Spatial Concentration Patterns Research Articles

Evaluation of the suitability of Landsat, MERIS, and MODIS for identifying spatial distribution patterns of total suspended matter from a self-organizing map (SOM) perspective

Three different empirical models based on Landsat, MERIS, and MODIS sensors were used to retrieve TSM concentrations and construct long-term TSM image datasets during the period from 2003 to 2011. These datasets were utilized to evaluate the suitability of Landsat, MERIS, and MODIS for identifying spatial distribution patterns of TSM concentration based on a self-organizing map (SOM) algorithm in the Pearl River Estuary (PRE). 12 spatial distribution patterns of TSM in the PRE were identified from long-term TSM data of each sensor based on a 4 × 3 SOM array. The expected frequency of occurrence of any given pattern and relative frequency of occurrence of each pattern were calculated and analyzed. The factors that influence the variability of TSM and the spatial distribution patterns of TSM were explained by the contribution of human activities, precipitation, and characteristics of satellite sensors. Our results showed that similar spatial distribution patterns of TSM were extracted from three different TSM image datasets. Each pattern presented a strip distribution from northeast to southwest, and the values of TSM decreased regularly from northwest to southeast. However, patterns identified from Landsat and MODIS TSM images presented some anomalous patterns, which were inconsistent with local circumstances and previous studies. High (low) level spatial distribution patterns of TSM in the SOM array were associated with a variety of high (low) values of TSM concentration in the PRE. Frequency analyses of each pattern demonstrated that notable differences of TSM concentration existed in the PRE from 2003 to 2011. These findings can assist us to better understand the dynamics of TSM concentration and the performance of different empirical models established by Landsat, MERIS, and MODIS for identifying spatial distribution patterns of TSM concentration using the SOM algorithm.

Source apportionment and source-to-sink transport of major and trace elements in coastal sediments: Combining positive matrix factorization and sediment trend analysis

Major and trace elemental concentrations in coastal marine sediments were incorporated into positive matrix factorization (PMF) to identify potential sources and source contributions. Transport pathways of fine-grained sediments and sediment-bound elements were inferred from sediment trend analysis (STA). The spatial distribution patterns of 21 elements (Co, Cu, Ni, Sr, Zn, V, Ba, Sc, Ga, Pb, Cr, Zr, SiO2, Al2O3, Fe2O3, MgO, CaO, K2O, MnO, TiO2, and P2O5) coupled with sediment grain sizes were investigated. The natural and anthropogenic sources of the elements were distinguished by their medium enrichment factors (EFs). Seven sources were recognized by PMF: weathering products, anthropologic emissions, sand, older sediment, biogenic carbonates, products of siliceous organisms, and mine exploitation. Some land-derived elements, including weathering products, anthropogenic-related elements, and mining-related elements, had a significant positive correlation with sediment silt, clay, and organic carbon contents. The spatial patterns of the land-derived elements' concentrations and source contributions were consistent with the sediment transport pathways inferred from the STA. This result revealed that the delivery of the land-derived elements was determined by marine current flows and the associated sediment transport processes. Conversely, elements originating from marine sources, such as sand and older sediment, and from the biological activities of calcareous and siliceous organisms showed little response to sediment transport and deposition processes. Our study links the outputs of statistically oriented approaches (e.g., PMF) to a process-based understanding of elemental transport in marine environments.

A comparison of factors affecting the small-scale distribution of mercury from artisanal small-scale gold mining in a Zimbabwean stream system

