Source apportionment of PM2.5 using organic/inorganic markers and emission inventory evaluation in the East Mediterranean-Middle East city of Beirut.

Source contributions to PM2.5 concentrations were evaluated in Greater Beirut (Lebanon), a typical East Mediterranean-Middle East (EMME) city, using Positive Matrix Factorization with two approaches. The first approach included only inorganic species (PMF-trad) and the other approach added organic markers (PMF-org). PMF-org identified 4 additional sources, and large discrepancies in contributions were observed for some major sources found in both approaches, highlighting the importance of including organic markers. The traffic factor was underestimated in PMF-trad by 2 to 7 folds. Moreover, results showed that this city is prone to high desert dust concentrations originating from uncontrollable dust storm events, like all cities in the Middle East. A PM2.5 mitigation plan taking into account the potency of the identified sources was developed. Sources like diesel generators or traffic presented smaller contributions in term of mass compared to desert dust, however the health impact of the latter is relatively small and actions should target sources with the highest potency. Local emission inventories in the EMME region are scarce and studies typically rely on global emission inventories for local air quality management plans, but these inventories significantly underestimate Beirut's road transport emissions by more than an order of magnitude.

Characteristics and source apportionment of atmospheric volatile organic compounds in Beijing, China.

This paper focused on VOCs and their source apportionment in urban Beijing. Our monitoring measured 52 VOCs in July 2014 and January 2015. The concentration of VOCs was in the range of 14.5~95.2 ppb in July and 2.1~93.1 ppb in January, with the top five compounds of toluene (10.7%), ethane (6.9%), ethylene (6.3%), n-butane (5.7%), and propane (5.6%) in July and ethylene (14.7%), n-butane (14.2%), ethane (9.6%), propylene (8.0%), toluene (7.9%), and benzene (6.9%) in January. The ratio of VOCs to CO reached 0.059 in July and 0.022 in January on average. These differences implied a potential seasonal difference in the VOC source contribution. Then, we conducted a source apportionment study based on 21 major VOCs and CO by using probabilistic matrix factorization (PMF) receptor model. According to the similarity between the PMF analysis profiles and the known source profiles, combustion sources, petrochemical industry sources, solvent utilization sources, and gasoline evaporation sources were identified. The correlation coefficient (R) between the PMF analysis profile and the source profile reached 0.68~0.87 in July and 0.53~0.92 in January. The better apportionment performance in July was mainly due to the use of intensive VOC observations at a 3-h resolution. When we conducted another PMF source apportionment for July based on 12-h resolved concentration input, the R values decreased to 0.47~0.73. Thus, the PMF model depends heavily on the sample number of concentration inputs, and intensive observation is more propitious. Our PMF apportionment results showed that combustion sources, petrochemical industry, solvent utilization, gasoline evaporation, and other sources contributed ambient VOCs in Beijing urban areas of 13.7 ppb, 5.1 ppb, 7.7 ppb, 12.8 ppb, and 3.3 ppb in July and 13.2 ppb, 2.0 ppb, 5.7 ppb, 6.6 ppb, and 1.0 ppb in January, respectively, on a monthly average. These apportionment results match well with the 2013 VOC emission inventory calculated by this study, but also presented significant seasonal differences in the petrochemical industry and gasoline evaporation, in which VOC emissions strongly respond to environmental temperature.

Differences between measured and reported volatile organic compound emissions from oil sands facilities in Alberta, Canada.

Large-scale oil production from oil sands deposits in Alberta, Canada has raised concerns about environmental impacts, such as the magnitude of air pollution emissions. This paper reports compound emission rates (E) for 69-89 nonbiogenic volatile organic compounds (VOCs) for each of four surface mining facilities, determined with a top-down approach using aircraft measurements in the summer of 2013. The aggregate emission rate (aE) of the nonbiogenic VOCs ranged from 50 ± 14 to 70 ± 22 t/d depending on the facility. In comparison, equivalent VOC emission rates reported to the Canadian National Pollutant Release Inventory (NPRI) using accepted estimation methods were lower than the aE values by factors of 2.0 ± 0.6, 3.1 ± 1.1, 4.5 ± 1.5, and 4.1 ± 1.6 for the four facilities, indicating underestimation in the reported VOC emissions. For 11 of the combined 93 VOC species reported by all four facilities, the reported emission rate and E were similar; but for the other 82 species, the reported emission rate was lower than E The median ratio of E to that reported for all species by a facility ranged from 4.5 to 375 depending on the facility. Moreover, between 9 and 53 VOCs, for which there are existing reporting requirements to the NPRI, were not included in the facility emission reports. The comparisons between the emission reports and measurement-based emission rates indicate that improvements to VOC emission estimation methods would enhance the accuracy and completeness of emission estimates and their applicability to environmental impact assessments of oil sands developments.

