Nitrous oxide is a potent greenhouse gas, with a global warming potential 298 times greater than that of CO2. In agricultural soils, N2O emissions are influenced by a large number of environmental characteristics and crop management techniques that are not systematically reported in experiments. Random Forest (RF) is a machine learning method that can handle missing data and ranks input variables on the basis of their importance. We aimed to predict N2O emission on the basis of local information, to rank environmental and crop management variables according to their influence on N2O emission, and to compare the performances of RI: with several regression models. RF outperformed the regression models for predictive purposes, and this approach led to the identification of three important input variables: N fertilization, type of crop, and experiment duration. This method could be used in the future for prediction of N2O emissions from local information. (c) 2013 Elsevier Ltd. All rights reserved.

Little information exists on emission factors (EFs, quantities of pollutants emitted per unit of fuel consumed) for brick kilns in China, although brick kilns are important emission sources of many air pollutants, and 45% of the world's bricks are produced in China. In this study, EFs of carbon dioxide (CO2), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOx), particulate matters (PMs), black carbon (BC), organic carbon (OC), and polycyclic aromatic hydrocarbons (PAHs) for brick kilns were derived based on field measurements of a total of 18 brick kilns of major types in China. This was the first study to quantify EFs of both stack and fugitive sources based on a modified carbon balance method that was developed for this study. The EFs of most pollutants, especially the incomplete combustion products in fugitive emissions, were much higher than those for stack emissions, indicating a substantial underestimation of total emissions when leakage is not taken into consideration. This novel method can be applied to quantify emissions from other similar sources with both stack and fugitive emissions.

Lead (Pb) isotope has been extensively used to identify sources of Pb and apportion their contributions in the environment. Conventionally, isotope ratios are used to express Pb isotopic composition. However, the linear combination of Pb isotope ratios is not consistent with mass balance. Moreover, the graphical presentations based on Pb isotope ratios are always inconsistent when different Pb isotope ratios are used. In this study, we proposed to use fractional abundance to express Pb isotopic composition to achieve more accurate and reliable source apportionment. A new method (rotation-projection method) based on fractional abundance was developed in this research. The new method compared favorably to the isotopic ratio-based method and to another fractional abundance based method using default 204Pb value (0) (Walraven’s method). It allows to present four-dimensional (4-D) Pb isotope fractional abundance data in a 3-D plot. In the meantime, due to the low variation of the fractional abundance of 204Pb in the terrestrial ecosystem, the terrestrial Pb isotope fractional abundance data fell nearly on a plane, which further allows to plot the Pb isotope fractional abundance data on a two-dimensional diagram. Proper presentation of the isotopic composition data helps to achieve more accurate and reliable source identification and apportionment.

Diethylhexyl phthalate (DEHP) is considered to be an endocrine disruptor, which unlike other chemicals that have either non-specific (e.g., narcotics) or more generalized reactive modes of action, affect the Hypothalamic-pituitary-gonadal (HPG) axis and tend to have specific interactions with particular molecular targets within biochemical pathways. Responding to this challenge, a novel method for deriving predicted no-effect concentration (PNEC) and probabilistic ecological risk assessment (PERAs) for DEHP based on long-term exposure to potentially sensitive species with appropriate apical endpoints was development for protection of Chinese surface waters. PNECs based on potencies to cause lesions in reproductive tissues of fishes, which ranged from 0.04 to 0.20 μg DEHP L−1, were significantly less than those derived based on other endpoints or other taxa, such as invertebrates. An assessment of risks posed by DEHP to aquatic organisms in surface waters of China showed that 88.17% and 78.85% of surface waters in China were predicted to pose risks to reproductive fitness of fishes with thresholds of protection for aquatic organisms based on 5% (HC5) and 10% (HC10), respectively. Assessment of risks of effects based on effects mediated by the HPG-axis should consider effects on chronic, non-lethal endpoints for specific taxa, especially for reproductive fitness of fishes.

A new methodology has been developed for the determination of secondary alkane sulfonates (SAS), an anionic surfactant, in environmental matrices. Sediment and sludge samples were extracted using pressurized liquid extraction and sonication, whereas wastewater and surface water samples were processed using solid-phase extraction. Extraction recoveries were acceptable for both aqueous (78–120%) and solid samples (83–100%). Determination of SAS was carried out by high or ultra performance liquid chromatography – mass spectrometry using ion trap and time-of-flight detectors. The methodology was applied to samples from Guadalete River (SW Spain), where SAS concentrations below 1 μg L−1 were measured in surface water, and from 72 to 9737 μg kg−1 in sediments. Differential partitioning was observed for SAS homologues as those having a longer hydrocarbon chain which preferentially sorbed onto particulate matter. A preliminary environmental risk assessment also showed that SAS measured levels were not harmful to the aquatic community in the sampling area.

