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The study aims to determine the impact of global meteorological parameters on SARS-COV-2, including population density and initiation of lockdown in twelve different countries. The daily trend of these parameters and COVID-19 variables from February 15th to April 25th, 2020, were considered. Asian countries show an increasing trend between infection rate and population density. A direct relationship between the time-lapse of the first infected case and the period of suspension of movement controls the transmissivity of COVID-19 in Asian countries. The increase in temperature has led to an increase in COVID-19 spread, while the decrease in humidity is consistent with the trend in daily deaths during the peak of the pandemic in European countries. Countries with 65°F temperature and 5 mm rainfall have a negative impact on COVID-19 spread. Lower oxygen availability in the atmosphere, fine droplets of submicron size together with infectious aerosols, and low wind speed have contributed to the increase in total cases and mortality in Germany and France. The onset of the D614G mutation and subsequent changes to D614 before March, later G614 in mid-March, and S943P, A831V, D839/Y/N/E in April were observed in Asian and European countries. The results of the correlation and factor analysis show that the COVID-19 cases and the climatic factors are significantly correlated with each other. The optimum meteorological conditions for the prevalence of G614 were identified. It was observed that the complex interaction of global meteorological factors and changes in the mutational form of CoV-2 phase I influenced the daily mortality rate along with other comorbid factors. The results of this study could help the public and policymakers to create awareness of the COVID-19 pandemic. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-021-17481-8.

Remote sensing and GIS technology were very helpful to determine an appropriate location of freshwater storage in Amhara, Ethiopia. The techniques were used to investigate the impact of lithology, surface geomorphology, slope parameters, drainage flow, drainage density, lineament density, land cover parameters on relief, and aerial and linear features and to understand their interrelationships. Morphometric parameters such as mean stream length (Lsm), stream length ratio (RL), bifurcation ratio (Rb), mean bifurcation ratio (Rbm), relief ratio (Rh), drainage density (Dd), stream frequency (Fs), drainage texture (Rt), form factor (Rf), circularity ratio (Rc), and elongation ratio (Re) were calculated. Spatial maps of morphometric parameters were produced by using AHP (analytical hierarchy process) of ArcGIS 10.3. Final priority map was generated by the overlay of those parameters with five categories of poor (16.6%), low (41.63%), moderate (29.61%), high (8.88%), and very high (3.28%) storage locations. The map showed that this study area belonged to the low to moderate storage location. The results exhibit precision-based assessment of the suitability for the dam construction sites of 6, 7, and 9 sub-basin zones. The outcome of this study strengthens the knowledge of geospatial analysis for water resources vulnerability and also allows policymakers in this drought-prone area to sustainably manage water supplies.

Evaluation of the hydrogeochemical processes governing the heavy metal distribution and the associated health risk is important in managing and protecting the health of freshwater resources. This study mainly focused on the health impacts due to the heavy metals pollution in a known Cretaceous-Tertiary (K/T) contact region (Tiruchinopoly, Tamilnadu) of peninsular India, using various pollution indices, statistical, and geochemical analyses. A total of 63 samples were collected from the hard rock aquifers and sedimentary formations during southwest monsoon and analysed for heavy metals, such as Li, Be, Al, Rb, Sr, Cs, Ba, pb, Mn, Fe, Cr, Zn, Ga, Cu, As, Ni, and Co. Ba was the dominant element that ranged from 441 to 42,638 μg/l in hard rock aquifers, whereas Zn was the major element in sedimentary formations, with concentrations that ranged from 44 to 118,281 μg/l. The concentrations of Fe, Ni, Cr, Al, Cr, and Ni fell above the permissible limit in both of the formations. However, the calculated heavy metal evaluation index (HEI), heavy metal pollution index (HPI), and the degree of contamination (Cd) parameters were higher in the sedimentary formation along the contact zone of the K/T boundary. Excessive health risks from consumption of contaminated groundwater were mostly confined to populations in the northern and southwestern regions of the study area. Carcinogenic risk assessment suggests that there are elevated risks of cancer due to prolonged consumption of untreated groundwater. Ba, Sr, and Zn were found to be geochemically highly mobile due to the partitioning between the rock matrix and groundwater, aided by the formation of soluble carbonato-complexes. Factor analysis indicates that the metals are mainly derived from the host rocks and anthropogenic inputs are relatively insignificant. Overall, this study indicated that groundwater in K/T contact zones is vulnerable to contamination because of the favorable geochemical factors. Long-term monitoring of such contact zones is required to avert the potential health hazards associated with consumption of the contaminated groundwater.

