Heavy metals in the liver and muscle of <Emphasis Type="Italic">Micropogonias manni</Emphasis> fish from Budi Lake,Araucania Region,Chile: potential risk for humans

The concentrations of cadmium, lead, manganese and zinc were determined in the fish species Micropogonias manni captured in Budi Lake, Araucanía Region (Chile). The measurements were made by atomic absorption spectroscopy, and the analysis considered the sex, weight and size of the species; the representative samples were taken from the liver and muscle tissue. The method was validated using certified reference material (DOLT-1). The ranges of concentrations found in the muscle tissue were: Cd, not determinate (n.d.)–0.26; Pb, n.d.–1.88; Mn, 0.02–12.17 and Zn, 0.48–39.04 mg kg⁻¹ (dry weight). The concentrations in muscle tissue were generally lower than those found in the liver. With respect to the average concentrations recorded for each metal in the edible part of the fish (muscle tissue), it was found that the levels of Cd, Pb, Mn and Zn are within the ranges published by other authors in similar works and below the maximum concentration limits permitted by current legislation (FAO/WHO 2004; EU 2001) and do not constitute a health hazard for consumers of this species. The results were subjected to statistical analysis to evaluate the correlations between the content of the various metals and the sex, weight and size of each sample.     

Measurement of particulate phase polycyclic aromatic hydrocarbon (PAHs) around a petroleum refinery

A study on concentrations of ambient particulates viz. total suspended particulate matters (TSP), respirable suspended particulate matter (RSPM) and polycyclic aromatic hydrocarbons (PAH) were carried out at six sites around the Asia’s largest, 12 MMTPA, petroleum refinery in west coast of India. PAH concentrations are correlated with each other in these sites, suggesting that they have related sources and sinks. The present article discusses the monitoring aspects such as sample collection, pretreatment and analytical methods and compares the monitored levels for assessing the source receptor distribution pattern. The main sources of RSPM and PAHs in urban air are automobile exhaust (CPCB, Polycyclic aromatic hydrocarbons (PAHs) in air and their effects on human health. “”, 2003; Manuel et al., Environmental Science and Technology, 13: 227–231, 2004) and industrial emissions like petroleum refinery (Vo-Dinh, Chemical analysis of polycyclic aromatic hydrocarbons, Wiley: New York, 1989; Wagrowaski and Hites, Environmental Science and Technology, 31: 279–282, 1997). Polycyclic aromatic hydrocarbons (PAH) are ubiquitous constituents of urban airborne particulate mostly generated by anthropogenic activities (Li et al., Environmental Science and Technology, 37:1958–2965, 2003; Thorsen et al., Environmental Science and Technology, 38: 2029–2037, 2004; Ohura et al., Environmental Science and Technology, 32: 450–455, 2004) and some of them are of major health concern mainly due to their well-known carcinogenic and mutagenic properties (Soclo et al., Marine Pollution Bulletin, 40: 387–396, 2000; Chen et al., Environment International, 28: 659–668, 2003; Larsen and Baker, Environmental Science and Technology, 32: 450–455, 2003). Limited information is available on PAHs contributions from refineries to ambient air. Hence this study would not only create a database but also provide necessary inputs towards dose-response relationship for fixing standards. Also, since it acts as precursor to green house gas, the data would be useful for climate change assessments. The objective of this article is to find out the concentration of PAHs in particulate matter around petroleum refinery and compare with their concentrations in major Indian urban centers.     

Characterization, Source Identification and Apportionment of Selected Metals in TSP in an Urban Atmosphere

