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Objective To ascertain the knowledge of lymphatic filariasis among inhabitants of an irrigation project community in north central Nigeria. Methods A descriptive cross sectional study which involved 285 participants ≥18 years who live in Omi and its surrounding communities was done. Data on socio-demographic characteristics and the knowledge, attitude and practices of the participants were obtained using pre-tested questionnaires. Data were analyzed usin SPSS software version 16.0. Results A greater proportion (82%) of the participants were not aware of lymphatic filariasis and the exact cause of the infection. Quite a good number (85%) reported pain and swelling as symptoms. The respondents generally had a fair understanding of prevention and management strategies of the disease. The results from this study showed that the association between awareness of lymphatic filariasis and gender, age, educational level and occupation of the participants was not significant (P > 0.05). Conclusions Many of the participants had a poor knowledge of lymphatic filariasis, the mode of transmission and symptoms of the disease. For proper understanding of lymphatic filariasis in the community, there is need for effective and realistic health education campaigns targeted at the grassroots.

Time-series analysis techniques are being increasingly used to process satellite observations of volcanic gas emissions and heat flux, with the aim of identifying cyclic behaviour that could inform hazard assessment or elucidate volcanic processes. However, it can be difficult to distinguish cyclic variations due to geophysical processes from those that are artefacts of the observation technique. Here, we conduct a comprehensive investigation into the origin of cyclicity in volcanic observations by analysing daily, global satellite measurements of volcanic SO2 loading by the Ozone Monitoring Instrument (OMI) and thermal infrared anomalies detected by the Moderate Resolution Imaging Spectroradiometer (MODIS). We use a fast Fourier Transform (FFT) multi-taper method (MTM) to analyse multiple phases of activity at 32 target volcanoes, utilising measurements obtained from three NASA satellite instruments (Aura – OMI, Aqua – MODIS and Terra – MODIS), and identify a common cycle (period of ~ 2.3 days), which is not considered to be of volcanic origin. Based on the presence of this cycle in multiple satellite datasets, we attribute it to variations in viewing angle during the 16-day orbit repeat cycle of sun-synchronous satellites maintained in Low Earth Orbit (LEO). A 5-point averaging correction procedure is tested on satellite observations from Kilauea volcano, Hawaii, and is found to reduce the impact of higher frequency cycles and reveal the presence of longer-period geophysical signals. In addition to the identification of a signal common to different measurement techniques, an underlying cyclical pattern was found in the OMI SO2 observations (periods of ~ 7.9 and 3.2 days) generated by the OMI Row Anomaly (ORA). We conclude that identification of the presence and magnitude of non-geophysical cyclic behaviour, which can suppress natural cycles in time-series data, and implementation of appropriate corrections, is crucial for accurate interpretation of satellite observations. The use of data averaging to suppress non-geophysical cycles imposes limits on the length of natural cycles that can be confidently identified in moderate resolution satellite observations from polar-orbiting spacecraft.

The Ozone Monitoring Instrument (OMI) is a push-broom imaging spectrometer, observing solar radiation backscattered by the Earth's atmosphere and surface. The incoming radiation is detected using a static imaging CCD (charge-coupled device) detector array with no moving parts, as opposed to most of the previous satellite spectrometers, which used a moving mirror to scan the Earth in the across-track direction. The field of view (FoV) of detector pixels is the solid angle from which radiation is observed, averaged over the integration time of a measurement. The OMI FoV is not quadrangular, which is common for scanning instruments, but rather super-Gaussian shaped and overlapping with the FoV of neighbouring pixels. This has consequences for pixel-area-dependent applications, like cloud fraction products, and visualisation.The shapes and sizes of OMI FoVs were determined pre-flight by theoretical and experimental tests but never verified after launch. In this paper the OMI FoV is characterised using collocated MODerate resolution Imaging Spectroradiometer (MODIS) reflectance measurements. MODIS measurements have a much higher spatial resolution than OMI measurements and spectrally overlap at 469 nm. The OMI FoV was verified by finding the highest correlation between MODIS and OMI reflectances in cloud-free scenes, assuming a 2-D super-Gaussian function with varying size and shape to represent the OMI FoV. Our results show that the OMPIXCOR product 75FoV corner coordinates are accurate as the full width at half maximum (FWHM) of a super-Gaussian FoV model when this function is assumed. The softness of the function edges, modelled by the super-Gaussian exponents, is different in both directions and is view angle dependent.The optimal overlap function between OMI and MODIS reflectances is scene dependent and highly dependent on time differences between overpasses, especially with clouds in the scene. For partially clouded scenes, the optimal overlap function was represented by super-Gaussian exponents around 1 or smaller, which indicates that this function is unsuitable to represent the overlap sensitivity function in these cases. This was especially true for scenes before 2008, when the time differences between Aqua and Aura overpasses was about 15 min, instead of 8 min after 2008. During the time between overpasses, clouds change the scene reflectance, reducing the correlation and influencing the shape of the optimal overlap function.

