Spatial analysis of trace elements in a moss bio-monitoring data over France by accounting for source, protocol and environmental parameters

Moss as a passive biomonitoring tool for the atmospheric deposition and spatial distribution pattern of toxic metals in an industrial city

Anthropogenic pollution impacts human and environmental health, climate change, and air quality. Karabük, an industrial area from the Black Sea Region in northern Türkiye, is vulnerable to environmental pollution, particularly soil and air. In this research on methodological aspects, we analyzed the concentrations of six potential toxic metals in the atmospheric deposition of the city using the passive method of moss biomonitoring. The ground-growing terrestrial moss, Hypnum cupressiforme Hedw., was collected during the dry season of August 2023 at 20 urban points. The concentrations of Cr, Cu, Cd, Ni, Pb, and Co were determined in mosses by the ICP-MS method. Descriptive statistical analysis was employed to evaluate the status and variance in the spatial distribution of the studied metals, and multivariate analysis, Pearson correlation, and cluster analysis were used to investigate the associations of elements and discuss the most probable sources of these elements in the study area. Cd and Co showed positive and significant inter-element correlations (r > 0.938), representing an anthropogenic association mostly present in the air particles emitted from several metal plants. The results showed substantial impacts from local industry, manufactured activity, and soil dust emissions. Steel and iron smelter plants and cement factories are the biggest emitters of trace metals in the Karabük area and the primary sources of Cr, Cd, Ni, and Co deposition.

Global ambient air quality monitoring: Can mosses help? A systematic meta-analysis of literature about passive moss biomonitoring

Surging incidents of air quality-related public health hazards, and environmental degradation, have prompted the global authorities to seek newer avenues of air quality monitoring, especially in developing economies, where the situation appears most alarming besides difficulties around 'adequate' deployment of air quality sensors. In the present narrative, we adopt a systematic review methodology (PRISMA, Preferred Reporting Items for Systematic reviews and Meta-Analyses) around recent global literature (2002-2022), around moss-based passive biomonitoring approaches which might offer the regulatory authorities a complementary means to fill 'gaps' in existing air quality records. Following the 4-phased search procedure under PRISMA, total of 123 documents were selected for review. A wealth of research demonstrates how passive biomonitoring, with strategic use of mosses, could become an invaluable regulatory (and research) tool to monitor atmospheric deposition patterns and help identifying the main drivers of air quality changes (e.g., anthropogenic and/or natural). Besides individual studies, we briefly reflect on the European Moss Survey, underway since 1990, which aptly showcases mosses as 'naturally occurring' sensors of ambient air quality for a slew of metals (heavy and trace) and persistent organic pollutants, and help assessing spatio-temporal changes therein. To that end, we urge the global research community to conduct targeted research around various pollutant uptake mechanisms by mosses (e.g., species-specific interactions, environmental conditions, land management practices). Of late, mosses have found various environmental applications as well, such as in epidemiological investigations, identification of pollutant sources and transport mechanisms, assessment of air quality in diverse and complex urban ecosystems, and even detecting short-term changes in ambient air quality (e.g., COVID-19 Lockdown), each being critical for the authorities to develop informed and strategic regulatory measures. To that end, we review current literature and highlight to the regulatory authorities how to extend moss-based observations, by integrating them with a wide range of ecological indicators to assess regional environmental vulnerability/risk due to degrading air quality. Overall, an underlying motive behind this narrative was to broaden the current regulatory outlook and purview, to bolster and diversify existing air quality monitoring initiatives, by coupling the moss-based outputs with the traditional, sensor-based datasets, and attain improved spatial representation. However, we also make a strong case of conducting more targeted research to fill in the 'gaps' in our current understanding of moss-based passive biomonitoring details, with increased case studies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10668-023-03043-0.

