11 research outputs found
Update on a Continuing Saga: Eelgrass and Green Crabs in Casco Bay, Maine (Poster)
https://digitalcommons.usm.maine.edu/cbep-graphics-maps-posters/1035/thumbnail.jp
Estimación de la concentración media diaria de material particulado fino en la región del Complejo Industrial y Portuario de Pecém, Ceará, Brasil
A exposição ao material particulado fino (MP2,5) está associada a inúmeros
desfechos à saúde. Desta forma, monitoramento da concentração ambiental
do MP2,5 é importante, especialmente em áreas amplamente industrializadas,
pois abrigam potenciais emissores do MP2,5 e de substâncias com potencial de
aumentar a toxicidade de partículas já suspensas. O objetivo desta pesquisa é estimar a concentração diária do MP2,5 em três áreas de influência do
Complexo Industrial e Portuário do Pecém (CIPP), Ceará, Brasil. Foi aplicado
um modelo de regressão não linear para a estimativa do MP2,5, por meio de
dados de profundidade óptica monitorados por satélite. As estimativas foram
realizadas em três áreas de influência (Ai) do CIPP (São Gonçalo do Amarante – Ai I, Paracuru e Paraipaba – Ai II e Caucaia – Ai III, no período de
2006 a 2017. As médias anuais das concentrações estimadas foram inferiores
ao estabelecido pela legislação nacional em todas as Ai (8µg m-3). Em todas as
Ai, os meses referentes ao período de seca (setembro a fevereiro) apresentaram
as maiores concentrações e uma predominância de ventos leste para oeste. Os
meses que compreendem o período de chuva (março a agosto) apresentaram as
menores concentrações e ventos menos definidos. As condições meteorológicas
podem exercer um papel importante nos processos de remoção, dispersão ou
manutenção das concentrações do material particulado na região. Mesmo com
baixas concentrações estimadas, é importante avaliar a constituição das partículas finas dessa região, bem como sua possível associação a efeitos adversos à
saúde da população local.Exposure to fine particulate matter (PM2.5) is associated with numerous negative health outcomes.
Thus, monitoring the environmental concentration of PM2.5 is important, especially in heavily
industrialized areas, since they harbor potential
emitters of PM2.5 and substances with the potential
to increase the toxicity of already suspended particles. This study aims to estimate daily concentrations of PM2.5 in three areas under the influence of
the Industrial and Port Complex of Pecém (CIPP),
Ceará State, Brazil. A nonlinear regression model
was applied to estimate PM2.5, using satellitemonitored optical depth data. Estimates were
performed in three areas of influence (Ai) of the
CIPP (São Gonçalo do Amarante – AiI, Paracuru
and Paraipaba – AiII, and Caucaia – AiIII), from
2006 to 2017. Estimated mean annual concentrations were lower than established by Brazil’s national legislation in all three Ai (8µg m-³). In all
the Ai, the months of the dry season (September to
February) showed the highest concentrations and
a predominance of east winds, while the months
of the rainy season (March to August) showed
the lowest concentrations and less defined winds
Weather conditions can play an important role in
the removal, dispersal, or maintenance of concentrations of particulate matter in the region. Even
at low estimated concentrations, it is important
to assess the composition of fine participles in this
region and their possible association with adverse
health outcomes in the local population.La exposición al material particulado fino (MP2,5)
está asociada a innumerables problemas de salud.
Por ello, la supervisión de la concentración ambiental del MP2,5 es importante, especialmente en
áreas ampliamente industrializadas, puesto que
albergan potenciales emisores de MP2,5 y de sustancias con potencial de aumentar la toxicidad
de partículas ya suspendidas. El objetivo de esta
investigación es estimar la concentración diaria
del MP2,5 en tres áreas de influencia del Complejo Industrial y Portuario de Pecém (CIPP), Ceará,
Brasil. Se aplicó un modelo de regresión no lineal
para la estimación del MP2,5, mediante datos de
profundidad óptica supervisados por satélite. Las
estimaciones fueron realizadas en tres áreas de influencia (Ai) del CIPP (São Gonçalo do Amarante
– Ai I, Paracuru y Paraipaba – Ai II y Caucaia
– Ai III en el período de 2006 a 2017. Las medias
anuales de las concentraciones estimadas fueron
inferiores a lo establecido por la legislación nacional en todas las Ai (8µg m-³). En todas las Ai, los
meses referentes al período de sequía (de setiembre
a febrero) presentaron las mayores concentraciones y una predominancia de vientos este a oeste,
los meses que comprenden el período de lluvia
(marzo a agosto) presentaron las menores concentraciones y vientos menos definidos. Las condiciones meteorológicas pueden ejercer un papel importante en los procesos de eliminación, dispersión o
mantenimiento de las concentraciones del material
particulado en la región. Incluso con bajas concentraciones estimadas es importante que se evalúe la
constitución de las partículas finas de esta región,
así como su posible asociación con efectos adversos
para la salud de la población local
Research Reference Document 98/3 : Anadromous Fish Restoration in the Androscoggin River Watershed; 1998 Program Results; A Report on the Operation of the Brunswick Fishway
https://digitalmaine.com/dmr_research_reference_documents/1023/thumbnail.jp
Research Reference Document 99/4 : Anadromous Fish Restoration in the Androscoggin River Watershed; 1998 Program Results; 1999 Report on the Operation of the Brunswick Fishway
https://digitalmaine.com/dmr_research_reference_documents/1024/thumbnail.jp
Reproducibility assessment and uncertainty quantification in subjective dust source mapping
Data quality control considerations in multivariate environmental monitoring: experience of the French coastal network SOMLIT
International audienceIntroduction While crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented. Methods With a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks (<20 laboratories) and multivariate datasets. Finally, the expanded uncertainty of measurement for 20 environmental variables routinely measured by SOMLIT from discrete sampling—including Essential Ocean Variables—is provided. Results, Discussion, Conclusion The examination of the temporal variations (2001–2021) in the repeatability, reproducibility, and trueness of the SOMLIT network over time confirms the essential role of ILC exercises as a tool for the continuous improvement of data quality in environmental monitoring datasets
Table_1_Data quality control considerations in multivariate environmental monitoring: experience of the French coastal network SOMLIT.xls
IntroductionWhile crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented.MethodsWith a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks (Results, Discussion, ConclusionThe examination of the temporal variations (2001–2021) in the repeatability, reproducibility, and trueness of the SOMLIT network over time confirms the essential role of ILC exercises as a tool for the continuous improvement of data quality in environmental monitoring datasets.</p
DataSheet_1_Data quality control considerations in multivariate environmental monitoring: experience of the French coastal network SOMLIT.docx
IntroductionWhile crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented.MethodsWith a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks (Results, Discussion, ConclusionThe examination of the temporal variations (2001–2021) in the repeatability, reproducibility, and trueness of the SOMLIT network over time confirms the essential role of ILC exercises as a tool for the continuous improvement of data quality in environmental monitoring datasets.</p