Fluxes and pools of methane in wetland rice soils with varying organic inputs

Measurements of methane emission rates and concentrations in the soil were made during four growing seasons at the International Rice Research Institute in the Philippines, on plots receiving different levels of organic input. Fluxes were measured using the automated closed chambers system (total emission) and small chambers installed between plants (water surface flux). Concentrations of methane in the soil were measured by collecting soil cores including the gas phase (soil-entrapped methane) and by sampling soil solution in situ (dissolved methane). There was much variability between seasons, but total fluxes from plots receiving high organic inputs (16–24 g CH₄ m^–2) always exceeded those from the low input plots (3–9 g CH₄ m^–2). The fraction of the total emission emerging from the surface water (presumably dominated by ebullition) was greater during the first part of the season, and greater from the high organic input plots (35–62%) than from the low input plots (15–23%). Concentrations of dissolved and entrapped methane in the low organic input plots increased gradually throughout the season; in the high input plots there was an early-season peak which was also seen in emissions. On both treatments, periods of high methane concentrations in the soil coincided with high rates of water surface flux whereas low concentrations of methane were generally associated with low flux rates.     

郑州市PM2.5浓度时空分布特征及预测模型研究

利用统计学原理和GIS技术,对郑州市2013年8月17—12月31日期间PM2.5浓度时空分布特征进行分析,同时结合气象资料与前一日污染数据,建立人工神经网络反向传播算法模型(BP-ANN)和多元线性回归模型用于该市细颗粒物污染的短期预测。结果表明,郑州市PM2.5浓度日变化呈单峰模式,随逆温现象的发生和交通的密集于上午11:00达到峰值,午后逐步下降。在工作日、周末与国庆节的对比中,国庆节期间颗粒物污染浓度高出平日32.8%,表明人为活动的加剧影响PM2.5的排放;周末与工作日期间无显著差异。在空间分布上,金水区、管城回族区污染最为严重,工业燃煤、地铁施工等源排放是造成污染的主要原因;位于远郊的岗里水库,受秸秆焚烧和市区污染输送等影响,PM2.5浓度亦维持较高水平。最后,研究将所构建的BP-ANN预测模型和多元线性回归模型对比,结果发现两模型在建模阶段预测值与真实值的拟合一致性指标分别为0.944、0.918,均方根误差分别为59.788、70.611;验证阶段拟合一致性指标分别为0.854、0.794,平均绝对误差分别为25.298、32.775,表明BP-ANN模型在预测郑州市PM2.5污染过程中更具优势。     

Comparison of a Subjective and a Physical Approach for Identification of Priority Areas for Soil and Water Management in a Watershed – A Case Study of Nagwan Watershed in Hazaribagh District of Jharkhand, India

The present investigation was an attempt to compare the within-watershed prioritization capabilities of a physical model based SDSS with the SYI and RPI model based subjective-SDSS, conventionally devised for between-watershed prioritizations, by All India Soil Survey and Land Use Planning Division of Ministry of Agriculture, Government of India. Application of these two approaches on a test watershed situated in Damodar-Barakar catchment in India, the second most seriously eroded area in the world, demonstrated that the proposed physical model based SDSS was capable of realistically and logically mimicking the sub-watershed-scaled water and soil losses thereby suggesting its immense application potential for priority area identification within the test watershed. In contrast to the proposed physical method, the subjective approaches, which assigned totally reverse priorities to about 67–93% of the test-sub-watersheds, were observed to be incapable of realistically assessing the impact of topography and varied land use and soil types in the test watershed on their sub-watershed scaled run-off and soil loss generating potential. Besides, the physical approach could be used for assessing the annual dynamics of the total water and sediment yields, under prevailing resource management systems in the test watershed with good to moderately good correlation coefficients of 0.83 and 0.65; model efficiency coefficients of 0.54 and 0.70; mean relative errors of –4.28% and –17.97% and root mean square prediction errors of 71.8 mm and 9.63 t/ha, respectively.     

