Indoor Particle Concentrations Research Articles

Reducing Indoor Particulate Air Pollution Improves Student Test Scores: A Randomized Double-Blind Crossover Study.

Short-term exposure to air pollution is associated with a decline in cognitive function. Standardized test scores have been employed to evaluate the effects of air pollution exposure on cognitive performance. Few studies aimed to prove whether air pollution is responsible for reduced test scores; none have implemented a "gold-standard" method for assessing the association such as a randomized, double-blind intervention. This study used a "gold-standard" method─randomized, double-blind crossover─to assess whether reducing short-term indoor particle concentrations results in improved test scores in college students in Tianjin, China. Participants (n = 162) were randomly assigned to one of two similar classrooms and completed a standardized English test on two consecutive weekends. Air purifiers with active or sham (i.e., filter removed) particle filtration were placed in each classroom. The filtration mode was switched between the two test days. Linear mixed-effect models were used to evaluate the effect of the intervention mode on the test scores. The results show that air purification (i.e., reducing PM) was significantly associated with increases in the z score for combined (0.11 [95%CI: 0.02, 0.21]) and reading (0.11 [95%CI: 0.00, 0.22]) components. In conclusion, a short-term reduction in indoor particle concentration led to improved test scores in students, suggesting an improvement in cognitive function.

The Impact of Indoor Air Humidity on the Infiltration of Ambient Particles

Ambient particles contribute to occupant exposure as they infiltrate indoor environments through building envelope cracks, impacting indoor air quality. This study investigates the impact of indoor air humidity on the infiltration of ambient particles, highlighting humidity’s crucial role in influencing particle dynamics in indoor environments. Employing a controlled chamber system, we conducted experiments to quantify the infiltration of size-resolved particles under varying relative humidity (RH) conditions. Both the total number and the mass concentration of particles increased with RH in the experimental chamber. The smallest particles (0.3–0.4 μm) experienced reduced infiltration at higher RH levels due to hygroscopic growth, while intermediate-sized particles showed increased infiltration, resulted from coagulation effects. Large particles (>1.0 μm) demonstrated reduced infiltration factors, caused by lower penetration and higher deposition rates, with minimal impact from RH changes. Our findings reveal that RH influences particle hygroscopic growth, deposition rate, and coagulation process, thereby affecting indoor particle size distribution and concentration.

Particle characterization in commercial buildings: A cross-sectional study in 40 offices in Singapore

There is a knowledge gap in understanding how existing office buildings are protecting occupants from exposure to particles from both indoor and outdoor sources. We report a cross-sectional study involving weekly measurements of size-resolved indoor and outdoor particle concentrations in forty commercial building offices in Singapore. The outdoor and indoor particles size distributions were single mode with daytime peak number concentrations at 36.5 nm and 48.7 nm. Outdoor concentrations were significantly greater than indoors for all particle diameters. Indoor particle concentrations were generally low due to: 1) relatively high indoor particle removal (IPR) rates; 2) low indoor source strengths; and 3) low indoor particle of outdoor proportion (IPOP). We found that the ventilation system type had a substantial effect on indoor particle levels, IPR and IPOP. Through linear mixed model analyses, we identified dependencies of IPR rates with the use of MERV13 filters in supply air and filter maintenance frequency, IPOP with the use of MERV13 filters in the fresh air and supply air ducts and low particle source strength with regular daily cleaning presumably due to dust reservoir removal. Lastly, the contribution of outdoor sources was mainly seen for ultrafine and fine particles but less pronounced for coarse particles. This study provided detailed understanding of particle exposure in building offices and their influencing factors, facilitating future research on health impact of particle exposures.

Prediction model for vertical distribution of oil particles under thermal plume and displacement ventilation in a machining workshop

Oil particle concentrations exhibit an inhomogeneous distribution in large-space machining workshops with a displacement ventilation system. The inhomogeneous distribution can lead to variations in the required supply air volume used to control the indoor particle concentration at different heights. To rapidly calculate the particle concentration distribution in the vertical direction, this study established a zonal particle concentration prediction model based on the mass and energy balance by considering the interaction between the heat source thermal plume, wall thermal plume, and supply airflow. An experiment was conducted in a scaled chamber to validate the proposed prediction model. The result showed that the relative error between the prediction model and experiment ranged from −17% to 10%. A case study was performed to demonstrate the applicability of the prediction model to the control of a displacement ventilation system. Using the prediction model, the control system can maintain the particle concentration in the work area below 0.5 mg/m³with variable particle source emission rates and reduce the supply air volume by at least 24% and 55% compared with the variable and constant air volume systems, respectively, neither of which can address the inhomogeneous distribution of oil particle concentration. The prediction model can also be used for the design of displacement ventilation systems when the inhomogeneous particle concentration distribution is considerable.

The research on the particle concentration distribution of directed airflow in cleanrooms for operators.

