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We present version 3 (V3) of the Cloud_cci Along-Track Scanning Radiometer (ATSR) and Advanced ATSR (AATSR) data set. The data set was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) programme. The cloud properties were retrieved from the second ATSR (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the AATSR on board Envisat, which spanned 2002–2012. The data are comprised of a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius, and optical thickness, alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top- and bottom-of-atmosphere shortwave and longwave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with co-located CALIPSO data. The cloud masking has improved significantly, particularly in its ability to detect clear pixels. The Kuiper Skill score has increased from 0.49 to 0.66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulus cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments. The correlation with MAC-LWP increased from 0.4 to over 0.8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth's Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new data set is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol–cloud interactions, and providing contextual information for co-located ATSR-2/AATSR surface temperature and aerosol products. The following new digital identifier has been issued for the Cloud_cci ATSR-2/AATSRv3 data set: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 (Poulsen et al., 2019).

DNA strand breaks are a common form of DNA damage that can contribute to chromosomal instability or gene mutations. Such strand breaks may be caused by exposure to heavy metals. The aim of this study was to assess the level of DNA strand breaks caused by µm-scale solid particles of known chemical composition with elevated heavy metals/metalloids, notably arsenic, using an in vitro cell-free DNA plasmid scission assay. These samples were incubated with and without H2O2 to see whether damage occurs directly or indirectly through the Fenton reaction. Levels of DNA damage in the absence of H2O2 were 2O2, all samples showed higher levels of damage ranging from 10 to 100% suggesting that damage was being incurred through the Fenton reaction. Using bivariate correlation analysis and multiple linear regression, manganese oxide (MnO), sulphur (S), copper (Cu), and zinc (Zn) concentrations in the particulates were found to be the most significant predictors of DNA damage. The mechanism of this DNA damage formation has yet to be thoroughly investigated but is hypothesised to be due to reactive oxygen species formation. Further work is required to assess the extent of contribution of reactive oxygen species to this DNA damage, but this study highlights the potential role of chemistry and/or mineralogy to the extent and/or nature of DNA damage caused by particulates.

Promutagenic O6-alkylguanine adducts in DNA are repaired in humans by O6-methylguanine-DNA-methyltransferase (MGMT) in an irreversible reaction. Here we describe the synthesis of a phosphoramidite that allows the preparation of oligodeoxyribonucleotides (ODNs) containing a novel tricyclic thio analogue of O6-methylguanine in which the third ring bridges the 6-thio group and C7 of a 7-deazapurine. These ODNs are very poor substrates for MGMT and poorly recognised by the alkyltransferase-like protein, Atl1. Examination of the active sites of both MGMT and Atl1 suggest large steric clashes hindering binding of the analogue. Such analogues, if mutagenic, are likely to be highly toxic.

Paraoxonase 1 (PON1) is a high-density lipoprotein (HDL)-associated enzyme that by hydrolysing exogenous and endogenous substrates can provide protection against substrate induced toxicity. To investigate the extent to which PON1 provides protection against lactone induced DNA damage, DNA damage was measured in HepG2 cells using the neutral Comet assay following lactone treatment in the presence and absence of exogenous recombinant PON1 (rPON1). Low dose lactones (10 mM) caused little or no damage while high doses (100 mM) induced DNA damage in the following order of potency: α-angelica lactone > γ-butyrolactone ~ γ-hexalactone > γ-heptalactone ~ γ-octaclactone ~ γ-furanone ~ γ-valerolactone > γ-decalactone. Co-incubation of 100 mM lactone with rPON1, resulted in almost all cells showing extensive DNA damage, particularly with those lactones that decreased rPON1 activity by > 25%. In contrast, with the lactones that are poor rPON1 subtrates (γ-decalactone and γ-furanone), rPON1 did not increase DNA damage. DNA damage induced by a 1 h co-treatment with 10 mM α-angelica lactone and rPON1 was reduced when cells when incubated for a further 4 h in fresh medium suggesting break formation was due to induced DNA damage rather than apoptosis. Preincubation (1–6 h) of α-angelica lactone with rPON1 in the absence of cells, decreased cellular DNA damage by around 40% in comparison to cells treated without preincubation. These results suggest that in addition to its well-recognised detoxification effects, PON1 can increase genotoxicity potentially by hydrolysing certain lactones to reactive intermediates that increase DNA damage via the formation of DNA adducts.

The most widely used satellite products are averages of data onto a regular spatiotemporal grid, known as Level 3 data. Some atmospheric variables can vary rapidly in response to changing conditions. Over the scales of Level 3 averaging, the combination of observations across different conditions may result in data that is not normally distributed, such that a simple mean is not representative. The problem is illustrated by the distribution of aerosol optical depth from different sensors and algorithms. A simple statistical technique is proposed to better convey the diversity of satellite observations to users whereby a multimodal log-normal distribution is fit to the distribution of data observed within each grid cell. Allowing multiple modes within each cell is shown to improve the agreement between satellite products by highlighting regions of significant variability and isolating systematic differences between instruments.