Shortly after the outbreak of the novel infectious disease (COVID-19) started at the end of 2019, it turned into a global pandemic, which caused the lockdown of many countries across the world. Various strict measures were adopted to reduce anthropogenic activities in order to prevent further spread and infection of the disease. In this study, we utilized continental scale remotely sensed data along with city scale in situ air quality observations for 2020 as well as data from the baseline period (2015–2019) to provide an early insight on air pollution changes in response to the COVID-19 pandemic lockdown, by combining both continental and city scales. For the continental scale analysis, data of NO2, SO2, and O3 were acquired from the ozone monitoring instrument (OMI) and data of aerosol optical depth (AOD) were collected from the moderate resolution imaging spectroradiometer (MODIS). For city scale analysis, data of NO2, CO, PM2.5, O3, and SO2 were derived from ground-based air quality observations. Results from satellite observations at the continental scale showed that concentrations of NO2, SO2, and AOD substantially dropped in 2020 during the lockdown period compared to their averages for the baseline period over all continents, with a maximum reduction of ~33% for NO2 in East Asia, ~41% for SO2 in East Asia, and ~37% for AOD in South Asia. In the case of O3, the maximum overall reduction was observed as ~11% in Europe, followed by ~10% in North America, while a slight increase was found in other study regions. These findings align with ground-based air quality observations, which showed that pollutants such as NO2, CO, PM2.5, and SO2 during the 2020 lockdown period decreased significantly except that O3 had varying patterns in different cities. Specifically, a maximum reduction of ~49% in NO2 was found in London, ~43% in CO in Wuhan, ~38% in PM2.5 in Chennai, and ~48% in SO2 in Beijing. In the case of urban O3, a maximum reduction of ~43% was found in Wuhan, but a significant increase of ~47% was observed in Chennai. It is obvious that restricted human activities during the lockdown have reduced the anthropogenic emissions and subsequently improved air quality, especially across the metropolitan cities.

The new-generation sensor TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel 5 precursor (S5P) satellite is promising for monitoring air pollutants with greater spatial resolution, especially for China, which suffers from severe pollution. As tropospheric NO2 vertical column densities (VCDs) from TROPOMI have become available since February 2018, this study presents the comparisons of NO2 data measured by TROPOMI and its predecessor Ozone Monitoring Instrument (OMI) over China, together with validation against ground Multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements. At the nationwide scale, we used two different filters performed for the TROPOMI data (named TROPOMI50 and TROPOMI75), and the TROPOMI50 yielded larger values than TROPOMI75. The TROPOMI NO2 datasets from different filters show consistent spatial patterns with OMI, and the correlation coefficient values were both above 0.93. However, linear regression indicates that NO2 loadings in TROPOMI is about 2/3 to 4/5 of those in OMI, which is presumably due to a different cloud mask and uncertainties of air mass factors. The absolute difference is prominent over the high pollution areas such as Jing-Jin-Ji region and during winter and autumn, exceeding 0.6 &times, 1016 molecules cm&minus, 2 (molec cm&minus, 2). However, the NO2 concentrations retrieved from TROPOMI50 in the southern China may be somewhat higher than OMI. When it comes to the local-scale Jing-Jin-Ji hotspot, the analysis focuses on a comparison to TROPOMI75. TROPOMI manifests high quality and exhibits a significantly better performance of representing spatial variability. In contrast, OMI shows fewer effective pixels and does a poor job of capturing local details due to its row anomaly and low resolution. The absolute difference between two datasets shows the same seasonal behavior with NO2 variation, which is most striking in the winter (0.31 &times, 1016 molec cm&minus, 2) and is lowest in the summer (0.05 &times, 2). Furthermore, the ground MAX-DOAS instrument in Xianghe station, the representative site in Jing-Jin-Ji, is used to assess the skill of satellite retrievals. It turns out that both OMI and TROPOMI underestimate the observations, ranging from 30% to 50%, with OMI being less biased. In spite of the negative drift, the temporal structures of changes derived from OMI and TROPOMI closely match the ground-based records, since the correlation coefficients are above 0.8 and 0.95 for daily and monthly scales, respectively. Overall, TROPOMI NO2 retrievals are better suited for applications in China as well as the Jing-Jin-Ji hotspot due to its higher spatial resolution, although some improvements are also needed in the near future.