Compound contamination and toxicity interaction necessitate the development of models that have an insight into the combined toxicity of chemicals. In this paper, a novel and simple model dependent only on the mixture information (MIM), was developed. Firstly, the concentration–response data of seven groups of binary and multi-component (pseudo-binary) mixtures with different mixture ratios to Vibrio qinghaiensis sp.-Q67 were determined using the microplate toxicity analysis. Then, a desirable non-linear function was selected to fit the data. It was found that there are good linear correlations between the location parameter (α) and mixture ratio (p) of a component and between the steepness (β) and p. Based on the correlations, a mixture toxicity model independent of pure component toxicity profiles was built. The model can be used to accurately estimate the toxicities of the seven groups of mixtures, which greatly simplified the predictive procedure of the combined toxicity.

Despite numerous reviews suggesting that microbial biosensors could be used in many environmental applications, in reality they have failed to be used for which they were designed. In part this is because most of these sensors perform in an aqueous phase and a buffered medium, which is in contrast to the nature of genuine environmental systems. In this study, a range of non-exhaustive extraction techniques (NEETs) were assessed for (i) compatibility with a naphthalene responsive biosensor and (ii) correlation with naphthalene biodegradation. The NEETs removed a portion of the total soil naphthalene in the order of methanol > HPCD > βCD > water. To place the biosensor performance to NEETs in context, a biodegradation experiment was carried out using historically contaminated soils. By coupling the HPCD extraction with the biosensor, it was possible to assess the fraction of the naphthalene capable of undergoing microbial degradation in soil. Exposure of microbial biosensors to cyclodextrin solutions allows the assessment of the degradable fraction of contaminants in soil.

A field intercomparison experiment of the disjunct eddy covariance (DEC) and the conventional eddy covariance (EC) techniques was conducted over a grass field. The half-hourly water vapor fluxes measured by the DEC were within the estimated uncertainty from the fluxes measured by the EC. On the average there was a slight overestimation (<10%) of the fluxes measured by the DEC during the day and underestimation during the night as compared to the fluxes measured by the EC. As this bias does not appear in the simulated DEC measurements it is likely to be due to instrumental problems. The insensitivity of the quality of the fluxes measured by the DEC method to the deficiencies in the gas analysis shows the robustness of this new approach for measuring the surface-atmosphere exchange of trace gases. Results from the first field intercomparison between a new state-of-the-art trace gas flux measurement technique and the direct eddy covariance measurements are reported in this paper.

Recent EU legislation is directed to reverse the upward trends in the concentrations of agricultural pollutants in groundwater. However, uncertainty of the groundwater travel time towards the screens of the groundwater quality monitoring networks complicates the demonstration of trend reversal. We investigated whether trend reversal can be demonstrated by relating concentrations of pollutants in groundwater to the time of recharge, instead of the time of sampling. To do so, we used the travel time to monitoring screens in sandy agricultural areas in the Netherlands, determined by 3H/3He groundwater dating. We observed that concentrations of conservative pollutants increased in groundwater recharged before 1985 and decreased after 1990. Thereby, we demonstrated trend reversal of groundwater quality. From this research we concluded that 3H/3He dating can be used to facilitate (re)interpretation of existing groundwater quality data. The presented approach is widely applicable in areas with unconsolidated granular aquifers and large agricultural pressures on groundwater resources. Groundwater age dating reveals trends and trend reversal in groundwater quality.

Surface sediment in eutrophic lakes is both a destination and a habitat for overwintering cyanobacteria. The resuspension and recovery of viable, overwintering cyanobacteria from the surface sediment during warm spring weather is usually the primary stage of cyanobacterial blooms (CBs) in shallow eutrophic lakes. Therefore, the elimination of overwintering cyanobacteria in sediment is vital to control CBs. In the present study, sediment plow-tillage (PT) was introduced as an innovative technique for eliminating overwintering cyanobacteria in sediments from Lake Chaohu. Four depths of PT (2, 5, 10, and 15 cm) were tested during the 42-day experiment. The results showed that rapid cell death during the first 0–7 d after PT was accompanied by high oxygen uptake rates. The viable cells in deeper sediment died more quickly and at a higher rate after PT. A PT depth of >10 cm effectively eliminated viable cyanobacteria (with a removal rate of 82.8%) from the sediment and prevented their resuspension. The activity of the viable cyanobacteria also decreased quickly as cyanobacteria were eliminated. It appears that the dark, anoxic environment of the deeper sediment after PT was responsible for the elimination of viable cells. Although high release rates of nitrogen and phosphorus were found to accompany the dying and decomposition of cyanobacteria during days 0–7 of the experiment, greater depth of PT was found to decrease nutrient concentrations in the overlying water. In conclusion, we recommend sediment PT as a new technique for eliminating overwintering algae in sediments. However, the release of nutrients from the sediment and the in situ control of CBs in lakes after PT should be further studied.