The creation of an historical meteorological database for environmental dose assessment

The focus of this study is to develop wind data for the SavannahRiver Site (SRS) between 1955 and 1961 to be used in an assessment of estimates of atmospheric dispersion and downwindrisk at the Savannah River Site. In particular, a study of theuncertainties of radioiodine dosimetry from the late 1950sprovides the underlying motivation for developing historicalwindroses at the Savannah River Site (SRS). Wind measurement towers did not exist at the SRS until theearly 1970s. Three relatively simple methods were used to createa 1955–1961 meteorological database for the SRS for a dosereconstruction project. The winds were estimated from onsitemeasurements in the 1990s and National Weather Service (NWS)observations in the 1990s and 1950s using (1) a linear regressionmethod, (2) a similarity theory approach, and (3) a simplestatistical differences method. The criteria for determining success were based on (1) howwell the mean values and standard deviations of the predictedwind speed agree with the known SRS values from the 1990s, (2) the shape of the predicted frequency distribution functions forwind speed, and (3) how closely the predicted windroses resembledthe SRS windrose for the 1990s. The linear regression model's wind speed distribution functionwas broad, flat, and skewed too much toward higher wind speeds.The similarity theory approach produced a wind speed distributionfunction that contained excess predicted speeds in the range 0–1.54 m s^-1 (0–3 kts) and had `excluded' bins caused bypredictions being made from integer values of knots in the NWSdata. The distribution function from the mean difference methodwas smooth with a shape like a Weibull distribution with a shapeparameter of 2 and appearedto resemble closely the SRS 1992–1996 distribution.The wind directions for all three methods of approach weresuccessfully based on the mean difference method. It wasdifficult to discern differences among the wind roses produced bythe three methods so the wind speed distribution functions needto be examined in order to make an informed choice for dose reconstruction.     

Measurement of atmospheric concentrations of common household pesticides: A pilot study

Air concentrations of 28 of the most commonly used household pesticides were measured inside nine homes in Jacksonville, Florida, and compared with corresponding outdoor levels. The households selected were sorted into three categories according to the degree of pesticide indoor usage. Personal air monitoring was also performed on one resident of each household by means of a portable sampler, which was kept with the person at all times. Five of the pesticides were found in the air inside of the majority of the homes at concentrations as high as 15 gm^–3 (average concentrations, 12 ngm^–3 to 2.4 gm^–3). Indoor levels were generally one to two ordrrs of magnitude higher than surrounding outdoor air levels and personal air measurements were within ± 50% of corresponding indoor values. All samples were collected over 24-hr periods on polyurethane foam and analyzed by capillary colum gas chromatography with mass spectrometric and/or electron capture detection.     

Urban Air Quality Assessment Model: UAQAM

The Urban Air Quality Assessment Model (UAQAM) calculates urban concentrations caused by city emissions themselves, the so-called city background concentration. Three versions of the model for describing the dispersion were studied: Box, Gifford Hanna (GH) and a combined form of these two (Box–GH model). Regional background emissions contributing to the urban background concentration were accounted for by using measurements and calculations from a dispersion model on the continental scale. The results of the three UAQAM versions for a number of European cities were compared to measurements of SO₂ and NO _X . The Box–GH model shows better results when compared to the Box model and slightly better results in comparison to the GH model. The Box–GH model has been taken as a starting point for the assessment of urban air quality with UAQAM.     

