Heavy grazing reduced the spatial heterogeneity of Artemisia frigida in desert steppe.

BACKGROUND: Grazing disturbance plays an important role in the desert steppe ecosystem in Inner Mongolia, China. Previous studies found that grazing affected the spatial distribution of species in a community, and showed patchiness characteristics of species under different grazing treatments. Artemisia frigida is the dominant species and semi-shrub in desert steppe, and whether grazing interference will affect the spatial distribution of A. frigida is studied. In this study, geo-statistical methods were mainly used to study the spatial distribution characteristics of A. frigida population in desert steppe of Inner Mongolia at two scales (quadrat size 2.5 m × 2.5 m, 5 m × 5 m) and four stocking rates (control, CK, 0 sheep·ha-1·month-1; light grazing, LG, 0.15 sheep·ha-1·month-1, moderate grazing, MG, 0.30 sheep·ha-1·month-1, heavy grazing, HG, 0.45 sheep·ha-1·month-1). RESULTS: The results showed that the spatial distribution of A. frigida tended to be simplified with the increase of stocking rate, and tended to be banded with increased spatial scale. The density and height of A. frigida increased with increasing scale. With increased stocking rate, the density of A. frigida population decreased linearly, while its height decreased in a step-wise fashion. The spatial distribution of A. frigida was mainly affected by structural factors at different scales and stocking rate. The density of A. frigida was more sensitive to change in stocking rate, and the patchiness distribution of A. frigida was more obvious with increase in scale. CONCLUSIONS: Stocking rate has a strong regulatory effect on the spatial pattern of A. frigida population in the desert steppe. Heavy grazing reduced the spatial heterogeneity of A. frigida in the desert steppe. The smaller dominant populations are unfavourable for its survival in heavy grazing condition, and affects the stability and productivity of the grassland ecosystem.

A loss function to evaluate agricultural decision-making under uncertainty: a case study of soil spectroscopy.

Modern sensor technologies can provide detailed information about soil variation which allows for more precise application of fertiliser to minimise environmental harm imposed by agriculture. However, growers should lose neither income nor yield from associated uncertainties of predicted nutrient concentrations and thus one must acknowledge and account for uncertainties. A framework is presented that accounts for the uncertainty and determines the cost-benefit of data on available phosphorus (P) and potassium (K) in the soil determined from sensors. For four fields, the uncertainty associated with variation in soil P and K predicted from sensors was determined. Using published fertiliser dose-yield response curves for a horticultural crop the effect of estimation errors from sensor data on expected financial losses was quantified. The expected losses from optimal precise application were compared with the losses expected from uniform fertiliser application (equivalent to little or no knowledge on soil variation). The asymmetry of the loss function meant that underestimation of P and K generally led to greater losses than the losses from overestimation. This study shows that substantial financial gains can be obtained from sensor-based precise application of P and K fertiliser, with savings of up to £121 ha-1 for P and up to £81 ha-1 for K, with concurrent environmental benefits due to a reduction of 4-17 kg ha-1 applied P fertiliser when compared with uniform application. Supplementary Information: The online version contains supplementary material available at 10.1007/s11119-022-09887-2.

Spatial distribution of soil nutrients and evaluation of cultivated land in Xuwen county.

It is of great significance to promote the quantitative research of soil science and the implementation of precision agriculture. On this basis, taking Xuwen County as the research object, this paper comprehensively analyzed the soil characteristics of cultivated land in Xuwen County and clarify the soil nutrient content and spatial distribution characteristics of cultivated land in Xuwen County, this paper comprehensively applied the methods of geostatistics, geographic information system (GIS) and fuzzy mathematics, and referred to the cultivated land quality grade standard (GB/T 33469-2016), to analyze the soil characteristics and evaluate the soil fertility of this region. The results show that the optimal interpolation model of soil pH and available phosphorus (AP) is a Gaussian model, and the optimal interpolation model of soil organic matter (SOM), available nitrogen (AN) and available potassium (AK) is a J-Bessel model. In addition, the spatial correlation of AK is weak, whereas pH, SOM, AN and AP show moderate spatial correlation. The proportion of excellent, good, average, medium and poor comprehensive fertility index are 26.00%, 32.67%, 19.33%, 19.00% and 3.00%, respectively. The overall level of soil fertility in Xuwen County is above the average, and the fertility quality presents an obvious trend of high in the South and low in the North. Areas that above average fertility are mainly distributed in Maichen Town, Qujie Town, Nanshan Town and Chengbei Town. The results can provide theoretical basis for improving the utilization rate of chemical fertilizer, fine management of cultivated land and ecological environment in this region, which can help in decision-making of precision fertilization.

