To increase the knowledge on the particulate matter of a wetland in Beijing, an experimental study on the concentration and composition of PM10 and PM2.5 was implemented in Beijing Olympic Forest Park from 2013 to 2014. This study analyzed the meteorological factors and deposition fluxes at different heights and in different periods in the wetlands. The results showed that the mean mass concentrations of PM10 and PM2.5 were the highest at 06:00–09:00 and the lowest at 15:00–18:00. And the annual concentration of PM10 and PM2.5 in the wetland followed the order of dry period (winter) > normal water period (spring and autumn) > wet period (summer), with the concentration in the dry period significantly higher than that in the normal water and wet periods. The chemical composition of PM2.5 in the wetlands included NH4+, K+, Na+, Mg2 +, SO42 −, NO3−, and Cl−, which respectively accounted for 12.7%, 1.0%, 0.8%, 0.7%, 46.6%, 33.2%, and 5.1% of the average annual composition. The concentration of PM10 and PM2.5 in the wetlands had a significant positive correlation with relative humidity, a negative correlation with wind speed, and an insignificant negative correlation with temperature and radiation. The daily average dry deposition amount of PM10 in the different periods followed the order of dry period > normal water period > wet period, and the daily average dry deposition amount of PM2.5 in the different periods was dry period > wet period > normal water period. 相似文献
Explosive-contaminated soil is harmful to people’s health and the local ecosystem. The acute toxicity of its extracting solution was tested by bacterial luminescence assay using three kinds of luminescent bacteria to characterize the toxicity of the soil. An orthogonal test L16 (45) was designed to optimize the soil extracting conditions. The optimum extracting conditions were obtained when the ultrasonic extraction time, ultrasonic extraction temperature, and the extraction repeat times were 6 h, 40 °C, and three, respectively. Fourier transform infrared spectroscopy (FTIR) results showed that the main components of the contaminated soil’s extracting solution were 2,4-dinitrotoluene-3-sulfonate (2,4-DNT-3-SO3−); 2,4-dinitrotoluene-5-sulfonate (2,4-DNT-5-SO3−); and 2,6-dinitrotoluene (2,6-DNT). Compared with Photobacterium phosphoreum and Vibrio fischeri, Vibrio qinghaiensis sp. Nov. is more suitable for assessing the soil extracting solution’s acute toxicity. Soil washing can remove most of the contaminants toxic to luminescent bacterium Vibrio qinghaiensis sp. Nov., suggesting that it may be a potential effective remediation method for explosive-contaminated soil.
The aim of the study was to determine the potential environmental contamination in a typical factory for recycling waste electrical and electronic equipment in Shanghai. Heavy metals (Cr, Ni, Cu, Zn, Cd, Pb) in the soil around the factory have been evaluated in this paper. Compared with the background value, the concentrations of six metals detected in all the samples were higher, which showed that toxic metals were released into soil around the factory. Compared with the Environmental Quality Standards for Soils, China grade III, all the six metals are under soil guidelines. The non-cancer risk in different directions from the factory was in the order of: the north > the west > the south > the east. For inhalation and ingestion, the non-cancer risk in the soil west of the factory was biggest. Nevertheless, the non-cancer risk in the soil north of the factory was the biggest for dermal contact. The trend of cancer risk was the west > the south > the north > the east. The non-cancer risk and the carcinogenic risk for Cr, Ni, and Cd were all below the limiting value. This study might provide a reference for the risk assessment involved in electronic waste management and recycling activities. 相似文献
The identification of disturbance thresholds is important for many aspects of aquatic resource management, including the establishment
of regulatory criteria and the identification of stream reference conditions. A number of quantitative or model-based approaches
can be used to identify disturbance thresholds, including nonparametric deviance reduction (NDR), piecewise regression (PR),
Bayesian changepoint (BCP), quantile piecewise constant (QPC), and quantile piecewise linear (QPL) approaches. These methods
differ in their assumptions regarding the nature of the disturbance-response variable relationship, which can make selecting
among the approaches difficult for those unfamiliar with the methods. We first provide an overview of each of the aforementioned
approaches for identifying disturbance thresholds, including the types of data for which the approaches are intended. We then
compare threshold estimates from each of these approaches to evaluate their robustness using both simulated and empirical
datasets. We found that most of the approaches were accurate in estimating thresholds for datasets with drastic changes in
responses variable at the disturbance threshold. Conversely, only the PR and QPL approaches performed well for datasets with
conditional mean or upper boundary changes in response variables at the disturbance threshold. The most robust threshold identification
approach appeared to be the QPL approach; this method provided relatively accurate threshold estimates for most of the evaluated
datasets. Because accuracy of disturbance threshold estimates can be affected by a number of factors, we recommend that several
steps be followed when attempting to identify disturbance thresholds. These steps include plotting and visually inspecting
the disturbance-response data, hypothesizing what mechanisms likely generate the observed pattern in the disturbance-response
data, and plotting the estimated threshold in relation to the disturbance-response data to ensure the appropriateness of the
threshold estimate. 相似文献