Comparison of SOC estimates and uncertainties from aerosol chemical composition and gas phase data in Atlanta

In the Southeastern US, organic carbon (OC) comprises about 30% of the PM_2.5 mass. A large fraction of OC is estimated to be of secondary origin. Long-term estimates of SOC and uncertainties are necessary in the evaluation of air quality policy effectiveness and epidemiologic studies. Four methods to estimate secondary organic carbon (SOC) and respective uncertainties are compared utilizing PM_2.5 chemical composition and gas phase data available in Atlanta from 1999 to 2007. The elemental carbon (EC) tracer and the regression methods, which rely on the use of tracer species of primary and secondary OC formation, provided intermediate estimates of SOC as 30% of OC. The other two methods, chemical mass balance (CMB) and positive matrix factorization (PMF) solve mass balance equations to estimate primary and secondary fractions based on source profiles and statistically-derived common factors, respectively. CMB had the highest estimate of SOC (46% of OC) while PMF led to the lowest (26% of OC). The comparison of SOC uncertainties, estimated based on propagation of errors, led to the regression method having the lowest uncertainty among the four methods. We compared the estimates with the water soluble fraction of the OC, which has been suggested as a surrogate of SOC when biomass burning is negligible, and found a similar trend with SOC estimates from the regression method. The regression method also showed the strongest correlation with daily SOC estimates from CMB using molecular markers. The regression method shows advantages over the other methods in the calculation of a long-term series of SOC estimates.     

The analysis of pollutant profiles by means of compositional analysis. An application to PCDD/F data

Compositional analysis consists of a group of techniques used to manipulate closed (=compositional) data, i.e. multivariate data summing to a fixed quantity (proportions, percentages). It is based on the analysis of the relations among variables and the use of logarithmic transformations. It has been claimed that this group of techniques should be used to analyse profiles of pollutant sources because profiles themselves are proportions. We show in this paper that, for the exploratory analysis of these data, a good strategy is to combine the analysis done with and without transformation because they give different and complementary insights on the structure of the data. We discuss in particular the study of processes such as the mixing of pollutants produced by different sources and the exponential decay of concentrations with distance to the source found in many studies. The clr transformation is also appropriate for the study of the variables having small proportions, which remain concealed by the abundant variables when analysed without transformation. We present simulations to illustrate these ideas and we also apply these techniques to two data sets of PCDD/F content in moss tissues.     

Automated data analysis to rapidly derive and communicate ecological insights from satellite-tag data: A case study of reintroduced red kites

Analysis of satellite-telemetry data mostly occurs long after it has been collected, due to the time and effort needed to collate and interpret such material. Delayed reporting reduces the usefulness of such data for nature conservation where timely information about animal movements is required. To counter this problem, we present a novel approach which combines automated analysis of satellite-telemetry data with rapid communication of insights derived from such data. A relatively simple algorithm (based on radial and angular velocity calculated from fixes) allowed instantaneous detection of excursions away from settlement areas and automated calculation of home ranges on the remaining data. Automating the detection of both excursions and home-range calculations enabled us to disseminate ecological insights from satellite-tag data instantaneously through a dedicated web portal. The automated analysis, interpretation, and communication of satellite-tag and other ecological data offer clear benefits to nature conservation research and practice.     

Chemical composition and ecophysiological responses of Empetrum nigrum to aboveground element application

Empetrum nigrum L. (crowberry) is one of the plants surviving near the Cu-Ni smelters in Finland and Russia. According to field observations, the fine roots of E. nigrum are situated below 40 cm depth and the root biomass is reduced in the polluted sites. This could cause a reduced root uptake of macronutrients and trace elements in the field and, therefore, the possible element uptake by aboveground parts of E. nigrum was studied in a greenhouse. Six different treatment solutions containing various heavy metal and macronutrient concentrations were applied to the stems and leaves of E. nigrum and the chemical composition and ecophysiological parameters were measured. Heavy metal concentrations in the leaves and stem bark, and Cu concentrations in the stems, increased with increasing metal concentrations in the spraying solutions. The bark and leaves had higher heavy metal concentrations than the stems of comparable age classes. The macronutrient and Mn concentrations in E. nigrum did not change significantly with increasing element concentrations in the spraying solution. Neither the stem water potential nor the leaf chlorophyll concentrations showed any clear response to element applications. Therefore, the element uptake by aboveground parts of E. nigrum was not confirmed by this study. However, there was a tendency to a decrease in CO2 exchange rate and increase in foliar abscisic acid content in plants treated with the highest element concentrations.     