Sperm DNA contains a range of DNA base damage that can arise, in part, from exposure to methylating agents. However, the effects are not fully characterized and so the aim of this study was to investigate associations between semen quality and the levels of N7-methyldeoxyguanosine (N7-MedG), a marker of exposure to methylating agents, and other markers of DNA damage and DNA methylation. Sperm samples were collected from 105 men attending an assisted reproduction clinic as part of a couple undergoing treatment for infertility and semen quality assessed manually according to WHO guidelines. Semen levels of N7-MedG, quantified by immunoslotblot, were significantly higher in men with sperm concentration 6/ml (p ≤ 0.01), semen volume DAZL but no other marker of global or gene-specific DNA methylation. Results support the hypothesis that the known toxic and DNA damaging properties of alkylating agent exposure may have direct deleterious consequences on semen quality.

Earth system models enable a broad range of climate interactions that physical climate models are unable to simulate. However, the extent to which adding Earth system components changes or improves the simulation of the physical climate is not well understood. Here we present a broad multivariate evaluation of the North Atlantic climate system in historical simulations of the UK Earth System Model (UKESM1) performed for CMIP6. In particular, we focus on the mean state and the decadal time scale evolution of important variables that span the North Atlantic climate system. In general, UKESM1 performs well and realistically simulates many aspects of the North Atlantic climate system. Like the physical version of the model, we find that changes in external forcing, and particularly aerosol forcing, are an important driver of multidecadal change in UKESM1, especially for Atlantic Multidecadal Variability and the Atlantic Meridional Overturning Circulation. However, many of the shortcomings identified are similar to common biases found in physical climate models, including the physical climate model that underpins UKESM1. For example, the summer jet is too weak and too far poleward; decadal variability in the winter jet is underestimated; intraseasonal stratospheric polar vortex variability is poorly represented; and Arctic sea ice is too thick. Forced shortwave changes may be also too strong in UKESM1, which, given the important role of historical aerosol forcing in shaping the evolution of the North Atlantic in UKESM1, motivates further investigation. Therefore, physical model development, alongside Earth system development, remains crucial in order to improve climate simulations.

BackgroundExposure to cleaning and disinfection products has been associated with respiratory disorders such as asthma in cleaning and healthcare workers. Safety data sheets (SDSs) provide information on hazardous chemicals that are present in products to help users with risk assessment and implement appropriate control measures. However, they have potential limitations in identifying respiratory hazards due to a lack of regulatory test methods for respiratory sensitisation and irritation of chemicals.MethodsSDSs were first used to identify chemicals on the database as respiratory sensitisers and irritants. A quantitative structure–activity relationship (QSAR) model and an asthmagen list established by the Association of Occupational and Environmental Clinics (AOEC) were used to identify potential respiratory sensitisers and irritants (by the AOEC list only) in the cleaning and disinfection products.ResultsFrom a total of 459 cleaning and disinfection products used in healthcare organisations across England and Wales, 35 respiratory sensitisers not labelled as such on the SDS were identified by QSAR or AOEC. Only 2% of cleaning and disinfection products contained at least one respiratory sensitiser as identified by their SDSs; this was increased to 37.7% of products when the QSAR or the AOEC list was used.ConclusionsA significantly higher proportion of cleaning products contain respiratory hazardous chemicals, particularly respiratory sensitisers than would be expected from the information provided by SDSs alone. Cleaners and healthcare workers may, therefore, be insufficiently protected.

Promutagenic

Background\ud \ud Few potentially modifiable risk factors of male infertility have been identified, and while different diets and food groups have been associated with male infertility, evidence linking dietary factors including phytoestrogens and semen quality is limited and contradictory.\ud \ud \ud \ud Objectives\ud \ud To study the associations between phytoestrogen intake and other dietary factors and semen quality.\ud \ud \ud \ud Materials and Methods\ud \ud A case‐referent study was undertaken of the male partners, of couples attempting conception with unprotected intercourse for 12 months or more without success, recruited from 14 UK assisted reproduction clinics. A total of 1907 participants completed occupational, lifestyle and dietary questionnaires before semen quality (concentration, motility and morphology) were assessed. Food intake was estimated by a 65‐item food frequency questionnaire (FFQ) covering the 12 months prior to recruitment. Analyses of dietary risk factors for low motile sperm concentration (MSC: 3 times/wk.\ud \ud \ud \ud Discussion\ud \ud In this case‐referent study of men attending an infertility clinic for fertility diagnosis, we have identified that low MSC is inversely associated with daidzein intake. In contrast, daidzein intake was not associated with PM but eating red milk and drinking whole milk were protective.\ud \ud \ud \ud Conclusions\ud \ud Dietary factors associated with semen quality were identified, suggesting that male fertility might be improved by dietary changes.

