Study of meteorological aspects and urban concentration of SO2 in atmospheric environment of La Plata, Argentina

This article presents and discusses SO(2) (ppbv) concentration measurements combined with meteorological data (mainly wind speed and direction) for a five-year campaign (1996 to 2000), in a site near an oil refinery plant close to the city of La Plata and surroundings (aprox. 740.000 inh.), considered one of the six most affected cities by air pollution in the country. Since there is no monitoring network in the area, the obtained results should be considered as medium term accumulated data that enables to determine trends by analyzing together gas concentrations and meteorological parameters. Preliminary characterization of the behaviour of the predominant winds of the region in relation with potential atmospheric gas pollutants from seasonal wind roses is possible to carry out from the data. These results are complemented with monthly averaged SO(2) measurements. In particular, for year 2000, pollutant roses were determined which enable predictions about contamination emission sources. As a general result we can state that there is a clear increase in annual SO(2) concentration and that the selected site should be considered as a key site for future survey monitoring network deployment. Annual SO(2) average concentration and prevailing seasonal winds determined in this work, together with the potential health impact of SO(2) reveals the need for a comprehensive and systematic study involving particulate matter an other basic pollutant gases.     

Study of Meteorological Aspects and Urban Concentration of SO2 in Atmospheric Environment of La Plata, Argentina

This article presents and discusses SO₂ (ppbv) concentration measurements combined with meteorological data (mainly wind speed and direction) for a five-year campaign (1996 to 2000), in a site near an oil refinery plant close to the city of La Plata and surroundings (aprox. 740.000 inh.), considered one of the six most affected cities by air pollution in the country. Since there is no monitoring network in the area, the obtained results should be considered as medium term accumulated data that enables to determine trends by analyzing together gas concentrations and meteorological parameters. Preliminary characterization of the behaviour of the predominant winds of the region in relation with potential atmospheric gas pollutants from seasonal wind roses is possible to carry out from the data. These results are complemented with monthly averaged SO₂ measurements. In particular, for year 2000, pollutant roses were determined which enable predictions about contamination emission sources. As a general result we can state that there is a clear increase in annual SO₂ concentration and that the selected site should be considered as a key site for future survey monitoring network deployment. Annual SO₂ average concentration and prevailing seasonal winds determined in this work, together with the potential health impact of SO₂ reveals the need for a comprehensive and systematic study involving particulate matter an other basic pollutant gases.     

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.     

Parameter uncertainty and sensitivity in a liquid-effluent dose model

Radioactive materials which are released into streams on the Savannah River Site (SRS) eventually flow into the Savannah River. Tritium, ⁹⁰Sr, ¹³⁷Cs, and ²³⁹Pu account for the majority of the radiation dose received by users of the Savannah River. This paper focuses on the dose uncertainties originating from variability in parameters describing the transport and uptake of these nuclides. Parameter sensitivity has also been determined for each liquid pathway exposure model. The models used here to estimate radiation dose to an exposed individual provide a range of possible dose estimates that span approximately one order of magnitude. A pathway analysis reveals that aquatic food and water consumption account for more than 95% of the total dose to an individual.     

Precipitable water modelling using artificial neural network in Çukurova region

Precipitable water (PW) is an important atmospheric variable for climate system calculation. Local monthly mean PW values were measured by daily radiosonde observations for the time period from 1990 to 2006. Artificial neural network (ANN) method was applied for modeling and prediction of mean precipitable water data in Çukurova region, south of Turkey. We applied Levenberg–Marquardt (LM) learning algorithm and logistic sigmoid transfer function in the network. In order to train our neural network we used data of Adana station, which are assumed to give a general idea about the precipitable water of Çukurova region. Thus, meteorological and geographical data (altitude, temperature, pressure, and humidity) were used in the input layer of the network for Çukurova region. Precipitable water was the output. Correlation coefficient (R²) between the predicted and measured values for monthly mean daily sum with LM method values was found to be 94.00% (training), 91.84% (testing), respectively. The findings revealed that the ANN-based prediction technique for estimating PW values is as effective as meteorological radiosonde observations. In addition, the results suggest that ANN method values be used so as to predict the precipitable water.     

226Ra in Tap and Mineral Water and Related Health Risk in the Republic of Croatia

The presence of 226Ra in drinking water may sometimes make important contribution to natural background radiation exposures. The paper describes the study of 226Ra content in drinking water of Croatia: tap water from the public supply system of several major towns and bottled mineral water from two selected mineral water springs. 226Ra was determined by alpha-spectrometric measurement after radiochemical separation. The radiation doses originating from drinking tap water and bottled mineral water were estimated. The annual dose from consumption of bottled mineral water was compared to that received from ingestion of public system tap water. The study showed that 226Ra content for investigated categories of waters is below the levels at which any unacceptable dose due to ingestion would arise.     