Effects of vegetation and terrain changes on spatial heterogeneity of soil C-N-P in the coastal zone protected forests at northern China.

Soil organic carbon (SOC), total nitrogen (TN) and total phosphorus (TP) are important indicators reflecting soil quality, and they can be used to effectively evaluate the effect of soil remediation. Many studies have evaluated the content of SOC, TN and TP in different ecosystems. However, after constructing protected forests for ecological restoration in the ecologically fragile coastal zone, the spatial distribution and influencing mechanism of SOC, TN and TP content is still uncertain. In this study, the spatial heterogeneity and influencing factors of SOC, TN and TP in surface (0-20 cm) soil were analyzed by traditional analysis and geostatistics. A total of 39 soil samples were collected under the coastal zone protected forest types including Quercus acutissima Carruth (QAC), Pinus thunbergii Parl (PTP), mixed PTP and QAC (QP) and Castanea mollissima BL (CMB) in the coastal zone protected forests in northern China. The results show that SOC, TN and TP content were defined as moderate variation, and they also show significant changes under different protected forest types (P < 0.05). The semivariance results indicate that SOC, TN and TP all exhibited strong spatial dependence class, with Range of 224 m, 229 m and 282 m respectively, which were more than the sampling scale of 200 m. The spatial prediction results showed that SOC, TN and TP content all appear in large areas of extremely low value in CMB, and its cross validation results showed that using vegetation and terrain factors as covariates in the spatial prediction of SOC, TN and TP can improve the prediction accuracy. The results of correlation analysis showed that the influencing factor for SOC and TN, and TP were NDVI and topographical changes, respectively. In general, vegetation and terrain factors as auxiliary factors can improved the accuracy of soil C-N-P spatial distribution prediction after afforestation in coastal zone.

Spatial heterogeneity of soil nutrients in Yili River Valley.

Soil nutrients are a vital reference index of soil fertility and are essential in studying spatial variability for the development of land resources. The traditional statistical methods including correlation analysis and geostatistical analysis, were used to explore the spatial variability of nutrients and its influencing factors in the Yili River Valley. The results showed that soil total potassium (STK) had a weak variation, soil organic carbon (SOC), soil total nitrogen (STN) and soil total phosphorus (STP) showed a moderate degree of variation. Correlation analysis showed that SOC had a significant correlation with STN, STP, STK, silt, soil water content (SWC), Cos a and altitude (p < 0.01). In contrast, negative correlations were found between the SOC and sand, soil bulk density (SBD) and pH (p < 0.01), the same as STN. STP had a significant correlation with STK, silt (p < 0.01) and Cos a (p < 0.05), whereas negative correlations were found between the STP, sand and SBD (p < 0.01). STK had a significant correlation with silt, whereas negative correlations were found between the STK, sand and SBD. Ordinary Kriging interpolation showed that the distribution of SOC and STN had a high value in the northeast, northwest and southeast, and a low value in the central and southwest. STP was high in the northwest and southeast and low in the northeast and southwest. STK was high in the northwest and northeast and low in the central and southeast regions. This is helpful for the rational exploitation of land resources in ecological economy development in the Yili River Basin.

Spatial variability and delineation of management zones based on soil micronutrient status in apple orchard soils of Kashmir valley, India.

