Data base on pelagic ciliates grazing and growth rate as a function of size, prey size and type compiled from the literature

Microzooplankton (the 20 to 200 µm size class of zooplankton) is recognised as an important part of marine pelagic ecosystems. In terms of biomass and abundance pelagic ciliates are one of the important groups of organism in microzooplankton. However, their rates - grazing and growth - , feeding behaviour and prey preferences are poorly known and understood. A set of data was assembled in order to derive a better understanding of pelagic ciliates rates, in response to parameters such as prey concentration, prey type (size and species), temperature and their own size. With these objectives, literature was searched for laboratory experiments with information on one or more of these parameters effect studied. The criteria for selection and inclusion in the database included: (i) controlled laboratory experiment with a known ciliates feeding on a known prey; (ii) presence of ancillary information about experimental conditions, used organisms - cell volume, cell dimensions, and carbon content. Rates and ancillary information were measured in units that meet the experimenter need, creating a need to harmonize the data units after collection. In addition different units can link to different mechanisms (carbon to nutritive quality of the prey, volume to size limits). As a result, grazing rates are thus available as pg C/(ciliate*h), µm**3/(ciliate*h) and prey cell/(ciliate*h); clearance rate was calculated if not given and growth rate is expressed as the growth rate per day.

Prediction of PM10 concentrations using Fuzzy c-Means and ANN

Salamanca has been considered among the most polluted cities in Mexico. The vehicular park, the industry and the emissions produced by agriculture, as well as orography and climatic characteristics have propitiated the increment in pollutant concentration of Particulate Matter less than 10 μg/m3 in diameter (PM10). In this work, a Multilayer Perceptron Neural Network has been used to make the prediction of an hour ahead of pollutant concentration. A database used to train the Neural Network corresponds to historical time series of meteorological variables (wind speed, wind direction, temperature and relative humidity) and air pollutant concentrations of PM10. Before the prediction, Fuzzy c-Means clustering algorithm have been implemented in order to find relationship among pollutant and meteorological variables. These relationship help us to get additional information that will be used for predicting. Our experiments with the proposed system show the importance of this set of meteorological variables on the prediction of PM10 pollutant concentrations and the neural network efficiency. The performance estimation is determined using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results shown that the information obtained in the clustering step allows a prediction of an hour ahead, with data from past 2 hours

Modelling Saharan dust transport into the Mediterranean basin with CMAQ

The need for a better quantification of the influence of Saharan dust transport processes on the air quality modelling in the Mediterranean basin led to the formulation of a dust emission module (DEM) integrated into the Air Quality Risk Assessment System for the Iberian Peninsula (SERCA). This paper is focused on the formulation of DEM based on the GOCART aerosol model, along with its integration and execution into the air quality model. It also addresses the testing of the module and its evaluation by contrasting results against satellite products such as MODIS and CALIPSO and ground-level observations of aerosol optical thickness (AOT) and concentration levels of PM10 for different periods in July 2007. DEM was found capable of reproducing the spatial (horizontal and vertical) and temporal profiles of Saharan dust outbreaks into the Mediterranean basin and the Atlantic coast of Africa. Moreover, it was observed that its combination with CMAQ increased the correlation degree between observed and modelled PM10 concentrations at the selected monitoring locations. DEM also enhanced CMAQ capabilities to reproduce observed AOT, although significant underestimations remain. The implementation of CMAQ + DEM succeeded in capturing Saharan dust transport into the Iberian Peninsula, with contributions up to 25 and 14 μg m−3 in 1 h and 24 h average PM10 respectively. The general improvement of total PM10 predictions in Spain are however moderate. The analysis of model performance for the main PM components points out that remaining PM10 underestimation is due to dust local sources missing in the inventories and misrepresentation of organic aerosol processes, which constitutes the main areas for future improvement of CMAQ capabilities to simulate particulate matter within SERCA.

Emission factors from road dust resuspension in a Mediterranean freeway

Particulate matter emissions from paved roads are currently one of the main challenges for a sustainable transport in Europe. Emissions are scarcely estimated due to the lack of knowledge about the resuspension process severely hampering a reliable simulation of PM and heavy metals concentrations in large cities and evaluation of population exposure. In this study the Emission Factors from road dust resuspension on a Mediterranean freeway were estimated per single vehicle category and PM component (OC, EC, mineral dust and metals) by means of the deployment of vertical profiles of passive samplers and terminal concentration estimate. The estimated PM10 emission factors varied from 12 to 47 mg VKT?1 (VKT: Vehicle Kilometer Traveled) with an average value of 22.7 ? 14.2 mg VKT?1. Emission Factors for heavy and light duty vehicles, passenger cars and motorbikes were estimated, based on average fleet composition and EPA ratios, in 187e733 mg VKT?1, 33e131 VKT?1, 9.4e36.9 VKT?1 and 0.8e3.3 VKT?1, respectively. These range of values are lower than previous estimates in Mediterranean urban roads, probably due to the lower dust reservoir on freeways. PM emitted material was dominated by mineral dust (9e10 mg VKT?1), but also OC and EC were found to be major components and approximately 14 e25% and 2e9% of average PM exhaust emissions from diesel passenger cars on highways respectively.

