Wind direction bias in generating wind roses and conducting sector-based air dispersion modeling

Certain widely used wind rose programs and air dispersion models use an overly simple data-transfer algorithm that induces a directional bias in their output products. The purpose of this paper is to provide a revised algorithm that corrects the directional bias that occurs from the aliasing that occurs when the sector widths used to report wind direction data are on the same order of magnitude, but not equal, to the sector widths used in the wind direction summaries. The directional bias issue arises when output products in 16 direction sectors (22.5 degrees each) are produced from wind direction data reported in terms of 36 sectors (10 degrees each). The result directional bias affects the results of simulations of air and surface concentrations using widely applied air dispersion models. Datasets or models with the directional bias discussed here give consistent positive biases (approximately 30%) for cardinal direction sectors (north, south, east, and west) and consistent negative biases for all of the other sectors (around -10%). Data summary and air dispersion programs providing outputs in direction sectors that do not match the observational sectors need to be checked for this bias. A revised data-transfer algorithm is provided that corrects the directional bias that can occur in transferring wind direction data between different sector widths.     

Urban observatories opportunities for environmental monitoring: solid wastes

Towns concentrate around 50% of world-wide population and the trend is oriented to underscore an urban profile of population. In addition, towns have become important for their economic contribution to the Gross Internal Product. The negative side of towns is the environmental and social impacts as a result of productive and domestic activities, besides the lack of available data. In order to overcome these shortcomings, the United Nations has established a project of urban monitoring throughout the Global Network of Urban Observatories; Mexico joined the project in 2005. The Local Urban Observatory of Mexicali has the task to produce information about cities that is useful to design public policies. Some of this information deals with a set of environmental indicators in the United Nations Habitat Agenda, which includes solid wastes. Therefore, this paper deals with two main topics; firstly, from the Habitat Agenda, a comparative urban analysis of waste production and coverage of domestic waste collection services; secondly, from the Local Agenda, the identification and ranking of environmental problems according to public perception coming from people involved in the municipal planning and decision making process. Results will be used to develop local indicators and public environmental policies.     

Seasonal Variation of Toxic Benzene Emissions in Petroleum Refinery

Petroleum refineries are largest chemical industries that are responsible for the emission of several pollutants into the atmosphere. Benzene is among the most important air pollutants that are emitted by petroleum refineries, since they are involved in almost every refinery process. Volatile organic compounds (VOCs) are a major group of air pollutants, which play a critical role in atmospheric chemistry. These contribute to toxic oxidants, which are harmful to ecosystem, human health and atmosphere. The variability of pollutants is an important factor in determining human exposure to these chemicals. The ambient air concentrations of benzene were measured in several sites around the Digboi petroleum refinery, near the city of Gowahati in northeast India, during winter and summer 2004. The seasonal and spatial variations of the ambient air concentrations of this benzene were investigated and analyzed. An estimation of the contribution of the refinery to the measured atmospheric levels of benzene was also performed. The ambient air mixing ratios of benzene in a large area outside the refinery was generally low, in ppbv range, much lower than the ambient air quality standards. This article presents the temporal and spatial variation of air pollution in and around petroleum refinery and showed that no health risk due to benzene is present in the areas adjacent to the refinery.     

Estimated Variability of National Atmospheric Deposition Program/Mercury Deposition Network Measurements Using Collocated Samplers

The National Atmospheric Deposition Program/Mercury Deposition Network (MDN) provides long-term, quality-assured records of mercury in wet deposition in the USA and Canada. Interpretation of spatial and temporal trends in the MDN data requires quantification of the variability of the MDN measurements. Variability is quantified for MDN data from collocated samplers at MDN sites in two states, one in Illinois and one in Washington. Median absolute differences in the collocated sampler data for total mercury concentration are approximately 11% of the median mercury concentration for all valid 1999–2004 MDN data. Median absolute differences are between 3.0% and 14% of the median MDN value for collector catch (sample volume) and between 6.0% and 15% of the median MDN value for mercury wet deposition. The overall measurement errors are sufficiently low to resolve between NADP/MDN measurements by ±2 ng·l⁻¹ and ±2 μg·m⁻²·year⁻¹, which are the contour intervals used to display the data on NADP isopleths maps for concentration and deposition, respectively.     

