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The COVID-19 lockdown contributes to the improvement of air quality. Most previous studies have attributed this to the reduction of human activity while ignoring the meteorological changes, this may lead to an overestimation or underestimation of the impact of COVID-19 lockdown measures on air pollution levels. To investigate this issue, we propose an XGBoost-based model to predict the concentrations of PM2.5 and PM10 during the COVID-19 lockdown period in 2022, Shanghai, and thus explore the limits of anthropogenic emission on air pollution levels by comprehensively employing the meteorological factors and the concentrations of other air pollutants. Results demonstrate that actual observations of PM2.5 and PM10 during the COVID-19 lockdown period were reduced by 60.81% and 43.12% compared with the predicted values (regarded as the period without the lockdown measures). In addition, by comparing with the time series prediction results without considering meteorological factors, the actual observations of PM2.5 and PM10 during the lockdown period were reduced by 50.20% and 19.06%, respectively, against the predicted values during the non-lockdown period. The analysis results indicate that ignoring meteorological factors will underestimate the positive impact of COVID-19 lockdown measures on air quality. © 2023 by the authors.
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Central Asian cities are one of the hotspots for air pollution worldwide. There are limited studies and knowledge regarding air quality variation in this region. This study investigated PM2.5 temporal variations and the influence of meteorological parameters on PM2.5 concentrations for six major cities in Central Asia: Almaty and Astana (Kazakhstan), Ashgabat (Turkmenistan), Bishkek (Kyrgyzstan), Dushanbe (Tajikistan), and Tashkent (Uzbekistan). The results show severe air quality deterioration in the cities with annual PM2.5 concentrations up to ten-fold higher than the limits. A clear seasonal pattern with winter peaks was observed in Almaty, Bishkek, and Astana, whereas winter and summer were highly polluted in Tashkent and Dushanbe. Based on the pollution profiles, cities were classified into several clusters. Episodes with high PM2.5 concentrations were evaluated for regional pollutant transportation using the HYSPLIT model. The results of this investigation highlight a significant discrepancy in official emissions inventory studies. While previous studies have suggested that transportation is the primary source of air pollution, the approach to estimate the share of emission sources was based on an outdated methodology that obscures information on the most hazardous pollutants, including PM2.5. This study shows that coal combustion is the primary source of PM2.5 pollution in most cities, offering policymakers critical insights into the sources of air pollution in the region. These findings demonstrate the need for policymakers to take swift action to address coal use and adopt effective measures to mitigate PM2.5 pollution, thereby improving the health and well-being of the population.
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PurposeThe COVID-19 pandemic has impacted 222 countries across the globe, with millions of people losing their lives. The threat from the virus may be assessed from the fact that most countries across the world have been forced to order partial or complete shutdown of their economies for a period of time to contain the spread of the virus. The fallout of this action manifested in loss of livelihood, migration of the labor force and severe impact on mental health due to the long duration of confinement to homes or residences.Design/methodology/approachThe current study identifies the focus areas of the research conducted on the COVID-19 pandemic. s of papers on the subject were collated from the SCOPUS database for the period December 2019 to June 2020. The collected sample data (after preprocessing) was analyzed using Topic Modeling with Latent Dirichlet Allocation.FindingsBased on the research papers published within the mentioned timeframe, the study identifies the 10 most prominent topics that formed the area of interest for the COVID-19 pandemic research.Originality/valueWhile similar studies exist, no other work has used topic modeling to comprehensively analyze the COVID-19 literature by considering diverse fields and domains.
