Effects of Milk Yield, Feed Composition, and Feed Contamination with Aflatoxin B1 on the Aflatoxin M1 Concentration in Dairy Cows’ Milk Investigated Using Monte Carlo Simulation Modelling

This study investigated the presence of aflatoxin M1 (AfM1) in dairy cows’ milk, given predefined scenarios for milk production, compound feed (CF) contamination with aflatoxin B1 (AfB1), and inclusion rates of ingredients, using Monte Carlo simulation modelling. The model simulated a typical dairy farm in the Netherlands. Six different scenarios were considered, based on two lactation and three CF composition scenarios. AfB1 contamination of the CF was based on results from the Dutch national monitoring programme for AfB1 in feed materials from 2000 until 2010. Monitoring data from feed materials used in CF production for dairy cattle in the Netherlands were used. Additionally, AfB1 contamination data from an incident in maize in 2013 were used. In each scenario, five different transfer equations of AfB1 from feed to AfM1 in the milk were used, and 1000 iterations were run for each scenario. The results showed that under these six scenarios, the weekly farm concentration of AfM1 in milk was above the EC threshold in less than 1% of the iterations, with all five transfer equations considered. However, this increased substantially in weeks when concentrations from the contaminated maize batch were included, and up to 28.5% of the iterations exceeded the EC threshold. It was also observed that an increase in the milk production had a minimal effect on the exceedance of the AfM1 threshold due to an apparent dilution effect. Feeding regimes, including the composition of CF and feeding roughages of dairy cows, should be carefully considered based on the potential AfM1 contamination of the farm’s milk

Application of Bayesian Networks in the development of herbs and spices sampling monitoring system

Knowing which products and hazards to monitor along the food supply chain is crucial for ensuring food safety. In this study, we developed a model to predict which types of herbs and spices products and food safety hazards should preferentially be monitored at each level of the supply chain (suppliers, border inspection points, market and consumers). A Bayesian Network method was used to develop a model based on notifications reported in the Rapid Alert System for Food and Feed and the database of the Dutch national monitoring program for chemical contaminants in food and feed over the period 2005-2014. The model was constructed by randomly selecting ca. 80% of the 3126 data records and validated using the remaining ca. 20% of the records. Model validation showed that the prediction accuracy was higher than 85%. Results showed that the sampling plan is closely related to the place where the products are checked along the supply chain, the products and the country of origin. Our approach of integrating different data sources and considering the entire supply chain can support industry and authorities at border inspection points and at all control points along the herbs and spices supply chain in setting priorities for their monitoring program

Historical emissions of octachlorodibenzodioxin in a watershed in Queensland, Australia: estimation from field data and an environmental fate model

An octachlorodibenzodioxin (OCDD)-dominated contamination is present along the coast of Queensland, Australia. Several findings indicate that this contamination originates from pesticide use, although due to limited information on OCDD levels in the pesticides used, estimating past and current emissions of OCDD solely from pesticide use data is unfeasible. We used all the qualitative and quantitative information available on OCDD in pesticides together with a previously validated chemical fate model for a catchment in the Queensland Wet Tropics to back-calculate the emissions of OCDD from measured soil concentrations. We estimate that under different emission scenarios an average of 2,500 kg of OCDD was emitted within the modelled 1,685 km(2) (Tully river) catchment between 1950 and 2010. Because this catchment represents only approximately 0.85% of the whole coast of Queensland under a similar contamination, the total amount of OCDD released in this region is considerably larger. For all emission scenarios, we could show that the OCDD currently present in agricultural soil is a result of historical emissions, and current-day emissions are less important in comparison to past emissions. Overall 18% was lost by degradation and 62% was buried below the agricultural surface soil, as a result of facilitated transport. (C) 2014 Elsevier B.V. All rights reserved

Describing the environmental fate of diuron in a tropical river catchment

The use of the herbicide diuron on sugarcane fields along the river catchments of the Great Barrier Reef (GBR) in Australia is an issue of concern due to high levels of diuron reported in the GBR lagoon, and has recently led to a restriction on the use of diuron during the 2011/12 wet season. An important question in this context is how much diuron is mobilised from the agricultural area by strong rainfall and floods in the wet season and transferred to the GBR lagoon. We have set up a multimedia chemical fate model for a tropical catchment to describe the fate of diuron within the Tully River catchment, Queensland, Australia. The model includes highly variable rainfall based on meteorological data from the Tully River catchment and a flood water compartment on top of the agricultural soil that is present during times for which floods were reported. The model is driven by diuron application data estimated for the Tully River catchment and is solved for time-dependent diuron concentrations in agricultural soil and seawater. Model results show that on average 25% of the diuron applied every year is transferred to the GBR lagoon with rainwater and flood water runoff. Diuron concentrations estimated for the seawater range from 0.1 ng/L to 12 ng/L and are in good agreement with concentrations measured in the GBR lagoon. The uncertainty of the diuron concentrations estimated for seawater is approximately a factor of two and mainly derives from uncertainty in the diuron degradation half-life in soil, properties of the soil compartment such as organic matter content, and the speed of the seawater current removing diuron dissolved in seawater from the seawater compartment of the model. (C) 2012 Elsevier B.V. All rights reserved

