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.     

Adjusting the effect of seasonal variability in the bioassessment of streams

Bioassessment tools should distinguish between the effects of anthropogenic degradation in communities and natural temporal changes. The present study tests the influence of natural seasonal variability on macroinvertebrate stream communities assessed by a predictive model (PORTRIV) and a multimetric index (IPtI) calibrated for spring. The scores of PORTRIV decreased significantly between spring and autumn, and between spring and winter (ca. 37 to 53 %, respectively), while those of IPtI did not change significantly between seasons. For non-reference samples, the results of the predictive model also indicate no significant differences. A correction factor (CF) was calculated to adjust the existing differences in the model assessments between seasons, based on the percentage of variation of reference site scores from spring to autumn and winter. After the application of the CF to the OE50 scores of spring reference samples, the differences were no longer significant. Independent reference validation sites confirmed this tendency. This method has the advantage of avoiding large efforts required for the construction of databases from other seasons and the development of new models to allow the assessment of streams in seasons other than spring. Further tests with models developed in regions with more marked seasonal changes should be done to confirm its wider applicability.     

Montane Meadows as Indicators of Environmental Change

We used a time series of satellite multispectral imagery for mapping and monitoring six classes of montane meadows arrayed along a moisture gradient (from hydric to mesic to xeric). We hypothesized that mesic meadows would support the highest species diversity of plants, birds, and butterflies because they are more moderate environments. We also hypothesized that mesic meadows would exhibit the greatest seasonal and interannual variability in spectral response across years. Field sampling in each of the meadow types was conducted for plants, birds, and butterflies in 1997 and 1998. Mesic meadows supported the highest plant species diversity, but there was no significant difference in bird or butterfly species diversity among meadow types. These data show that it may be easier to detect significant differences in more species rich taxa (e.g., plants) than taxa that are represented by fewer species (e.g., butterflies and birds). Mesic meadows also showed the greatest seasonal and interannual variability in spectral response. Given the rich biodiversity of mesic montane meadows and their sensitivity to variations in temperature and moisture, they may be important to monitor in the context of environmental change     

Heavy metal concentration in fish tissues inhabiting waters of “Buško Blato” reservoar (Bosnia and Herzegovina)

Heavy metals concentration (mercury, lead, cadmium, arsenic, copper, zinc and chromium) in tissues (muscles, liver, kidney and gonads) of Dalmatian barbelgudgeon, the nase, the souffie and brown trout, inhabiting waters of Busko Blato reservoir in Bosnia and Herzegovina, has been determined by atomic absorption spectrophotometry. The meat of the tested fish sorts does not contain elevated concentration of most analyzed heavy metals with exception of lead (higher than MAC in Italy, Germany and Denmark) and mercury (in muscles of brown trout higher than MAC in most countries). The lowest level of all heavy metals is always detected in gonads, with higher values in fry compared to milt for copper, zinc, chromium and arsenic. The highest copper concentration is observed in the liver from the souffie which is suggested as a suitable biomonitor for copper intoxication. In muscles of all fish sorts, lead was always present in much higher concentration than cadmium, while in kidneys of most fish sorts, lead and cadmium concentrations were similar. We showed that bioaccumulation of some heavy metals in the fish sorts analyzed is tissue and sex dependent. Also, we concluded that the small water exchange in reversible shallow reservoir does not induce elevated concentration of heavy metals in fish tissues inhabiting Busko Blato.     

Precipitation composition and wet deposition temporal pattern in Central Serbia for the period from 1998 to 2004

Bulk samples collected on a daily basis at three principal meteorological stations in central Serbia were analyzed on chloride (Cl(-)), nitrate [Formula: see text], sulfate [Formula: see text], sodium (Na(+)), ammonium [Formula: see text], potassium (K(+)), calcium (Ca(2+)), and magnesium (Mg(2+)) in addition to precipitation amount, pH and conductivity measurements over the period 1998-2004. The data were subjected to variety of analyses (linear regression, principal component analysis, time series analysis) to characterize precipitation chemistry in the study area. The most abundant ion was [Formula: see text] with annual volume weighted mean concentration of 242 microeq L(-1). Neutralization of precipitation acidity occurs both as a result of the dissolution of alkaline compounds containing Ca(2+), Mg(2+), and K(+) as well as the absorption of ammonia. The ratio of [Formula: see text] was above 5, which indicated that the combustion process of low-grade domestic lignite for electricity generation from coal-fired thermal power plants was the main source of pollution in the investigated area. A considerable mean annual bulk wet deposition of SO(4)-S determined by precipitation amount and concentrations of sulfate in the precipitation was calculated to be 12-35 kg ha(-1).     

