The aim of the study is to evaluate the association between summer temperatures and emergency department visits (EDVs) in Bologna (Italy) and assess whether this association varies across areas with different socioeconomic and microclimatic characteristics. We included all EDVs within Bologna residences during the summers of 2010–2019. Each subject is attributed a deprivation and a microclimatic discomfort index according to the residence. A time-stratified case-crossover design was conducted to estimate the risk of EDV associated with temperature and the effect modification of deprivation and microclimatic characteristics. In addition, a spatial analysis of data aggregated at the census block level was conducted by applying a Poisson and a geographically weighted Poisson regression model. For each unit increase in temperature above 26 °C, the risk of EDV increases by 0.4% (95%CI: 0.05–0.8). The temperature–EDV relationship is not modified by the microclimatic discomfort index but rather by the deprivation index. The spatial analysis shows that the EDV rate increases with deprivation homogeneously, while it diminishes with increases in median income and microclimatic discomfort, with differences across areas. In conclusion, in Bologna, the EDV risk associated with high temperatures is not very relevant overall, but it tends to increase in areas with a low socioeconomic level. Full article

The large availability of both air pollution and COVID-19 data, and the simplicity to make geographical correlations between them, led to a proliferation of ecological studies relating the levels of pollution in administrative areas to COVID-19 incidence, mortality or lethality rates. However, the major drawback of these studies is the ecological fallacy that can lead to spurious associations. In this frame, an increasing concern has been addressed to clarify the possible role of contextual variables such as municipalities’ characteristics (including urban, rural, semi-rural settings), those of the resident communities, the network of social relations, the mobility of people, and the responsiveness of the National Health Service (NHS), to better clarify the dynamics of the phenomenon. The objective of this paper is to identify and collect the municipalities’ and community contextual factors and to synthesize their information content to produce suitable indicators in national environmental epidemiological studies, with specific emphasis on assessing the possible role of air pollution on the incidence and severity of the COVID-19 disease. A first step was to synthesize the content of spatial information, available at the municipal level, in a smaller set of “summary indexes” that can be more easily viewed and analyzed. For the 7903 Italian municipalities (1 January 2020—ISTAT), 44 variables were identified, collected, and grouped into five information dimensions a priori defined: (i) geographic characteristics of the municipality, (ii) demographic and anthropogenic characteristics, (iii) mobility, (iv) socio-economic-health area, and (v) healthcare offer (source: ISTAT, EUROSTAT or Ministry of Health, and further ad hoc elaborations (e.g., OpenStreetMaps)). Principal component analysis (PCA) was carried out for the five identified dimensions, with the aim of reducing the large number of initial variables into a smaller number of components, limiting as much as possible the loss of information content (variability). We also included in the analysis PM_2.5, PM₁₀ and NO₂ population weighted exposure (PWE) values obtained using a four-stage approach based on the machine learning method, “random forest”, which uses space–time predictors, satellite data, and air quality monitoring data estimated at the national level. Overall, the PCA made it possible to extract twelve components: three for the territorial characteristics dimension of the municipality (variance explained 72%), two for the demographic and anthropogenic characteristics dimension (variance explained 62%), three for the mobility dimension (variance explained 83%), two for the socio-economic-health sector (variance explained 58%) and two for the health offer dimension (variance explained 72%). All the components of the different dimensions are only marginally correlated with each other, demonstrating their potential ability to grasp different aspects of the spatial distribution of the COVID-19 pathology. This work provides a national repository of contextual variables at the municipality level collapsed into twelve informative factors suitable to be used in studies on the association between chronic exposure to air pollution and COVID-19 pathology, as well as for investigations on the role of air pollution on the health of the Italian population. Full article

Increases in particulate matter in cities threaten both public health and ecosystems. Street trees, which are a corridor-type green infrastructure capable of absorbing particulate matter, have been promoted as one possible solution to this problem. However, planting selected trees solely with the goal of reducing particulate matter may adversely affect street tree ecosystem resilience by inhibiting species diversity. This study aims to investigate urban street tree planting strategies that reduce particulate matter while maintaining ecosystem resilience. To this end, a study site in Suwon, South Korea was selected, and street tree planting scenarios were developed based on the selected site information. A scenario analysis was conducted using a system dynamics model. The model simulated the long-term trends under each scenario regarding the amount of particulate matter absorbed by the trees and the changes in species diversity. The analysis results clearly show that strategic planting of street trees while focusing on only a specific purpose—reducing particulate matter—can adversely affect ecosystem resilience. The scenario analysis also revealed that increasing the number of street trees while maintaining a balance among various species is the best option for reducing particulate matter without degrading species diversity. Additionally, the results support the need to plant evergreen species to consider the winter season. Full article

