Mathematical modeling of ammonia emission rate in newly constructed buildings
N.О. Barnova1,4, А.V. Meltser1, Y.V. Dadali1,2, I.S. Iakubova1, M.A. Аndreeva1,3
1North-Western State Medical University named after I.I. Mechnikov, 41 Kirochnaya Str., Saint-Petersburg, 191015, Russian Federation
2RMC “HOME OF PHARMACY”, 3-245 Zavodskaya Str., Vsevolozhsk district, Leningrad region, Kuzmolovo, 188663, Russian Federation
3Hygiene and Epidemiology Center of Saint-Petersburg and Leningrad region, 77 Volkovsky Ave., Saint-Petersburg, 192102, Russian Federation
4Branch of the Hygiene and Epidemiology Center of Saint-Petersburg and Leningrad region in Vsevolozhskii and Kirovskii districts, 77 Volkovsky Ave., Saint-Petersburg, 192102, Russian Federation
A rapid growth in monolithic residential construction over recent decades has created a problem associated with ammonia contamination inside newly constructed buildings. Absence of substantiated preventive actions aimed at minimizing ammonia emissions hinders commissioning of new residential buildings and may create an unfavorable sanitary-epidemiological situation with obvious olfactory-reflex and irritating effects on public health.
The aim of this study was to develop a scientifically grounded method to predict when ammonia concentrations emitted from concrete constructions would reach their permissible levels in air inside contaminated premises in newly constructed buildings.
Ammonia emissions were estimated based on data of laboratory tests that involved analyzing indoor air samples taken in Saint Petersburg and the Leningrad region. Indoor air was analyzed in 4 newly constructed residential buildings (165 premises, 57 test protocols, 893 air samples tested to identify ammonia in them). Relationships between changes in ammonia concentrations and ventilation time were obtained by using regression analysis (regression equation, least square method). To establish reproducibility of the results and a possibility to compare them, we tested variances for homogeneity by using Fisher criterion. Sampled populations were compared with Student’s t-test in case the data fitted to a normal distribution (Kolmogorov – Smirnov test, Shapiro – Wilks test). Critical significance was taken at 0.05 in all the statistical comparisons.
We have developed a method for predicting when ammonia concentrations that occurred in indoor air inside newly constructed buildings due to multi-day emissions from building materials would reach their permissible levels. The method involves multi-day measurements (y, mg/m3) of ammonia concentrations sequentially in each premise inside a newly constructed building on any day of measurements during the time period t; building up relationships between averaged ammonia concentrations (yav, mg/m3) and a time moment t; mathematical analysis of the obtained relationships by parameterization and statistical analysis of the obtained kinetic parameters.
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