Modelling the spatial distribution of ammonia emissions in the UK

Ammonia emissions (NH3) are characterised by a high spatial variability at a local scale. When modelling the spatial distribution of NH3 emissions, it is important to provide robust emission estimates, since the model output is used to assess potential environmental impacts, e.g. exceedance of critical loads. The aim of this study was to provide a new, updated spatial NH3 emission inventory for the UK for the year 2000, based on an improved modelling approach and the use of updated input datasets. The AENEID model distributes NH3 emissions from a range of agricultural activities, such as grazing and housing of livestock, storage and spreading of manures, and fertilizer application, at a 1-km grid resolution over the most suitable landcover types. The results of the emission calculation for the year 2000 are analysed and the methodology is compared with a previous spatial emission inventory for 1996.     

Medium scale spatial structures of Polycyclic Aromatic Hydrocarbons in the topsoil of Tianjin area

The spatial distribution patterns of Polycyclic Aromatic Hydrocarbons (PAHs) in soil are important to regional environmental assessment. In this paper, the spatial structural features of sixteen prior PAH compounds in the topsoil of Tianjin area, as well as soil properties, were studied. Results shown that medium scale spatial autocorrelations were well revealed. Spherical models with sills could be used to fit all experimental variograms. The spatial structures of PAHs contents demonstrated significant anisotropy. Air precipitation caused by the combustion of coal was the key factor in the formation of the spatial structural patterns of PAHs in the topsoil of Tianjin area.     

Medium Scale Spatial Structures of Polycyclic Aromatic Hydrocarbons in the Topsoil of Tianjin Area

The spatial distribution patterns of Polycyclic Aromatic Hydrocarbons (PAHs) in soil are important to regional environmental assessment. In this paper, the spatial structural features of sixteen prior PAH compounds in the topsoil of Tianjin area, as well as soil properties, were studied. Results shown that medium scale spatial autocorrelations were well revealed. Spherical models with sills could be used to fit all experimental variograms. The spatial structures of PAHs contents demonstrated significant anisotropy. Air precipitation caused by the combustion of coal was the key factor in the formation of the spatial structural patterns of PAHs in the topsoil of Tianjin area.     

Analysis of the spatial distribution of collectors in dust scrubber based on image processing

The spatial distribution of the collectors in dust scrubber is key in determining the effectiveness of the dust removal process. In the present study, a high-speed camera was used to capture images of the distribution of the collectors. Some of the image information was extracted by image processing, such as the gray mean (GM), the angular second moment (ASM), and the entropy (ENT) from the gray-level co-occurrence matrix of the image. Subsequently, the spatial distribution rules of the collectors were studied by analyzing the spatial proportion, dispersion area, and uniformity and intensiveness of the collectors. It is an intuitive approach and a novel analysis method for the operating state of dust scrubber. The results show that the spatial distribution of the collectors could be better reflected by image processing methods. The dispersion area of the collectors expanded with an increase in the airflow velocity. When the initial liquid level (ILL) was higher, the collectors expanded in an approximate circular shape, and when the ILL was lower the collectors expanded in an approximate sector shape. In general, the variation trend in the spatial proportion enhanced with an increase in ILL and airflow velocity, which is consistent with the uniformity of collectors. When the liquid level was 0?20 mm and the airflow velocity was greater than 6.5 m/sec, the spatial proportion and uniformity of the collectors reached the highest degree. However, the growth rate of the spatial proportion and uniformity of the collectors slowed down and even led to negative growth when the ILL was lower and the airflow velocity was higher. The intensiveness of the collectors was great when the ILL was higher, which was free from the apparent influence of the airflow velocity and the ILL. However, when the ILL was lower, the intensiveness of the collectors was poor, intensifying as the airflow velocity and ILL increased. When the liquid level was ?5?10 mm and the airflow velocity was greater than 8 m/sec, the intensiveness of the collectors reached the highest degree, indicating that a liquid level greater than 0 mm and a higher airflow velocity improved the spatial distribution of the collectors.