Sampling Considerations for Establishment of Baseline Loadings from Forested Watersheds for TMDL Application

Five methods for estimating maximum daily and annual nitrate (NO3) and suspended sediment loads using periodic sampling of varying intensities were compared to actual loads calculated from intensive stormflow and baseflow sampling from small, forested watersheds in north central West Virginia to determine if the less intensive sampling methods were accurate and could be utilized in TMDL development. There were no significant differences between the annual NO3 load estimates using non-intensive sampling methods and the actual NO3 loads. However, maximum daily NO3 loads were estimated less accurately than annual loads. The ability to estimate baseline NO3 loads fairly accurately with non-intensive concentration data is attributed to the small fluctuation in NO3 concentrations over flow and time, particularly during storms. By contrast, suspended sediment exports determined by any of the non-intensive methods varied significantly and widely from and compared poorly to the actual exports for both daily and annual methods. Weekly sampling better approximated actual annual exports, but there were no significant statistical differences among weekly, monthly, and quarterly estimates. Suspended sediment concentrations varied widely within and among storm events, so that accurate estimates of total annual or maximum daily loads could not be obtained from infrequent sampling.     

Influence of aerosol spectrum and air pollutants on fog formation in urban environment of megacity Delhi, India

Urban areas are facing increasing fog frequencies that may result due to increased air pollution emanating from variety of sources. The increased pollution levels may lead to the atmospheric reactions resulting into the formation of secondary pollutants that may also lead to increased aerosol number concentrations (ANC) in the atmosphere. This could cause enhanced water aerosols in the presence of favourable meteorological conditions and high relative humidity. This study deals with the atmospheric pollution and visibility during winter season of megacity Delhi in order to assess the relationship between the two specifically during fog episodes. Thus, this study analyses the levels of air pollutants, aerosol spectrum and meteorological conditions during one week each in the winter season of the years 2004 and 2006 in order to have an improved understanding of their role in fog formation in mega-city Delhi. More than 300 h of measurements which included episodes of dense, thick and moderate fogs of about 25 h, were studied. The measurements cover most of the accumulation mode and greater size spectrum of aerosols. Thus, the analysis is performed for the entire period, specifically, before the fog sets up, during and afterwards. In general, the relatively small variations in number concentration show larger variations in visibility prior and post dense fog formation than during dense fog episodes. Preliminary analysis of monthly averaged RSPM (Respirable Suspended particulate Matter or PM(10)) concentration values for four winter months for a period of 6 years (1996-2001) and visibility did not show a good correlation with total occurrences of fog. However, daily averaged RSPM concentration showed a good correlation with the occurrences of thick fog. Diurnal variation of Sulfur-dioxide and Nitrogen dioxide were found to have inverse relationship with visibility during fog which may be due to formation of secondary pollutants such as sulfate and to a lesser extent nitrates. Amongst, the daily averaged concentrations of all the criteria pollutants, RSPM was found to be best correlated with the fog in comparison to other pollutants.     

拉萨市环境空气质量与气象特征分析

分析了拉萨市环境空气质量及其拉萨市的地理位置、地形地貌和气候特征的关系。研究结果表明 ,自然沙尘是拉萨市环境空气质量的主要自然源。月降尘量与降水、大风等有明显的相关关系。加快拉萨地区生态环境建设 ,增加植被覆盖率 ,减少沙源是改善拉萨市环境空气质量的关键     

210-Polonium studies in some environmental and biological matrices of Domiasiat uranium deposit area, West Khasi Hills, Meghalaya, India

The study was performed using a silicon surface barrier alpha spectrometer at Bhabha Atomic Research Centre, Mumbai, India. Through the study, the observed ²¹⁰Po activity in water sample from different locations in the Domiasiat area ranges from 0.04 to 0.69 Bq/l. The daily and annual intake of ²¹⁰Po through water was also estimated and the mean value of 0.72 and 263.61 Bq, respectively, were observed. It is observed that the effective doses through water were higher than the World Health Organization recommended dose of 0.05 mSv/year. The total annual effective doses through terrestrial ingestion for all the locations was studied and the mean annual effective dose was observed to be 0.315 mSv, which, when compared to the worldwide and the Indian values, was observed to be slightly higher. The mean activity in soil is found to be 124.8 ±5.7 Bq/kg and in meat the activity is 0.43 ±0.05 Bq/kg. In fishes, an activity of 0.48 ±0.07 Bq/kg in Garra lamta, 0.29 ±0.02 Bq/kg in Neolissocheilus hexaganolepis, and 3.3 ±0.1 Bq/kg in Macrobrachium sp. is observed. Activity concentration in plant samples was analyzed and the activity ranges from 0.020 ±0.002 to 9.69 ±0.35 Bq/kg. Committed effective dose by the adult population of the Domiasiat area through intake of ²¹⁰Po through these food items was also determined and compared with the Indian average value and the worldwide average value.     