Sediment core samples have been collected from the Karankadu mangrove areas in Tamil Nadu, India. To know the distribution, characteristics and source identification of the heavy metals Cd, Mn, Fe, Cu, Pb, Zn, and Ni were investigated and analyzed by atomic absorption spectrometer (AAS). From the observed results, the sediment textural characteristics silty sand, sandy silt, sand, and silt with sand were noted. The metal concentrations distributed in the following order of decreasing: Fe > Mn > Zn > Cu > Ni > Pb > Cd. The analysis shows that these metals have a much higher concentration close to the coastal regions. Enrichment factor (Ef) shows that Cd and Zn were moderate to extremely polluted and the following order of decreasing Cd > Zn > Pb > Cu > Ni > Mn. Pollution load index (PLI) and geoaccumulation index (Igeo) reveal that most of the samples are highly polluted by heavy metals. Overall, the sediments of the Karankadu mangroves are moderate to highly polluted by Cd and Zn.

This study evaluated the status of deteriorating water quality around the Vembanad Lake of Kerala State in India. A total of 40 water samples from lake (L, n = 5), river (R, n = 6), open well (W, n = 26), and bore well (BW, n = 9) and were analysed for major ions as per the APHA methods. Different concentrations of Ca (10–190 mg/L), Mg (2–220 mg/L), Na (10–216 mg/L), K (2–50 mg/L), HCO3 (20–400 mg/L), CO3 (10–50 mg/L), Cl (46.5–950 mg/L), NO3 (0.62–19.75 mg/L), SO4 (20.8–423 mg/L) and PO4 (1.63–16.18 mg/L) represent the three different water types: Ca HCO3, Na Cl and mixed type of Ca Na HCO3. Strong connection between the host rock and groundwater quality indicated substantial water-rock interaction. Factor analysis helped to understand the associations of chemical parameters and their sources. TDS, TH, calcium, magnesium, sodium, potassium and chloride exceeded the BIS (2010) based on desirable drinking water and irrigational quality standards in SE, W, and NW directions due to man-made bunds, industrial wastes, agricultural wastes, household sewages, tourism, lime shell, and sand mining. All point and non-point sources of pollution adversely affected water in and around the Vembanad Lake system and caused by water quality deterioration.

In this study, we investigated the historical variation, source identification, and distribution of heavy metal pollution in sediments of the Pearl River Estuary (PRE) using 210Pb dating. Our results suggest that the heavy metal concentrations were higher in the western part of the estuary. For all heavy metals, Cd was significantly enriched in the sediments. The Pearl River Delta (PRD) has experienced rapid economic development in the past 40 years, a decreasing trend in heavy metal fluxes after 2004 was identified, which suggests a reduction in heavy metal concentrations due to the removal of heavy polluting industries and the effective control of sewage discharge. A binary mixing model reveals that the contributions of anthropogenic Pb ranged from 45.4 to 64%. Based on lead isotopic ratios (206/207Pb and 208/206Pb), it was found that geologic materials and industrial pollution were the main sources of heavy metals in the PRE sediments.

Heavy metals (Fe, Mn, Zn, Pb, Cu, Cr, Ni, and Cd) in core sediments from Qi’ao Island, South China were subjected to distribution determination, risk assessment, and source identification. The concentrations (in microgram per gram) of the metals decreased in the following order: Fe (27275.8 - 50893.60) > Mn (372.0 - 2063.6) > Zn (104.8 - 314.9) > Pb (44.1 - 84.8) > Cu (32.5 - 102.2) > Cr (19.6 - 467.6) > Ni (13.0 - 62.7) > Cd (1.9 - 37.8). The geoaccumulation index (I g e o ) and contamination factor ( C f ) indicated that the sediments were heavily contaminated with Cd and moderately to very highly contaminated with Cu, Cr, Ni, Pb, and Zn. Single metal risk factor (E f i ) showed that Cu, Ni, Cr, and Zn posed low risks ( 320%). In terms of risk index (RI), all study sites were considered to have a high ecological risk (RI>600). As regards pollution load index (PLI) classification, the majority of the sites were classified as “polluted” with a mean PLI of 2.8. Correlation and PCA analyses showed that the metal sources were well correlated with one another, and these sources were geogenic and industrial (agrochemicals and electroplating) wastewater discharge, as well as domestic sewage activities in the PRDE and surrounding areas. Overall, our findings showed that Qi’ao Island was moderately to highly contaminated with heavy metals.

