Cadmium-hazard mapping using a general linear regression model (Irr-Cad) for rapid risk assessment

Research undertaken over the last 40 years has identified the irrefutable relationship between the long-term consumption of cadmium (Cd)-contaminated rice and human Cd disease. In order to protect public health and livelihood security, the ability to accurately and rapidly determine spatial Cd contamination is of high priority. During 2001–2004, a General Linear Regression Model Irr-Cad was developed to predict the spatial distribution of soil Cd in a Cd/Zn co-contaminated cascading irrigated rice-based system in Mae Sot District, Tak Province, Thailand (Longitude E 98°59′–E 98°63′ and Latitude N 16°67′–16°66′). The results indicate that Irr-Cad accounted for 98% of the variance in mean Field Order total soil Cd. Preliminary validation indicated that Irr-Cad ‘predicted’ mean Field Order total soil Cd, was significantly (p < 0.001) correlated (R ² = 0.92) with ‘observed’ mean Field Order total soil Cd values. Field Order is determined by a given field's proximity to primary outlets from in-field irrigation channels and subsequent inter-field irrigation flows. This in turn determines Field Order in Irrigation Sequence (Field Order^IS). Mean Field Order total soil Cd represents the mean total soil Cd (aqua regia-digested) for a given Field Order^IS. In 2004–2005, Irr-Cad was utilized to evaluate the spatial distribution of total soil Cd in a ‘high-risk’ area of Mae Sot District. Secondary validation on six randomly selected field groups verified that Irr-Cad predicted mean Field Order total soil Cd and was significantly (p < 0.001) correlated with the observed mean Field Order total soil Cd with R ² values ranging from 0.89 to 0.97. The practical applicability of Irr-Cad is in its minimal input requirements, namely the classification of fields in terms of Field Order^IS, strategic sampling of all primary fields and laboratory based determination of total soil Cd (T-Cd_P) and the use of a weighed coefficient for Cd (Coeff_W). The use of primary fields as the basis for Irr-Cad is also an important practical consideration due to their inherent ease of identification and vital role in the classification of fields in terms of Field Order^IS. The inclusion of mean field order soil pH (1:5_water) to the Irr-Cad model accounted for over 79% of the variation in mean Field Order bio-available (DTPA (diethylenetriaminepentaacetic acid)-extractable) soil Cd. Rice is the staple food of countries of the Greater Mekong Sub-region (includes Vietnam, Myanmar, Lao PDR, Thailand and Yunnan Province, China). These countries also have actively and historically mined Zn, Pb, and Cu deposits where Cd is likely to be a potential hazard if un-controlled discharge/runoff enters areas of rice cultivation. As such, it is envisaged that the Irr-Cad model could be applied for Cd hazard assessment and effectively form the basis of intervention options and policy decisions to protect public health, livelihoods, and export security.     

The effects of sewage on alpine streams in Kosciusko National Park,NSW

The impact of resort developments in three alpine streams of Kosciusko National Park was examined by the State Pollution Control Commission of NSW over 1981 and 1982. Physico-chemical measurements such as nutrient concentrations, stream flow and temperature were correlated with measures of periphyton growth using artificial substrates and the Thomas (1978) method for estimation of in-stream biomass.Stream flow was the major physical parameter controlling in-stream periphyton growth, far outweighing seasonal temperature variations. Nutrients emanating from resort developments were also a major influence on biomass and taxa. Natural accumulations occurred upstream of resort developments under low flow conditions and were associated with taxa typical of clean water conditions. The relationships between periphyton biomass and nutrient loads could be quantified.     

An experimental comparison of conservative versus optimal collision avoidance warning system thresholds

In the distributed signal detection theoretic (DSDT) model, the human operator and the warning mechanism are independent decision makers who work together as a team. The DSDT demonstrates that the optimal warning threshold, in general, differs from the signal detection theoretic (SDT) threshold, which assumes a single decision maker. This prediction was tested in an experiment where drivers received monetary rewards for making safe passing decisions on a driving simulator. The experiment focused on evaluating the quality of the decision making of the drivers, and not on perceptual issues. A collision avoidance system provided a warning when the probability of an inadequate overtaking gap exceeded a threshold. Three thresholds were tested. The control threshold resulted in no detections or false alarms. The DSDT threshold resulted in some misses but no false alarms. The SDT threshold resulted in no misses but frequent false alarms. As predicted, (1) drivers performed the best when the warning system used the DSDT threshold, and (2) use of the SDT threshold improved performance over the control threshold, even though four of the 10 drivers occasionally ignored the warning and made risky passing attempts in the SDT conditions, possibly because of earlier false alarms. These findings support the conclusion that the DSDT model is a useful, quantitative tool that should be used by warning designers.