Knowledge and up-scaling of status, availability, and distribution of soil micronutrients are hugely significant for enhancing crop productivity and profitability. However, regional database entailing spatial variability of key micronutrients for a major apple-producing region like the Kashmir Himalayan Region (KHR) is missing. We investigated 588 topsoil samples between 2016 and 2017 (to 30 cm depth) to estimate spatial variability of extractable Zn, Cu, Mn, and Fe; develop spatial maps; and delineate potential management zones (MZs) in apple orchards using geo-statistical methods. Soil sampling was performed post-harvest season. Principal component analysis and fuzzy c-mean clustering were performed to develop MZs. Results exhibited wide variation, with high coefficient of variation (%) for Mn and Cu (123.9 and 114.4, respectively) and low (71.6) and medium (104) variability for Fe and Zn. Mean concentrations followed the order: Fe > Mn > Cu > Zn, with deficiencies evident towards central and northern regions of the study area. The best-fitted model was exponential. The nugget/sill ratio values were 0.41, 0.08, 0.37, and 0.38 for Zn, Cu, Mn, and Fe, respectively, indicating strong spatial dependence for Cu and moderate dependence for Fe, Zn, and Mn. Correlations between elevation, slope, and soil pH with micronutrients were negative, whereas with soil organic carbon and electrical conductivity positive relationships were identified. Three principal components accounted for 67·18% data variance. Based on the fuzzy performance index and modified partition entropy, five MZs were delineated, which exhibited variations from each other. These MZs highlighted the need for specific supplemental provisions in increasing soil fertility and apple productivity.

Valorisation of mine waste - Part II: Resource evaluation for consolidated and mineralised mine waste using the Central African Copperbelt as an example.

Mine waste can create long-term and occasionally catastrophic environmental degradation. Due diligence of mine waste in the form of monitoring and maintenance requires a constant supply of societal resources. Furthermore, mine waste is unlikely to disappear with current mining methods and instead, it is more likely to accumulate at a faster rate due to decreasing primary ore grades and increasing societal demands. However, mine waste can be a societal asset, as it can offer an alternative source of partly critical raw materials (CRMs) that can augment primary sources and provide an opportunity to mitigate supply-risk while ensuring sustainability and easing geopolitical tensions. Cobalt is a critical raw material that is largely a by-product of mining of copper, nickel and platinum-group element ores. It is an element that the renewable energy and high-tech sectors critically depend on and for which no reasonable substitutes currently exist. The majority of the global cobalt production stems from the Central African Copperbelt. Published cobalt production figures for the Central African Copperbelt were used to evaluate cobalt tailings from the Central African Copperbelt. As part of a waste valorisation framework that focuses on primarily on the technical aspects of mine waste valorisation, this study assesses the application of key geostatistical methods, such as kriging and conditional simulation, followed by uniform conditioning, to evaluate the resource potential in a hypothetical copper-cobalt tailing deposit from the Central African Copperbelt. The results indicate that methods such as traditional algorithmic kriging, sequential Gaussian simulation and uniform conditioning are highly effective tools in resource modelling of mine waste. The resource assessment framework component developed in this study makes it possible to systematically characterise, profile and model any mine waste storage facility and thus supplements other framework components discussed in an accompanying paper to maximise mine waste utilization.

Factorial kriging for estimating and mapping the geochemical background from in situ gamma dose rate measurements downstream of a former uranium mine.

A geostatistical approach is applied for extracting the geochemical background from gamma dose rate data acquired downstream of a former French uranium mining area. The exploratory data analysis shows that the spatial structure of the gamma dose rate consists of two components: a short isotropic component (10 m-range) that corresponds to the geochemical background; and a long anisotropic component (30-60 m-range) that corresponds to the drainage network features previously fed by the mine discharge water. The gamma dose rate on the whole area of interest was estimated and simulated (to deal with uncertainties) through a kriging of the measured values. The spatial component related to the geochemical background was then extracted through factorial kriging. The proportion of the gamma dose rate explained by the geochemical background according to factorial kriging is consistent within uncertainties with geochemical analyses performed on soil and sediment samples. This study thus highlights the potential of such geostatistical approaches for better exploiting radiometric data.

Spatial prediction of the concentration of selenium (Se) in grain across part of Amhara Region, Ethiopia.

