1  Introduction
Currently, socio-ecological systems have a great impact on companies, cities and territories; the sustainability and technology associated with smart cities are merged to better understand the behavior of this type of systems, and the data provides cities and territories with the information necessary for sufficient monitoring and evaluation leading to coherent environmental policies in adaptive environments (Waylen et al., 2019). It is necessary to formulate new socio-ecological models that allow describing the coevolution of the economy, the environment and society in the face of the dynamics of wealth and population (Ursino, 2019). However, few models efficiently predict the entry of random variables into these complex processes, which validate their evolution over time. One of the clearest examples of a chaotic variable is climate, however, there are other variables that can quickly intervene in a socio-ecological system and wreak havoc, such as a virus.
For example, in Brisbane, Australia ecological factors appear to have played an important role in H1N1 transmission cycles (Hu et al., 2012), with temperature and precipitation being substantial variables in the evolution of the virus. There are some other works of socioeconomic studies and viruses such as (Mamelund et al., 2019), where a study is carried out between the socioeconomic levels and the influenza-related pandemics of 1918 and 2009. The foregoing demonstrates the importance of correlating the factors that can substantially alter the socio-ecological systems in which we live and to be able to study their evolution and impact on society.
One of the key factors in recent years, which has been the subject of several scientific studies, is the impact of poor air quality on people’s health and its consequences over time. The emission of pollutants such as particulate matter (PM), sulphur oxides (SOx), nitrogen oxides (NOx), carbon monoxide (CO) and carbon dioxide (CO2), are the pollutants that are generated in greater quantity and according to estimates of the World Health Organization (WHO) 2016 produce annually in cities and rural areas around the world about 4.2 million premature deaths (Cohen et al., 2017). The WHO (World Health Organization, 2018) estimates that about seven million people die each year from exposure to PM2.5 particles, which enter directly into the respiratory system and are deposited in the lung region causing serious diseases such as stroke, lung cancer, chronic obstructive pulmonary disease, heart disease and respiratory infections such as pneumonia. (Cachon et al., 2014), (Gu et al., 2017), (Ng et al., 2019). On the other hand, a World Bank report of 2018 shows in graphs the most relevant socio-economic and socio-ecological aspects that impact the world, where global warming, poor air quality and urban population growth among others, leave chilling figures, as 91% of the world population lives in places with poor air quality, places like cities that increased by 55% their urban residents between 1960 and 2018 (The World Bank, 2018).
In December 2019, one of the most deadly viruses in the last 100 years is reported (Lu et al., 2020). China reports this new pathogen to the WHO on December 31, and only three months later this organization declares it a pandemic. The new virus called SARS-CoV2 and the cause of COVID-19 has stopped global activity in a few months and has taken the lives of thousands of people in different cities around the world. The impact of this virus on the socio-economic level is causing markets to tremble, world stock markets to collapse, all flights to be cancelled and borders and transport systems to be closed. On the other hand, oil demand has dropped and producers are running out of places to store all the excess barrels of oil as it has fallen below $0 US per barrel. However, this pandemic also caused air quality to improve in many of the world’s cities, reducing environmental pollution. This global closure has made it possible to obtain interesting environmental data for analysis and several scientific investigations related precisely to these socio-ecological changes.
In China, for example, CO2 emissions were reduced by 25% and by 6% worldwide according to (Hanaoka and Masui, 2020). In (Dutheil et al., 2020), an initial comparative analysis was made of the number of deaths from COVID-19 and the number of annual air quality deaths with respect to nitrogen dioxide NO2 emissions. This analysis was based on data obtained by satellite (NASA, 2020) showing the advantages that the isolation of the population in their homes has had due to the emergency by the shutdown of industries and vehicle mobility (Tan et al., 2009). The same information from NASA, plus information taken from ESA, was used in (Muhammad et al., 2020) to perform a compilation of satellite environmental data before and after coronavirus. The figures in this paper show the temporary environmental benefit as a major positive impact and as a learning model for governments to enable new socio-environmental policies. This last analysis was done for Europe, China and North America. Likewise, in (Mollalo et al., 2020) models are made of the type of spatial dependence and weighted regression of 35 variables from the environmental to the socioeconomic ones related to the incidence of the disease in the first 90 days of the outbreak in the United States. These results, according to Mollalo, will serve as a basis for future geographic modeling of any disease, as well as for policy with targeted, science-based interventions that can be extrapolated to other cities and countries around the world. Finally, Ogen’s research has found a direct relationship between contamination and mortality caused by the coronavirus. The study concludes that 78% of the 4443 deaths recorded on a single day in Europe (19 march) occurred in five specific, highly contaminated areas: four regions of northern Italy and Madrid. These results indicate that long-term exposure to particulate pollutants may be a major contributor to coronavirus mortality, not only in these regions, but in the rest of the world (Ogen, 2020).
All these analyses described above are necessary to evaluate the socio-ecological and socio-economic changes in all the cities of the world and try to show the positive impacts in order to obtain some benefits from this global crisis. Ultimately, this paper uses data from the weather stations of the 50 most polluted cities in the world and makes a comparison of air quality with respect to PM2.5 particulate matter before and during the quarantine of each capital city.