Modeling phosphorus transport in an agricultural watershed using the WEPP model

The Water Erosion Prediction Project (WEPP) model has been tested for its ability to predict soil erosion, runoff, and sediment delivery over a wide range of conditions and scales for both hillslopes and watersheds. Since its release in 1995, there has been considerable interest in adding a chemical transport element to it. Total phosphorus (TP) loss at the watershed outlet was simulated as the product of TP in the soil, amount of sediment at the watershed outlet, and an enrichment ratio (ER) factor. WEPP can be coupled with a simple algorithm to simulate phosphorus transport bound to sediment at the watershed outlet. The objective of this work was to incorporate and test the ability of WEPP in estimatingTP loss with sediment at the small watershed scale. Two approaches were examined. One approach (P-EER) estimated ER according to an empirical relationship; the other approach used the ER calculated by WEPP (P-WER).The data used for model performance test were obtained from two side-by-side watersheds monitored between 1976 and 1980. The watershed sizes were 5.05 and 6.37 ha, and each was in a corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotation. Measured and simulated results were compared for the period April to October in each year. There was no statistical difference between the mean measured and simulated TP loss. The Nash-Sutcliffe coefficient was 0.80 and 0.78 for the P-EER and P-WER methods, respectively. It was critical for both methods that WEPP adequately represent the biggest sediment yield events because sediment is the main driver for TP loss so that the model can adequately simulate TP losses bound to sediment. The P-WER method is recommended because it does not require use of empirical parameters to estimate TP loss at the watershed outlet.     

Modeling Inorganic Aerosols and Their Response to Changes in Precursor Concentration in Mexico City

Abstract

Based on data from the 1997 Investigación sobre Materia Particulada y Deterioro Atmosférico-Aerosol and Visibility Evaluation Research (IMADA-EVER) campaign and the inorganic aerosol model ISORROPIA, the response of inorganic aerosols to changes in precursor concentrations was calculated. The aerosol behavior is dominated by the abundance of ammonia and thus, changes in ammonia concentration are expected to have a small effect on particle concentrations. Changes in sulfate and nitrate are expected to lead to proportional reductions in inorganic fine particulate matter (PM_2.5). Comparing the predictions of ISORROPIA with the observations, the lowest bias and error are achieved when the aerosols are assumed to be in the efflorescence branch. Including crustal species reduces the bias and error for nitrate but does not improve overall model performance. The estimated response of inorganic PM_2.5 to changes in precursor concentrations is affected by the inclusion of crustal species in some cases, although average responses are comparable with and without crustal species. Observed concentrations of particle chloride suggest that gas phase concentrations of hydrogen chloride may not be negligible, and future measurement campaigns should include observations to test this hypothesis. Our ability to model aerosol behavior in Mexico City and, thus, design control strategies, is constrained primarily by a lack of observations of gas phase precursors. Future campaigns should focus in particular on better understanding the temporal and spatial distribution of ammonia concentrations. In addition, gas phase observations of nitric acid are needed, and a measure of particle water content will allow stable versus metastable aerosol behavior to be distinguished.     

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis.     

Influence of competing inorganic cations on the ion exchange equilibrium of the monovalent organic cation metoprolol on natural sediment

The aim of this study was to systematically investigate the influence of the mono- and divalent inorganic ions Na⁺ and Ca²⁺ on the sorption behavior of the monovalent organic cation metoprolol on a natural sandy sediment at pH = 7. Isotherms for the beta-blocker metoprolol were obtained by sediment–water batch tests over a wide concentration range (1–100 000 μg L^?1). Concentrations of the competing inorganic ions were varied within freshwater relevant ranges. Data fitted well with the Freundlich sorption model and resulted in very similar Freundlich exponents (n = 0.9), indicating slightly non-linear behavior. Results show that the influence of Ca²⁺ compared to Na⁺ is more pronounced. A logarithmic correlation between the Freundlich coefficient K_Fr and the concentration or activity of the competing inorganic ions was found allowing the prediction of metoprolol sorption on the investigated sediment at different electrolyte concentrations. Additionally, the organic carbon of the sediment was completely removed for investigating the influence of organic matter on the sorption of metoprolol. The comparison between the experiments with and without organic carbon removal revealed no significant contribution of the organic carbon fraction (0.1%) to the sorption of metoprolol on the in this study investigated sediment. Results of this study will contribute to the development of predictive models for the transport of organic cations in the subsurface.     