The OMI NO2 standard product, OMNO2d, has been widely used in estimating surface NO2 concentrations. The Peking University Ozone Monitoring Instrument NO2 product (POMINO) is claimed to provide an improved quality over east-central China. This study estimated one year (Dec.2016–Nov.2017) of surface NO2 concentrations at satellite overpass time based on OMNO2d data and POMINO data, respectively. We used an extra-trees (ET) regression model to convey the non-linear relationship between surface NO2 and predictors, and compared the prediction accuracy with that of random forests (RF) regression model. The ET model showed a better estimation performance than the RF model, with the cross-validation R2 of 0.72 (RMSE = 9.20 μg/m3) and R2 of 0.70 (RMSE = 9.42 μg/m3) based on POMINO and OMNO2d data, respectively. The POMINO-derived monthly mean surface NO2 concentrations were closer to ground NO2 measurements than that OMNO2d-derived. Although the estimations from both satellite products were underestimated in polluted situations, the use of POMINO reduced the underestimation as compared to the use of OMNO2d data.

As one of geostationary earth orbit constellation for environmental monitoring over the next decade, the Geostationary Environment Monitoring Spectrometer (GEMS) has been designed to observe the Asia-Pacific region to provide information on atmospheric chemicals, aerosols, and cloud properties. In order to continuously monitor sensor performance after its launch in early 2020, we suggest in this paper deep convective clouds (DCCs) as a possible target for the vicarious calibration of the GEMS, the first ultraviolet and visible hyperspectral sensor onboard a geostationary satellite. The Tropospheric Monitoring Instrument (TROPOMI) and the Ozone Monitoring Instrument (OMI) are used as a proxy for GEMS, and a conventional DCC-detection approach applying a thermal threshold test is used for DCC detection based on collocations with the Advanced Himawari Imager (AHI) onboard the Himawari-8 geostationary satellite. DCCs are frequently detected over the GEMS observation area at an average of over 200 pixels within a single observation scene. Considering the spatial resolution of the GEMS (3.5 × 8 km2), which is similar to the TROPOMI and its temporal resolution (eight times a day), the availability of DCCs is expected to be sufficient for the vicarious calibration of the GEMS. Inspection of the DCC reflectivity spectra estimated from OMI and TROPOMI data also shows promising results. The estimated DCC spectra are in good agreement within a known uncertainty range with comparable spectral features even with different observation geometries and sensor characteristics. When DCC detection is improved further by applying both visible and infrared tests, the variability of DCC reflectivity from TROPOMI data is reduced from 10% to 5%. This is mainly due to the efficient screening out of cold, thin cirrus clouds in the visible test and of bright, warm clouds in the infrared test. Precise DCC detection is also expected to contribute to the accurate characterization of cloud reflectivity, which will be investigated further in future research.

The Chengdu&ndash, Chongqing Economic Zone (CCEZ), which is located in southwestern China, is the fourth largest economic zone in China. The rapid economic development of this area has resulted in many environmental problems, including extremely high concentrations of nitrogen dioxide (NO2) and fine particulate matter (PM2.5). However, current ground observations lack spatial and temporal coverage. In this study, satellite remote sensing techniques were used to analyze the variation in NO2 and PM2.5 from 2005 to 2015 in the CCEZ. The Ozone Monitoring Instrument (OMI) and the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) product were used to retrieve tropospheric NO2 vertical columns and estimate ground-level PM2.5 concentrations, respectively. Geographically, high NO2 concentrations were mainly located in the northwest of Chengdu and southeast of Chongqing. However, high PM2.5 concentrations were mainly located in the center areas of the basin. The seasonal average NO2 and PM2.5 concentrations were both highest in winter and lowest in summer. The seasonal average NO2 and PM2.5 were as high as 749.33 &times, 1013 molecules&middot, cm&minus, 2 and 132.39 &micro, g&middot, m&minus, 3 in winter 2010, respectively. Over 11 years, the annual average NO2 and PM2.5 values in the CCEZ increased initially and then decreased, with 2011 as the inflection point. In 2007, the concentration of NO2 reached its lowest value since 2005, which was 230.15 &times, 2, and in 2015, the concentration of PM2.5 reached its lowest value since 2005, which was 26.43 &micro, 3. Our study demonstrates the potential use of satellite remote sensing to compensate for the lack of ground-observed data when quantitatively analyzing the spatial&ndash, temporal variations in regional air quality.

