Artificial neural networks modeling ethanol oxidation reaction kinetics catalyzed by polyaniline-manganese ferrite supported platinum-ruthenium nanohybrid electrocatalyst

Chemical characterization and source attribution of organic pollutants in industrial wastewaters from a Chinese chemical industrial park

Accelerated urbanization and industrialization have led to an alarming increase in the generation of wastewater with complex chemical contents. Industrial wastewaters are often a primary source of water contamination. The chemical characterization of different industrial wastewater types is an essential task to interpret the chemical fingerprints of wastewater to identify pollution sources and develop efficient water treatment strategies. In this study, we conduct a non-target chemical analysis for the source characterization of different industrial wastewater samples collected from a chemical industrial park (CIP) located in southeast China. The chemical screening identified volatile and semi-volatile organic compounds that included dibutyl phthalate at a maximum concentration of 13.4 μg/L and phthalic anhydride at 35.9 μg/L. Persistent, mobile, and toxic (PMT) substances among the detected organic compounds were identified and prioritized as high-concern contaminants given their impact on drinking water resources. Moreover, a source analysis of the wastewater collected from the wastewater outlet station indicated that the dye production industry contributed the largest quantities of toxic contaminates (62.6%), and this result was consistent with the ordinary least squares and heatmap results. Thus, our study utilized a combined approach of a non-target chemical analysis, a pollution source identification method, and a PMT assessment of different industrial wastewater samples collected from the CIP. The results of the chemical fingerprints of different industrial wastewater types as well as the results of the PMT assessment benefit risk-based wastewater management and source reduction strategies.

Anthropogenic emissions from coal-water slurry combustion: Influence of component composition and registration methods

The flue gas composition is often measured using a combination of techniques that differ in terms of both physical operation principle and type of output. Gas analyzers, FTIR spectrometers, and mass spectrometers are the most popular tools used for this purpose. In this research, we study the composition of the flue gas from the combustion of fuel slurries and dry composite fuels based on industrial and agricultural waste. It has been established that the use of slurry fuels makes the anthropogenic emissions 2-4 times lower than from the combustion of coal slime. For example, the CO₂ emissions from the combustion of dry coal slime were 2.5-3.7 times higher than from the combustion of slurry fuels. In addition, the combustion of slurry fuels made it possible to cut down the nitrogen oxide emissions by 1.3-1.5 times and sulfur oxide emissions by 1.3-2.7 times. A comparison of the results obtained using different measurement techniques has shown that differences between the CO and CO₂ content in the combustion products measured by a gas analyzer and an FTIR spectrometer did not exceed 20%. The use of FTIR spectroscopy provided new knowledge on the concentrations of hydrocarbons from the combustion of fuels based on promising industrial wastes.