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PM2.5 was continuously collected in Ho Chi Minh City (HCMC), Vietnam, during the period from September 2019 to August 2020, which included the period of socioeconomic suppression caused by restrictions imposed in the face of the coronavirus disease of 2019. The concentrations of PM2.5 mass, water-soluble ions (WSIs), organic carbon (OC), elemental carbon (EC), and water-soluble organic carbon (WSOC) were determined to evaluate the seasonal variations in PM2.5, the effect of socioeconomic suppression on PM2.5, and potential PM2.5 sources in HCMC. The PM2.5 mass concentration during the sampling period was 28.44 +/- 11.55 mu g m(-3) (average +/- standard deviation). OC, EC, and total WSIs accounted for 30.7 +/- 6.6%, 9.7 +/- 2.9%, and 24.9 +/- 6.6% of the PM2.5 mass, respectively. WSOC contributed 46.4 +/- 10.1% to OC mass. NO3-, SO42-, and NH4+ were the dominant species in WSIs (72.7 +/- 17.7% of the total WSIs' mass). The concentrations of PM2.5 mass and total WSIs during the rainy season were lower than those during the dry season, whereas the concentrations of carbonaceous species during the rainy season were higher. The concentrations of PM2.5 mass and chemical species during the socioeconomic suppression period significantly decreased by 45%-61% compared to the values before this period. The OC/EC ratio (3.28 +/- 0.61) and char-EC/soot-EC (4.88 +/- 2.72) suggested that biomass burning, coal combustion, vehicle emissions, cooking activities are major PM2.5 sources in HCMC. Furthermore, the results of a concentration-weighted trajectory analysis suggested that the geological sources of PM2.5 were in the local areas of HCMC and the northeast provinces of Vietnam (where coal-fired power plants are located).
ABSTRACT
Housing quality and affordability are well established as social determinants of health through direct and indirect mechanisms. Respiratory illnesses related to housing are nearly all the result of housing disrepair that allows intrusion into the home of environmental agents that are directly or indirectly associated with disease. Structural deficiencies such as leaks, cracks in the foundation or holes in the home's exterior can facilitate the presence of mould, which is causally linked to the development of asthma and is associated with exacerbation of asthma symptoms in children and adults. Indoor cleanliness can also contribute to the presence of mice and cockroaches. Proper ventilation can improve air quality, reducing exposure to PM, VOCs and infectious respiratory agents. Disparities in exposure to the housing conditions associated with respiratory disease are readily apparent across socioeconomic lines. Low-income families are less likely to be able to afford the costs of maintaining a home, which prevents them from making repairs that could improve respiratory health.Copyright © ERS 2023.
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Air pollution in India is a serious health issue. A countrywide lockdown was imposed in India in response to the COVID-19 pandemic, firstly for three weeks starting from March 24 to April 14, 2020, and then extended until May 3, 2020. Because of the restrictions imposed, pollution levels in cities all over the country have dropped dramatically in just a few days, raised questions among scientists about lockdown as the most effective alternative approach for reducing air pollution. Hyderabad was chosen for this study because it is India's 5th largest city by area and 4th largest city by population, as well as major industrial centre in South-East Asia with strong air quality statistics. In light of the recent COVID-19 outbreak around the country, a detailed analysis based on air quality parameters from six distinct air quality monitoring sites in Hyderabad, Telangana, has been performed. For simple interpretation of air quality data, establishing a correlation between different pollutants, identifying sources of pollution, and determining the most significant parameters, different multivariate statistical approaches such as Cluster analysis (CA), Principle component analysis (PCA), correlation analysis, and multiple linear regression analysis (MLR) were used. The aim of this study is to evaluate the major air pollution sources in Hyderabad and to identify the most significant air pollutants based on their individual contributions to the Air Quality Index (AQI). Variation in air quality parameters collected for six air quality monitoring stations were represented using box or whisker plots. The data set has been grouped into four major clusters depending on the similarities in the air quality data. Major sources of air pollution in each cluster were identified using PCA. MLR analysis was used to create models for predicting AQI for each cluster based on concentrations of important air contaminants. The findings revealed that PM10 and PM2.5 play a significant role in determining AQI levels. © 2023 Author(s).
