Occurrence and formation of disinfection by-products in the swimming pool environment： A critical review

Disinfection of water for human use is essential to protect against microbial disease;however, disinfection also leads to formation of disinfection by-products（DBPs）, some of which are of health concern. From a chemical perspective, swimming pools are a complex matrix, with continual addition of a wide range of natural and anthropogenic chemicals via filling waters, disinfectant addition, pharmaceuticals and personal care products and human body excretions. Natural organic matter, trace amounts of DBPs and chlorine or chloramines may be introduced by the filling water, which is commonly disinfected distributed drinking water. Chlorine and/or bromine is continually introduced via the addition of chemical disinfectants to the pool. Human body excretions（sweat, urine and saliva） and pharmaceuticals and personal care products（sunscreens, cosmetics, hair products and lotions） are introduced by swimmers. High addition of disinfectant leads to a high formation of DBPs from reaction of some of the chemicals with the disinfectant.Swimming pool air is also of concern as volatile DBPs partition into the air above the pool.The presence of bromine leads to the formation of a wide range of bromo-and bromo/chloro-DBPs, and Br-DBPs are more toxic than their chlorinated analogues. This is particularly important for seawater-filled pools or pools using a bromine-based disinfectant.This review summarises chemical contaminants and DBPs in swimming pool waters, as well as in the air above pools. Factors that have been found to affect DBP formation in pools are discussed. The impact of the swimming pool environment on human health is reviewed.

Variability scaling and capacity planning in Covid-19 pandemic

Capacity planning is a very important global challenge in the face of Covid-19 pandemic.In order to hedge against the fluctuations in the random demand and to take advantage of risk pooling effect,one needs to have a good understanding of the variabilities in the demand of resources.However,Covid-19 predictive models that are widely used in capacity planning typically often predict the mean values of the demands(often through the predictions of the mean values of the confirmed cases and deaths)in both the temporal and spatial dimensions.They seldom provide trustworthy prediction or estimation of demand variabilities,and therefore,are insufficient for proper capacity planning.Motivated by the literature on variability scaling in the areas of physics and biology,we discovered that in the Covid-19 pandemic,both the confirmed cases and deaths exhibit a common variability scaling law between the average of the demand μ and its standard deviationσ,that is,σ ∝ μ^(β),where the scaling parameterμis typically in the range of 0.65 to 1,and the scaling law exists in both the temporal and spatial dimensions.Based on the mechanism of contagious diseases,we further build a stylized network model to explain the variability scaling phenomena.We finally provide simple models that may be used for capacity planning in both temporal and spatial dimensions,with only the predicted mean demand values from typical Covid-19 predictive models and the standard deviations of the demands derived from the variability scaling law.