Spatial distribution of multi-elements in moss revealing heavy metal precipitation in London Island, Svalbard, Arctic

The Arctic is a sink for major pollutants in the Northern Hemisphere, and is an ideal place to investigate the migration of concerned metals on the local environment. In this study, 13 elements including Li, Ti, V, Cr, Mn, Fe, Co, Cu, Zn, As, Cd, Hg, and Pb were determined in mosses (Dicranum angustum) from London Island in Ny-Ålesund. The results showed that the concentrations of different elements varied greatly at different altitudes, while their distributions in low (0-200 m) and high (200-300 m) altitudes based on cluster analysis were significantly different. Among them, Li, Ti, V, Cr, Mn, Fe, Co, Cu, and As showed significant positive correlations with elevation. This result may be due to the influence of key environmental factors such as elements transported by the airborne dust carried by winds, and surface runoff from snow meltwater. Multiple receptor models (PCA, PMF, and UNMIX) were employed to discuss the sources of metals in mosses from London Island. Elements that showed positive correlation with altitude were attributed to natural sources, and Zn, Cd, Hg, and Pb, which lacked apparent correlation with elevation, were interpreted as from anthropogenic sources by the models. Among them, Zn, Cd, and Hg were from long-range deposition, while Pb was from mixed industrial sources.

Effects of urease-producing bacteria and eggshell on physiological characteristics and Cd accumulation of pakchoi (Brassica chinensis L.) plants

Soil cadmium (Cd) contamination resulting from anthropogenic activity poses severe threats to food safety and human health. In this study, a pot experiment was performed to evaluate the possibility of using urease-producing bacterium UR21 and eggshell (ES) waste for improving the physiological characteristics and reducing Cd accumulation of pakchoi (Brassica chinensis L.) plants. UR21 has siderophore and IAA production ability. The application of UR21 and ES individually or in combination could improve the root and shoot length, and fresh and dry weight of pakchoi plants under Cd stress. In Cd + ES + UR21-treated plants, the dry weight of shoot and root were increased by 61.54% and 72.73%, respectively. The chlorophyll a, chlorophyll b, and carotenoid content were increased by 52.19%, 42.95%, and 95.56% in Cd + ES + UR21-treated plants. Meanwhile, the H₂O₂ and MDA content were decreased while the SOD and POD activity were increased, and an increase of soluble protein level in pakchoi plants was observed under Cd + ES + UR21 treatment. Importantly, eggshell and UR21 alone or in combination induced a decline of Cd content in pakchoi plants, especially that Cd + ES + UR21 treatment decreased Cd content in shoot and root by 26.96% and 42.91%, respectively. Meanwhile, the soil urease and sucrase activities were enhanced. Generally, the combined application of ureolytic bacteria UR21 and eggshell exhibited better effects than applied them individually in terms of alleviating Cd toxicity in pakchoi plants. Our findings may give a unique perspective for an eco-friendly and sustainable strategy to remediate heavy metal-polluted soils.

Foliar uptake, accumulation, and distribution of cadmium in rice (Oryza sativa L.) at different stages in wet deposition conditions

Atmospheric deposition of cadmium (Cd) in rice (Oryza sativa L.) has become a major global concern. Foliar uptake allows vegetables to accumulate heavy metals from the atmosphere, but this has rarely been studied in rice. Therefore, this study investigated the Cd accumulation in rice growing at different exposure periods (the tillering, booting, heading, and maturity stages) under a wet deposition of CdCl₂·2.5H₂O solution through pot experiments. The Cd concentrations in leaves, roots, husk, brown rice, and leaf structures were analyzed to explore foliar uptake, accumulation, and distribution of Cd in rice tissues at different growth stages. The results showed that wet deposited Cd can be absorbed on the rice leaf surface and remains on the leaves for a long time. The sequence of Cd accumulation in rice tissues was: leaves > brown rice > husk > roots, with leaves accounting for greater than 71.78% of the total accumulation. The accumulation of wet deposited Cd in leaves, husk, and brown rice had large temporal variations between the four typical stages. There was no significant variations in Cd content in roots between different growth stages. Correspondingly, the foliar uptake of Cd was rarely transported from the leaves via the phloem to roots. Conversely, the foliar uptake of Cd was transported upwards to grains. The accumulation of Cd fluctuated with each growth stage, initially increasing and then decreasing at the heading stage and finally reaching a peak at the maturity stage. The highest total accumulation of Cd in both the high and low wet deposition conditions occurred at maturity, resulting in 15.53 and 11.23 μg plant^-1, respectively. These results provide theoretical support for further research into identifying efficient foliar control measures to reduce Cd accumulation and maintain food safety.