ABSTRACT
COVID-19 pandemic has resulted in a halt to the daily lifestyle of people around the world and bound them to abide by the lockdown measures enforced to prevent the disease from further spreading. In India also, lockdown has been enforced from March 2020. As a result, the level of air pollutants in the atmosphere goes on decreasing. To know the air quality pattern of Bangalore city, ten stations around the city were selected. Air quality data of these stations has been availed from the Central Pollution Control Board (CPCB) of India website. Box chart concept of graphical representation has been applied to show the range of temporal variation of the air pollutants selected (CO, NO2, Ozone, PM2.5, PM10 and SO2) for the study area over two distinct periods (pre-lockdown and post-lockdown). It has been observed that all the pollutants level were drastically or significantly reduced except for SO2 which showed mixed behavior during the entire study period probably due to no restriction on the operation of power plants. GIS based contour mapping is done for each pollutant over the entire study area and separately for two distinct periods (pre-lockdown and post-lockdown). It was found that, change in CO level over the entire study area was significant and the reason behind it was complete restriction on vehicular movement which is the primary reason for CO emission in atmosphere. Reduction in PMs and ozone was also noticeable, but change in SO2 over the entire study area was almost insignificant. To find out the probable sources of pollution during the lockdown and before the lockdown period and the most significant parameters statistical approach has been adopted. The whole data set has been grouped based on similarity and divided into three distinct clusters for both pre-lockdown and post-lockdown period separately using Hierarchical Agglomerative Cluster Analysis (HACA) concept. Principal Component Analysis (PCA) was done for each of the clusters and each time period considered. From the results of PCA it can be confirmed that the most significant parameters were PM10, PM2.5, ozone and SO2. Results suggest that the probable sources of pollution during pre-lockdown period were vehicular emissions, power plants, industrial activities etc. In contrast, during post-lockdown period the sources of pollution were power plants, construction sites and household pollution only. MLR (Multiple Linear Regression) models were developed to predict Air Quality Index (AQI). Most of the models showed good fit with adjusted R2 value more than 0.9. Regression coefficient (R2) values for PM10 followed PM2.5 were highest in each cluster. © 2023 Author(s).
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The discovery of the Covid-19 virus in China at the end of 2019 has drastically altered the global landscape. The virus, which has now become a pandemic, has wrought devastation on the world, infecting over 500 million people and killing over 6 million. The virus's mutation into a few variations, however, has enabled the world's alarming situation to continue until now. Airborne particles and viruses including the new Covid-19 variant -Omricon, is not only extremely contagious but also can be transferred by airborne transmission, putting vulnerable people like children at risk, particularly in classrooms. Amongst the strategies to control airborne transmission of viruses and to improve indoor thermal and air quality is using ventilation strategies -such as dynamic insulation. Thus, this paper will review at how dynamic insulation systems in conventional farming and residential buildings, cleanrooms and other controlled environments work to reduce airborne viruses and particles in a room. An innovative "Airhouse" concept that combines with activated carbon has been researched and investigated with regard to the dynamic insulation systems.This system has a high potential to reduce the air temperature, humidity, and airborne viruses including Covid-19 whilst maintaining a steady airflow rate in a normal room. Therefore, it has a great deal of potential to decrease or eliminate concerns about the transmission of airborne viruses and adapt ventilation systems to new pandemic threats.
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From satellites to ground-based sensors, as well as mobile networks of monitors, the availability of massive data sets has increased the need for educating students in data literacy in order to ensure their competency in the global market (Bluhm et al. 2020;Gibson and Mourad 2018). The U.S. Environmental Protection Agency (EPA) defines environmental justice as, "... the fair treatment and meaningful involvement of all people regardless of race, color, national origin, or income, with respect to the development, implementation, and enforcement of environmental laws, regulations, and policies." According to Lacombe, more individuals die yearly from car exhaust (53,000) in the United States than road casualties (37,400). Students worked in groups to discuss their assumptions about factors they perceived to have an impact on air pollution levels (e.g., affluence, traffic, and vegetation).
