The COVID-19 pandemic has caused a decrease in outdoor activities, but an increase in indoor ones. This change in the intensity of land use has caused changes in pollution patterns. Urban dust contaminated with heavy metals can be a risk to the human population. Therefore, the objective of this work was to evaluate the pollution caused by heavy metals in urban dust indoors and outdoors due to changes in land use during the pandemic. Sampling was carried out by the Gomez Palacio citizens. The total number of urban dust samples was 330, 50% indoor samples and 50% outdoor sample. The elements studied were Ca, Cu, Fe, K, Mn, Ni, Pb, Rb, Sr, Ti, Y, Zn, and Zr. The heavy metals were measured through a portable XRF; the contamination factor and the load pollution index were used to assess the pollution level. The human health risk was evaluated with the USEPA methodology. Cu, Pb, and Zn presented higher concentrations indoors than outdoors, probably due to domestic factors, such as the age of the houses and the paint on the walls. Zn presented the highest pollution level among all the metals, outdoors and indoors; spatially, the sites sampled in the northwest, close to agricultural areas, presented the highest Zn pollution. Pb had a moderate pollution level in most of the samples (60%), but some samples showed a high Pb pollution. The health risk was considered within the acceptable levels for Cu, Fe, Ni, Pb, Zn. However, Mn deserves attention because the average of the samples slightly exceeded the USEPA safety limits for children. Children are at higher risk compared to adults. Indoor environments need to be better analyzed because they were shown to represent a higher risk to the population than outdoor ones due to heavy metal pollution by Zn, Cu, and Pb. The pandemic impacted land use intensity; this study reports an apparent effect of the pandemic on the amount and type of heavy metals indoors and outdoors.

Around eight million people—mainly in cities—die prematurely from pollution-related diseases; thus, studies of urban dust have become increasingly relevant over the last two decades. In this study, an assessment of heavy metal and metalloid contamination in urban dust was conducted in downtown Murcia, Spain. The objectives were to evaluate the level of contamination and the associated health risks, both with a spatially explicit focus. One hundred and twenty-eight urban dust samples were collected, each from a 1-square-meter area, using plastic tools to prevent contamination. The dust was dried and weighed, then acid-digested before analysis via inductively coupled plasma mass spectrometry. Corresponding maps were then generated using a geographic information system. The elements analyzed in the urban dust (with their median concentrations, given in mg/kg) were As (2.14), Bi (14.06), Cd (0.38), Co (1.88), Cr (71.17), Cu (142.60), Fe (13,752), Mn (316.64), Mo (3.90), Ni (21.94), Pb (106.27), Sb (6.54), Se (4.34), Sr (488.08), V (28.05), and Zn (357.33). The sequence of median concentrations for the analyzed elements was Fe > Sr > Zn > Mn > Cu > Pb > Cr > V > Ni > Bi > Sb > Se > Mo > As > Co > Cd. The pollution assessment reveals that the city is moderately polluted. Using local background levels, the elements with median values exceeding the threshold for considerable contamination were As, Cu, Pb, Sb, Se, and Zn. Using the global background level, the elements with median values exceeding the threshold for considerable contamination were Bi, Cu, Mo, Pb, Sb, Se, and Zn. The median value of the sum of the hazard index (1.82) indicates a risk to children’s health. The hazard index revealed that 43% of the sites pose a relative risk to children. In contrast to previous global studies, the present research provides a multi-scale assessment of urban pollution and health risks. Pollution is evaluated by metal, city, zone, and site, while health risks are assessed by metal, city, and site. We recommend a strategy for both local authorities and residents.

Heavy metal contamination of street dust in the city of Morelia is well‐documented; however, contamination of indoor dust remains largely unexplored, despite people spending most of their time indoors. Given the mobility restrictions during the COVID‐19 pandemic, it was necessary to engage citizens in science; a total of 480 samples (60 houses, 4 weeks, two locations: indoor and outdoor) were collected by citizens, and general information was recorded in an app developed for this research. Heavy metal concentrations were measured by x‐ray fluorescence. Contamination factor, pollution load index, and human health risk assessment were carried out. Contamination was moderate for Cu, Mn, Ni, Pb, and Zr and high for Zn. Contamination action limits were proposed based on local background values. Indoor concentrations of Cu (90 mg/kg), Pb (45 mg/kg), and Zn (731 mg/kg) were higher than outdoor concentrations, while outdoor concentrations of Fe (34217 mg/kg), Mn (838 mg/kg), and Sr (399 mg/kg) were higher than indoors. Mn, Fe, and Pb had the highest hazard indices (> 0.1) for children’s health; ailments can be expected due to Mn and Pb exposure to indoor and outdoor dust. In addition, the extreme values of Cu, Ni, and Zn were also higher than 0.1 and, therefore, these extreme values posed a risk to children’s health, both indoors and outdoors. This research was made possible through citizen science, and now, citizen participation is also essential for managing polluted dust exposure.