Monitoring and assessment of soil and forage molybdenum near an atmospheric source

Forage and soil molybdenum (Mo) were measured in the vicinity of a Mo processing plant in southwestern Pennsylvania, USA. Molybdenum concentrations in red clover plants (Trifolium pratense L.), measured at 23 sites, ranged from 1.1 to 56.6 mg kg^–1. Fourteen of the 23 sites sampled had red clover plants with Mo concentrations over the threshold value of 6 mg kg^–1. Red clover Cu:Mo concentration ratios were below the recommended ratio of 4 in 19 of the sites. The low Cu:Mo values, along with high plant Mo concentrations, indicates that there is a potential risk of molybdenosis in ruminant animals in this area. Acid digested (sorbed) soil Mo concentrations, measured at 30 sites, ranged from 7.0 (background level) to 131 mg kg^–1. Using the Baker Soil Test (BST) extract, molybdenum soil concentrations ranged from 0.01 to 3.99 mg kg^–1. Regression equations were developed to predict plant uptake of soil Mo based on the red clover plant, soil extracts and soil pH data. The R-squared values for predicting plant uptake were 81.9% for the BST extract and 81.6% for the acid digestion extract plus soil pH. Based on the above results, a protocol has been implemented for assessing the risk of high soil Mo near this Mo processing plant.     

Mapping Soil Gas Radon Concentration: A Comparative Study of Geostatistical Methods

Understanding soil gas radon spatial variations can allow the constructor of a new house to prevent radon gas flowing from the ground. Indoor radon concentration distribution depends on many parameters and it is difficult to use its spatial variation to assess radon potential. Many scientists use to measure outdoor soil gas radon concentrations to assess the radon potential. Geostatistical methods provide us a valuable tool to study spatial structure of radon concentration and mapping. To explore the structure of soil gas radon concentration within an area in south Italy and choice a kriging algorithm, we compared the prediction performances of four different kriging algorithms: ordinary kriging, lognormal kriging, ordinary multi-Gaussian kriging, and ordinary indicator cokriging. Their results were compared using an independent validation data set. The comparison of predictions was based on three measures of accuracy: (1) the mean absolute error, (2) the mean-squared error of prediction; (3) the mean relative error, and a measure of effectiveness: the goodness-of-prediction estimate. The results obtained in this case study showed that the multi-Gaussian kriging was the most accurate approach among those considered. Comparing radon anomalies with lithology and fault locations, no evidence of a strict correlation between type of outcropping terrain and radon anomalies was found, except in the western sector where there were granitic and gneissic terrain. Moreover, there was a clear correlation between radon anomalies and fault systems.     

Concentrations of heavy metals in oysters from the coastline of Northern Territory,Australia

The concentrations of five metals in oysters from ten locations along the Northern Territory coastline were determined during the dry season of 1989. The measured concentrations of iron, cadmium, zinc, manganese and copper in oysers were 11.6–274, 0.17–9.1, 4.79–735, 0.25–69.85 and nd-70.2 µg g^–1 wet weight. The level of cadmium exceeded the National Health and Medical Research Council (NHMRC) recommended limit at five sites. The largest fluctuation occurred in zinc and cadmium while the other metals displayed much less variation.     

A Wavelet-based Neural Network Model to Predict Ambient Air Pollutants’ Concentration

The present paper proposes a wavelet based recurrent neural network model to forecast one step ahead hourly, daily mean and daily maximum concentrations of ambient CO, NO₂, NO, O₃, SO₂ and PM_2.5 — the most prevalent air pollutants in urban atmosphere. The time series of each air pollutant has been decomposed into different time-scale components using maximum overlap wavelet transform (MODWT). These time-scale components were made to pass through Elman network. The number of nodes in the network was decided on the basis of the strength (power) of the corresponding input signals. The wavelet network model was then used to obtain one-step ahead forecasts for a period extending from January 2009 to June 2010. The model results for out of sample forecast are reasonably good in terms of model performance parameters such as mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), normalized mean absolute error (NMSE), index of agreement (IOA) and standard average error (SAE). The MAPE values for daily maximum concentrations of CO, NO₂, NO, O₃, SO₂ and PM2.5 were found to be 9.5%, 17.37%, 21.20%, 13.79%, 17.77% and 11.94%, respectively, at ITO, Delhi, India. Bearing in mind that the forecasts are for daily maximum concentrations tested over a long validation period, the forecast performance of the model may be considered as reasonably good. The model results demonstrate that a judicious selection of wavelet network design may be employed successfully for air quality forecasting.     