The atmosphere is essential in the nature of the Earth, it is a layer of gases that, among other things, allows the temperature of the Earth to be hospitable to all living species. The interaction of solar radiation on the surface of the Earth and in the atmosphere has been the sum importance throughout the evolution of the Earth. Solar radiation is the source of energy that induces a diversity of natural phenomena, of enormous proportions, and a large number of these phenomena, is produced by photons of solar radiation of very specific wavelengths, such as photosynthesis and reactions of photodisociation. The photodissociation of Oxygen at high altitudes gives rise to Ozone formation. Ozone, despite being a trace of gas that represents less than 0.00001% in the atmosphere, plays an important and irreplaceable role because it attenuates UV-B and UV-A radiation to relatively harmless levels for living beings. For this reason, to know the tendencies of the behavior of the erythema UV radiation and its relation with the Total Ozone Column is great importance. This work includes the systematization and analysis of the behavior of the erythematous dose in the State of Zacatecas from the end of 2005 to the beginning of 2006, data provided by NASA. The systematization found is indicative of the erythematous dose levels that may occur in the State throughout the year. La atmósfera es esencial en la naturaleza de la Tierra, es una capa de gases que, entre otras cosas, permite que la temperatura de la Tierra sea hospitalaria para todas las especies vivientes. La interacción de la radiación solar en la superficie de la Tierra y en la atmósfera ha sido de suma importancia a lo largo de la evolución de la Tierra. La radiación solar es la fuente de energía que induce una diversidad de los fenómenos naturales, de enormes proporciones, y un gran número de estos fenómenos, se produce por fotones de radiación solar de longitudes de onda muy específicos, tales como la fotosíntesis y las reacciones de fotodisociación. La fotodisociación del Oxígeno en grandes altitudes da lugar a la formación del Ozono. El Ozono, a pesar de ser un gas traza que en la atmósfera representa menos del 0.00001%, cumple un importante e insustituible papel pues atenúa la radiación UV-B y UV-A hasta niveles relativamente inofensivos para los seres vivos. Por este motivo, conocer las tendencias del comportamiento de la radiación eritemal UV y su relación con la Columna Total de Ozono es de suma importancia. Este trabajo comprende la sistematización y análisis del comportamiento de la dosis eritematosa en el Estado de Zacatecas de fines del 2005 a principios del 2006, datos proporcionados por la NASA. La sistematización encontrada es indicativa de los niveles de dosis eritematosa que puede ocurrir en el Estado a lo largo del año.

Batu Tara (Indonesia) and Tinakula (Solomon Island) are two poorly known volcanoes with morphologies and short-term eruptive activity similar to Stromboli (Italy). However, quantitative information about their long-term eruptive behaviour is limited, making the comparisons with Stromboli descriptive and based on short periods of observations. Here, we use over a decade of satellite data to measure and compare the radiant flux (2000–2017) and the SO2 mass (2004–2017) of all three volcanoes. The combined analysis of volcanic radiant power (from MODIS data) and SO2 flux (from OMI data) reveals different long-term eruptive trends and contrasting ratios of SO2/VRP. These data indicate that the eruptive mechanisms operating at each volcano are quite different. The persistent open-vent activity of Stromboli volcano is episodically interrupted by flank eruptions that drain degassed magma stored in the very shallow portion of the central conduit. In contrast, a long-lasting exponential decay of both VRP and SO2 flux observed at Batu Tara is consistent with the eruption of undegassed magma from a deep, closed magma chamber, whilst Tinakula displays multiple year-long eruptive phases, characterised by evolving gas/thermal ratios and an eruptive intensity increasing with time. Magma budget calculations for the latter volcano are consistent with eruption from a volatile-zoned magma chamber, coupled with periods of gas/magma accumulations at depth. Our results suggest that the combined analysis of satellite thermal/gas data provides a valuable tool for decrypting the long-term volcanic dynamics that could remain hidden over shorter timescales.

A conservative downscaling technique was applied when comparing nitrogen dioxide (NO2) column densities from space-borne observations and a fine-scale regional model. The conservative downscaling was designed to enhance the spatial resolution of satellite measurements by applying the fine-scale spatial structure from the model, with strict mass conservation at each satellite footprint pixel level. With the downscaling approach, NO2 column densities from the Ozone Monitoring Instrument (OMI; 13 × 24 km nadir footprint resolution) and the Global Ozone Monitoring Experiment-2 (GOME-2; 40 × 80 km) show excellent agreement with the Community Multiscale Air Quality (CMAQ; 4 × 4 km) NO2 column densities, with R = 0.96 for OMI and R = 0.97 for GOME-2. We further introduce an approach to reconstruct surface NO2 concentrations by combining satellite column densities and simulated surface-to-column ratios from the model. Compared with the Environmental Protection Agency’s (EPA) Air Quality System (AQS) surface observations, the reconstructed surface concentrations show a good agreement; R = 0.86 for both OMI and GOME-2. This study demonstrates that the conservative downscaling approach is a useful tool to compare coarse-scale satellites with fine-scale models or observations in urban areas for air quality and emissions studies. The reconstructed fine-scale surface concentration field could be used for future epidemiology and urbanization studies.

El principal objetivo del presente trabajo es el de mostrar las nuevas orientaciones a las cuales se dedicará próximamente la “International Association of Classification Societies (IACS)”, tomando como guía de referencia su plan estratégico del periodo 2016 – 2017. De tal modo, a lo largo de este trabajo se mostrarán las actuales y futuras funciones o roles de las sociedades de clasificación, las cuales no se reducen exclusivamente a las ya clásicas clasificaciones e inspecciones de buques, y su contribución de esta manera a la seguridad marítima.