Artisanal small-scale gold mining (ASGM) operations use mercury liberally in the gold extraction process and account for approximately one quarter of the anthropogenic mercury consumption worldwide. ASGM activities are concentrated in many impoverished and poorly regulated countries such as Zimbabwe, resulting in a number of negative impacts to health and the environment. To examine levels of mercury contamination in one such geographic locality, sediment and tailing samples were collected in a heavily mined watershed in southern Zimbabwe from May–June 2015. Samples were collected from multiple points within the stream system, as well as from around six stamp mills and a single industrial mine in the watershed. GPS point location data were taken for mining operations and sampling sites to examine the spatial patterns of mercury concentration. Data were first analyzed using linear regression and development of a MARS model, followed by application of an ANCOVA model to assess the relationship among mercury concentrations and percent organic material, distance downstream, and distance from potential contamination source. Mercury concentrations within the study area ranged from 6 to 1541 μg/kg dw (mean 142 μg/kg dw). Analyses of mercury concentrations indicated a positive relationship with percent organic material but a negative relationship with distance downstream and distance from potential contamination source. Results from this study help elucidate the relationship between gold production and the spatial scale of mercury contamination in aquatic ecosystems in Africa. These data may lead to a better understanding of the relationship between mercury use and community health, which may aid both the local and global communities in regulating mercury contamination of the environment.

A precipitation-weighted landscape structure model to predict potential pollution contributions at watershed scales

The impact of landscape structure—often described by landscape composition and configuration—on ecological processes is well-known. Appropriately quantifying landscape structure that critically affect nutrient processes within watersheds remains challenging. A precipitation-weighted landscape structure model (LSM) was developed to predict nutrient concentrations at a large number of watersheds. The LSM was developed based on the landscape location features including topography and precipitation within the watershed. The inequality function of Lorenz curve was used to quantify the spatial structure of different landscape types. The LSM was fitted and validated using the measurements of total nitrogen (TN) and total phosphorus (TP) in 132 watersheds. Regression models predicted the spatial patterns of TN and TP concentrations in 1578 watersheds of the Haihe River Basin, China. (1) Predictive models can explain 64 and 52% of the variation in total TN and TP, respectively. (2) Agricultural and residential lands served as nutrient sources. The contributions of agricultural land were 18 and 21% while those of residential land were 46 and 38% to TN and TP concentrations, respectively. (3) Grassland and forest land were nutrient sinks. Grassland had major contributions of 22 and 30% to TN and TP concentrations, respectively. The contributions of forest land were 7 and 11% to TN and TP concentrations, respectively. The LSM focuses on the nutrient processes and is feasible to implement across a large number of watersheds. This study provides useful implications for quantifying landscape structure and predicting potential pollution under different landscape scenarios.

Mapping percentile statistics of element concentrations in moss specimens collected from 1990 to 2015 in forests throughout Germany

Monitoring and mapping of atmospheric deposition can be achieved by use of chemical transport models, technical sampling devices and/or bio-accumulators such as mosses, lichens, etc. Within the European Moss Survey programme, since 1990 every 5 years mos specimens have been collected and analysed for heavy metals, nitrogen and persistent organic pollutants according a harmonised methodology. Calculation and geostatistical mapping of percentile statistics of element concentration in moss is in the focus of this paper. Thereby, element- and survey-specific as well as heavy metals and surveys integrating statistical evaluations and GIS-mapping were performed. Cr, Sb and Zn show contrary to Fe and Pb, no constant decrease of element concentrations, but an intermediate increase between 2000 and 2005, which did not continue until 2015. Cd, Hg, Pb and N which are of priority according to the Convention on Long-Range Transboundary Air Pollution are in focus in this paper. Additionally, Cr is regarded as representing those elements with an intermediate increase between the years 2000 and 2005 as is also true for Sb and Zn. Surveys integrating percentile statistics depict the spatial patterns of, in most cases, declining element concentrations across time. Survey-specific statistical analyses corroborate that the spatial patterns of element concentrations in moss are changing element-specifically across time. The long-term information on the percentile statistics of bioaccumulation of atmospheric deposition in moss is essential for further scientific evaluation as well as for measurements and reporting of nature protection and environmental management.

