Suburban Soils Research Articles

SEQUENTIAL EXTRACTION OF SELECTED HEAVY METALS IN THE SOILS OF ABUJA, NIGERIA

Speciation of selected heavy metals in Abuja metropolitan soil samples was investigated using a sequential extraction analytical technique. Flame atomic absorption spectrometer was used for instrumental analysis. Metals were bound in six operational phases, in the sequential extraction method. Pb, Mn and Cd speciate more in exchangeable, As and Ni speciate more in bound to carbonate, Cu and Fe speciate more in bound to Fe-Mn oxide, Cr and Zn speciate more in organically bound while Al speciate more in residual in urban soil samples. In sub-urban samples, Pb and Cd speciate more in exchangeable and bound to Fe-Mn oxide, Cu speciate more in exchangeable, Al speciate more in bound to Fe-Mn oxide, Fe and Al speciate more in residual, Ni and As speciate more in bound to carbonate, Zn speciate more in organically bound and Cr speciate more in exchangeable and organically bound. Asokoro Forest (control) has most of the metals as non-residuals except Al and As which speciate more in residual phase. Sequence of ionic mobility in decreasing order for Abuja urban soils is as follows: Zn>Cu>Fe>Al>Mn>>As>Ni>Cr>Cd>Pb and in sub-urban soil samples is: Zn>Cu>Fe>Al>Mn>>Ni>As>Pb>Cd>Cr. From the results, it can be deduced that Zn is the ion with highest speciation. This portends danger to Abuja metropolis due to Zn phytoxicity which hinders photosynthesis in plants, thereby increasing the amount of CO2 giving rise to global warming. This requires that relevant authorities should enforce reduction of the activities that lead to abundance of Zn in Abuja soils.

Identifying the Local Influencing Factors of Arsenic Concentration in Suburban Soil: A Multiscale Geographically Weighted Regression Approach.

Exploring the local influencing factors and sources of soil arsenic (As) is crucial for reducing As pollution, protecting soil ecology, and ensuring human health. Based on geographically weighted regression (GWR), multiscale GWR (MGWR) considers the different influence ranges of explanatory variables and thus adopts an adaptative bandwidth. It is an effective model in many fields but has not been used in exploring local influencing factors and sources of As. Therefore, using 200 samples collected from the northeastern black soil zone of China, this study examined the effectiveness of MGWR, revealed the spatial non-stationary relationship between As and environmental variables, and determined the local impact factors and pollution sources of As. The results showed that 49% of the samples had arsenic content exceeding the background value, and these samples were mainly distributed in the central and southern parts of the region. MGWR outperformed GWR with the adaptative bandwidth, with a lower Moran's I of residuals and a higher R2 (0.559). The MGWR model revealed the spatially heterogeneous relationship between As and explanatory variables. Specifically, the road density and total nitrogen, clay, and silt contents were the primary or secondary influencing factors at most points. The distance from an industrial enterprise was the secondary influencing factor at only a few points. The main pollution sources of As were thus inferred as traffic and fertilizer, and industrial emissions were also included in the southern region. These findings highlight the importance of considering adaptative bandwidths for independent variables and demonstrate the effectiveness of MGWR in exploring local sources of soil pollutants.

Urbanization-driven forest soil greenhouse gas emissions: Insights from the role of soil bacteria in carbon and nitrogen cycling using a metagenomic approach