ABSTRACT
Air pollution is a serious problem in Romania, with the country ranking 13th among the most polluted countries in Europe in the 2021 World Air Quality Report. Despite the recognized impact of pollutants on health, there has been a lack of large-scale studies conducted in Romania. This study investigated the impact of air pollutants on patients with chronic respiratory, cardiovascular, cerebrovascular, or metabolic diseases in Bucharest and its metropolitan area from 20 August 2018 to 1 June 2022. The daily limit values for particulate matter PM10 and PM2.5 were exceeded every month, especially during the cold season, with a decrease during the COVID-19 pandemic restrictions. A significant statistical correlation was found between the monthly average values of PM2.5 and PM10 and hospitalizations for respiratory and cardiovascular diseases. A 10 µg/m3 increase in monthly average values resulted in a 40–60% increase in admissions for each type of pathology, translating to more than 2000 admissions for each pathology for the study period. This study highlights the urgent need for national and local measures to ensure a cleaner environment and enhance public health in Romania according to international regulations. © 2023 by the authors.
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There is a growing concern about Indoor Environmental Quality (IEQ) in buildings as humans are spending longer in indoor environments, whether this is associated or not with climate change and vulnerability to extreme weather events. In the wake of the COVID pandemic, the need for indoor air quality control is likely to increase, the result of many adaptations in home environments to switch to remote work. In hot countries in the Global South, one of the alternatives is split A/C units with limited air renewal. While, odorless and colorless CO2, commonly generated by occupants through respiration, is among the relevant indoor air pollutants. The purpose of this study is to evaluate a low-cost, responsive air-renewal system in a climate chamber equipped with a standard split A/C unit. The results show the system's feasibility in curbing IAQ concerns and also highlight the risk of negative impacts on indoor thermal conditions and on energy consumption on using A/C. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The COVID-19 pandemic has highlighted the importance of incorporating nature-based solutions in urban design, in order to create sustainable and resilient cities. Inspired by these events, the present study aims at exploring the mental health benefits of nature exposure during the outbreak. Secondarily, we investigate changes in use patterns towards urban green spaces (UGS) and urban blue spaces (UBS) and whether extreme conditions, such as these of a lockdown, can lead to an increase in people's appreciation of urban nature. Through an online survey, we observed that the pandemic resulted in a decrease in the frequency of visitation to UGS/UBS (p < 0.001). Significant differences were found for exercise (p < 0.001) and socialization (p < 0.05) as main drivers for visiting urban nature pre- and post-lockdown. Accordingly, visitation rates for forests (p < 0.05), playgrounds (p < 0.001), and the sea (p < 0.001) differed significantly when comparing the two periods. In people's perception, UGS/UBS are important for the urban fabric (89%). Our structural equation model indicated that nature exposure had a beneficial effect on participants' mental health (p < 0.001). Pathways that explain the relationship between nature exposure and post- lockdown value were nature relatedness, motivation, and perceived importance of UGS/UBS. No mediation could be extracted for nature exposure and mental health. Our findings show the positive association between nature exposure and mental health improvement, especially in times of crisis, as well as a shift in the "value domain” towards urban nature.
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The results of a preliminary analysis of the relationship between the short-term impact of air pollution exposure on hospitalizations associated with COVID-19 in Tomsk, Russia are presented. The statistical data on air pollution and COVID-19 associated hospitalization were collected and analyzed for the period from March 16, 2022 to April 14, 2022. This period corresponds to a flat plateau of confirmed COVID-19 cases after the main pandemic wave in 2022 in Tomsk and the Tomsk region which were associated with omicron strain of SARS-CoV-2. It was found that all representative peaks in a graph of daily hospitalizations coincide with the peaks in graphs of measured levels of air pollution. The increase in hospitalizations occurred on the same days when air pollution levels increased, or with a slight lag of 1-2 days. This allows us to tentatively conclude that air pollution has a quick effect on infected persons and may provoke an increase in symptoms and severity of the disease. Further detailed research is required. © 2022 SPIE.