Distribución espacial del índice de concentración de precipitación diaria en los andes centrales peruanos: valle del río Mantaro

Los altos porcentajes de concentración de precipitación diaria en pocos días, pueden incrementar el potencial de erosión, inestabilidad de laderas y riesgo de inundaciones, siendo estos problemas comunes en el Perú, por lo que es importante el conocimiento acerca de la precipitación a nivel diario. En este articulo, se ha llevado a cabo una investigación acerca de los patrones espaciales y temporales de la concentración de precipitación diaria en los andes centrales del Perú, mediante el índice de concentración (IC), que evalúa la variación de la valoración de precipitación diaria, la contribución de grandes lluvias a la cantidad total presentada. El índice es aplicado a una curva exponencial como Y = aX exp(bX ) , el cual ajusta el porcentaje acumulado de precipitación en Y contribuida por el porcentaje acumulado de días X llevado a cabo en un lugar, en el periodo 1964-2004, con el cual es posible generar superficies de concentración pluviométrica. Donde las máximas concentraciones registradas en el valle del rio Mantaro, posiblemente estén asociadas a la dinámica de los vientos, como la corriente de chorro de Sudamérica, que se adentran al valle proveniente del Norte y Sur. Donde el 25% de días más lluviosos representan el 60% o más de la cantidad total de días con lluvia.

Mercury in the Arctic tundra snowpack: temporal and spatial concentration patterns and trace gas exchanges

Abstract. In the Arctic, the snowpack forms the major interface between atmospheric and terrestrial cycling of mercury (Hg), a global pollutant. We investigated Hg dynamics in an interior Arctic tundra snowpack in northern Alaska during two winter seasons. Using a snow tower system to monitor Hg trace gas exchange, we observed consistent concentration declines of gaseous elemental Hg (Hggas0) from the atmosphere to the snowpack to soils. The snowpack itself was unlikely a direct sink for atmospheric Hggas0. In addition, there was no evidence of photochemical reduction of HgII to Hggas0 in the tundra snowpack, with the exception of short periods during late winter in the uppermost snow layer. The patterns in this interior Arctic snowpack thus differ substantially from observations in Arctic coastal and temperate snowpacks. We consistently measured low concentrations of both total and dissolved Hg in snowpack throughout the two seasons. Chemical tracers showed that Hg was mainly associated with local mineral dust and regional marine sea spray inputs. Mass balance calculations show that the snowpack represents a small reservoir of Hg, resulting in low inputs during snowmelt. Taken together, the results from this study suggest that interior Arctic snowpacks are negligible sources of Hg to the Arctic.

Spatio-temporal patterns of high summer ozone events in the Madrid Basin, Central Spain

Complex spatial and temporal patterns of ground-level O3 and NO2 concentrations have been revealed across an important southern European O3 exceedance area (Madrid Basin, central Spain). Data were obtained from 102 diffusion tube sites and 49 monitoring stations (25 urban/suburban, 12 urban/suburban-traffic, 7 remote, 3 rural, 2 urban-industrial) located through a wide area inside and beyond the city. This new, high-density database confirms that current locations of monitoring stations in the Madrid networks are well positioned to record representative levels of O3 across the area. Two air quality monitoring stations were identified as reference measurement points, based on their lower O3 and NO2 concentrations, and used as a proxy for regional and hemispheric background levels. Although a main regional contribution was evidenced, emissions of local precursors within the Madrid urban plume play a key role in the generation of O3 exceedances, which are higher and occur earlier near the city than at rural sites, where the effect of NO titration is lower. Despite the fact that weekend emissions of O3 precursors in Madrid are typically lower than on weekdays, mainly due to fewer road traffic emissions, there is little difference in average values of weekday and weekend O3. However, more subtle “weekend effect” differences are revealed by probability density analysis, with high O3 and low NO2 at the highest temperature range (30-35° C) at weekends reflecting lower NO titration. This analysis highlights the importance of NO timing with respect to the photochemical activity timing. The complexity of these O3 pollution patterns in and around the city is dependent on an ever-changing interplay between weather conditions, emission sources, and the timescale required for pollutant transport, chemical processing and recirculation in an evolving contaminated airmass.

Widespread anatoxin-a detection in benthic cyanobacterial mats throughout a river network.

