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The indoor climate of non-climatized churches is usually subject to cyclical fluctuations of temperature and relative humidity induced by external climate conditions which might be dampened by the high thermal capacity of their envelope. However, several phenomena affect their indoor climate (e.g., internal gains due to people and artificial lighting, air infiltration, etc.), which lead to environmental variations that might jeopardize the artworks contained within. In particular, one of the most influential parameters that may affect non-climatized churches is the massive and intermittent presence of people who constantly visit their spaces. In such regard, long-term monitoring allows the collection of environmental data with different building operation conditions and visitor fluxes. This paper analyses the indoor climate of the Milan Cathedral (Duomo di Milano) in Italy for three continuous years (including the lockdown period that occurred in 2020 caused by the COVID-19 pandemic), with a focus on visitors' effects on the indoor environment and the conservation of the main artworks contained within. The results of the analysis have shown that spaces with huge volume are most influenced by the opening of the doors rather than the hygrothermal contribution of the intermittent presence of massive crowds. Moreover, the absence of visitors for a prolonged period correlates with an improvement in the indoor conservation conditions for artworks, especially those made of hygroscopic materials, due to the reduction in short, rapid climate fluctuations.
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The increasing concentration of anthropogenic CO2 in the atmosphere is causing a global environmental crisis, forcing significant reductions in emissions. Among the existing CO2 capture technologies, microalgae-guided sequestration is seen as one of the more promising and sustainable solutions. The present review article compares CO2 emissions in the EU with other global economies, and outlines EU's climate policy together with current and proposed EU climate regulations. Furthermore, it summarizes the current state of knowledge on controlled microalgal cultures, indicates the importance of CO2 phycoremediation methods, and assesses the importance of microalgae-based systems for long-term storage and utilization of CO2. It also outlines how far microalgae technologies within the EU have developed on the quantitative and technological levels, together with prospects for future development. The literature overview has shown that large-scale take-up of technological solutions for the production and use of microalgal biomass is hampered by economic, technological, and legal barriers. Unsuitable climate conditions are an additional impediment, forcing operators to implement technologies that maintain appropriate temperature and lighting conditions in photobioreactors, considerably driving up the associated investment and operational costs.
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Most of recent events have attracted a lot of attention towards importance of automatic crowd classification and management. COVID-19 is the most setback for the entire world. During these events proper breakout and public crowd management leads to the requirement of managing, counting, securing as well as tracking the crowd. But automatic analysis of the crowd is very challenging task because of varying climatic and lighting conditions, varying postures etc. During this paper we have developed PYTHON based system for automatic crowd images classification using Deep learning. This paper is the first attempt for automatic classification of crowd images. We have prepared the dataset of crowd classification consisting of three categories. The proposed methodology of crowd classification starts with preprocessing during which we have used median filtering for noise removal. Deep learning models are developed using 70% training images. The performance of the system is evaluated for various deep learning algorithms including one block VGG, two block VGG and three block VGG. We have also evaluated the performance of three block VGG using dropout. VGG16 transfer learning based crowd classification is developed using PYTHON. Using VGG16 transfer learning we achieved the accuracy of 69.44.% which is highest among all deep learning classification models during this study © 2022 IEEE.
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Air pollution is one of the worst avoidable threats in developing nations across the world. India has undergone a substantial number of infrastructure changes during recent years due to the ever-increasing population. This and the consequent industrialization, the air quality of Indian cities became worsened. The changes in climatic conditions across various cities in India also contribute to air pollution. To control the air pollution within the acceptable limit several control measures have been imposed in India, despite these efforts the air pollution level has not decreased considerably. In India, the first COVID-19 case has reported on 30th January 2020 in the state of Kerala. To control the quick spread of COVID-19 in India, the central government executed a three-week nationwide lockdown from 24th March 2020, and further, it has extended into several phases. It was the first time in India a long-term shutting down of all the sectors happening and which resulted in positively on the environment. This study is dealing with the lockdown effect on air quality in metro cities in India and is compared with the pre-existing conditions. Also, the seasonal variations in air quality in the course of the past two years are compared. The data of pollutants PM10, PM2.5, SO2, NO2, O3, CO, and NH3 from metro cities were collected and by adopting the National Air Quality Index to depict the variations in overall air quality. During the lockdown period, most of the cities experience a considerable improvement in overall air quality and PM10, NO2, PM2.5, and CO concentrations. Whereas, the Ozone shows some increasing trend in a few cities might be due to the increment in the temperature caused by the exposure of sun during the summer season. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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A numerical analysis using OpenFOAM has been performed in this work to investigate the infection risk due to droplet dispersal in an enclosed environment resembling an elevator, since infection risk in such confined places is very high. The effect of two scenarios on droplet dispersal, namely, the quiescent and the fan-driven ventilation, both subjected to various climatic conditions (of temperature and humidity) ranging from cold-humid (15 °C, 70% relative humidity) to hot-dry (30 °C, 30% relative humidity) have been studied. A risk factor derived from a dose-response model constructed upon the temporally averaged pathogen quantity existing around the commuter's mouth is used to quantify the risk of infection through airborne mode. It is found that the hot, dry quiescent scenario poses the greatest threat of infection (spatio-averaged risk factor 42%), whereas the cold-humid condition poses the least risk of infection (spatio-averaged risk factor 30%). The proper fan speed is determined for the epidemiologically safe operation of the elevator. The fan ventilation scenario with 1100 RPM (having a spatio-averaged risk factor of 10%) decreases the risk of infection by 67% in a hot, dry climatic condition as compared to a quiescent scenario and significantly in other climatic ambiences as well. The deposition potential of aerosolized droplets in various parts of the respiratory tract, namely, the extrathoracic and the alveolar and bronchial regions, has been analyzed thoroughly because of the concomitant repercussions of infection in various depths of the respiratory region. In addition, the airborne mode of infection and the fomite mode of infection (infection through touch) have also been investigated for both the ventilation scenarios. © 2022 Author(s).
