ABSTRACT
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.
ABSTRACT
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.
ABSTRACT
The COVID-19 pandemic has highlighted the importance of indoor air quality (IAQ) since SARS-CoV-2 may be transmitted through virus-laden aerosols in poorly ventilated spaces. Multiple air cleaning technologies have been developed to mitigate airborne transmission risk and improve IAQ. In-duct bipolar ionization technology is an air cleaning technology that can generate ions for inactivating airborne pathogens and increasing particle deposition and removal while without significant byproducts generated. Many commercial in-duct ionization systems have been developed but their practical performance on pollutant removal and potential formation of byproducts have not been investigated comprehensively. The results in this study showed that the in-duct bipolar ionization technology can significantly improve the particle removal efficiency of the regular filter, while no significant ozone and ion were released to the indoor air. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
ABSTRACT
Handan is a typical city affected by regional particulate pollution. In order to investigate particulate matter (PM) characterization, source contributions and health risks for the general populations, we collected PM samples at two sites affected by a pollution event (12–18 May 2020) during the COVID-19 pandemic and analyzed the major components (SNA, OCEC, WSIIs, and metal elements). A PCA-MLR model was used for source apportionment. The carcinogenic and non-carcinogenic risks caused by metal elements in the PM were assessed. The results show that the renewal of old neighborhoods significantly influences local PM, and primarily the PM10;the average contribution to PM10 was 27 μg/m3. The source apportionment has indicated that all other elements came from dust, except Cd, Pb and Zn, and the contribution of the dust source to PM was 60.4%. As PM2.5 grew to PM10, the PM changed from basic to acidic, resulting in a lower NH4+ concentration in PM10 than PM2.5. The carcinogenic risk of PM10 was more than 1 × 10−6 for both children and adults, and the excess mortality caused by the renewal of the community increased by 23%. Authorities should pay more attention to the impact of renewal on air quality. The backward trajectory and PSCF calculations show that both local sources and short-distance transport contribute to PM—local sources for PM10, and short-distance transport in southern Hebei, northern Henan and northern Anhui for PM2.5, SO2 and NO2. © 2023 by the authors.
ABSTRACT
Air pollution is one of the major global problems causing around 7 million dead per year. In fact, a connection between infectious disease transmission, including COVID-19, and air pollution has been proved: COVID-19 consequences on human health are found to be more severe in areas characterized by high levels of particulate matter (PM). Therefore, after the COVID-19 pandemic, the production of air filtration devices with high filtration efficiency has gained more and more attention. Herein, a review of the post-COVID-19 pandemic progress in nanofibrous polymeric membranes for air filtration is provided. First, a brief discussion on the different types of filtration mechanism and the key parameters of air filtration is proposed. The materials recently used for the production of nanofibrous filter membranes are presented, distinguishing between non-biodegradable polymeric materials and biodegradable ones. Subsequently, production technique proposed for the fabrication of nanofibrous membranes, i.e., electrospinning and solution blow spinning, are presented aiming to analyze and compare filtration efficiency, pressure drop, reusability and durability of the different polymeric system processed with different techniques. Finally, present challenges and future perspectives of nanofibrous polymeric membranes for air filtration are discussed with a particular emphasis on strategies to produce greener and more performant devices. © 2023 The Authors. Macromolecular Materials and Engineering published by Wiley-VCH GmbH.
