Volatile compounds released by microalgae-water phase from Taihu Lake in China.

The spectrum of Volatile Organic Compounds (VOCs) released by the microalgae-water phase of Taihu Lake in China was examined, then release behaviors were studied using non-methane hydrocarbons (NMHC, including a few polar organics) to describe the total amount of the released VOCs. Coupled dynamic headspace sampling with on-line monitoring of methane and NMHC was used to reflect the quasi-realtime release behavior of methane and NMHC by the microalgae-water phase. Alkanes, alkenes, oxygenated VOCs (OVOCs) and volatile sulfide chemicals (VOSCs) were detected. Their relative contents over time varied markedly from the stationary to the apoptosis phase, with their release rates as described by NMHC estimated from 0.02 to 0.59 µgC/(h g). Methane was investigated simultaneously, and its release rate was found to be 0.05-3.96 µgC/(h g). The release rates of both NMHC and methane were found to relate to the culture phase of the microalgae.

[Statistical Characteristics of Urban Changzhou PM2.5 Based on k-means Analysis].

Statistical analysis methods was utilized to investigate the variations of monthly average concentrations of the six basic pollutants (SO2, NO2, CO, O3, PM2.5 and PM10) of six national standard monitoring sites from 2013 to 2014 in urban Changzhou. The results showed that, except for O3, SO2, NO2, CO, PM2.5 and PM10 concentrations were all high in winter and low in summer. The relationship between particulate matter and wind speed showed, with increasing wind speed, the concentration of PM2.5 reduced. However, the concentration variations of PM10 were complicated and when wind speed increased, its concentration started to go down and then elevated. Fast-cluster analysis (k-means) and the index of SWV & DIV were used to classify the six basic pollutants into four clusters, and then the relationship between gaseous pollutants and PM2.5in each cluster was emphatically discussed by statistical analysis method. Four clusters were assigned to fossil fuel combustion emissions (cluster1), O3 and secondary aerosols (cluster2), incomplete combustion emissions and regional haze (cluster3), urban city "background" (cluster4). Incomplete combustion cluster accounted for the smallest percentage of urban Changzhou and city "background" was cluster of urban Changzhou with the largest contribution. k-means analysis results also showed that PM2.5 had complex sources in urban Changzhou.