Statistical Issues in Assessing Anthropogenic Background for Arsenic

Conceptual and statistical issues surrounding the estimation of a background concentration distribution for arsenic are reviewed. How background area is defined and samples collected are shown to impact the shape and location of the probability density function that in turn affects the estimation and precision of associated distributional parameters. The overall background concentration distribution is conceptualized as a mixture of a natural background distribution, an anthropogenic background distribution and a distribution designed to accommodate the potential for contamination site samples being included into the background sample set. This concept is extended to a discussion of issues surrounding estimation of natural and anthropogenic background distributions for larger geographic areas. Finally, the mixture model is formally defined and statistical approaches to estimating its parameters discussed.     

Environmental–geochemical characteristics of Cu in the soil and water in copper-rich deposit area of southeastern Hubei Province, along the middle Yangtze River, Central China

In this study, the natural Cu background concentration and Cu natural and anthropogenic contamination in soil, water and crop were investigated systematically in Huangshi area. The results show that regional geology is the dominant factor controlling the natural Cu background concentration in soil and water, and that pH is important to control the vertical distribution of Cu in soil under the same geographical and climatic conditions. The mineralization of rock bodies causes the natural Cu increase in soil and water, whereas, a large number of mining–smelting plants and chemical works are the main sources of Cu anthropogenic contamination. Cu in naturally and anthropogenically polluted soil displays differences in total and available contents, vertical distribution patterns and physico-chemical properties, the same happens in water.     

Combining a finite mixture distribution model with indicator kriging to delineate and map the spatial patterns of soil heavy metal pollution in Chunghua County, central Taiwan

This study identifies the natural background, anthropogenic background and distribution of contamination caused by heavy metal pollutants in soil in Chunghua County of central Taiwan by using a finite mixture distribution model (FMDM). The probabilities of contaminated area distribution are mapped using single-variable indicator kriging and multiple-variable indicator kriging (MVIK) with the FMDM cut-off values and regulation thresholds for heavy metals. FMDM results indicate that Cr, Cu, Ni and Zn can be individually fitted by a mixture model representing the background and contamination distributions of the four metals in soil. The FMDM cut-off values for contamination caused by the metals are close to the regulation thresholds, except for the cut-off value of Zn. The receiver operating characteristic (ROC) curve validates that indicator kriging and MVIK with FMDM cut-off values can reliably delineate heavy metals contamination, particularly for areas lacking background information and high heavy metal concentrations in soil.     

Evaluation of environmental magnetic pollution screening in soils of basaltic origin: results from Nashik Thermal Power Station, Maharashtra, India

Background, aim, and scope

Soils of basaltic origin cause difficulties in environmental magnetic screening for heavy metal pollution due to their natural high background values. Magnetic parameters and heavy metal content of highly magnetic topsoils from the Deccan Trap basalts are investigated to assess their potential for use in environmental magnetic pollution screening. This work extends the fast and cost-effective magnetic pollution screening techniques into soils with high natural magnetic signals.

Materials and methods

Fifty-five topsoil samples from N?CS and W?CE transects were collected and subdivided according to grain size using wet sieving technique. Magnetic susceptibility, soft isothermal remanent magnetization (Soft IRM), thermomagnetic analysis, scanning electron microscopy (SEM), and heavy metal analysis were performed on the samples.

Results

Magnetic analyses reveal a significant input of anthropogenic magnetic particulate matter within 6 km of the power plant and the adjacent ash pond. Results depend strongly on the stage of soil development and vary spatially. While results in the W, E, and S directions are easily interpretable, in the N direction, the contribution of the anthropogenic magnetic matter is difficult to assess due to high magnetic background values, less developed soils, and a more limited contribution from the fly ash sources. Prevailing winds towards directions with more enhanced values seem to have a certain effect on particulate matter accumulation in the topsoil. Thermomagnetic measurements show Verwey transition and Hopkinson peak, thus proving the presence of ferrimagnetic mineral phases close to the pollution source. A quantitative decrease of the anthropogenic ferrimagnetic mineral concentration with increased distance is evident in Soft IRM measurements. SEM investigations of quantitatively extracted magnetic particles confirm the fly ash distribution pattern obtained from the magnetic and heavy metal analyses. Evaluation of magnetic and chemical data in concert with the Pollution Load IndiceS (PLIS) of Pb, Zn, and Cu reveals a good relationship between magnetic susceptibility and the metal content.