Benthic algae fuel summer food webs in many sunlit rivers, and are hotspots for primary and secondary production and biogeochemical cycling. Concerningly, riverine benthic algal assemblages can become dominated by toxic cyanobacteria, threatening water quality and public health. In the Eel River in Northern California, over a dozen dog deaths have been attributed to cyanotoxin poisonings since 2000. During the summers of 2013–2015, we documented spatial and temporal patterns of cyanotoxin concentrations in the watershed, showing widespread distribution of anatoxin-a in benthic cyanobacterial mats. Solid phase adsorption toxin tracking (SPATT) samplers were deployed weekly to record dissolved microcystin and anatoxin-a levels at 10 sites throughout the watershed, and 187 Anabaena-dominated or Phormidium-dominated cyanobacterial mat samples were collected from 27 locations to measure intracellular anatoxin-a (ATX) and microcystins (MCY). Anatoxin-a levels were higher than microcystin for both SPATT (mean MCY = 0.8 and ATX = 4.8 ng g resin-1 day-1) and cyanobacterial mat samples (mean MCY = 0.074 and ATX = 1.89 μg g-1 DW). Of the benthic mats sampled, 58.9% had detectable anatoxin-a (max = 70.93 μg g-1 DW), while 37.6% had detectable microcystins (max = 2.29 μg g-1 DW). SPATT cyanotoxin levels peaked in mid-summer in warm mainstem reaches of the watershed. This is one of the first documentations of widespread anatoxin-a occurrence in benthic cyanobacterial mats in a North American watershed.

Global radiative effects of solid fuel cookstove aerosol emissions

Abstract. We apply the NCAR CAM5-Chem global aerosol-climate model to quantify the net global radiative effects of black and organic carbon aerosols from global and Indian solid fuel cookstove emissions for the year 2010. Our assessment accounts for the direct radiative effects, changes to cloud albedo and lifetime (aerosol indirect effect, AIE), impacts on clouds via the vertical temperature profile (semi-direct effect, SDE) and changes in the surface albedo of snow and ice (surface albedo effect). In addition, we provide the first estimate of household solid fuel black carbon emission effects on ice clouds. Anthropogenic emissions are from the IIASA GAINS ECLIPSE V5a inventory. A global dataset of black carbon (BC) and organic aerosol (OA) measurements from surface sites and aerosol optical depth (AOD) from AERONET is used to evaluate the model skill. Compared with observations, the model successfully reproduces the spatial patterns of atmospheric BC and OA concentrations, and agrees with measurements to within a factor of 2. Globally, the simulated AOD agrees well with observations, with a normalized mean bias close to zero. However, the model tends to underestimate AOD over India and China by ∼ 19 ± 4 % but overestimate it over Africa by ∼ 25 ± 11 % (± represents modeled temporal standard deviations for n = 5 run years). Without BC serving as ice nuclei (IN), global and Indian solid fuel cookstove aerosol emissions have net global cooling radiative effects of −141 ± 4 mW m−2 and −12 ± 4 mW m−2, respectively (± represents modeled temporal standard deviations for n = 5 run years). The net radiative impacts are dominated by the AIE and SDE mechanisms, which originate from enhanced cloud condensation nuclei concentrations for the formation of liquid and mixed-phase clouds, and a suppression of convective transport of water vapor from the lower troposphere to the upper troposphere/lower stratosphere that in turn leads to reduced ice cloud formation. When BC is allowed to behave as a source of IN, the net global radiative impacts of the global and Indian solid fuel cookstove emissions range from −275 to +154 mW m−2 and −33 to +24 mW m−2, with globally averaged values of −59 ± 215 and 0.3 ± 29 mW m−2, respectively. Here, the uncertainty range is based on sensitivity simulations that alter the maximum freezing efficiency of BC across a plausible range: 0.01, 0.05 and 0.1. BC–ice cloud interactions lead to substantial increases in high cloud (< 500 hPa) fractions. Thus, the net sign of the impacts of carbonaceous aerosols from solid fuel cookstoves on global climate (warming or cooling) remains ambiguous until improved constraints on BC interactions with mixed-phase and ice clouds are available.