Coastal Flood Risk Analysis Using Landsat-7 ETM+ Imagery and SRTM DEM: A Case Study of Izmir, Turkey

The Intergovernmental Panel on Climate Change (IPCC) reports an acceleration of the global mean sea-level rise (MSLR) in the twentieth century in response to global climate change. If this acceleration remains constant, then some coastal areas are most likely to be inundated by the year 2100. The ability to identify the differential vulnerability of coastlines to future inundation hazards as result of global climate change is necessary for timely actions to be taken. Yildiz et al. (Journal of Mapping, 17, 1-75, 2003) reported that the local MSLR in the city of Izmir rose at a rate of 6.8 +/- 0.9 mm year(-1) between 1984 and 2002. In this study, the spatial distribution of the coastal inundation hazards of Izmir region was determined using not only land-use and land-cover (LULC) types derived from the maximum likelihood classification of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) multi-spectral image set but also the classification of the digital elevation model (DEM) acquired by the shuttle radar topography mission (SRTM). Coastal areas with elevations of 2 and 5 m above mean sea-level vulnerable to inundation were found to cover 2.1 and 3.7% of the study region (6,107 km(2)), respectively. Our findings revealed that Menemen plain along Gediz river, and the settlements of Karsiyaka, Alacati, Aliaga, Candarli and Selcuk are at high risk in order of decreasing vulnerability to permanent and episodic inundation by 2100 under the high MSLR scenarios of 20 to 50 mm year(-1).     

Serial Correlation and Inter-annual Variability in Relation to the Statistical Power of Monitoring Schemes to Detect Trends in Fish Populations

We studied the effects of inter-annual variability and serial correlation on the statistical power of monitoring schemes to detect trends in biomass of bream (Abramis brama) in Lake Veluwemeer (The Netherlands). In order to distinguish between 'true' system variability and sampling variability we simulated the development of the bream population, using estimates for population structure and growth, and compared the resulting inter-annual variabilities and serial correlations with those from field data. In all cases the inter-annual variability in the field data was larger than in simulated data (e.g. for total biomass of all assessed bream sigma = 0.45 in field data, and sigma = 0.03-0.14 in simulated data) indicating that sampling variability decreased statistical power for detecting trends. Moreover, sampling variability obscured the inter-annual dependency (and thus the serial correlation) of biomass, which was expected because in this long-lived population biomass changes are buffered by the many year classes present. We did find the expected serial correlation in our simulation results and concluded that good survey data of long-lived fish populations should show low sampling variability and considerable inter-annual serial correlation. Since serial correlation decreases the power for detecting trends, this means that even when sampling variability would be greatly reduced, the number of sampling years to detect a change of 15%.year(-1) in bream populations (corresponding to a halving or doubling in a six-year period) would in most cases be more than six. This would imply that the six-year reporting periods that are required by the Water Framework Directive of the European Union are too short for the existing fish monitoring schemes.     