Existing research of non-unidirectional cleanrooms generally suggests that lower-side return air outlets provide better control effect on indoor particle concentration. As a result, there has been relatively less focus on return air outlets. However, installing return air outlets oriented towards operators as particle emission sources can reduce the impact on process layout and improve space utilization, while also provide less impact from upper particle emission sources on the workbench area. To investigate the characteristics of return air outlet for operators (abbreviated as H), this study compared the particle concentration distribution, non-uniformity, and purification efficiency of return air oultet H and the traditional lower-side (abbreviated as L) return air outlets by experiments and CFD simulations. Based on the theory of mass conservation, the expression of required air supply volume under equivalent cleanroom conditions was derived. Under corresponding experimental and simulation conditions, the particle concentration differences range from 2.0% to 12.7% for return air outlet H and from 12.4% to 33.2% for return air outlet L, and these differences gradually decrease with the air exchange rate (ACH) increases. The results show that ACH = 20 is sufficient for cleanliness requirements with return air outlet H when there is one person in the cleanroom, while a higher rate of ACH = 35 is needed when there are two persons. Although lower-side return air outlets have certain potential for reducing particle concentration in the cleanroom, increasing the air exchange rate remains the most effective method to control indoor particle concentration. Compared to the traditional lower-side return air outlet L, the ranges of the non-uniformity coefficients for return air outlet H and L are 0.50 to 0.67 and 0.45 to 0.53, respectively. The average non-uniformity coefficient differs by 11.9%, and there is not a significant difference in uniformity with more than 20 air changes per hour. The use of return air outlets H only requires an additional 11% of air supply volume to achieve the same cleanliness, demonstrating its effectiveness in controlling particle concentration. It is suitable for cleanrooms with higher requirements for workbenches and for cleanrooms with restricted floor usage or requiring flexible layouts. The study also explores the impact of width of return air outlet oriented towards operators as particle emission sources, the results show that the larger-sized outlets facilitate the particle discharge and control the particle distribution inside the room.

High-frequency electric knife smoke particles: An experimental study on factors influencing emission characteristics

During surgery, the use of a high-frequency electric knife produces smoke, which can be harmful to the health of indoor medical staff and patients. The quantity and particle size distribution of smoke particles produced by different tissues may vary. Understanding the release characteristics of these smoke particles is necessary to clarify their impact on the surgical environment and to seek effective smoke control methods. A previous comparative analysis of human and pig tissues revealed that they share similar water and fat compositions in certain anatomical regions. In this study, we investigated the emission characteristics of smoke particles from various tissues of pigs (skeletal muscle, liver, kidney, skin, and subcutaneous fat) under different operating powers of an electric knife. We measured the indoor particle number concentration (particle concentration), and estimated the PM2.5 mass concentration (PM2.5 concentration), particle size distribution, and emission rate of the smoke particles. The study obtained the particle emission rates of different tissues under different electric knife operating powers, results of which showed that (1) during the operation of the electric knife, mainly small particles below 1 μm are produced. Among them, particles of 0.3 μm were the most abundant, with a particle concentration level of up to 109 particles/m3, accounting for 85.17–97.64% of the total particle number, and as the particle size increased, the particle concentration and percentage decreased significantly. (2) The water and fat compositions of different tissues influenced the indoor particle concentration and emission rate of the smoke emitted by the electric knife. Among different tissues, subcutaneous fat tissue had the lowest particle concentration and emission rate. (3) The electric knife operating power mainly affected particles below 1 μm, and except for kidney tissue, the indoor concentration and emission rate of these particle sizes were positively correlated with the power. The experimental results can provide data reference for the use of high-frequency electric knives in surgeries involving different human tissues in the operating room.

Analysis and research on inherent angle ventilation control of residential kitchen range hoods

The emission of oil fume particles during kitchen cooking processes constitutes a significant factor that impacts indoor air quality and human health. Range hoods, as indispensable ventilation devices in kitchens, play a crucial role in reducing indoor particle concentrations. This study employs a combined approach of orthogonal experiments and computational fluid dynamics simulations to investigate the exhaust characteristics of inherent-angle-measurement-based range hoods. It analyzes the diffusion patterns of cooking-generated particulate matter under various cooking scenarios, considering factors such as the opening and closing of windows, cooking source velocities, and different airflow rates of the range hood. Based on different airflow organization patterns, a supplementary ventilation system is designed. The rationality and effectiveness of the supplementary ventilation system are analyzed to establish an effective control scheme for reducing particulate matter in various kitchen environments. The simulated research results indicate that particles disperse along the inclined surface of the side-draft range hood, resulting in higher pollutant concentrations in the breathing zone compared to the cooking zone. Increasing the exhaust airflow rate of the range hood enhances particle capture efficiency by 9.8 %. The induced airflow generated by opening windows improves particle capture efficiency by 12.9 %. However, when the velocity of the window-induced airflow exceeds 1.5 m/s, it hampers the promotion of particle capture efficiency. In the case of windows being unconditionally open, implementing a ceiling-mounted supplementary air supply system effectively improves the kitchen's particle concentration, achieving a maximum particle capture efficiency of 97.66 %. When windows can be opened, setting a baffle on the range hood, the simulation results revealed that with a baffle angle of 120° and a length of 0.3 m, the particle concentration capture efficiency in the breathing zone increased by 34.59 %. This achieved the standard limit requirement of 50 µg/m3, thus meeting the indoor air quality requirements.

