Trends in snowpack chemistry and comparison to National Atmospheric Deposition Program results for the Rocky Mountains, US, 1993–2004

Seasonal snowpack chemistry data from the Rocky Mountain region of the US was examined to identify long-term trends in concentration and chemical deposition in snow and in snow-water equivalent. For the period 1993–2004, comparisons of trends were made between 54 Rocky Mountain Snowpack sites and 16 National Atmospheric Deposition Program wetfall sites located nearby in the region. The region was divided into three subregions: Northern, Central, and Southern. A non-parametric correlation method known as the Regional Kendall Test was used. This technique collectively computed the slope, direction, and probability of trend for several sites at once in each of the Northern, Central, and Southern Rockies subregions. Seasonal Kendall tests were used to evaluate trends at individual sites.Significant trends occurred during the period in wetfall and snowpack concentrations and deposition, and in precipitation. For the comparison, trends in concentrations of ammonium, nitrate, and sulfate for the two networks were in fair agreement. In several cases, increases in ammonium and nitrate concentrations, and decreases in sulfate concentrations for both wetfall and snowpack were consistent in the three subregions. However, deposition patterns between wetfall and snowpack more often were opposite, particularly for ammonium and nitrate. Decreases in ammonium and nitrate deposition in wetfall in the central and southern rockies subregions mostly were moderately significant (p<0.11) in constrast to highly significant increases in snowpack (p<0.02). These opposite trends likely are explained by different rates of declining precipitation during the recent drought (1999–2004) and increasing concentration. Furthermore, dry deposition was an important factor in total deposition of nitrogen in the region. Sulfate deposition decreased with moderate to high significance in all three subregions in both wetfall and snowpack. Precipitation trends consistently were downward and significant for wetfall, snowpack, and snow-telemetry data for the central and southern rockies subregions (p<0.03), while no trends were noted for the Northern Rockies subregion.     

Footprints on ammonia concentrations from environmental regulations

Releases of ammonia (NH3) to the atmosphere contribute significantly to the deposition of nitrogen to both terrestrial and aquatic ecosystems. This is the background for the national NH3 emission ceilings in Europe. However, in some countries the national legislation aims not only to meet these ceilings but also to reduce the atmospheric nitrogen deposition to local ecosystems. Such measures to reduce the load of nitrogen to local ecosystems were introduced in Denmark in 1994. In this paper we demonstrate that this regulation is reflected in the NH3 concentrations in Denmark. The Danish legislation forces farmers to applying manure to the fields during the crop-growing season. We have analyzed the seasonal variation in local NH3 concentrations over the time period of 1989-2003. During this period the seasonal variation has changed from having moderate spring and autumn concentration peaks to having a single and much more pronounced spring peak. In the analysis we apply an NH3 emission model to demonstrate that these changes in the seasonal variation are a result of the changes in the Danish legislation. The analysis demonstrates the strength of using a high-resolution emission model in the analysis of routine monitoring data.     

Characterizing effects of uncertainties in MSW composting process through a coupled fuzzy vertex and factorial-analysis approach

A coupled fuzzy vertex and factorial-analysis approach was developed in this study for systematically characterizing effects of uncertainties in a municipal solid waste composting process. A comprehensive composting process model was also embedded into the system framework and used to address substrate decomposition and biomass growth, as well as the interactions between moisture contents, temperatures, and oxygen concentrations. The applicability of the proposed method was verified through a custom-made pilot-scale composting system. Results from fuzzy simulation indicated that the fuzzy vertex method could effectively communicate implicit knowledge into dynamic simulations and thus provide valuable information for enhancing composting process control under uncertainty. The factorial analysis was effective in quantifying the proportion to which the uncertainty of each single or interactive effect of model parameters contributes to the overall uncertainty of the system outcomes. Thus, sensitive parameters that may lead to errors or unreasonable predictions can be determined. The proposed study system could not only be used in characterizing combined effects of uncertainties for composting processes, but was also applicable to many other environmental modelling systems.     

