The removal of chlorophenolic compounds from kraft mill effluents bleached with chlorine (cBKME) or chlorine plus hemicellulases (bBKME) was studied in reactors of aerobic treatment lagoons. In these laboratory models, a stable microbial population removed biochemical oxygen demand at similar rates of the mill lagoon. Complete removal of nine chlorophenols and chloroguaiacols during microbial treatment of these effluents was detected by gas chromatography. Abiotic removal was only observed with 2,4-dichlorophenol and 2,4,5-trichlorophenol. There were no significant differences in degradative ability between microorganisms acclimated to grow in reactors fed with cBKME or bBKME. The latter had a lower content of adsorbable organic halogen and chlorophenols than cBKME. Microorganisms acclimated to cBKME or bBKME were only able to grow on phenol or guaiacol as sole carbon source. However, these microorganisms removed (0.1-0.5 mM) 4-chlorophenol, 2,4-dichlorophenol and 2,4-dichlorophenoxyacetate with BKME as primary carbon source. Under these conditions, 2,4,6- and 2,4,5-trichlorophenol, 4,5-dichloroguaiacol, 4,5,6-trichloroguaiacol and tetrachloroguaiacol were not removed. These results suggest that the microbial removal of bleaching chlorophenols and chloroguaiacols during aerobic treatment, probably takes place only because of their very low concentration (1-200 ppb) in BKME.

Considering the exponential growth of today’s industry and the wastewater results of its processes, it needs to have an optimal treatment system for such effluent waters to mitigate the environmental impact generated by its discharges and comply with the environmental regulatory standards that are progressively increasing their demand. This leads to the need to innovate in the control and management information systems of the systems responsible to treat these residual waters in search of improvement. This paper proposes the development of an intelligent system that uses the data from the process and makes a prediction of its behavior to provide support in decision making related to the operation of the wastewater treatment plant (WWTP). To carry out the development of this system, a multilayer perceptron neural network with 2 hidden layers and 22 neurons each is implemented, together with process variable analysis, time-series decomposition, correlation and autocorrelation techniques; it is possible to predict the chemical oxygen demand (COD) at the input of the bioreactor with a one-day window and a mean absolute percentage error (MAPE) of 10.8%, which places this work between the adequate ranges proposed in the literature.

NO2 ambient concentrations were measured in a coastal Caribbean city. Barranquilla is a Caribbean city located in the North of Colombia that has approximately 1.200.000 inhabitants and possesses a warm, humid climate. In order to obtain the concentration of the contaminant in an adequate resolution, 137 passive diffusion tubes from Gradko© were installed. Diffusion passive tubes prepared with 20% TEA/water were located at the roadside between 1 and 5 m from the kerb edge. The sampling period was two weeks, from 3/16/2019 to 3/30/2019. Samples were analyzed on the UV CARY1 spectrophotometer by Gradko©. Results showed an average of 19.92 ±11.50 µg/m 3 , with a maximum and minimum value of 70.27 and 0.57 µg/m 3 , respectively. Spatial NO2 correlation with low traffic load was higher than with maximum traffic. The expected results include analyzing the areas of the city with high concentrations of this pollutant that exceed the WHO guidelines in six (6) points. Overall, the multiregression analysis is a very effective method to enrich the understanding of NO2 distributions. It can provide scientific evidence for the relationship between NO2 and traffic, beneficial for developing the targeted policies and measures to reduce NO2 pollution levels in hot spots. This research may subsidize knowledge to serve as a tool for environmental and health authorities.

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In this work, the degradation of several environmental pollutants by Alcaligenes eutrophus JMP134 (pJP4) was studied. It has been reported that this strain grows on 2,4‐dichlorophenoxyacetate, 3‐chlorobenzoate, and phenol, and that it is resistant to Hg2+ toxicity. Except degradation of phenol, all these properties are encoded on pJP4. Although this bacterium was unable to grow on several chlorophenols or chloroguaiacols as sole carbon and energy source, it proliferated in 4‐chlorophenol, 2,4‐dichlorophenol, and 2,4,6‐trichlorophenol. Degradation of 2,4,6‐trichlorophenol (up to 0.4 mM) did not depend on the presence of pJP4, since the cured strain JMP222 also expressed this property. In chemostats fed with 2,4,6‐trichlorophenol (0.4 mM) or phenol (1 mM) plus 2,4,5‐trichlorophenol (0.05 mM), strain JMP134 was able to degrade 2,4,5‐trichlorophenol. On the other hand, strain JMP134 grew at higher levels of HgCl2 (0.1 mM) or merbromine (1.5 mM) in rich medium, but growth was not detected in minimal medium cultures, containing either chlorinated or nonchlorinated compounds. The ability of strain JMP134 to survive and degrade chlorphenols in the presence of pulp bleaching effluent was assessed in aerated batch cultures. This biodegradable organic matter‐and chlorophenol‐containing effluent allowed the proliferation of the strain JMP134. When 2,4‐dichlorophenoxyacetate or 2,4,6‐trichlorophenol was added, complete degradation of these compounds was detected. The degradation was not affected by the presence of indigenous microorganisms or the amount of degradable material. © 1996 by John Wiley & Sons, Inc.