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Documento que sirvio para probar el subir archivos a RPubs

Air pollution significantly and severely affects human health, the environment, materials, and the economy emerging as a key microclimate and air quality regulation issue. Hence, the spatial and temporal characterisation of air pollutants and their relationship with meteorological constraining factors is paramount, particularly from a climate change perspective. Air pollutants’ spatial and temporal characterisation over Portugal is performed, focusing particularly on the emissions of Particulate Matter (PM) during the major wildfire events in 2017-2018. This will be performed based on the Copernicus Atmosphere Monitoring (CAMS) data, to benefit from having reliable and gridded information on the atmosphere composition and its related processes, anywhere in the world. Specifically, to take advantage of having gridded air quality (AQ) data over the Portuguese territory, to assess AQ environmental emergencies in less covered areas from the national air quality network. Within this context, we propose an exploratory statistical tool that combines functional data analysis (FDA) with unsupervised learning algorithms and spatial statistics to extract meaningful information about the main spatiotemporal patterns underlying air pollutant exceedances in mainland Portugal. Firstly, we describe the temporal evolution of air pollutant concentrations by CAMS grid node (OU usamos an expressão pixel?) as a function of time and outline the main temporal patterns of variability using a functional principal component analysis. Then, CAMS grid nodes are classified according to their spatiotemporal similarities through hierarchical clustering adapted to spatially correlated functional data.

This report is the analysis of Specified Greenhouse Gases Activities in Ontario from 2010 to 2021. We took the dataset from the official website from Ontario government. This report aim to visualize the changes of greenhouse gases activities according to the categories and predict the future growth of average greenhouse gas emissions in Ontario.

Time Series Analysis Problems

In-class activity 3

In-class activity 3