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Evidence shows that people have a major impact on building performance. Occupants’ impact is especially important in social housing, where their occupants may present greater vulnerabilities, and their needs are not always considered. This study aims to analyse the socio-demographic influence in social rental housing concerning hygrothermal comfort and energy consumption in a case study located in Vitoria, Spain during the first 4-month period of 2020 and 2021 (during and after COVID-19 lockdown). An innovative data management system is included, where the users and administration can see in real-time the temperature and consumption in the dwellings. A 2-phase method has been applied;phase 1 is associated with outdoor climate conditions, building properties and social profile. Phase 2 determined the results in energy consumption, indoor hygrothermal comfort and occupant energy-use pattern. The results show that the comfort levels and energy consumption vary according to the analysed social profiles, as well as the heating activation periods and domestic hot water system usage. In conclusion, socio-demographic characteristics of social housing households influence the hygrothermal comfort of their dwellings, occupants’ behaviour and heating and domestic hot water energy consumption.
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After more than a year from the first confirmed cases of coronavirus (COVID-19) disease, the role of meteorological factors in the transmission of the virus still needs to be correctly determined. In this scenario of deep uncertainty, the present study aims to investigate the effects of temperature and relative humidity on daily new cases of COVID-19. For this purpose, the COVID-19's development of infection in fourteen Algerian cities characterized by different climatic conditions, during the period from April 1, 2020, to August 31, 2020, has been investigated. A detailed time series analysis along with linear regression was used to state a possible correlation among some climate's factor variability (temperature and relative humidity) and daily new confirmed cases of COVID-19. The results showed a weak correlation between daily new cases of COVID-19 and meteorological factors throughout the selected regions. In addition, we concluded that the COVID-19 could fit to high or low values of temperature and relative humidity, and other factors not climates could affect the spreading of the virus like demography and human contact. So, after the discovery of the vaccine and before vaccination of 70% of the world's population, living with the virus has become an inevitable reality, and it is mandatory to apply the sanitary procedures to slow down the COVID-19 transmission.
Subject(s)
COVID-19 , Pandemics , Africa, Northern , Algeria/epidemiology , COVID-19/epidemiology , Humans , Humidity , SARS-CoV-2 , TemperatureABSTRACT
The incidence of type 1 diabetes (T1D) is increasing worldwide. The onset of T1D usually occurs in childhood and is caused by the selective destruction of insulin-producing pancreatic islet cells (ß-cells) by autoreactive T cells, leading to insulin deficiency. Despite advanced research and enormous progress in medicine, the causes of T1D are still not fully understood. Therefore, an extensive online search for scientific research on environmental factors associated with diabetes and the identification of new factors of unexplained etiology has been carried out using the PubMed, Cochrane, and Embase databases. The search results were limited to the past 11 years of research and discovered 143 manuscripts published between 2011 and 2022. Additionally, 21 manuscripts from between 2000 and 2010 and 3 manuscripts from 1974 to 2000 were referenced for historical reference as the first studies showcasing a certain phenomenon or mechanism. More and more scientists are inclined to believe that environmental factors are responsible for the increased incidence of diabetes. Research results show that higher T1D incidence is associated with vitamin D deficiency, a colder climate, and pollution of the environment, as well as the influence of viral, bacterial, and yeast-like fungi infections. The key viral infections affecting the risk of developing T1DM are rubella virus, mumps virus, Coxsackie virus, cytomegalovirus, and enterovirus. Since 2020, i.e., from the beginning of the COVID-19 pandemic, more and more studies have been looking for a link between Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and diabetes development. A better understanding of the role of viral, bacterial, and yeast-like fungi infections related to the risk of T1DM in children and adolescents and the identification of new risk factors, especially those spread by the droplet route, is of great importance for people and families with diabetes.
