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This study emphasizes the possible utilization of carbonized microplastic particles (CMPs) prepared from polyethylene terephthalate (PET) plastic bottle waste for dye adsorption. Methylene blue (MB) and methyl orange (MO) are adsorbed in a batch experiment to determine the effects of various experimental factors, including contact time (1–210 min), solution pH (3–11), adsorbent dosage (1–20 g/L), temperature (25–600 °C), and initial dye concentration (5–70 mg/L). The variance analysis (ANOVA) results of response surface methodology (RSM) indicated that the second-order model was statistically significant and had a high coefficient value (R2 = 0.99 for MO and R2 = 0.92 for MB). The RSM results stated that solution pH and adsorbent dose significantly influence MO and MB dyes removal, where the maximum adsorption removal was 99.95 and 99.04% for MO and MB dye at high acidic (pH 3) and alkaline (pH 11) conditions, respectively, with high adsorbent doses. Furthermore, trained neural networks demonstrated a strong correlation between the experimental and projected colour removal efficiencies. The adsorption data for MO and MB were well explained by pseudo-second-order kinetics and Langmuir isotherm models. A thermodynamic study shows that dyes adsorptions are favourable, exothermic, and spontaneous. Finally, real wastewater and desorption studies indicate the effectiveness and environmentally friendly properties of CMPs.

Farmers in the south-west coastal Bangladesh are frequently affected by climate change due to their proximity to the Bay of Bengal and heavy reliance on agriculture for their livelihoods. In this case, farmers need to know the best implementation methods (adaptation strategies) to reduce crop losses in a changing climate. The present research evaluated the perceptions of farmers to climate change and determine the socio-economic factors which influence the farmers in choosing the right adaptation decisions. Data were collected through close-ended and open-ended structured questionnaire from 52 coastal households and analyzed through descriptive statistics and logistic regression using SPSS V.16. Results revealed that almost all farmers perceived increasing temperature and changes in rainfall patterns over the last 15 years. In response to a changing climate, farmers adopted 13 adaptation strategies where irrigation ranked the first and crop insurance was the last. The logit analysis suggests that household age, education, family income, family member, farm size, farming experience, organizational participations, and training received have a significant influence on farmer’s adaptation choices. Despite various support and technological interventions being available, changing weather, natural disaster pattern, lower income, and lack of credit facilities ranked as the highest problems farmers encountered during adaptation. This study helps to identify important household characteristics that can be applied in the future to formulate and implement a successful adaptation policy. Finally, this study recommends that effective training and early warning systems and provision of credit and market access facilities are necessary to enhance farmer’s resilience to climate change.