Quantification of polychlorinated biphenyl contamination using human placenta as biomarker from Punjab Province, Pakistan.

The present study biomonitored the placental polychlorinated biphenyl (PCB) concentrations in women from Punjab Province, Pakistan, that provides the pioneer data for occurrence and body burden of PCBs in placental tissues from South Asian women. The ∑34PCB concentrations in placental tissues were ranged from 20.2 to 115.98ng/g lipid weight (lip. wt.), with predominance of tetra-PCB (54.67%). The levels of ∑8DL-PCBs and ∑6-indicator PCBs were ranged from 2.03 to 27.64ng/g (lip. wt.) and 1.71 to 30.8ng/g (lip. wt.), respectively. The WHO-TEQ2005 values for DL-PCBs were ranged from 1.18 × 10-5 to 0.067ng/g (lip. wt.), with highest value evaluated for CB-126. The estimated daily intake (EDI) for DL-PCBs was ranged from 9.27 × 10-8 to 5.25 × 10-4pg WHO-TEQ/kg body weight (bw), which was within the tolerable daily intake (TDI) values established by international organizations. The spatial distribution patterns of Σ34PCB concentrations from study area have shown relative higher concentrations in samples from urban and industrial cities than rural areas, and industrial and urban releases along with e-waste handling were recognized as vital PCB sources in the environment. In order to ascertain the transplacental transfer of PCBs, the fetal growth parameters were correlated with the ∑34PCB concentrations in placental tissues. The relationship between ∑34PCB concentrations in placental tissues and infant's anthropometric measures through multiple linear regression showed a negative correlation of infant's body weight (R2= 0.0728), crown to heel length (R2= 0.068), head circumference (R2= 0.0342), chest circumference (R2= 0.0001), and mid arm circumference (R2= 0.0096) that noticeably highlights the inhibited fetal anthropometric development associated with maternal PCB bioaccumulation. Hence, an immediate elimination of ongoing PCB addition in the studied area has been emphasized and further investigations are suggested to appropriately manage the public and neonatal health risks in the region.

Evaluation of missing value methods for predicting ambient BTEX concentrations in two neighbouring cities in Southwestern Ontario Canada

High density air monitoring campaigns provide spatial patterns of pollutant concentrations which are integral in exposure assessment. Such analysis can assist with the determination of links between air quality and health outcomes, however, problems due to missing data can threaten to compromise these studies. This research evaluates four methods; mean value imputation, inverse distance weighting (IDW), inter-species ratios, and regression, to address missing spatial concentration data ranging from one missing data point up to 50% missing data. BTEX (benzene, toluene, ethylbenzene, and xylenes) concentrations were measured in Windsor and Sarnia, Ontario in the fall of 2005. Concentrations and inter-species ratios were generally similar between the two cities. Benzene (B) was observed to be higher in Sarnia, whereas toluene (T) and the T/B ratios were higher in Windsor. Using these urban, industrialized cities as case studies, this research demonstrates that using inter-species ratios or regression of the data for which there is complete information, along with one measured concentration (i.e. benzene) to predict for missing concentrations (i.e. TEX) results in good agreement between predicted and measured values. In both cities, the general trend remains that best agreement is observed for the leave-one-out scenario, followed by 10% and 25% missing, and the least agreement for the 50% missing cases. In the absence of any known concentrations IDW can provide reasonable agreement between observed and estimated concentrations for the BTEX species, and was superior over mean value imputation which was not able to preserve the spatial trend. The proposed methods can be used to fill in missing data, while preserving the general characteristics and rank order of the data which are sufficient for epidemiologic studies.

