Assessment of livestock greenhouse gases in Colombia between 1995 and 2015.

The livestock sector in Colombia significantly participates in national economic dynamics but makes significant worldwide contributions to greenhouse gas emissions. Hence, climate change mitigation in this sector is essential. This study aims to assess the greenhouse gas in the livestock sector. The results are reported in methane emissions (CH4) and nitrous oxide (N2O) from enteric fermentation, and N2O by manure management based on the information from the Emission Database for Global Atmospheric Research (EDGAR), in all cases expressed as dioxide of carbon (CO2eq). The emissions obtained from the EDGAR database for 2015 were proportional to the values of the National Inventory of Greenhouse Gases published by the Institute of Hydrology, Meteorology, and Environmental Studies (IDEAM) in 2016. Colombia is the 12th on global, 4th in America and 2nd in South America position by livestock GHG emission, and is the dominant source in all economic sector. The results showed higher records for CH4 emissions during the years 2010 and 2015, while the N2O emissions were higher during 2015. The regions with the highest emissions of CH4 and N2O corresponded to the northwestern area of Colombia. The Spearman correlation test showed a positive correlation between the CH4 emissions, and the age groups studied. The post hoc analysis of the Kruskal-Wallis test showed a more significant influence on CH4 emissions.

Aerobiological modelling II: A review of long-range transport models.

The long-range atmospheric transport models of pollen and fungal spores require four modules for their development: (i) Meteorological module: which contain the meteorological model, and it can be coupled to transport model with the same output configuration (spatio-temporal resolution), or uncoupled does not necessarily have the same output parameters. (ii) Emission module: settles the mass fluxes of bioaerosol, it can be done with a complex parameterization integrating phenological models and meteorological factors or by a simple emission factor. (iii) Sources of emission module, specifically refers to forestry/agronomy maps or, in the case of herbs and fungi, to potential geographical areas of emission. Obtaining the highest possible resolution in these maps allows establishing greater reliability in the modelling. (iv) Atmospheric transport module, with its respective established output parameters. The review and subsequent analysis presented in this article, were performed on published electronic scientific articles from 1998 to 2016. Of a total of 101 models applied found in 64 articles, 33 % performed forward modelling (using 15 different models) and 67 % made backward modelling (with three different models). The 88 % of the cases were applied to pollen (13 taxa) and 12 % to fungal spores (3 taxa). Regarding the emission module, 22 % used parametrization (four different parameters) and 10 % emission factors. The most used transport model was HYSPLIT (59 %: 56 % backward and 3 % forward) following by SILAM 10 % (all forward). Main conclusions were that the models of long-range transport of pollen and fungal spores had high technical-scientific requirements to development and that the major limitations were the establishment of the flow and the source of the emission.

Noise Levels and Sleep in a Surgical ICU.

Sleep is disturbed in critically ill patients and is a frequently overlooked complication. The aim of our study is to evaluate the impact of sound levels in our surgical ICU on our patients' sleep on the first night of admission. The study was performed in a tertiary care university hospital, in a 12-bed surgical ICU. Over a 6-week period, a total of 148 adult, non-intubated and non-sedated patients completed the study. During this six-week period, sound levels were continuously measured using a type II sound level meter. Sleep quality was evaluated using the Richards-Campbell Sleep Questionnaire (RCSQ), which was completed both by patients and nurses on the first morning after admission. A non-significant correlation was found between night sound levels and sleep quality in the overall sample (r = -1.83, 95% CI; -4.54 to 0.88, p = 0.19). After multivariable analysis, a correlation was found between higher sound levels at night and lower RCSQ evaluations (r = -3.92, 95% CI; -7.57 to -0.27, p = 0.04). We found a significant correlation between lower sound levels at night and a better quality of sleep in our patients; for each 1 dBA increase in LAFeq sound levels at night, patients scored 3.92 points lower on the sleep questionnaire.

Aerobiological modeling I: A review of predictive models.

