A clustering review of vegetation-indicating parameters in urban thermal environment studies towards various factors.

People in outdoor areas suffer from more heat stress than indoors during warm seasons due to the lack of shelters or cooling facilities. This problem is pressing with urban heat island and continuous global warming. Researchers have explored various strategies for ameliorating thermal stress, coining the term 'outdoor thermal environment (OTE)' for this area of study. It has been found that the OTE is affected by vegetation and other factors (i.e., geometry) of a location. There have been many studies on vegetation, with these conducted at various levels and using different methods. Several parameters have been used to characterise vegetation and have been found to statistically correlate with many thermal indices (i.e., physiologically equivalent temperature, PET; universal thermal climate index, UTCI etc.). This article reports on a review of journal papers that investigated the climatic regulations of vegetation. In this study vegetation-indicating parameters were clustered according to the methods, scope, and thermal indices. Studies involving large scales preferred general indicators (e.g., NDVI, vegetation cover etc.) whereas specific, detailed parameters (e.g., crown sizes) were more frequently used in studies of micro levels. Outdoor thermal environment studies involving vegetation were mostly conducted in regions with high heat stress levels. Also, remote sensing and meteorological station observation were more frequently used in large-scale studies, while small-scale studies preferred simulation and field measurements. Their findings were expressed by the statistical correlation between vegetation parameters and thermal indices. For instance, NDVI, LAI, and crown size were negatively correlating with temperatures. The findings of this study help inform directions for future vegetation studies regarding outdoor thermal environment designs. Researchers would be clearer on selection methods and thermal indices regarding their targets and supporting tools.

A study of physical factors influencing park cooling intensities and their effects in different time of the day.

The quality of residents' lives have been negatively affected by problems resulting from global warming and urban heat island. Investigators have explored several ways to mitigate those problems. They found that vegetation (especially trees) and water surfaces played a significant role in the adjustments of climate. Sites with more vegetation and larger-size waterbodies were cooler. However, the cooling effects of these elements were affected by contextual factors. For instance, cooling intensities of both vegetation and water surfaces fluctuated through the day. To further explore this phenomenon, this study investigated the cooling effects of trees and large waterbodies at different times of the day by means of field measurement. It was found that leaf area index (LAI) and distance from the sea (DFS) had a significant impact on park cooling intensities (PCI). Park points with more trees (indicated higher LAI) and those located closer to the sea were cooler. In addition, their cooling effects varied depending on the time of the day. LAI showed significant microclimatic adjusting effects late in the evening. Increasing the LAI by 1 point could help increase the PCI by 0.31 °C (18:00, R2 = 0.2421). In contrast, rising DFS resulted in PCI decrease by more than 2 °C (12:00 p.m., R2 = 0.4327). Cooling performances of the two factors were significant at different time periods of the day, that is, in the noon (the sea) and evening (trees) respectively. Further, the cooling effects of the trees might be affected by the distance from the sea. Findings from this study provided new understandings towards the climatic conditions of waterside cities.

Anxiety and depression and the related factors in nurses of Guilan University of Medical Sciences hospitals during COVID-19: A web-based cross-sectional study.

BACKGROUND: The outbreak of COVID-19 is an unprecedented challenge to the health systems in Iran. We aimed to assess the psychological impact of this outbreak on nurses in the hospitals of Guilan University of Medical Sciences that is one of the top provinces of incidence of COVID-19. METHODS: In a web-based cross-sectional study, 441 nurses working were selected from the hospitals, from 7 to 12 April 2020. Anxiety and depression were measured using the Generalized Anxiety Disorder-7 and the Patient Health Questionnaire-9, respectively. Simple and multiple logistic regression models were used to identify the factors related to anxiety and depression. RESULTS: The majority were in contact with suspected or confirmed COVID-19 cases (93.4%) and their relatives had been infected with COVID-19 (42%). The mean of anxiety-7 and depression total scores were 8.64 ± 5.60 and 8.48 ± 6.19, respectively. Female (OR = 3.27, 95% CI = 1.01-10.64), working in COVID-19 designated hospital (OR = 1.82, 95% CI = 1.13-2.93), being suspected with COVID-19 infection (OR = 2.01, 95% CI = 1.25-3.26), and insufficient personal protective equipment (OR = 2.61, 95% CI = 1.68-4.06) were associated with anxiety. Depression was significantly associated with female sex (OR = 4.62, %95 CI = 1.24-17.16), having chronic disease (OR = 2.12, 95% CI = 1.20-3.74), being suspected or confirmed with COVID-19 infection (OR = 3.44, 95% CI = 2.11-5.59, and OR = 2.21, 95% CI = 1.04-4.70, respectively), and insufficient personal protective equipment (OR = 1.86, 95% CI = 1.19-2.91). CONCLUSION: The finding declares healthcare workers are at high risk for mental illness. Continuous supervision of the psychological consequences following infectious diseases outbreaks should be a part of the preparedness efforts of health care systems.

Quality of Life (QoL) Survey in Hong Kong: Understanding the Importance of Housing Environment and Needs of Residents from Different Housing Sectors.

This study presents a Quality of Life (QoL) survey to understand the influence of the housing environment and needs of residents from different housing sectors. The research focuses on Hong Kong where living conditions have become the main affect for people's QoL. Through a household survey using a standard instrument "Word Health Organisation (WHO) Quality of Life-BREF", the article found that among the four WHO QoL domains (Physical Health, Psychological Health, Social Relations And Environment), Environment, particularly its constitute aspect housing environment was the most influential factor for overall quality of life for the public rental housing sector where low-income people live. This research also found that different groups of people have differing needs of their housing environments: the low-income group needs better location and privacy while the medium and high-income groups need better architectural quality. Based on differentiating their needs and wants, this research argues for prioritizing the low-income group's needs for effectively improving their QoL.