Background: Many studies have demonstrated that lifestyle factors can affect sperm quality and fertility. Sperm Telomere Length (STL) has been reported as potential biomarker or sperm quality. However, no studies have investigated the how lifestyle factors can effect STL and associated clinical outcomes.Objectives: The purpose of this manuscript is to investigate any association between STL with lifestyle factors, semen parameters and clinical outcomes. Materials and methods: Sperm Telomere Length was measured using real-time PCR in normozoospermic male partners (n = 66) of couples undergoing ART treatment. Each participant also completed a detailed questionnaire about general lifestyle. Linear regression univariate and ANCOVA analyses were performed to respectively determine correlations between STL and study parameters or identify statistically significant differences in STL while controlling for age, BMI and other factors. Results: Using a linear regression model, STL is positively correlated with in vitro fertilisation success (n = 65, r = 0.37, p = 0.004) but not with embryo cleavage rates and post-implantation clinical outcomes including gestational age-adjusted birth weight. No associations were observed between STL and sperm count, concentration or progressive motility. We further found that STL did not associate age, BMI, health or lifestyle factors. Discussion: In somatic cells - The rate of telomere shortening is influenced by a number of lifestyle factors such as: smoking, diet and occupation. However, little is known about how lifestyle factors affect STL and subsequently reproductive outcome. Out data suggest that STL might have an important role mechanistically for fertilisation rate regardless of sperm parameters and lifestyle factors Conclusion: The results of this study demonstrate that STL is associated with in vitro fertilization rates, but not with semen parameters nor lifestyle factors. Further investigations are warranted to identify the potential variation of STL overtime to clarify its significance as a potential biomarker in ART

We present version 3 (V3) of the Cloud_cci ATSR-2/AATSR dataset. The dataset was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) program. The cloud properties were retrieved from the second Along- Track Scanning Radiometer (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the Advanced ATSR (AATSR) on board Envisat, which spanned 2002–2012. The data comprises a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius and optical thickness alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top and bottom-of-atmosphere short- and long-wave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with collocated CALIPSO data. The cloud masking has improved significantly, particularly the ability to detect clear pixels The Kuiper Skill score has increased from .49 to .66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulous cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments, the Correlation with MAC-LWP increase from .4 to over .8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth’s Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new dataset is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol-cloud interactions, and providing contextual information for collocated ATSR-2/AATSR surface temperature and aerosol products. For the Cloud_cci ATSR-2/AATSRv3 dataset a new digital identifier has been issued: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 Poulsen et al. (2019).

A very large ensemble is used to identify subgrid-scale parameter settings for the HadCM3 model that are capable of best simulating the ocean state over the recent past (1980–2010). A simple particle filtering technique based upon the agreement of basin mean sea surface temperature (SST) and upper 700-m ocean heat content with EN3 observations is applied to an existing perturbed physics ensemble with initial conditions perturbations. A single set of subgrid-scale parameter values was identified from the wide range of initial parameter sets that gave the best agreement with ocean observations for the period studied. The parameter set, different from the standard model parameters, has a transient climate response of 1.68 K. The selected parameter set shows an improved agreement with EN3 decadal-mean SST patterns and the Atlantic meridional overturning circulation (AMOC) at 26°N as measured by the Rapid Climate Change (RAPID) array. Particle filtering techniques as demonstrated here could have a useful role in improving the starting point for traditional model-tuning exercises in coupled climate models.

Inhaled natural rubber latex (NRL) allergens in a healthcare environment can cause NRL sensitization and reduce pulmonary functions.To determine the amount of proteins and the effects of NRL gloves on the pulmonary functions of female nurses in two hospitals in the southern Thailand.The study included 340 female nurses from two hospitals in which self-reported information and a blood sample were collected. NRL sensitization was determined by using a solid-phase enzyme-labeled fluoroenzyme-immunoassay for anti-NRLIgE antibodies. Proteins in NRL gloves were measured by a modified Lowry method. Pulmonary function was measured by a spirometer.The prevalences of respiratory effects self-attributed to NRL glove use and of NRL sensitization were 6.5 and 4.7%, respectively. Four of the 16 sensitized nurses reported respiratory symptoms. NRL sensitized nurses had lower forced expiratory flow (FEF25-75% predicted value) than those who were non-sensitized (Adj. difference = -12.56, 95% CI = -24.41 to -0.70). Furthermore, examination gloves contained protein levels in the range of 111-250 mg/dm2. Difference types of NRL glove contained with different amount of proteins.NRL sensitization was more prevalent in nurses with high concentrations of proteins in NRL gloves (p = 0.04).Sensitization to NRL was associated with a decrease in FEF25-75% predicted value, indicating narrowing of the small airways of the lung. Use of gloves with low proteins can reducing NRL allergen exposure in these hospitals, which may reduce the risk of developing respiratory problems and NRL sensitization.

