This study evaluated the effect of wood extracts from Tectona grandis, Dalbergia sissoo, Cedrus deodara, and Pinus roxburghii combined with linseed oil as protectants of two non-durable wood species against the termite, Heterotermes indicola. Heartwood blocks (19 × 19 × 19 mm) and wood shavings were extracted using an ethanol/toluene (2:1) solvent system. Results of choice and no-choice tests with solvent-extracted and non-extracted heartwood blocks showed greater wood mass loss from termite feeding on solvent-extracted blocks compared with non-extracted blocks for all wood species. Significantly higher termite mortality was observed after termite exposure to non-extracted blocks compared with extracted blocks for all durable species. Sapwood blocks of two non-durable wood species (southern pine and cottonwood) were vacuum/pressure impregnated separately with each of the four types of extract at a concentration of 7.5 mg ml⁻¹, linseed oil (20%) and a mixture of oil (20%) and extracts (4.25 mg ml⁻¹) for the laboratory and field tests. Results showed that extract-oil mixture imparted significantly higher termite resistance compared with linseed or extracts alone under laboratory conditions. This apparent synergistic effect was clearly noted when linseed oil was combined with extracts from T. grandis or D. sissoo followed by an extract-oil mixture using C. deodara. These extract oil mixtures showed significantly less weight loss for the treated non-durable wood species and higher termite mortality (83–100%) compared with the control treatments and other extract-linseed oil mixtures tested. Treatment of both non-durable wood species with T. grandis + oil and D. sissoo + oil prevented termite damage compared with other treatments when blocks and stakes were exposed in the field for a period of 2 years. Results of the current study indicated that a mixture of a particular heartwood extract with linseed oil has potential to be used as environmentally friendly wood protectants.

Response surface methodology (RSM) and artificial neural network (ANN) were used to generate a model for the optimization of fluoride removal using chemically activated Dalbergia sissoo sawdust (CADS). The single and collective effects of process parameters, i.e., solution pH, CADS dose, initial fluoride concentration, and contact time, were studied. The point of zero charge was found to be 4.2 with zeta potential analysis. In the first phase, a single-parameter study was performed to reveal dependency of fluoride removal on a particular process parameter. Positive effects of increment in CADS dose and contact time and negative effects of solution pH and initial fluoride concentration were observed. The second phase included RSM in which analysis of variance (ANOVA) was applied to test the feasibility of the mathematical model. The F value 1.91, R² value 0.87, and P value 0.11 show significance of the proposed model. Results obtained from the experiment set for central composite design (CCD) were used to predict the ANN response. Reasonable acceptable values of regression for training, test, and validation (0.76, 0.93, and 0.37) represent the suitability of the model. The ANN predicted 22.1% fluoride removal, which was close to the actual value (20.1%) and was comparable with CCD prediction (25.0%). BET surface area of CADS was found to be 76.33 m²/g. FTIR was performed to recognize the functional groups available for fluoride binding while SEM and EDX were conducted to ensure the changes in adsorbent surface morphology. Regeneration of CADS was feasible using an alkali medium. This study shows that CADS can be used for fluoride removal from aqueous stream in an efficient way.

The present study was planned to explore the bioaccumulation potential of 23 plant species via bioaccumulation factor (BAf), metal accumulation index (MAI), translocation potential (Tf), and comprehensive bioconcentration index (CBCI) for seven heavy metals (cadmium, chromium, cobalt, copper, iron, manganese, and zinc). The studied plants, in the vicinity of ponds at Sahlon: site 1, Chahal Khurd: site 2, and Karnana: site 3 in Shaheed Bhagat Singh Nagar, Punjab (India), were Ageratum conyzoides (L.) L., Amaranthus spinosus L., Amaranthus viridis L., Brassica napus L., Cannabis sativa L., Dalbergia sissoo DC., Duranta repens L., Dysphania ambrosioides (L.) Mosyakin & Clemants, Ficus infectoria Roxb., Ficus palmata Forssk., Ficus religiosa L., Ipomoea carnea Jacq., Medicago polymorpha L., Melia azedarach L., Morus indica L., Malva rotundifolia L., Panicum virgatum L., Parthenium hysterophorus L., Dolichos lablab L., Ricinus communis L., Rumex dentatus L., Senna occidentalis (L.) Link, and Solanum nigrum L. BAf and Tf values showed high inter-site deviations for studied metals. MAI values were found to be more substantial in shoots as compared with that of roots of plants. Maximum CBCI values were observed for M. azedarach (0.626), M. indica (0.572), D. sissoo (0.497), and R. communis (0.474) for site 1; F. infectoria (0.629), R. communis (0.541), D. sissoo (0.483), F. palmata (0.457), and D. repens (0.448) for site 2; D. sissoo (0.681), F. religiosa (0.447), and R. communis (0.429) for site 3. Although, high bioaccumulation of individual metals was observed in herbs like C. sativa, M. polymorpha, and Amaranthus spp., cumulatively, trees were found to be the better bioaccumulators of heavy metals.