Conclusions

Integrated approaches in data acquisition of magnetic and chemical parameters enable the application of magnetic screening methods in highly magnetic soils. Combined data evaluation allows identification of sampling sites that are affected by human activity, through the deviation of the magnetic and chemical data from the general trend. It is shown that integrative analysis of magnetic parameters and a limited metal concentration dataset can enhance the quality of the output of environmental magnetic pollution screening significantly.     

Stochastic evaluation of mass discharge from pointlike concentration measurements

The contaminant mass discharge crossing a control plane is an important metric in the assessment of natural attenuation at contaminated sites. For risk-assessment purposes, the mass discharge must be estimated together with a level of uncertainty. We present a conditional Monte Carlo approach that allows estimating the statistical distribution of mass discharge. The approach is based on conditioning multiple realizations of the hydraulic conductivity field on all data available. We jointly determine a first-order decay coefficient in each realization, leading to conditional statistical distributions of all estimated parameters and the total mass discharge. The resulting statistical distribution of contaminant mass discharges can be used in the assessment of risks at the contaminated site. The method is applied to data of hypothetical test cases, which gives the opportunity to compare estimation results to the true field. As concentration data, we account for pointlike measurements obtained in multi-level sampling wells. The obtained empirical distribution of mass discharge crossing the multi-level sampling fence could be well fitted by a log-normal distribution.     

Arsenic Background Concentrations in Florida,U.S.A. Surface Soils: Determination and Interpretation

Background concentrations of soil arsenic have been used as an alternative soil cleanup criterion in many states in the U.S. This research addresses issues related to the interpretation of background concentrations of arsenic in near pristine soils in Florida. Total arsenic was measured in 448 taxonomic and geographic representative surface soil samples using USEPA Method 3052 (HCl-HNO 3 -HF, microwave digestion) and graphite furnace atomic absorption spectrophotometry analysis procedure. Values were log-normally distributed, with geometric mean and baseline concentration (defined as 95% of the expected range of background concentrations) providing the most satisfactory statistical results. An upper baseline concentration of 6.21 mg As/kg was estimated for undisturbed soils (n=267) compared to 7.63 mg As/kg for disturbed soils (n=181). Temporal trend of total soil arsenic concentrations from 1967 to 1989 paralleled decreased usage of arsenic in U.S. agriculture. Soil arsenic background concentrations were generally higher in south Florida than in north and central Florida, and associated with wet soils. Individual high arsenic sites were scattered throughout the state, but the most highly concentrated of these occurred in the Leon-Lee belt along the Ocala uplift district extending to the southwestern flatwoods district. Extrapolation of the data using a single arsenic value regardless of the taxonomic and geographical differences in soil arsenic distribution would underestimate potential arsenic contamination in upland soils.     

Multivariate statistical and lead isotopic analyses approach to identify heavy metal sources in topsoil from the industrial zone of Beijing Capital Iron and Steel Factory