The global coronavirus (COVID-19) pandemic has tremendously reshaped the tourism industry and destinations worldwide. Tourism destinations and the travel market require empirical research to support their post-pandemic strategies, especially in relation to the influences of changing perceptions of tourism risks, experience, and behavioural intention. This paper aims to propose a conceptual model and its hypotheses of the perceived tourism risks of natural and man-made disasters to explain the associations between the expected travel experience and ultimate travel behaviour. This paper provides a foundation for further empirical study based on a literature review and discussion. Several areas of theoretical development are identified for immediate research: (1) comparison of self-interpretation and understanding of multi-dimensional tourism risks of natural and man-made complexity in epidemics across a great variety of geographical and geo-political territories; (2) a complex web of influence to changing safety concerns and risk perception by information dissemination; (3) the effect of destination selection or hesitation in travel intention caused by changing destination image; and (4) local perception of the epidemic and health crisis. Destination authorities are recommended to (1) strengthen the preparedness and emergency responses of an effective disaster management process, (2) maintain the emotional solidarity of both tourists and local residents, and (3) mitigate multiple dimensions of the perceived risks, mainly associated with the health and psychological risks of those affected. Full article

Green spaces are defined as open spaces of ground, covered by vegetation, including parks and gardens. This kind of environment is linked to many positive effects and its importance is growing due to increasing urbanization. Understanding what drives people to use green urban space is fundamental to creating appropriate campaigns to develop the use of such spaces and improve the citizens’ quality of life. A questionnaire on the attitude towards green space was developed and submitted to people from two Italian regions. Emilia-Romagna and Veneto are two regions in the North of Italy with different territorial policies. Three hundred and ten surveys were collected (167 in Emilia-Romagna and 143 in Veneto). Significant differences were observed between regions, age groups and in relation to the kind of work (p < 0.05). People from Emilia-Romagna have higher scores of attitudes towards green space than people from Veneto, underlining the importance of territorial policies. Moreover, younger participants (18–30 years) seem to be less attracted to green urban space. Being an employee seems to influence the attitude towards green space. Particular attention should be given to subjects of the younger age groups and to the number of hours spent at work. This could be an important element for future research, so that political action can be implemented with these categories in mind. Full article

A microclimate classification of the entire Bologna Municipality has been carried out in order to give a tool to the local administration in the drafting of the General Urbanistic Plan (PUG). The city was classified considering the variation of air temperature as a function of the surface characteristics, the vegetation fraction, the building density and the H/W ratio (height to width). Starting from the microclimate analysis carried out with fluid-dynamic modeling (Envi-met) for some areas of the city of urban interest, the air temperature variation was correlated to the physiological equivalent temperature (PET) in order to make a classification of physiological well-being for the resident population. An urban map of a normalized microclimate well-being index (BMN) has been obtained to give support when private, and public actors want to regenerate part of the city, taking into account the climate-centered approach for the development of a sustainability city. Full article

Global pandemics, such as the Coronavirus Disease 2019 (COVID-19), have serious harmful effects on people′s physical health and mental well-being. It is imperative therefore that we seek to understand community resilience and identify ways to enhance this, especially within our cities and communities. Therefore, great emphasis is now placed on how cities prepare for and recover from such disasters, and community resilience has emerged as a key consideration. Drawing upon research on the theory of resilience, this study seeks to identify the factors that influence community resilience and to analyze their causation toward helping to manage the risks associated with the COVID-19 pandemic. Seventeen factors from the five dimensions of social capital, economic capital, physical environment, demographic characteristics, and institutional factors are used to construct an index system. This is used to establish the structural level and importance of each factor. Data were collected using a questionnaire survey involving 12,000 members of key community groups in the city of Wuhan. An interpretative structural model (ISM) combining the analytic hierarchy process (AHP) method was then used to obtain the multi-level hierarchical structure composed of direct factors, indirect factors, and fundamental factors. The results show that the income level, vulnerability of the population, and the built environment are the main factors that affect the resilience of communities affected by COVID-19. These findings provide useful guidance toward the effective planning and design of urban construction and infrastructure. The results are expected to be useful to inform future decision-making and toward the long term, sustainable management of the risks posed by COVID-19. Full article