Recent years have seen the increasing inclusion of per-retrieval prognostic (predictive) uncertainty estimates within satellite aerosol optical depth (AOD) data sets, providing users with quantitative tools to assist in the optimal use of these data. Prognostic estimates contrast with diagnostic (i.e. relative to some external truth) ones, which are typically obtained using sensitivity and/or validation analyses. Up to now, however, the quality of these uncertainty estimates has not been routinely assessed. This study presents a review of existing prognostic and diagnostic approaches for quantifying uncertainty in satellite AOD retrievals, and it presents a general framework to evaluate them based on the expected statistical properties of ensembles of estimated uncertainties and actual retrieval errors. It is hoped that this framework will be adopted as a complement to existing AOD validation exercises; it is not restricted to AOD and can in principle be applied to other quantities for which a reference validation data set is available. This framework is then applied to assess the uncertainties provided by several satellite data sets (seven over land, five over water), which draw on methods from the empirical to sensitivity analyses to formal error propagation, at 12 Aerosol Robotic Network (AERONET) sites. The AERONET sites are divided into those for which it is expected that the techniques will perform well and those for which some complexity about the site may provide a more severe test. Overall, all techniques show some skill in that larger estimated uncertainties are generally associated with larger observed errors, although they are sometimes poorly calibrated (i.e. too small or too large in magnitude). No technique uniformly performs best. For powerful formal uncertainty propagation approaches such as optimal estimation, the results illustrate some of the difficulties in appropriate population of the covariance matrices required by the technique. When the data sets are confronted by a situation strongly counter to the retrieval forward model (e.g. potentially mixed land–water surfaces or aerosol optical properties outside the family of assumptions), some algorithms fail to provide a retrieval, while others do but with a quantitatively unreliable uncertainty estimate. The discussion suggests paths forward for the refinement of these techniques.

This article introduces ‘IMPRESS: Improving exposure assessmentmethodologies for epidemiological studies on pesticides’,a new research project focussed on better understanding theperformance of exposure assessment methodologies in pesticideepidemiology studies.

Humans are widely exposed to a wide variety of DNA alkylating agents (AAs) either directly, for example via cigarette smoke or indirectly via their formation in the gastrointestinal tract. Certain AAs, such as the tobacco specific nitrosamine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone) are known human carcinogens but the role that other AAs may play in the aetiology of human cancers is still uncertain due to difficulties in assessing human exposure to these agents. The aim of this work was therefore to develop a screening method to assess exposure to AAs by measuring the formation of O6-alkylguanines (O6-AlkGs) in DNA and applying it to the analysis of human DNA samples. To do this we took advantage of the S. pombe alkyltransferase-like protein (Atl1), which binds to all O6-AlkGs so far studied, to develop a slot blot assay. For this, sonicated heat denatured DNA was bound to Hybond-N+ membranes and probed with horseradish peroxidase-conjugated maltose-binding protein-Atl1 fusion protein. The binding was quantitated via peroxidase-mediated enhanced chemiluminescence using TMZ-methylated calf thymus (CT) DNA standards previously calibrated using a tritium-based competition assay. Using 1 μg DNA, the limit of quantitation and detectability were approximately 1.0 and 0.5 fmoles O6-MeG/μg DNA, respectively. Prior treatment of the TMZ-CT DNA standards with the DNA repair protein, O6-methylguanine DNA methyltransferase, reduced the detectable signal to background levels, confirming that the assay detected O6-methylguanine (O6-MeG) in TMZ-CT DNA. Importantly, CT DNA reacted in vitro with the alkylating agents N-ethyl-N-nitrosourea, N-propyl-N-nitrosourea, N-butyl-N-nitrosourea, N-benzyl-N-nitrosourea, N-allyl-N-nitrosourea and potassium diazoacetate all produced strong signals in the assay demonstrating its ability to detect a range of different O6-AlkGs. In addition, a variety of human DNA samples have been analysed in pilot studies: of 14 human placental DNA samples, 8 had O6-AlkG levels in the range of 1.05-1.71 fmoles/μg DNA, 3 had trace levels and in 3 samples there was no detectable signal. Of 5 human breast tumour DNA samples, 4 had O6-AlkGs levels in the range of 1.07-1.30 fmoles/µg DNA and 1 had trace levels. Two DNA samples from normal human breast tissue had no detectable O6-AlkGs but DNA from the tumours of the same patients had levels >1 fmoles/μg DNA. Of 6 DNA samples from whole blood 2 had detectable levels of O6-AlkGs (1.23 & 1.56 fmoles/μg DNA), 3 had trace amounts and 1 had no detectable level. These data thus show the potential usefulness of this slot blot assay as a screening tool to detect and quantify total O6-alkGs adducts in human DNA samples. Citation Format: Hanum Yaakub, Anthony Howell, Geoffrey Margison, Andrew Povey. Developing a screen for O6-alkylguanines in human DNA using the damage-specific binding protein, Atl1 [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5780.

Bracken fern is carcinogenic when fed to domestic and laboratory animals inducing bladder and ileal tumours and is currently classified as a possible human carcinogen by IARC. The carcinogenic illudane, ptaquiloside (PTQ) was isolated from bracken fern and is widely assumed to be the major bracken carcinogen. However, several other structurally similar illudanes are found in bracken fern, in some cases at higher levels than PTQ and so may contribute to the overall toxicity and carcinogenicity of bracken fern. In this review, we critically evaluate the role of illudanes in bracken fern induced toxicity and carcinogenicity, the mechanistic basis of these effects including the role of DNA damage, and the potential for human exposure in order to highlight deficiencies in the current literature. Critical gaps remain in our understanding of bracken fern induced carcinogenesis, a better understanding of these processes is essential to establish whether bracken fern is also a human carcinogen.