ABSTRACT
Particulate air pollution represented by PM2.5 is one of the biggest environmental challenges in the 21st century. Especially in 2020, the global outbreak of COVID-19 has brought new challenges to melt-blown filter materials, such as the attenuation of filtration efficiency with breathing, even no filtration effect for viruses as their smaller diameter, the sharp decline of filter efficiency after oily filtration cycle, and its limit in some explosive occasions. Here, using the diameter difference of polystyrene (PS), polyvinylidene fluoride (PVDF) and nylon 6(PA6) fibers, we report a multistage structure nanofiber membrane (PS/PVDF/PA6&Ag MSNMs) with high efficiency, low resistance and antibacterial effect by constructing gradient pore structure and introducing silver nanoparticles (Ag NPs), overcoming the above defects. The average filtration efficiency of PS/PVDF/PA6&Ag MSNMs for diisooctyl sebacate (DEHS) monodisperse particles from 0.2 μm to 4.9 μm was 99.88%, and the pressure drop was only 128 Pa. After repeated circulation for 100 times, the filtration efficiency and pressure drop remained stable. Above all, the antibacterial nanofiber membrane with high efficiency and low resistance has been preliminarily constructed, the future research will further focus on the performance after circulation. © 2023 Elsevier Ltd
ABSTRACT
In this paper, there are four distinct models utilized for the retrieval of CSPM from the Sentinel 2A/2B satellite imageries by using cloud computing techniques. In this study, a comparative analysis of different CSPM models was carried out at three different sites (Haridwar, Varanasi, and Hooghly). The study reveals that there are significant changes in CSPM in the Ganges in three different periods such as pre, during, and post-COVID. Noteworthy, fewer anthropogenic activities have generated important transformations in aquatic environments during the COVID. © 2023 IEEE.
ABSTRACT
The association between oxidative protein damage in early pregnant women and ambient fine particulate matter (PM2.5) is unknown. We estimated the effect of PM2.5 exposures within seven days before blood collection on serum 3-nitrotyrosine (3-NT) and advanced oxidation protein products (AOPP) in 100 women with normal early pregnancy (NEP) and 100 women with clinically recognized early pregnancy loss (CREPL). Temporally-adjusted land use regression model was applied for estimation of maternal daily PM2.5 exposure. Daily nitrogen dioxide (NO2) exposure of each participant was estimated using city-level concentrations of NO2. Single-day lag effect of PM2.5 was analyzed using multivariable linear regression model. Net cumulative effect and distributed lag effect of PM2.5 and NO2 within seven days were analyzed using distributed lag non-linear model. In all 200 subjects, the serum 3-NT were significantly increased with the single-day lag effects (4.72%–8.04% increased at lag 0–2), distributed lag effects (2.32%–3.49% increased at lag 0–2), and cumulative effect within seven days (16.91% increased). The single-day lag effects (7.41%–10.48% increased at lag 0–1), distributed lag effects (3.42%–5.52% increased at lag 0–2), and cumulative effect within seven days (24.51% increased) of PM2.5 significantly increased serum 3-NT in CREPL group but not in NEP group. The distributed lag effects (2.62%–4.54% increased at lag 0–2) and cumulative effect within seven days (20.25% increased) of PM2.5 significantly increased serum AOPP in early pregnant women before the coronavirus disease (COVID-19) pandemic but not after that, similarly to the effects of NO2 exposures. In conclusion, PM2.5 exposures were associated with oxidative stress to protein in pregnant women in the first trimester, especially in CREPL women. Analysis of NO2 exposures suggested that combustion PM2.5 was the crucial PM2.5 component. Wearing masks may be potentially preventive in PM2.5 exposure and its related oxidative protein damage. © 2022 Elsevier Ltd
ABSTRACT
The effectiveness and cost implications are always top factors for policy makers while deciding upon the appropriate air pollution abatement measures. The present study aimed to understand the actual particulate matter (PM2.5 and PM10) patterns during different phases of COVID-19 lockdown periods and depict their spatial distributions covering the 36 major areas in Delhi, India. Drastic visible reduction in both the pollutants was found during lockdown phase 1 and 2. Average PM2.5 reductions of 41.97%, 39.24%, 56.04%, and 56.77% were recorded comparing lockdown and/or study period with the years 2018, 2019, 2021, and 2022, respectively. Similar average reduction of PM10 to the magnitude of 51.72%, 48.95%, 48.24%, and 49.00% was found for the referred years. However, the reduction during the before-lockdown period of 2018 and 2019 and the year 2020 did not follow such radical reduction returning the values for PM2.5 as 7.66-14.88% and that for PM10 as 12.86-20.67%. The geospatial maps generated for Delhi city followed the similar findings at macro level depicting huge reduction in PM distribution classes for the study period. For instance, the percent surface area under "moderately high"polluted due to PM2.5 came down to 0.61 during lockdown phase 2 from 13.96 during January 2020. Further, about 15 of the 36 locations reported compliance to the National Ambient Air Quality Standards (NAAQS) for either of the pollutants during the study period. Nevertheless, such reductions are short-lived because the levels went up again in the years 2021 and 2022 (except similar lockdowns) as the situation got back to normal daily life activities postlockdown. Although, lockdown may be imposed in case of severe ambient air quality in a densely populated megacity like Delhi, it remains a temporary or quick-fix solution, to be looked as a last line of defense. © 2023 Mary Ann Liebert, Inc., publishers.
