Occasion with points of red colour. The MODIS Terra/Aqua sensor platform was used to acquire the thermal anomalies/active fire image [40]. The yellow points would be the monitoring stations for PM2.5 . two.two. Data 2.two.1. PM2.five Information PM2.five data were collected hourly through September (720 hours) by the Air Good quality Network of Quito, which can be formed by 5 monitoring stations, and they may be described in Table 1. The monitoring network made use of a Thermo Fisher Scientific FH62C14-DHS Continuous Ambient Particulate Monitor 5014i with beta rays’ attenuation technique (Waltham, Massachusetts, USA), as 3-Hydroxybenzaldehyde supplier suggested by the Environmental Protection Agency (EPA). The Air Good quality Network of Quito is a permanent air pollution surveillance network. The data had been obtained in the open-source on the net information repository managed by the environmental agency of Quito, and hosted at Secretaria de Ambiente del Distrito Metropolitano de Quito [41].Atmosphere 2021, 12,three ofFigure 1. Wildfire event on 14 September 2015, obtained from the MODIS-Terra/Aqua sensor platform in Quito. The wildfires are represented by red points, and also the monitoring stations by yellow points. Table 1. Monitoring stations for PM2.five and their major qualities. Station Name Carapungo Belisario Cotocollao Centro Los Chillos Station Code ST_1 ST_2 ST_3 ST_4 ST_5 78 26 Location 50 78 29 24 78 29 59.two 78 30 50.four 78 27 18.eight W, 54 S W, 0 ten 48 S W, 0 06 38.eight S W, 0 13 17.six S W, 0 17 49.5 S 0 5 Elevation (m.a.l.s.) 2851 2835 2739 28202.two.2. Meteorological Data The meteorological information were collected from meteorological assimilation systems determined by satellite data. This short article used Modern-Era Retrospective evaluation for Investigation and Applications version 1 and two (MERRA and MERRA-2) from NASA’s Giovanni web platform; MERRA-2 published quite a few analysis solutions used in meteorological and air high quality modelling [42,43]. Some works utilized the soil surface Dicyclanil Protocol temperature variable to indicate wildfire events [446]. Table two shows the principle characteristics of meteorological data.Table 2. Meteorological information descriptions. Covariates Air temperature Stress Radiation Surface temperature Units K mb W -2 K Temporal Resolution Hourly Hourly Hourly Hourly Spatial Resolution 0.5 .625 0.5 .625 0.five .625 0.five .667 lat-lon lat-lon lat-lon lat-lon Source M2I1NXLFO.five.12.4 M2T1NXRAD.five.12.four M2T1NXSLV.five.12.four MAT1NXSLVAtmosphere 2021, 12,four of2.three. Statistical Modelling two.three.1. Dynamic Linear Models (DLM) Two equations defined the dynamic linear modelling; the first a single is denoted because the observation equation. The dependent variable, yst , is the observed generic pollutant concentration at spatial place s (s = 1, . . . , S) on time t (t = 1, . . . , T) and it is actually described in Equation (1): yst = Xst + st + vst (1) exactly where vst denotes the measurement error, which is assumed to become independent, and it features a variance, 2 . The vector of regression coefficients is represented by vector ; Xst v represents a vector of regressors that transform temporally. Operator ” is applied to indicate multiplication of scalars, vectors or matrices depending on the context within this report. The second equation that describes the dynamic linear modelling is related to the term st ; its name will be the technique equation, and it describes a dynamic autoregressive first-order model, shown as: st = a s, t-1 + wst (two) exactly where wst would be the temporal and spatial error; it has a regular distribution plus a variance, 2 / 1 – a2 . The temporal and spatial variance (two ) is based on the correlation among w w.