Grain and soil were sampled across a large part of Amhara, Ethiopia in a study motivated by prior evidence of selenium (Se) deficiency in the Region's population. The grain samples (teff, Eragrostis tef, and wheat, Triticum aestivum) were analysed for concentration of Se and the soils were analysed for various properties, including Se concentration measured in different extractants. Predictive models for concentration of Se in the respective grains were developed, and the predicted values, along with observed concentrations in the two grains were represented by a multivariate linear mixed model in which selected covariates, derived from remote sensor observations and a digital elevation model, were included as fixed effects. In all modelling steps the selection of predictors was done using false discovery rate control, to avoid over-fitting, and using an α-investment procedure to maximize the statistical power to detect significant relationships by ordering the tests in a sequence based on scientific understanding of the underlying processes likely to control Se concentration in grain. Cross-validation indicated that uncertainties in the empirical best linear unbiased predictions of the Se concentration in both grains were well-characterized by the prediction error variances obtained from the model. The predictions were displayed as maps, and their uncertainty was characterized by computing the probability that the true concentration of Se in grain would be such that a standard serving would not provide the recommended daily allowance of Se. The spatial variation of grain Se was substantial, concentrations in wheat and teff differed but showed the same broad spatial pattern. Such information could be used to target effective interventions to address Se deficiency, and the general procedure used for mapping could be applied to other micronutrients and crops in similar settings.

Spatial variability of precompression stress and volumetric water content of a red-yellow latosol (Oxisol) / Variabilidade espacial da pressão de preconsolidação e da umidade volumétrica de um latossolo vermelho amarelo

The intensive agricultural machinery traffic to which soils under coffee crops are exposed may cause significant changes in soil structure. The goals of this study were to: a) characterize the spatial variability of precompression stress (σp) and volumetric water content (θ) of a Red-Yellow Latosol (Oxisol) and determine their spatially dependent structures using ordinary kriging semivariograms; b) using this date to construct a load-bearing capacity (LBC) map for the site, identifying the depth with higher ; and c) use the map as a decision support tool regarding agricultural machinery logistic management in coffee plantations. The research was conducted on an experimental farm of the Agricultural Research Company of Minas Gerais (Epamig), Patrocinio, MG, on a clayey Oxisol. Samples were collected from 2.0 × 1.5 m sampling pits at intersections of a rectangular 40 × 150 m grid, totaling 28 sampling points. The soil samples were collected with metal rings (0.0254 m in height and 0.0630 m in diameter) using an Uhland sampler. Sampling at each pit was at 3 layers: 0.00­0.03 m, 0.10­0.13 m, and 0.25­0.28 m, and seven samples arranged in a matrix form were collected at each layer, totaling 588 samples. The σp and θ showed a spatially dependent structure. The depth of 0.00­0.03 m showed higher LBC, indicating that this depth was more compacted compared to other depths. Based on the σp maps, the tractor and the combine should not traffic into the areas at water content of 0.45 m3 m-3, because the soil has a LBC of 200 kPa. If this condition is not respected, additional compaction will occur. Tractor traffic is permissible when the water content reaches values less than 0.36 m3 m-3, whereas for combine traffic, the water content values must be less than 0.30 m3 m-3.