We present the key features of the Community Cloud retrieval for CLimate (CC4CL) processing algorithm. We focus on the novel features of the framework: the optimal estimation approach in general, explicit uncertainty quantification through rigorous propagation of all known error sources into the final product, and the consistency of our long-term, multi-platform time-series provided at various resolutions, from 0.5° to 0.02°. By describing all key input data and processing steps, we aim to inform the user about important features of this new retrieval framework, and its potential applicability to climate studies. We provide an overview of the retrieved and derived output variables. These are analysed for four, partly very challenging, scenes collocated with CALIOP (Cloud-Aerosol lidar with Orthogonal Polarization) observations in the high-latitudes and over the Gulf of Guinea/West Africa. The results show that CC4CL provides very realistic estimates of cloud top height and cover for optically thick clouds but, where optically thin clouds overlap, returns a height between the two layers. CC4CL is a unique, coherent, multi-instrument cloud property retrieval framework applicable to passive sensor data of several EO missions. Through its flexibility, CC4CL offers the opportunity for combining a variety of historic and current EO missions into one data set, which, compared to single sensor retrievals, is improved in terms of accuracy and temporal sampling.

The Community Cloud retrieval for Climate (CC4CL) is a cloud property retrieval system for satellite-based multispectral imagers and is an important component of the Cloud Climate Change Initiative (Cloud_cci) project. In this paper we discuss the optimal estimation retrieval of cloud optical thickness, effective radius and cloud top pressure based on the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm. Key to this method is the forward model which, includes the clear-sky model, the liquid water and ice cloud models, the surface model including a bidirectional reflectance distribution function (BRDF), the "fast" radiative transfer solution (which includes a multiple scattering treatment) All of these components and their assumptions and limitations will be discussed in detail. The forward model provides the accuracy appropriate for our retrieval method. The errors are comparable to the instrument noise for cloud optical thicknesses greater than 10. At optical thicknesses less than 10 modelling errors become more significant. The retrieval method is then presented describing optimal estimation in general, the non-linear inversion method employed, measurement and a priori inputs, the propagation of input uncertainties and the calculation of subsidiary quantities that are derived from the retrieval results. An evaluation of the retrieval was performed using measurements simulated with noise levels appropriate for the MODIS instrument. Results show errors less than 10 % for cloud optical thicknesses greater than 10. Results for clouds of optical thicknesses less than 10 have errors ranging up to 20 %.

Introduction The presentation describes a comprehensive study to better understand the reliability of assessment of human exposure to plant protection products (PPP) in previous occupational epidemiological investigations, and to use this information to recommend improvements in scientific practice for future studies. Further, it aims to assess the reliability and external validity of surrogate measures used in these studies to assign exposure to individuals or groups of individuals on the basis of self-reported information, job/crop exposure matrices and exposure algorithms. The project will also evaluate the size and the effects of recall bias on the misclassification of exposure to PPPs and associated health effects. Methods Existing and newly collected (biological) monitoring data from several existing epidemiological studies and historical records across various populations in Europe, Africa and Asia. Urinary metabolites of pesticides will be selected with due consideration on the extent of use within the study populations, validity of biomonitoring methods etc. The performance of the various exposure assessment methods will be compared and contrasted within existing epidemiological studies. Results The main outcome will be the validation of widely accepted and easily adaptable semi-quantitative individual-based exposure assessment methods against measured levels of urinary PPP metabolites in a broad range of settings. Additionally, the study will compare the reliability and performance of several grouped- and individual-based exposure assessment methods in the frame of existing epidemiological studies. Conclusion The project is due to commence in September 2017. We propose to present the study protocols, rationale and outcomes of a mini-symposium to be held at EPICOH 2017. © British Crown copyright (2017). This work is funded by the European Crop Protection Association (ECPA). The Health and Safety Laboratory is the commercial arm of the Health and Safety Executive (HSE); the paper’s contents including any opinions and/or conclusions expressed, are those of the authors alone and do not necessarily reflect ECPA or HSE policy.