Increasing population densities and urban sprawl have induced greenhouse gas (GHG) emissions from the soil, and the soil microbiota of urban forests play a critical role in the production and consumption of GHGs, supporting green development. However, the function and potential mechanism of soil bacteria in GHG emissions from forests during urbanization processes need to be better understood. Here, we measured the fluxes of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) in Cinnamomum camphora forest soils along an urbanization gradient. 16S amplicon and metagenomic sequencing approaches were employed to examine the structure and potential functions of the soil bacterial community involved in carbon (C) and nitrogen (N) cycling. In this study, the CH4 and CO2 emissions from urban forest soils (sites U and G) were significantly greater than those from suburban soils (sites S and M). The N2O emissions in the urban center (site U) were 24.0 % (G), 13.8 % (S), and 13.5 % (M) greater than those at the other three sites. These results were related to the increasing bacterial alpha diversity, interactions, and C and N cycling gene abundances (especially those involved in denitrification) in urban forest soils. Additionally, the soil pH and metal contents (K, Ca, Mg) affected key bacterial populations (such as Methylomirabilota, Acidobacteriota, and Proteobacteria) and indicators (napA, nosZ, nrfA, nifH) involved in reducing N2O emissions. The soil heavy metal contents (Fe, Cr, Pb) were the main contributors to CH4 emissions, possibly by affecting methanogens (Desulfobacterota) and methanotrophic bacteria (Proteobacteria, Actinobacteriota, and Patescibacteria). Our study provides new insights into the benefits of conservation-minded urban planning and close-to-nature urban forest management and construction, which are conducive to mitigating GHG emissions and supporting urban sustainable development by mediating the core bacterial population.

Legacy effects of long‐term autumn leaf litter removal slow decomposition rates and reduce soil carbon in suburban yards

Societal Impact StatementAs cities grow, it is essential to understand how landscape management decisions in urban spaces alter ecosystem function. This study demonstrates that the ubiquitous practice of long‐term leaf litter removal in suburbs, even in relatively small patches of a yard, reduces the soil's ability to cycle nutrients in plant litter and results in lower amounts of carbon stored in the soil. Even two years of retaining leaves where they previously were removed is insufficient to restore decomposition rates or carbon pools. This research is an important step in creating best practices for litter management to maintain essential ecosystem functions, like carbon sequestration, water holding capacity, and soil fertility.Summary Seasonal senesced leaf litter removal eliminates considerable organic material from suburban soils annually. We test if this disturbance alters decomposition and carbon cycles and depletes soils of organic matter over time, creating persistent legacy effects. We used a factorial experimental design to implement 1–2 years of current leaf litter manipulations (remove or retain fallen leaves) within historically raked and unraked areas in suburban Maryland yards. We then compared total organic soil carbon and decomposition using a standardized substrate decomposition methodology (Tea Bag Index) across treatment plots. Long‐term litter removal in suburban yards reduced decomposition rates by 17% and total soil organic carbon concentration by up to 24% compared to areas where leaf litter was retained in situ. In contrast, short‐term management changes (1–2 years) did not significantly impact decomposition rates or total organic soil carbon concentrations. Our findings suggest that long‐term suburban litter raking creates legacy effects that alter decomposition and carbon storage process trajectories that are not easily reversed. This is important in understanding urban ecosystem function and sustainable management.

Fractal Characteristics of the Particle Size Distribution of Soil along an Urban–Suburban–Rural–Desert Gradient

In order to investigate the difference in particle size distribution of soil along an urban–suburban–rural–desert (USRD) gradient in an arid zone, surface soil (0–20 cm) samples were gathered at the urban, suburban, rural, and desert gradients in Urumqi, a northwestern Chinese city. Laser diffraction technology was adopted for determining the particle size distribution of the soil. Comparisons were made regarding the particle size distribution traits and soil properties in different gradient zones based on parameters such as the mean particle size (MG), fractal dimension (Dv), sorting coefficient (ơG), kurtosis (KG), and skewness (SKG). Results indicate that (1) particle size distribution in the urban, suburban, and rural soils was mainly sand particle sizes, whereas the desert soil was mainly composed of silt particle sizes. The average Dv value ranking for soil in each gradient is desert > suburban > urban > rural. (2) The width and peak of the soil particle size frequency curve ranged within 0–500 μm, and the width and peak of the soil particle size frequency curve of each gradient were different. (3) The MG of rural soil was the highest, whereas the MG of desert soil was the lowest. The ơG values of the surface soil of each gradient were all greater than 4.0, and the sorting performance was extremely poor. The SKG of the desert and urban soil particle size showed extremely positive and negative skewness, respectively, while the SKG of the rural and suburban soil particle size showed extremely negative skewness. The KG values of the particle sizes of the rural and suburban soils exhibited narrow and medium peaks, whereas those of the urban and desert soils exhibited very broad and flat peaks. (4) The Dv of the soil in each gradient was strongly influenced by the soil particle size distribution, with the clay content of the soil playing a dominant role. Finally, the fractal dimension was identified as an indicator of the characteristics of the fine particle matter content in the soil structure. The novel contribution of this work is to clarify the fractal differences in the particle size distribution of soil along an urbanization gradient. The present research findings can offer fundamental information relating to the characteristics of soil particle size distribution along an urbanization gradient zone.

