Correlations in polycyclic aromatic hydrocarbon (PAH) concentrations in UK ambient air and implications for source apportionment

The extent of correlation in polycyclic aromatic hydrocarbon (PAH) concentration data obtained by the UK PAH Monitoring and Analysis Air Quality Network from March 2008 to November 2010 has been assessed. Application of principal component analysis (PCA) to the dataset has revealed that the concentrations of the vast majority of PAHs are very highly correlated. The use of diagnostic PAH ratios (including a new benzo[b]naph[2,1-d]thiophene/benzo[a]pyrene diagnostic ratio), and a novel 'combined diagnostic ratio - PCA' approach has revealed information about the main sources of PAH at individual Network sites, allowing the sites to be grouped in terms of those influenced by solid fuel use, industry and traffic, and those of an urban or rural nature. Solid fuel use has also been delineated from other fuel burning. Conclusions are drawn about a number of UK PAH Network sites - four sites are shown to be influenced significantly by solid fuel use, and the sites in South Wales and at London Marylebone Road are found to be located in distinct and unusual PAH pollution climates - the identification of a unique PAH pollution climate in South Wales is a key and novel conclusion of the work.     

The Impacts of Different Meteorology Data Sets on Nitrogen Fate and Transport in the SWAT Watershed Model

In this study, we investigated how different meteorology data sets impacts nitrogen fate and transport responses in the Soil and Water Assessment Tool (SWAT) model. We used two meteorology data sets: National Climatic Data Center (observed) and Mesoscale Model 5/Weather Research and Forecasting (simulated). The SWAT model was applied to two 10-digit hydrologic unit code watersheds in the Coastal Plain and Piedmont zones of North Carolina. Nitrogen cycling and loading response to these meteorological data were investigated by exploring 19 SWAT nitrogen outputs relating to landscape delivery, biogeochemical assimilation, and atmospheric deposition. The largest difference in model output using both meteorology data sets was for large loads/fluxes. Landscape delivery outputs (e.g., NO^? ₃ watershed discharge, groundwater NO^? ₃ flux, soil NO^? ₃ percolation) showed the largest difference across all values. Use of the two weather data sources resulted in a nearly twofold difference in NO^? ₃ watershed discharge and groundwater NO^? ₃ flux. Differences for many nitrogen outputs were greater than those for sub-basin flow. Nitrogen outputs showed the greatest difference for agricultural land covers and there was no flow-related pattern in output differences across sub-basins or over time (years). In general, nitrogen parameter models that had a greater number of nitrate concentration, flow, and temperature terms (equation variables) in each transport model showed the greatest difference between both meteorology applications.     

A Multiple Criteria Decision Analysis Model Based on ELECTRE TRI-C for Erosion Risk Assessment in Agricultural Areas

This paper deals with a real-world decision-aiding problem for zoning the risk of erosion, total suspended solids emissions, and ecological consequences of their transfers towards the streams. One of these consequences is the decrease of fishes into the streams in agricultural watersheds, because of the clogging of spawning areas. Given the multiple criteria nature of the problem, the originality of our research is to adapt a new decision-aiding sorting method, ELECTRE TRI-C, for identifying risk zones in rural areas, where measures must be taken. The developed model was applied in a small watershed (Low Normandy, France) where the objective was to assess the most appropriate intervention for protecting the reproduction habitat of the salmonid fishes. Agricultural parcels were evaluated on multiple criteria for grouping them into four risk categories, which are related to risk levels as well as priorities on the improvement works. The decision-aiding sorting model is co-constructed, within a constructive approach, through an interaction process between decision-aiding analysts, environmental experts, and local actors for improving transparency and communication on the results. This model is linked with a geographical information system (GIS) for assessing a set of criteria and the visualization of the farming parcels along with their type of intervention they should be submitted to best practices. The assignment results were validated by the environmental experts. These results have a strong impact on the agricultural practices of the farmers into the watersheds. The model proposed in this paper can be considered as a useful decision aid tool in any regions for implementing public agricultural and environmental policies for protecting the ecological areas.     