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The prefabricated anti-epidemic emergency hospital needs its own characteristics of reasonable process, rapid construction and safe operation. Based on the specific climatic conditions in the severe cold region of Northeast China, the operation of the actual project and the problems exposed are analyzed. At the same time, in the face of the global epidemic To prevent and control the trend of long-term and normalization, comprehensively consider the relationship between construction input costs and long-term operation and maintenance funds and the possibility of fluctuations in the epidemic situation, so as to ensure the flexibility and variability of the combined use of prefabricated anti-epidemic emergency hospitals. The principle of energy-saving design is implemented in the design to solve the contradiction between the short construction period and high daily operation and maintenance costs of the prefabricated anti-epidemic emergency hospital in severe cold areas. Green medical environment.
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Grasslands on the Mongolian Plateau are critical for supporting local sustainable development. Sufficient measured sample information is the basis of remote sensing modeling and estimation of grassland production. Limited by field inventory costs, it is difficult to collect sufficient and widely distributed samples in the Mongolian Plateau, especially in transboundary areas, which affects the results of grassland production estimation. Here, considering that the measured sample points are sparse, this study took Xilingol League of Inner Mongolia Autonomous Region in China and Dornogovi Province in Mongolia as the study areas, introduced multiple interpolation methods for interpolation experiments, established a statistical regression model based on the above measured and interpolated samples combined with the normalized differential vegetation index, and discussed the applicability of grassland production estimation. The comparison results revealed that the point estimation biased sample hospital-based area disease estimation method and radial basis function showed the best interpolation results for grassland production in Xilingol League and Dornogovi Province, respectively. The power function model was suitable for grassland production estimation in both regions. By inversion, we obtained annual grassland production for 2010–2021 and the uneven spatial distribution of grassland production in both regions. In these two regions, the spatial change in grassland production showed a decreasing trend from northeast to southwest, and the interannual change generally showed a dynamic upward trend. The growth rate of grassland output was faster in Xilingol League than in Dornogovi Province with similar physical geography and climate conditions, indicating that the animal husbandry regulation policies play important roles beyond the influence of climate change. The study recommended grassland estimation methods for an area with sparse samples and the results can be used to support decision making for sustainable animal husbandry and grassland succession management.
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In this article, the legal and regulatory concepts for the use of renewable energy in the construction industry are reviewed, relying on some laws in a number of countries, which were taken into account as a model for its application in Iraqi cities. In this article, we have highlighted the problems and prospects for the application of renewable energy in general, including marine energy represented by wave, tidal energy, and its predictability. Also, in this article, we put a brief study on concentrated solar energy and the technology used to generate electricity using energy from solar radiation through the technology known as CSP. In summary, we reviewed the most important challenges that faced renewable energy projects as a result of the outbreak of the Corona virus, Covid-19, the health crisis that led to hundreds of victims among the cadres working in this field, and thus the energy sectors were directly affected as a result of the tightening of preventive measures and the budgets of many countries.
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Exploitation of oil and gas resources in the Arctic offshore is one of Russia’s key priorities in such areas as science, economy, and technology. Global trends, harsh climate conditions, fragile ecosystems, conditions of the pandemic and post-pandemic periods, price volatility, and the growing importance of the environmental factor require that the process of developing the Arctic’s hydrocarbon resources should become strategically sustainable. The paper provides a deep literature review on sustainability issues, sustainable development, strategic sustainability, and project efficiency in the Arctic offshore oil and gas sector. The paper analyzes the trends and conditions that substantiate the need to transform the traditional sustainability concept to meet new challenges and comply with new policies. Based on the analysis, the authors propose a definition of and a conceptual framework for strategic sustainability of oil and gas offshore projects in the Arctic.