The question of how to derive and present uncertainty information in climate data records (CDRs) has received sustained attention within the European Space Agency Climate Change Initiative (CCI), a programme to generate CDRs addressing a range of essential climate variables (ECVs) from satellite data. Here, we review the nature, mathematics, practicalities, and communication of uncertainty information in CDRs from Earth observations. This review paper argues that CDRs derived from satellite-based Earth observation (EO) should include rigorous uncertainty information to support the application of the data in contexts such as policy, climate modelling, and numerical weather prediction reanalysis. Uncertainty, error, and quality are distinct concepts, and the case is made that CDR products should follow international metrological norms for presenting quantified uncertainty. As a baseline for good practice, total standard uncertainty should be quantified per datum in a CDR, meaning that uncertainty estimates should clearly discriminate more and less certain data. In this case, flags for data quality should not duplicate uncertainty information, but instead describe complementary information (such as the confidence in the uncertainty estimate provided or indicators of conditions violating the retrieval assumptions). The paper discusses the many sources of error in CDRs, noting that different errors may be correlated across a wide range of timescales and space scales. Error effects that contribute negligibly to the total uncertainty in a single-satellite measurement can be the dominant sources of uncertainty in a CDR on the large space scales and long timescales that are highly relevant for some climate applications. For this reason, identifying and characterizing the relevant sources of uncertainty for CDRs is particularly challenging. The characterization of uncertainty caused by a given error effect involves assessing the magnitude of the effect, the shape of the error distribution, and the propagation of the uncertainty to the geophysical variable in the CDR accounting for its error correlation properties. Uncertainty estimates can and should be validated as part of CDR validation when possible. These principles are quite general, but the approach to providing uncertainty information appropriate to different ECVs is varied, as confirmed by a brief review across different ECVs in the CCI. User requirements for uncertainty information can conflict with each other, and a variety of solutions and compromises are possible. The concept of an ensemble CDR as a simple means of communicating rigorous uncertainty information to users is discussed. Our review concludes by providing eight concrete recommendations for good practice in providing and communicating uncertainty in EO-based climate data records.

This paper discusses a best-practice representation of uncertainty in satellite remote sensing data. An estimate of uncertainty is necessary to make appropriate use of the information conveyed by a measurement. Traditional error propagation quantifies the uncertainty in a measurement due to well-understood perturbations in a measurement and in auxiliary data – known, quantified "unknowns". The under-constrained nature of most satellite remote sensing observations requires the use of various approximations and assumptions that produce non-linear systematic errors that are not readily assessed – known, unquantifiable "unknowns". Additional errors result from the inability to resolve all scales of variation in the measured quantity – unknown "unknowns". The latter two categories of error are dominant in under-constrained remote sensing retrievals, and the difficulty of their quantification limits the utility of existing uncertainty estimates, degrading confidence in such data. This paper proposes the use of ensemble techniques to present multiple self-consistent realisations of a data set as a means of depicting unquantified uncertainties. These are generated using various systems (different algorithms or forward models) believed to be appropriate to the conditions observed. Benefiting from the experience of the climate modelling community, an ensemble provides a user with a more complete representation of the uncertainty as understood by the data producer and greater freedom to consider different realisations of the data.

The European Union's 7th Framework Programme (EU's FP7) project HEALS - Health and Environment-wide Associations based on Large Population Surveys - aims a refinement of the methodology to elucidate the human exposome. Human biomonitoring (HBM) provides a valuable tool for understanding the magnitude of human exposure from all pathways and sources. However, availability of specific biomarkers of exposure (BoE) is limited. The objective was to summarize the availability of BoEs for a broad range of environmental stressors and exposure determinants and corresponding reference and exposure limit values and biomonitoring equivalents useful for unraveling the exposome using the framework of environment-wide association studies (EWAS). In a face-to-face group discussion, scope, content, and structure of the HEALS deliverable "Guidelines for appropriate BoE selection for EWAS studies" were determined. An expert-driven, distributed, narrative review process involving around 30 individuals of the HEALS consortium made it possible to include extensive information targeted towards the specific characteristics of various environmental stressors and exposure determinants. From the resulting 265 page report, targeted information about BoE, corresponding reference values (e.g., 95th percentile or measures of central tendency), exposure limit values (e.g., the German HBM I and II values) and biomonitoring equivalents (BEs) were summarized and updated. 64 individual biological, chemical, physical, psychological and social environmental stressors or exposure determinants were included to fulfil the requirements of EWAS. The list of available BoEs is extensive with a number of 135; however, 12 of the stressors and exposure determinants considered do not leave any measurable specific substance in accessible body specimens. Opportunities to estimate the internal exposure stressors not (yet) detectable in human specimens were discussed. Data about internal exposures are useful to decode the exposome. The paper provides extensive information for EWAS. Information included serves as a guideline - snapshot in time without any claim to comprehensiveness - to interpret HBM data and offers opportunities to collect information about the internal exposure of stressors if no specific BoE is available. This work has received funding from the European Union's Seventh Programme for research, technological development and demonstration under grant agreement No. 603946 (Health and Environment-wide Associations based on Large population Surveys, HEALS). All HEALS partners involved in the discussion of deliverable 4.2 during the annual HEALS meeting in Edinburgh, UK, on September 16, 2014, are grate-fully acknowledged. Special thanks go to our colleagues outside WP4 and outside HEALS who reviewed chapters of their expertise: Thank you, Tomislav Bituh, Danijela Š timac, and Matthias Weigl.