Big data and artificial intelligence application in energy field: a bibliometric analysis

Environmental Science and Pollution Research - This paper uses bibliometrics to characterize the knowledge systems of big data, artificial intelligence (AI), and energy based on the Science...     

杭州市大气降雨化学组成特征及来源分析

研究了2006-2008年杭州市大气降雨的化学组成及其来源,并与国内外的相关研究结果进行了比较.结果表明,总体来说,杭州市各月的降雨量相对均衡,月均降雨量为7.1～25.3 mm;降雨pH为3.99～5.64,雨量加权平均pH为4.50;降雨电导率为1.30～8.55 mS/m,雨量加权平均值为3.73 mS/m,降雨电导率与雨量、pH均呈负相关;夏季降雨中的水溶性离子平均浓度较低,雨量加权平均pH较高,而其他季节降雨中的水溶性离子平均浓度较高,雨量加权平均pH较低;其中SO2-4和NO-3是降雨中的主要水溶性阴离子,NH+4和Ca2+是降雨中的主要水溶性阳离子;SO2-4/NO-3(当量浓度比)为2.87,低于国内其他城市,降雨类型为硫酸型,但硝酸在降雨酸性中起的作用有增大趋势;降雨中水溶性阳离子总当量浓度/水溶性阴离子总当量浓度为1.11,低于国内外大部分城市;NH+4、Ca2+当量浓度之和与SO2-4、NO-3当量浓度之和之比为0.89,也低于国内外大部分城市,NH+4和Ca2+是主要的酸性中和物质;总体来说,杭州市降雨中各水溶性离子间的相关性均较好,但H+浓度与大部分离子的相关性不明显;杭州降雨中的化学组分主要来源于工业源和地壳源,此外部分来源于海盐粒子.     

Seasonal trend of fog water chemical composition in the Po Valley

Fog frequency in the Po Valley, Northern Italy, can be as high as 30% of the time in the fall-winter season. High pollutant concentrations have been measured in fog water samples collected in this area over the past few years. The combined effects of high fog occurrence and high pollutant loading of the fog droplets can determine, in this area, appreciable chemical deposition rates. An automated station for fog water collection was developed, and deployed at the field station of S. Pietro Capofiume, in the eastern part of the Po Valley for an extended period: from the beginning of November 1989 to the end of April 1990. Time-resolved sampling of fog droplets was carried out during all fog events occurring in this period, and chemical analyses were performed on the collected samples. Statistical information on fog occurrence and fog water chemical composition is reported in this paper, and a tentative seasonal deposition budget is calculated for H+, NH4+, NO3- and SO4(2-) ions. The problems connected with fog droplet sampling in sub-freezing conditions are also addressed in the paper.     

Sources and chemical composition of atmospheric fine and coarse particles in the Helsinki area