乌鲁木齐市煤改气工程对采暖期 SO2和 NO2浓度变化的影响分析

通过对乌鲁木齐市2011-2013年采暖期SO2、NO2、PM10的年均浓度、月均浓度、日均浓度的变化比较，分析了乌鲁木齐市煤改气工程实施前后大气环境发生的变化趋势，论证了乌鲁木齐市煤改气工程对城市大气环境的改善作用，为该工程今后的推广与发展得到了可靠的实践依据。     

上海市郊春季PM10 污染的观测研究

利用上海市郊金山环境监测站2007年春季的逐时PM10和气象参数的观测数据,分析了PM10日平均质量浓度和最大质量浓度的时间变化规律,小时平均质量浓度的分布规律,气象条件对PM10质量浓度的影响,并利用HYSPLIT轨迹模型结合气象观测数据对一次最严重的PM10污染过程进行了分析.结果表明,PM10在春季有11日出现超标,污染比较严重;风和降雨对PM10质量浓度均有较为明显的影响;4月2日监测点PM10日平均和最高质量浓度分别达到0.78 mg/m3和1.0 mg/m3,均为全年最高值,这与北方冷空气携带沙尘南下的影响有关.     

成都市大气能见度变化特征及影响因子研究

利用MICAPS 2008—2011年地面观测资料,分析了成都市区大气能见度的变化特征。以2009年成都地区一次低能见度天气过程为例,分析大气能见度与各气象要素的变化关系,讨论影响成都市大气能见度变化的主要因素。结果表明:近年来伴随着霾天数的逐年下降,成都市区年平均大气能见度呈上升趋势,夏季平均值最高,春季次之,冬季最低。高湿和低风速是造成成都市低能见度现象的主要气象条件。PM2.5的浓度与成都市大气能见度呈显著负相关,PM2.5浓度的快速增长是造成大气能见度急剧降低的重要原因。有效降低PM2.5浓度,减少大气污染物排放,是改善成都市区大气能见度的有效途径。     

“十一五”期间新疆大气降尘量时空分布特征及影响因素分析

通过对"十一五"期间新疆134个大气降尘监测点位数据进行统计分析发现,"十一五"期间,全疆年均降尘量维持在22.2~24.6 t/km2.月,变化幅度小于10%。一年内降尘主要集中在3~6月份,占全年降尘量的51%。在空间分布上,新疆年均降尘量呈现明显的南疆高于北疆的特征,南疆五地、州的总降尘量占全疆总降尘量的70.2%,为新疆降尘的主要集中区。特殊的气象、生态环境是决定新疆大气降尘时空分布特征的主要因素。     

考虑水温变化的变降解系数在北京市北运河水质模拟中的应用

综合降解系数是水质模拟预测、水环境容量计算中的关键参数之一,并且受温度影响较大。首先基于北京市北运河代表站2010年逐日水温资料,根据描述氨氮降解系数与温度之间数量关系的经验公式,得到随水温变化的动态降解系数以及年均水温对应的恒定降解系数,并采用模型试错法进行修正。然后基于MIKE11模型,模拟了采用变降解系数和恒定降解系数2种情景下北运河榆林庄断面氨氮浓度的变化。结果表明:2种情景均能较好地模拟氨氮浓度的年变化趋势,但采用变降解系数下大多月份模拟得到的月均质量浓度相对实测值误差较小,尤其是4—12月各月平均质量浓度模拟误差控制在15%以内,全年日均质量浓度模拟误差不足4%,模型表现更为稳定。     

Quantifying urban heat island intensity in Hong Kong SAR, China

This paper addresses the methodological concerns in quantifying urban heat island (UHI) intensity in Hong Kong SAR, China. Although the urban heat island in Hong Kong has been widely investigated, there is no consensus on the most appropriate fixed point meteorological sites to be used to calculate heat island intensity. This study utilized the Local Climate Zones landscape classification system to classify 17 weather stations from the Hong Kong Observatory’s extensive fixed point meteorological observation network. According to the classification results, the meteorological site located at the Hong Kong Observatory Headquarters is the representative urban weather station in Hong Kong, whereas sites located at Tsak Yue Wu and Ta Kwu Ling are appropriate rural or nonurbanized counterparts. These choices were validated and supported quantitatively through comparison of long-term annual and diurnal UHI intensities with rural stations used in previous studies. Results indicate that the rural stations used in previous studies are not representative, and thus, the past UHI intensities calculated for Hong Kong may have been underestimated.     

