees/shrubs and green roofs; ii) rank 95 urban plant species based on the ability to maximize air quality and minimize disservices, and iii) provide novel insights on the management of urban green spaces to maximize urban air quality. Trees showed higher O₃ removal capacity (3.4 g m⁻² year⁻¹ on average) than green roofs (2.9 g m⁻² year⁻¹ as average removal rate), with lower installation and maintenance costs (around 10 times). To overcome present gaps and uncertainties, a novel Species-specific Air Quality Index (S-AQI) of suitability to air quality improvement is proposed for tree/shrub species. We recommend city planners to select species with an S-AQI>8, i.e. with high O₃ removal capacity, O₃-tolerant, resistant to pests and diseases, tolerant to drought and non-allergenic (e.g. Acer sp., Carpinus sp., Larix decidua, Prunus sp.). Green roofs can be used to supplement urban trees in improving air quality in cities. Urban vegetation, as a cost-effective and nature-based approach, aids in meeting clean air standards and should be taken into account by policy-makers.

In urbanized regions with expansive impervious surfaces and often low vegetation cover, air pollution due to motor vehicles and other combustion sources, is a problem. The poor air quality days in Montreal, Quebec are mainly due to fine particulate matter and ozone. Businesses using wood ovens are a source of particulates. Careful vegetation selection and increased green roof usage can improve air quality. This paper reviews different green roofs and the capability of plants in particulate matter (PM), ozone (O3) as well as nitrogen dioxide (NO2) level reductions. Both the recommended green roof category and plants to reduce these pollutants in Montreal's zone 5 hardiness region are provided. Green roofs with larger vegetation including shrubs and trees, or intensive green roofs, remove air pollutants to a greater extent and are advisable to implement on existing, retrofitted or new buildings. PM is most effectively captured by pines. The small Pinus strobus ‘Nana’, Pinus mugho var. pumilio, Pinus mugho ‘Slowmound’ and Pinus pumila ‘Dwarf Blue’ are good candidates for intensive green roofs. Drought tolerant, deciduous broadleaved trees with low biogenic volatile organic compound emissions including Japanese Maple or Acer palmatum ‘Shaina’ and ‘Mikawa-Yatsubusa’ are options to reduce O3 levels. Magnolias are tolerant to NO2 and it is important in their metabolic pathways. The small cold-tolerant Magnolia ‘Genie’ is a good option to remove NO2 in urban settings and to indirectly reduce O3 formation. Given the emissions by Montreal businesses' wood ovens, calculations performed based on their respective complex roof areas obtained via Google Earth Pro indicates 88% Pinus mugho var. pumilio roof coverage can annually remove 92.37 kg of PM10 of which 35.10 kg is PM2.5. The removal rates are 4.00 g/m2 and 1.52 g/m2 for PM10 and PM2.5, respectively. This paper provides insight to addressing air pollution through urban rooftop greening.

Perennial plant communities in the proximity of metal smelters and refineries may receive substantial inputs of base metal particulate as well as sulphate from the co-emission of sulphur dioxide. The Ni refinery at Port Colborne (Canada) operated by Inco (now Vale Canada Ltd.) emitted Ni, Co and Cu, along with sulphur dioxide, between 1918 and 1984. The objectives were to determine if vascular plant community composition, including standing litter, in twenty-one woodlots on clay or organic soil, were related to soil Ni concentration which decreased in concentration with distance from the Ni refinery. The soil Ni concentration in the clay woodlots ranged from 16 to 4130 mg Ni/kg, and in the organic woodlots, ranged from 98 to 22,700 mg Ni/kg. The concentrations of Co and Cu in the soils were also elevated, and highly correlated with soil Ni concentration. In consequence, each series of woodlots constituted a ‘fixed ratio ray’ of metal mixture exposure. For each of the woodlots, there were 16 independent measurements of ‘woodlot status’ which were correlated with elevated soil Ni concentration. Of the 32 combinations, there were eight linear correlations with soil Ni concentration, considerably more than would be expected by chance alone at a p-value of 0.05. With the exception of mean crown rating for shrubs at the clay sites, the correlations were consistent with the hypothesis that increased soil metal concentrations would be correlated with decreased diversity, plant community health or fitness, and increased accumulation of litter. Only five of the eight linear correlations were from the organic woodlots, suggesting that the observations were not confounded with soil type nor range in soil metal concentrations.