Large-scale chemical accidents that occur near areas with large populations can cause significant damage not only to employees in a workplace but also to residents near the accident site. Despite the increasing frequency and severity of chemical accidents, few researchers have argued for the necessity of developing scenarios and simulation models for these accidents. Combining the TRANSIMS (Transportation Analysis and Simulation System) agent-based model with the ALOHA (Areal Location of Hazardous Atmospheres) dispersion model, this study aims to develop a modeling framework for simulating emergency evacuations in response to large-scale chemical accidents. The baseline accident scenario assumed the simultaneous leakage of toxic chemicals from industrial complexes near residential areas. The ALOHA model results showed that approximately 60% of residents in the scenario’s city were required to evacuate their homes. The majority of evacuees completed their evacuations within 5 h in the baseline scenario (evacuating maximum number of private vehicles without any intervention), while the distribution of the population and street network density caused geographical variability in clearance time. Clearance time can be significantly reduced by changing both the evacuees’ behaviors and the evacuation policy, which suggests the necessity for proper public intervention when the mass evacuation of residents is required due to chemical accidents. Full article

Identifying the most vulnerable subjects is crucial for the effectiveness of health interventions aimed at limiting the adverse consequences of high temperatures. We conducted a case crossover study aimed at assessing whether suffering from mental health disorders modifies the effect of high temperatures on mortality. We included all deaths occurred in the area of Bologna Local Health Trust during the summers 2004–2017. Subjects with mental disorders were identified by using the local Mental Health Registry. A conditional logistic model was applied, and a z-test was used to study the effect modification. Several models were estimated stratifying by subjects’ characteristics. For every 1 °C above 24 °C, mortality among people without mental disorders increased by 1.9% (95% CI 1.0–2.6, p < 0.0001), while among mental health service users, mortality increased by 5.5% (95% CI 2.4–8.6, p < 0.0001) (z-test equal to p = 0.0259). The effect modification varied according to gender, residency and cause of death. The highest probability of dying due to an increase in temperature was registered in patients with depression and cognitive decline. In order to reduce the effects of high temperatures on mortality, health intervention strategies should include mental health patients among the most vulnerable subjects taking account of their demographic and clinical characteristics. Full article

The coronavirus disease 2019 (COVID-19) pandemic is the most severe global health and socioeconomic crisis of our time, and represents the greatest challenge faced by the world since the end of the Second World War. The academic literature indicates that climatic features, specifically temperature and absolute humidity, are very important factors affecting infectious pulmonary disease epidemics - such as severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS); however, the influence of climatic parameters on COVID-19 remains extremely controversial. The goal of this study is to individuate relationships between several climate parameters (temperature, relative humidity, accumulated precipitation, solar radiation, evaporation, and wind direction and intensity), local morphological parameters, and new daily positive swabs for COVID-19, which represents the only parameter that can be statistically used to quantify the pandemic. The daily deaths parameter was not considered, because it is not reliable, due to frequent administrative errors. Daily data on meteorological conditions and new cases of COVID-19 were collected for the Lombardy Region (Northern Italy) from 1 March, 2020 to 20 April, 2020. This region exhibited the largest rate of official deaths in the world, with a value of approximately 1700 per million on 30 June 2020. Moreover, the apparent lethality was approximately 17% in this area, mainly due to the considerable housing density and the extensive presence of industrial and craft areas. Both the Mann–Kendall test and multivariate statistical analysis showed that none of the considered climatic variables exhibited statistically significant relationships with the epidemiological evolution of COVID-19, at least during spring months in temperate subcontinental climate areas, with the exception of solar radiation, which was directly related and showed an otherwise low explained variability of approximately 20%. Furthermore, the average temperatures of two highly representative meteorological stations of Molise and Lucania (Southern Italy), the most weakly affected by the pandemic, were approximately 1.5 °C lower than those in Bergamo and Brescia (Lombardy), again confirming that a significant relationship between the increase in temperature and decrease in virulence from COVID-19 is not evident, at least in Italy. Full article

Various environmental factors influence the outbreak and spread of epidemic or even pandemic events which, in turn, may cause feedbacks on the environment. The novel coronavirus disease (COVID-19) was declared a pandemic on 13 March 2020 and its rapid onset, spatial extent and complex consequences make it a once-in-a-century global disaster. Most countries responded by social distancing measures and severely diminished economic and other activities. Consequently, by the end of April 2020, the COVID-19 pandemic has led to numerous environmental impacts, both positive such as enhanced air and water quality in urban areas, and negative, such as shoreline pollution due to the disposal of sanitary consumables. This study presents an early overview of the observed and potential impacts of the COVID-19 on the environment. We argue that the effects of COVID-19 are determined mainly by anthropogenic factors which are becoming obvious as human activity diminishes across the planet, and the impacts on cities and public health will be continued in the coming years. Full article