To understand the metal distribution characteristics in the atmosphere of urban Islamabad, total suspended particulate (TSP) samples were collected on daily 12 h basis, at Quaid-i-Azam University campus, using high volume sampler. The TSP samples were treated with HNO₃/HClO₄ based wet digestion method for the quantification of eight selected metals; Fe, Zn, Pb, Mn, Cr, Co, Ni and Cd by FAAS method. The monitoring period ran from June 2001 to January 2002, with a total of 194 samples collected on cellulose filters. Effects of different meteorological conditions such as temperature, relative humidity, wind speed and wind direction on selected metal levels were interpreted by means of multivariate statistical approach. Enhanced metal levels for Fe (930 ng/m³), Zn (542 ng/m³) and Pb (210 ng/m³) were found on the mean scale while Mn, Cr, Co and Ni emerged as minor contributors. Statistical correlation study was also conducted and a strong correlation was observed between Pb-Cr (r=0.611). The relative humidity showed some significant influence on atmospheric metal distribution while other meteorological parameters showed weak relationship with TSP metal levels. Regarding the origin of sources of heavy metals in TSP, the statistical procedure identified three source profiles; automobile emissions, industrial/metallurgical units, and natural soil dust. The metal levels were also compared with those reported for other parts of the world which showed that the metal levels in urban atmosphere of Islamabad are in exceedence than those of European industrial and urban sites while comparable with some Asian sites.     

Investigating the impacts of some meteorological parameters on air pollution in Balikesir, Turkey

Air pollution is one of the most important environmental problems in Balikesir, situated in the western part of Turkey, during the winter periods. The unfavorable climate as well as the city’s topography, and inappropriate fuel usage cause serious air pollution problems. The air pollutant concentrations in the city have a close relationship with meteorological parameters. In the present study, the relationship between daily average total suspended particulate (TSP) and sulphur dioxide (SO₂) concentrations measured between 1999–2005 winter seasons were correlated with meteorological factors, such as wind speed, temperature, relative humidity and pressure. This statistical analysis was achieved using the stepwise multiple linear regression method. According to the results obtained through the analysis, higher TSP and SO₂ concentrations are strongly related to colder temperatures, lower wind speed, higher atmospheric pressure and higher relative humidity. The statistical models of SO₂ and TSP gave correlation coefficient values (R ²) of 0.735 and 0.656, respectively.     

Analysis of Lead Levels in Local Jordanian and Imported Sheep Meat and Organs Using Atomic Absorption Spectrometry

A total of two hundred and forty random samples were collected equally from mutton, liver and kidney of 40 local (Jordanian) and 40 imported Australian sheep (40 each sub sample). Fresh samples were collected from 12–18 m old sheep slaughtered in abattoirs in Jordan in 2002. Besides, 40 fresh mutton samples of imported Chinese sheep were collected from different markets. Atomic absorption spectrometry (AAS) was used to estimate the lead (Pb) content of the samples. Results indicated that Australian mutton had significantly higher (p < 0.05) mean of lead pollution than that of the local and Chinese muttons. The mean concentration of lead (mg/kg) in Australian, local and Chinese muttons was 4.30, 3.15 and 2.17, respectively. The mean concentration of lead in Australian sheep liver was significantly higher (p < 0.05) than that recorded in the local sheep liver. The mean concentration of Pb in Australian and local sheep liver was 5.69 and 4.52 mg/kg, respectively. The mean concentrations of Pb in the kidney of the Australian and local sheep were not significantly different (p > 0.05). They were 4.59 and 3.87 mg/kg, respectively.On the basis of the samples lead level, 85, 92 and 87.5% of local, Australian and Chinese mutton respectively, exceeded the international safe permissible limit of 1.0 mg/kg. Furthermore, the effect of Pb on animal and human health was discussed.     

Diatoms as indicators in the Environmental Monitoring and Assessment Program-Surface Waters (EMAP-SW)

As a part of the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program-Surface Waters (EMAP-SW), sedimentary diatom assemblages were studied from 66 lakes in the northeastern U.S.A. to evaluate the applicability of diatoms for this nation-wide monitoring program. Sediment cores were collected from the study lakes and diatoms were analyzed from the top (present-day) and bottom (pre-industrial) sediment samples. Canonical correspondence analysis (CCA) was used to examine which environmental variables correlate most closely with the distributions of diatom taxa in the top (surface) samples. Forward selection and Monte Carlo permutation tests showed that diatom species distributions were significantly related to total lakewater phosphorus (TP), pH, chloride, Secchi depth, and lake size and maximum depth. We developed weighted-averaging calibration and regression models for inferring TP (r ²=0.62), chloride (r ²=0.61), pH (r ²=0.86), and Secchi depth (r ²=0.62). An index of overall lake disturbance was also developed. Our diatom data indicate that marked changes have occurred in the study lakes since pre-industrial times as a result of anthropogenic activity.     

