Assessment of groundwater quality: a fusion of geochemical and geophysical information via Bayesian neural networks

Deplorable quality of groundwater arising from saltwater intrusion, natural leaching and anthropogenic activities is one of the major concerns for the society. Assessment of groundwater quality is, therefore, a primary objective of scientific research. Here, we propose an artificial neural network-based method set in a Bayesian neural network (BNN) framework and employ it to assess groundwater quality. The approach is based on analyzing 36 water samples and inverting up to 85 Schlumberger vertical electrical sounding data. We constructed a priori model by suitably parameterizing geochemical and geophysical data collected from the western part of India. The posterior model (post-inversion) was estimated using the BNN learning procedure and global hybrid Monte Carlo/Markov Chain Monte Carlo optimization scheme. By suitable parameterization of geochemical and geophysical parameters, we simulated 1,500 training samples, out of which 50 % samples were used for training and remaining 50 % were used for validation and testing. We show that the trained model is able to classify validation and test samples with 85 % and 80 % accuracy respectively. Based on cross-correlation analysis and Gibb’s diagram of geochemical attributes, the groundwater qualities of the study area were classified into following three categories: “Very good”, “Good”, and “Unsuitable”. The BNN model-based results suggest that groundwater quality falls mostly in the range of “Good” to “Very good” except for some places near the Arabian Sea. The new modeling results powered by uncertainty and statistical analyses would provide useful constrain, which could be utilized in monitoring and assessment of the groundwater quality.     

Decreasing reliance on mineral nitrogen--yet more food

Higher crop production normally demands higher nutrient application rates and consequently increased mineral nitrogen use. With food demand for 2030 estimated around 2800 mill. tonnes (t) yr-1, the corresponding mineral N consumption figure is 96 mill. t (78 mill. t yr-1 in 1995/1997). Global-level mineral N losses to the environment from mineral fertilizer use are currently 36 mill. t yr-1, worth USD 11,700 mill. and with adverse environmental impacts. However, innovative fertilizer-use efficiency (FUE) technologies enable increased production with a less than a proportionate increase in mineral-N use. Moreover, nitrogen-nutrient supplies can be augmented through improvements in agricultural production systems and in the exploitation of alternative sources such as biological nitrogen fixation (BNF). By 2030, with adequate policy, technology transfer, research and investment support, the on-farm adoption of BNF and FUE technologies could generate savings of 10 mill. t yr-1 of mineral N, worth USD 3300 mill.     

A Spanish model for quantification and management of construction waste

Currently, construction and demolition waste (C&D waste) is a worldwide issue that concerns not only governments but also the building actors involved in construction activity. In Spain, a new national decree has been regulating the production and management of C&D waste since February 2008. The present work describes the waste management model that has inspired this decree: the Alcores model implemented with good results in Los Alcores Community (Seville, Spain). A detailed model is also provided to estimate the volume of waste that is expected to be generated on the building site. The quantification of C&D waste volume, from the project stage, is essential for the building actors to properly plan and control its disposal. This quantification model has been developed by studying 100 dwelling projects, especially their bill of quantities, and defining three coefficients to estimate the demolished volume (CT), the wreckage volume (CR) and the packaging volume (CE). Finally, two case studies are included to illustrate the usefulness of the model to estimate C&D waste volume in both new construction and demolition projects.     

Evaluating pollution-related damage and restoration success in urban forests with participatory monitoring and digital tools

Peri-urban forest monitoring requires indicators of vegetation damage. An example is the sacred fir (Abies religiosa) forests surrounding Mexico City, which have been heavily exposed to tropospheric ozone, a harmful pollutant, for over 4 decades. We developed a participatory monitoring system with which local community members and scientists generated data on ozone tree damage. Santa Rosa Xochiac rangers (13) used the digital tool KoboToolBox to record ozone damage to trees, tree height, tree ages, tree condition, tree position, and whether the tree had been planted. Thirty-five percent of the trees (n = 1765) had ozone damage. Younger trees had a lower percentage of foliage damaged by ozone than older trees (p < 0.0001), and asymptomatic trees tended to be younger (p < 0.0001). Symptomatic trees were taller than asymptomatic trees of the same age (R²_c = 0.43, R²_m = 0.27). Involving local communities facilitated forest monitoring and using digital technology improved data quality. This participatory system can be used to monitor forest condition change over time and thus aids restoration efforts driven by government or local communities’ interests, facilitating local decision-making.     

A comparison of fish tissue mercury concentrations from homogenized fillet and nonlethal biopsy plugs

The use of biopsy plugs to sample fish muscle tissue for mercury analyses is a viable alternative to lethal sampling; however, the practice has yet to be widely implemented in routine monitoring due to concerns about variability of mercury concentrations in fish muscle tissues. Here we examine distribution of mercury in fillets of four fish species (Walleye, Northern Pike, Smallmouth Bass and Lake Trout), suitability of left/right side of fillet for biopsy sampling, and appropriateness of re-using a biopsy punch. The results showed that average mercury concentrations in left and right fillets of fish are similar. Mercury concentrations in biopsy plug samples, taken from the anterior dorsal area of the fish fillet, were statistically equivalent to the mercury concentrations in homogenized fillets. There was no discernible cross contamination between samples when a biopsy punch was reused after washing in hot soapy water, and as such, biopsy punches can be recycled during sampling to reduce the sampling cost. If a tissue mass collected from a specific site on the fillet is insufficient, then we suggest sampling corresponding locations on the other fillet rather than sampling two adjacent sites on one fillet to obtain more tissue. The results presented here can improve the accuracy of fillet biopsy plug sampling, minimize fish mortality for mercury monitoring, and reduce labor and material costs in monitoring programs.