Radical precursors and related species from traffic as observed and modeled at an urban highway junction

Nitrous acid (HONO) and formaldehyde (HCHO) are important precursors for radicals and are believed to favor ozone formation significantly. Traffic emission data for both compounds are scarce and mostly outdated. A better knowledge of today's HCHO and HONO emissions related to traffic is needed to refine air quality models. Here the authors report results from continuous ambient air measurements taken at a highway junction in Houston, Texas, from July 15 to October 15, 2009. The observational data were compared with emission estimates from currently available mobile emission models (MOBILE6; MOVES [MOtor Vehicle Emission Simulator]). Observations indicated a molar carbon monoxide (CO) versus nitrogen oxides (NO_x) ratio of 6.01 ± 0.15 (r ² = 0.91), which is in agreement with other field studies. Both MOBILE6 and MOVES overestimate this emission ratio by 92% and 24%, respectively. For HCHO/CO, an overall slope of 3.14 ± 0.14 g HCHO/kg CO was observed. Whereas MOBILE6 largely underestimates this ratio by 77%, MOVES calculates somewhat higher HCHO/CO ratios (1.87) than MOBILE6, but is still significantly lower than the observed ratio. MOVES shows high HCHO/CO ratios during the early morning hours due to heavy-duty diesel off-network emissions. The differences of the modeled CO/NO_x and HCHO/CO ratios are largely due to higher NO_x and HCHO emissions in MOVES (30% and 57%, respectively, increased from MOBILE6 for 2009), as CO emissions were about the same in both models. The observed HONO/NO_x emission ratio is around 0.017 ± 0.0009 kg HONO/kg NO_x which is twice as high as in MOVES. The observed NO₂/NO_x emission ratio is around 0.16 ± 0.01 kg NO₂/kg NO_x, which is a bit more than 50% higher than in MOVES. MOVES overestimates the CO/CO₂ emission ratio by a factor of 3 compared with the observations, which is 0.0033 ± 0.0002 kg CO/kg CO₂. This as well as CO/NO_x overestimation is coming from light-duty gasoline vehicles.

Implications: Nitrous acid (HONO) and formaldehyde (HCHO) are important precursors for radicals that ultimately contribute to ozone formation. There still exist uncertainties in emission sources of HONO and HCHO and thus regional air quality modeling still tend to underestimate concentrations of free radicals in the atmosphere. This paper demonstrates that the latest U.S. Environmental Protection Agency (EPA) traffic emission model MOVES still shows significant deviations from observed emission ratios, in particular underestimation of HCHO/CO and HONO/NO_x ratios. Improving the performance of MOVES may improve regional air quality modeling.     

Temporal and spatial patterns of micropollutants in urban receiving waters

Based on a monitoring program over the course of a year, we characterize the temporal and spatial distribution of selected micropollutants in an urban watershed within the city of Leipzig, Germany. Micropollutants revealed a ubiquitous presence in untreated and treated wastewater, surface water and groundwater. The loads of 4-nonylphenol in the effluents of the municipal wastewater treatment plant followed a seasonal trend, whereas the loads of all other micropollutants were highly variable and not correlated to seasons. In the surface water, load seasonality of caffeine, galaxolide and tonalide resulted from a rapid removal with increased water temperature. The loads of 4-nonylphenol and of caffeine in the colder months increased when rainfall occurred. In the groundwater, complex spatial and temporal patterns were apparent and were related to varying input, retardation and removal processes. As a consequence, an assessment of micropollutants in urban waters should consider different micropollutants' temporal and spatial variability.     