Statistical Simulation to Estimate Uncertain Behavioral Parameters of Hybrid Energy-Economy Models

In energy-economy modeling, new hybrid models attempt to combine the technological explicitness of bottom-up models with the macroeconomic feedbacks and statistically estimated behavioral parameters of top-down models. However, statistical estimation of behavioral parameters (portraying firm and household technology choices) with such models is challenged by the number of uncertain variables and the lack of historical data on technologies in terms of capital costs, operating costs, and market shares. Multiple combinations of parameter values might equally explain past technology choices. This paper reports on the application of a Bayesian statistical simulation approach for estimating the most likely values for these key behavioral parameters in order to best explain past technology choices and then simulate policies to influence future technology choices. The method included (1) data collection of key technology market shares, capital costs, and operating costs over the past; (2) backcasting a hybrid energy-economy model over a historical time period; and (3) the application of Markov chain Monte Carlo statistical simulation using the Metropolis–Hastings algorithm as a tool for estimating distributions for key parameters in the model. The results provide a means of indicating the uncertainty bounds around key behavioral parameters when generating forecasts of the effect of certain policies. However, the results also indicate that this approach may have limited applicability, given that future available technologies may differ substantially from past technologies and that it is difficult to separate the effects of parameter uncertainty from model structure uncertainty.     

Extreme Nitrogen Oxide and Ozone Concentrations in Athens Atmosphere in Relation to Meteorological Conditions

In the present study, we investigate the variation of NO _x (NO + NO₂) and O₃ concentrations and the relation between the extreme events (episodes) of NO _x and O₃ concentrations and the relevant meteorological conditions in the urban atmosphere of the Athens basin. Hourly data of NO, NO₂ and O₃ concentrations from 10 representative monitoring sites located in the Athens basin were used, covering the 10-year time period from 1994 to 2003. The results of our analysis show that the concentrations of air pollutants differ significantly from one monitoring site to another, due to the location and proximity of each station to the emission sources. For each site, there are also significant differences in NO _x and O₃ concentrations from day to day, as well as from month to month and/or from season to season. The annual and seasonal variations show higher NO values in winter and lower in summer. On the contrary, NO₂ and O₃ values are higher in summer (photochemical production of O₃) and lower in winter. These differences are attributed, to a large extent, to the prevailing synoptic and meteorological conditions, the most important between them being the wind direction and speed as well as the atmospheric pressure. Our analysis of the identified 179 extreme NO _x air pollution events shows that most of them took place under anticyclonic conditions, associated with calm or weak winds (speed <2.5 ms⁻¹) of mostly southern to southwestern directions, as well as with low air temperatures and intense stable surface atmospheric conditions. There exists a significant decreasing tendency in NO _x air pollution episodic events over the 10-year study period, resulting in very few to none events in the period from 2000 to 2003. As far as it concerns the extreme O₃ concentrations, 34 air pollution events were identified, occurring under high air temperatures, variable weak winds and intense solar irradiation. The trends of O₃ concentrations are stronger in suburban sites than in urban ones.     

Tropical storm off Myanmar coast sweeps reefs in Ritchie’s Archipelago, Andaman

The reefs in some islands of Andaman and Nicobar suffered severe damage following a tropical storm in the Bay of Bengal off Myanmar coast during 13–17 March 2011. Surveys were conducted at eight sites in Andaman, of which five were located in the Ritchie’s Archipelago where maximum wind speeds of 11 m?s^-1 was observed; and three around Port Blair which lay on the leeward side of the storm and had not experienced wind speeds of more than 9 m?s^-1. Corals in the shallow inshore reefs were broken and dislodged by the thrust of the waves. Significant damage in the deeper regions and offshore reefs were caused by the settlement of debris and sand brought down from the shallower regions. The fragile branching corals (Acropora sp.) were reduced to rubbles and the larger boulder corals (Porites sp.) were toppled over or scarred by falling debris. The reefs on the windward side and directly in the path of the storm winds were the worst affected. The investigation exposes the vulnerability of the reefs in Andaman to the oceanographic features which generally remain unnoticed unless the damage is caused to the coastal habitats.     