ABSTRACT
Face masks are commonly used to protect an individual's respiratory system from inhaling fine particulate matter (PM2.5) in polluted air, as well as the airborne pathogens, especially during the ongoing coronavirus disease 2019 (COVID-19) pandemic. However, all conventional masks with anti-PM2.5 function suffer from insufficient facial thermal comfort, particularly in a hot and humid environment. Herein, we demonstrated a novel infrared-transmittance visible-opaque PM2.5 media for radiative cooling utilizing rutile titanium dioxide particle-embedded polyamide 6 (PA6-TiO2). The transmission of visible light and infrared and PM2.5 removal performance of composite media containing a variety of microstructures, such as TiO2 particles of varying sizes, shapes, and contents, were numerically examined to determine the optimal ranges. Then the PA6-TiO2 media was effectively electrospun by controlling the arrangement of fibers and the morphology of TiO2 particles. By transmitting more than 85% of the thermal radiation from the human body and selectively blocking solar irradiance, the developed PA6-TiO2(flower-shaped) media cooled the simulative skin by 10.3°C as compared with commercial masks under strong solar irradiance. Additionally, they demonstrated a high PM2.5 removal efficiency of 95.3%, a low air resistance of 22.5 Pa (at 5.3 cm/s), and a sound water vapor transmission rate of 0.0169 g cm−2 h−1. This study presents an effective strategy for making thermally comfortable anti-PM2.5 masks, which will significantly benefit the public health prevention and control. © The Author(s) 2022.
ABSTRACT
The lockdown in 2020 implemented due to the SARS-CoV-2 pandemic has resulted in a significant improvement in air quality at a global scale. Nationwide lockdown also considerably improved air quality at a local scale, especially in cities which were almost completely shut down during the first coronavirus wave, with nearly no activity. We tested the hypothesis that a reduction in the intensity of vehicle traffic causes a drastic decrease in urban air pollution at a local scale. We focused on two urban agglomerations, Warsaw and Cracow, in Poland. Data of the concentrations of traffic-related sources, namely NOx, PM10, and PM2.5, obtained from two air pollution monitoring stations were analyzed for the years 2020 and 2021, during which lockdown and pandemic restrictions were in effect, and for 2019, as a reference. In the years 2020–2021, the average annual concentration of NOx was decreased by ~ 19%, PM2.5 by ~ 19%, and PM10 by ~ 18% in Warsaw, while in Cracow the average annual concentration of NOx was decreased by ~ 16%, PM2.5 by ~ 22%, and PM10 by ~ 2%, compared to 2019. The contribution from traffic-related sources to the overall level of air pollution was estimated. The results indicated that ~ 30 µg/m3 of PM10, ~ 15 µg/m3 of PM2.5, and ~ 120 µg/m3 of NOx in Cracow, and ~ 20 µg/m3 of PM2.5 in Warsaw originate from moving vehicles. The nationwide lockdown allowed us to conduct this study to understand how a reduction in local traffic emissions can decrease ambient air pollution levels. © 2022, The Author(s).