Correlation between SO2 and NO2 measured in an atmospheric column by a Brewer spectrophotometer and at ground-level by photochemical techniques

An investigation to determine the correlation of atmospheric amounts of SO₂ and NO₂ between columnar measurements from the ground and ground point determinations has been performed. The experimental data have been obtained from a Brewer spectrophotometer for columnar measurements and standard analytical techniques for ground measurements.The results show that the Brewer can give a correct indication of the trend of these pollutants on a monthly averaged basis. The possibility of deducing the mixing layer depth from the measured data has also been investigated but the results obtained are not conclusive due to the lack of an accurate experimental verification.     

降尘规律研究--兰州城区降尘变化规律及多元自身回归预测

探讨了降尘的年变化、月变化.运用逐步回归筛选变量.采用主分量分析法,得出不同季节的主分量,揭示了降尘的规律,建立了多元自身回归预测方程.对城区降尘进了预测,并与实测作了验证和对比,取得较好效果.     

Mathematical models for accurate prediction of atmospheric visibility with particular reference to the seasonal and environmental patterns in Hong Kong

Atmospheric visibility impairment has gained increasing concern as it is associated with the existence of a number of aerosols as well as common air pollutants and produces unfavorable conditions for observation, dispersion, and transportation. This study analyzed the atmospheric visibility data measured in urban and suburban Hong Kong (two selected stations) with respect to time-matched mass concentrations of common air pollutants including nitrogen dioxide (NO(2)), nitrogen monoxide (NO), respirable suspended particulates (PM(10)), sulfur dioxide (SO(2)), carbon monoxide (CO), and meteorological parameters including air temperature, relative humidity, and wind speed. No significant difference in atmospheric visibility was reported between the two measurement locations (p > or = 0.6, t test); and good atmospheric visibility was observed more frequently in summer and autumn than in winter and spring (p < 0.01, t test). It was also found that atmospheric visibility increased with temperature but decreased with the concentrations of SO(2), CO, PM(10), NO, and NO(2). The results showed that atmospheric visibility was season dependent and would have significant correlations with temperature, the mass concentrations of PM(10) and NO(2), and the air pollution index API (correlation coefficients mid R: R mid R: > or = 0.7, p < or = 0.0001, t test). Mathematical expressions catering to the seasonal variations of atmospheric visibility were thus proposed. By comparison, the proposed visibility prediction models were more accurate than some existing regional models. In addition to improving visibility prediction accuracy, this study would be useful for understanding the context of low atmospheric visibility, exploring possible remedial measures, and evaluating the impact of air pollution and atmospheric visibility impairment in this region.     

Application of artificial neural network approach and remotely sensed imagery for regional eco-environmental quality evaluation

Eco-environment quality evaluation is an important research theme in environment management. In the present study, Fuzhou city in China was selected as a study area and a limited number of 222 sampling field sites were first investigated in situ with the help of a GPS device. Every sampling site was assessed by ecological experts and given an Eco-environment Background Value (EBV) based on a scoring and ranking system. The higher the EBV, the better the ecological environmental quality. Then, three types of eco-environmental attributes that are physically-based and easily-quantifiable at a grid level were extracted: (1) remote sensing derived attributes (vegetation index, wetness index, soil brightness index, surface land temperature index), (2) meteorological attributes (annual temperature and annual precipitation), and (3) terrain attribute (elevation). A Back Propagation (BP) Artificial Neural Network (ANN) model was proposed for the EBV validation and prediction. A three-layer BP ANN model was designed to automatically learn the internal relationship using a training set of known EBV and eco-environmental attributes, followed by the application of the model for predicting EBV values across the whole study area. It was found that the performance of the BP ANN model was satisfactory and capable of an overall prediction accuracy of 82.4%, with a Kappa coefficient of 0.801 in the validation. The evaluation results showed that the eco-environmental quality of Fuzhou city is considered as satisfactory. Through analyzing the spatial correlation between the eco-environmental quality and land uses, it was found that the best eco-environmental areas were related to forest lands, whereas the urban area had the relatively worst eco-environmental quality. Human activities are still considered as a major impact on the eco-environmental quality in this area.