O tráfego intenso de máquinas agrícolas sobre solos cultivados com cafeeiro pode causar alterações significativas na estrutura do solo. Os objetivos deste estudo foram: a) avaliar e identificar a variabilidade espacial da pressão de preconsolidação (σp) e a umidade volumétrica (θ) de um Latossolo Vermelho-Amarelo (LVA) e determinar a estrutura de dependência espacial através de semivariogramas utilizando a krigagem ordinária; b) verificar no mapa, a profundidade com maior capacidade de suporte de carga (CSC) do solo ; c) dar suporte a tomada de decisão no manejo do maquinário agrícola da cultura cafeeira e utilizar esses mapas para a logística de manejo de trafego de máquinas. O experimento foi conduzido num LVA textura muito argilosa na Fazenda da Epamig (Empresa de Pesquisa Agropecuária de Minas Gerais), em Patrocínio-MG. A amostragem foi realizada numa malha retangular (150 m x 40 m), onde foram coletadas amostras indeformadas em anéis metálicos de 0,0254 m de altura por 0,0630 m de diâmetro com auxílio do amostrador tipo Uhland em 28 trincheiras. Cada trincheira possui três degraus que correspondem às profundidades de (0.00-0.03; 0.10-0.13 e 0.25-0.28 m) e as dimensões dos degraus foram de 2,0 x 1,5 m, coletaram-se sete amostras (disposta em forma matricial) para cada degrau, totalizando 588 amostras. A σp e θ apresentaram estrutura de dependência espacial. A profundidade de 0.00-0.03m apresentou maior CSC indicando que esta profundidade está mais compactada em relação as demais profundidades. Com base nos mapas da σp, o trator e a colhedora não devem trafegar na área para umidade volumétrica igual a 0.45 m3 m-3, pois o solo possui CSC de 200 kPa. Se essa condição for desrespeitada, a compactação adicional poderá ocorrer. Para o tráfego do trator, deve-se esperar por um período, para que a θ atinja um valor menor que 0.36 m3 m-3, enquanto que para o tráfego da colhedora deve-se esperar a θ atingir valor menor que 0.30 m3 m-3.

Environmental assessment of agricultural activities and groundwater nitrate pollution susceptibility: a regional case study (Southwestern Romania).

Diffuse pollution of water resources from agricultural sources is a major environmental issue in Europe. The nutrients released in groundwater from cultivated fields and livestock production, together with pesticides, are the main source of concern in the framework of the European Nitrates Directive (91/676/EEC). Southern Romania continues to represent one of the most important cereal production areas of the country. The intensive exploitation during the communist period continues to have repercussions for the precarious quality of groundwater. The aim of our study was to establish the environmental conditions, quantify the agricultural activities at the local administrative unit level and afterwards, to highlight areas of susceptibility to nitrate pollution of groundwater within the Oltenia Plain. One of the most efficient methods to evaluate human influences by agricultural activities on groundwater is using different types of indicators, such as land use indicators (cultivated surfaces), animal husbandry indicators (livestock and great beef units), and agri-environmental indicators (use of fertilisers based on nitrogen and phosphorus, quantity/ha). Throughout the paper, GIS methods are used to determine the degree of influence on nitrate pollution of several eco-pedological indicators: soil types and subtypes, slope of the land, soil texture, soil permeability, and groundwater level. Statistics indicate that 85% of the study area is susceptible to nitrate pollution from agriculture. Indicators provide information that can be easily interpreted by decision and policy makers, and they facilitate the process of reducing nitrate pollution. This study shows that the correlation of statistics and GIS modelling is a useful method for guiding prevention practices for groundwater pollution at the regional scale in Southwestern Romania.

[Temporal-spatial Distribution of Nitrogen and Phosphorus Nutrients in Lake Taihu Based on Geostatistical Analysis].

It is of great significance to investigate the spatio-temporal variation in nitrogen and phosphorus nutrients as a mechanism for controlling the sudden increase of algae in eutrophic water. Based on the geostatistical analysis, we studied the sources and occurring forms of nitrogen and phosphorus in different areas of Lake Taihu-a large shallow and eutrophic lake in China. We also examined the spatial distribution of the type of nutrient restriction and its reason by monitoring the sites seasonally from August 2014 to May 2015. The results showed that:① The concentrations of soluble nitrogen and phosphorus were higher in the winter than in other seasons, and they gradually decreased spatially from the northwest to southeast. The concentrations of particulate nitrogen, phosphorus, and chlorophyll a were highest in the summer, and the high-concentration regions in the winter and other seasons were located in the southern and northwestern parts of the lake, respectively. ② The composition of nitrogen and phosphorus in algae-and macrophyte-dominated regions changed substantially with the seasonal change. The algae-dominated regions were dominated by nitrate nitrogen and organic phosphorus in the winter and particulate nitrogen and phosphorus during the other seasons. However, the macrophyte-dominated region was dominated by particulate nitrogen and phosphorus in the winter and ammonia, organic nitrogen, and phosphorus during the other seasons. ③ The ratios of total nitrogen to total phosphorus in the algae-dominated region were greater than 16:1 in the autumn and winter but less than 16:1 in the summer and spring. Meanwhile, the ratios of total nitrogen to total phosphorus in the macrophyte-dominated region increased from less than 16:1 in the autumn and winter to more than 16:1 in the summer and spring. In the algae-dominated region, the spatial variation in the dissolved total nitrogen to total phosphorus ratio was consistent with the ratio of total nitrogen to total phosphorus. In the macrophyte-dominated region, the dissolved total nitrogen to total phosphorus ratio increased from less than 16:1 in the autumn to more than 16:1 in the summer, winter, and spring. The temporal and spatial variation in the ratio of particulate nitrogen to phosphorus was not significant (P>0.05), and this ratio was less than and greater than 16 in algae-and macrophyte-dominated regions, respectively.

