Assessment of genotoxic and humoral immune system alterations in silica exposed workers from pottery industries in South India

Chemicals, especially silica, have been suspected to cause genetic alterations in pottery industry workers. The present study aims to analyze the frequency of chromosomal aberrations (CA), micronucleus (MN) and DNA damage (comet assay) in the peripheral blood lymphocytes and the immunological alterations workers chronically exposed to silica and in control subjects. In our study, 50 silica exposed workers and 35 control subjects were recruited and silica level was measured by respirable dust and respirable quartz concentrations of badge dosimeter. The serum immunoglobulins (IgM, IgG, and IgA) of all the subjects were measured by using ELISA method. The individuals exposed to silica have a significant increase in the frequency of CA, MN and the total DNA damage (p < 0.05). Immunoglobulin elevation on silica exposed workers was statistically significant (p < 0.05) on comparison with their respective controls. Investigation of the smoking and alcohol habitats coupled with silica exposure in exposed and control subjects represents alcohol consumption and smoking as additional risk factors and must be avoided. Multiple linear regression analysis obtained for CA, MN and comet assay confirm these tests as biomarkers for silica exposed pottery workers. Some confounding factors also showed significant influence on exposed subjects. These results indicate the mutagenic risk in the working environment has a high probability of association with the silica dust exposure in pottery industries. Nevertheless, the present study will create awareness and public concern not only among the silica exposed workers but also to the welfare of their progeny.     

Partial substitution of peat moss with biochar for sustainable cultivation of <Emphasis Type="Italic">Durio zibethinus L</Emphasis>. in nurseries

The extensive use of peat moss as potting medium in nurseries worldwide is not sustainable causing peatland depletion and greenhouse gas emissions. This research seeks to explore whether wood biochar produced by the environment-friendly flame curtain method can partially substitute peat moss in plant nurseries without affecting plant growth and health. Biochar was produced from durian wood logs in a top-quenched Kon-Tiki earth kiln, crushed, and mixed with peat moss at dosages of 0, 1, 2.5 and 5% (w/w). Durian seedlings were grown in 2.5 L polybags arranged in randomised complete block design with 4 replicates per treatment. Plant height, collar diameter, pH, moisture content, number of branches and leaves, and plant health were monitored weekly for 94 days. Liquid fish fertiliser was used as organic fertiliser. Our results demonstrated that biochar can substitute at least 5% (w/w) peat moss without negatively affecting plant height, collar diameter, number of leaves and branches, and plant health. In addition, organic fertiliser is not required during the first 3 months of cultivation resulting in cost savings to the nursery operator. Plant height was found to be the most accurate yet simple monitoring parameter studied. A better understanding of the effect of higher biochar application rates as well as the number of times the potting medium can be reused without loss of potting medium properties and health can help to further cut nursery cost and reduce reliance on peat moss.     

Chemical weathering and carbon dioxide consumption in a small tropical river catchment,southwestern India

Aquatic Geochemistry - Studies done on small tropical west-flowing river catchments located in the Western Ghats in southwestern India have suggested very intense chemical weathering rates and...     

Automatic Tree Identification and Diameter Estimation Using Single Scan Terrestrial Laser Scanner Data in Central Indian Forests

Forest inventory parameters, primarily tree diameter and height, are required for several management and planning activities. Currently, Terrestrial Laser Scanning (TLS) is a promising technology in automated measurements of tree parameters using dense 3D point clouds. In comparison with conventional manual field inventory methods, TLS systems would supplement field data with detailed and relatively higher degree of accurate measurements and increased measurement frequency. Although, multiple scans from TLS captures more area, they are resource and time consuming to ensure proper co-registration between the scans. On the other hand, Single scans provide a fast and recording of the data but are often affected by occlusions between the trees. The current study evaluates potential of single scan TLS data to (1) develop an automatic method for tree stem identification and diameter estimation (diameter at breast height—DBH) using random sample consensus (RANSAC) based circle fitting algorithm, (2) validate using field based measurements to derive accuracy estimates and (3) assess the influence of distance to scanner on detection and measurement accuracies. Tree detection and diameter measurements were validated for 5 circular plots of 20 m radius using single scans in dry deciduous forests of Betul, Madhya Pradesh. An overall tree detection accuracy of 85 and 70% was observed in the scanner range of 15 and 20 m respectively. The tree detection accuracies decreased with increased distance to the scanner due to the decrease in visible area. Also, estimated stem diameter using TLS was found to be in agreement with the field measured diameter (R² = 0.97). The RMSE of estimated DBH was found to be 3.5 cm (relative RMSE ~20%) over 202 trees detected over 5 plots. Results suggest that single scan approach suffices the cause of accuracy, reducing uncertainty and adds to increased sampling frequency in forest inventory and also implies that TLS has a seemingly high potential in forest management.     

