I have selected ozone, oxides of nitrogen and carbon monoxide that are produced during wildfires. Therefore, it is important to select data required to check air quality and weather conditions. The EPA provides data for the entire state and it is a large data set, often slowing the processing time. Precipitation Record (2007-2020), San Diego, CA. EPA website/ User Guide to download data. Plot data to view any anomalies in data and identify source of the anomaly. Use Scikit learn multivariate analysis to predict ozone levels. Import data into dataframes using appropriate functions(date-parser, indexing, remove missing values)Ītmospheric gases and particulate matter data Jan - Dec. Set working directory to "earth-analytics"ĭefine paths to download data files from data folder 'sd_fires_2014' Import datetime conversion tools beteween panda and matplotlib for time series analysisĭownload air quality data from the EPA website Pulgas Fire 2014, San Diego, CA (source= wikimedia) May 2014 Wildfires. Picture of an unprecdented wildfire near Camp Pendelton. Understanding changes in the chemical composition of the atmosphere and identify markers that can trigger respiratory stress and cardio-vascular diseases. Understanding weather pattern using advanced machine learning tools to identify certain markers that can be used to forecast future events. I have laid out this study in multiple sections: This goal of this study is to understand the weather data that can trigger wildfires and consequences of wildfires on the atmospheric chemistry and how we can predict and plan for a better future to mitigate disastrous consequences. This analysis is not only an academic endeavor but also a humble beginning to understand the complex interactions between atmosphere and biosphere in the nature and how we can plan for a better future for those who suffered the most during these catastrophic wildfires. The state of California with ~ 40 million residents and ~ 4.5 million housings and properties has experienced the most devastating economic, ecological and health consequences during and after wildfires (Baylis and Boomhower, 2019 Liao Y and Kousky C, 2020,).ĭuring 2014 wildfires in San Diego, I volunteered to help people in the emergency shelters and watching the devastating effects of wildfires on children and adults emotional and physical health had a profound impact on me and moved me at a deeper level to search for potential markers/predictors of these events in the nature. In the western U.S., wildfires are projected to increase in both frequency and intensity as the planet warms (Abatzoglou and Williams, 2016). Wildfires are no exception, as seen in the recent years, devastating blazes across the globe (Amazon forest in 2019, California 2017-18 and Australia in 2019-2020. A comparison with the historical data indicates higher frequency, larger magnitude, longer duration, and timing of many of these events around the world has also changed singniciantly (Seneviratne et al., 2018). Over the last two decades, humanity has observed record-breaking extreme weather events. The rising carbon dioxide in the atmosphere is contributing to constant increase in global temperatures.
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