Implications: This paper focuses on the spatial distribution of the collectors in dust scrubber. Some of the image information was extracted by image processing, such as the gray mean of the image, the angular second moment, and the entropy from the gray-level co-occurrence matrix of the image. The spatial distribution rules of the collectors were studied by analyzing the spatial proportion, the dispersion area, and the uniformity and intensiveness of the collectors.     

Environmental filtering in the dry season and spatial structuring in the wet: different fish community assembly rules revealed in a large subtropical floodplain lake

Although environmental filtering and spatial structuring are commonly regarded as two key factors shaping community dynamics, their relative contribution remains unknown for numerous aquatic ecosystems, particularly highly dynamic floodplain lakes. This issue is here addressed by examining the seasonal metacommunity dynamics of freshwater fishes in Lake Dongting, a large subtropical lake of the middle Chang-Jiang basin in southern China. Physicochemical variables and fish assemblages were recorded at 20 sampling sites during the wet, normal, and dry seasons. Distance-based redundancy analysis and associated variation partitioning were used to examine the relative role of environmental variables and spatial factors in fish community assembly in each season. Analysis results demonstrated that the relative contribution of environmental filtering and spatial structuring varied depending on environmental features and the extent of hydrological connectivity in different seasons. Intensified physicochemical parameters in the dry season convinced the enhanced environmental filtering, whereas high hydrological connectivity in the wet season favored the stronger spatial process. Specifically, the community assembly processes were temporally dynamic; spatial structuring (or mass effects), resulting from excessively high dispersal rates, was dominant during the flooding season, and environmental filtering was stronger than spatial structuring (or dispersal limitation) during the non-flooding season. These findings highlight the importance of conserving local habitats of Lake Dongting during the dry and normal seasons, and maintaining of the flood pulse of the lake and its natural variability during the wet season. Apparently, the construction of a water-level regulation project at the Chenglingji Channel, the outlet watercourse of Lake Dongting, is not supported because it will change the flood pulse of this lake and thus impact habitat heterogeneity or variability.

     

Spatial variations of concentrations of copper and its speciation in the soil-rice system in Wenling of southeastern China

Copper (Cu) is one of the essential elements for plant growth, while excessive Cu in soils has potential environmental risks. There is little information on spatial variation of Cu in practical paddy fields. This is now important for appropriate agricultural management. The spatial patterns of Cu, its fractions in soils, and its concentrations in rice were investigated in a typical rice production region—Wenling of southeastern China. A total of 96 pairs of rice grain and soil samples (0–15 cm) were collected. The total concentration of Cu and its fractions were very variable, with large skewness, kurtosis, and coefficient of variation (CV) values. Compared to the guideline value (50 mg kg^?1), Cu pollution in paddy fields was observed in the study area. All the measured Cu concentrations in rice were lower than 10 mg kg^?1, suggesting that they remained at a safe level. Spatial analyses including Moran’s I index and geostatistics results indicated that high-high spatial patterns for both Cu in soils and rice were found in the northwest part, which was mainly related to industrial and E-waste dismantling activities. The low-low spatial patterns of Cu in the soil-rice system were located in the south part of study area. The cross-correlogram results indicated that Cu concentration in rice was significantly spatially correlated with total Cu in soils, its fractions, and soil organic matter (SOM), but significantly negatively correlated with pH and electrical conductivity (EC). Most of the selected variables had a clear spatial correlation range with Cu in rice. The ranges of significant spatial correlation (p?<?0.05) could be obtained and further used for dividing agricultural management zones.     