A Procedure for NEPA Assessment of Selenium Hazards Associated With Mining

This paper gives step-by-step instructions for assessing aquatic selenium hazards associated with mining. The procedure was developed to provide the U.S. Forest Service with a proactive capability for determining the risk of selenium pollution when it reviews mine permit applications in accordance with the National Environmental Policy Act (NEPA). The procedural framework is constructed in a decision-tree format in order to guide users through the various steps, provide a logical sequence for completing individual tasks, and identify key decision points. There are five major components designed to gather information on operational parameters of the proposed mine as well as key aspects of the physical, chemical, and biological environment surrounding it — geological assessment, mine operation assessment, hydrological assessment, biological assessment, and hazard assessment. Validation tests conducted at three mines where selenium pollution has occurred confirmed that the procedure will accurately predict ecological risks. In each case, it correctly identified and quantified selenium hazard, and indicated the steps needed to reduce this hazard to an acceptable level. By utilizing the procedure, NEPA workers can be confident in their ability to understand the risk of aquatic selenium pollution and take appropriate action. Although the procedure was developed for the Forest Service it should also be useful to other federal land management agencies that conduct NEPA assessments, as well as regulatory agencies responsible for issuing coal mining permits under the authority of the Surface Mining Control and Reclamation Act (SMCRA) and associated Section 401 water quality certification under the Clean Water Act. Mining companies will also benefit from the application of this procedure because priority selenium sources can be identified in relation to specific mine operating parameters. The procedure will reveal the point(s) at which there is a need to modify operating conditions to meet environmental quality goals. By recognizing concerns early in the NEPA process, it may be possible for a mining company to match operational parameters with environmental requirements, thereby increasing the likelihood that the permit application will be approved.     

Pesticide Residues in Bovine Milk from a Predominantly Agricultural State of Haryana, India

One hundred forty seven samples of bovine milk were collected from 14 districts of Haryana, India during December 1998–February 1999 and analysed for the presence of organochlorine pesticide (OCPs) residues. ∑HCH, ∑DDT, ∑endosulfan and aldrin were detected in 100%, 97%, 43% and 12% samples and with mean values of 0.0292, 0.0367, 0.0022 and 0.0036 μg/ml, respectively. Eight percent samples exceeded the maximum residue limit (MRL) of 0.10 mg/kg as recommended by WHO for ∑HCH, 4% samples of 0.05 mg/kg for α-HCH, 5% samples of 0.01 mg/kg for γ-HCH, 26% samples of 0.02 mg/kg for β-HCH as recommended by PFAA and 24% samples of 0.05 mg/kg as recommended by FAO for ∑DDT. Concentrations of β-HCH and p,p′-DDE were more as compared to other isomers and metabolites of HCH and DDT.     

Deficit analysis: service capacity assessment and planning in developing countries – case study in the Philippines

Current demand analysis methods do not formally cover the case of chronic deficits in quantity or quality of water and sanitation services. These services include drinking water supply (DWS), wastewater and sewage treatment (WST), and municipal solid waste management (MSW). Formal analysis of this case would, at minimum, define the deficit state and evaluate appropriate options for reducing it. This paper proposes for a formal analytical model for municipal sanitation systems (MSS) that operate with deficits in at least one of the constituent services of DWS, WST, or MSW. The model introduces definitions and notation for describing the deficit state for conducting demand analysis on municipal sanitation systems. This model of demand analysis for systems with chronic deficits will hereinafter be referred to as deficit analysis. A case study for Bacoor, Philippines is presented as an example.     

Relation of waste generation and composition to socio-economic factors: a case study

To develop an effective waste management strategy for a given region, it is important to know the amount of waste generated and the composition of the waste stream. Past research has shown that the amount of waste generated is proportional to the population and the average mean living standards or the average income of the people. In addition, other factors may affect the amount and composition of waste. These are climate, living habits, level of education, religious and cultural beliefs, and social and public attitudes. This paper presents the findings of a study carried out in a suburban municipal area in Sri Lanka to determine the solid waste generation rate and waste composition based on field surveys and to determine the related socio-economic factors. A database was developed that included information on the quantity and composition of waste generated in a sample of households in the study area over a time period. The collected data was analysed to relate waste generation and composition data to various socio-economic factors. Over 400 sample households were selected for the study using a stratified random sampling methodology based on municipal wards and property values. A technique that considers both the number of households in a particular income group (property value range) and the standard deviation of property values within a given income group was used to determine the appropriate sample size for each municipal ward. Through category and regression analyses, the quantities of waste and waste composition were related to several socio-economic factors. The paper describes the basis for the sample selection, the methodology adopted for data collection, the socio-economic parameters used for the analysis, and the relationships developed from the analysis.