Hidden diversity within Beauveria and Metarhizium – Comparing morphology, barcoding, multilocus phylogenies and whole-genome sequences

Accurately identifying entomopathogenic fungi is crucially important, but the current approach of analysing four genes might not provide sufficient resolution. In this study, we investigated the different resolution provided by multilocus phylogenies and approaches based on whole genome sequence data. Fungi were isolated from soil samples that were collected from five different vegetation types (dry sclerophyll forest, agricultural grassland, rainforest, suburban parkland, and sugar cane fields) and across four different suburban soil habitat types in southeast Queensland. Three different agricultural pests were used as live baits, cotton stainer bug, diamondback moth, and rust-red flour beetle. Whole-genome sequencing was conducted for all 83 isolates recovered, and the ITS2 region was extracted from the genome assemblies to make initial species identifications with the UNITE database. We also extracted tef1a 3′, tef1a 5’, rpb1 and rpb2 genes from the Metarhizium genomes and the bloc, tef1a and rpb1 genes from Beauveria genomes to construct multilocus phylogenies and obtain species identification. To investigate the genetic relationships across 14 isolates of Beauveria bassiana and (independently) across 43 isolates of Metarhizium based on whole-genome data, we genotyped single nucleotide polymorphism (SNP) markers and conducted principal components analysis on the whole-genome SNP data. The multilocus methods identified isolates to species more precisely than ITS2, except in the one unresolved clade in the Metarhizium phylogeny. The whole-genome approach identified more genetic clusters than the multilocus phylogenies identified species among the isolates, and the morphological results correlated with some of the genetic clusters, so they likely represent distinct species not detected by the other methods. The genetic clusters were not associated with vegetation type or bait insect species. This is the first comparison of the resolution of multilocus phylogenetics with that of whole-genome SNP data for these genera. We suggest how the genetic clusters identified here may be investigated further to determine whether they represent unrecognised species within these groups.

Extraction methods optimization of available heavy metals and the health risk assessment of the suburb soil in China.

Heavy metal pollution has attracted increasing concern due to its high toxicity and persistence. A suitable extraction procedure for available heavy metals in soil is necessary for assessing the ecological risk. In this work, the single extraction methods aided by shaking and microwaves were investigated and analyzed for their ability to extract available heavy metals from soil samples, and a total of 42 soil samples were collected from suburbs of Zhengzhou city in China. The extraction efficiency of Cu, Zn, As, and Cd in the certified fluvo-aquic soil was compared using eight different types of solutions: CaCl2, CH3COONH4, NH4NO3, CH3COOH, Na2EDTA, DTPA, HNO3, and NH4H2PO4. Results indicated that the shaking-assisted method that utilized Na2EDTA as an extractant demonstrated satisfactory efficiency and was chosen for further optimization and that the optimal conditions were obtained using 0.05M Na2EDTA at pH 7, soil-liquid ratio 1:20, and extraction duration 2h, which gained the perfect extraction efficiency ranging from 85.8 to 109.5%. The proposed approach has been applied to extract available Cu, Zn, As, and Cd in soils of Zhengzhou suburbs, where the mean values varied from 0.129 to 6.881mg/kg. The bioavailability of different heavy metals in the soil varies greatly, with Cd having the highest activity in the survey region. Significant (p < 0.01) positive relationships were observed between the available state and the total amount of all the heavy metals. The assessment of health risks associated with heavy metals indicated that there was no risk for chronic non-carcinogenic effects. Even though the total amount of metal elements in suburban soil of Zhengzhou is 1.6% with high carcinogenic risk, the risk of available elements is still within the acceptable range, which verified that the risk grade obtained by the total amount is higher than the actual risk.