The creation and validation of the Jamaica personality disorder inventory / Creación y validación del inventario de trastornos de la personalidad en Jamaica

OBJECTIVE: To describe the creation and validation of the Jamaica Personality Disorder Inventory (JPDI) screening questionnaire. METHOD: Using the phenomenological triad of power management, dependency and psychosexual issues, drafts of the JPDI were piloted on patients from psychiatric and medical wards. The JPDI consisted of 38 close-ended, yes/no questions. Validation was conducted in a sample of 200 patients, using the International Personality Disorder Examination-Screening Instrument (IPDE-S), the Brief Screen for Depression and consultant psychiatrists' Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) personality disorder interview. Construct validity was assessed through principal component factor analysis; Spearman correlation was used to assess criterionrelated and discriminant validity; Cronbach's alpha was used to assess reliability of the entire scale as well as the resulting factors. The Multitrait Multimethod Matrix (MTMM) was used to assess discriminant and construct validity. RESULTS: Factor analysis revealed eight clusters consisting of 30 of the 38 questions, which had close congruence with the clinical triad. Cronbach's alpha for the entire scale was α = 0.79, ranging from a high 0.70 to 0.82 to low 0.63 to 0.45. The JPDI exhibited a sensitivity of 95.06% and a specificity of 67.71%. Significant correlation of scores for the JPDI and IPDE-S (r = 0.432, p = 0.000) and the JPDI and the DSM IV-TR diagnosis (r = 0.598, p = 0.000) established concurrent validity for the JPDI. Correlations (r = 0.293, p = 0.000) suggested that the JPDI possessed predictive validity. The complete sample matrix of the MTMM provided evidence of both convergent and discriminant validity, and thereby, construct validity. CONCLUSION: The JPDI demonstrated reliability, and criterion-related and discriminant validity.

OBJETIVO: Describir la creación y validación del cuestionario de tamizaje del Inventario de Trastornos de la Personalidad en Jamaica (JPDI). MÉTODO: Usando la tríada fenomenológica de manejo del poder, dependencia y problemas psicosexuales, se realizaron pruebas pilotos usando versiones p rovisionales del JPDI con pacientes de salas médicas y psiquiátricas. El JPDI constaba de 38 preguntas cerradas, del tipo que requieren sí o no. La validación se realizó con una muestra de 200 pacientes, usando el Instrumento de Tamizaje del Examen Internacional de los Trastornos de Personalidad (IPDE-S), la Prueba Breve para la Depresión, y el Manual Diagnóstico y Estadístico de los Trastornos Mentales, cuarta edición (DSM-IV) de los psiquiatras consultantes, para entrevistas de trastornos de personalidad. La validez de constructo se evaluó a través de análisis factorial de componentes principales. El coeficiente de correlación de Spearman se utilizó para evaluar la validez de criterio y la validez discriminante. El coeficiente Alfa de Cronbach fue utilizado para evaluar la fiabilidad de toda la escala, así como los factores resultantes. La matriz multirasgo-multimétodo (MTMM) fue utilizada para evaluar la validez de constructo y la validez discriminante. RESULTADOS: El análisis factorial reveló ocho clústeres que constaban de 30 de las 38 preguntas, las cuales presentaban una estrecha congruencia con la tríada clínica. El Alfa de Cronbach para toda la escala fue α = 0.79, fluctuando desde valores altos de 0.70 a 0.82 hasta valores bajos de 0.63 a 0.45. El inventario JPDI mostró una sensibilidad de 95.06% y una especificidad de 67.71%. La correlación significativa de las puntuaciones para el JPDI y el IPDE-S (r = 0.432, p = 0.000) y el JPDI y el diagnóstico de DSM IV-TR (r = 0.598, p = 0.000) estableció una validez concurrente para el JPDI. Las correlaciones (r = 0.293, p = 0.000) sugirieron que el JPDI poseía validez predictiva. La matriz completa de la muestra de la MTMM proporcionó evidencia tanto de la validez discriminante como de la validez convergente, y por ende, de la validez de constructo. CONCLUSIÓN: El inventario JPDI demostró fiabilidad, así como validez de criterio y validez discriminante.