The present works’ aim has been to gain further insights into the proteolytic mechanisms present in necroptosis via multiple routes: investigating an in-vivo model for necroptosis in DSS-induced colitis in mice with an extremely reduced expression of the sheddase ADAM17, investigating the role of the phosphoglycerate mutase family member 5 (PGAM5) in necroptosis, analysis of the function of the protease HtrA2/Omi and its possible substrates in

This paper focuses on the inter-comparison of integrated water vapor (IWV) products derived from the following satellite instruments: Global Ozone Monitoring Instrument (GOME-2), Moderate-Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites, Ozone Monitoring Instrument (OMI), Spining Enhanced Visible and InfraRed Imager (SEVIRI), Atmospheric Infrared Sounder (AIRS), and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). IWV data from GPS in nine ground-based stations located in the Iberian Peninsula are used as reference. The study period extends from 2007 to 2012. The results show that, in general, OMI has good accuracy (pseudomedian of the relative differences between OMI and GPS IWV of ( −0.7 ± 1.1)%). However, OMI, SCIAMACHY and AIRS show higher inter-quartile range (IQR) (which indicates lower precision) than the rest of satellite instruments. Both MODIS satellite instruments and SEVIRI products tend to slightly underestimate reference IWV data while GOME-2 exhibits a notable overestimation (16.7 ± 0.8%). All satellite instruments showed a tendency to reduce IWV extreme values: low IWV is overestimated while high IWV is underestimated. As for the influence of solar zenith angle (SZA), it can be observed that GOME-2 strongly overestimates the reference for high SZA values (by around 60% for SZA 60 − 80°). OMI shows, however, a high IQR for high SZA values. Both MODIS instruments show an increase in the pseudomedian of relative differences and IQR with SZA at daytime, with more stable values at night. Seasonal dependence is mainly due to the SZA and IWV typical values in each season. In general, in summer the tendency is to underestimate with low IQR (which happens when IWV is high and SZA is low), and in winter the trend is to overestimate with high IQR (which happens when IWV is low and SZA is high). SCIAMACHY shows a high pseudomedian in summer and autumn, and lower in winter and spring. It must be noted that GOME-2 shows a higher overestimation and OMI shows a higher IQR than other satellite instruments in winter and autumn. The influence of clouds was also studied, showing an increase of IQR as cloudiness increases in all satellites. Pseudomedian also worsens as cloudiness increases, generally. This work was supported by the Spanish Ministry of Economy and Competitiveness through project CGL2014-56255-C2. Manuel Antón thanks Ministerio de Ciencia e Innovación and Fondo Social Europeo (RYC-2011-08345) for the award of a postdoctoral grant (Ramón y Cajal). Support from the Junta de Extremadura (Research Group Grants GR15137) is gratefully acknowledged. The GOME-2/MetOp-A products were generated at DLR under the auspices of the O3MSAF project funded by EUMETSAT and national contributions. The generation of SCIAMACHY data was supported by ESA, DLR Bonn and by the University of Bremen, Germany. Work at Universidad de Valladolid is supported by projects CMT2015-66742-R and MINECO VA100U14. Work at Universidad de Granada was supported by the Andalusia Regional Government (project P12-RNM-2409) and the Spanish Ministry of Economy and Competitiveness and FEDER funds under the projects CGL2013-45410-R, CGL2016-81092-R and “Juan de la Cierva-Formación” program. Work at SAO is supported by NASA’s Atmospheric Composition: Aura Science Team program (sponsor contract number NNX14AF56G). Work at Universidade de Évora is cofunded by the European Union through the European Regional Development Fund, included in the COMPETE 2020 (Operational Program Competitiveness and Internationalization) through the ICT project (UID/GEO/04683/2013) with the reference POCI-01-0145-FEDER-007690.

Uno de los mayores problemas ambientales hoy en día es la contaminación del medio marino. Una parte de este problema está causada por la deficiente gestión de residuos en los buques durante su actividad operacional. El propósito de este proyecto es realizar el diseño de ingeniería de un sistema de gestión y tratamiento de residuos producidos en la actividad operacional de un buque de pasaje y carga rodada (RO-PAX) cumpliendo las prescripciones del Anexo V del Convenio MARPOL de la OMI de prevención y reducción de la contaminación por basuras. Abstract: Marine environment contamination is one of the most important environmental problems. Part of this issue is caused by a deficient vessels’ garbage management during their operation. The purpose of this project is to carry out the engineering design of a garbage management and treatment system for residues produced in a passenger and rolling cargo (RO-PAX) vessel operation complying with IMO’s MARPOL Convent’s Annex V prescriptions about prevention and reduction of garbage contamination. Grado en Ingeniería Marítima

La Organización Marítima Internacional es el organismo especializado de la ONU responsable de la seguridad, la seguridad de la navegación y la prevención de la contaminación del mar por los buques. El Plan de auditorias, actualmente es de carácter obligatorio para todos los Estados Miembros de la OMI, desde el 01 de enero de 2016. En el presente proyecto desarrollamos el Marco normativo, una guía para la realización de auditorias a dichos Estados, así como el código para la implantación de los instrumentos de la OMI (Código III). Estas auditorias se incluyen en un Plan que tiene por objeto proporcionar una evaluación amplia y objetiva de la eficacia con que se administran e implantan los instrumentos obligatorios de la OMI.