Validation of a hybrid life-cycle inventory analysis method

The life-cycle inventory analysis step of a life-cycle assessment (LCA) may currently suffer from several limitations, mainly concerned with the use of incomplete and unreliable data sources and methods of assessment. Many past LCA studies have used traditional inventory analysis methods, namely process analysis and input-output analysis. More recently, hybrid inventory analysis methods have been developed, combining these two traditional methods in an attempt to minimise their limitations. In light of recent improvements, these hybrid methods need to be compared and validated, as these too have been considered to have several limitations. This paper evaluates a recently developed hybrid inventory analysis method which aims to improve the limitations of previous methods. It was found that the truncation associated with process analysis can be up to 87%, reflecting the considerable shortcomings in the quantity of process data currently available. Capital inputs were found to account for up to 22% of the total inputs to a particular product. These findings suggest that current best-practice methods are sufficiently accurate for most typical applications, but this is heavily dependent upon data quality and availability. The use of input-output data assists in improving the system boundary completeness of life-cycle inventories. However, the use of input-output analysis alone does not always provide an accurate model for replacing process data. Further improvements in the quantity of process data currently available are needed to increase the reliability of life-cycle inventories.     

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.     

Determination of Impact of Urbanization on Agricultural Land and Wetland Land Use in Balçovas’ Delta by Remote Sensing and GIS Technique

Because of their intense vegetation and the fact that they include areas of coastline, deltas situated in the vicinity of big cities are areas of greet attraction for people who wish to get away from in a crowded city. However, deltas, with their fertile soil and unique flora and fauna, need to be protected. In order for the use of such areas to be planned in a sustainable way by local authorities, there is a need for detailed data about these regions. In this study, the changes in land use of the Balçova Delta, which is to the immediate west of Turkey’s third largest city Izmir, from 1957 up to the present day, were investigated. In the study, using aerial photographs taken in 1957, 1976 and 1995 and an IKONOS satellite image from the year 2005, the natural and cultural characteristics of the region and changes in the coastline were determined spatially. Through this study, which aimed to reveal the characteristics of the areas of land already lost as well as the types of land use in the Balçova delta and to determine geographically the remaining areas in need of protection, local authorities were provided with the required data support. Balçova consists of flat and fertile wetland with mainly citrus-fruit orchards and flower-producing green houses. The marsh and lagoon system situated in the coastal areas of the delta provides a habitat for wild life, in particular birds. In the Balçova Delta, which provides feeding and resting for migratory birds, freshwater sources are of vital importance for fauna and flora. The settlement area, which in 1957 was 182 ha, increased 11-fold up to the year 2005 when it reached 2,141 ha. On the other hand, great losses were determined in farming land, olive groves, forest and in the marsh and lagoon system. This unsystematic and rapid urbanization occurring in the study region is not only causing the loss of important agricultural land and wetland, but also lasting water and soil pollution.     

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).     

Mapping Turbidity in the Charles River, Boston Using a High-resolution Satellite

The usability of high-resolution satellite imagery for estimating spatial water quality patterns in urban water bodies is evaluated using turbidity in the lower Charles River, Boston as a case study. Water turbidity was surveyed using a boat-mounted optical sensor (YSI) at 5 m spatial resolution, resulting in about 4,000 data points. The ground data were collected coincidently with a satellite imagery acquisition (IKONOS), which consists of multispectral (R, G, B) reflectance at 1 m resolution. The original correlation between the raw ground and satellite data was poor (R2 = 0.05). Ground data were processed by removing points affected by contamination (e.g., sensor encounters a particle floc), which were identified visually. Also, the ground data were corrected for the memory effect introduced by the sensor's protective casing using an analytical model. Satellite data were processed to remove pixels affected by permanent non-water features (e.g., shoreline). In addition, water pixels within a certain buffer distance from permanent non-water features were removed due to contamination by the adjacency effect. To determine the appropriate buffer distance, a procedure that explicitly considers the distance of pixels to the permanent non-water features was applied. Two automatic methods for removing the effect of temporary non-water features (e.g., boats) were investigated, including (1) creating a water-only mask based on an unsupervised classification and (2) removing (filling) all local maxima in reflectance. After the various processing steps, the correlation between the ground and satellite data was significantly better (R2 = 0.70). The correlation was applied to the satellite image to develop a map of turbidity in the lower Charles River, which reveals large-scale patterns in water clarity. However, the adjacency effect prevented the application of this method to near-shore areas, where high-resolution patterns were expected (e.g., outfall plumes).