The return periods and risk assessment of severe dust storms in Inner Mongolia with consideration of the main contributing factors

This study presents a methodology for return period analysis and risk assessment of severe dust storm disaster. Meteorological observation data, soil moisture data, and remote sensing data from 30 meteorological stations in Inner Mongolia (western China) from 1985 to 2006 were used for the study. A composite index of severe dust storm disaster (Index I (SDS)) based on the influence mechanisms of the main contributing factors was developed by using the analytic hierarchy process and the weighted comprehensive method, and the hazard risk curves (i.e., the transcendental probability curves of I (SDS)) for the 30 stations were established using the parameter estimation method. We then analyzed the risk of the occurrence of severe dust storm under different scenarios of 5-, 10-, 20-, and 50-year return periods. The results show that the risk decreased from west to east across Inner Mongolia, and there are four severe dust storm occurrence peak value centers, including Guaizihu, Jilantai, Hailisu, and Zhurihe-Erenhot. The severity of dust storms in seven places will be intolerable in the 50-year return period scenario and in three places in the 20-year return period scenario. These results indicate that these locations should concentrate forces on disaster prevention, monitoring, and early warning. The I (SDS) was developed as an easily understandable tool useful for the assessment and comparison of the relative risk of severe dust storm disasters in different areas. The risk assessment was specifically intended to support local and national government agencies in their management of severe dust storm disasters in their efforts to (1) make resource allocation decisions, (2) make high-level planning decisions, and (3) raise public awareness of severe dust storm risk.     

Stationary and Non-stationary Extreme Value Approaches for Modelling Extreme Temperature: the Case of Riyadh City,Saudi Arabia

Climate change is one of the most fiercely debated scientific issues in recent decades, and the changes in climate extremes are estimated to have greater negative impacts on human society and the natural environment than the changes in mean climate. Extreme value theory is a well-known tool that attempts to best estimate the probability of adversarial risk events. In this paper, the focus is on the statistical behaviour of extreme maximum values of temperature. Under the framework of this theory, the methods of block maxima and threshold exceedances are employed. Due to the non-stationary characteristic of the series of temperature values, the generalized extreme value distribution and the generalized Pareto distribution were extended to the non-stationary processes by including covariates in the parameters of the models. For the purpose of obtaining an approximately independent threshold excesses, a declustering method was performed and then the de-clustered peaks were fitted to the generalized Pareto distribution. The stationary Gumbel distribution was found a reasonable model for the annual block maxima; however, a non-stationary generalized extreme value distribution with quadratic trend in the location was recommended for the half-yearly period. The findings also show that there is an improvement in modelling daily maxima temperature when it is applied to the declustered series and the given model outperforms the non-stationary generalized Pareto distribution models. Furthermore, the retained generalized Pareto distribution model proved better than the generalized extreme value distribution. Estimates of the return levels obtained from both extreme value models show that new records on maximum temperature event could appear within the next 20, 50 and 100 years.     

Prediction of extreme ozone levels in Barcelona, Spain

Barcelona is one of the most polluted cities in Western Europe, although our levels of air pollution are within the World Health Organisation air quality guidelines. However, high concentrations of air pollution have not been studied yet. Ground ozone levels is a topic of considerable environmental concern, since excessive level of ozone are taken as indicative of high pollution. In terms of the air quality guidelines ozone levels higher than 100 µg m^–3 can start to be health-hazards for human health. Our objective is to report a detailed analysis of ozone data exceeding the thresholds established by the air quality guidelines. Data analysed were collected in two measurement stations in Barcelona, for the reference period 1991–1996. Applying statistical techniques commonly used in the analysis of extreme values, mainly the Peak Over Threshold method was used for in this study. The analysis reveal that the ozone threshold values for the protection of human health has exceeded many times in both stations. The estimated return values for 3, 10, and 40 yr exceed the threshold value for information to the public of almost once in both stations, also it seems to be unlikely that the threshold value for warning to the public will be exceeded in 40 yr.     