Transport of atmospheric fine particulate matter: part 2--findings from recent field programs on the intraurban variability in fine particulate matter

Air quality field data, collected as part of the fine particulate matter Supersites Program and other field measurements programs, have been used to assess the degree of intraurban variability for various physical and chemical properties of ambient fine particulate matter. Spatial patterns vary from nearly homogeneous to quite heterogeneous, depending on the city, parameter of interest, and the approach or method used to define spatial variability. Secondary formation, which is often regional in nature, drives fine particulate matter mass and the relevant chemical components toward high intraurban spatial homogeneity. Those particulate matter components that are dominated by primary emissions within the urban area, such as black carbon and several trace elements, tend to exhibit greater spatial heterogeneity. A variety of study designs and data analysis approaches have been used to characterize intraurban variability. High temporal correlation does not imply spatial homogeneity. For example, there can be high temporal correlation but with spatial heterogeneity manifested as smooth spatial gradients, often emanating from areas of high emissions such as the urban core or industrial zones.     

Spatial variability of PM2.5 in urban areas in the United States

Data from the U.S. Environmental Protection Agency's Aerometric Information Retrieval System (now known as the Air Quality System) database for 1999 and 2000 have been used to characterize the spatial variability of concentrations of particulate matter with aerodynamic diameter < or = 2.5 microg (PM2.5) in 27 urban areas across the United States. Different measures were used to quantify the degree of uniformity of PM2.5 concentrations in the urban areas characterized. It was observed that PM2.5 concentrations varied to differing degrees in the urban areas examined. Analyses of several urban areas in the Southeast indicated high correlations between site pairs and spatial uniformity in concentration fields. Considerable spatial variation was found in other regions, especially in the West. Even within urban areas in which all site pairs were highly correlated, a variable degree of heterogeneity in PM2.5 concentrations was found. Thus, even though concentrations at pairs of sites were highly correlated, their concentrations were not necessarily the same. These findings indicate that the potential for exposure misclassification errors in time-series epidemiologic studies exists.     

Transport of Atmospheric Fine Particulate Matter: Part 2—Findings from Recent Field Programs on the Intraurban Variability in Fine Particulate Matter

Abstract

Air quality field data, collected as part of the fine particulate matter Supersites Program and other field measurements programs, have been used to assess the degree of intraurban variability for various physical and chemical properties of ambient fine particulate matter. Spatial patterns vary from nearly homogeneous to quite heterogeneous, depending on the city, parameter of interest, and the approach or method used to define spatial variability. Secondary formation, which is often regional in nature, drives fine particulate matter mass and the relevant chemical components toward high intraurban spatial homogeneity. Those particulate matter components that are dominated by primary emissions within the urban area, such as black carbon and several trace elements, tend to exhibit greater spatial heterogeneity. A variety of study designs and data analysis approaches have been used to characterize intraurban variability. High temporal correlation does not imply spatial homogeneity. For example, there can be high temporal correlation but with spatial heterogeneity manifested as smooth spatial gradients, often emanating from areas of high emissions such as the urban core or industrial zones.     

Spatial Variability of PM2.5 in Urban Areas in the United States

Abstract

Data from the U.S. Environmental Protection Agency's Aerometric Information Retrieval System (now known as the Air Quality System) database for 1999 and 2000 have been used to characterize the spatial variability of concentrations of particulate matter with aerodynamic diameter ≤2.5 μg (PM_2.5) in 27 urban areas across the United States. Different measures were used to quantify the degree of uniformity of PM_2.5 concentrations in the urban areas characterized. It was observed that PM_2.5 concentrations varied to differing degrees in the urban areas examined. Analyses of several urban areas in the Southeast indicated high correlations between site pairs and spatial uniformity in concentration fields. Considerable spatial variation was found in other regions, especially in the West. Even within urban areas in which all site pairs were highly correlated, a variable degree of heterogeneity in PM_2.5 concentrations was found. Thus, even though concentrations at pairs of sites were highly correlated, their concentrations were not necessarily the same. These findings indicate that the potential for exposure misclassification errors in time-series epidemiologic studies exists.     

Small-scale spatial and temporal variance in the concentration of heavy metals in aquatic sediments: a review and some new concepts.