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Temporary structures are being extensively used by emergency services (rescue, disaster relief, military response units), and other end-users requiring temporary mobile off-grid energy solutions for different purposes (event organization, vacation homes, summer camps, etc.). Yet energy systems for these purposes largely remain fossil-based (such as diesel generators). Although such energy systems are inexpensive, they are carbon intensive and inefficient. This study presents a methodology of simulating temporary shelter with access to an energy supply system through a mobile energy unit with renewable (PV) power supply systems to ensure on-site electricity production, as well as heating/cooling and ventilation. Digital modeling simulations have been performed for a simulated temporary shelter in different climate conditions incorporating different combinations of electricity generation systems with a fossil fuel-based solution and a PV system, using TRNSYS software. Study results show that the operation of a mobile energy generation unit can operate HVAC systems and generate electricity for temporary shelter occupants in off-grid solutions. The modeling results show that the use of a mobile energy generation unit can significantly reduce diesel consumption in temporary shelters from 54% annually (in Riga, Latvia) to 96 % annually (in Jerusalem, Israel). Furthermore, the output of PV-generated electricity is higher (in most cases) than the consumed electricity amount.
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(1) Background: considering multiple, and somehow conflicting, design objectives can potentially make achieving a high-performance design a complex task to perform. For instance, shading devices can dramatically affect the building performance in various ways, such as energy consumption and daylight. This paper introduces a novel procedure for designing shading devices as an integral part of daylightophil architecture for office buildings by considering daylight and energy performance as objectives to be optimal. (2) Methods: to address the topic, a three-step research method was used. Firstly, three different window shades (fixed and dynamic) were modeled, one of which was inspired by traditional Iranian structures, as the main options for evaluation. Secondly, each option was evaluated for energy performance and daylight-related variables in critical days throughout the year in terms of climatic conditions and daylight situations (equinoxes and solstices including 20 March, 21 June, 22 September, and 21 December). Finally, to achieve a reliable result, apart from the results of the comparison of three options, all possible options for fixed and dynamic shades were analyzed through a multi-objective optimization to compare fixed and dynamic options and to find the optimal condition for dynamic options at different times of the day. (3) Results: through different stages of analysis, the findings suggest that, firstly, dynamic shading devices are more efficient than fixed shading devices in terms of energy efficiency, occupants’ visual comfort, and efficient use of daylight (roughly 10%). Moreover, through analyzing dynamic shading devices in different seasons and different times of the year, the optimal form of this shading device was determined. The results indicate that considering proper shading devices can have a significant improvement on achieving high-performance architecture in office buildings. This implies good potential for daylightophil architecture, but would require further studies to be confirmed as a principle for designing office buildings.
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At the beginning of the SARS-COV-2 outbreak in Brazil, there was a striking difference between the contamination rate in the Amazonian States and the South and the Southeast States. The regions near the Amazon rainforest presented much higher and faster contaminations. This paper attempts to explain this phenomenon through a global analysis of the COVID-19 epidemic in Brazil. It also investigates the relationship between climate conditions and airborne transmission with the evolution of contagion in the Amazonian states. The method of investigation of the spread of SARS-COV-2 in these different macro-environments was based on the analysis of three extensive daily official databases on the number of deaths, the percentage of adherence of the populations to the restriction policies, and the local climatic conditions. Besides, the social conditions in those States were also taken into account. Then, it was compared the epidemiologic results for States with very different climatic characteristics and that had adopted, almost simultaneously, similar social isolation measures. However, all these analyses were not able to explain the remarkable difference in the evolution of the pandemic among Brazilian regions. So, it was necessary to invoke airborne transmission, facilitated by the very high air humidity, as a decisive factor to explain the faster evolution of contagion in the rainforest region. Air humidity seems to be the most important climatic factor in viral spreading, while usual ambient temperatures do not have a strong influence. Another very important result of this analysis was the observation that the onset of collective immunity may have been achieved with a contamination rate of about 15% of the Amazonian population.
Subject(s)
COVID-19 , Disease Outbreaks , SARS-CoV-2 , Brazil/epidemiology , COVID-19/epidemiology , Humans , Humidity , Rainforest , TemperatureABSTRACT
In Asia, Europe and South America, the role of atmospheric condition in aiding or abating the growth curve of COVID-19 has been analysed. However, no study to date has examined such climatic extensions for the growth or otherwise of the novel coronavirus in Africa. Africa, with a mostly relatively warmer temperature differs from other regions of the world and in addition, has recorded far fewer cases compared to Asian, Europeans and the Americans (North and South). It then becomes imperative to examine the influence of meteorological indices in the growth or otherwise of coronavirus diseases in Africa to establish whether findings on the climatic conditions-COVID-19 growth are regionally specific. In this study, we examined the influence of meteorological factors for aiding or abating the spread of the aerosolised pathogen of COVID-19 in Africa. We rely on the generalised additive model (GAM) and found wind speed to positively relate to COVID-19 growth while mean temperature and relative humidity to inversely relates to COVID-19 growth curve in Africa. We accounted for potential cofounders in the core GAM model and discuss policy implications.