Heavy metals are considered toxic to humans and ecosystems. In the present study, heavy metal concentration in soil was investigated using the single pollution index (PIi), the integrated Nemerow pollution index (PIN), and the geoaccumulation index (Igeo) to determine metal accumulation and its pollution status at the abandoned site of the Capital Iron and Steel Factory in Beijing and its surrounding area. Multivariate statistical (principal component analysis and correlation analysis), geostatistical analysis (ArcGIS tool), combined with stable Pb isotopic ratios, were applied to explore the characteristics of heavy metal pollution and the possible sources of pollutants. The results indicated that heavy metal elements show different degrees of accumulation in the study area, the observed trend of the enrichment factors, and the geoaccumulation index was Hg > Cd > Zn > Cr > Pb > Cu ≈ As > Ni. Hg, Cd, Zn, and Cr were the dominant elements that influenced soil quality in the study area. The Nemerow index method indicated that all of the heavy metals caused serious pollution except Ni. Multivariate statistical analysis indicated that Cd, Zn, Cu, and Pb show obvious correlation and have higher loads on the same principal component, suggesting that they had the same sources, which are related to industrial activities and vehicle emissions. The spatial distribution maps based on ordinary kriging showed that high concentrations of heavy metals were located in the local factory area and in the southeast-northwest part of the study region, corresponding with the predominant wind directions. Analyses of lead isotopes confirmed that Pb in the study soils is predominantly derived from three Pb sources: dust generated during steel production, coal combustion, and the natural background. Moreover, the ternary mixture model based on lead isotope analysis indicates that lead in the study soils originates mainly from anthropogenic sources, which contribute much more than the natural sources. Our study could not only reveal the overall situation of heavy metal contamination, but also identify the specific pollution sources.

     

Regional geochemical baselines for Portuguese shelf sediments

Metal concentrations (Al, Cr, Cu, Ni, Pb and Zn) from the DGM-INETI archive data set have been examined for sediments collected during the 1970s from 267 sites on the Portuguese shelf. Due to the differences in the oceanographic and sedimentological settings between western and Algarve coasts, the archive data set is split in two segments. For both shelf segments, regional geochemical baselines (RGB) are defined using aluminium as a reference element. Seabed samples recovered in 2002 from four distinct areas of the Portuguese shelf are superimposed on these models to identify and compare possible metal enrichments relative to the natural distribution. Metal enrichments associated with anthropogenic influences are identified in three samples collected nearby the Tejo River and are characterised by the highest enrichment factors (EF; EF(Pb)<3, EF(Zn)<4). EF values close to 1 suggest a largely natural origin for metal distributions in sediments from the other areas included in the study.     

Resembling a “natural formation pattern” of chlorinated dibenzo-p-dioxins by varying the experimental conditions of hydrothermal carbonization

Until several years ago dioxins were considered as just an unwanted by product of anthropogenic activities and stigmatized as the symbol of man-made environmental pollution. Natural processes, such as forest fires, can emit dioxins, but compared to industrial processes, usually very low quantities are emitted. However after a case of food contamination occurred in the United States of America in 1996 caused by kaolinitic clay a discussion on the provenience started. Besides the relatively high concentration also an unusual PCDD/F distribution pattern was found in these ball clay samples. This specific pattern related to none of the known anthropogenic sources for these contaminants and, in relation to a supposed natural formation, later it was named “natural formation pattern”. Hydrothermal carbonization (HTC) can transform biomass within hours into a brown coal-like product which resembles naturally occurring coal formation. HTC can also transform an already present PCDD/F contamination in a way to obtain a “natural formation pattern” characterized by an unusual high ratio between 1,2,3,7,8,9-HxCDD and 1,2,3,6,7,8-HxCDD and the absence of almost all chlorinated dibenzofurans. By varying the experimental conditions of the HTC process applied to sewage sludge samples contaminated with PCDD/Fs from anthropogenic sources, beside the “natural formation pattern” at a temperatures of 255 °C, a remarkable increase of the toxicity based on WHO–TEQ was observed.     

Impact of the global economic crisis on metal levels in particulate matter (PM) at an urban area in the Cantabria Region (Northern Spain)

Air pollution by particulate matter is well linked with anthropogenic activities; the global economic crisis that broke out in the last year may be a proper indicator of this close relationship. Some economic indicators show the regional effects of the crisis on the Cantabria Region. The present work aims to evaluate the impact of the economic crisis on PM10 levels and composition at the major city of the region, Santander. Some metals linked to anthropogenic activities were measured at Santander and studied by Positive Matrix Factorization; this statistical analysis allowed to identify three main factors: urban background, industrial and molybdenum-related factor. The main results show that the temporal trend of the levels of the industrial tracers found in the present study are well agree with the evolution of the studied economic indicators; nevertheless, the urban background tracers and PM10 concentration levels are not well correlated with the studied economic indicators.     