The present work is the first of two reviews on applied modeling in the field of aerobiology. The aerobiological predictive models for pollen and fungal spores, usually defined as predictive statistical models, will, amongst other objectives, forecast airborne particles' concentration or dynamical behavior of the particles. These models can be classified into Observation Based Models (OBM), Phenological Based Models (PHM), or OTher Models (OTM). The aim of this review is to show, analyze and discuss the different predictive models used in pollen and spore aerobiological studies. The analysis was performed on published electronic scientific articles from 1998 to 2016 related to the type of model, the taxa and the modelled parameters. From a total of 503 studies, 55.5% used OBM (44.8% on pollen and 10.7% on fungal spores), 38.5% PHM (all on pollen) and 6% OTM (5.4% on pollen and 0.6% on fungal spores). OBM have been used with high frequency to forecast concentration. The most frequent model of OBM was linear regression (18.5% out of 503) on pollen and artificial neural networks (4.6%) on fungal spores. In the PHM, the principal use was to characterize the main pollen season (flowering season) based on the model of growth degree days. Finally, OTM have been used to estimate concentrations at unmonitored areas. Olea (14,5%) on pollen and Alternaria (4,8%) on fungal spores were the taxa most frequently modelled. Daily concentration was the most modelled parameter by OBM (25.2%) and season start day by PHM (35.6%). The PHM approaches include greater model diversity and use fewer independent variables than OBM. In addition, PHM show to be easier to apply than OBM; however, the wide range of criteria to define the parameters to use in PHM (e.g.: pollination start day) makes that each model is used with a lesser frequency than other models.

Logistic regression models for predicting daily airborne Alternaria and Cladosporium concentration levels in Catalonia (NE Spain).

Alternaria and Cladosporium are the most common airborne fungal spores responsible for health problems, as well as for crop pathologies. The study of their behavior in the air is a necessary step for establishing control and prevention measures. The aim of this paper is to develop a logistic regression model for predicting the daily concentrations of airborne Alternaria and Cladosporium fungal spores from meteorological variables. To perform the logistic regression analysis, the concentration levels are binarized using concentration thresholds. The fungal spore data have been obtained at eight aerobiological monitoring stations of the Aerobiological Network of Catalonia (NE Spain). The meteorological data used were the maximum and minimum daily temperatures and daily rainfall provided by the meteorological services. The relationship between the meteorological variables and the fungal spore levels has been modeled by means of logistic regression equations, using data from the period 1995-2012. Values from years 2013-2014 were used for validation. In the case of Alternaria, three equations for predicting the presence and the exceedance of the thresholds 10 and 30 spores/m3 have been established. For Cladosporium, four equations for the thresholds 200, 500, 1000, and 1500 spores/m3 have been established. The temperature and cumulative rainfall in the last 3 days showed a positive correlation with airborne fungal spore levels, while the rain on the same day had a negative correlation. Sensitivity and specificity were calculated to measure the predictive power of the model, showing a reasonable percentage of correct predictions (ranging from 48 to 99%). The simple equations proposed allow us to forecast the levels of fungal spores that will be in the air the next day, using only the maximum and minimum temperatures and rainfall values provided by weather forecasting services.

Effectiveness of a visual noise warning system on noise levels in a surgical ICU: A quality improvement programme.