Assessment of tropical suburban surface soils contamination from Jengka, Malaysia

Heavy metals in suburban soils pose both indirect and direct health risks. This study assessed the concentrations of Cr, Zn, Pb, and Cd in Jengka (Malaysia) suburban soil and estimated the human health risk. Health risk assessment (HRA) was utilized to assess non-cancer and cancer risks. The concentrations of heavy metals increased in the following order: Cd < Zn < Cr < Pb. The heavy metals were found to be divided into two components using principal component analysis (PCA), with PC1 comprising Pb and Cd and PC2 containing Zn and Cr. PC1 originates from anthropogenic sources, while PC2 is often from mixed anthropogenic and natural sources. Despite having the lowest mean concentration, Cd was enriched based on the geo-accumulation index (Igeo) and enrichment factor (EF). Average hazard index values were below the acceptable threshold (HI < 1) for dermal and inhalation pathways suggesting a low non-cancer risk. Jengka suburban soil had total lifetime cancer risk values slightly higher than the acceptable threshold (1 × 10−5). Skin contact was the most prominent contributing exposure pathway for both non-carcinogenic and carcinogenic risks. This study suggests that heavy metal bioactivity levels be used to make a plausible HRA of heavy metal pollution in suburban soils.

First Record of Beauveria varroae, Cordyceps blackwelliae, and Purpureocillium lavendulum from Greece and Their Pathogenicity against Thaumetopoea pityocampa

Entomopathogenic fungi (EPF) consist of a wide range of fungi that can be used as pest control agents, endophytes, and plant growth promoters. In this study of EPF in suburban soils from Achaia, Greece, we used adult beetles as baits for trapping fungal isolates. According to the macroscopic and microscopic traits of the collected isolates, three species corresponded to Beauveria varroae Vuill. (Hypocreales: Cordycipitaceae); Purpureocillium lavendulum Perdomo, Gené, Cano &amp; Guarro (Hypocreales: Ophiocordycipitaceae); and Cordyceps blackwelliae Mongkolsamrit, Noisripoom, Thanakitpipattana, Spatafora &amp; Luangsaard (Hypocreales: Claviceptaceae). Their taxonomic identity was established by ITS-rDNA sequence amplification and sequencing, molecular database comparisons, and phylogenetic analysis. The application of these new EPF species clearly demonstrated remarkable insecticidal action on Thaumetopoea pityocampa (Lepidoptera, Notodontidae) larvae, which increased with the application dose. Our findings are important based on the enhancement of the application of new EPF species as biocontrol agents within the framework of eco-friendly pest management.

VNIR estimation of heavy metals concentrations in suburban soil with multi-scale geographically weighted regression

Visible and near-infrared reflectance (VNIR) spectroscopy serves as a promising alternative to detect heavy metal contamination in suburban soils. However, the traditional regression method assumes a global rather than a non-stationary relationship between soil spectra and heavy metals. This study explored the spatially varying relationships between soil chromophores (e.g., SOM and TFe2O3) and heavy metals, and further investigated its implication for heavy metal estimation with VNIR. Specifically, we (i) explore the spatial patterns and covariation of soil chromophore and heavy metals, (ii) verify the feasibility of using multi-scale geographically weighted regression (MGWR) in the VNIR estimation of heavy metals, and (iii) investigate the potential mechanism underlying the models. Specifically, continuum removal and derivation were used to preprocess the reflectance spectra, and then a random frog algorithm was performed to select candidate feature wavelengths, followed by the removal of wavelengths with a correlation higher than 0.80 to avoid collinearity. Standard errors were calculated to further eliminate the variables with a high variance of coefficients. The remaining wavelengths were retained as inputs of the estimation models. The results demonstrated that MGWR outperformed its competitors, resulting in an increase in the coefficient of determination and a decrease in the residual sum of squares. Our study revealed the spatial heterogeneities of the relationships between heavy metals concentrations and soil spectra, and found that the spatial correlation between heavy metals and TFe2O3 (p < 0.01) was the main reason that Cr and Ni can be estimated by using VNIR. The MGWR method not only improves the capability of VNIR in the estimation of heavy metal concentrations, but promotes our understanding of the estimation mechanism.