Measurements and Modelling of Air Pollution in a Street Canyon in Helsinki

A measuring campaign was conducted in the street canyon 'Runeberg street' in Helsinki in 1997. Hourly concentrations of carbon monoxide (CO), nitrogen oxides (NO_X), nitrogen dioxide (NO₂) and ozone (O₃) were measured at the street and roof levels, and the relevant hourly meteorological parameters were measured at the roof level. The hourly street level measurements and on-site electronic traffic counts were conducted during the whole year 1997, and roof level measurements were conducted during approximately two months, from 3 March to 30 April in 1997. The Operational Street Pollution Model (OSPM) was used to calculate the street concentrations and the results were compared with the measurements. The overall agreement between measured and predicted concentrations was good for CO and NO_x, but the model slightly overestimated the measured concentrations of NO₂. The database, which contains all measured and predicted data, is available for a further testing of other street canyon dispersion models.     

Statistical Analysis of Air Pollutants and Meteorological Parameters in Afyon, Turkey

In this study, the relation between sulfur dioxide (SO₂) and particulate matter (PM) concentrations periodically measured in the city of Afyon’s atmosphere with meteorological factors such as precipitation, humidity, temperature, wind velocity, and inversion were investigated. The mean values of SO₂ and PM concentrations measured during the winter months of October–March 1990–1999 were correlated with the meteorological parameters of the same period. Simple and multiple linear regression analysis were utilized to evaluate the contribution of meteorological variables. The statistical results show that the pollutants, i.e., SO₂ and PM are dependent upon humidity, temperature, and inversion at the 1% significance level; while the dependence of both pollutants with temperature is negative when those of humidity and inversion are positive. Two models in which temperature and inversion are dependent with multiple variables are recommended for predicting the contribution of meteorological parameters on SO₂ and PM. In addition, the relationship between humidity, temperature, and inversion with pollutants is also determined using nonlinear (polynomial) models.     

Dynamics of atmospheric polychlorinated biphenyls (PCBs): concentrations, patterns, partitioning, and dry deposition level estimations in a residential site of Turkey

Air samples were collected at a residential site (Gulbahce, Bursa, Turkey) between August 2004 and April 2005 using a modified high volume air sampler. The mean of gas and particle phase concentrations of polychlorinated biphenyls (PCBs) were 468 ± 297 and 43 ± 37 pg m^???3 (average ± standard deviation, SD), respectively. The dominated PCB homologs were 3-CBs, 4-CBs, and 5-CBs. The measured PCB concentrations were higher than the values of pristine sites. In order to assess the gas/particle partitioning fate, log K _P–log $P_{\rm L}^o$ , log K _P–log K _OA and the Junge–Pankow model were applied to the data. Experimental K _P was well correlated with $\log P_{\rm L}^o$ and log K _OA at p?<?0.05. Then, dry deposition fluxes were estimated using atmospheric concentrations and dry deposition velocities obtained from literature. A correlation matrix was formed for PCB homologs including 27 congeners with concurrently measured 16 polycyclic aromatic hydrocarbons (PAHs) and meteorological parameters. Most of PAH compounds were significantly correlated with 5-CBs and 6-CBs.     

