Water is one of the most crucial substances for life. In order to maintain their public health, each and every country has defined standards of drinking water quality, beyond which the water is considered harmful for human health. The current study compares physical, chemical, and biological standards of drinking water quality for the USA, EU, Japan, India, and Bangladesh, considering 4 physical parameters (namely, color, odor, taste, and turbidity), 35 chemical parameters (such as Calcium (Ca), Magnesium (Mg), Phosphate (PO43-), Sodium (Na), Phenolic compounds, Nitrite (NO2-), Arsenic (As), Aluminum (Al), etc.) and 2 biological parameters (i.e., Coliform (Fecal) and Coliform (Total)). The data has been collected from several secondary sources and since processes of data collection for water quality differ from one another, this aspect has been ignored. No variation has been found in biological water quality standards along with physical quality standards of the considered regions. In order to find out the differences in chemical parameters, standard ANOVA and pair-wise F-test have been conducted. There was no disparity among chemical parameters in ANOVA test. Moreover, thanks to the few excessive values of the standards (as in case of Bangladesh), the COD value is 4 mg/L, whereas in other countries this parameter is much less. However, the chemical parameters of water quality standards in Bangladesh vary significantly from other countries. Besides, there has been no variation among the standards of other countries, even though they are located in different continents. Most interestingly, despite being neighbors, Bangladesh and India differ significantly in this regard.

This article comments on the current reality of particulate matter (PM) concentrations breathed by commuters on subway train platforms and considers what can be done to improve air quality underground. We propose the introduction of a targeted, color-coded approach to the problem, based on the methodology of the World Health Organisation and designed to encourage transport authorities to aim for progressive PM reductions. The method defines thresholds that cascade down through bands of decreasing PM concentrations towards the ideal WHO Air Quality Guideline of PM₂.₅ annual mean level of 10 μg m⁻³, where negative health effects of long term particle inhalation are minimal.

Traffic emissions are a complex and variable cocktail of toxic chemicals. They are the major source of atmospheric pollution in the parts of cities where people live, commute and work. Reducing exposure requires information about the distribution and nature of emissions. Spatially and temporally detailed data are required, because both the rate of production and the composition of emissions vary significantly with time of day and with local changes in wind, traffic composition and flow. Increasing computer processing power means that models can accept highly detailed inputs of fleet, fuels and road networks. The state of the science models can simulate the behaviour and emissions of all the individual vehicles on a road network, with resolution of a second and tens of metres. The chemistry of the simulated emissions is also highly resolved, due to consideration of multiple engine processes, fuel evaporation and tyre wear. Good results can be achieved with both commercially available and open source models. The extent of a simulation is usually limited by processing capacity; the accuracy by the quality of traffic data. Recent studies have generated real time, detailed emissions data by using inputs from novel traffic sensing technologies and data from intelligent traffic systems (ITS). Increasingly, detailed pollution data is being combined with spatially resolved demographic or epidemiological data for targeted risk analyses.