Environmental lead exposure risks associated with children's outdoor playgrounds

This study examines exposure risks associated with lead smelter emissions at children's public playgrounds in Port Pirie, South Australia. Lead and other metal values were measured in air, soil, surface dust and on pre- and post-play hand wipes. Playgrounds closest to the smelter were significantly more lead contaminated compared to those further away (t(27.545) = 3.76; p =.001). Port Pirie post-play hand wipes contained significantly higher lead loadings (maximum hand lead value of 49,432 μg/m²) than pre-play hand wipes (t(27) = 3.57, p =.001). A 1% increase in air lead (μg/m³) was related to a 0.713% increase in lead dust on play surfaces (95% CI, 0.253-1.174), and a 0.612% increase in post-play wipe lead (95% CI, 0.257-0.970). Contaminated dust from smelter emissions is determined as the source and cause of childhood lead poisoning at a rate of approximately one child every third day.8 page(s

Spatial variability of herbicide mobilisation and transport at catchment scale: insights from a field experiment

During rain events, herbicides can be transported from their point of application to surface waters, where they may harm aquatic organisms. Since the spatial pattern of mobilisation and transport is heterogeneous, the contributions of different fields to the herbicide load in the stream may vary considerably within one catchment. Therefore, the prediction of contributing areas could help to target mitigation measures efficiently to those locations where they reduce herbicide pollution the most. Such spatial predictions require sufficient insight into the underlying transport processes. To improve the understanding of the process chain of herbicide mobilisation on the field and the subsequent transport through the catchment to the stream, we performed a controlled herbicide application on corn fields in a small agricultural catchment (ca. 1 km2) with intensive crop production in the Swiss Plateau. Water samples were collected at different locations in the catchment (overland flow, tile drains and open channel) for two months after application in 2009, with a high temporal resolution during rain events. We also analysed soil samples from the experimental fields and measured discharge, groundwater level, soil moisture and the occurrence of overland flow at several locations. Several rain events with varying intensities and magnitudes occurred during the study period. Overland flow and erosion were frequently observed in the entire catchment. Infiltration excess and saturation excess overland flow were both observed. However, the main herbicide loss event was dominated by infiltration excess. Despite the frequent and wide-spread occurrence of overland flow, most of this water did not reach the channel directly, but was retained in small depressions in the catchment. From there, it reached the stream via macropores and tile drains. Manholes of the drainage system and storm drains for road and farmyard runoff acted as additional shortcuts to the stream. Although fast flow processes such as overland and macropore flow reduce the influence of the herbicide's chemical properties on transport due to short travel times, sorption properties influenced the herbicide transfer from ponding overland flow to tile drains (macropore flow). However, no influence of sorption was observed during the mobilisation of the herbicides from soil to overland flow. These observations on the role of herbicide properties contradict previous findings to some degree. Furthermore, they demonstrate that valuable insight can be gained by making spatially detailed observations along the flow paths.ISSN:1027-5606ISSN:1607-793

Are ready biodegradation tests effective screens for non-persistence in all environmental compartments?

Abstract Background Persistence assessment is a cornerstone of chemical hazard and risk assessment in numerous regulatory frameworks, as the longevity of a substance in the environment relates to exposure and ultimately the risk it poses. A chemical that is readily biodegradable is commonly assumed to undergo rapid and ultimate biodegradation under most environmental conditions. Ready biodegradability tests (RBT), such as the OECD 301 test series, are used to quickly screen out non-Persistent substances and focus regulatory scrutiny on the most hazardous substances. The stringency of the RBT as a screen for all environmental compartments is paramount to ensure that there are no readily biodegradable yet Persistent substances. To assess this stringency in practice, we here describe a systematic comparison of substances with both RBT data and biodegradation simulation test data for soil, sediment, or water compartments to see whether there are any substances which are readily biodegradable yet meet EU REACH regulatory Persistence criteria in any specific environmental compartment. Results A rough assembly of data extracted from the ECHA database showed that, out of 263 substances with both RBT and simulation test data, there were 19 substances that were readily biodegradable but Persistent (based on the most conservative result and after a temperature adjustment to the half-life). However, many of the underpinning simulation study information were either not high-quality guideline studies or the substances were UVCBs. To more accurately compare the RBT and simulation testing outcomes, quality criteria on the RBT and simulation tests were applied, which limited the data set to about one-third. Conclusions When examining quality-screened, temperature-adjusted simulation testing half-lives for readily biodegradable substances, there were no readily biodegradable substances that were Persistent. A side-by-side comparison of the available data supports the stringency and effectiveness of RBTs to identify non-Persistent chemicals