Predicting Bioaccumulation of Potentially Toxic Element in Soil–Rice Systems Using Multi-Source Data and Machine Learning Methods: A Case Study of an Industrial City in Southeast China

Potentially toxic element (PTE) pollution in farmland soils and crops is a serious cause of concern in China. To analyze the bioaccumulation characteristics of chromium (Cr), zinc (Zn), copper (Cu), and nickel (Ni) in soil-rice systems, 911 pairs of top soil (0–0.2 m) and rice samples were collected from an industrial city in Southeast China. Multiple linear regression (MLR), support vector machines (SVM), random forest (RF), and Cubist were employed to construct models to predict the bioaccumulation coefficient (BAC) of PTEs in soil–rice systems and determine the potential dominators for PTE transfer from soil to rice grains. Cr, Cu, Zn, and Ni contents in soil of the survey region were higher than corresponding background contents in China. The mean Ni content of rice grains exceeded the national permissible limit, whereas the concentrations of Cr, Cu, and Zn were lower than their thresholds. The BAC of PTEs kept the sequence of Zn (0.219) > Cu (0.093) > Ni (0.032) > Cr (0.018). Of the four algorithms employed to estimate the bioaccumulation of Cr, Cu, Zn, and Ni in soil–rice systems, RF exhibited the best performance, with coefficient of determination (R2) ranging from 0.58 to 0.79 and root mean square error (RMSE) ranging from 0.03 to 0.04 mg kg−1. Total PTE concentration in soil, cation exchange capacity (CEC), and annual average precipitation were identified as top 3 dominators influencing PTE transfer from soil to rice grains. This study confirmed the feasibility and advantages of machine learning methods especially RF for estimating PTE accumulation in soil–rice systems, when compared with traditional statistical methods, such as MLR. Our study provides new tools for analyzing the transfer of PTEs from soil to rice, and can help decision-makers in developing more efficient policies for regulating PTE pollution in soil and crops, and reducing the corresponding health risks.

Heavy metal(loid)s contamination and health risk assessment of soil-rice system in rural and peri-urban areas of lower brahmaputra valley, northeast India

The soil-rice system in rural and peri-urban areas of the lower Brahmaputra valley, northeast India was investigated for heavy metal(loid)s using Nemerow's pollution index (PI_N) and potential ecological risk index (RI). Potential health risk due to rice consumption grown in the region was assessed in terms of carcinogenic and non-carcinogenic risks. Around 95% of the soil showed acidic nature that ranged from weakly acidic to strongly acidic soil. In terms of PI_N, 27.3% of the sampling sites were heavily polluted (PI_N≥3), 34.8% moderately, and 37.9% were slightly polluted. The Pb concentration was comparably higher in 57.1% of the rice grain samples and the mean As level (0.17 mg kg^-1) was close to the WHO limit. The non-carcinogenic risk in terms of hazard quotient (HQ) was high primarily due to As (HQ > 1), whereas other metals had limited contribution (HQ < 1). The carcinogenic risk based on total cancer risk (TCR) values for adults and children ranged between 0.0039 - 0.019 and 0.0043-0.0211, respectively, exceeding the maximum acceptable level of 1 × 10^-4. Among the rice varieties, for non-carcinogenic risks, the maximum hazard index (HI) was noticed for Bahadur and the minimum for Ranjit. Whereas for carcinogenic risks, the maximum TCR was observed for Mahsuri and the minimum for Moynagiri.

Heavy metals in different moss species in alpine ecosystems of Mountain Gongga, China: Geochemical characteristics and controlling factors

Terrestrial mosses are promising tracers for research concerning metal atmospheric deposition and pollution. Concentrations of Cr, Co, Ni, Zn, Sr, Cd, Ba, and Pb in different moss species from Mountain Gongga, China were analyzed to investigate the effects of growth substrates, geographic elevation, and type of moss species on the accumulation characteristics of heavy metals, as well as to identify heavy metal sources. The ability of heavy metals to accumulate in moss varied significantly, with low concentrations of Cd and Co; medium concentrations of Cr, Ni, and Pb; and high concentrations of Zn, Sr, and Ba. Elevation significantly influenced the accumulation characteristics of heavy metals, with high concentrations found at lower elevations due to proximal pollution. Growth substrate and moss species were found to have certain influence on the bioconcentration capacities of heavy metals in moss in this study. Correlation analysis showed similar sources for Sr, Zn, and Ba, as well as for Ni, Co, and Cr. The positive matrix factorization (PMF) model was consistent with atmospheric deposition of Pb and Cd; substrate sources of Cr, Co, and Ni; and anthropogenic sources of Ba, Sr, and Zn. This research characterized the accumulation characteristics of heavy metals and their influence factors in different mosses found in alpine ecosystems and provides a reference for future studies in similar areas.

