scholarly journals Environmental Heat Exposure and Heat-Related Symptoms in United States Coast Guard Deepwater Horizon Disaster Responders

2018 ◽  
Vol 13 (03) ◽  
pp. 561-569
Author(s):  
Elizabeth A. Erickson ◽  
Lawrence S. Engel ◽  
Kate Christenbury ◽  
Laura Weems ◽  
Erica G. Schwartz ◽  
...  
Keyword(s):  
Global Climate ◽  
Heat Exposure ◽  
Error Variance ◽  
Deepwater Horizon ◽  
Coast Guard ◽  
Heat Index ◽  
Climate Data ◽  
Weather Extremes ◽  
Us Coast Guard ◽  
Survey Responses

ABSTRACTObjectivesThe response to the 2010 Deepwater Horizon oil spill was impacted by heat. We evaluated the association between environmental heat exposure and self-reported heat-related symptoms in US Coast Guard Deepwater Horizon disaster responders.MethodsUtilizing climate data and postdeployment survey responses from 3648 responders, we assigned heat exposure categories based on both wet bulb globe temperature (WBGT) and heat index (HI) measurements (median, mean, maximum). We calculated prevalence ratios (PRs) and 95% confidence intervals (CIs) via adjusted Poisson regression models with robust error variance to estimate associations with reported heat-related symptoms. We also evaluated the association between use of personal protective equipment (PPE) and heat-related symptoms.ResultsThose in the highest WBGT median–based heat exposure category had increased prevalence of heat-related symptoms compared to those in the lowest category (PR=2.22 [95% CI: 1.61, 3.06]), and there was a significant exposure-response trend (P<.001). Results were similar for exposure categories based on WBGT and HI metrics. Analyses stratified by use of PPE found significantly stronger associations between environmental heat exposure and heat-related symptoms in those who did not use PPE (PR=2.23 [95% CI: 1.10, 4.51]) than in those who did (PR=1.64 [95% CI: 1.14, 2.36]).ConclusionsUS Coast Guard Deepwater Horizon disaster responders who experienced higher levels of environmental heat had higher prevalences of heat-related symptoms. These symptoms may impact health, safety, and mission effectiveness. As global climate change increases the frequency of disasters and weather extremes, actions must be taken to prevent heat-related health impacts among disaster responders. (Disaster Med Public Health Preparedness. 2019;13:561-569)

scholarly journals Admiral Thad Allen, MPA ‘86, 23rd Commandant of the US Coast Guard

2011 ◽  
Vol 18 (1) ◽  
pp. 130
Author(s):  
Andrea Leung ◽  
Kaitlin Welborn
Keyword(s):  
Public Administration ◽  
Hurricane Katrina ◽  
Deepwater Horizon ◽  
Lessons Learned ◽  
Coast Guard ◽  
George Washington ◽  
The Us ◽  
Twitter Account ◽  
Us Coast Guard ◽  
Washington University

Admiral Thad Allen, the 23rd Commandant of the US Coast Guard, graduated from The George Washington University with his Master of Public Administration in 1986. Since that point, he has been in charge of the federal responses for Hurricane Katrina as well as for the Deepwater Horizon oil spill. Admiral Allen sat down with the Editor-in-Chief and the Managing Editor of Policy Perspectives to talk about lessons learned from his career, “dogs who hunt,” and the possibility of an Admiral Allen Twitter account.

Asbestos Survey for Fort Point US Coast Guard Station. Volume 1

1991 ◽  
Author(s):  
STOLLAR (R L) AND ASSOCIATES INC DENVER CO
Keyword(s):  
Coast Guard ◽  
Us Coast Guard

New methodical approaches to mapping of geosystems (by the example of Baikalian Siberia’s geosystems)

2018 ◽  
Vol 937 (7) ◽  
pp. 23-34 ◽  
Author(s):  
I.N. Vladimirov
Keyword(s):  
Global Climate ◽  
Remote Sensing Data ◽  
Field Research ◽  
Scientific Basis ◽  
Nature Management ◽  
Climate Data ◽  
Structural Dynamic ◽  
Digital Elevation ◽  
North Asia ◽  
Elevation Model

The article considers a new approach to landscape mapping based on the synthesis of remote sensing data of high and medium spatial resolution, a digital elevation model, maps of various thematic contents, a set of global climate data, and materials of field research. The map of the Baikalian’s Siberia geosystems is based on the principles of the multistage regional-typological and structural-dynamic classification of geosystems proposed by Academician V.B. Sochava. The structure of the geosystems of the Baikalian Siberia is characterized by great complexity, both in the set of natural complexes and in the degree of their contrast. The regional classification range covers the geosystems inherent in different subcontinents of Asia and reflects their interpenetration, being a unique landscape-situational example of Siberian nature within North Asia. The map of the geosystems of the Baikalian Siberia reflects the main structural and dynamic diversity of geosystems in the region in the systems of their geographic and genetic spatial structures. These landscape cartographic studies fit into a single system of geographic forecasting and create a new fundamental scientific basis for developing recommendations for optimizing nature management in the Baikal region within the framework of implementing state environmental policy.