Use of pesticides in agriculture may lead to downstream exposure of farmers' families to pesticide residues inadvertently taken home. Identification of the independent contribution of different exposure pathways from the farmer to their children can provide clear targets to reduce exposure of farmers' children. Individual contributions of different pesticide transfer exposure pathways were investigated using structural equation modeling methods, and the benefits of these methods compared to standard multiple regression are described. A total of 72 Thai families, consisting of a farmer, a spouse, and a child, participated in this study. Family members completed a questionnaire and self-collected three spot morning urine samples in the spraying season. Urine samples were analyzed for diethyl phosphate, diethyl thiophosphate, diethyl dithiophosphate, dimethyl phosphate, dimethyl thiophosphate, and dimethyl dithiophosphate. A path model was developed based on an a priori hypothesized framework to examine the individual contributions of different exposure pathways that may directly or indirectly affect transfer of pesticide residues from farmers to their children. Transfer from the farmer to the child occurs indirectly, primarily through transfer to the spouse in the first instance, but also through contamination of the home environment. Clear targets for interventions are directly the reduction of farmers' take-home exposures and indirectly frequent cleaning of the home to avoid buildup of pesticide residues.

Introduction Organophosphate (OP) pesticides exposure has been linked to various health effects but the association between exposure and semen quality is unclear. This systematic review aimed to investigate the association between OP exposure and semen quality.Methods Electronic databases including Ovid-Medline, PubMed and Website of Science were searched for studies on OP and semen quality published between 2000 and 2016. Terms representing population, exposure and outcome were used in combination. Relevant articles were extracted and critically appraised using the Newcastle Ottawa Scale.Results 12 epidemiological studies were identified of which 10 were cross- sectional and two case-control studies. Eight studies were of occupationally exposed workers with exposure assessed by self-report in four studies or inferred in three studies or by the use of urinary dialkylphosphates in five studies. Sperm concentration or motility or morphology was altered in eight studies. Concentration was reduced in one study of which assessed exposure by self-report, one by inference and three by biomarkers. Motility was reduced in four studies of which assessed exposure by self-report, one by inference and two by biomarkers. Morphology was reduced in three studies of which assessed exposure by self-report and one by inference. More fundamentally only one study examined the relationship between time of exposure and outcome assessment.Conclusion There was a lack of consistency in the reported associations and hence there is limited evidence to support a causal association between OP exposure and semen quality. This could be due to heterogeneity in study populations and different in exposure assessment

New cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for cloud detection and cloud typing followed by cloud property retrievals based on the optimal estimation (OE) technique. The OE-based retrievals are applied to simultaneously retrieve cloud-top pressure, cloud particle effective radius and cloud optical thickness using measurements at visible, near-infrared and thermal infrared wavelengths, which ensures spectral consistency. The retrieved cloud properties are further processed to derive cloud-top height, cloud-top temperature, cloud liquid water path, cloud ice water path and spectral cloud albedo. The Cloud_cci products are pixel-based retrievals, daily composites of those on a global equal-angle latitude–longitude grid, and monthly cloud properties such as averages, standard deviations and histograms, also on a global grid. All products include rigorous propagation of the retrieval and sampling uncertainties. Grouping the orbital properties of the sensor families, six datasets have been defined, which are named AVHRR-AM, AVHRR-PM, MODIS-Terra, MODIS-Aqua, ATSR2-AATSR and MERIS+AATSR, each comprising a specific subset of all available sensors. The individual characteristics of the datasets are presented together with a summary of the retrieval systems and measurement records on which the dataset generation were based. Example validation results are given, based on comparisons to well-established reference observations, which demonstrate the good quality of the data. In particular the ensured spectral consistency and the rigorous uncertainty propagation through all processing levels can be considered as new features of the Cloud_cci datasets compared to existing datasets. In addition, the consistency among the individual datasets allows for a potential combination of them as well as facilitates studies on the impact of temporal sampling and spatial resolution on cloud climatologies.For each dataset a digital object identifier has been issued:Cloud_cci AVHRR-AM: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-AM/V002Cloud_cci AVHRR-PM: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V002Cloud_cci MODIS-Terra: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Terra/V002Cloud_cci MODIS-Aqua: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Aqua/V002Cloud_cci ATSR2-AATSR: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V002Cloud_cci MERIS+AATSR: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MERIS+AATSR/V002

There are concerns about genetic risks associated with long-term exposure to pesticides as these compounds may damage DNA, resulting in mutations that eventually lead to cancer, neurological, and reproductive adverse health effects. This study assessed DNA damage in intensive agricultural workers exposed to pesticides by determining the levels of N7-methyldeoxyguanosine (N7-MedG), an adduct known to be a robust biomarker of recent exposure to chemical methylating agents. A cohort of 39 plastic greenhouse workers was assessed for changes in lymphocyte DNA N7-MedG levels between low level and high level exposures during the course of a spraying season. The contributions of genetic polymorphisms of the pesticide-metabolizing enzymes paraoxonase-1 (PON1) and the glutathione S-transferases, GSTM1 and GSTT1, on N7-MedG levels and other potential confounders were also assessed. N7-MedG increased in the period of high pesticide exposure as compared to the low exposure period (0.23 and 0.18 µmol N7-MedG/mol dG for the unadjusted and adjusted linear mixed models, P = 0.02 and 0.08, respectively). Significant decreased levels of erythrocyte acetylcholinesterase and plasma cholinesterase were observed in the high versus low exposure period in both the unadjusted (2.85 U/g hemoglobin and 213.13 U/L, respectively) and adjusted linear mixed models (2.99 U/g hemoglobin and 230.77 U/L, respectively), indicating pesticide intake. In intensive agriculture workers, higher pesticide exposure increased DNA alkylation levels, further demonstrating the genotoxicity of pesticides in man. In addition, pesticide-exposed individuals with inherited susceptible metabolic genotypes (particularly, null genotype for GSTM1 and the PON1 192R allele) appear to have an increased risk of genotoxic DNA damage. Environ. Mol. Mutagen. 56:437–445, 2015. © 2014 Wiley Periodicals, Inc.