PBDEs and PCBs in sediments of the Thi Nai Lagoon (Central Vietnam) and soils from its mainland

Concentration and distribution of PCBs, PCB 11, and PBDEs in both surficial sediment and soil samples, taken from a zone subject to recent accelerated development, were investigated to assess the environmental quality and understand both natural and anthropogenic processes that influence contaminant behaviors. Values of PCB and PBDE are in the lower range of those reported in literature, typical of low impacted coastal zones. This could be due to efficient processes of resuspension and removal. Contaminants in the lagoon showed higher concentrations in sediments from sites close to the city and the outfalls of the industrial area, while soils showed maximum values in the northern samples. In addition, congener patterns and statistical analyses suggest the presence of effective degradation processes, especially for PBDEs, with the exception of the most concentrated samples that may indicate a direct input. PCB 11 is a significant component (up to 18%) in most lagoon sediments. Its presence is strongly associated with fine particles, thus the distribution seems to be driven mainly by the system hydrodynamic and does not trace the sources. Due to evaporation, only flooded agricultural soils show a similar relative abundance of this congener.     

Arsenic Background Concentrations in Florida,U.S.A. Surface Soils: Determination and Interpretation

Background concentrations of soil arsenic have been used as an alternative soil cleanup criterion in many states in the U.S. This research addresses issues related to the interpretation of background concentrations of arsenic in near pristine soils in Florida. Total arsenic was measured in 448 taxonomic and geographic representative surface soil samples using USEPA Method 3052 (HCl-HNO₃-HF, microwave digestion) and graphite furnace atomic absorption spectrophotometry analysis procedure. Values were log-normally distributed, with geometric mean and baseline concentration (defined as 95% of the expected range of background concentrations) providing the most satisfactory statistical results. An upper baseline concentration of 6.21 mg As/kg was estimated for undisturbed soils (n = 267) compared to 7.63 mg As/kg for disturbed soils (n = 181). Temporal trend of total soil arsenic concentrations from 1967 to 1989 paralleled decreased usage of arsenic in U.S. agriculture. Soil arsenic background concentrations were generally higher in south Florida than in north and central Florida, and associated with wet soils. Individual high arsenic sites were scattered throughout the state, but the most highly concentrated of these occurred in the Leon-Lee belt along the Ocala uplift district extending to the southwestern flatwoods district. Extrapolation of the data using a single arsenic value regardless of the taxonomic and geographical differences in soil arsenic distribution would underestimate potential arsenic contamination in upland soils.     

Natural emissions for regional modeling of background ozone and particulate matter and impacts on emissions control strategies

Natural emissions adopted in current regional air quality modeling are updated to better describe natural background ozone and PM concentrations for North America. The revised natural emissions include organosulfur from the ocean, NO from lightning, sea salt, biogenic secondary organic aerosol (SOA) precursors, and pre-industrial levels of background methane. The model algorithm for SOA formation was also revised. Natural background ozone concentrations increase by up to 4 ppb in annual average over the southeastern US and Gulf of Mexico due to added NO from lightning while the revised biogenic emissions produced less ozone in the central and western US. Natural PM_2.5 concentrations generally increased with the revised natural emissions. Future year (2018) simulations were conducted for several anthropogenic emission reduction scenarios to assess the impact of the revised natural emissions on anthropogenic emission control strategies. Overall, the revised natural emissions did not significantly alter the ozone responses to the emissions reductions in 2018. With revised natural emissions, ozone concentrations were slightly less sensitive to reducing NOx in the southeastern US than with the current natural emissions due to higher NO from lightning. The revised natural emissions have little impact on modeled PM_2.5 responses to anthropogenic emission reductions. However, there are substantial uncertainties in current representations of natural sources in air quality models and we recommend that further study is needed to refine these representations.     

Estimation of anthropogenic and natural heavy metals in the northwestern Mediterranean rainwater and total atmospheric deposition

As already done for aerosols, natural and anthropogenic Pb, Cd, Cu, and Zn concentrations in rainwater have been separated by a statistical numerical method. The natural part is found to strongly decrease from aerosol to rainwater: from 10–20% to 1% for Pb, Cu and Zn, and from 0.9% to 0.6% for Cd. The mean natural and anthropogenic levels in total atmospheric deposition is estimated.     