黑龙江省环境空气污染物和气象要素的典型相关分析

通过对黑龙江省4个自然年(2016年1月1日—2019年12月31日)环境空气污染物和气象要素的分析,揭示了黑龙江省气象条件对空气污染物浓度的影响规律与特征.对PM2.5、PM10、SO2、NO2、CO和O3等6项污染物的描述性统计和简单的相关分析显示:黑龙江省环境空气质量呈现逐年变好的趋势,非采暖期环境空气质量好于采...     

An Application of the Pump-to-Fill Policy for Management of Urban Stormwater

We consider the management of urban stormwater in two connected dams. Stormwater generated by local rainfall flows into a capture dam and is subsequently pumped into a similar sized holding dam. We assume random gross inflow and constant demand. If we wish to minimise overflow from the system then the optimal management policy is to pump as much water as possible each day from the capture dam to the holding dam without allowing the holding dam to overflow. We shall refer to this policy as the pump-to-fill policy. The model is based on the Parafield stormwater management system in the City of Salisbury (CoS) but assumes constant demand instead of level dependent outflow. If there is insufficient water in the holding dam to meet the desired daily demand then all water in the holding dam is used and the shortfall is obtained from other sources. CoS, in suburban Adelaide in South Australia, is recognised in local government circles as a world leader in urban stormwater management. The water is supplied to local industry to replace regular mains water and is also used to restore and maintain urban wetlands. In mathematical terms the pump-to-fill policy defines a Markov chain with a large transition matrix and a characteristic regular block structure. We use specialised Matrix Analytic Methods to decompose the event space and find simplified equations for the steady state probability vector. In this way we enable an elementary solution procedure which we illustrate by solving the modified Parafield problem. The optimal nature of the pump-to-fill policy is established in a recent paper by Pearce et al. (JIMO 3(2):313–320, 2007). The purpose of the current study is to find optimal management policies for urban stormwater systems. Work supported by the Australian Research Council.     

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.     

Mann–Kendall trend of pollutants,temperature and humidity over an urban station of India with forecast verification using different ARIMA models

The purpose of the present research is to identify the trends in the concentrations of few atmospheric pollutants and meteorological parameters over an urban station Kolkata (22° 32′ N; 88° 20′ E), India, during the period from 2002 to 2011 and subsequently develop models for precise forecast of the concentration of the pollutants and the meteorological parameters over the station Kolkata. The pollutants considered in this study are sulphur dioxide (SO₂), nitrogen dioxide (NO₂), particulates of size 10-μm diameters (PM₁₀), carbon monoxide (CO) and tropospheric ozone (O3). The meteorological parameters considered are the surface temperature and relative humidity. The Mann–Kendall, non-parametric statistical analysis is implemented to observe the trends in the data series of the selected parameters. A time series approach with autoregressive integrated moving average (ARIMA) modelling is used to provide daily forecast of the parameters with precision. ARIMA models of different categories; ARIMA (1, 1, 1), ARIMA (0, 2, 2) and ARIMA (2, 1, 2) are considered and the skill of each model is estimated and compared in forecasting the concentration of the atmospheric pollutants and meteorological parameters. The results of the study reveal that the ARIMA (0, 2, 2) is the best statistical model for forecasting the daily concentration of pollutants as well as the meteorological parameters over Kolkata. The result is validated with the observation of 2012.     

