Influence of input uncertainty on prediction of within-field pesticide leaching risks

Previous research has suggested that pesticide losses at the field scale can be dominated by a small proportion of the field area. The objective of this study was to investigate whether site-specific applications (i.e. avoiding high-risk areas) at the field scale can contribute to a reduction of pesticide leaching despite uncertainty in the underlying model-based leaching risk map. Using a meta-model of the dual-permeability model MACRO, the annual average pesticide leaching concentrations were estimated for 162 sample sites on a 47 ha field. The procedure was repeated for different scenarios describing different patterns of spatial variation of degradation half-lives and the partition coefficient to soil organic carbon. To account for interpolation uncertainty, maps of predicted pesticide leaching risk were produced by the method of sequential Gaussian simulation. The results of the case study show that larger reductions of predicted leaching were achieved by site-specific application than by that of a comparable uniform dose reduction. Hence, site-specific-applications may be a feasible method to reduce pesticide leaching at the field-scale providing that the model approach gives reasonable estimates of the spatial pattern of pesticide leaching.     

Validation of a diffusive sampler for NO2

A diffusive sampler for NO2, Willems badge, was validated in laboratory experiments and field tests. The collecting reagent for NO2 in the sampler is triethanolamine, and the analysis is based on a modified colorimetric method, the Saltzman method. The analysis was performed by a flow injection analysis (FIA) technique. The sampling rate for the sampler was determined to be 40.0 ml min-1. There was no effect of NO2 concentration or relative humidity on sampling rate, and the influence of sampling time was found to be small. The detection limit was 4 micrograms m-3 for a 24 h sample. The capacity is high enough to allow sampling of 150 micrograms m-3 for 7 days, which is twice the recommended Swedish short-term (24 h) guideline value as a 98-percentile over 6 months. In field tests, the sampler performed well, even at wind speeds higher than 2 m s-1, and at low temperatures. The overall uncertainty of the method was 24%. The sensitivity and capacity of the method also make it suitable for personal sampling for 2-8 h in working environments.     

Distribution of Np and Pu in Swedish lichen samples (Cladonia stellaris) contaminated by atmospheric fallout

The activity concentrations of (237)Np and the two Pu isotopes, (239)Pu and (240)Pu, were determined in lichen samples (Cladonia stellaris) contaminated by fallout from atmospheric nuclear test explosions and the Chernobyl accident. The samples were collected at 18 locations in Sweden, from north to south, between 1986 and 1988 and analysed with high-resolution inductively coupled plasma mass spectrometry (HR-ICP-MS) and alpha spectrometry. Data on the activity ratios (238)Pu/(239+240)Pu and (134)Cs/(137)Cs measured previously were also included in this study for comparison. The (237)Np activity concentration ranged from 0.08 +/- 0.01 to 2.08 +/- 0.17 MBq kg(-1), depending on the location of the sampling site and time of collection. The (239+240)Pu activity concentration ranged from 0.09 +/- 0.01 to 4.09 +/- 0.15 Bq kg(-1), with the (240)Pu/(239)Pu atomic ratio ranging between 0.16 +/- 0.01 and 0.44 +/- 0.03, the higher ratios indicating a combination of weapons test fallout and Chernobyl fallout. The (237)Np/(239)Pu atomic ratios ranged between 0.06 +/- 0.01 and 0.42 +/- 0.04, the lower ratios indicating combination of weapons test fallout and Chernobyl fallout. At a well-defined sampling site at Lake Rogen (62.32 degrees N, 12.38 degrees E), additional lichen samples were collected between 1987 and 1998 to study the distribution of Np and Pu in different layers. The concentrations of the two elements follow each other quite well in the profile.     

Design of optimized PI controller for 7-level inverter: a new control strategy

Photovoltaic (PV) system produces electricity that differs from variations in environmental parameters such as temperature and solar radiation. The PV network will operate at maximum power point (MPP) and deal with an ever-increasing energy demand, that changes from both load and weather conditions.” Moreover, energy storage devices could be a potential solution for improving the efficiency and performance of renewable energy sources (RES). This paper intends to establish a control design by an optimization-assisted PI controller for a 7-level inverter. Accordingly, the gains of PI controller are adjusted dynamically by FireFly Integrated-Sea Lion Optimization algorithm (FFI-SLnO) that integrates the concepts of both Sea Lion Optimization (SLnO) and FireFly algorithm (FF). The gains should be tuned such that the error among the reference signal and fault signal should be low and hence better dynamic performance can be obtained by the presented optimized PI controller. Finally, the performance of the proposed method is compared over other traditional models with respect to certain measures and its superiority is proved.