Advances in the data rescue and digitization of historical wind speed observations in Sweden: the WINDGUST project

2021 ◽  
Author(s):  
Erik Engström ◽  
Cesar Azorin-Molina ◽  
Lennart Wern ◽  
Sverker Hellström ◽  
Christophe Sturm ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Global Climate ◽  
Current Status ◽  
Weather Data ◽  
Climate Data ◽  
Intergovernmental Panel ◽  
Staff Members ◽  
The 1960S

<p>Here we present the progress of the first work package (WP1) of the project “Assessing centennial wind speed variability from a historical weather data rescue project in Sweden” (WINDGUST), funded by FORMAS – A Swedish Research Council for Sustainable Development (ref. 2019-00509); previously introduced in EGU2019-17792-1 and EGU2020-3491. In a global climate change, one of the major uncertainties on the causes driving the climate variability of winds (i.e., the “stilling” phenomenon and the recent “recovery” since the 2010s) is mainly due to short availability (i.e., since the 1960s) and low quality of observed wind records as stated by the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC).</p><p>The WINDGUST is a joint initiative between the Swedish Meteorological and Hydrological Institute (SMHI) and the University of Gothenburg aimed at filling the key gap of short availability and low quality of wind datasets, and improve the limited knowledge on the causes driving wind speed variability in a changing climate across Sweden.</p><p>During 2020, we worked in WP1 to rescue historical wind speed series available in the old weather archives at SMHI for the 1920s-1930s. In the process we followed the “Guidelines on Best Practices for Climate Data Rescue” of the World Meteorological Organization. Our protocol consisted on: (i) designing a template for digitization; (ii) digitizing papers by an imaging process based on scanning and photographs; and (iii) typing numbers of wind speed data into the template. We will report the advances and current status, challenges and experiences learned during the development of WP1. Until new year 2020/2021 eight out of thirteen selected stations spanning over the years 1925 to 1948 have been scanned and digitized by three staff members of SMHI during 1,660 manhours.</p>

scholarly journals Bulk Processing of Multi-Temporal Modis Data, Statistical Analyses and Machine Learning Algorithms to Understand Climate Variables in the Indian Himalayan Region

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7416
Author(s):  
Mohd Anul Haq ◽  
Prashant Baral ◽  
Shivaprakash Yaragal ◽  
Biswajeet Pradhan
Keyword(s):  
Machine Learning ◽  
Global Climate ◽  
Learning Algorithms ◽  
Remotely Sensed ◽  
Machine Learning Algorithms ◽  
Himalayan Region ◽  
Lapse Rate ◽  
Climate Data ◽  
Modis Data ◽  
Bulk Processing

Studies relating to trends of vegetation, snowfall and temperature in the north-western Himalayan region of India are generally focused on specific areas. Therefore, a proper understanding of regional changes in climate parameters over large time periods is generally absent, which increases the complexity of making appropriate conclusions related to climate change-induced effects in the Himalayan region. This study provides a broad overview of changes in patterns of vegetation, snow covers and temperature in Uttarakhand state of India through bulk processing of remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) data, meteorological records and simulated global climate data. Additionally, regression using machine learning algorithms such as Support Vectors and Long Short-term Memory (LSTM) network is carried out to check the possibility of predicting these environmental variables. Results from 17 years of data show an increasing trend of snow-covered areas during pre-monsoon and decreasing vegetation covers during monsoon since 2001. Solar radiation and cloud cover largely control the lapse rate variations. Mean MODIS-derived land surface temperature (LST) observations are in close agreement with global climate data. Future studies focused on climate trends and environmental parameters in Uttarakhand could fairly rely upon the remotely sensed measurements and simulated climate data for the region.

scholarly journals Acute and longer-term cardiovascular conditions in the Deepwater Horizon Oil Spill Coast Guard Cohort

2022 ◽  
Vol 158 ◽  
pp. 106937
Author(s):  
Hristina Denic-Roberts ◽  
Nicole Rowley ◽  
Mark C. Haigney ◽  
Kate Christenbury ◽  
John Barrett ◽  
...  
Keyword(s):  
Oil Spill ◽  
Deepwater Horizon ◽  
Coast Guard ◽  
Deepwater Horizon Oil Spill

scholarly journals Heat index trends and climate change implications for occupational heat exposure in Da Nang, Vietnam

2016 ◽  
Vol 2-3 ◽  
pp. 41-51 ◽  
Author(s):  
Sarah Opitz-Stapleton ◽  
Lea Sabbag ◽  
Kate Hawley ◽  
Phong Tran ◽  
Lan Hoang ◽  
...  
Keyword(s):  
Climate Change ◽  
Heat Exposure ◽  
Heat Index ◽  
Occupational Heat Exposure
Sign in / Sign up

Export Citation Format

Share Document