Distribution and mass of groundwater orthophosphorus in an agricultural watershed

Orthophosphorus (OP) is the form of dissolved inorganic P that is commonly measured in groundwater studies, but the spatial distribution of groundwater OP across a watershed has rarely been assessed. In this study, we characterized spatial patterns of groundwater OP concentrations and loading rates within the 5218ha Walnut Creek watershed (Iowa) over a two-year period. Using a network of 24 shallow (<6m) monitoring wells established across watershed, OP concentrations ranged from <0.01 to 0.58mg/l in all samples (n=147) and averaged 0.084±0.107mg/l. Groundwater OP concentrations were higher in floodplains and OP mass loading rates were approximately three times higher than in uplands. We estimated that approximately 1231kg of OP is present in floodplain groundwater and 2869kg is present in upland groundwater within the shallow groundwater zone (0–5m depth). Assuming no new inputs of OP to shallow groundwater, we estimated it would take approximately eight years to flush out existing OP mass present in the system. Results suggest that conservation practices focused on reducing OP loading rates in floodplain areas may have a disproportionately large water quality benefit compared to upland areas.

Characterization of air pollutant concentrations, fleet emission factors, and dispersion near a North Carolina interstate freeway across two seasons

We present field measurement data and modeling of multiple traffic-related air pollutants during two seasons at a site adjoining Interstate 40, near Durham, North Carolina. We analyze spatial-temporal and seasonal trends and fleet-average pollutant emission factors and use our data to evaluate a line source dispersion model. Month-long measurement campaigns were performed in summer 2015 and winter 2016. Data were collected at a fixed near-road site located within 10 m from the highway edge, an upwind background site and, under favorable meteorological conditions, along downwind perpendicular transects. Measurements included the size distribution, chemical composition, and volatility of submicron particles, black carbon (BC), nitrogen oxides (NOx), meteorological conditions and traffic activity data. Results show strong seasonal and diurnal differences in spatial distribution of traffic sourced pollutants. A strong signature of vehicle emissions was observed within 100–150 m from the highway edge with significantly higher concentrations during morning. Substantially higher concentrations and less-sharp near-road gradients were observed in winter for many species. Season-specific fleet-average fuel-based emission factors for NO, NOx, BC, and particle number (PN) were derived based on up- and down-wind roadside measurements. The campaign-average NOx and PN emission factors were 20% and 300% higher in winter than summer, respectively. These results suggest that the combined effect of higher emissions and their slower downwind dispersion in winter dictate the observed higher downwind concentrations and wider highway influence zone in winter for several species. Finally, measurements of traffic data, emission factors, and pollutant concentrations were integrated to evaluate a line source dispersion model (R-LINE). The dispersion model captured the general trends in the spatial and temporal patterns in near-road concentrations. However, there was a tendency for the model to under-predict concentrations near the road in the mornings and over-predict concentrations in the evenings.

Multivariate analyses of the effect of an urban wastewater treatment plant on spatial and temporal variation of water quality and nutrient distribution of a tropical mid-order river.

Freshwater resources are increasingly scarce due to human activities, and the understanding of water quality variations at different spatial and temporal scales is necessary for adequate management. Here, we analyze the hypotheses that (1) the presence of a wastewater treatment plant (WWTP) and (2) a polluted tributary that drains downstream from the WWTP change the spatial patterns of physicochemical variables (pH, turbidity, dissolved oxygen, and electrical conductivity) and nutrient concentrations (reactive soluble phosphorus, total phosphorus, nitrogen series, total nitrogen, and total dissolved carbon) along a mid-order river in SE Brazil and that these effects depend on rainfall regime. Six study sites were sampled along almost 4years to evaluate the impacts of human activities, including sites upstream (1-3) and downstream (5-6) from the WWTP. The impacts were observed presenting an increasing trend from the source (site 1) towards Água Quente stream (site 4, the polluted tributary), with signs of attenuation at site 5 (downstream from both WWTP and site 4) and the river mouth (site 6). Input of nutrients by rural and urban runoff was observed mainly at sites 2 and 3, respectively. At sites 4 and 5, the inputs of both untreated and treated wastewaters increased nutrient concentrations and changed physicochemical variables, with significant impacts to Monjolinho River. Seasonal variations in the measured values were also observed, in agreement with the pluviometric indexes of the region. Univariate analyses suggested no effect of the WWTP for most variables, with continued impacts at sites downstream, but non-parametric multivariate analysis indicated that these sites were recovering to chemical characteristics similar to upstream sites, apparently due to autodepuration. Therefore, multivariate methods that allow rigorous tests of multifactor hypotheses can greatly contribute to determine effects of both point and non-point sources in river systems, thus contributing to freshwater monitoring and management.