Micromorphology and chemistry of airborne particles in Brussels during agriculture working periods in surrounding region

The main objective of our research was to compare the airborne particle micromorphology and chemistry in the Brussels environment during agriculture working periods in the surrounding farming region. We used specific methods and instrumentation that are adapted to the climate peculiarities of the Brussels region, the period of investigations (12 months) and the proposed objectives. For the agricultural works we defined the following six periods: before sowing, sowing, after sowing, before harvest, harvest and after harvest. The results indicate a possible temporal correlation between agricultural work periods and airborne particle concentration, micromorphology and chemistry in the Brabant-Brussels region. For wheat and corn plant-growth periods, the average particle size, defined as the area obtained by a planar projection of the particulate, showed important variations in time. For sugar beet and endive, the average area size variations are less important. The roughness and sphericity parameters for the growth periods of the four different plants also showed significant differences. Many of the larger particulates (> 10 microm) are aggregates of even finer particles coated with many still finer ones. The airborne particle chemistry averages (atomic percentage At%), showed that three constituents (Si, S and Fe) dominate all the samples (except for particles 3-10 microm in size, which contain a relatively large percentage of Al). Applying similar investigation methods to study the correlations between airborne particle dynamics in urban zones and the agriculture working periods in their surrounding regions could be of interest to better understand the complexity of the PM problematic.     

Prediction models of CO, SPM and SO2 concentrations in the Campo de Gibraltar Region, Spain: a multiple comparison strategy

The 'Campo de Gibraltar' region is a very industrialized area where very few air pollution studies have been carried out. Up to date, no model has been developed in order to predict air pollutant levels in the different towns spread in the region. Carbon monoxide (CO), Sulphur dioxide (SO(2)) and suspended particulate matter (SPM) series have been investigated (years 1999-2000-2001). Multilayer perceptron models (MLPs) with backpropagation learning rule have been used. A resampling strategy with two-fold crossvalidation allowed the statistical comparison of the different models considered in this study. Artificial neural networks (ANN) models were compared with Persistence and ARIMA models and also with models based on standard Multiple Linear Regression (MLR) over test sets with data that had not been used in the training stage. The models based on ANNs showed better capability of generalization than those based on MLR. The designed procedure of random resampling permits an adequate and robust multiple comparison of the tested models. Principal component analysis (PCA) is used to reduce the dimensionality of data and to transform exogenous variables into significant and independent components. Short-term predictions were better than medium-term predictions in the case of CO and SO(2) series. Conversely, medium-term predictions were better in the case of SPM concentrations. The predictions are significantly promising (e.g., d (SPM 24-ahead) = 0.906, d (CO 1-ahead) = 0.891, d (SO2 1-ahead) = 0.851).     

Chemical dynamics of the Sava riverine system

Presented here is a study of the geochemical dynamics of the entire River Sava watershed, a major tributary of the River Danube which has not previously been investigated. The sampling was performed at 33 selected locations along the main channel of the stream and at its largest tributaries during three sampling seasons (fall 2005, spring 2006 and fall 2006), going from headwater locations to the mouth near the confluence with the Danube. Almost 80% of the solutes are derived from carbonate mineral weathering and represent over 50% of specific HCO(3)(-) flux normalized to unit basin area at the mouth of the Danube. Statistical analysis indicates that agricultural and industrial sources contribute significantly to increased Na(+), K(+), Cl(-), SO(4)(2-) and NO(3)(-) concentrations in tributary waters. Different processes control the water chemistry along the course of the Sava's drainage-the upper reaches are largely regulated by contributions from carbonate mineral weathering, the middle reaches are influenced by agricultural activity and biological processes related to eutrophication, while the lower reaches tend to have more pronounced parameters related to the industrial processing along with leakages from municipal sanitary systems of these higher population density areas.