Contamination level, sources, and health risk of polycyclic aromatic hydrocarbons in suburban vegetable field soils of Changchun, Northeast China

Polycyclic aromatic hydrocarbons (PAHs) are a class of persistent organic pollutants. With the expansion of the city, the suburban environment is being increasingly polluted by PAHs, which pose a huge potential risk for suburban agriculture. Therefore, we conducted a survey focusing on the pollution level, sources, and risk of PAHs in Changchun suburban vegetable soils, Northeast China. The total concentrations of 16 PAHs (Σ16PAHs) in soils were between 2338.2 and 15,200 ng g−1 (mean 6778.1 ng g−1), which were significantly higher than those in most other cities. High molecular weight PAHs were the major components, which occupied over 85.63% of all PAHs. Seven potential carcinogenic PAHs accounted for 56.96% of the Σ16PAHs. Source apportionment results based on the ratio of PAH isomers and principal components analysis showed that PAHs were primarily derived from pyrolysis sources, such as biomass/coal combustion, traffic emissions, and petroleum. Ecological risk values of PAHs were between effects range-low (ERL) and effects range-median (ERM), which might cause occasionally ecological risks in the suburbs. According to the incremental lifetime cancer risk assessment results, the health risks to the exposed population were in the acceptable level, with dermal contact and ingestion being the predominant exposure pathway.

Source identification and toxicity apportionment of polycyclic aromatic hydrocarbons in surface soils in Beijing and Tianjin using a PMF-TEQ method.

Beijing and Tianjin are two of the largest cities in northern China with high population densities and highly developed manufacturing industries. In the past decade, some authors have reported their PAH concentrations in surface soils, identified their sources and quantitatively reported their health risks. However, the contributions of different PAH sources to their toxicity have not been reported thus far. In this study, we reviewed the PAH concentrations, contributions of different sources to the toxicity, and cancer risks in soils from different land use types found within Beijing and Tianjin from data gathered by 41 studies. The total PAH concentration varied in the range of 175.7–1989.0 ng g-1 with a higher median PAH concentration detected in urban soils (789.7 ng g-1), followed by suburban soils (647.3 ng g-1) and rural soils (390.8 ng g-1). Source identification using diagnostic ratios and principal component analysis (PCA) suggested that the PAHs in all three land use types mainly originated from biomass and coal combustion, vehicular emissions, and petrogenic processes with contributions varying from 13% to 62%. Furthermore, results from a positive matrix factorization (PMF) model suggested that vehicular emissions and coal combustion in urban soils, and the vehicular emissions, coal combustion and biomass combustion in suburban and rural soils dominated the total PAH concentrations (>85%). These results were consistent with those of the PCA model. Results of the additional toxicity apportionment performed using the PMF model suggested that vehicular emissions and coal combustion contributed the most to the toxic equivalent quantity for Benzo(a)Pyrene (BaPTEQ) and, by extension, to the carcinogenic potencies. The incremental lifetime cancer risk (ILCR) values suggested a low risk level for adults exposed to PAHs in the different land use types found within Beijing and Tianjin.