Promotion of growth and phytoextraction of cadmium and lead in Solanum nigrum L. mediated by plant-growth-promoting rhizobacteria

Plant growth-promoting rhizobacteria (PGPR) are a specific category of microbes that improve plant growth and promote greater tolerance to metal stress through their interactions with plant roots. We evaluated the effects of phytoremediation combining the cadmium accumulator Solanum nigrum L. and two Cd- and Pb-resistant bacteria isolates. To understand the interaction between PGPR and their host plant, we conducted greenhouse experiments with inoculation treatments at Nanjing Agricultural University (Jiangsu Province, China), in June 2018. Two Cd- and Pb-resistant PGPR with various growth-promoting properties were isolated from heavy metal-contaminated soil. 16S rRNA analyses indicated that the two isolates were Bacillus genus, and they were named QX8 and QX13. Pot experiments demonstrated that inoculation may improve the rhizosphere soil environment and promote absorption of Fe and P by plants. Inoculation with QX8 and QX13 also enhanced the dry weight of shoots (1.36- and 1.7-fold, respectively) and roots (1.42- and 1.96-fold) of plants growing in Cd- and Pb-contaminated soil, and significantly increased total Cd (1.28-1.81 fold) and Pb (1.08-1.55 fold) content in aerial organs, compared to non-inoculated controls. We also detected increases of 23% and 22% in the acid phosphatase activity of rhizosphere soils inoculated with QX8 and QX13, respectively. However, we did not detect significant differences between inoculated and non-inoculated treatments in Cd and Pb concentrations in plants and available Cd and Pb content in rhizosphere soils. We demonstrated that PGPR-assisted phytoremediation is a promising technique for remediating heavy metal-contaminated soils, with the potential to enhance phytoremediation efficiency and improve soil quality.

Improved Mapping of Potentially Toxic Elements in Soil via Integration of Multiple Data Sources and Various Geostatistical Methods

Soil pollution by potentially toxic elements (PTEs) has become a core issue around the world. Knowledge of the spatial distribution of PTEs in soil is crucial for soil remediation. Portable X-ray fluorescence spectroscopy (p-XRF) provides a cost-saving alternative to the traditional laboratory analysis of soil PTEs. In this study, we collected 293 soil samples from Fuyang County in Southeast China. Subsequently, we used several geostatistical methods, such as inverse distance weighting (IDW), ordinary kriging (OK), and empirical Bayesian kriging (EBK), to estimate the spatial variability of soil PTEs measured by the laboratory and p-XRF methods. The final maps of soil PTEs were outputted by the model averaging method, which combines multiple maps previously created by IDW, OK, and EBK, using both lab and p-XRF data. The study results revealed that the mean PTE content measured by the laboratory methods was as follows: Zn (127.43 mg kg−1) > Cu (31.34 mg kg−1) > Ni (20.79 mg kg−1) > As (10.65 mg kg−1) > Cd (0.33 mg kg−1). p-XRF measurements showed a spatial prediction accuracy of soil PTEs similar to that of laboratory analysis measurements. The spatial prediction accuracy of different PTEs outputted by the model averaging method was as follows: Zn (R2 = 0.71) > Cd (R2 = 0.68) > Ni (R2 = 0.67) > Cu (R2 = 0.62) > As (R2 = 0.50). The prediction accuracy of the model averaging method for five PTEs studied herein was improved compared with that of the laboratory and p-XRF methods, which utilized individual geostatistical methods (e.g., IDW, OK, EBK). Our results proved that p-XRF was a reliable alternative to the traditional laboratory analysis methods for mapping soil PTEs. The model averaging approach improved the prediction accuracy of the soil PTE spatial distribution and reduced the time and cost of monitoring and mapping PTE soil contamination.