ABSTRACT
The hospital room is the first line of assistance to patients, to ensure the comfort of doctors and patients at the same time, but also to ensure the protection of the personal safety of doctors and patients. For this reason, a good airflow organization helps to reduce the concentration of respiratory particles in the whole space and also creates a comfortable environment. Based on the CFD theory of computational fluid dynamics, ANSYS Fluent software is used to simulate the clinic environment, and four airflow organizations are used as the research objects, and the temperature cloud map, air age, and draft rate (DR) are used as the evaluation indexes, while the particulate matter concentration in the clinic is analyzed, and the 10 main indexes for evaluating the clinic environment are subjected to the principal component analysis algorithm (PCA), the four airflow organizations are comprehensive ranking. Since the traditional questionnaire has a lot of human subjectivity, using the algorithm can effectively compensate for the shortcomings of the questionnaire, and comparing the conclusions derived from the PCA algorithm with the results of the questionnaire can make the conclusions more scientific. The final conclusion is that the airflow organization of the replacement air supply can meet human comfort and air freshness while reducing the concentration of respiratory particulate matter in the clinic environment under the evaluation of various indexes, for which the replacement air supply scheme can provide a theoretical basis and reference for future construction implementation. © 2022 SPIE.
ABSTRACT
Since COVID-19 became a global pandemic, improving air quality has been increasingly important to mitigate the transmission of pathogenic aerosols. Air filters such as MERV filters have been widely used in heating, ventilation, and air conditioning (HVAC) systems to clean inlet air. In recent years, ultraviolet (UV) light has been used for decontamination and disinfection in various applications, including indoor air cleaning, e.g., upper-room ultraviolet germicidal irradiation (UVGI). There are a variety of air purification devices available in the market, with some incorporating UV technology. However, many of them are not formally tested and certified for their effectiveness in mitigating airborne pathogens and particulate matter. The research's objectives are to (1) evaluate, design, and upgrade an existing air filtration device (~2,200 CFM) with the addition of UV-C lamps;(2) test the effectiveness of the upgraded device in mitigating airborne pathogens (bacteria) and particulate matter (PM) in real scenario (poultry farm). The testing results of air quality are expressed in particular matter (PM) levels and colony-forming units (CFUs). The preliminary data showed that both MERV-8 & MERV 13 and UV-C lamps can inactivate up to 100% of airborne bacteria, and the device can remove over 95% of total PM after treatment in a ~150-layer room. © 2022 ASABE. All Rights Reserved.
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We examine the correlation between COVID-19 case activity and air pollution in two cities of Delhi and Mumbai in India. Data regarding air quality index (AQI) of PM2.5 and PM10 from Delhi and Mumbai were collected between July and November 2020. Within the same time period, confirmed cases and daily deaths due to COVID-19 in these two cities were also recorded. AQI levels in Delhi were worst in November (PM2.5: 446 ± 144.6 µg/m3;PM10: 318 ± 131.7 µg/m3) and were significantly higher as compared to Mumbai (PM2.5: 130 ± 41.2 µg/m3;PM10: 86 ± 21.2 µg/m3). This correlated with greater number of cases and higher mortality in Delhi (cases: 6243;deaths: 85) relative to Mumbai (cases: 1526;deaths: 35) during the same time period. This observational study shows that air pollution is associated with poor outcomes in patients with COVID-19. There is an urgent unmet need for appropriate public health measures to decrease air pollution along with strict policy change. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Significant topic of interest in many European countries is monitoring the air pollution, especially particulate matter (PM) concentrations, mostly because of its harmful effects on the human health. Measurement of the particulate matter concentrations can be done in a different ways, one of the possible solutions is by using low-cost and energy-efficient monitoring system using sensor network. The main goal of this paper is to analyze the influence of the green areas on particulate matter mitigation, analyzing the period of pandemic COVID-19 restrictions. The paper analyze the connection among the impact of the location of the sensor nodes and green areas and other objects to the particulate matter concentrations using various statistical tools and hypothesis testing. The tests are based on the data collected during summer 2020 at the technical campus of the Ss Cyril and Methodius University. This is the period when the World Health Organization (WHO) declared COVID-19 pandemic, and the universities were closed. In this research it can be confirmed that green areas at the Faculty pacio, reduced traffic vehicles and not having presence of the faculty staff in this period have a high impact in the reduction of particulate matter. © 2022 IEEE.