The identification of cyclic volcanic activity can elucidate underlying eruption dynamics and aid volcanic hazard mitigation. Whilst satellite datasets are often analysed individually, here we exploit the multi-platform NASA A-Train satellite constellation to cross-correlate cyclical signals identified using complementary measurement techniques at Soufriere Hills Volcano (SHV), Montserrat. In this paper we present a Multi-taper (MTM) Fast Fourier Transform (FFT) analysis of coincident SO 2 and thermal infrared (TIR) satellite measurements at SHV facilitating the identification of cyclical volcanic behaviour. These measurements were collected by the Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) (respectively) in the A-Train. We identify a correlating cycle in both the OMI and MODIS data (54–58 days), with this multi-week feature attributable to episodes of dome growth. The ~ 50 day cycles were also identified in ground-based SO 2 data at SHV, confirming the validity of our analysis and further corroborating the presence of this cycle at the volcano. In addition a 12 day cycle was identified in the OMI data, previously attributed to variable lava effusion rates on shorter timescales. OMI data also display a one week (7–8 days) cycle attributable to cyclical variations in viewing angle resulting from the orbital characteristics of the Aura satellite. Longer period cycles possibly relating to magma intrusion were identified in the OMI record (102-, 121-, and 159 days); in addition to a 238-day cycle identified in the MODIS data corresponding to periodic destabilisation of the lava dome. Through the analysis of reconstructions generated from cycles identified in the OMI and MODIS data, periods of unrest were identified, including the major dome collapse of 20th May 2006 and significant explosive event of 3rd January 2009. Our analysis confirms the potential for identification of cyclical volcanic activity through combined analysis of satellite data, which would be of particular value at poorly monitored volcanic systems.

Proxies for estimating nucleation mode number concentrations and further simplification for their use with satellite data have been presented in Kulmala et al. (2011). In this paper we discuss the underlying assumptions for these simplifications and evaluate the resulting proxies over an area in South Africa based on a comparison with a suite of ground-based measurements available from four different stations. The proxies are formulated in terms of sources (concentrations of precursor gases (NO2 and SO2) and UVB radiation intensity near the surface) and a sink term related to removal of the precursor gases due to condensation on pre-existing aerosols. A-Train satellite data are used as input to compute proxies. Both the input data and the resulting proxies are compared with those obtained from ground-based measurements. In particular, a detailed study is presented on the substitution of the local condensation sink (CS) with satellite aerosol optical depth (AOD), which is a column-integrated parameter. One of the main factors affecting the disagreement between CS and AOD is the presence of elevated aerosol layers. Overall, the correlation between proxies calculated from the in situ data and observed nucleation mode particle number concentrations (Nnuc) remained low. At the time of the satellite overpass (13:00–14:00 LT) the highest correlation is observed for SO2/CS (R2 = 0.2). However, when the proxies are calculated using satellite data, only NO2/AOD showed some correlation with Nnuc (R2 = 0.2). This can be explained by the relatively high uncertainties related especially to the satellite SO2 columns and by the positive correlation that is observed between the ground-based SO2 and NO2 concentrations. In fact, results show that the satellite NO2 columns compare better with in situ SO2 concentration than the satellite SO2 column. Despite the high uncertainties related to the proxies calculated using satellite data, the proxies calculated from the in situ data did not better predict Nnuc. Hence, overall improvements in the formulation of the proxies are needed.

People in central-eastern China are suffering from severe air pollution of nitrogen oxides. Top-down approaches have been widely applied to estimate the ground concentrations of NO2 based on satellite data. In this paper, a one-year dataset of tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI) together with ambient monitoring station measurements and meteorological data from May 2013 to April 2014, are used to estimate the ground level NO2. The mean values of OMI tropospheric NO2 columns show significant geographical and seasonal variation when the ambient monitoring stations record a certain range. Hence, a geographically and temporally weighted regression (GTWR) model is introduced to treat the spatio-temporal non-stationarities between tropospheric-columnar and ground level NO2. Cross-validations demonstrate that the GTWR model outperforms the ordinary least squares (OLS), the geographically weighted regression (GWR), and the temporally weighted regression (TWR), produces the highest R2 (0.60) and the lowest values of root mean square error mean (RMSE), absolute difference (MAD), and mean absolute percentage error (MAPE). Our method is better than or comparable to the chemistry transport model method. The satellite-estimated spatial distribution of ground NO2 shows a reasonable spatial pattern, with high annual mean values (>40 μg/m3), mainly over southern Hebei, northern Henan, central Shandong, and southern Shaanxi. The values of population-weight NO2 distinguish densely populated areas with high levels of human exposure from others.