Uncertainty associated with data derived by the analyses of heavy metals in aquatic sediment is due to variance produced in the laboratory (precision), plus 'natural', small-scale spatial variance, (or field variance) at the sampling site. Precision is easily determined and is usually reported in contaminant studies, but field variance is poorly understood and seldom documented. It is important to have an understanding of the field variance because if small-scale spatial variance in the concentration of heavy metals is excessive, regional trends may be limited value. Similarly, if temporal change is large, the results of single synoptic surveys may be questionable and the ability to demonstrate anthropogenic contributions over time will be difficult. However, it is evident from the literature that the information needed to address problems of spatial and temporal variance in the field is beyond the resources of most researchers. Analytical precision of about 5% relative standard deviation (RSD) for heavy metal analysis is typical of a well-managed laboratory. Many studies of small-scale spatial variability made during the current investigation indicate that field variance is related to ambient energy and to the type of sedimentological environment. Total variance (analytical plus field variance) is approximately 10% RSD (mean for a suite of nine trace elements) for depositional parts of estuaries and the marine environment, but increases to about 20-35% RSD for the more dynamic parts of the estuarine environment and the fluvial system. Repeated sampling over periods of up to 7 years undertaken during the present study, indicate a similar order of magnitude for temporal variability in these sedimentological environments. A proposed scheme to provide information on field variance is to undertake small-scale spatial and temporal studies in discrete sedimentological environments in the study area after sediment sampling and characterisation has been completed. The comparatively large proportion of total variance associated with small-scale spatial and temporal variability in the field questions the often excessive cost and effort made in attempting minor reductions in analytical precision in contaminant investigations.     

Spatial characteristics and influential mechanism of the coupling coordination degree of urban accessibility and human development index in China

To optimize the accessibility algorithm and quantify the potential relationship between human development index and traffic comprehensive accessibility system, this paper analyzed the spatial distribution pattern of urban accessibility and human development index of highway, railway, and aviation transportation systems using data on highway, railway, and aviation schedules based on GIS spatial analysis method. Furthermore, the coupling degree between human development index and accessibility and its influence mechanism on the city level in China were explored based on the super-efficiency data envelopment analysis model. Results showed as follows: (1) Spatial distribution of human development index from high to low was gradually changing from east to west. The spatial distribution of urban accessibility of the three traffic systems had an evident “Hu Huanyong Line” effect. (2) The coordination degree of urban accessibility and human development index spread in a ladder mode. High coordination of cities in North and East China and the central Yangtze River region forms the spatial distribution of urban development circles connecting an urban development belt. (3) Railway connectivity and control value were highly sensitive to human development index in cities where serious imbalance between accessibility and human development index. Highway connectivity and control value were highly sensitive to human development index in cities where high coordination between accessibility and human development index. The results would provide scientific references for spatial planning of transportation, economic, and social development of cities and coordinated development of urban agglomeration in China.

     

Stochastic analysis to assess the spatial distribution of groundwater nitrate concentrations in the Po catchment (Italy)

A large database including temporal trends of physical, ecological and socio-economic data was developed within the EUROCAT project. The aim was to estimate the nutrient fluxes for different socio-economic scenarios at catchment and coastal zone level of the Po catchment (Northern Italy) with reference to the Water Quality Objectives reported in the Water Framework Directive (WFD 2000/60/CE) and also in Italian legislation. Emission data derived from different sources at national, regional and local levels are referred to point and non-point sources. While non-point (diffuse) sources are simply integrated into the nutrient flux model, point sources are irregularly distributed. Intensive farming activity in the Po valley is one of the main Pressure factors Driving groundwater pollution in the catchment, therefore understanding the spatial variability of groundwater nitrate concentrations is a critical issue to be considered in developing a Water Quality Management Plan. In order to use the scattered point source data as input in our biogeochemical and transport models, it was necessary to predict their values and associated uncertainty at unsampled locations. This study reports the spatial distribution and uncertainty of groundwater nitrate concentration at a test site of the Po watershed using a probabilistic approach. Our approach was based on geostatistical sequential Gaussian simulation used to yield a series of stochastic images characterized by equally probable spatial distributions of the nitrate concentration across the area. Post-processing of many simulations allowed the mapping of contaminated and uncontaminated areas and provided a model for the uncertainty in the spatial distribution of nitrate concentrations.     