Bottom sediments of the Arabian Gulf--III. Trace metal contents as indicators of pollution and implications for the effect and fate of the Kuwait oil slick

The trace metal contents of 71 core samples collected in 1992 from the bottom sediments of the Arabian Gulf are used to determine the regional distribution of concentration and pollution levels of these substances in the region. Chronic contamination was recorded in seven locations: the northwestern area (Fe), the northeastern area (Fe, V and Ni), the north-central area (V and Ni), the central area (Fe, Pb, V and Ni), the south-central area (Cu), the eastern area (Cu) and the southeastern area (Fe, V and Ni). Present-day contamination was identified in three locations only: the north-central area (V), the central area (Pb, V and Ni) and the southeastern area (Fe, V and Ni). Diversified natural and anthropogenic inputs may have provided the sources of this contamination. The V/Ni ratios of recent marine sediments cannot be used in identifying oil spillages or in oil-sediment correlation studies. Positive correlations are found between increasing trace metal concentration and decreasing carbonate content and grain size, verifying that adsorption onto muds is the primary mechanism of trace metal concentration in marine sediments. Correlations with TOC (total organic carbon) contents indicate that organic matter is a significant concentrator only in the case of Pb and Cu. With the exception of the Fe contamination in the northwest area due to river transport, all chronic and present-day trace metal concentrations are within the permissible natural background levels in the western offshore areas, including the two areas thought to be polluted by the Kuwait oil slick, thereby supporting the idea that airborne fallout from oil fires was deposited in a limited coastal area between Kuwait and Bahrain, and verifying that the oil slick had minimal effect on the state of pollution by trace metals in the Arabian Gulf.     

Comparison of spatiotemporal distribution patterns of NO2 between four different types of air quality monitoring stations

The concentration data of nitrogen dioxide (NO(2)), obtained from four different types of air quality monitoring (AQM) stations in Korea (i.e., urban traffic (A), urban background (B), suburban background (C), and rural background (D)), were explored to evaluate the fundamental facets of its distribution and behavior. As there are many distinctions between these four types of AQM stations, the observed NO(2) values were clearly distinguished from each other. It is found that the average NO(2) concentrations from all A stations exhibit notably high values within the range of 24.8 (Gwangju) to 54.6 ppb (Seoul), while those of all B stations change from 19.6 (Ulsan) to 34.7 ppb (Seoul). Similarly, large differences were also observed from NO(2) values measured between C and D type stations. The NO(2) values of the former were from 16.5 (Jeonbuk) to 30.2 ppb (Gyunggi), while the latter from 4.3 (Gyeongbuk) to 8.7 ppb (Gyunggi). Although their annual patterns are rather complicated to explain, the results by and large reflected the changes in the conditions of the surrounding environment. When the results are compared across seasons, most stations (A, B, and D types) tend to exhibit their maximum values in the winter followed by spring, fall, and summer. The results of this study confirm that the distribution patterns of NO(2) are fairly sensitive enough to reflect the basic characteristics of its source processes in association with such factors as the intensity of anthropogenic activity or population density.     

Ozone recovery as seen in perspective of the Dobson spectrophotometer measurements at Belsk (52°N, 21°E) in the period 1963–2008