Assessment of various parameters on 3D semantic object-based point cloud labelling on urban LiDAR dataset

Semantic labelling of LiDAR point cloud is critical for effective utilization of 3D points in numerous applications. 3D segmentation, incorporation of ancillary data, feature extraction and classification are the key stages in object-based point cloud labelling. The choice of algorithms and tuning parameters adopted in these stages has substantial impact on the quality of results from object-based point cloud labelling. This paper critically evaluates the performance of object-based point cloud labelling as a function of different 3D segmentation approaches, incorporation of spectral data and computational complexity of the point cloud. The designed experiments are implemented on the datasets provided by the ISPRS and the results are independently validated by the ISPRS. Results indicate that aggregation of dense point cloud into higher-level object analogue (e.g. supervoxels) before 3D segmentation stage offers superior labelling results and best computational performance compared to the popular surface growing-based approaches.     

Saturation states of carbonate minerals in a freshwater-seawater mixing zone of small tropical island’s aquifer

Groundwater is a crucial resource on the Manukan Island as it is the only source of freshwater available on the island. The aquifer has deteriorated to a high degree, during the last decade. Nine domestic wells were sam-pled from March 2006 to January 2007 to probe the hydrochemical components that influence the water quality. Geochemical data on dissolved major constituents in groundwater samples from the Manukan Island revealed the main processes responsible for their geochemical evolution. The results using statistical analyses, graphical method and numerical model output (PHREEQC) showed that the groundwater was chemically highly enriched in Na and Cl, indicative of seawater intrusion into the aquifer as also supported from the Na-Cl signature on the Piper diagram. From the PHREEQC simulation model, calcite, dolomite and aragonite solubility showed positive values of the saturation indices (SI), indicating supersaturation which led to mineral precipitation condition of water by these min-erals.     

Climate change adaptation cost in the US: what do we know?

Researchers and policy makers increasingly recognize the need to adapt to future changes in climate, given that past emissions of greenhouse gases have already committed the world to some level of climate change. However, the current understanding of the costs and benefits of adaptation measures is still fairly rudimentary, and far from comprehensive. An assessment is presented of the current state of knowledge on the magnitude of adaptation costs in the United States. While incomplete, the studies suggest that adaptation cost could be as high as tens or hundreds of billions of dollars per year by the middle of this century. Key studies are identified in each sector, and the cost estimates and approaches to cost estimation are surveyed. Methodological issues are highlighted in interpreting, comparing, and aggregating adaptation cost estimates. Policy recommendations are made along with appropriate steps to make future adaptation cost studies more comparable within and across sectors and more accessible and relevant to policy and decision makers.

Policy relevance

Designing and implementing climate change adaptation policy requires good information about the effectiveness and cost of available adaptive options. The current state of knowledge on adaptation costs in the United States is assessed and significant gaps in the literature are highlighted – particularly in terms of sectoral and geographic coverage – as well as inconsistencies in methodologies and assumptions that hamper comparison across studies. Critical steps are identified that can be taken to make adaptation cost studies more accessible and useful to decision makers. The findings and recommendations are relevant to adaptation cost studies globally, not just in the United States.     

Skill assessment of global climate model wind speed from CMIP5 and CMIP6 and evaluation of projections for the Bay of Bengal

Climate Dynamics - Atmospheric and oceanic parameters derived from global climate model (GCM) simulations have received wide global attention and importance in representing the future world under...