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Half of the world's population lives in cities, where usually there are few little green space and there are also high levels of air pollution. Moreover, the traditional urbanization of cities contributes to climate change, promotes the loss of global biodiversity and induces serious health problems for citizens. Both climate change and the loss of biodiversity affect negatively to the ecosystems and therefore human health, as they are responsible for providing clean air, food, fresh water, medicines, renewable resources. . . This deterioration increases significantly the risk of human-borne infectious diseases such as coronavirus or HIV. The ability we have to re-naturalize anthropogenic spaces and learn to generate spaces for coexistence will be key for the future of our society. The research presented in this paper aims to do a step forward to achieve that ability by working in three schools of the city of Barcelona and their surroundings. Among other actions, in this project, a diagnosis of neighborhood has been carried out. The diagnosis includes the identification and quantification of relevant indicators regarding neighborhood's biodiversity and also the quality of daily life and the analysis of pollutants (NO2 and PM10) near the schools during the 2021-2022 school year. All these information has been merged in a single geographic data base and relevant hotspots where to act have been identified. The information has been shared with city council and citizens. Copyright © 2023 by SCITEPRESS – Science and Technology Publications, Lda.
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In this paper we report two applications of a subcategory of air cleaning devices based on soft ionization that do not cause molecular fragmentation. A system that includes two unipolar ionizing modules has been used to simultaneously produce positive and negative ions in the air. In one set of experiments a large chamber (28 m3) was used to study the effect of ions on reducing PM1.0 particles produced by a research grade calibrated cigarette. The data presented in this paper were obtained using a carbon-brush-based bipolar ionizer and a MERV 10 filter with electret media in a recirculating HVAC system. Significant improvement in removal rate of fine and ultrafine particles was achieved when using the bipolar ionizer in conjunction with the MERV 10 filter. The second set of experiments were conducted using a 36 m3 chamber, following BSL-3 standards, to study the effect of ions on aerosolized SARS-CoV-2. Results of these investigations reveal the inactivation rate of SARS-CoV-2 are enhanced when ions are introduced in the air;inactivation rates were increased by more than 60%and 90%for ion densities of 10,000/cc and 18,000/cc. IEEE
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Air pollution is one of the major causes of health risks as it leads to widespread disease and death each year. Countries have invested heavily in fighting air pollution, arguably without convincing results. The outbreak of the highly infectious disease COVID-19 in December 2019 has been declared a pandemic and a worldwide health crisis by World Health Organization (WHO). Countries resorted to city lockdowns that sternly curtailed personal mobility and economic activities to control the spread of this deadly coronavirus disease. This paper examines the impact of Covid-19 city lockdowns on air quality. The researchers adopted a comprehensive interpretative document analysis for this study, which guided the careful but rigorous examination of air quality and coronavirus data. This method affirmed the authenticity of the information examined and interpreted in the US, Italy and China, the study areas. The study found that Covid-19 city lockdowns have contributed to a significant improvement in air quality within the first four months of the outbreak of Covid-19. National Aeronautics and Space Administration (NASA) had reported that NO2 concentrations in the study areas had reduced significantly using evidence from their Sentinel-5P instrument. Air quality in Covid-19 cities' lockdowns also improved because of the enforcement of other types of measures enacted to battle the virus. WHO still believes that the amount of NO2 concentration in the atmosphere is still high per their standards and regulations. Based on this, the researchers recommend that governments and other stakeholders put in much effort in terms of legislation to "win the war” against air pollution.