Unsupervised method to classify PM10 pollutant concentrations

In this paper a method based mainly on Data Fusion and Artificial Neural Networks to classify one of the most important pollutants such as Particulate Matter less than 10 micrometer in diameter (PM10) concentrations is proposed. The main objective is to classify in two pollution levels (Non-Contingency and Contingency) the pollutant concentration. Pollutant concentrations and meteorological variables have been considered in order to build a Representative Vector (RV) of pollution. RV is used to train an Artificial Neural Network in order to classify pollutant events determined by meteorological variables. In the experiments, real time series gathered from the Automatic Environmental Monitoring Network (AEMN) in Salamanca Guanajuato Mexico have been used. The method can help to establish a better air quality monitoring methodology that is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilitate the pollutants reduction.

Fatores de bioconcentração e disponibilidade de bário, cádmio, cobre, níquel e zinco em solos e em culturas de interesse agronômico

Os elementos potencialmente tóxicos (EPTs) estão presentes nos solos em concentrações dependentes do material de origem e das ações antrópicas. A adição de EPTs ao solo pelas atividades antrópicas pode ocasionar risco à saúde humana, já que estes elementos podem ser acumulados no organismo por meio do contato dérmico com o solo, da inalação de partículas em suspensão, de ingestão de solo e de alimentos contaminados. A contaminação dos alimentos ocorre pelo cultivo em áreas com alta biodisponibilidade de EPTs, e nessa condição ocorre absorção e translocação para a parte aérea, com possível acúmulo dos metais nas porções comestíveis, como raízes, frutos e grãos. A biodisponibilidade dos EPTs é regulada pelas características químicas dos elementos e por atributos do solo, como a CTC, o pH e a matéria orgânica (MO). Sintomas de toxicidade e alterações morfológicas e fisiológicas podem aparecer dependendo da absorção e da movimentação dos EPTs nas plantas. Objetivou-se neste trabalho avaliar o efeito da adição de bário (Ba), de cádmio (Cd), de cobre (Cu), de níquel (Ni) e de zinco (Zn) em amostras de um Neossolo Quartzarênico e um Latossolo Vermelho distrófico, sob duas condições de saturação por bases (30% e 50 ou 70%, dependendo da cultura), no cultivo de arroz (Oryza sativa), alface (Lactuca sativa), girassol (Helianthus annuus) e tomate (Solanum lycopersicum). Os EPTs nos solos foram extraídos com EPA 3051a, Água Régia, DTPA, Mehlich 1, Mehlich 3, HNO3 (0,43 mol L-1) e CaCl2 (0,01 mol L-1), e seus teores correlacionados com os presentes nas raízes, na parte aérea, nos frutos e com a quantidade acumulada pelas plantas. Os fatores de bioconcentração (FBC) e de transferência (FT) foram calculados para as culturas. O índice SPAD (Soil Plant Analysis Development - Chlorophyll Meter) foi determinado na fase vegetativa da alface, do arroz e do girassol, enquanto a atividade fotossintética foi determinada pelo IRGA (Infrared gas analyzer). Os maiores teores de EPTs foram observados nas plantas cultivadas no Neossolo. As quantidades de Cu, Ni e Zn acumuladas nas plantas apresentaram correlação positiva com os teores extraídos pelo EPA 3051a e pela Água Régia. Os teores extraídos com HNO3 (0,43 mol L-1) apresentaram elevada correlação positiva com os teores reativos extraídos com DTPA e com Mehlich 3, e também com as quantidades de EPTs acumuladas pelas plantas. Os FBCs foram mais altos nos solos com baixa CTC, baixos teores de MO e baixos valores de pH. O arroz apresentou a menor translocação de Cd do sistema radicular para os grãos. O Cu, o Ni e o Zn causaram alterações no desenvolvimento da alface e do girassol, e diminuíram a transpiração e a condutância estomática da alface. O arroz apresentou a menor absorção de EPTs e a maior tolerância ao Ba, ao Cd, ao Ni e ao Zn, no entanto, as plantas apresentaram maiores condutividade estomática e transpiração.

(Table 2) pH and concentrations of dissolved and particulate chemical elements in the mixing zone of the Yur'eva River water and the Okhotsk Sea water

Data on behavior of iron, manganese, nickel, copper, and zinc in the zone where acidic volcanic waters of the Yur'eva River (Paramushir Island, Kuril Islands) mix with sea water are presented. Distributions of dissolved and particulate forms of these elements indicate that the mixing zone acts as a pH-based geochemical barrier, at which almost all dissolved iron and smaller amounts of other metals are precipitated. When chemogenic particulate matter formed in the mixing zone enters the open ocean, it can sorb trace elements from sea water.