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Tracking and classifying Amazon fire events in near real time.

ABSTRACT: Exceptional fire activity in 2019 sparked concern about Amazon forest conservation. However, the inability to rapidly separate satellite fire detections by fire type hampered fire suppression and assessment of ecosystem and air quality impacts. Here, we describe the development of a near-real-time approach for tracking contributions from deforestation, forest, agricultural, and savanna fires to burned area and emissions and apply the approach to the 2019 fire season in South America. Across the southern Amazon, 19,700 deforestation fire events accounted for 39% of all satellite active fire detections and the majority of fire carbon emissions (63%; 69 Tg C). Multiday fires accounted for 81% of burned area and 92% of carbon emissions from the Amazon, with many forest fires burning uncontrolled for weeks. Most fire detections from deforestation fires were correctly identified within 2 days (67%), highlighting the potential to improve situational awareness and management outcomes during fire emergencies.

SUBMITTER: Andela N

PROVIDER: S-EPMC9337759 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Tracking and classifying Amazon fire events in near real time.

Andela Niels N Morton Douglas C DC Schroeder Wilfrid W Chen Yang Y Brando Paulo M PM Randerson James T JT

Science advances 20220729 30

Exceptional fire activity in 2019 sparked concern about Amazon forest conservation. However, the inability to rapidly separate satellite fire detections by fire type hampered fire suppression and assessment of ecosystem and air quality impacts. Here, we describe the development of a near-real-time approach for tracking contributions from deforestation, forest, agricultural, and savanna fires to burned area and emissions and apply the approach to the 2019 fire season in South America. Across the ...[more]

PMID: 35905176

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Project description:ObjectivesCritical care teams are encouraged to follow best practice protocols to help wean mechanically ventilated patients from the ventilator to reduce ventilator-associated events including ventilator-associated conditions, probable ventilator-associated pneumonias, and infection-related ventilator-associated conditions. Providers monitor for alerts suggestive of possible ventilator-associated events and advise when patients should undergo spontaneous breathing trials. Compliance with protocols in most units is suboptimal.DesignRetrospective review of clinical data over 24 months.SettingSt. Joseph Mercy Hospital Candler Hospital Medical-Surgical ICU.PatientsAll mechanically ventilated patients.InterventionsThe Respiratory Knowledge Portal was implemented in our ICU. For 13 months, Respiratory Knowledge Portal data were ported to ICU workstations (control). For the following 11 months, Respiratory Knowledge Portal data were also presented on tablet computers (intervention) for use during multidisciplinary rounds. We performed a retrospective review of Respiratory Knowledge Portal data from before and after the implementation of the tablet computers.Measurements and main resultsData were collected from 337 patients (187 control group, 150 intervention group). A decrease in the occurrence of ventilator-associated events was observed during the intervention group compared with the control group. Only 2.0% of patients in the intervention group experienced any category of ventilator-associated event, while 11.2% of patients in the control group experienced one event (p = 0.003). Intervention patients experienced less ventilator-associated conditions (p = 0.002), infection-related ventilator-associated conditions (p = 0.026), and probable ventilator-associated pneumonias (p = 0.036) than control patients. Twenty-one of the 24 patients with any ventilator-associated events were in the control group. There was no significant difference between the days spent on ventilation nor hospital length of stay in the control compared with intervention group patients.ConclusionsFewer ventilator-associated events, ventilator-associated conditions, infection-related ventilator-associated conditions, and probable ventilator-associated pneumonias were seen during the period when Respiratory Knowledge Portal monitoring data was presented on tablet computers. There was no difference in time on ventilator nor overall length of stay.

Dataset Information

Tracking and classifying Amazon fire events in near real time.

Publications

Tracking and classifying Amazon fire events in near real time.

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