Numerical modelling of temporal and spatial patterns of petroleum hydrocarbons concentration in the Bohai Sea

The discharge of petroleum hydrocarbons (PHs; ~10,000tons annually) into the Bohai Sea, a shallow inland sea in China, presents a serious threat to the marine environment. To evaluate the effects of PHs pollution and estimate the corresponding environmental capacity, we have developed a genetic algorithm-based coupled hydrodynamic/transport for simulating PHs concentration evolution and distribution from July 2006 to October 2007, with the predicted values being in good agreement with monitoring results. Importantly, the mean PHs concentrations and seasonal concentration variations were primarily determined by external loading, i.e., currents were shown to drive PHs transport, reconfigure local PHs patterns, and increase PHs concentration in water masses, even at large distances from discharge sources. The developed model could realistically simulate PHs distribution and evolution, thus being a useful tool for estimating the seasonal environmental capacity of PHs.

Predicting macroalgal pigments (chlorophyll a, chlorophyll b, chlorophyll a + b, carotenoids) in various environmental conditions using high-resolution hyperspectral spectroradiometers

ABSTRACTPhotosynthetic pigments may indicate the health and productivity of vegetation and thereby are among the most important targets of the remote-sensing science. We studied the relationship between macroalgae pigment concentration measured in situ and spectral reflectance, to develop predictive remote-sensing methods for macroalgal pigments. The measurements of spectral reflectance of macroalgae were made using both a field portable spectrometer Ramses built by TriOS GmbH (Germany) and a laboratory hyperspectral imaging device HySpex built by Norsk Elektro Optikk (Norway). Our results showed that differences in total chlorophyll (Chl-a + b) concentrations resulted in the consistent change of spectral reflectance for studied brown (Fucus vesiculosus) and green (Cladophora glomerata, Ulva intestinalis) macroalgae species. Charophytes (Chara aspera, Chara horrida) were also studied, and the relationship was much weaker for this taxon. If spectral indices predicted relatively well the concentration of Chl-a + b (R2 = 0.64–0.73) and the carotenoid to total chlorophyll ratio (Car:Chl-a + b, R2 = 0.80) across the five studied macroalgae species, then the concentration of chlorophyll a (Chl-a), chlorophyll b (Chl-b), and carotenoids (Car) were more difficult to model (R2 = 0.004–0.51). The HySpex imaging system yielded systematically better results in predicting pigment concentrations compared to the Ramses spectroradiometer. By using traditional assessment of pigment concentration along with the Hyspex imaging device, we were able to build models with a capability to predict the spatial patterns of pigment concentration for Baltic Sea macroalgae.

Spatial Simulation of Black Carbon Concentrations Based on a Land Use Regression Model and Mobile Monitoring over Shanghai, China

