There is widespread debate on the drivers of heterogeneity of adverse COVID-19 pandemic outcomes and, more specifically, on the role played by context-specific factors. We contribute to this literature by testing the role of environmental factors as measured by environmentally protected areas. We test our research hypothesis by showing that the difference between the number of daily deaths per 1,000 inhabitants in 2020 and the 2018-19 average during the pandemic period is significantly lower in Italian municipalities located in environmentally protected areas such as national parks, regional parks, or Environmentally Protected Zones. After controlling for fixed effects and various concurring factors, municipalities with higher share of environmentally protected areas show significantly lower mortality during the pandemic than municipalities that do not benefit from such environmental amenities.

We investigate drivers of preferences for policies of climate change mitigation using the European Social Survey. We find that the share of individuals who agree on (bonus/malus) potentially balanced budget policies that tax fossil fuels and subsidize renewable energies is much less than those who agree only on subsidizing renewable energies. Low levels of education and income are significantly and negatively correlated with the probability of being part of the group of tax-and-subsidy advocates. We also find evidence of a strong seasonal effect, with a significantly higher share of support for the tax-and-subsidy policy being present when interviews are conducted during the hottest months of the year. We discuss the implications of our findings in terms of politically feasible climate change policies.

We investigate the time-varying effect of particulate matter (PM) on COVID-19 deaths in Italian municipalities. We find that the lagged moving averages of PM_2.5 and PM₁₀ are significantly related to higher excess deceases during the first wave (end February-end May) of the disease, after controlling, among other factors, for time-varying mobility, regional and municipality fixed effects, the nonlinear contagion trend, and lockdown effects. Our findings are confirmed after accounting for potential endogeneity, heterogeneous pandemic dynamics, and spatial correlation through pooled and fixed-effect instrumental variable estimates using municipal and provincial data. In addition, we decompose the overall PM effect and find evidence that pre-COVID long-term exposure and short-term variation during the pandemic matter, thereby supporting the two research hypotheses on the role of PM exposure. In terms of magnitude, we observe that a 1 µg/m³ increase in PM_2.5 leads to 20 percent more deaths in Italian municipalities, which is equivalent to a 5.9 percent increase in mortality rate.

The uneven geographical distribution of the novel coronavirus epidemic (COVID-19) in Italy is a puzzle given the intense flow of movements among the different geographical areas before lockdown decisions. To shed light on it, we test the effect of five potential correlates of daily adverse COVID-19 outcomes at province level, that is lockdown decisions, demographic structure, economic activity, temperature and quality of air (proxied by particulate matter and nitrogen dioxide). We find that poor quality of air is negatively correlated with adverse outcomes of the epidemic, with lockdown being strongly significant and more effective in reducing deceases in more polluted areas. Results are robust to different methods including cross-section, pooled and fixed-effect panel regressions (also controlling for spatial correlation), as well as difference-in-differences estimates of lockdown decisions through predicted counterfactual trends. They are consistent with the consolidated body of literature in previous medical studies suggesting that poor quality of air creates chronic exposure to adverse outcomes from respiratory diseases. The heterogeneity of diffusion does not seem to depend on other controls such as temperature, commuting flows, quality of regional health systems, share of public transport users, population density and the presence of Chinese community. We also find that adverse COVID-19 outcomes are significantly and positively correlated with the share of small (artisan) firms. Our findings provide suggestions for investigating uneven geographical distribution patterns in other countries, and, if preliminary evidence is corroborated by causation links, have relevant implications with respect to environmental and lockdown policies.

According to the gender life satisfaction/depression paradox women are significantly more likely to report higher levels of life satisfaction than men after controlling for all relevant socio-demographic factors, but also significantly more likely to declare they are depressed. We find that the paradox holds in the cross-country sample of the European Social Survey and is stable across age, education, self-assessed health, macroregion and survey round splits. We find support for the affect intensity rationale showing that women are relatively more affected in their satisfaction about life by the good or bad events or achievements occurring during their existence and less resilient (less likely to revert to their standard levels of happiness after a shock). We as well discuss biological, genetic, cultural, personality rationales advocated in the literature that can explain our findings.

The emergence of the despair death crisis in the US stimulates researchers and policymakers to look at subjective wellbeing data from a different perspective. We wonder what can be done to avoid a similar situation in Europe and to this purpose we analyse factors correlated with depression in the European Social Survey by considering the latter as a proxy of despair deaths. We find the strongest correlations with poor income, high income expectations, low education, low skilled jobs, poor social relationships, failure and shocks in affective relational life. We perform robustness checks finding that our results are robust when using alternative measures of psychological health and when instrumenting married status. If causality links between all these drivers and the dependent variable are verified and confirmed, as for marital status, we can conclude that the despair death crisis depends from a mix of material and immaterial factors (with the latter being dominant) that cannot be fully solved by mere monetary redistribution.

Background

The questioned link between air pollution and coronavirus disease 2019 (COVID-19) spreading or related mortality represents a hot topic that has immediately been regarded in the light of divergent views. A first “school of thought” advocates that what matters are only standard epidemiological variables (i.e. frequency of interactions in proportion of the viral charge). A second school of thought argues that co-factors such as quality of air play an important role too.

Methods

We analyzed available literature concerning the link between air quality, as measured by different pollutants and a number of COVID-19 outcomes, such as number of positive cases, deaths, and excess mortality rates. We reviewed several studies conducted worldwide and discussing many different methodological approaches aimed at investigating causality associations.

Results

Our paper reviewed the most recent empirical researches documenting the existence of a huge evidence produced worldwide concerning the role played by air pollution on health in general and on COVID-19 outcomes in particular. These results support both research hypotheses, i.e. long-term exposure effects and short-term consequences (including the hypothesis of particulate matter acting as viral “carrier”) according to the two schools of thought, respectively.

Conclusions

The link between air pollution and COVID-19 outcomes is strong and robust as resulting from many different research methodologies. Policy implications should be drawn from a “rational” assessment of these findings as “not taking any action” represents an action itself.