Source analysis and source-oriented risk assessment of heavy metal pollution in agricultural soils of different cultivated land qualities

Heavy metal pollution in soil has received much attention in recent decades. Many studies have analyzed the contamination status, spatial distribution, and pollution sources of heavy metals. Little information is available on the interaction between cultivated land quality and soil heavy metal pollution. Combining soil quality information and intensive heavy metal sampling surveys, this study analyzed heavy metal contamination and the ecological and health risks of various soils with different quality levels. Additionally, through the PMF model and risk assessment techniques, the ecological and health risks of specific pollution sources and their interaction with soil quality were investigated. The results showed that the mean content of the studied elements followed the increasing order of Hg (0.12 mg/kg) < Cd (0.19 mg/kg) < As (6.98 mg/kg) < Pb (25.57 mg/kg) < Cr (72.02 mg/kg). In addition, with increasing soil quality, the concentrations of Pb, Cr and Hg as well as the overall ecological risk increased significantly. Regarding health risks, heavy metal pollution posed a higher risk to children than adults, and ingestion was the main exposure pathway. The total hazard index and carcinogenic risk also increased with increasing soil quality. The PMF analysis showed that Pb and Cr mainly came from industrial activities, As could be attributed to natural sources, Cd was mainly derived from agricultural activities, and Hg pollution was determined by coal combustion. Considering the risks of specific pollution sources, agricultural activities and coal combustion were the major reasons for high ecological risks, whereas industrial activities and coal combustion posed significantly higher risks in suburban high-quality soil. Industrial activities mainly determined the health risk, which contributed more than 50% to the total risk. There was an upward health risk trend with increasing soil quality. Industrial activities in high-quality suburban soil posed the highest health risk to both adults and children. Reasonable and effective policies should be formulated to control industrial pollution and improve the ecological environment in this area.

Prediction of bioaccessible lead in urban and suburban soils with Vis-NIR diffuse reflectance spectroscopy

The successful use of visible and near-infrared (Vis-NIR) reflectance spectroscopy analysis requires selecting an optimal procedure of data acquisition and an accurate modeling approach. In this study, Vis-NIR with 350–2500 nm wavelengths were applied to detect different forms of lead (Pb) through the spectrally active soil constituents combining principal component regression (PCR) and Partial least-square regression (PLSR) for the Vis-NIR model calibration. Three clouds with different soil spectral properties were divided by the Linear discriminant analysis (LDA) in categories of Pb contamination risks: “low,” “health,” “ecological,” ranging from 200 to 750 mg kg−1. Farm soils were used for calibration (n = 26), and more polluted garden soils (n = 36) from New York City were used for validation. Total and bioaccessible Pb concentrations were examined with PLSR models and compared with Support Vector Machine (SVM) Regression and Boosting Regression Tree (BRT) models. Performances of all models' predictions were qualitatively evaluated by the Root Mean Square Error (RMSE), Residual Prediction Deviation (RPD), and coefficient of determination (R2). For total Pb, the best predictive models were obtained with BRT (R2 = 0.82 and RMSE 341.80 mg kg−1) followed by SVM (validation, R2 = 0.77 and RMSE 337.96 mg kg−1), and lastly by PLSR (validation, R2 = 0.74 and RMSE 499.04 mg kg−1). The PLSR technique is the most accurate calibration model for bioaccessible Pb with an R2 value of 0.91 and RMSE of 68.27 mg kg−1. The regression analysis indicated that bioaccessible Pb is strongly influenced by organic content, and to a lesser extent, by Fe concentrations. Although PLSR obtained lower accuracy, the model selected many characteristic bands and, thus, provided accurate approach for Pb pollution monitoring.

Yeast complexes of urbanozems of some southern cities of Russia (Krasnodar, Maykop, Simferopol, Sochi)

Yeasts number and diversity in urban soils of Krasnodar, Maykop, Simferopol, and Sochi was investigated. The soils of botanical gardens and suburbans were studied as a control. Maximum number was found in the topsoil 0-20 cm in the urban soils of Sochi and Simferopol, where it was 5.7 ± 0.2 and 5.4 ± 0.01 lg(CFU/g), respectively. The minimum number, 2.0 ± 0.1 lg(CFU/g), was characteristic of a 60-80-cm layer in the suburban soils in all cities. The number of yeasts was shown to depend primarily on the depth and type of soil and to a lesser extent on location. A total of 20 yeast species were isolated. In the soils of the major tourist cities of Sochi and Simferopol, a high relative abundance of Candida sake and Meyerozyma guilliermondii was found, which fundamentally distinguished the studied soils from the ones of Krasnodar and Maykop. The cities of Sochi and Simferopol are characterized by a higher anthropogenic load compared to Krasnodar and Maykop, which is associated not only with their high population, but also with a significant tourist load. Detection in urban soils of C. sake and M. guilliermondii which are clinically significant species, was therefore consequential.