This article documents the new precipitates formed related to acid mine drainage (AMD) at Dabaoshan mine (South China). X-ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope & Energy Spectrometer (SEM-EDS) have been used to detect minerals in AMD impoundment and downstream creeks. The occurrences, the mineralogical species and the micro-morphological characteristics of secondary minerals from different pH conditions has been carried out. Iron- hydroxysulfates and iron-oxyhydroxides are the main secondary minerals, and they occurred as both poorly and well-crystalline minerals. Jarosite nearly predominate as pseudocubic crystals at pH 2.5–4.0. Schwertmannite-rich sediments occurred at pH 3.82–4.5 as urchin-like, pin-cushion and as well as globular-like aggregates and show high concentrations of Mn, Cu, Pb and As due to adsorption and co-precipitation. Goethite formed mainly as botryoidal and flaky assemblages. Paragenesis of different types of schwertmannite indicate that pH condition is not the dominant factor controlling morphology but the main parameter for the variation of minerals species. Statistical analysis reveal obvious changing tendency in Zn, Cd and SO4 within pH. FTIR analysis show adsorption of Cu, Pb, Zn and As on secondary iron minerals. Water elements with high concentrations in the impoundment and the obvious decrease in downstream creak reflected an accumulation and evaporation in AMD impoundment and a dilution in downstream area respectively. These results indicate that secondary minerals associated with AMD can play an important role in attenuating toxic elements.

The distribution of elements in soil is affected by various natural processes, and therefore, it is essential that exploration geochemists are able to recognize whether an elemental concentration is related to mineralization or other processes. This research aimed to recognize the elemental distribution and its controlling factors around the Zhaojikou Pb–Zn ore deposit, SE China, via fractal and compositional data analysis. Firstly, histograms over the raw data and log-ratio transformations were used to check whether the concentration data followed a normal distribution or not. The concentration distribution maps of elements were then generated via spretrum–area fractal plot to show the spatial relationships. Afterward, the inter-relationships among different elements were studied through robust principal component analysis based on compositional data theory. The factors controlling the distribution of elements were discussed and geochemical indices were proposed for future exploration. Finally, a comprehensive anomaly map was generated to show important prospecting areas. Results showed how the interpretation of distributions of elements was enhanced due to the application of data log-ratio transformation in univariate and multivariate analysis compared to the use of raw data. The histograms based on isometric log-ratio performed best among the three log-ratio transformations. The concentration distribution maps showed three anomalous areas at the surface. It clearly allowed identifying the relationships between the elements and their possible source patterns. Area I with anomalous assemblage of Pb–Zn–Ag–Cu–Cd corresponded to the current known ore deposits, while Area II with anomalous assemblage of Pb–Zn–Ag–Cu–Cd may indicate the occurrence of new potential base metal (Pb–Zn) ore bodies, and Area III with anomalous assemblage of W–As–Sb may indicate the occurrence of new potential Au mineralization/ore occurences. The robust biplot of PCA shows that the distributions of elements of interest were generally controlled by three geological processes: Pb–Zn ore-forming process, Au mineralization and weathering. Lead, Zn, Ag, Cu, and Cd, were affected mainly by Pb–Zn ore-forming processes; W, Sb, and As were affected mainly by Au mineralization, whereas Al2O3, K2O, Rb, Ba, Sr, Na2O, CaO, MgO, and SiO2 were affected to a greater extent by weathering processes. Sulphur, a mineralizing agent, was controlled by the ore-forming processes, being affected greatly by weathering. Finally, we proposed Pb > 160 ppm, Zn > 120 ppm, Ag > 193 ppb, Cu > 50 ppm, Cd > 210 ppb, W > 5 ppm, As > 25 ppm, Sb > 3.5 ppm, and S > 120 ppm as geochemical indices based on concentration-area fractal model analysis for future surficial geochemical prospecting in the Zhaojikou District.