BACKGROUND: The effects of noise are harmful to patients in the ICU environment, and the latter are particularly noisy places. High noise levels seem to be a factor in sleep disturbance, which can, in turn, result in increased morbidity. LOCAL PROBLEM: High noise levels are a recognised problem in ICUs worldwide. OBJECTIVE(S): The goal was to estimate the effect of a visual noise-warning system on noise levels in a surgical ICU before and after its implementation. DESIGN: A quality improvement initiative. SETTING: A 12-bedded surgical ICU in a tertiary care university hospital. PATIENTS: A total of 148 adult nonintubated and nonsedated patients completed the study, during a 6-week period. INTERVENTION: Noise levels were continuously recorded using a Type II sound level meter for 6 weeks. The study was divided into three phases. The first 2 weeks, baseline noise levels were measured (phase I). In week 3 of the study, a visual noise warning system (SoundEar II) that changed colour depending on noise levels within the ICU was installed and implemented (phase II). The alarm system was set to light up green at levels below 55 dBA, orange at levels between 55 and 60 dBA and red at levels above 60 dBA. The device was switched off at the beginning of week 5 and the sound level meter continued recording noise levels for another 2 weeks (phase III). RESULTS: Mean night-time noise level was 55.98 dBA in the preintervention phase, 54.14 dB during the intervention, and 54.98 dBA in the postintervention phase. Mean noise level was reduced statistically significantly by 1.35 dBA, and there was a sustained reduction of 0.86 dBA from the baseline noise level 2 weeks after SoundEar II was switched off. CONCLUSION: Visual noise warning systems can be effective in achieving a reduction in noise levels in critical care units.

Noise level in a neonatal intensive care unit in Santa Marta - Colombia.

INTRODUCTION: The environment of neonatal intensive care units is influenced by numerous sources of noise emission, which contribute to raise the noise levels, and may cause hearing impairment and other physiological and psychological changes on the newborn, as well as problems with care staff. OBJECTIVE: To evaluate the level and sources of noise in the neonatal intensive care unit. METHODS: Sampled for 20 consecutive days every 60 seconds in A-weighting curves and fast mode with a Type I sound level meter. Recorded the average, maximum and minimum, and the 10th, 50th and 90th percentiles. The values are integrated into hours and work shift, and studied by analysis of variance. The sources were characterized in thirds of octaves. RESULTS: The average level was 64.00 ±3.62 dB(A), with maximum of 76.04 ±5.73 dB(A), minimum of 54.84 ±2.61dB(A), and background noise of 57.95 ±2.83 dB(A). We found four sources with levels between 16.8-63.3 dB(A). Statistical analysis showed significant differences between the hours and work shift, with higher values in the early hours of the day. CONCLUSION: The values presented exceed the standards suggested by several organizations. The sources identified and measured recorded high values in low frequencies.

INTRODUCCIÓN: El ambiente de las unidades de cuidado intensivo neonatal está influenciado por numerosas fuentes de emisión de ruido, que contribuyen a elevar los niveles de ruido y que pueden provocar deficiencias auditivas entre otras alteraciones fisiológicas y psicológicas sobre el neonato, así como problemas al personal asistencial cuando se exceden los niveles. OBJETIVO: Evaluar el nivel y fuentes de emisión del ruido en la unidad de cuidado intensivo neonatal. MÉTODOS: Se muestreo durante 20 días continuos cada 60 segundos en escala de ponderación frecuencias A y espacial fast, con un sonómetro tipo I, se registraron los parámetros acústicos de nivel medio, máximo y mínimo, y percentil 10, 50 y 90. Se integraron en periodos horarios y por turno, y se estudiaron mediante un análisis de varianza. Las fuentes se caracterizaron en tercios de octavas. RESULTADOS: El nivel medio reportado fue 64.00 ±3.62 dB(A), con máximo de 76.04 ±5.73 dB(A), mínimo de 54.84 ±2.61 dB(A) y ruido de fondo de 57.95 ±2.83 dB(A). Se identificaron cuatro fuentes con rango entre 16.8-63.3 dB(A). El análisis estadístico mostró diferencias significativas entre una media y otra con valores mayores en las primeras horas del día. CONCLUSIÓN: Los valores presentados superan los estándares sugerido por diversas organizaciones. Las fuentes identificadas y medidas registraron mayor aporte en las frecuencias bajas.

