Subsurface nutrient modelling using finite element model under Boro rice cropping system

Boro rice, an emerging low-risk crop variety of rice, cultivated using residual or stored water after Kharif season. To enhance the quality and production of rice, potassium (K) and phosphorus (P) are the common constituents of agricultural fertilizers. However, excess application of fertilizers causes leaching of nutrients and contaminates the groundwater system. Therefore, assessment and optimization of fertilizer dose are needed for better management of fertilizers. Towards this, the present study determines the path, persistence, and mobility of K and P under the Boro rice cropping system. The experimental site consisted of four plots having Boro rice with four different fertilizer doses of nitrogen (N), P, K viz. 100%, 75%, 50%, and 25% of the recommended dose. Disturbed soil samples were analysed for K and P from pre-sown land to tillering stage at 0–5, 5–10, 10–15, 15–30, 30–45, and 45–60 cm depths. Simultaneously, K and available P were also simulated in the subsurface soil layers through the HYDRUS-1D model. The statistical comparisons were made with RMSER, E, and PBIAS between the modelled values and laboratory-measured values. Although, the results showed that all the treatments considered had agreeable simulations for both K and P, the K simulations were found to be better as compared to P simulations except for 25% where P simulations outperformed K. The simulated concentration at all doses was found most appropriate when measured for the subsurface layers (up to 45 cm), while showed an underestimation in the bottom layers (45–60 cm) of soil.

     

Multivariate assessment of outflow water quality in highly urbanized creek system: implication of natural and anthropogenic processes

Environmental Science and Pollution Research - Nutrient source and transport study in tropical creeks adjacent to megacities are sparse on a regional and global scale. High-frequency chemical data...     

Gas chromatographic methods for monitoring of wastewater chlorophenol degradation in anaerobic reactors

Wastewater samples from an anaerobic reactor were extracted with hexane and derivatized with diazomethane (method 1) and with acetic anidride (method 2). Gas chromatography with electron-capture detection (ECD) was employed for separating the parent compound and intermediates trichlorophenols (TCP) and dichlorophenols (DCP) which originated from the penta chlorophenol (PCP) degradation process. The relations between concentrations of PCP, TCP and DCP areas were linear in the range of concentrations of 0.2 to 8 mg/L and 0.025 mg/L to 5 mg/L for methods 1 and 2, respectively. The repeatability of the extraction methods was satisfactory, with variation coefficients lower than 11%. For method 1, at the fortification level of 0.2 mg/L, recovery of PCP, TCP, and DCP was 112%, 74% and 45%, respectively. For method 2, the corresponding recovery values at the fortification level of 0.1 mg/L were 91%, 93% and 103%, respectively. Storage of the frozen samples did not alter their PCP determination properties. The chromatographic methods adapted for chlorophenol determination in wastewater were suitable with relatively simple manipulation techniques. The obtained results were reproducible and allowed identification of intermediates formed during the PCP degradation process.     

A directional passive air sampler for monitoring polycyclic aromatic hydrocarbons (PAHs) in air mass

A passive air sampler was developed for collecting polycyclic aromatic hydrocarbons (PAHs) in air mass from various directions. The airflow velocity within the sampler was assessed for its responses to ambient wind speed and direction. The sampler was examined for trapped particles, evaluated quantitatively for influence of airflow velocity and temperature on PAH uptake, examined for PAH uptake kinetics, calibrated against active sampling, and finally tested in the field. The airflow volume passing the sampler was linearly proportional to ambient wind speed and sensitive to wind direction. The uptake rate for an individual PAH was a function of airflow velocity, temperature and the octanol-air partitioning coefficient of the PAH. For all PAHs with more than two rings, the passive sampler operated in a linear uptake phase for three weeks. Different PAH concentrations were obtained in air masses from different directions in the field test.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Reduction of SO2 emissions by ammonia gas during unstaged combustion

