The main objective of a research program, whose output is presented here, has been to estimate “Ventilation Coefficients”, a critical parameter in determining air pollution concentration near the surface ground which signifies the ability for natural ventilation of an air shed in an urban or rural area. Relevant measured data from the city of Tehran has been used to calibrate and further demonstrate the validity of the mathematical model developed. Since most polluted mega cities require significant air pollution modeling activities, capable of providing relatively reliable outputs, calculating such highly important parameter is by far the most important outcome of this research. The Ventilation Coefficients have been estimated assuming normal adiabatic lapse rates and utilizing ten-year daily atmospheric radio-sound data. Mean Maximum Mixing Depth, Wind Speed at Mean Maximum Mixing Depth, and the Ventilation Coefficients have been computed and as a result it has been noted that despite the fact that Mean Maximum Mixing Depth peacks in June and Wind Speed at Mean Maximum Mixing Depth reaches its maximum in April, this has caused the Ventilation Coefficient to remain at its peack almost constant over April-June time span. It may also be observed for an urban area such as Tehran, the Ventilation Coefficient stands maximum in spring at 22329.17 m2/s and minimum in fall at 22329.17 m2/s.

Experimental investigations and observations indicate that water quality modeling is related to the formation of flows in the dam reservoirs. Correct estimation of dam reservoir flow, plunging point and plunging depth are very important for the dam reservoir sedimentation and water quality problem. Therefore, inflow riverwater into a dam is modeled in two dimensions through a reservoir with sloping bottom. The model is developed using nonlinear and unsteady continuity, momentum, energy and k-ε turbulence model equations. The equations of the model are solved based on the initial and boundary conditions of the dam reservoir flow for a range of bottom slopes. In addition to velocity, temperature and turbulence viscosity variation through the dam reservoir, the effects of density flow parameters such as plunging depths, plunging points, mixing rate are determined from the simulation results. The results of the present model are compared to the previous experimental works and the mathematical models.

Multivariate statistical techniques were applied for evaluation of Temporal/ spatial variations and interpretation of a large complex water-quality data set of Shiroud River that discharges to southern part of Caspian Sea, Iran. Totally 16 parameters of water quality were monitored during 12 months at 8 sites in mountainous, flat and estuary areas. Factor analysis (FA) results showed that the first factor explained 25.76% of the total variance [comprise of electrical conductivity (EC), total dissolved solids (TDS), total hardness, calcium ion and water temperature levels]. The second factor called water quality indicator factor explained 13.99% [comprise of silicate, dissolved oxygen (DO) and pH levels], and the third factor called phosphate pollutant factor explained 10.72% (comprise of orthophosphate and total phosphorus (TP)). Additional factors were affected by part of nutrient, flow rate and general water quality, each of them recorded variance less than 10%. Discriminate analysis (DA) gave the best results for both spatial and Temporal analysis. It has provided an important data reduction as it uses only four parameters (mean river depth, DO, NH4+, and EC). Thus, DA allowed a reduction in the dimensionality of the large data set, explaining a few indicator parameters responsible for large variations in water quality. The present study shows the usefulness of multivariate statistical techniques for analysis and interpretation of complex data sets, and identifies probable source components in order to explain the pollution of Shiroud River.

Introduction: Chattogram is known as the Bangladesh’ s commercial capital with its diversified industrial areas and seaport. This study aimed to assess the Particulate Matter (PM2. 5 and PM10) in relation to meteorological characteristics in Chattogram city from 2013-2018. Materials and methods: Monthly PM2. 5 and PM10 data were collected from the Continuous Air Monitoring Station (CAMS) in Chattogram City (Agrabad Point) which is operated by the Department of Environment (DoE) of Bangladesh under the Clean Air and Sustainable Environment (CASE) project. Results: This Study found the higher concentration of both PM2. 5 and PM10 occurred from December to February and it decreases from July-September and begins to increase from the month of October. The PM values seasonally varied being higher during the winter seasons and decreased in rainy seasons. The PM2. 5 mass was detected 50% of that of PM10 which is mostly from biomass burn and vehicles activities. Meteorological parameters such as rainfall and humidity had strong inverse relation with both PM2. 5 and PM10 over the years. Conclusion: The Study found the average annual concentration of PM2. 5 was 5-6 times higher and PM10 was 3 times higher than Bangladesh National Ambient Air Quality Standard (BNAAQS) in Chattogram city over this six year period. It can be concluded that the air pollution in Dhaka city is deteriorating rapidly and it is high time to implement the clean air act urgently to reduce such destruction.