Noise level in a neonatal intensive care unit in Santa Marta - Colombia / Nivel de ruido de una unidad de cuidado intensivo neonatal en Santa Marta - Colombia

Abstract Introduction: The environment of neonatal intensive care units is influenced by numerous sources of noise emission, which contribute to raise the noise levels, and may cause hearing impairment and other physiological and psychological changes on the newborn, as well as problems with care staff. Objective: To evaluate the level and sources of noise in the neonatal intensive care unit. Methods: Sampled for 20 consecutive days every 60 seconds in A-weighting curves and fast mode with a Type I sound level meter. Recorded the average, maximum and minimum, and the 10th, 50th and 90th percentiles. The values are integrated into hours and work shift, and studied by analysis of variance. The sources were characterized in thirds of octaves. Results: The average level was 64.00 ±3.62 dB(A), with maximum of 76.04 ±5.73 dB(A), minimum of 54.84 ±2.61dB(A), and background noise of 57.95 ±2.83 dB(A). We found four sources with levels between 16.8-63.3 dB(A). Statistical analysis showed significant differences between the hours and work shift, with higher values in the early hours of the day. Conclusion: The values presented exceed the standards suggested by several organizations. The sources identified and measured recorded high values in low frequencies.

Resumen Introducción: El ambiente de las unidades de cuidado intensivo neonatal está influenciado por numerosas fuentes de emisión de ruido, que contribuyen a elevar los niveles de ruido y que pueden provocar deficiencias auditivas entre otras alteraciones fisiológicas y psicológicas sobre el neonato, así como problemas al personal asistencial cuando se exceden los niveles. Objetivo: Evaluar el nivel y fuentes de emisión del ruido en la unidad de cuidado intensivo neonatal. Métodos: Se muestreo durante 20 días continuos cada 60 segundos en escala de ponderación frecuencias A y espacial fast, con un sonómetro tipo I, se registraron los parámetros acústicos de nivel medio, máximo y mínimo, y percentil 10, 50 y 90. Se integraron en periodos horarios y por turno, y se estudiaron mediante un análisis de varianza. Las fuentes se caracterizaron en tercios de octavas. Resultados: El nivel medio reportado fue 64.00 ±3.62 dB(A), con máximo de 76.04 ±5.73 dB(A), mínimo de 54.84 ±2.61 dB(A) y ruido de fondo de 57.95 ±2.83 dB(A). Se identificaron cuatro fuentes con rango entre 16.8-63.3 dB(A). El análisis estadístico mostró diferencias significativas entre una media y otra con valores mayores en las primeras horas del día. Conclusión: Los valores presentados superan los estándares sugerido por diversas organizaciones. Las fuentes identificadas y medidas registraron mayor aporte en las frecuencias bajas.

Nivel de ruido en la unidad de cuidado intensivo adulto: Medición, estándares internacionales e implicancias sanitarias / Noise level in the intensive care unit for adults: measurement, international standards and health implications

Objetivo: Evaluar el nivel continuo equivalente de ruido en una unidad de cuidado intensivo adulto perteneciente a un hospital de la ciudad de Santa Marta con los niveles sugeridos por los estándares internacionales. Materiales y métodos: Se realizó un muestreo continuo durante 20 días registrando datos cada minuto con un sonómetro tipo I en un eje central de la unidad de cuidado intensivo adulto del hospital; los datos registrados correspondían a los valores máximos, mínimos y el nivel continuo equivalente de ruido en ponderación frecuencial A y el filtro de ponderación temporal Fast. Resultados: Se reporta que el nivel de ruido continuo equivalente varió entre 49 ­ 71 dBA con un valor máximo de 91,19 dBA y un mínimo de 46,65 dBA. El análisis de varianza infiere que el valor medio de ruido varía con la hora del día. Conclusiones: El nivel de ruido continuo equivalente presentado en la unidad de cuidado intensivo adulto es consistente con otros estudios similares, no obstante los valores presentados exceden los estándares internacionales de ruido sugeridos, generando una preocupación por los riesgos de exposición a los que se encuentran pacientes y personal médico de la unidad.