Surface NO2 volume mixing ratio (VMR) at a specific time (13:45 Local time) (NO2 VMRST) and monthly mean surface NO2 VMR (NO2 VMRM) are estimated for the first time using three regression models with Ozone Monitoring Instrument (OMI) data in four metropolitan cities in South Korea: Seoul, Gyeonggi, Daejeon, and Gwangju. Relationships between the surface NO2 VMR obtained from in situ measurements (NO2 VMRIn-situ) and tropospheric NO2 vertical column density obtained from OMI from 2007 to 2013 were developed using regression models that also include boundary layer height (BLH) from Atmospheric Infrared Sounder (AIRS) and surface pressure, temperature, dew point, and wind speed and direction. The performance of the regression models is evaluated via comparison with the NO2 VMRIn-situ for two validation years (2006 and 2014). Of the three regression models, a multiple regression model shows the best performance in estimating NO2 VMRST and NO2 VMRM. In the validation period, the average correlation coefficient (R), slope, mean bias (MB), mean absolute error (MAE), root mean square error (RMSE), and percent difference between NO2 VMRIn-situ and NO2 VMRST estimated by the multiple regression model are 0.66, 0.41, −1.36 ppbv, 6.89 ppbv, 8.98 ppbv, and 31.50%, respectively, while the average corresponding values for the other two models are 0.75, 0.41, −1.40 ppbv, 3.59 ppbv, 4.72 ppbv, and 16.59%, respectively. All three models have similar performance for NO2 VMRM, with average R, slope, MB, MAE, RMSE, and percent difference between NO2 VMRIn-situ and NO2 VMRM of 0.74, 0.49, −1.90 ppbv, 3.93 ppbv, 5.05 ppbv, and 18.76%, respectively.

The relevance of studying various forms of deviant behavior in a legal state is due to a crisis of socio-economic relations, which is aggravated by the growth of specific offences that directly affect the stability of social, economic and legal systems. The aim of the study was to explore the relationship between the misery index and the crime rate in the Russian Federation as one of the forms of deviant behavior. The model of the pairwise factor analysis was used to determine the correlation between selected types of crime and the misery index (including the additional relationship between the inflation rate, and unemployment, and the interest rate separately), establishing its focus and quantification. The results indicate that there is (1) a longterm (direct) average relationship between the misery index and the overall crime rate, theft and economic crimes; (2) direct high dependence between the misery index and drug trafficking. Additionally, it was revealed (3) direct high relationship between interest rates and overall crime rates, theft and economic crimes, as well as (4) a strong influence of unemployment on arms trafficking. The findings of this study can be used as recommendations for financial regulation of social, economic and legal processes. Актуальность изучения различных форм девиантного поведения в правовом государстве обусловлена кризисом социально-экономических отношений, который усиливается на фоне роста отдельных правонарушений, непосредственно воздействующих на устойчивость социальной, экономической и правовой систем. Целью данного исследования было изучение взаимосвязи между индексом несчастья5 и уровнем преступности в России как одной из форм девиантного поведения. Модель парного коэффициента анализа была использована авторами для определения наличия связи между отобранными видами преступности и индексом несчастья (включая дополнительный анализ связи между показателями инфляции и безработицы, значениями процентной ставки по отдельности), установления ее направленности и количественной оценки. Результаты работы указывают на то, что существуют следующие закономерности: 1) долгосрочная прямая средняя взаимосвязь между индексом несчастья и общим уровнем преступности, хищениями чужого имущества и экономическими преступлениями; 2) прямая высокая зависимость – между индексом несчастья и незаконным оборотом наркотиков; дополнительно была выявлена 3) прямая высокая взаимосвязь между значениями процентной ставки и общего уровня преступности, хищений чужого имущества и экономических преступлений; 4) сильное влияние уровня безработицы на незаконный оборот оружия. Результаты исследования могут быть использованы в качестве рекомендаций по финансовому регулированию социальных, экономических и правовых процессов. Работа выполнена в рамках исследований, выполненных за счет бюджетных средств по государственному заданию Финуниверситета 2017 года (проект AAAA-A17-117060110148-8)

El Código internacional para la Protección de los Buques y de las Instalaciones Portuarias (Código PBIP o ISPS) es un reglamento adoptado, por la Organización Marítima Internacional (OMI) cuyo fin es la construcción de un marco de cooperación internacional de detección de amenazas contra la protección tanto de las instalaciones portuarias como de los buques y adoptar medidas preventivas frente a ellas. En esteTrabajo de Fin de Grado se habla sobre los objetivos con los que fue creado dicho código, se analizan algunos ejemplos de su aplicación en el buque “Bencomo Express” y se comentan los ejercicios que deben realizarse periódicamente para preparar a la tripulación ante acontecimientos que puedan afectar a la protección del buque. Finalmente, hay un apartado dedicado al terrorismo marítimo y a las medidas que dicho reglamento promulga ante situaciones terroristas.