Evaluation of Saccharomyces cerevisiae strains as probiotic agent with aflatoxin B1 adsorption ability for use in poultry feedstuffs

In this study the aflatoxin B₁ (AFB₁) removal capacity, the tolerance to salivary and gastrointestinal conditions, autoaggregation and coaggregation with pathogenic bacteria of Saccharomyces cerevisiae strains isolated from broiler feces, were evaluated. Only four of twelve isolated strains were identified as Saccharomyces cerevisiae using molecular techniques. The results obtained in AFB₁ binding studies indicated that the amount of AFB₁ removed was both strain and mycotoxin-concentration dependent. Therefore, a theoretical model was applied in order to select the most efficient strain to remove AFB₁ in a wide range of mycotoxin concentration. The results indicated that S. cerevisiae 08 and S. cerevisiae 01 strains were the most efficient microorganisms in the mycotoxin removal. Viability on simulated salivary and gastrointestinal conditions was investigated and S. cerevisiae 08 strain showed the best results, achieving 98% of total survival whereas S. cerevisiae 01 reached only 75%. Autoaggregation and coaggregation assays showed S. cerevisiae 08 as the most appropriate strain, mainly because it was the unique strain able to coaggregate with the four bacterial pathogens assayed. Consequently, S. cerevisiae 08 is the best candidate for future in vivo studies useful to prevent aflatoxicosis. Further quantitative in vitro and in vivo studies are required to evaluate the real impact of yeast-binding activity on the bioavailability of AFB₁ in poultry. However, this study could be useful in selecting efficient strains in terms of AFB₁ binding and provide an important contribution to research into microorganisms with potential probiotic effects on the host.     

Analysis and modelling of the pollutant emissions from European cars regarding the driving characteristics and test cycles

Within the European research project ARTEMIS, significant works have been conducted to analyse the hot emissions of pollutant from the passenger cars regarding the driving cycles and to propose modelling approaches taking into account large but heterogeneous datasets recorded in Europe. The review and analysis of a large range of test cycles enabled first the building-up of a set of contrasted cycles specifically designed for characterizing the influence of the driving conditions. These cycles were used for the measurement of the pollutants emission rates from nine passenger cars on a chassis dynamometer.Emissions measured on 30 vehicles tested on cycles adapted to their motorization (i.e., cycles for high- or low-powered cars, inducing thus a significant difference in the dynamic) were also considered for analysing the influence of the cycles and of the kinematic parameters on the hot emission rates of the regulated pollutants (CO, HC, NO_x, CO₂, PM). An analyses of variance demonstrated the preponderance of the driving type (urban, rural road, motorway), of the vehicle category (fuel, emission standard) and emitting status (high/normal emitter) and thus the pertinence of analysing and modelling separately the corresponding emissions. It also demonstrated that Urban driving led systematically to high diesel emission rates and to high CO₂, HC and NO_x emissions from petrol cars. Congested driving implied high CO₂ (diesel and petrol) and high diesel NO_x emission. On motorway, the very high speeds generated high CO₂, while unsteady speeds induced diesel NO_x and petrol CO over-emissions. A search for pertinent kinematic parameters showed that urban diesel emissions were mostly sensitive to stops and speed parameters, while petrol emissions were rather sensitive to acceleration parameters. On the motorway, diesel NO_x and CO₂ emissions rates increased with the speed variability and occurrence of high speeds, while CO₂ and CO over-emission from petrol cars were linked to the occurrence of strong acceleration at high speeds.A modelling approach based on partial least square regression was tested, which demonstrates its ability to discriminate satisfactorily the emissions according to dynamic related parameters and in particular when considering the two-dimensionnal distribution of instantaneous speed and acceleration.Finally, a strategy was proposed to analyse the large but heterogeneous set of hot emission data collected within the ARTEMIS project. The approach consisted in analysing the similarity of the numerous cycles as regards their kinematic, grouping them into reference test patterns through an automatic clustering, and then computing reference emissions for these patterns. These principles enabled the development of a method to compute the emissions at a low spatial scale, i.e. the so-called traffic situation approach, which was implemented in the European Artemis model for estimating the cars’ pollutant emissions.     

Chemical degradation of 2,3,7,8-TCDD by means of polyethyleneglycols in the presence of weak bases and an oxidant

A chemical method for destroying the 2,3,7,8-TCDD is reported; it provides gradual and progressive substitution of the chlorine atoms by hydrogen atoms. The dehalogenation is promoted by a mixture made up of polyethyleneglycols (high molecular weight) of a weak base (K₂ CO₃) and of an inorganic peroxide (Na₂ O₂) which begins the radical process. The organic chlorine is transformed into inorganic chloride.The reaction mixture administered to male guinea-pigs did not lead to any direct or histological effect.