Differences in the Spatial Distribution and Chemical Composition of PM10 Between the UK and Poland

The Fine Resolution Atmospheric Multi-pollutant Exchange Model was used to calculate the spatial distribution and chemical composition of PM₁₀ concentrations for two geographically remote countries in Europe—the UK and Poland—for the year 2007. These countries are diverse in terms of pollutant emissions as well as climate conditions. Information on the contribution of natural and anthropogenic as well as national and imported particles in total PM₁₀ concentrations in both countries is presented. The paper shows that the modelled national annual average PM₁₀ concentrations, calculated for the entire country area, are similar for the UK and Poland and close to 12 μg m^?3. Secondary inorganic aerosols dominate the total PM₁₀ concentrations in Poland. Primary particulate matter has the greatest contribution to total PM₁₀ in the UK, with large contribution of base cations. Anthropogenic sources predominate (81 %) in total PM₁₀ concentrations in Poland, whereas natural prevail in the UK—hence, the future reduction of PM₁₀ air concentrations by emissions reduction could be more difficult in the UK than in Poland.     

Potential Impact of Clean Air Act Regulations on Nitrogen Fate and Transport in the Neuse River Basin: a Modeling Investigation Using CMAQ and SWAT

There has been extensive analysis of Clean Air Act Amendment (CAAA) regulation impacts to changes in atmospheric nitrogen deposition; however, few studies have focused on watershed nitrogen transfer particularly regarding long-term predictions. In this study, we investigated impacts of CAAA NOx emissions on the fate and transport of nitrogen for two watersheds in the Neuse River Basin. We applied the Soil and Water Assessment Tool (SWAT) using simulated deposition rates from the Community Multiscale Air Quality (CMAQ) model. Two scenarios were investigated: one that considered CAAA emission controls in CMAQ simulation (with) and a second that did not (without). By 2020, results showed a 70 % drop in nitrogen discharge for the Little River watershed and a 50 % drop for the Nahunta watershed from 1990 levels under the with-CAAA scenario. Denitrification and plant nitrogen uptake played important roles in nitrogen discharge from each watershed. Nitrogen watershed response time to a change in atmospheric nitrogen deposition was 4 years for Nahunta and 2 years for Little River. We attribute these differences in nitrogen response time to contrasts in agricultural land use and diversity of crop types. Soybean, hay, and corn land covers had comparatively longer response times to changes in atmospheric deposition. The studied watersheds demonstrate relatively large nitrogen retention: ≥80 % of all delivered nitrogen.     

Potential effects on the marine environment of dredging of the Bonny channel in the Niger Delta

This study is an assessment of the possible effects of the dredging project on the water quality of the surrounding environment. Water quality data for the Bonny offshore river were collected. The parameters assessed were temperature, dissolved oxygen (DO), pH, biochemical oxygen demand (BOD), total dissolved solids (TDS), total suspended solids (TSS), nitrogen as nitrate, and phosphate. The concentrations of TDS, TSS, and nitrate far exceeded the permissible standard. There were significant differences between the dry and rainy season values of BOD5, TDS, TSS, nitrate, and phosphate. Also, the sediment physicochemical analysis indicated the presence of heavy metals such as Pb, Fe, Cd, Zn, Cr, and elements such as Ca, K, and Na. Following an assessment of the potential impact of the project using interaction matrix and checklist questionnaires, results showed that the major physicochemical parameters influenced by dredging are DO, TDS, TSS, heavy metals and calcium, potassium, and sodium. Mitigation measures for eliminating or reducing the negative impacts of dredging are presented.     

A survey on the utility of the USEPA CADDIS stressor identification procedure

The Environmental Protection Agency (EPA) has made available on the worldwide web a systematic stream stressor identification procedure, the “Causal Analysis/Diagnosis Decision Information System” or CADDIS. We report here the results of a survey of regulators and scientists in 11 states who use CADDIS or another stressor identification procedure in their work. The 13 survey questions address guidelines as to what impairment scenarios to approach with stressor identification, what information is needed to perform stressor identification, and what the stakeholder role is in performing stressor identification. At the time of this survey (the summer of 2009), the EPA CADDIS website was less commonly used among the state regulators surveyed than the published EPA stressor identification document on which it is based. The respondents generally find the EPA stressor identification procedure useful and capable of being adapted to their individual needs. Survey respondents all use stressor identification in their Total Maximum Daily Load work, but also in a wide variety of other applications. All the “types of evidence” included in the CADDIS stressor identification procedure are used by the practitioners surveyed with the exception of the results of ecological simulation models. While the CADDIS documentation encourages the involvement of stakeholders in stressor identification, most respondents do not assemble stakeholder teams of local officials and citizens to participate in stressor analyses.     