Objective: To assess the continuous equivalent noise level in an intensive care unit for adults that belongs to a hospital in the city of Santa Marta using the levels suggested by international standards. Materials and methods: A continuous sampling was done during 20 days where the data was recorded every minute by using a sound level meter type I in a central axis of the intensive care unit for adults in the hospital; the recorded data corresponded to the maximum, minimum values and the equivalent continuous level of noise on frequency weighting A and the Fast time weighting filter. Results: It was reported that the equivalent continuous noise level varied between 49-71 dBA with a maximum value of 91, 19 dBA and a minimum of 46, 65 dBA. The variance analysis infers that the mean value of noise varies according to the time of day. Conclusions: The level of equivalent continuous noise presented in the intensive care unit for adults is consistent with other similar studies; however, the displayed values exceed the international standards of noise suggested, which generates a concern about the risks of exposure for the patients as well as for the medical staff of the unit.

Análisis de los factores ambientales y ocupacionales en la concentración de aerobacterias en unidades de cuidado intensivo del Hospital Universitario Fernando Troconis, 2009 Santa Marta- Colombia / Analysis of occupational and environmental factors in the concentration of aerobacters in intensive care units of the Fernando Troconis Universitary Hospital, 2009 Santa Marta-Colombia

Introducción: La evaluación de la calidad biológica del aire de ambientes hospitalarios resulta de especial interés debido a que los pacientes puedan servir como una fuente de bacterias patógenas para el personal del hospital, los visitantes y otros pacientes, siendo relevante en unidades de asistencia especializadas en atención de patologías crónicas como cáncer, SIDA y pacientes con trasplante de órganos o con complicaciones severas en su estado de salud, y que requieren una intervención masiva para su tratamiento en salas de cirugía y/o unidades de cuidado intensivo. Evaluar la influencia de factores ambientales y de ocupación de la unidad en la concentración de aerobacterias de unidades de cuidado intensivo del Hospital Universitario Fernando Troconis. Materiales y Métodos: Se colectaron muestras triplicadas con agar selectivo para Staphylococcus spp. y Pseudomonas spp., en dos estaciones de cada una de las tres UCI, mediante impactador de 2 etapas ubicado a altura de1.5m y caudal constante (28.3l/min) durante 5min, incubándolas a 37°C por 48h. Los factores ambientales se registraron con anemómetro Kestrel 4500 y ocupación de la unidad mediante registro manual del número de pacientes y personal asistencial de la unidad. Resultados: La máxima concentración fue 979.9±31.3UFC/m3 y el máximo promedio, 315.6±59.7UFC/m3. Staphylococcus spp. Superaron la concentración de Pseudomonas spp. La máxima ocupación fue en UCI Adulto, mayor temperatura en UCI Pediátrica y humedad más baja en UCI Adulto. Discusión y Conclusiones: La concentración de aerobacterias superó valores reportados por estudios aerobiológicos hospitalarios, y presenta relaciones leves con temperatura y escasa o nula con ocupación de la unidad.

Introduction: Assessing of biological quality of air in hospital environments is of particular interest because patients can be a source of pathogenic bacteria for hospital staff, visitors and other patients. It is relevant in specialized care of chronic diseases like cancer, AIDS and organ transplant patients or severe health complications, which require massive intervention for treatment in the operating room and/or intensive care units. To evaluate the influence of environmental factors and intensive care unit occupancy in the concentration of aerobacteria in intensive care units of Fernando Troconis Universitary Hospital. Materials and Methods: Triplicate samples were collected with selective agar for Staphylococcus spp. and Pseudomonas spp. using two-stage cascade impactor located 1.5 m high and constant flow (28.3l/min) for five minutes, locating two stations in each of the three ICU; the collected samples were incubated at 37°C for 48 hours. Environmental factors were recorded with anemometer Kestrel 4500 and occupancy of the unit by manually recording the number of patients and health care personnel of the unit. Results: Maximum concentration was 979.9±31.3CFU/m3 and maximum average 315.6±59.7CFU/m3. Staphylococcus spp. exceeded the concentration of Pseudomonas spp. Maximum intensive care unit occupancy was in adult ICU, higher temperature in pediatric ICU and lower humidity in adult ICU. Discussion and Conclusions: Aerobacteria concentration exceeded values reported by other aerobiological studies in hospital also has little relationship with temperature and little or no with intensive care unit occupancy.