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PurposeThis study aims to review the role of green training and green work life balance (GWLB) on sustainable organizational performance (SOP) with a moderating variable "Emotional Intelligence” (EI).Design/methodology/approachFor the development of the construct of the present study, a Scopus database was selected and research papers published in indexed journals were considered. Relevant keywords were selected and literature was searched on green training, EI, SOP, GWLB. The literature was reviewed to find out the linkage and possibility of development of integrated model. The main focus was on highlighting the relevance of green training on GWLB and its influence on SOP.FindingsSOP can be achieved with the intervention of EI and GWLB;further green training is one of the influential practices of human resource development (HRD) which helps to develop the green behavior.Research limitations/implicationsIt can give new insight to the organization for application of green human resource practices for SOP. Development and designing the cohesive environmental work culture and willingness to protect environment through green training can be implemented by HRD. Perhaps, the application of green training encourages GWLB.Practical implicationsQuantitative research and cross sectional study is required to find out the intervening role of EI and work–life balance between green training and SOP across a broader range of sectors.Originality/valueThis research extends the literature review and developed a new integrated model which shows the link between green training and SOP.
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Air quality and environmental justice To introduce how socioeconomic status affects the physical aspects of exposure to differing air-quality levels, students used an anthropological technique of comparison to "make the strange familiar and the familiar strange." Students analyzed a New York Times story revealing the air-quality inequities of two teens residing in India: "Who Gets to Breathe Clean Air in New Delhi?" For 25 minutes, students interact with the website and reflect on paper: * One new and interesting fact that they encountered in the article about air quality, * How they think the information might relate to air quality in the United States, and * What, if anything, they think we could do to help increase awareness about these types of environmental disparities. For the next 35 minutes, students search online for articles about air quality and environmental justice in the area near our school's location. The data from real-time air quality index reports are available on every cell phone, and students decided to record it on a calendar to chart in Excel.
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Air pollution is one of the most significant concerns of the present era, which has severe and alarming effects on human health and the environment, thereby escalating the climate change issue. Hence, in-depth analysis of air pollution data and accurate air quality forecasting is crucial in controlling the growing pollution levels. It also aids in designing appropriate policies to prevent exposure to toxic pollutants and taking necessary precautionary measures. Air quality in Delhi, the capital of India, is inferior compared to other major cities in the world. In this study, daily and hourly concentrations of air pollutants in the Delhi region were collected and analyzed using various methods. A comparative analysis is performed based on months, seasons, and the topography of different stations. The effect of the Covid-19 lockdown on the reduction of pollutant levels is also studied. A correlation analysis is performed on the available data to show the relationships and dependencies among different pollutants, their relationship with weather parameters, and the correlations between the stations. Various machine learning models were used for air quality forecasting, like Linear Regression, Vector Auto Regression, Gradient Boosting Machine, Random Forest, and Decision Tree Regression. The performance of these models was compared using RMSE, MAE, and MAPE metrics. This study is focused on the dire state of air pollution in Delhi, the primary reasons behind it, and the efficacy of calculated lockdowns in bringing down pollution levels. It also highlights the potential of Linear Regression and Decision Tree Regression models in predicting the air quality for different time intervals. © 2022 IEEE.
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The outbreak of the recent Covid-19 pandemic changed many aspects of our daily life, such as the constant wearing of face masks as protection from virus transmission risks. Furthermore, it exposed the healthcare system's fragilities, showing the urgent need to design a more inclusive model that takes into account possible future emergencies, together with population's aging and new severe pathologies. In this framework, face masks can be both a physical barrier against viruses and, at the same time, a telemedical diagnostic tool. In this paper, we propose a low-cost, 3D-printed face mask able to protect the wearer from virus transmission, thanks to internal FFP2 filters, and to monitor the air quality (temperature, humidity, CO2) inside the mask. Acquired data are automatically transmitted to a web terminal, thanks to sensors and electronics embedded in the mask. Our preliminary results encourage more efforts in these regards, towards rapid, inexpensive and smart ways to integrate more sensors into the mask's breathing zone in order to use the patient's breath as a fingerprint for various diseases. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.