Diagnosis of cadmium contamination in urban and suburban soils using visible-to-near-infrared spectroscopy

Previous studies have mostly focused on using visible-to-near-infrared spectral technique to quantitatively estimate soil cadmium (Cd) content, whereas little attention has been paid to identifying soil Cd contamination from a perspective of spectral classification. Here, we developed a framework to compare the potential of two spectral transformations (i.e., raw reflectance and continuum removal [CR]), three optimization strategies (i.e., full-spectrum, Boruta feature selection, and synthetic minority over-sampling technique [SMOTE]), and three classification algorithms (i.e., partial least squares discriminant analysis, random forest [RF], and support vector machine) for diagnosing soil Cd contamination. A total of 536 soil samples were collected from urban and suburban areas located in Wuhan City, China. Specifically, Boruta and SMOTE strategies were aimed at selecting the most informative predictors and obtaining balanced training datasets, respectively. Results indicated that soils contaminated by Cd induced decrease in spectral reflectance magnitude. Classification models developed after Boruta and SMOTE strategies out-performed to those from full-spectrum. A diagnose model combining CR preprocessing, SMOTE strategy, and RF algorithm achieved the highest validation accuracy for soil Cd (Kappa = 0.74). This study provides a theoretical reference for rapid identification of and monitoring of soil Cd contamination in urban and suburban areas.

A questionnaire based probabilistic risk assessment (PRA) of heavy metals in urban and suburban soils under different land uses and receptor populations

The choice of receptor populations is crucial for assessing the health risk posed by heavy metals in soil. A total of 457 questionnaires were conducted on 10 sensitive receptor populations, which were exposed to potentially contaminated soil under four land uses, to determine their exposure frequency (EF) and exposure time (ET) values. The exposure risk (ER: the probability of being exposed to target soil) varied between the receptor populations because of their different EF and ET values. Green maintenance workers in park soil, who had fixed outdoor working hours (6 or 7 days per week and 8 h per day), had the highest EF and ET values, while adults and children who visited parks only at weekends had the lowest EF values. Green maintenance workers, sanitation workers, and children faced the highest hazards (i.e., hazard index (HI) values) from heavy metals in soil in parks and residential areas, roadsides, and farmland, and were found to be the most sensitive receptor populations (MSRPs) for these land uses. The 90th percentile of the HI value for the four land uses based on MSRPs followed the order of roadsides (0.48) > parks (0.44) > residential areas (0.21) > suburban farmlands(0.18), and all were lower than 1, indicating a virtually safe level. Washing hands immediately and wearing shoes when working on farmland considerably reduced the HI values by 56.6%. The EF, ET, and body weight (BW) values were the most sensitive parameters in the health risk assessment. The results suggested that the type of receptor population will greatly affect the results of a health risk assessment for soil pollutants. It is necessary to select the risk receptors carefully based on the land use types.

Impact of human disturbances on soil cyanobacteria diversity and distribution in suburban arid area of Marrakesh, Morocco