ABSTRACT
The novel coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a public health emergency of international concern. Exposure to droplets produced in the coughs and sneezes of infected individuals has been perceived as the dominant transmission mode for COVID-19. However, increasingly more evidence supports claims of COVID-19 having airborne transmission. An in-depth understanding of the transmission pathways and influencing factors of SARS-CoV-2 is of great significance for formulating more effective intervention strategies. A large number of epidemiological investigations into the influence of atmospheric environmental conditions on virus transmission have been conducted. In this paper, we review current understandings of the association between COVID-19 and atmospheric environmental conditions. We first summarize the epidemiological investigations on the impact of atmospheric environmental factors (including solar radiation, temperature and humidity, wind speed, particulate matters, and gaseous pollutants) on the spread of COVID-19, and 164 epidemiological investigations are included, in which air temperature and relative humidity received the greatest attention. However, the impact of these factors on the prevalence of COVID-19 remains largely uncertain. 56% and 41% of investigations of temperature and humidity, respectively, show that cold and dry weather promotes COVID-19 transmission, while some studies come to the opposite conclusion, and still others do not show a significant relationship between them. Investigations of solar radiation are limited, but have come to the consistent conclusion that weak solar radiation is linked to increased severity of COVID-19 infection. Investigation of the impact of air pollution mainly focuses on particulate matters, and more than 70% of investigations indicate that PM2.5 likely contributes to the spread of COVID-19. Similarly, 62%, 51%, and 31% of investigations of NOx, O3, and SO2, respectively, indicate that the exposure to severe pollution can aggravate COVID-19 transmission. Therefore, the available findings reveal the complexity of the impact of atmospheric environmental conditions on the spread of COVID-19. We further discuss their mechanisms from three perspectives: (1) Atmospheric environmental conditions influence the generation of virus-laden aerosols and the occurrence of SARS-CoV-2 in the atmosphere. Relative humidity can affect the evaporation process of water on virus-laden aerosol, and thus affect its atmospheric life and probability of being inhaled by human body. (2) Atmospheric environmental conditions directly affect the stability of infection activity of SARS-CoV-2. Generally, high temperature, medium relative humidity, and intense solar radiation promote the inactivation of SARS-CoV-2. (3) Atmospheric environmental conditions indirectly affect the infection ability of SARS-CoV-2 by changing the defense ability of host cells. Air pollutants, especially PM2.5, can affect human susceptibility to the virus by increasing the expression of the SARS-CoV-2 receptor (angiotensin converting enzyme 2) in host cells. Meanwhile, meteorological conditions and air pollution can lead to respiratory system and other diseases in the human body, thus reducing human immunity and increasing the risk of virus infection, as well as the numbers of severely infected and fatal cases. All three mechanisms may contribute to the prevalence of COVID-19, but the dominant mechanism remains unclear. Finally, future directions of in-depth studies regarding the association between the epidemic and atmospheric conditions are proposed. © 2022 Chinese Academy of Sciences. All rights reserved.
ABSTRACT
The main sources which spread communicable diseases are polluted air and vex bugs. Various kinds of microorganisms such as bacteria, viruses, fungus, and toxic particulate matter are the main pollutants in the air. Insects such as mosquitos and flies, who are called vex bugs are the carriers of those microorganisms. Industrialization and Urbanization have led to environmental pollution, and this has a direct impact on the spreading of infectious diseases. Recently, the biggest pandemic outbreak is the coronavirus. This virus is spread by polluted air. Hence this work has implemented a method using technologies such as IoT and auto-controlling, to mitigate these issues through air purification, air refreshing, and vex bugs controlling. © 2022 IEEE.
