System-on-a-Chip (SOC) based environmental monitoring platform for the detection of hazardous materials

The purpose of this research is design considerations for environmental monitoring platforms for the detection of hazardous materials using System-on-a-Chip (SoC) design. Design considerations focus on improving key areas such as: (1) sampling methodology; (2) context awareness; and (3) sensor placement. These design considerations for environmental monitoring platforms using wireless sensor networks (WSN) is applied to the detection of methylmercury (MeHg) and environmental parameters affecting its formation (methylation) and deformation (demethylation). ^ The sampling methodology investigates a proof-of-concept for the monitoring of MeHg using three primary components: (1) chemical derivatization; (2) preconcentration using the purge-and-trap (P&T) method; and (3) sensing using Quartz Crystal Microbalance (QCM) sensors. This study focuses on the measurement of inorganic mercury (Hg) (e.g., Hg2+) and applies lessons learned to organic Hg (e.g., MeHg) detection. ^ Context awareness of a WSN and sampling strategies is enhanced by using spatial analysis techniques, namely geostatistical analysis (i.e., classical variography and ordinary point kriging), to help predict the phenomena of interest in unmonitored locations (i.e., locations without sensors). This aids in making more informed decisions on control of the WSN (e.g., communications strategy, power management, resource allocation, sampling rate and strategy, etc.). This methodology improves the precision of controllability by adding potentially significant information of unmonitored locations.^ There are two types of sensors that are investigated in this study for near-optimal placement in a WSN: (1) environmental (e.g., humidity, moisture, temperature, etc.) and (2) visual (e.g., camera) sensors. The near-optimal placement of environmental sensors is found utilizing a strategy which minimizes the variance of spatial analysis based on randomly chosen points representing the sensor locations. Spatial analysis is employed using geostatistical analysis and optimization occurs with Monte Carlo analysis. Visual sensor placement is accomplished for omnidirectional cameras operating in a WSN using an optimal placement metric (OPM) which is calculated for each grid point based on line-of-site (LOS) in a defined number of directions where known obstacles are taken into consideration. Optimal areas of camera placement are determined based on areas generating the largest OPMs. Statistical analysis is examined by using Monte Carlo analysis with varying number of obstacles and cameras in a defined space. ^

Salinity and Chlorophyll a as Performance Measures to Rehabilitate a Mangrove-Dominated Deltaic Coastal Region: the Ciénaga Grande de Santa Marta–Pajarales Lagoon Complex, Colombia

Salinity, water temperature, and chlorophyll a (chl-a) biomass were used as performance measures in the period 1999–2001 to evaluate the effect of a hydrological rehabilitation project in the Ciénaga Grande de Santa Marta (CGSM)–Pajarales lagoon complex, Colombia where freshwater diversions were initiated in 1995 and completed in 1998. The objective of this study was to evaluate how diversions of freshwater into previously hypersaline (>80) environments changed the spatial and temporal distribution of environmental characteristics. Following the diversion, 19 surveys and transects using a flow-through system were surveyed in the CGSM–Pajarales complex to continuously measure selected water quality parameters. Geostatistical analysis indicates that hydrology and salinity regimes and water circulation patterns in the CGSM lagoon are largely controlled by freshwater discharge from the Fundacion, Aracataca, and Sevilla Rivers. Residence times in the CGSM lagoon were similar before (15.5 ± 3.8 days) and after (14.2 ± 2.0 days) the rehabilitation project and indicated that the system is flushed regularly. In contrast, chl-a biomass was highly variable in the CGSM–Pajarales lagoon complex and not related to discharge patterns. Mean annual chl-a biomass (44–250 μg L−1) following the diversion project was similar to values recorded since the 1980s and still remains among the highest reported in coastal systems around the world owing to its unique hydrology regulated by the Magdalena River and Sierra Nevada de Santa Marta watersheds and the high teleconnection to the El Niño Southern Oscillation (ENSO). Our results confirm that the reduction in salinity in the CGSM lagoon and Pajarales complex during 1999–2000 was largely driven by high precipitation (2500 mm) induced by the ENSO–La Niña rather than by the freshwater diversions.