Black carbon (BC) is an important component of atmospheric pollution and has significant impacts on air quality and human health. Choosing Shanghai city for a case study, this paper explores the statistical characteristics and spatial patterns of BC concentrations using a mobile monitoring method, which differs from traditional fixed-site observations. Land use regression (LUR) modeling was conducted to examine the determinants for on-road BC concentrations, e.g. population, economic development, traffic, etc. These results showed that the average on-road BC concentrations were (9.86±8.68) μg·m-3, with a significant spatial variation. BC concentrations in suburban areas[(10.47±2.04) μg·m-3] were 32.03% (2.54 μg·m-3) higher than those in the city center[(7.93±2.79) μg·m-3]. Besides, meteorological factors (e.g. wind speed and relative humidity) and traffic variables (e.g. the length of roads, distance to provincial roads, distance to highway) had significant effects on on-road BC concentrations (r:0.5-0.7, P<0.01). Moreover, the LUR model, including meteorological and traffic variables performed well (adjusted R2:0.62-0.75, cross validation R2:0.54-0.69, RMSE:0.15-0.20 μg·m-3), which demonstrates that on-road BC concentrations in Shanghai are mainly affected by these factors and traffic sources to some extent. Among them, the most accurate LUR model was developed with a 100 m buffer, followed by the LUR model with a 5 km buffer. This study is of great significance for the identification of spatial distribution patterns for on-road BC concentration and exploring their influencing factors in Shanghai, which can provide a scientific basis and theoretical support for simulating and predicting the response mechanisms of BC on human health and the natural environment.

Additive Models Reveal Sources of Metals and Organic Pollutants in Norwegian Marine Sediments

We characterized spatial patterns of surface sediment concentrations of seven polychlorinated biphenyls (PCBs), seven polycyclic aromatic hydrocarbons (PAHs), three chlorinated pesticides, and five metals in Norwegian waters and Skagerrak. In total, we analyzed 5036 concentrations of 22 chemical substances that were measured between 1986 and 2014 at 333 sampling sites by means of generalized additive models (GAMs). We found that GAMs with organic carbon content of the sediment and latitude and longitude as co-variates explained as ca. 75% of the variability of the contaminant sediment concentrations. For metals, a predominantly hotspot-driven spatial pattern was found, i.e., we identified historical pollution hotspots (e.g., Sørfjord in western Norway) for mercury, zinc, cadmium, and lead. Highest concentrations of PAHs and PCBs were found close to densely populated and industrialized regions, i.e., in the North Sea and in the Kattegat and Skagerrak. The spatial pattern of the PCBs suggests the secondary and diffuse atmospheric nature of their sources. Atmospheric inputs are the main sources of pollution for most organic chemicals considered, but north of the Arctic circle, we found that concentrations of PAHs increased from south to north most likely related to a combination of coal-eroding bedrock and the biological pump. The knowledge acquired in the present research is essential for developing effective remediation strategies that are consistent with international conventions on pollution control.

Using spatial-stream-network models and long-term data to understand and predict dynamics of faecal contamination in a mixed land-use catchment

An 11year dataset of concentrations of E. coli at 10 spatially-distributed sites in a mixed land-use catchment in NE Scotland (52km2) revealed that concentrations were not clearly associated with flow or season. The lack of a clear flow-concentration relationship may have been due to greater water fluxes from less-contaminated headwaters during high flows diluting downstream concentrations, the importance of persistent point sources of E. coli both anthropogenic and agricultural, and possibly the temporal resolution of the dataset. Point sources and year-round grazing of livestock probably obscured clear seasonality in concentrations. Multiple linear regression models identified potential for contamination by anthropogenic point sources as a significant predictor of long-term spatial patterns of low, average and high concentrations of E. coli. Neither arable nor pasture land was significant, even when accounting for hydrological connectivity with a topographic-index method. However, this may have reflected coarse-scale land-cover data inadequately representing “point sources” of agricultural contamination (e.g. direct defecation of livestock into the stream) and temporal changes in availability of E. coli from diffuse sources. Spatial-stream-network models (SSNMs) were applied in a novel context, and had value in making more robust catchment-scale predictions of concentrations of E. coli with estimates of uncertainty, and in enabling identification of potential “hot spots” of faecal contamination. Successfully managing faecal contamination of surface waters is vital for safeguarding public health. Our finding that concentrations of E. coli could not clearly be associated with flow or season may suggest that management strategies should not necessarily target only high flow events or summer when faecal contamination risk is often assumed to be greatest. Furthermore, we identified SSNMs as valuable tools for identifying possible “hot spots” of contamination which could be targeted for management, and for highlighting areas where additional monitoring could help better constrain predictions relating to faecal contamination.