Monitoring and Assessment of Exhaust Emission in Bangkok Street Air

Measurement of the exhaust emission from gasoline-powered motor vehicles in Bangkok were performed on chassis dynamometer. A fleet of 10 vehicles of different model, years and manufacturers were selected to measure the air pollutants in the exhaust effluent. The study revealed that the carbon monoxide and hydrocarbon emissions averaged 32.3–64.2 and 1.82–2.98 g km^–1, respectively, for 1990–1992 cars and decreased to 17.8–40.71 and 0.75–1.88 g km^–1, respectively, for 1994–1995 cars. A monitoring program for air pollutant concentrations in ambient air was also conducted to evaluate the air pollution problems in Bangkok arising from vehicle exhaust emission. Four air sampling stations were strategically established to cover the Bangkok Metropolitan Region (BMR). Composite air samples in this study area were collected during the day/night times and weekday/weekend. The average concentrations of suspended particulate matter, carbon monoxide, and nitrogen dioxide in Bangkok street air were found to be 0.65 mg/m³ (24 hr ave.), 19.02 mg/m³ (8 hr ave.) and 0.021 mg/m³ (1 hr ave.), respectively. The average concentrations of benzene and toluene in the ambient air of the study area were found to be 15.07–50.20 and 25.76–130.95 g/mf³, respectively, for 8 hr average. These results indicated that there was a significant increase in air pollutant emissions with increasing car mileage and model year. Subsequent analysis of data showed that there were only 20% of the test vehicles complied to approved emission standard. The finding also revealed that there was a correlation between the average air pollutant concentrations with average traffic speed in each traffic zone of the Bangkok Metropolitan Region (BMR).     

Modeling of Hydrodynamics and Cohesive Sediment Processes in an Estuarine System: Study Case in Danshui River

The Danshui River estuarine system is the largest estuarine system in northern Taiwan and is formed by the confluence of Tahan Stream, Hsintien Stream, and Keelung River. A comprehensive one-dimensional (1-D) model was used to model the hydrodynamics and cohesive sediment transport in this branched river estuarine system. The applied unsteady model uses advection/dispersion equation to model the cohesive sediment transport. The erosion and deposition processes are modeled as source/sink terms. The equations are solved numerically using an implicit finite difference scheme. Water surface elevation and longitudinal velocity time series were used to calibrate and verify the hydrodynamics of the system. To calibrate and verify the mixing process, the salinity time series was used and the dispersion coefficient of the advection/dispersion equation was determined. The cohesive sediment module was calibrated by comparing the simulated and field measured sediment concentration data and the erosion coefficient of the system was determined. A minimum mean absolute error of 4.22 mg/L was obtained and the snapshots of model results and field measurements showed a reasonable agreement. Our modeling showed that a 1-D model is capable of simulating the hydrodynamics and sediment processes in this estuary and the sediment concentration has a local maximum at the limit of salinity intrusion. Furthermore, it was indicated that for Q ₅₀ (the flow which is equaled or exceeded 50% times), the turbidity maximum location during neap tide is about 1 km closer to the mouth compared to that during spring tide. It was found that deposition is the dominant sediment transport process in the river during spring–neap periods. It was shown that, while sediment concentration at the upstream depends on the river discharge, the concentration in the downstream is not a function of river discharge.     

Analysis of Wet Precipitation of Air Pollutants in Mumbai (India)

Bulk precipitation samples at Mumbai (India) were collectedduring the monsoon seasons of 1991 to 1996 and analysed forionic concentrations using an Ion Chromatograph DIONEX model100. The variability of sulphate to nitrate ratio in rainwaterfluctuates in a wide range from 1.5 to 20 and governed by thesulphate concentrations in the sample. The regression analysisof the data reveals that in the bulk precipitation at Mumbai, SO₄ ^2- is becoming increasingly important relative toNO₃ ^-. The role of meteorological influences onscavenging of air pollutants by rain water has been tried toexplain the phenomena. The computed wet deposition rates for Sand N during 1991–1996 show that the S deposition is higherthan N in all the years. There is a wide fluctuation indeposition rates of S ranging from 2 to 55 kg km² per annum.     

General plume dispersion model (GPDM) for point source emission

Gaussian-based dispersion models are widely used to estimate local pollution levels. The accuracy of such models depends on stability classification schemes as well as plume rise equations. A general plume dispersion model (GPDM) for a point source emission, based on Gaussian plume dispersion equation, was developed. The program complex was developed using Java and Visual basic tools. It has the flexibility of using five kinds of stability classification schemes, i.e., Lapse Rate, Pasquill–Gifford (PG), Turner, σ–θ and Richardson number. It also has the option of using two types of plume rise formulations – Briggs and Holland’s. The model, applicable for both rural and urban roughness conditions, uses meteorological and emission data as its input parameters, and calculates concentrations of pollutant at the center of each cell in a predefined grid area with respect to the given source location. Its performance was tested by comparing with 4-h average field data of continuous releases of SO₂ from Dadri thermal power plant (Uttar Pradesh, India). Results showed that the Turner scheme used with Holland’s equation gives the best outcome having a degree of agreement (d) of 0.522.     

