## 4 Discussion  
The Colombian government's restrictions to curb the spread of the COVID-19 pandemic have had a significant impact in several sectors of its economy due to the cessation of some activities [58]. Our results showed reductions for the four groups of pollutants analyzed. In particular, a total of 6010 Gg were eliminated, mainly in seven territorial subdivisions of Colombia where close to 50% of the national population live [59]. One of the positive impacts identified is the emissions reduction from decreased road transport. This is registered by recent studies on air quality improvements carried out in Sao Paulo (Brazil), which reported high reductions of air pollutant concentrations during its partial lockdown due to the decrease in vehicular traffic in analyzed areas [60]. In Barcelona (Spain), the most significant reductions were estimated for pollutants related to traffic emissions [61]. Emissions in China caused by road transport have been affected by the lockdown, generating a reduction of the pollutants associated with this sector [62]. Therefore, the lockdown significantly reduced the air pollution (air pollutants and warming gases) in most cities across the world [26]. Figure 5: Spatial distribution of mean levels of tropospheric NO\({}_{2}\) through internal political and territorial divisions (departments) between April and June 2018 and 2020. Source: Time averaged map of NO\({}_{2}\) tropospheric column (30% cloud screened) daily 0.25 deg. (OMI OMNO2 dv003) 1/cm\({}^{2}\). Emissions of the four pollutant groups selected in this study depend on the consumption of fossil fuels, which during the lockdown decreased in accordance with the lower vehicle traffic in Colombia. According to Colombian government reports, diesel and gasoline consumption experienced a drop of 50% and 65%, respectively, since mid-March when the lockdown began [63]. Furthermore, the Mercantile Exchange Colombia did not register increases in the consumption data for CNG [50]. This led to a reduction in the estimated emissions of the four pollutant groups studied, with the most variation in GHGs, specifically CO\({}_{2}\). It is consistent with recent studies that affirm the first sector with the greatest reduction in global emissions of CO\({}_{2}\) during isolation was transportation [64]. The emissions reduction of ozone precursor gases (CO, NMVOC, NOx) registered in this study is consistent with the highest reduction of CO and NO\({}_{2}\) that occurred in China due the lockdown measures taken to control the COVID-19 pandemic, which dramatically reduced the number of vehicles on the road, and consequently led to an improvement in air quality due most likely to reduced emissions from some sectors (such as the transportation linked to the NO\({}_{2}\) emissions). This occurred chiefly in those provinces with large fleet vehicular and secondary industries, which suggests that the reduced emissions from the transportation and industrial sectors caused a decrease in concentrations of these gases [18]. In addition, it was reported that NO\({}_{2}\) emissions were reduced by up to 60% in the city of Santander (Spain) [32]. Other studies found a 20-30% reduction in emissions of NO\({}_{2}\) in China, Spain, France, Italy, and the USA due to the lockdown [9] and a drastic reduction of NO (up to \(-\)77.3%), NO\({}_{2}\) (up to \(-\)54.3%), and CO (up to \(-\)64.8%) in Sao Paulo (Brazil). In the case of NO, one recent study demonstrated that heavy-duty diesel trucks are the major sources of this pollutant [65]. While the NMVOC emissions reduction was \(-\)22% in this study, other research has shown a PM\({}_{2.5}\) emissions reduction of \(-\)17% [23]. Aerosol reductions (BC, PM\({}_{10}\), PM\({}_{2.5}\)) in our study were consistent with recent studies. Chinese researchers carried out an analysis of PM\({}_{2.5}\) data in cities such as Beijing, Shanghai, Guangzhou, and Wuhan during COVID-19 and found a pronounced reduction in air pollution attributed to the reduction of emissions in transportation and industrial sectors [18].