Current status, spatial features, health risks, and potential driving factors of soil heavy metal pollution in China at province level

In this study we systematically reviewed 1203 research papers published between 2008 and 2018 in China and recorded related data on eight kinds of soil heavy metals (Cr, Pb, Cd, Hg, As, Cu, Zn, and Ni). Based on that, the pollution levels, ecological risk and health risk caused by soil heavy metals were evaluated and the pollution hot spots and potential driving factors of different heavy metals in different provinces were also identified. Results indicated accumulation of heavy metals in soils of most provinces in China compared with background values. Consistent with previous findings, the most prevalent polluted heavy metals were Cd and Hg. Polluted regions are mainly located in central, southern and southwestern China. Hunan, Guangxi, Yunnan, and Guangdong provinces were the most polluted provinces. For the potential health risk caused by heavy metals pollution, children are more likely confront with non-carcinogenic risk than adults and seniors. And children in Hunan and Guangxi province were experiencing relatively larger non-carcinogenic risk. In addition, children in part of provinces were undergoing potentially carcinogenic risks due to soil heavy metals exposure. Furthermore, in our study the 31 provinces in mainland China were divided into six subsets according to corresponding potential driving factors for heavy metal accumulation. Our study provide more comprehensive and updated information for contributing to better soil management, soil remediation, and soil contamination control in China.

Métaux, pollution de l’air et santé

L’exposition à long terme aux particules atmosphériques a des effets bien documentés sur la santé humaine, mais le rôle des métaux reste à explorer. En France, la réglementation impose le suivi des teneurs ambiantes de certains métaux. Mais ces données, du fait d’un maillage trop large ou irrégulier, sont difficilement exploitables en épidémiologie à grande échelle. Les mousses, des végétaux capables d’accumuler les métaux atmosphériques, sont utilisées depuis plusieurs décennies en biosurveillance de la qualité de l’air. Elles fournissent des données exploitables en épidémiologie grâce auxquelles nous avons montré une association entre métaux d’origine anthropique et sur-risque de mortalité en France.

Improvement of Spatial Modeling of Cr, Pb, Cd, As and Ni in Soil Based on Portable X-ray Fluorescence (PXRF) and Geostatistics: A Case Study in East China

To verify the feasibility of portable X-ray fluorescence (PXRF) for rapidly analyzing, assessing and improving soil heavy metals mapping, 351 samples were collected from Fuyang District, Hangzhou City, in eastern China. Ordinary kriging (OK) and co-ordinary kriging (COK) combined with PXRF measurements were used to explore spatial patterns of heavy metals content in the soil. The Getis-Ord index was calculated to discern hot spots of heavy metals. Finally, multi-variable indicator kriging was conducted to obtain a map of multi-heavy metals pollution. The results indicated Cd is the primary pollution element in Fuyang, followed by As and Pb. Application of PXRF measurements as covariates in COK improved model accuracy, especially for Pb and Cd. Heavy metals pollution hot spots were mainly detected in northern Fuyang and plains along the Fuchun River in southern Fuyang because of mining, industrial and traffic activities, and irrigation with polluted water. Area with high risk of multi-heavy metals pollution mainly distributed in plain along the Fuchun River and the eastern Fuyang. These findings certified the feasibility of using PXRF as an efficient and reliable method for soil heavy metals pollution assessment and mapping, which could contribute to reduce the cost of surveys and pollution remediation.

Identifying heavy metal pollution hot spots in soil-rice systems: A case study in South of Yangtze River Delta, China

The soil-rice system in China is subjected to increasing concentrations of heavy metals (HMs) which derived from various sources. It is very critical to investigate the concentrations, spatial characteristics and hot spots of HMs content in the soil-rice system. This study presents work completed on 915 soil-rice sample pairs collected from South of Yangtze River Delta, China. These samples were evaluated for HM concentrations. Ordinary Kriging and the Getis-Ord index were used to explore spatial distributions and pollution hot spots. Averaged HMs content in soil is shown to be Zn > Cr > Pb > Cu > Ni > As > Hg > Cd, and concentrations in rice arrange as Zn > Cu > Cr > Ni > As > Cd > Pb > Hg. Compared with Chinese maximum permissible limits, mean content of all HMs in farmland soil are at safe levels and averaged content of all HMs in rice were also at safe levels except As and Ni. Ni was most polluted HM in soil Most of and showed relatively high content in farmland soil in southeastern part. As and Ni are the most polluted in rice, with highest content distributed in the northwestern and southern area, respectively. The majority of HMs pollution hot spots in soil clustered in the central area. Pollution hot spots of Ni and As in rice are mainly concentrated in the central part and southeastern part, correspondingly. Our results found a weak link between content and spatial pattern of pollution status of HMs in soil and rice. The results are anticipated to contribute to more efficient and accurate control of HMs pollution in soil-rice system, and assist decision-makers achieve a balance between cost and regulation of HM pollution.