Variability and spatial correlation of aggregates and organic carbon in indian dark earth in Apuí region, AM / Variabilidade e correlação espacial de agregados e carbono orgânico em terra preta de índio na região do Apuí, AM

Having in mind the importance of knowing the variability and spatial correlation of soil properties in Indian Dark Earth (IDE), we evaluated in this study the variability and the spatial correlation of aggregates and carbon in an Ultisol under coffee cultivation in southern Amazonas. It was established a 48 x 88 m sampling grid spaced 06 x 08 m, totalling 88 sampling points. Then soil samples were collected at: 0.0-.05, 0.05-0.10, and 0.10-0.20 m layers. The spatial variability of the Mean Weighted Diameter (MWD) attributes, aggregates > 2 mm, < 2 mm, bulk density (BD) and organic carbon (OC) was analyzed by adjusting the simple semivariograms, while spatial correlations of the OC with aggregates and BD were analyzed by cross-semivariogram. We could conclude that there was spatial dependence in the variables, wherein the largest ones were observed at 0.0-0.05 m, except for Mean Weighted Diameter (MWD) and aggregates greater than 2.00 mm with larger range of values in depth from 0.05-0.10 and 0.10-0.20 m. The mean weight diameter and aggregate class attributes greater than 2.00 mm had negative spatial correlation with organic carbon at 0.0-0.05 m, while the smaller aggregates than 2.00 mm classes and bulk density correlated positively with organic carbon at 0.0-0.05 m and 0.10-0.20 m.

Considerando a importância do conhecimento da variabilidade e correlação espacial dos atributos do solo em Terra Preta de Índio (TPIs), avaliou-se neste trabalho a variabilidade e a correlação espacial de agregados e carbono em um Argissolo Amarelo eutrófico sob cultivo de café na região sul do Amazonas. Foi estabelecido um grid amostral com dimensões de 48 x 88 m e espaçamentos de 06 x 08 m, totalizando 88 pontos amostrais. Em seguida, foram coletadas amostras de solos nas profundidades: 0,0-0,05, 0,05-0,10, e 0,10-0,20 m. A variabilidade espacial dos atributos diâmetro médio ponderado (DMP), agregados > 2 mm, < 2 mm, densidade do solo (Ds) e carbono orgânico (CO) foi analisada ajustando os semivariogramas simples, enquanto as correlações espaciais do CO com agregados e Ds foram analisadas por semivariogramas cruzados. Concluiu-se que as variáveis apresentaram dependência espacial, e os maiores alcances são constatados na profundidade 0,0-0,05 m, exceto para DMP e agregados maiores que 2,00 mm com maiores valores de alcance na profundidade 0,05-0,10 e 0,10-0,20 m. Os atributos diâmetro médio ponderado e classes de agregados maior que 2,00 mm apresentam correlação espacial negativa com carbono orgânico na profundidade 0,0-0,05 m, enquanto a classes de agregados menor que 2,00 mm e densidade do solo apresentam correlação positiva com carbono orgânico nas profundidades 0,0-0,05 m e 0,10-0,20 m.

Spatial variability and solubility of barium in a petroleum well-drilling waste disposal area.

