The main objective of this study is to assess the impacts of cooking and indoor air quality (IAQ) in the southwestern region of Bangladesh. Here we report and compare the IAQ in considering a total of eight kitchens and living rooms of four selected households (HHs) in Jashore city and suburb area, the southwest district of Bangladesh. Air quality parameters, such as particulate matter (PM_2.5) and volatile organic compounds (VOC), were assessed continuously for 24 h. In addition, Carbon dioxide (CO₂) was evaluated in different phases during the study period. PM_2.5, VOC, and CO₂ levels were ranged from 18.52 to 207 μg/m³, 7.95-35.66 ppm, and 1061-2459 mg/m³, respectively, in the indoor cooking HHs. Conversely, while the average concentration was found between 20.63 and 23.72 μg/m³ PM_2.5, 11.18-12.36 ppm VOC, and 1097-1747 mg/m³ CO₂ in the outdoor cooking HHs. A significant increase in CO₂ due to kitchen activities (cooking, frying, boiling) was observed that ranged between 5 and 77% compared to the background level. The calculated range of toxicity potential (TP) values was between 0.8 and 8.3 for PM_2.5 in the HHs. In most of the observations, PM_2.5, VOC, and CO₂ exceed the standard values. The study reports that well ventilation systems and clean fuel use significantly reduce the indoor air contaminants level. Our study offers new insights about the IAQ of the southwest region of Bangladesh, particularly for suburbs and urban setups, and provides a background for further study, and decision-making. It will serve as a reference for the formulation and implementation of policies to improve air quality.

Koyra (Khulna District) is the coastal Upazila of Bangladesh and is very susceptible to salinity intrusion. The surface and shallow tube well water in the Upazila is naturally saline. The quality of subterranean tube well water in the deliberate area is hardly presented for different Unions of Koyra. Dakshin Bedkashi Union of Koyra is very saline prone. Therefore, the groundwater chemistry of Dakshin Bedkashi Union was determined to legalize if the groundwater is fit for drinking and irrigation or not. Spatially dispersed 30 water samples were collected from the deep aquifer (550 to 700 feet depth) in December, 2016 and analyzed for physico-chemical properties. The outcomes were compared with WHO, USEPA and BBS drinking water quality standard and with FAO standard for irrigation purpose. The pH varied from 6.73 to 8.33, indicating that the water samples were within the WHO drinking water quality standard. The TDS showed a long range variation (230.5 to 2052.0 ppm) with an average of 841.23 ppm, of which 33% of water sources exceeded BBS standard value. The mean value of salinity was 0.65 (±0.43) ppt and EC was 1,400.9 (±904.18) µS cm-1. The loads of key ions were ranked as Na+> Ca2+> Mg2+> K+ and HCO3-> Cl-> SO42-> NO3-> PO4-. The Piper diagram demonstrated that the existing hydro-chemical facies of groundwater were Na+-Cl--HCO3- and Na+-Ca2+-HCO3- type. The Gibbs diagram illustrated that the chemical arrangement of groundwater is mainly misrepresented by rock weathering. Silicate weathering was the profuse process along study area. The Wilcox diagram proved that the greater water sources were allowable to suspicious for irrigation. The core component analysis ensured that rock suspension and sea water intrusion was the primary source of ions in groundwater. The controlling factors of groundwater chemistry were typically related to geologic factors, while the anthropogenic factors have not any momentous effects.

Model spin-up is an adjustment process where its internal stores move from an initial state of unusual conditions to one of equilibrium. Model outputs during this spin-up process are often unrealistic and misleading. This study investigates some primary factors affecting spin-up time using the Xinanjiang model for 22 river basins throughout the United States. A 10-year recursive simulation with three data sets indicates that time required for model equilibrium is not only a function of initial conditions, but also is affected by input data sets (precipitation and evaporation). The model requires less time to be equilibrated under wetter initial conditions (lowest under saturated initial condition). Moreover, model spin-up time shows distinct variations with the dryness of the input data sets. Analysis suggests that wet basins (ratio of evaporation over precipitation <0.9) require less time (55 days) for model equilibrium in comparison to that of dry basins (298 days). The spin-up time displayed an exponential relationship with the basin aridity index (r² = 0.85). This relationship could provide a way to predict the maximum model spin-up time using the precipitation and evaporation information only. Predicting maximum model spin-up time based on this relationship could be valuable to reduce uncertainty, particularly under data scarce situations.