Source Identification and Apportionment of Trace Elements in Soils in the Yangtze River Delta, China

Trace elements pollution has attracted a lot of attention worldwide. However, it is difficult to identify and apportion the sources of multiple element pollutants over large areas because of the considerable spatial complexity and variability in the distribution of trace elements in soil. In this study, we collected total of 2051 topsoil (0⁻20 cm) samples, and analyzed the general pollution status of soils from the Yangtze River Delta, Southeast China. We applied principal component analysis (PCA), a finite mixture distribution model (FMDM), and geostatistical tools to identify and quantitatively apportion the sources of seven kinds of trace elements (chromium (Cr), cadmium (Cd), mercury (Hg), copper (Cu), zinc (Zn), nickel (Ni), and arsenic (As)) in soil. The PCA results indicated that the trace elements in soil in the study area were mainly from natural, multi-pollutant and industrial sources. The FMDM also fitted three sub log-normal distributions. The results from the two models were quite similar: Cr, As, and Ni were mainly from natural sources caused by parent material weathering; Cd, Cu, and Zu were mainly from mixed sources, with a considerable portion from anthropogenic activities such as traffic pollutants, domestic garbage, and agricultural inputs, and Hg was mainly from industrial wastes and pollutants.

Heavy Metal Pollution Delineation Based on Uncertainty in a Coastal Industrial City in the Yangtze River Delta, China

Assessing heavy metal pollution and delineating pollution are the bases for evaluating pollution and determining a cost-effective remediation plan. Most existing studies are based on the spatial distribution of pollutants but ignore related uncertainty. In this study, eight heavy-metal concentrations (Cr, Pb, Cd, Hg, Zn, Cu, Ni, and Zn) were collected at 1040 sampling sites in a coastal industrial city in the Yangtze River Delta, China. The single pollution index (PI) and Nemerow integrated pollution index (NIPI) were calculated for every surface sample (0–20 cm) to assess the degree of heavy metal pollution. Ordinary kriging (OK) was used to map the spatial distribution of heavy metals content and NIPI. Then, we delineated composite heavy metal contamination based on the uncertainty produced by indicator kriging (IK). The results showed that mean values of all PIs and NIPIs were at safe levels. Heavy metals were most accumulated in the central portion of the study area. Based on IK, the spatial probability of composite heavy metal pollution was computed. The probability of composite contamination in the central core urban area was highest. A probability of 0.6 was found as the optimum probability threshold to delineate polluted areas from unpolluted areas for integrative heavy metal contamination. Results of pollution delineation based on uncertainty showed the proportion of false negative error areas was 6.34%, while the proportion of false positive error areas was 0.86%. The accuracy of the classification was 92.80%. This indicated the method we developed is a valuable tool for delineating heavy metal pollution.

Magnetic susceptibility of spider webs as a proxy of airborne metal pollution

The purpose of this pilot study was to test spider webs as a fast tool for magnetic biomonitoring of air pollution. The study involved the investigation of webs made by four types of spiders: Pholcus phalangioides (Pholcidae), Eratigena atrica and Agelena labirynthica (Agelenidae) and Linyphia triangularis (Linyphiidae). These webs were obtained from outdoor and indoor study sites. Compared to the clean reference webs, an increase was observed in the values of magnetic susceptibility in the webs sampled from both indoor and outdoor sites, which indicates contamination by anthropogenically produced pollution particles that contain ferrimagnetic iron minerals. This pilot study has demonstrated that spider webs are able to capture particulate matter in a manner that is equivalent to flora-based bioindicators applied to date (such as mosses, lichens, leaves). They also have additional advantages; for example, they can be generated in isolated clean habitats, and exposure can be monitored in indoor and outdoor locations, at any height and for any period of time. Moreover, webs are ubiquitous in an anthropogenic, heavily polluted environment, and they can be exposed throughout the year. As spider webs accumulate pollutants to which humans are exposed, they become a reliable source of information about the quality of the environment. Therefore, spider webs are recommended for magnetic biomonitoring of airborne pollution and for the assessment of the environment because they are non-destructive, low-cost, sensitive and efficient.