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Social lockdowns improved air quality during the COVID-19 pandemic. Governments had previously spent a lot of money addressing air pollution without success. This bibliometric study measured the influence of COVID-19 social lockdowns on air pollution, identified emerging issues, and discussed future perspectives. The researchers examined the contributions of countries, authors, and most productive journals to COVID-19 and air pollution research from January 1, 2020, to September 12, 2022, from the Web of Sciences Core Collection (WoS). The results showed that (a) publications on the COVID-19 pandemic and air pollution were 504 (research articles) with 7495 citations, (b) China ranked first in the number of publications (n = 151; 29.96% of the global output) and was the main country in international cooperation network, followed by India (n = 101; 20.04% of the total articles) and the USA (n = 41; 8.13% of the global output). Air pollution plagues China, India, and the USA, calling for many studies. After a high spike in 2020, research published in 2021 declined in 2022. The author's keywords have focused on "COVID-19," "air pollution," "lockdown," and "PM25." These keywords suggest that research in this area is focused on understanding the health impacts of air pollution, developing policies to address air pollution, and improving air quality monitoring. The COVID-19 social lockdown served as a specified procedure to reduce air pollution in these countries. However, this paper provides practical recommendations for future research and a model for environmental and health scientists to examine the likely impact of COVID-19 social lockdowns on urban air pollution. [ABSTRACT FROM AUTHOR]

The current nationally determined contributions, pledged by the countries under the Paris Agreement, are far from limiting climate change to below 2 ∘C temperature increase by the end of the century. The necessary ratcheting up of climate policy is projected to come with a wide array of additional benefits, in particular a reduction of today's 4.5 million annual premature deaths due to poor air quality. This paper therefore addresses the question how climate policy and air pollution–related health impacts interplay until 2050 by developing a comprehensive global modeling framework along the cause and effect chain of air pollution–induced social costs. We find that ratcheting up climate policy to a 2 ∘ compliant pathway results in welfare benefits through reduced air pollution that are larger than mitigation costs, even with avoided climate change damages neglected. The regional analysis demonstrates that the 2 ∘C pathway is therefore, from a social cost perspective, a "no-regret option" in the global aggregate, but in particular for China and India due to high air quality benefits, and also for developed regions due to net negative mitigation costs. Energy and resource exporting regions, on the other hand, face higher mitigation cost than benefits. Our analysis further shows that the result of higher health benefits than mitigation costs is robust across various air pollution control scenarios. However, although climate mitigation results in substantial air pollution emission reductions overall, we find significant remaining emissions in the transport and industry sectors even in a 2 ∘C world. We therefore call for further research in how to optimally exploit climate policy and air pollution control, deriving climate change mitigation pathways that maximize co-benefits. [ABSTRACT FROM AUTHOR]

The chaotic structure of air pollution, human health, the evidence of cointegration and causality between the air pollution, transportation, tourism, construction, and manufacturing industries and the evidence of cointegration and causality between the air pollution, transportation, tourism, construction, and manufacturing industries and mortality rate were explored for China, India, and Turkey in the period of 1975-2018 by using four different methods. Firstly, Lyapunov and Shannon tests were applied to determine chaotic dynamics. The maximum Lyapunov test, for the selected variables, found the evidence of chaotic dynamics. Secondly, Fourier ADF and NL tests were applied. Fourier unit root test determined stationary of the variables. Thirdly, bootstrapping autoregressive distributed lag with Fourier transformation (FBARDL) was used to determine the evidence of cointegration between the variables with two different models. FBARDL test determined that the manufacturing, tourism, transport, and construction industries, air pollution, and mortality rate have evidence of cointegration in different two models. Lastly, the causality test with Fourier transformation was used to determine the direction of causality between the variables. Granger causality test determined that there is evidence of one-way causality running from transportation, tourism, construction, and manufacturing industries to air pollution and mortality rates. Accordingly, the results of this paper suggest air pollution and human health have chaotic behaviors. Air pollution has a complex, multi-variable, and multi-coupling system. Air pollutants influencing factors and air pollution itself have adverse effects on human health. [ABSTRACT FROM AUTHOR]