Making quantitative evaluations of the environmental functions of the soil in a quantitative way is an urgent necessity for transitioning towards the sustainable use of soils. The objective of this work was to use and improve the Soil and Environment software for soils of volcanic areas, for which the software was not designed to work on. The study was conducted in the volcanic area of Michoacan, Mexico. Nine soil profiles were described; samples were taken from each horizon and the physical and chemical properties of each sample were analyzed. The Soil and Environment software was used to conduct pedoecological evaluations of the soil samples and, subsequently, an evaluation of the environmental functions of the soils and the modeling of scenarios was carried out. The soil profiles studied showed variable properties of hydraulic conductivity, field capacity, air capacity, effective cation exchange capacity, and soil organic carbon. The soils showed very high nutrient retention, high naturalness and sorption of heavy metals, and low cultural and natural archive properties. The Soil and Environment software generally works well with soils of volcanic areas; however, we suggest improvements in the evaluation method of the following functions: naturalness and agricultural quality. Additionally, the estimating method of aeration capacity and hydraulic conductivity should be calibrated for the properties of the volcanic soils. The modeling of scenarios allowed us to identify the soil profiles that are most vulnerable to degradation. The modeling of scenarios provided a clear idea of the negative and positive effects that a change in soil use would have.

Particle emissions from vehicular traffic are one of the main sources of heavy metals in cities. During the COVID- 19 pandemic, mobility was reduced, which created the opportunity to measure baseline heavy metal pollution in cities. Citizens took urban dust samples at 25 sites inside and outside their homes, with four repetitions; 159 urban dust samples were analyzed. The elements analyzed with FRX equipment in triplicate were Mn, Ni, Cu, Pb, Rb, Sr, Y, Zn, K, Ca, Ti, Cr, Fe, Zr, Nb, Sn, Sb, V and Ag. The contamination factor and health risk indices were calculated, and the most contaminated sites were geographically identified. The highest average values for the contamination factor were those of copper, vanadium, and zinc. The other metals presented moderate contamination. The extreme contamination cases with values higher than CF > 6 were Cu indoors, Mn outdoors, Pb indoors, and Ni, V, and Zn in both cases. The health risk index, no danger was observed in adults and children. However, sites 2 and 6, located in the east and southeast of the city, were the most contaminated outdoors, while indoors, they were sites 1 and 20 in the southwest and west, respectively. The results of this study carried out under low mobility conditions allowed the identification of two possible background levels for heavy metals: (a) the first decile and (b) the median value of the concentrations of Cr, Cu, Fe, Mn, Ni, Pb, Sb, Sn, V and Zn, for tourist cities and industrial cities in karst areas.

Heavy metal contamination in urban street dust is often highly heterogeneous, limiting the effectiveness of conventional geostatistical mapping approaches. In Mexico City, previous studies have reported very low spatial autocorrelation for key elements, making interpolation-based methods unsuitable for representing contamination patterns. This study proposes a multiscale cartographic framework to analyze and visualize heavy metal contamination in street dust from 482 sampling sites using the contamination factor (CF) and pollution load index (PLI) at three levels of spatial analysis: (i) city-scale patterns identified through hierarchical clustering of districts based on median CF values, (ii) district-scale variability assessed through statistical comparisons of PLI distributions, and (iii) site-scale identification of contamination hotspots using observed PLI values. Results revealed five contamination clusters and significant differences in pollution load among districts (Kruskal–Wallis, p < 0.05); PLI values in Xochimilco and Tláhuac are significantly lower than in Cuauhtémoc, Gustavo A. Madero, and Magdalena Contreras. Higher contamination levels were concentrated in northern and central districts, whereas lower levels predominated in the south. Site-scale analysis identified localized hotspots associated with transportation infrastructure, industrial areas, and commercial corridors, reflecting the influence of local emission sources. The results demonstrate that contamination patterns operate simultaneously at city, district, and site scales and cannot be adequately represented through interpolation alone. The proposed framework provides a practical approach for visualizing heterogeneous contamination datasets, supporting environmental decision-making, and may apply to other metropolitan regions characterized by weak spatial autocorrelation and localized pollution processes.