During April 1996–June 1997 size-segregated atmospheric aerosol particles were collected at an urban and a rural site in the Helsinki area by utilising virtual impactors (VI) and Berner low-pressure impactors (BLPI). In addition, VI samples were collected at a semi-urban site during October 1996–May 1997. The average PM_2.3 (fine particle) concentrations at the urban and rural sites were 11.8 and 8.4 μg/m³, and the PM_2.3−15 (coarse particle) concentrations were 12.8 and about 5 μg/m³, respectively. The difference in fine particle mass concentrations suggests that on average, more than one third of the fine mass at the urban site is of local origin. Evaporation of fine particle nitrate from the VI Teflon filters during sampling varied similarly at the three sites, the average evaporation being about 50–60%.The average fine particle concentrations of the chemical components (25 elements and 13 ions) appeared to be fairly similar at the three sites for most components, which suggests that despite the long-range transport, the local emissions of these components were relatively evenly distributed in the Helsinki area. Exceptions were the average fine particles Ba, Fe, Sb and V concentrations that were clearly highest at the urban site pointing to traffic (Ba, Fe, Sb) and to combustion of heavy fuel oil (V) as the likely local sources. The average coarse particle concentrations for most components were highest at the urban site and lowest at the rural site.Average chemical composition of fine particles was fairly similar at the urban and rural sites: non-analysed fraction (mainly carbonaceous material and water) 43% and 37%, sulphate 21% and 25%, crustal matter 12% and 13%, nitrate 12% and 11%, ammonium 9% and 10% and sea-salt 2.5% and 3.2%, respectively. At the semi-urban site also, the average fine particle composition was similar. At the urban site, the year round average composition of coarse particles was dominated by crustal matter (59%) and the non-analysed components (28%, mainly carbonaceous material and water), while the other contributions were much lower: sea-salt 7%, nitrate 4% and sulphate 2%. At the rural site, the coarse samples were collected in spring and summer and the percentage was clearly lower for crustal matter (37%) and sea-salt (3%) but higher for the not-analysed fraction (51%). At the semi-urban site, the average composition of coarse particles was nearly identical to that at the urban site.Correlations between the chemical components were calculated separately for fine and coarse particles. In urban fine particles sulphate, ammonium, Tl, oxalate and PM_2.3 mass correlated with each other and originated mainly from long-range transport. The sea-salt ions Na⁺, Cl⁻ and Mg²⁺ formed another group and still another group was formed by the organic anions oxalate, malonate, succinate, glutarate and methane sulphonate. Ni and V correlated strongly pointing to combustion of heavy fuel oil as the likely source. In addition, some groups with lower correlations were detected. At the rural and semi-urban sites, the correlating components were rather similar to those at the urban site, although differences were also observed.     

A simplified approach to the indirect evaluation of the chemical composition of atmospheric aerosols from PM mass concentrations

The present work shows a straightforward procedure to indirectly estimate the chemical composition at a given site only from the determination of the PM concentrations, and the classification of the days according to the main meteorological scenarios. A previous study based on the mean chemical composition associated to the main meteorological scenarios is required.This experiment has been carried out with data from two monitoring sites in the North-Western Mediterranean, one regional and one suburban background. At both sites, one-year datasets on chemical PM₁₀ composition were obtained. Based on these datasets, the mean PM₁₀ compositions according to the most relevant meteorological situations were calculated for both locations. After that, the reconstruction of the chemical composition for all the days with available PM₁₀ concentrations was completed. Subsequently, the estimated PM₁₀ composition was compared with that determined experimentally. The comparison between the rebuilt and the experimental results was very satisfactory in the case of the regional background site, and relatively replaced in the other case. Furthermore, the validation of the method at the regional background site has been conducted from the reconstruction of a 4-year data base, and subsequent comparison with the experimental chemical composition.Our results show that it is possible to attain a good approach to the chemical composition at regional background sites, where local emission sources are negligible. Conversely, when the local sources rise in importance, i.e., at a suburban background site, the approach is suitable only for those components with a more regional origin and/or those from long range transport of air masses.     

Exploratory data analysis in the study of 7Be present in atmospheric aerosols

Purpose

Exploratory data analysis (EDA) is applied in this research to study the behavior of radioactive aerosols present in the surface atmosphere of Granada, using ⁷Be as radiotracer. The reason for this study is to reduce the large number of parameters involved in understanding their behavior, given the complexity of the atmosphere.

Methods

Aerosol particles were collected weekly in Granada (Spain) over a 5-year period. Low-background gamma spectrometry was used to determine concentrations of ⁷Be-aerosol activity. The variables studied were: ⁷Be concentration, cosmic ray intensity, temperature, temperature interval, rainfall, relative humidity, and Saharan intrusions. Least significant difference test (LSD), hierarchical cluster analysis (HCA), and principal component analysis (PCA) with varimax rotation have been applied to study the datasets.