The total ozone monthly means derived from measurements by the Dobson spectrophotometer at Belsk (52°N, 21°E) and satellite observations over central and midlatitudinal Europe are analyzed for the long-term changes between 1995 and 2008. Standard explanatory variables representing physical and chemical processes known to influence the ozone distribution are considered. The potential proxies are: atmospheric loading by the ozone depleting substances characterized by the equivalent effective stratospheric chlorine (EESC) time series, various drivers of ozone dynamical variability including solar cycle, teleconnection patterns, temperature at 50 hPa, and pressure at the tropopause level. The multivariate adaptive regression splines (MARS) methodology is used to find optimal set of the explanatory variables and shape of the anthropogenic trend curve. Following options for the trend curve are examined: proportional to EESC, piecewise linear (with the turning points in 1980 and 1995), and selected from a smooth curve fit to the total ozone time series having “natural variations” removed. Statistical estimates and their uncertainties are calculated using block bootstrapping. The analyses indicate that ozone over Belsk, in central Europe, and in midlatitudinal Europe reaches at least first stage of recovery as defined by the World Meteorological Organization: a statistically significant reduction in the rate of decline. Model using the EESC time series as a proxy for the anthropogenic trend pattern yields even the second stage, i.e., a positive trend in time series that remains after removal dynamical signal from the analyzed data. Substantial seasonal dependent long-term ozone oscillations by the dynamical drivers are revealed causing estimation of the ozone recovery time even more uncertain.     

Sampling duration calculations

Routine air quality monitoring produces filter samples that, when analyzed, yield the total amount of the aerosol present in the volume of air drawn by the pump in the monitoring device during the given sampling period. From this we obtain an average concentration of the aerosol for the given duration. The samples are therefore really aggregate samples. A natural question then is "what is the effect of the duration of aggregation on the accuracy and precision of the estimate of the quantity of interest?" The answer depends on a number of factors, such as the quantity that is being estimated: a mean, or an extreme value, or some other quantity; the nature of the measurement error--additive versus multiplicative; the costs of laboratory analyses, and so on. In this paper, we investigate these issues when the interest is in estimating the mean concentration of a specified aerosol species over a fixed time period. In particular, we propose a method for determining a sampling duration that will yield the "best estimate" of the mean concentration for a given cost whenever appropriate statistical assumptions hold.     

Metal contamination of short-term snow cover near urban crossroads: correlation analysis of metal content and fine particles distribution

Snow samples were collected near crossroads in Novi Sad, Serbia, during December 2009 to assess metal concentrations (Ca, K, Zn, Fe, Cu, Mn, Al, Pb and Na), fine particle distribution and pH value. The filtered samples of melted snow were analysed, with a focus on particles smaller than a few μm. The most common values of the frequency number distribution curve were either in the range of 0.05-0.07 μm or one order of magnitude higher (0.2-0.5 μm). At examined locations metal concentrations varied from 0.0004 mg L⁻¹ for Pb to 18.9 mg L⁻¹ for Na. Besides Na, which mostly originated from de-icing salt, Ca is found to be the most abundant element in snow indicating the dominant influence of natural factors on snow chemistry. No significant difference was found in concentration of the elements at locations near crossroads with either low or high traffic volume, except for Na and Zn.To investigate how metals were related a correlation analysis was done for the concentrations of metals and with respect to the particle size distribution parameters and pH values. The major influence on the fine particle volume (mass) was concluded to be due to the elements from anthropogenic sources. This conclusion was based on the significant positive correlation between Fe, Zn and Al and the fine particle volume based distribution parameters.     

Sulphur in the arctic environment (2): results of multi-medium regional mapping.

The regional distribution patterns of S in terrestrial moss and in the O-, B-, and C-horizon of podzols have been studied in a 188,000 km2 area in Arctic Europe with both, large natural (marine aerosols) and anthropogenic gradients of S-input. Although the existence of a pollution source is visible in the S-maps for moss, the S-deposition gradient is not depicted. The concentration of S in moss is not at all influenced by input of marine aerosols. In contrast, the O-horizon of podzols shows a coastal enrichment of S but does not reflect the anthropogenic input. Even the coastal pattern visible in the map of S in the O-horizon is, however, not linked to the input of SO4(2-) via sea spray but is rather caused by low litter decomposition rates due to low temperature, increasing total S and decreasing mobile S near coast. S-concentrations as observed in the deeper soil horizons are only locally influenced by both anthropogenic and marine input of S. These results suggest that in undisturbed terrestrial environments no mechanism exists for enriching an additional input of S from anthropogenic or natural sources. A very high local variability in the four sample materials points to small-scale local processes being most important for the observed S-concentrations.