The petroleum industry generates a range of wastes which is often are disposed in soil close to the well location, negatively affecting soil and water quality. The objective of this study was to evaluate the solubility and map the spatial variability of barium in a potentially contaminated area. The study area consisted of a petroleum well-drilling waste disposal site located in the municipality of Mato Rico-PR. A large georeferenced sampling grid was organized. Soil samples were collected at depths of 30, 60, 90, and 120 cm for determination of the "pseudo-total" concentrations and geochemical fractionation of barium. The barium concentrations showed spatial dependence, which permitted the use of geostatistical interpolators. Regarding depth, the depth of 0-30 cm showed the largest contaminated area; however, higher concentrations of barium were found at the depth of 60-90 cm. The results of geochemical fractionation showed that the analyzed samples contained percentages higher than 99% in the non-labile fraction (residual). These results indicate clearly that the barium was in a condition of low solubility, even for samples that had the highest concentrations, presenting low-environmental risk.

Spatial assessment of potential ecological risk of heavy metals in soils from informal e-waste recycling in Ghana.

The rapidly increasing annual global volume of e-waste, and of its inherently valuable fraction, has created an opportunity for individuals in Agbogbloshie, Accra, Ghana to make a living by using unconventional, uncontrolled, primitive and crude procedures to recycle and recover valuable metals from this waste. The current form of recycling procedures releases hazardous fractions, such as heavy metals, into the soil, posing a significant risk to the environment and human health. Using a handheld global positioning system, 132 soil samples based on 100 m grid intervals were collected and analysed for cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), lead (Pb) and zinc (Zn). Using geostatistical techniques and sediment quality guidelines, this research seeks to assess the potential risk these heavy metals posed to the proposed Korle Ecological Restoration Zone by informal e-waste processing site in Agbogbloshie, Accra, Ghana. Analysis of heavy metals revealed concentrations exceeded the regulatory limits of both Dutch and Canadian soil quality and guidance values, and that the ecological risk posed by the heavy metals extended beyond the main burning and dismantling sites of the informal recyclers to the school, residential, recreational, clinic, farm and worship areas. The heavy metals Cr, Cu, Pb and Zn had normal distribution, spatial variability, and spatial autocorrelation. Further analysis revealed the decreasing order of toxicity, Hg>Cd>Pb> Cu>Zn>Cr, of contributing significantly to the potential ecological risk in the study area.

Geographically weighted regression and geostatistical techniques to construct the geogenic radon potential map of the Lazio region: A methodological proposal for the European Atlas of Natural Radiation.

In many countries, assessment programmes are carried out to identify areas where people may be exposed to high radon levels. These programmes often involve detailed mapping, followed by spatial interpolation and extrapolation of the results based on the correlation of indoor radon values with other parameters (e.g., lithology, permeability and airborne total gamma radiation) to optimise the radon hazard maps at the municipal and/or regional scale. In the present work, Geographical Weighted Regression and geostatistics are used to estimate the Geogenic Radon Potential (GRP) of the Lazio Region, assuming that the radon risk only depends on the geological and environmental characteristics of the study area. A wide geodatabase has been organised including about 8000 samples of soil-gas radon, as well as other proxy variables, such as radium and uranium content of homogeneous geological units, rock permeability, and faults and topography often associated with radon production/migration in the shallow environment. All these data have been processed in a Geographic Information System (GIS) using geospatial analysis and geostatistics to produce base thematic maps in a 1000 m × 1000 m grid format. Global Ordinary Least Squared (OLS) regression and local Geographical Weighted Regression (GWR) have been applied and compared assuming that the relationships between radon activities and the environmental variables are not spatially stationary, but vary locally according to the GRP. The spatial regression model has been elaborated considering soil-gas radon concentrations as the response variable and developing proxy variables as predictors through the use of a training dataset. Then a validation procedure was used to predict soil-gas radon values using a test dataset. Finally, the predicted values were interpolated using the kriging algorithm to obtain the GRP map of the Lazio region. The map shows some high GRP areas corresponding to the volcanic terrains (central-northern sector of Lazio region) and to faulted and fractured carbonate rocks (central-southern and eastern sectors of the Lazio region). This typical local variability of autocorrelated phenomena can only be taken into account by using local methods for spatial data analysis. The constructed GRP map can be a useful tool to implement radon policies at both the national and local levels, providing critical data for land use and planning purposes.