Results and discussion

The results of our study reveal that aerosol behavior is represented by two principal components which explain 86.23?% of total variance. Components PC1 and PC2 respectively explain 74.61 and 11.62?% of total variance. PC1 explains the cyclical and seasonal pattern of the samples, while PC2 is related to the production of ⁷Be. In addition, PCA and HCA show good distribution of the samples by families with two groups, summer and winter, at the extremes and spring?Cautumn in the middle. This result corroborates that there are no differences between spring and autumn in the climate of Granada.

Conclusions

EDA has been found to be quite useful in studying the behavior of radioactive aerosols in the surface atmosphere of a city with the climate and geographical characteristics of Granada.     

An urban emissions inventory for South America and its application in numerical modeling of atmospheric chemical composition at local and regional scales

This work describes the development of an urban vehicle emissions inventory for South America, based on the analysis and aggregation of available inventories for major cities, with emphasis on its application in regional atmospheric chemistry modeling. Due to the limited number of available local inventories, urban emissions were extrapolated based on the correlation between city vehicle density and mobile source emissions of carbon monoxide (CO) and nitrogen oxides (NOx). Emissions were geographically distributed using a methodology that delimits urban areas using high spatial resolution remote sensing products. This numerical algorithm enabled a more precise representation of urban centers. The derived regional inventory was evaluated by analyzing the performance of a chemical weather forecast model in relation to observations of CO, NOx and O₃ in two different urban areas, São Paulo and Belo Horizonte. The gas mixing ratios simulated using the proposed regional inventory show good agreement with observations, consistently representing their hourly and daily variability. These results show that the integration of municipal inventories in a regional emissions map and their precise distribution in fine scale resolutions are important tools in regional atmospheric chemistry modeling.     

Dynamic chemical characteristics of soil solution after pig manure application: A column study

When manures from intensive livestock operations are applied to agricultural or vegetable fields at a high rate, large amounts of salts and metals will be introduced into soils. Using a column leaching experiment, this study assessed the leaching potential of the downward movement of Cu and Zn as well as some salt ions after an intensive farm pig manure at rates of 0%, 5% and 10% (w/w) were applied to the top 20 cm of two different textured soils (G soil -sandy loam soil; H soil-silty clay loam soil), and investigated the growth of amaranth and Cu and Zn transfer from soil to amaranth (Amaranthus tricolor). Soil solutions were obtained at 20, 40 and 60 cm depth of the packed column and analyzed for pH, electrical conductivity (EC), dissolved organic matter (DOC) and Cu and Zn concentrations. The results indicated that application of pig manure containing Cu and Zn to sandy loam soil might cause higher leaching and uptake risk than silty clay loam soil, especially at high application rates. And manure amendment at 5% and 10% significantly decreased the biomass of amaranth, in which the salt impact rather than Cu and Zn toxicity from manures played more important role in amaranth growth. Thus the farmer should avoid application the high rate of pig manure containing metal and salt to soil at a time, especially in sandy soil.     

Dynamic chemical characteristics of soil solution after pig manure application: a column study

When manures from intensive livestock operations are applied to agricultural or vegetable fields at a high rate, large amounts of salts and metals will be introduced into soils. Using a column leaching experiment, this study assessed the leaching potential of the downward movement of Cu and Zn as well as some salt ions after an intensive farm pig manure at rates of 0%, 5% and 10% (w/w) were applied to the top 20 cm of two different textured soils (G soil -sandy loam soil; H soil-silty clay loam soil), and investigated the growth of amaranth and Cu and Zn transfer from soil to amaranth (Amaranthus tricolor). Soil solutions were obtained at 20, 40 and 60 cm depth of the packed column and analyzed for pH, electrical conductivity (EC), dissolved organic matter (DOC) and Cu and Zn concentrations. The results indicated that application of pig manure containing Cu and Zn to sandy loam soil might cause higher leaching and uptake risk than silty clay loam soil, especially at high application rates. And manure amendment at 5% and 10% significantly decreased the biomass of amaranth, in which the salt impact rather than Cu and Zn toxicity from manures played more important role in amaranth growth. Thus the farmer should avoid application the high rate of pig manure containing metal and salt to soil at a time, especially in sandy soil.     