BackgroundCyanobacteria are among the first photoautotrophic component of soil microorganism communities which play a key ecological role in nutrient cycles and soil productivity. However, the sustainability of these soil biodiversity ecosystem services is increasingly compromised, especially in urban and peri-urban areas where soils are heavily exploited and used for a wide range of human activities. The aim of this study is to assess the impact of different types of human disturbances on cyanobacteria diversity and distribution in suburban soils of Marrakesh. Soil and cyanobacteria sampling were carried out during two campaigns at six sites located along an anthropogenic gradient from the least urbanized suburbs of Marrakesh to the highly anthropized suburban area. In the laboratory, soil physicochemical characteristics were measured. The morphological identification of cyanobacteria species was based both on microscopic observation and on soil cultures in solid and liquid Z8 media.ResultsThe results showed a total of 25 cyanobacteria taxa belonging to ten genera, four families, and two orders (Oscillatoriales 88% and Chroococcales 12% of taxa). Among the taxa identified, seven strains were isolated in soil culture in nutrient media and purified in monoalgal culture. The highest cyanobacterial diversity was recorded in irrigated soil with treated wastewater compared to the non-cultivated control soil. In Principal Component and Cluster Analysis, suburban soils were subdivided into three groups depending on the chemical properties and cyanobacteria composition. Cyanobacteria diversity was significantly associated with the soil moisture, total organic carbon (TOC), PO4-P, NO3-N, and NH4-N contents.ConclusionsWhile diversity and microalgal biomass were significantly lower in the soils affected by municipal and mining solid wastes, the input of organic matter and nutrients from treated wastewater appears to be beneficial for the increasing of the biodiversity of soil cyanobacteria. This survey provides a first inventory of the soil cyanobacterial communities and shows their spatial variability and high sensitivity to the land-use practices and anthropogenic disturbances on urban soil in Moroccan drylands.

Urbanization reduces overall cyanobacterial abundance but favors heterocystous forms

Managing agricultural land, both in terms of quantity and quality, is one of the major challenges of the world. Urbanization is a powerful human-induced land use transformation that not only affects adversely the availability of arable lands, but also the soil microbial diversity crucial for maintaining fertility and other soil functions. The study reports the change in cyanobacterial diversity and community composition along a rural-urban gradient, through amplicon sequencing using Illumina MiSeq approach. Urbanization significantly altered the diversity, abundance and community composition of cyanobacteria that vary along the gradient. Rural soils had the highest diversity and maximal abundance of uncultured cyanobacteria, followed by sub-urban and urban soils. In general, along the gradient Oscillatoriales (non-heterocystous forms) were the most abundant taxa, while abundance of Nostocales (i.e., heterocyst bearing N2-fixers) increased in the urban soil. The favored growth of specific taxa in urban soils indicates biotic homogenization. The relative dominance of genus Leptolyngbya in urban and sub-urban soils could be used as an indicator of urbanization.

Loss of organic carbon in suburban soil upon urbanization of Chengdu megacity, China

Urbanization is progressing rapidly. It can affect soils ecosystem services directly through land management and indirectly through changes in the socioeconomic environment, which eventually leads to an increase in emissions of greenhouse gases. Soil carbon (C) sequestration plays an important role in offsetting the anthropogenic C emissions. However, there is limited knowledge of how urbanization affects the soil C especially that in suburban. In this study, we studied changes in easily oxidizable organic C (EOC) and total organic C (TOC) of suburban soils (0–100 cm) in the rapid urbanising megacity Chengdu, China. The EOC stock and TOC stock decreased from the outer-suburb to the inner-suburb by 17.8–28.2% and 5.4–13.5%, respectively; particularly, the inner-suburb EOC decreased by 31.4–38.6% during the past 10 years. The quotient of EOC/TOC in the soil profile, reflecting the stability of soil C, declined from the outer-suburb (0.78) to the inner-suburb (0.20). Factors that influenced the EOC and TOC included the changes in economics (economic density, industrialization), farmland (cultivated area, farmland structure), urbanization (city size, population growth) and traffic flow. Among which, economic density growth was the primarily driver of the loss in TOC, explaining 31.6% of the variation in soil surface TOC and 16.0% of the variation in subsoil TOC; changes in farmland and urban expansion were the main factors contributing to the loss of subsoil EOC, with 40.4% explanatory ability. In addition, traffic flow also has contribution to the subsoil EOC loss. We concluded that the increasing soil C loss with decreasing distance from the city centre has a continuous contribution to C emission, and the C loss will persist until the suburbs are fully urbanized. The large losses of EOC and TOC caused by urbanization, and their contribution to global warming, necessitate their consideration in future appraisals of climate change and urban planning projects.