The influence of two culturing techniques on toxicity of four chemicals in Arabidopsis

Plots of Arabidopsis thaliana L. (Heynh.) plants were grown in two hydroponic systems, one using a solid rooting support media (vermiculite) and the other a flowing solution culture. Both were tested with various concentrations of bromacil (5-bromo-3-sec-butyl-6-methyluracil), dichlobenil (2,6-dichlorobenzonitrile), copper sulfate (CuSO₄·5H₂O) and 3-aminotriazole. The effects on biomass production were compared. Plants treated with bromacil at concentrations up to 0.05 mg l^–1 were similarly reduced in growth in both culture methods. However, the toxic effects of dichlobenil, copper sulfate and 3-aminotriazole were different for both culture methods. Dichlobenil decreased plant growth in the solution culture at lower concentrations than in the vermiculite system. All aspects of growth were suppressed in the solution culture while the vegetative weight was unaffected in the vermiculite culture. Plants treated with 20 mg l^–1 copper sulfate in solution culture yielded mean seed weight of 1.2 g/plot compared to 3.1 g/plot when treated with the same concentration in the double-plot system. Plants treated with 0.5 mg l^–1 3-aminotriazole in solution culture produced no seed, while plants with the same nominal concentration in the double-pot method produced a mean seed weight of 6.5 g/plot. Solution culture testing was generally more sensitive and since roots were bathed directly in a solution of known pH, nutrient level and chemical concentration, the test conditions were more accurately defined.     

EFFICIENCY OF AN INFILTRATION BASIN IN REMOVING CONTAMINANTS FROM URBAN STORMWATER

The efficiency of a Stormwater Infiltration Basin (SIB) to remove contaminants from urban stormwater was assessed in the current investigation. The SIB, installed in an urban suburb in eastern Sydney (Australia), was monitored over seven rainfall events to assess the removal efficiency of the remedial device for total suspended solids (TSS), nutrients (TP, TKN, N_ox, TN), trace metals (Cd, Cr, Cu, Fe, Mn, Ni, Pb, Zn), organochlorine pesticides and faecal coliforms (FC) from stormwater. The weighted average concentration (WAC) of TSS in the stormwater effluent from the SIB was reduced by an average of 50%, whereas the WAC of Cu, Pb and Zn were also reduced by an average 68%, 93% and 52%, respectively. However, the WAC of Cr, Fe, Mn and Ni displays either similar concentrations as the stormwater influent (Cr and Mn), or substantially higher concentrations (Fe and Ni), due possibly to leaching of fine-grained zeolite clay particles in the filtration bed. The mean removal efficiency of the SIB for total phosphorus (TP) and total Kjeldahl nitrogen (TKN) was 51% and 65%, respectively. In contrast, the average WAC of oxidisable nitrogen (nitrate and nitrite nitrogen or N_ox) is about 2.5 times greater in the effluent (1.34 ± 0.69 mg L^–1) than in the incoming stormwater (0.62 ± 0.25 mg L^–1). The WAC of total nitrogen (TN) was similar for stormwater at the in-flow and out-flow points. The SIB was very efficient in removing FC from stormwater; and the WAC of almost 70 (100 mL)^–1 at inflow was reduced to <2000 cfu (100 Ml)^–1 at the outflow, representing a mean removal efficiency of 96%. Due to the low concentrations of Cd, organochlorine pesticides and PAHs in the stormwater, it was not possible to assess the efficiency of the SIB in removing these contaminants.