Intake fraction distributions for benzene from vehicles in the Helsinki metropolitan area

The intake fraction (iF) gives a measure of the portion of a source's emissions that is inhaled by an exposed population over a defined period of time. This study examines spatial and population-based iF distributions of a known human carcinogen, benzene, from a ubiquitous urban source, local vehicular traffic, in the Helsinki Metropolitan Area using three computational methods. The first method uses the EXPAND model (EXPosure to Air pollution, especially to Nitrogen Dioxide and particulate matter), which incorporates spatial and temporal information on population activity patterns as well as urban-scale and street canyon dispersion models to predict spatial population exposure distributions. The second method uses data from the personal monitoring study EXPOLIS (Air Pollution Exposure Distributions of Adult Urban Populations in Europe) to estimate the intake fractions for individuals in the study. The third method, a one-compartment box model provides estimates within an order-of-magnitude or better for non-reactive agents in an urban area. Population intake fractions are higher using the personal monitoring data method (median iF 30 per million, mean iF 39 per million) compared with the spatial model (annual mean iF 10 per million) and the box model (median iF 4 per million, mean iF 7 per million). In particular, this study presents detailed intake fraction distributions on several different levels (spatial, individual, and generic) for the same urban area.     

Characterization of spatially homogeneous regions based on temporal patterns of fine particulate matter in the continental United States

Statistical analyses of time-series or spatial data have been widely used to investigate the behavior of ambient air pollutants. Because air pollution data are generally collected in a wide area of interest over a relatively long period, such analyses should take into account both spatial and temporal characteristics. The objective of this study is 2-fold: (1) to identify an efficient way to characterize the spatial variations of fine particulate matter (PM2.5) concentrations based solely upon their temporal patterns, and (2) to analyze the temporal and seasonal patterns of PM2.5 concentrations in spatially homogenous regions. This study used 24-hr average PM2.5 concentrations measured every third day during a period between 2001 and 2005 at 522 monitoring sites in the continental United States. A k-means clustering algorithm using the correlation distance was used to investigate the similarity in patterns between temporal profiles observed at the monitoring sites. A k-means clustering analysis produced six clusters of sites with distinct temporal patterns that were able to identify and characterize spatially homogeneous regions of the United States. The study also presents a rotated principal component analysis (RPCA) that has been used for characterizing spatial patterns of air pollution and discusses the difference between the clustering algorithm and RPCA.     

Spatial variability of bacteria in the rhizosphere of Elsholtzia splendens under Cu contamination

Elsholtzia splendens is a well-known Cu-tolerant plant; yet, the impact of Cu-contaminated soil on bacterial community in its rhizosphere is not known. We studied the spatial variability of bacteria in the rhizosphere using Cu-contaminated soil with polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and real-time PCR. In the uncontaminated soil, the content of the dissolved organic carbon (DOC) and bacterial diversity gradually increased in the rhizosphere soil along the root growth direction (from the interface zone to the meristematic zone), while for the Cu-contaminated soil, the highest DOC content and the strongest potential bioavailability of Cu were found in the interface zone, which also had the lowest bacteria diversity. Bacteria diversity was positively correlated with DOC in the uncontaminated soil (p?Firmicutes only existed in the rhizosphere of contaminated soil, while the very small amount (if any) of some species exists such as Deinococcus-Thermus, indicating that the contaminated environment altered the bacterial composition. Moreover, spatial variation of the bacterial community was found among different soil zones. Real-time PCR confirmed the spatial variation via the gene expression of flagellin (fliC) and chemotaxis gene (cheA). The spatial characteristics of cheA expression were consistent with that of DOC and bacterial diversity. In conclusion, we demonstrated that the spatial variation of the bacterial community in the rhizosphere was present, independent of Cu contamination. DOC and Cu toxicity may affect specific gene expressions such as fliC and cheA, resulting in bacterial spatial variation.     

