995 resultados para pollutant emission


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The potentially significant role of the biogenic trace gas dimethylsulfide (DMS) in determining the Earth's radiation budget makes it necessary to accurately reproduce seawater DMS distribution and quantify its global flux across the sea/air interface. Following a threefold increase of data (from 15,000 to over 47,000) in the global surface ocean DMS database over the last decade, new global monthly climatologies of surface ocean DMS concentration and sea-to-air emission flux are presented as updates of those constructed 10 years ago. Interpolation/extrapolation techniques were applied to project the discrete concentration data onto a first guess field based on Longhurst's biogeographic provinces. Further objective analysis allowed us to obtain the final monthly maps. The new climatology projects DMS concentrations typically in the range of 1–7 nM, with higher levels occurring in the high latitudes, and with a general trend toward increasing concentration in summer. The increased size and distribution of the observations in the DMS database have produced in the new climatology substantially lower DMS concentrations in the polar latitudes and generally higher DMS concentrations in regions that were severely undersampled 10 years ago, such as the southern Indian Ocean. Using the new DMS concentration climatology in conjunction with state-of-the-art parameterizations for the sea/air gas transfer velocity and climatological wind fields, we estimate that 28.1 (17.6–34.4) Tg of sulfur are transferred from the oceans into the atmosphere annually in the form of DMS. This represents a global emission increase of 17% with respect to the equivalent calculation using the previous climatology. This new DMS climatology represents a valuable tool for atmospheric chemistry, climate, and Earth System models.

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Due to the impacts of natural processes and anthropogenic activities, different coastal wetlands are faced with variable patterns of heavy metal contamination. It is important to quantify the contributions of pollutant sources, in order to adopt appropriate protection measures for local ecosystems. The aim of this research was to compare the heavy metal contamination patterns of two contrasting coastal wetlands in eastern China. In addition, the contributions from various metal sources were identified and quantified, and influencing factors, such as the role of the plant Spartina alterniflora, were evaluated. Materials and methods Sediment samples were taken from two coastal wetlands (plain-type tidal flat at the Rudong (RD) wetland vs embayment-type tidal flat at Luoyuan Bay (LY)) to measure the content of Al, Fe, Co, Cr, Cu, Mn, Mo, Ni, Sr, Zn, Pb, Cd, and As. Inductively coupled plasma atomic emission spectrometry, flame atomic absorption spectrometry, and atomic fluorescence spectrometry methods were used for metal detection. Meanwhile, the enrichment factor and geoaccumulation index were applied to assess the pollution level. Principle component analysis and receptor modeling were used to quantify the sources of heavy metals. Results and discussion Marked differences in metal distribution patterns between the two systems were present. Metal contents in LY were higher than those in RD, except for Sr and Mo. The growth status of S. alterniflora influenced metal accumulations in RD, i.e., heavy metals were more easily adsorbed in the sediment in the following sequence: Cu > Cd > Zn > Cr > Al > Pb ≥ Ni ≥ Co > Fe > Sr ≥ Mn > As > Mo as a result of the presence and size of the vegetation. However, this phenomenon was not observed in LY. A higher potential ecological risk was associated with LY, compared with RD, except for Mo. Based on a receptor model output, sedimentary heavy metal contents at RD were jointly influenced by natural sedimentary processes and anthropogenic activities, whereas they were dominated by anthropogenic activities at LY. Conclusions A combination of geochemical analysis and modeling approaches was used to quantify the different types of natural and anthropogenic contributions to heavy metal contamination, which is useful for pollution assessments. The application of this approach reveals that natural and anthropogenic processes have different influences on the delivery and retention of metals at the two contrasting coastal wetlands. In addition, the presence and size of S. alterniflora can influence the level of metal contamination in sedimentary environments.

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Current global inventories of ammonia emissions identify the ocean as the largest natural source. This source depends on seawater pH, temperature, and the concentration of total seawater ammonia (NHx(sw)), which reflects a balance between remineralization of organic matter, uptake by plankton, and nitrification. Here we compare [NHx(sw)] from two global ocean biogeochemical models (BEC and COBALT) against extensive ocean observations. Simulated [NHx(sw)] are generally biased high. Improved simulation can be achieved in COBALT by increasing the plankton affinity for NHx within observed ranges. The resulting global ocean emissions is 2.5 TgN a−1, much lower than current literature values (7–23 TgN a−1), including the widely used Global Emissions InitiAtive (GEIA) inventory (8 TgN a−1). Such a weak ocean source implies that continental sources contribute more than half of atmospheric NHx over most of the ocean in the Northern Hemisphere. Ammonia emitted from oceanic sources is insufficient to neutralize sulfate aerosol acidity, consistent with observations. There is evidence over the Equatorial Pacific for a missing source of atmospheric ammonia that could be due to photolysis of marine organic nitrogen at the ocean surface or in the atmosphere. Accommodating this possible missing source yields a global ocean emission of ammonia in the range 2–5 TgN a−1, comparable in magnitude to other natural sources from open fires and soils.

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We have modeled self-consistently the density and temperature profiles of gas and dust in protoplanetary disks, taking into account irradiation from a central star. Making use of this physical structure, we have calculated the level populations of molecular hydrogen and the line emission from the disks. As a result, we can reproduce the observed strong line spectra of molecular hydrogen from protoplanetary disks, both in the ultraviolet (UV) and the near-infrared, but only if the central star has a strong UV excess radiation.

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In this paper NOx emissions modelling for real-time operation and control of a 200 MWe coal-fired power generation plant is studied. Three model types are compared. For the first model the fundamentals governing the NOx formation mechanisms and a system identification technique are used to develop a grey-box model. Then a linear AutoRegressive model with eXogenous inputs (ARX) model and a non-linear ARX model (NARX) are built. Operation plant data is used for modelling and validation. Model cross-validation tests show that the developed grey-box model is able to consistently produce better overall long-term prediction performance than the other two models.

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