BACKGROUND: Epidemiological evidence linking low dose pesticide exposure and chronic ill-health in UK sheep farmers is limited. Our aim was to examine whether neuropsychiatric disorders were associated with low dose chronic and/or more acute pesticide exposure in sheep farmers. METHODS: A cohort of British farmers working in the 1970s was sent a screening questionnaire which asked about their health and work history. The prevalence of screen-positive depression, dementia, Parkinsonism and neuropathy was determined using a priori algorithms. Self-reported pesticide exposure was assessed by whether the participant had ever handled the pesticide concentrate (for low dose chronic exposure) or sought advice for pesticide poisoning (acute exposure) and participants categorised into those with only acute or chronic exposure, those with both acute and chronic exposure and those with neither acute nor chronic exposure. Associations between acute and chronic pesticide exposure, and screen-positive ill-health were determined after adjustment for demographic, lifestyle, occupation and somatic severity scores and other variables. RESULTS: In those participants, who had never sought advice for pesticide poisoning, handling the pesticide concentrate for treating sheep was associated with elevated ORs for screen-positive neuropathy (ORadi 1.57 95%CI 0.97-2.54) and Parkinsonism (ORadj 1.56 95%CI 0.95-2.56) but not depression or dementia. In those participants who had handled the pesticide concentrate, seeking advice for pesticide poisoning was associated with screen-positive depression (Odds ratio, ORadj=9.97 95%CI 4.76-20.8 ), dementia (OR=6.94 95%CI 3.44-14.0), Parkinsonism (ORadj=4.77 95% 2.39-9.52), and neuropathy (ORadj=4.77 95%CI 2.39-9.52). Adjustment for somatic severity score modified little the associations with pesticide handling in those not acutely exposed but reduced the ORs for seeking advice for pesticide poisoning in those exposed chronically. Furthermore, stratification of results based upon somatic severity score indicated that the highest ORs for handling the pesticide concentrate associated with neuropathy and Parkinsonism were found in those participants whose somatic score was minimal. CONCLUSIONS: Results are consistent with low-dose exposure to pesticides being associated with screen-positive neuropathy and Parkinsonism but the stronger associations between seeking advice for pesticide poisoning and screen-positive ill-health suggest that acute pesticide exposure remains an important determinant of ill-health. Further work is required to better delineate to what extent low dose exposures may contribute to ill-health in populations without acute exposures. Somatising tendency does not appear to play an important role in this population.

STUDY QUESTION: Are common lifestyle factors associated with poor sperm morphology? SUMMARY ANSWER: Common lifestyle choices make little contribution to the risk of poor sperm morphology. WHAT IS KNOWN ALREADY: Although many studies have claimed that men's lifestyle can affect sperm morphology, the evidence is weak with studies often underpowered and poorly controlled. STUDY DESIGN, SIZE, DURATION: Unmatched case-referent study with 318 cases and 1652 referents. Cases had poor sperm morphology (

Objective We examined occupational exposures and sperm morphology to establish whether exposures implicated differed from those affecting motile sperm concentration. Methods Computer aided sperm morphometric assessment was undertaken on morphology slides obtained as part of a multi-centre study in 1999–2002 of occupational factors in male infertility. Men attending 14 fertility clinics across the UK were recruited and gave a semen sample. Before results of the semen analysis were known, the men completed detailed questionnaires about their employment and lifestyle. Occupational exposures were assessed by occupational hygienists. Data were analysed using an unmatched case-referent design, allowing for clustering and for confounders. Three case definitions were used: poor morphology (normal morphology 6 ) and either condition. Results Morphology results were available for 1861/2011 men employed at the time of recruitment. Of these 1861, 296 (15.9%) had poor morphology; of the 2011with sperm count, 453 (22.5%) had low MSC; 654/1981 (33.0%) had either condition. Poor morphology, adjusted for confounding, was related to self-reported lifetime exposure to lead (OR=1.33; 95% CI 1.00 to 1.75). Low MSC was also related to self-reported lead and to hygienist-assessed glycol ether exposure. Self-reported use of paint stripper (OR=1.47; 95% CI 1.07 to 2.03) and lead, but not glycol ether, were significantly related to the combined case definition. Conclusions While this study did not identify any occupational exposure uniquely related to sperm morphology, the capacity of the study to detect risk was increased by including morphology with sperm concentration and motility.