Source characterisation of road dust based on chemical and mineralogical composition

Road dust contain potentially toxic pollutants originating from a range of anthropogenic sources common to urban land uses and soil inputs from surrounding areas. The research study analysed the mineralogy and morphology of dust samples from road surfaces from different land uses and background soil samples to characterise the relative source contributions to road dust. The road dust consist primarily of soil derived minerals (60%) with quartz averaging 40-50% and remainder being clay forming minerals of albite, microcline, chlorite and muscovite originating from surrounding soils. About 2% was organic matter primarily originating from plant matter. Potentially toxic pollutants represented about 30% of the build-up. These pollutants consist of brake and tire wear, combustion emissions and fly ash from asphalt. Heavy metals such as Zn, Cu, Pb, Ni, Cr and Cd primarily originate from vehicular traffic while Fe, Al and Mn primarily originate from surrounding soils. The research study confirmed the significant contribution of vehicular traffic to dust deposited on urban road surfaces.     

Chemometric data analysis application to Sparus aurata samples from two offshore farming plants along the Apulian (Italy) coastline

The levels of polychlorodibenzo-p-dioxins (PCDDs), polychlorodibenzofurans (PCDFs), dioxin-like polychlorobiphenyls (DL-PCBs), non-dioxin-like polychlorobiphenyls (NDL-PCBs), and polybromodiphenyl ethers (PBDEs) in fish collected from two marine offshore farming plants were determined. Each sample was constituted by specimens of the same size collected at the same time in four different seasons along the farming year. The feeds given were of industrial origin and the plants were positioned in two different sites respectively exposed to different environmental characteristics. A chemometric approach was applied to interpret the subtle differences observed in fish body burdens across the three chemical groups taken into consideration. The approach consisted in a stepwise multivariate process including a hierarchical cluster analysis (CA) and a linear discriminant analysis (DA). The two main clusters determined by CA were subjected to the canonical DA, backward and forward selection procedures to select the best discriminative functions. A clear temporal and spatial discrimination was found among the samples. Across the three chemical groups, the monthly separation seemed to depend on the growth process and the main exposure was due to the feed. In addition, the two plants differed significantly from the environmental point of view and the most important discriminating group of chemicals were the NDL-PCBs. The approach resulted really effective in discriminating the subtle differences and in individuating suggestions to improve the quality of culturing conditions.     

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.     

光纤化学传感器的实验研究

主要研究对象为基于离子选择性中性载体的无机离子化学传感器,采用以吸光度为主要测量信号的分光光度法为主要分析方法。依据该传感器的特征,可使分析光束与被测溶液分开,甚至对不透明的液体作分光光度分析。为此,在离子选择性中性载体PVC膜的响应特征基础上设计并研制一种新型结构的光吸收池,应用前景广阔。     

BETR-World: a geographically explicit model of chemical fate: application to transport of alpha-HCH to the Arctic

The Berkeley-Trent (BETR)-World model, a 25 compartment, geographically explicit fugacity-based model is described and applied to evaluate the transport of chemicals from temperate source regions to receptor regions (such as the Arctic). The model was parameterized using GIS and an array of digital data on weather, oceans, freshwater, vegetation and geo-political boundaries. This version of the BETR model framework includes modification of atmospheric degradation rates by seasonally variable hydroxyl radical concentrations and temperature. Degradation rates in all other compartments vary with seasonally changing temperature. Deposition to the deep ocean has been included as a loss mechanism. A case study was undertaken for alpha-HCH. Dynamic emission scenarios were estimated for each of the 25 regions. Predicted environmental concentrations showed good agreement with measured values for the northern regions in air, and fresh and oceanic water and with the results from a previous model of global chemical fate. Potential for long-range transport and deposition to the Arctic region was assessed using a Transfer Efficiency combined with estimated emissions. European regions and the Orient including China have a high potential to contribute alpha-HCH contamination in the Arctic due to high rates of emission in these regions despite low Transfer Efficiencies. Sensitivity analyses reveal that the performance and reliability of the model is strongly influenced by parameters controlling degradation rates.