The reduction of SO₂ by the addition of ammonia gas has been studied in a 2 m high fluidized bed combustor having a 30 cm static bed height and a freeboard height of 170 cm. Ammonia gas was injected at 52 cm above the distributor where the temperature is ca. 700° C by an uncooled stainless steel tube injector. Experiments were carried out to investigate the effects of amminia gas injection on sulphur dioxide emissions at unstaged conditions of: (i) excess air level, (ii) NH₃:SO₂ molar ratio, (iii) fluidizing velocity and (iv) bed height.A maximum reduction of 75% in SO₂ emissions was found at 40% excess air, at an NH₃:SO₂ molar ratio of 5.4. The onset of SO₂ reduction occurred at an NH₃:SO₂ ratio of 1.5 However, the most effective ratio was found to be between 3 and 5. Fluidizing velocity and bed height were also found to have significant influence on SO₂ reduction.It is difficult to determine how the SO₂ reduction varied with operating conditions. When ammonia is added in the main combustor zone, the temperature is much higher than that required for the occurrence of sulphur dioxide-ammonia and sulphur trioxide-ammonia reactions. However, this paper points out the significance of ammonia addition in the reduction of sulphur dioxide.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Chemical monitoring and evaluation of the water quality of the Douro River at the Crestuma-Lever dam

Water taken from the Crestuma-Lever dam on the Douro River was evaluated considering the Portuguese Decree-law no. 236/98 of 1st August, 1998. This paper presents the metrological characteristics, validation of analytical methodologies and the data obtained from seasonal samplings. The test parameters selected are: temperature, pH, chloride, conductivity, carbon dioxide, alkalinity, hardness, oxidability, dissolved oxygen, BOD5, total suspended solids, sulfide, phosphate, silica, ammonium, nitrite, nitrate, sulfate, sodium, potassium, calcium, magnesium, iron, manganese, copper and zinc. From data analysis we can conclude that the water presented the following characteristics: a pH situated in the neutral zone; a median mineralization; a medium hardness; well oxygenated water; and a carbonate hardness exclusively due to bicarbonates. The temperature, pH, dissolved oxygen, ammonia, chlorides, sulfates, copper, zinc and BOD5 were compared with the legal limits presented in annexes XXI and I of Decree-law 236/98. The results relating to total hardness, nitrites, calcium, magnesium, sodium, potassium, aluminium, sulfides and oxidability were compared with the legal values in annex VI as there are no limits relating to these parameters in annexes XXI and I.     

Soil properties and crop productivity as influenced by flyash incorporation in soil

Field experiments were carried out during 1996–97at Gulawathi, Muthiani and Salarpur Villages, IARI Farm, NewDelhi and NCPP Campus, Dadri to evaluate changes in soilcharacteristics and growth of wheat (Triticum aestivum L.),mustard (Brassica juncea L.), lentil (Lence esculentaMoench.), rice (Oryza sativa L.) and maize (Zea mays L.) byvarying amounts of flyash addition (up to 50t ha^-1) in soils atsowing/transplanting time of crops. Flyash addition in areasadjoining NCPP Thermal Power Plant, Dadri, Ghaziabad, U.P.ranged from 5–12 t ha^-1 yr^-1 in 1995–96. Shoot and root growthand yield of test crops at different locations after flyashincorporation resulted in beneficial effects of flyashaddition in most cases. The silt dominant texture of flyashimproved loamy sand to sandy loam textures of the surfacesoils at the farmers' fields. The increased growth in yield ofcrops with flyash incorporation was possibly due tomodifications in soil moisture retention and transmissioncharacteristics, bulk density, physico-chemical characterssuch as pH and EC and organic carbon content. The response offlyash addition in the soil on soil health and cropproductivity needs to be evaluated on long-term sustainableaspects.     

Flue gas treatability studies: a tool for techno-economic control of industrial air pollution

Air pollution problems in developing countries have gained larger fraction in the last decade especially due to non functioning and non implementation of effective air pollutioncontrol devices in industries. In industrial wastewater management, adequate treatability studies are conducted to arrive at a techno-economic treatment option. However no suchstudies were done for reducing air pollution or emission fromindustries until now in India. Little information was availableabout such studies in other countries. This article provides information about a novel technique known asflue gas treatability studies and to undertake such studies, a pilot scale system is installed in Air Pollution Control Divisionof M/s National Environmental Engineering research Institute, NEERI, Nagpur-20, India. This study is a tool for techno-economicselection of air pollution control systems specially for small/medium scale industrial emissions.