Contamination potential of nitrogen compounds in the heterogeneous aquifers of the Choushui River alluvial fan, Taiwan

This study aimed to analyze the contamination potential associated with the reactive transport of nitrate-N and ammonium-N in the Choushui River alluvial fan, Taiwan and to evaluate a risk region in developing a groundwater protection policy in 2021. In this area, an aquifer redox sequence provided a good understanding of the spatial distributions of nitrate-N and ammonium-N and of aerobic and anaerobic environments. Equiprobable hydraulic conductivity (K) fields reproduced by geostatistical methods characterized the spatial uncertainty of contaminant transport in the heterogeneous aquifer. Nitrogen contamination potential fronts for high and low threshold concentrations based on a 95% risk probability were used to assess different levels of risk. The simulated result reveals that the spatial uncertainty of highly heterogeneous K fields governs the contamination potential assessment of the nitrogen compounds along the regional flow directions. The contamination potential of nitrate-N is more uncertain than that for ammonium-N. The high nitrate-N concentrations (> or =3 mg/L) are prevalent in the aerobic environment. The low concentration nitrate-N plumes (0.5-3 mg/L) gradually migrate to the mid-fan area and to a maximum distance of 15 km from the aerobic region. The nitrate-N plumes pose a potential human health risk in the aerobic and anaerobic environments. The ammonium-N plumes remain stably confined to the distal-fan and partial mid-fan areas.     

Development of a GIS-based decision support system for urban air quality management in the city of Istanbul

A decision support system has been developed for urban air quality management in the metropolitan area of Istanbul. The system is based on CALMET/CALPUFF dispersion modeling system, digital maps, and related databases to estimate the emissions and spatial distribution of air pollutants with the help of a GIS software. The system estimates ambient air pollution levels at high temporal and spatial resolutions and enables mapping of emissions and air quality levels. Mapping and scenario results can be compared with air quality limits. Impact assessment of air pollution abatement measures can also be carried out.     

The spatial distribution of different elements in and on the foliage of Norway spruce growing in Switzerland

This study centres around the question of how far the analysis of spruce needles (Picea abies L.) provides a suitable tool for detecting and describing large-scale air pollution, primarily by heavy metals, in Switzerland. For that reason 1637 spruce shoots from 833 sites were analysed, relationships between the different elements were calculated and maps of their spatial distribution drawn. The results show that needle analysis is a valid instrument for the identification of various air pollutants in Switzerland. The element best suited is Pb, followed by some others like Mo, Fe, Cd or S. The most heavily polluted areas in Switzerland are the midlands, and in the north and north-west. Their spatial distribution suggests that in these areas the indicator elements are derived from local sources.     

Characterization of Spatially Homogeneous Regions Based on Temporal Patterns of Fine Particulate Matter in the Continental United States

Abstract

Statistical analyses of time-series or spatial data have been widely used to investigate the behavior of ambient air pollutants. Because air pollution data are generally collected in a wide area of interest over a relatively long period, such analyses should take into account both spatial and temporal characteristics. The objective of this study is 2-fold: (1) to identify an efficient way to characterize the spatial variations of fine particulate matter (PM_2.5) concentrations based solely upon their temporal patterns, and (2) to analyze the temporal and seasonal patterns of PM_2.5 concentrations in spatially homogenous regions. This study used 24-hr average PM_2.5 concentrations measured every third day during a period between 2001 and 2005 at 522 monitoring sites in the continental United States. A k-means clustering algorithm using the correlation distance was used to investigate the similarity in patterns between temporal profiles observed at the monitoring sites. A k-means clustering analysis produced six clusters of sites with distinct temporal patterns that were able to identify and characterize spatially homogeneous regions of the United States. The study also presents a rotated principal component analysis (RPCA) that has been used for characterizing spatial patterns of air pollution and discusses the difference between the clustering algorithm and RPCA.