Coral assemblages in Tonga: spatial patterns, replenishment capacities, and implications for conservation strategies

Coral reefs in Tonga have been confronted by multiple threats of various origins, including large-scale disturbances and human-induced stressors. These reef communities have been poorly studied, and efficient conservation actions are urgently needed. The aim of this study was to: (1) examine the spatial distribution of coral assemblages in the lagoon of Tongatapu; (2) determine the degree to which spatial heterogeneity of adult corals is influenced by recruitment processes; and (3) examine the implications of these results in terms of conservation actions. We recorded a total of 37 adult and 28 juvenile coral genera, a mean density of 11.6 adult and 5.5 juvenile colonies m^?2, and a dominance of Montipora, Acropora, and Porites. For seven of the 10 dominant genera, spatial patterns of adults were linked to the short-term recruitment pattern history. Despite a reduced diversity and abundance of adult corals in some areas, the lagoon of Tongatapu retains the potential for replenishment through recruitment of young corals. Consequently, we suggest that conservation actions should focus on reducing factors causing coral mortality and maintain suitable conditions for the establishment and growth of juvenile corals, thus increasing the probability that they will reach maturity and participate to the maintenance of local populations. Rather than establishing a large marine protected area, which will almost certainly suffer from a lack of control and poor enforcement, alternative conservation measures could be successfully implemented through the establishment of several small village-based marine reserves, as has been undertaken in other South Pacific islands with promising results.     

Accuracy and uncertainty assessment on geostatistical simulation of soil salinity in a coastal farmland using auxiliary variable

Understanding the spatial soil salinity aids farmers and researchers in identifying areas in the field where special management practices are required. Apparent electrical conductivity measured by electromagnetic induction instrument in a fairly quick manner has been widely used to estimate spatial soil salinity. However, methods used for this purpose are mostly a series of interpolation algorithms. In this study, sequential Gaussian simulation (SGS) and sequential Gaussian co-simulation (SGCS) algorithms were applied for assessing the prediction accuracy and uncertainty of soil salinity with apparent electrical conductivity as auxiliary variable. Results showed that the spatial patterns of soil salinity generated by SGS and SGCS algorithms showed consistency with the measured values. The profile distribution of soil salinity was characterized by increasing with depth with medium salinization (EC_e 4–8 dS/m) as the predominant salinization class. SGCS algorithm privileged SGS algorithm with smaller root mean square error according to the generated realizations. In addition, SGCS algorithm had larger proportions of true values falling within probability intervals and narrower range of probability intervals than SGS algorithm. We concluded that SGCS algorithm had better performance in modeling local uncertainty and propagating spatial uncertainty. The inclusion of auxiliary variable contributed to prediction capability and uncertainty modeling when using densely auxiliary variable as the covariate to predict the sparse target variable.     

Elemental composition of sediments in Lake Jinzai, Japan: Assessment of sources and pollution

Bottom sediments from Lake Jinzai in southwest Japan were analyzed to determine their chemical compositions and to assess the potential for ecological harm by comparison with sediment quality guidelines. The pollution status of lake sediments was evaluated by employing contamination factor (CF), pollution load index (PLI), and geoaccumulation index (I(geo)), focusing on a suite of elements in lakebed and core sediments. Elevated concentrations of As, Pb, Zn, Cu, TOC, N, and P were present in several layers of the upper core and other surface sediments. The elevated metal concentrations are likely related to the fine-grained nature of the sediments, reducing bottom conditions produced by abundant organic matter, and possibly minor non-point anthropogenic sources. Moreover, correlations between the concentrations of trace metals and organic carbon, nitrogen, phosphorus, and iron, suggest that these elements play a role in controlling abundances. Calculated CF, PLI, and I(geo) indicate that the sediments are strongly polluted with respect to As, moderately to strongly polluted with Zn, and moderately polluted with Pb and Cu. Metal concentrations exceed the New York State Department of Environmental Conservation (NYSDEC) lowest effect level and the Canadian Council of Ministers of the Environment (CCME) interim sediment quality guidelines that indicate moderate impact on aquatic organisms in the study area.