La Organización Marítima Internacional (OMI) adoptó una enmienda al Capítulo V del Convenio Internacional para la Salvaguarda de la Vida Humana en el Mar de 1974 (SOLAS), que introduce nuevas obligaciones de notificación de posición de los buques SOLAS. El Capítulo V del Reglamento SOLAS, relativo a la identificación y seguimiento a larga distancia (LRIT), se refiere a un sistema que exige que los buques transmitan automáticamente su identidad, posición y fecha / hora de la posición comunicada. Las Normas de Desempeño de la OMI para el LRIT (MSC.263 (84)) estipulan además que el sistema LRIT a bordo debe ser capaz de transmitir automáticamente y sin intervención humana la información LRIT del buque a intervalos de 6 horas. Los objetivos de este TFG incluyen una mejor comprensión de la arquitectura del sistema LRIT, de su funcionamiento y de cómo el uso de diferentes tipos datos combinados de diferentes sistemas pueden ser útiles para llevar a cabo un mejor seguimiento de lo que suceda en las aguas mundiales.

We validate the Ozone Monitoring Instrument (OMI) Ozone Profile (PROFOZ) product from October 2004 through December 2014 retrieved by the Smithsonian Astrophysical Observatory (SAO) algorithm against ozonesonde observations. We also evaluate the effects of OMI row anomaly (RA) on the retrieval by dividing the dataset into before and after the occurrence of serious OMI RA, i.e., pre-RA (2004–2008) and post-RA (2009–2014). The retrieval shows good agreement with ozonesondes in the tropics and midlatitudes and for pressure ∼ 50 hPa after applying OMI averaging kernels to ozonesonde data. The MBs of the stratospheric ozone column (SOC, the ozone column from the tropopause pressure to the ozonesonde burst pressure) are within 2 % with SDs of ∼ 50 hPa. The SOC MBs increase up to 3 % with SDs as great as 6 % and the TOC SDs increase up to 30 %. The comparison generally degrades at larger solar zenith angles (SZA) due to weaker signals and additional sources of error, leading to worse performance at high latitudes and during the midlatitude winter. Agreement also degrades with increasing cloudiness for pressure > ∼ 100 hPa and varies with cross-track position, especially with large MBs and SDs at extreme off-nadir positions. In the tropics and midlatitudes, the post-RA comparison is considerably worse with larger SDs reaching 2 % in the stratosphere and 8 % in the troposphere and up to 6 % in TOC. There are systematic differences that vary with latitude compared to the pre-RA comparison. The retrieval comparison demonstrates good long-term stability during the pre-RA period but exhibits a statistically significant trend of 0.14–0.7 % year−1 for pressure

In this study we present an analysis of spatio–temporal variability of monthly averaged Vertical Tropospheric Columns (VTCs) of NO2 over Pakistan using OMI (ozone monitoring instrument) dataset from December 2004 to November 2008. The results have shown significant spatial and temporal variability of NO2 column values over the study region. Four NO2 hotspots and a high density corridor were identified within the study region. The main sources of NO2 emissions in these areas were also investigated. During the study period, an average value of NO2 was observed to be 1.102 ± 0.081 × 1015 molecules/cm2, with an increasing trend of 3.29% per year. Twin cities of Islamabad/Rawalpindi, Lahore, Dera Ghazi Khan and Karachi have shown positive trends of 44.10%, 23.48%, 31.40%, and 32.32% per year respectively. Karachi has shown the highest and the lowest mean monthly average values of 11.33 × 1015 molecules/cm2 and 0.98 × 1015 molecules/cm2 respectively. Air mass trajectories for hotspot regions have been used to track possible long–range transport of NO2.

For the first time, maps of surface concentration of nitrogen dioxide (NO2) are presented for the Colombian territory. NO2 surface concentrations for the year 2007 are inferred based on two sources of tropospheric NO2 column data: (1) a simulation using a three-dimensional global model (GEOS-Chem) and (2) measurements made by the ozone monitoring instrument (OMI) onboard the NASA Aura satellite. Results show monthly averages between 0.1 and 6 ppbv. We compare these inferred values to corrected ground measurements of NO2. We find correlation coefficients of up to 0.91 between the inferred data and the corrected observational data. A significant source of NO2 is biomass burning, which can be diagnosed by data of fire radiative power (FRP) from the Monitoring of Atmospheric Composition and Climate (MACC) reanalysis. We find a close relationship between high values of inferred NO2 surface concentrations and biomass burning for a large area which encompasses the departments of Caquetá, Meta, Guaviare, Vichada, and Putumayo.