Spatial assessment of potential ecological risk of heavy metals in soils from informal e-waste recycling in Ghana

The rapidly increasing annual global volume of e-waste, and of its inherently valuable fraction, has created an opportunity for individuals in Agbogbloshie, Accra, Ghana to make a living by using unconventional, uncontrolled, primitive and crude procedures to recycle and recover valuable metals from this waste. The current form of recycling procedures releases hazardous fractions, such as heavy metals, into the soil, posing a significant risk to the environment and human health. Using a handheld global positioning system, 132 soil samples based on 100 m grid intervals were collected and analysed for cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), lead (Pb) and zinc (Zn). Using geostatistical techniques and sediment quality guidelines, this research seeks to assess the potential risk these heavy metals posed to the proposed Korle Ecological Restoration Zone by informal e-waste processing site in Agbogbloshie, Accra, Ghana. Analysis of heavy metals revealed concentrations exceeded the regulatory limits of both Dutch and Canadian soil quality and guidance values, and that the ecological risk posed by the heavy metals extended beyond the main burning and dismantling sites of the informal recyclers to the school, residential, recreational, clinic, farm and worship areas. The heavy metals Cr, Cu, Pb and Zn had normal distribution, spatial variability, and spatial autocorrelation. Further analysis revealed the decreasing order of toxicity, Hg>Cd>Pb> Cu>Zn>Cr, of contributing significantly to the potential ecological risk in the study area.

Modeling olive pollen intensity in the Mediterranean region through analysis of emission sources.

Aerobiological monitoring of Olea europaea L. is of great interest in the Mediterranean basin because olive pollen is one of the most represented pollen types of the airborne spectrum for the Mediterranean region, and olive pollen is considered one of the major cause of pollinosis in this region. The main aim of this study was to develop an airborne-pollen map based on the Pollen Index across a 4-year period (2008-2011), to provide a continuous geographic map for pollen intensity that will have practical applications from the agronomical and allergological points of view. For this purpose, the main predictor variable was an index based on the distribution and abundance of potential sources of pollen emission, including intrinsic information about the general atmospheric patterns of pollen dispersal. In addition, meteorological variables were included in the modeling, together with spatial interpolation, to allow the definition of a spatial model of the Pollen Index from the main olive cultivation areas in the Mediterranean region. The results show marked differences with respect to the dispersal patterns associated to the altitudinal gradient. The findings indicate that areas located at an altitude above 300ma.s.l. receive greater amounts of olive pollen from shorter-distance pollen sources (maximum influence, 27km) with respect to areas lower than 300ma.s.l. (maximum influence, 59km).

Analysis of field-scale spatial correlations and variations of soil nutrients using geostatistics.

Spatial correlations and soil nutrient variations are important for soil nutrient management. They help to reduce the negative impacts of agricultural nonpoint source pollution. Based on the sampled available nitrogen (AN), available phosphorus (AP), and available potassium (AK), soil nutrient data from 2010, the spatial correlation, was analyzed, and the probabilities of the nutrient's abundance or deficiency were discussed. This paper presents a statistical approach to spatial analysis, the spatial correlation analysis (SCA), which was originally developed for describing heterogeneity in the presence of correlated variation and based on ordinary kriging (OK) results. Indicator kriging (IK) was used to assess the susceptibility of excess of soil nutrients based on crop needs. The kriged results showed there was a distinct spatial variability in the concentration of all three soil nutrients. High concentrations of these three soil nutrients were found near Anzhou. As the distance from the center of town increased, the concentration of the soil nutrients gradually decreased. Spatially, the relationship between AN and AP was negative, and the relationship between AP and AK was not clear. The IK results showed that there were few areas with a risk of AN and AP overabundance. However, almost the entire study region was at risk of AK overabundance. Based on the soil nutrient distribution results, it is clear that the spatial variability of the soil nutrients differed throughout the study region. This spatial soil nutrient variability might be caused by different fertilizer types and different fertilizing practices.