Status and Trends of Dissolved Oxygen in Corpus Christi Bay, Texas, U.S.A.

The purpose of this studywas to determine status and long-term trends of dissolved oxygen concentrations (DO) in Corpus Christi Bay, Texas, U.S.A. A 20-year record of randomized stations was used to determine the trend of surface water DO, salinity, and temperature over space and time. A 13-year record of two fixed stations was used to determine the temporal nutrient trends. A 10-year record of fixed stations in the southeastern region of Corpus Christi Bay was used to determine the status of disturbance caused by low DO in bottom waters. From 1982 to 2002, there was a significant decrease in surface water DO at a rate of 0.06 mg L⁻¹ yr⁻¹ and a significant increase in surface water temperature at a rate of 0.07°C yr⁻¹. The southeastern region of Corpus Christi Bay had the lowest average DO, and during July and August, DO are steadily declining at a rate of 0.09 mg L⁻¹ yr⁻¹. It is not likely that eutrophication is causing hypoxia, because freshwater inflow rates have significantly decreased since 1941 and nutrient levels have not changed from 1987 to 2000. Even though long-term trends indicate that average surface DO is decreasing, disturbance by hypoxia appears to be stable, but this may be due to just eight years of data. In fact, if the current trend continues, surface water DO will not meet exceptional aquatic life standards (≤5 mgL⁻¹) in 2032.     

Use of cluster and principal component analyses to profile areas in California where ground water has been contaminated by pesticides

An empirical approach to profiling areas of ground water contamination by pesticides was devised that did not rely upon determining the level of vulnerability between land areas and that did not assume any particular pathway for ground water contamination. Climatic and soil data were obtained for 1-square mile sections of land in California where pesticide residues had been found in well water samples and the detection was attributed to legal agricultural applications. These sections were designated as known contaminated (KC) sections. Climate and soil data were also obtained for sections which lacked either well sampling data or a positive pesticide detection. These sections were designated as candidate sections. Statistical procedures were used to cluster groups of KC sections first with respect to climate characteristics and then with respect to soil characteristics. Principal components analysis (PCA) was used to construct a statistical profile of soil variables for each cluster of KC sections. A method based on the PCA was developed to compare the similarity of soil profiles derived for each KC section cluster to individual candidate sections. Since the profiling scheme was based only on data from KC sections, candidate sections that did not match any KC cluster profile could only be considered dissimilar to contaminated sections, receiving a status of not-classified. This profiling method is flexible and it can be revised to incorporate updated well sampling information.     

A review of potential physical impacts on harbours in the Mediterranean Sea under climate change

Regional Environmental Change - The potential impact of climate change on port operations and infrastructures has received much less attention than the corresponding impact for beach systems....     

A Cost-Effective Weighing Chamber for Particulate Matter Filters

ABSTRACT

Particulate matter (PM) is a ubiquitous air pollutant that has been receiving increasing attention in recent years due in part to the association between PM and a number of adverse health outcomes, including mortality and increases in emergency room visits and respiratory symptoms, as well as exacerbation of asthma and decrements in lung function.^1-5 As a result, the ability to accurately sample ambient PM has become important, both to researchers and to regulatory agencies. The federal reference method for the determination of fine PM as PM_2.5 in the atmosphere recommends that particle-sampling filters be conditioned and weighed in an environment with constant temperature and relative humidity (RH).⁶ It is also recommended that vibration, electrostatic charges, and contamination of the filters from laboratory air be minimized to reduce variability in filter weight measurements. These controls have typically been maintained in small, environmentally controlled “cleanrooms.” As an alternative to constructing an elaborate cleanroom, we have designed, and presented in this paper, an inexpensive weighing chamber to maintain the necessary level of humidity control.     

Relationships between lichen community composition and concentrations of NO2 and NH3

The relationship between different features of lichen communities in Quercus robur canopies and environmental variables, including concentrations of NO₂ and NH₃ was investigated. NO₂ concentration was the most significant variable, it was positively correlated with the proportion of lichen cover comprising nitrophytes and negatively correlated with total lichen cover. None of the lichen community features were correlated with NH₃ concentrations, which were relatively low across the site. Since nitrophytes and nitrophobes are likely to react in opposite directions to nitrogenous compounds, total lichen cover is not a suitable indicator for these pollutants. It is, therefore, suggested that the proportion of lichen cover comprising nitrophytes may be a suitable simple indicator of air quality, particularly in locations where the pollution climate is dominated by oxides of nitrogen.     

Comparing universal kriging and land-use regression for predicting concentrations of gaseous oxides of nitrogen (NOx) for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

BACKGROUND: Epidemiological studies that assess the health effects of long-term exposure to ambient air pollution are used to inform public policy. These studies rely on exposure models that use data collected from pollution monitoring sites to predict exposures at subject locations. Land use regression (LUR) and universal kriging (UK) have been suggested as potential prediction methods. We evaluate these approaches on a dataset including measurements from three seasons in Los Angeles, CA. METHODS: The measurements of gaseous oxides of nitrogen (NOx) used in this study are from a "snapshot" sampling campaign that is part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). The measurements in Los Angeles were collected during three two-week periods in the summer, autumn, and winter, each with about 150 sites. The design included clusters of monitors on either side of busy roads to capture near-field gradients of traffic-related pollution. LUR and UK prediction models were created using geographic information system (GIS)-based covariates. Selection of covariates was based on 10-fold cross-validated (CV) R(2) and root mean square error (RMSE). Since UK requires specialized software, a computationally simpler two-step procedure was also employed to approximate fitting the UK model using readily available regression and GIS software. RESULTS: UK models consistently performed as well as or better than the analogous LUR models. The best CV R(2) values for season-specific UK models predicting log(NOx) were 0.75, 0.72, and 0.74 (CV RMSE 0.20, 0.17, and 0.15) for summer, autumn, and winter, respectively. The best CV R(2) values for season-specific LUR models predicting log(NOx) were 0.74, 0.60, and 0.67 (CV RMSE 0.20, 0.20, and 0.17). The two-stage approximation to UK also performed better than LUR and nearly as well as the full UK model with CV R(2) values 0.75, 0.70, and 0.70 (CV RMSE 0.20, 0.17, and 0.17) for summer, autumn, and winter, respectively. CONCLUSION: High quality LUR and UK prediction models for NOx in Los Angeles were developed for the three seasons based on data collected for MESA Air. In our study, UK consistently outperformed LUR. Similarly, the 2-step approach was more effective than the LUR models, with performance equal to or slightly worse than UK.