Monitoring seasonal bat activity on a coastal barrier island in Maryland, USA

Research on effects of wind turbines on bats has increased dramatically in recent years because of significant numbers of bats killed by rotating wind turbine blades. Whereas most research has focused on the Midwest and inland portions of eastern North America, bat activity and migration on the Atlantic Coast has largely been unexamined. We used three long-term acoustic monitoring stations to determine seasonal bat activity patterns on the Assateague Island National Seashore, a barrier island off the coast of Maryland, from 2005 to 2006. We recorded five species, including eastern red bats (Lasiurus borealis), big brown bats (Eptesicus fuscus), hoary bats (Lasiurus cinereus), tri-colored bats (Perimyotis subflavus), and silver-haired bats (Lasionycteris noctivagans). Seasonal bat activity (number of bat passes recorded) followed a cosine function and gradually increased beginning in April, peaked in August, and declined gradually until cessation in December. Based on autoregressive models, inter-night bat activity was autocorrelated for lags of seven nights or fewer but varied among acoustic monitoring stations. Higher nightly temperatures and lower wind speeds positively affected bat activity. When autoregressive model predictions were fitted to the observed nightly bat pass totals, model residuals >2 standard deviations from the mean existed only during migration periods, indicating that periodic increases in bat activity could not be accounted for by seasonal trends and weather variables alone. Rather, the additional bat passes were attributable to migrating bats. We conclude that bats, specifically eastern red, hoary, and silver-haired bats, use this barrier island during migration and that this phenomenon may have implications for the development of near and offshore wind energy.     

Combining Stochastic Optimization and Monte Carlo Simulation to Deal with Uncertainties in Climate Policy Assessment

In this paper, we explore the impact of several sources of uncertainties on the assessment of energy and climate policies when one uses in a harmonized way stochastic programming in a large-scale bottom-up (BU) model and Monte Carlo simulation in a large-scale top-down (TD) model. The BU model we use is the TIMES Integrated Assessment Model, which is run in a stochastic programming version to provide a hedging emission policy to cope with the uncertainty characterizing climate sensitivity. The TD model we use is the computable general equilibrium model GEMINI-E3. Through Monte Carlo simulations of randomly generated uncertain parameter values, one provides a stochastic micro- and macro-economic analysis. Through statistical analysis of the simulation results, we analyse the impact of the uncertainties on the policy assessment.     

Estimating the Microbial Risk of E. coli in Reclaimed Wastewater Irrigation on Paddy Field

Microbial risk was quantified to assess human health risk as a result of exposure to E. coli in reclaimed wastewater irrigation. Monitoring data on E. coli were collected from pond water in paddy rice plots during the growing season. Five treatments were used and each was triplicated to evaluate the changes in E. coli concentrations in experiments performed in 2003 and 2004. The Beta-Poisson model was used to estimate the microbial risk of pathogen ingestion among farmers and neighboring children. A Monte Carlo simulation (10,000 trials) was conducted to estimate the risk associated with uncertainty. In this study, risk values ranged from 10⁻⁴ to 10⁻⁸. UV-disinfected irrigation water showed a lower risk value than others, and its level was within the range of the actual paddy rice field with surface water. Agricultural activity was thought to be safer after 1–2 days, when the paddy field was irrigated with reclaimed wastewater. Also, children were found to have a greater risk of infection with E. coli. This paper should be viewed as a first step in the application of quantitative microbial risk assessment of wastewater reuse in paddy rice culture.     

Spatiotemporal Modeling of Ambient Sulfur Dioxide Concentrations in Rural Western Canada

The provinces of Saskatchewan, Alberta, and British Columbia are major oil- and gas-producing regions in western Canada. With increasing oil and gas production activities, there has been a growing concern of the effect of oil and gas industry emissions on health. Nevertheless, lack of proper tools to estimate the exposure to these emissions has been a hindrance to epidemiological studies and risk assessment. This paper presents a spatiotemporal modeling approach to estimating ambient sulfur dioxide (SO₂) levels based on environmental monitoring data (N = 10,295), which were collected at rural sites (591 per month on average) of this region from June 1, 2001 to May 31, 2002. Based on the model, illustrative maps consistently revealed high and low SO₂ concentration sub-regions. The sub-regions with elevated SO₂ concentrations had increased levels during the winter months from December 2001 to March 2002 and then decreased during the spring of 2002. This statistical modeling approach may help researchers estimate the SO₂ levels within the study area for their epidemiological studies or risk assessment.