Water quality has recently emerged as one of the utmost severe ecological problems being faced by the developing countries all over the world, and Bangladesh is no exception. Both surface and groundwater sources contain different contaminants, which lead to numerous deaths due to water-borne diseases, particularly among children. This study presents one of the most comprehensive reviews on the current status of water quality in Bangladesh with a special emphasis on both conventional pollutants and emerging contaminants. Data show that urban rivers in Bangladesh are in a critical condition, especially Korotoa, Teesta, Rupsha, Pashur, and Padma. The Buriganga River and few locations in the Turag, Balu, Sitalakhya, and Karnaphuli rivers have dissolvable oxygen (DO) levels of almost zero. Many waterways contain traces of NO3, NO2, and PO4-3 pollutants. The majority of the rivers in Bangladesh also have Zn, Cu, Fe, Pb, Cd, Ni, Mn, As, and Cr concentrations that exceed the WHO permissible limits for safe drinking water, while their metal concentrations exceed the safety threshold for irrigation. Mercury poses the greatest hazard with 90.91% of the samples falling into the highest risk category. Mercury is followed by zinc 57.53% and copper 29.16% in terms of the dangers they pose to public health and the ecosystem. Results show that a considerable percentage of the population is at risk, being exposed to contaminated water. Despite hundreds of cryptosporidiosis cases reported, fecal contamination, i.e., Cryptosporidium, is totally ignored and need serious considerations to be regularly monitored in source water.

We explore how water pollution policy reforms in China could reduce industrial wastewater pollution with minimum adverse impact on GDP growth. We use a multi-sector dynamic Computable General Equilibrium (CGE) model, jointly developed by Harvard University and Tsinghua University, to examine the long-term impact of pollution taxes. A firm-level dataset of wastewater and COD discharge is compiled and aggregated to provide COD-intensities for 22 industrial sectors. We simulated the impact of 4 different sets of Pigovian taxes on the output of these industrial sectors, where the tax rate depends on the COD-output intensity. In the baseline low rate of COD tax, COD discharge is projected to rise from 36 million tons in 2018 to 48 million in 2030, while GDP grows at 6.9% per year. We find that raising the COD tax by 8 times will lower COD discharge by 1.6% by 2030, while a high 20-times tax will cut it by 4.0%. The most COD-intensive sectors—textile goods, apparel, and food products—have the biggest reduction in output and emissions. The additional tax revenue is recycled by cutting existing taxes, including taxes on profits, leading to higher investment. This shift from consumption to investment leads to a slightly higher GDP over time.