ABSTRACT
The lockdown restrictions during the COVID-19 pandemic provided a 'path' of reinstatement of the air quality globally. Despite several financial challenges, air quality improvement positively impacted the environment due to lockdown in the worst pandemic situations. The present study assessed the air pollution scenario in the post lockdown phase in the seven major metropolises of Rajasthan, namely, Jodhpur, Alwar, Jaipur, Kota, Pali, Ajmer, and Udaipur) in the recent pandemic year 2020. The air pollution scenario is determined with the help of the Air Quality Index (AQI) and the concentration level of PM2.5 PM10, NO2, and SO2. This study reveals that Most Cities of Rajasthan are violating India's national ambient air quality standards (NAAQS). It is found that Jodhpur is on rank first in terms of pollution levels, followed by Alwar, Jaipur, Pali, and Udaipur. The pollution level was higher before the lockdown period then reduced to a certain level due to restricted activities in lockdown. The pollution level is not rapidly increased after lockdown due to rainfall occurred in Rainy season from Southwest monsoon. Winter Season consists of higher concentration levels of pollutant and higher than Before Lockdown Period. The study shows the Significant impact of lockdown in reducing air pollution levels in cities. But imposing lockdown in a city or country is not a permanent solution to curb air pollution. So, regulating agencies and stakeholders should implement better control and reduction technologies for Indian cities. © The Electrochemical Society
ABSTRACT
The lockdown measures implemented due to the SARS-CoV-2 pandemic to reduce the epidemic curve, in most cases, have had a positive impact on air quality indices. Our study describes the changes in the concentration levels of PM2.5 and PM10 during the lockdown and post-lockdown in Victoria, Mexico, considering the following periods: before the lockdown (BL) from 16 February to 14 March, during the lockdown (DL) from 15 March to 2 May, and in the partial lockdown (PL) from 3 May to 6 June. When comparing the DL period of 2019 and 2020, we document a reduction in the average concentration of PM2.5 and PM10 of −55.56% and −55.17%, respectively. Moreover, we note a decrease of −53.57% for PM2.5 and −51.61% for PM10 in the PL period. When contrasting the average concentration between the DL periods of 2020 and 2021, an increase of 91.67% for PM2.5 and 100.00% for PM10 was identified. Furthermore, in the PL periods of 2020 and 2021, an increase of 38.46% and 31.33% was observed for PM2.5 and PM10, respectively. On the other hand, when comparing the concentrations of PM2.5 in the three periods of 2020, we found a decrease between BL and DL of −50.00%, between BL and PL a decrease of −45.83%, and an increase of 8.33% between DL and PL. In the case of PM10, a decrease of −48.00% between BL and DL, −40.00% between BL and PL, and an increase of 15.38% between the DL and PL periods were observed. In addition, we performed a non-parametric statistical analysis, where a significant statistical difference was found between the DL-2020 and DL-2019 pairs (x2 = 1.204) and between the DL-2021 and DL-2019 pairs (x2 = 0.372), with a p < 0.000 for PM2.5, and the contrast between pairs of PM10 (DL) showed a significant difference between all pairs with p < 0.01. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
ABSTRACT
Although humans spend a majority of their lives in indoor environments, indoor air quality is immensely understudied, compared to ambient air. Here, we show the first long-term measurements of household indoor PM concentrations in the southeastern United States, for one year (May 2019 through April 2020) covering the COVID-19 hard-lockdown period (March and April 2020). Particle size distributions between 0.25–35 µm were measured with a low-cost sensor, which does not utilize hazardous chemicals and radiation sources and is ideal for indoor air monitoring in real households without disruption of residents’ living conditions. Our observations show that while cooking and cleaning are two major emissions sources for the residential indoor PM, consistent with the literature knowledge, but we also show that human occupancy affects the indoor PM level substantially. During the hard lockdown during the COVID-19 pandemic, the background level of indoor PM increased by ~200%, while the ambient PM decreased by ~50% during the same period. Before the pandemic, the indoor PM level was lower than the outdoor, but it became similar or higher than the outdoor level during the pandemic. Thanksgiving holiday cooking (prior to COVID-19) produced high concentrations of PM for an extended period (e.g., over 6 hours) even with active kitchen ventilation. PM concentrations during a cooking and cleaning event usually increased linearly to a maximum value and then decayed exponentially. The decay time of indoor PM ranged from several minutes up to ~100 minutes and increased with the particle size, indicating that particle deposition to the interior surfaces is the main sink process of the indoor PM. © 2022, AAGR Aerosol and Air Quality Research. All rights reserved.