공기청정기와 기류 제어용 FAN의 운전조건에 따른 교실 내 공기질 변화에 대한 해석적 연구

This study investigated the influence of the operating conditions on an air purifier and extra FAN efficiency in reducing particulate matter in a classrooms. Computational fluid dynamics (CFD) simulation considering three locations of Air purifiers and operating conditions of four FANs was conducted to evaluate the optimal operating condition. In this study, the Clean Air Delivery Rate (CADR) of Air purifier was 2.4 m3/min (161.4 CMH) and 4.8 m3/min(322.8 CMH). Assuming the indoor particulate concentration is 150 μg/m3, the performance of reducing particle concentration varies by a maximum of 31.2% depending on the position of the air purifier and the operating condition of the FAN. When the CADR of the air purifier is low, particulate matter reduction performance can be improved by a FAN. When using the FAN, make sure that it does not interfere with the airflow of the air purifier.

Performance of a heat recovery ventilation system for controlling human exposure to airborne particles in a residential building

Heat recovery ventilation (HRV) system is emerging as a sustainable technology to reduce human exposure to air pollutants in residential buildings. However, there is a lack of information on the HRV system performance for controlling both indoor-generated and outdoor-generated particles in a residential building. To fill this knowledge gap, we conducted field monitoring of indoor airborne particles with two representative HRV system operating modes (ventilation and circulation modes) in a full-scale residential testbed. The results reveal that the filter efficiency, airflow rate, and filter bypass factor of the HRV system play important roles in indoor particle concentrations. The indoor/outdoor concentration ratio is reduced by 72%–92% when operating the HRV system. For both circulation and ventilation modes, the bypass factor is crucial for the particle removal performance of the HRV system. A 20% filter bypass factor leads to up to a 50% increase in indoor exposure to outdoor-originated and indoor-generated PM2.5 compared to the no-bypass scenario. Although circulation mode performed better than ventilation mode, both operating modes with a minimal bypass factor can effectively remove particles generated from indoor emission sources (e.g., incense stick burning and bacon pan frying). The study results suggest that HRV system can reduce human exposure to indoor-generated particles by 56%–90% and particle control performance hinges upon minimizing HRV filter bypass.

Predicting indoor particle concentration in mechanically ventilated classrooms using neural networks: Model development and generalization ability analysis

This study presents a comprehensive analysis of the model development (structure, parameter settings, and prediction accuracy) and generalization ability of neural networks in the classroom setting. A normalized database for model prediction and verification including indoor parameters from 27 high school classrooms over the course of four semesters was set up (a total of 14,112 sets of data for each variable). Three different models were compared: a back propagation artificial neural network (BP-ANN), a nonlinear autoregressive exogenous neural network (NARX), and a long-term and short-term memory neural network (LSTM). For the prediction of PM1 and PM2.5, which are impacted by outdoor PM concentrations, the best performance was achieved by the NARX model: the mean absolute percentage error (MAPE), root mean squared error (RMSE), and coefficient of determination (R2) were 41–55%, 0.45–1.27 μg/m3, and 0.81–0.87, respectively. The R2 of this model was 22% higher than that of the BP-ANN model and much higher than that of the LSTM model. For the prediction of indoor PM10, which are mostly emitted by indoor sources, relatively good performance was achieved by the LSTM model. The trained NARX model was used successfully to predict indoor time-series PM2.5 concentration and source strength in classrooms in five Chinese cities and five American cities. The calculated indoor source strength was 95.5–119.1 μg/h/P, within the range of the measured indoor source strength. The indoor PM2.5 concentrations calculated by a theoretical equation without the consideration of indoor source were 20.8–60.0% smaller than those calculated by the trained model.

LASSO and attention-TCN: a concurrent method for indoor particulate matter prediction.

Long time exposure to indoor air pollution environments can increase the risk of cardiovascular and respiratory system damage. Most previous studies focus on outdoor air quality, while few studies on indoor air quality. Current neural network-based methods for indoor air quality prediction ignore the optimization of input variables, process input features serially, and still suffer from loss of information during model training, which may lead to the problems of memory-intensive, time-consuming and low-precision. We present a novel concurrent indoor PM prediction model based on the fusion model of Least Absolute Shrinkage and Selection Operator (LASSO) and an Attention Temporal Convolutional Network (ATCN), together called LATCN. First, a LASSO regression algorithm is used to select features from PM1, PM2.5, PM10 and PM (>10) datasets and environmental factors to optimize the inputs for indoor PM prediction model. Then an Attention Mechanism (AM) is applied to reduce the redundant temporal information to extract key features in inputs. Finally, a TCN is used to forecast indoor particulate concentration in parallel with inputting the extracted features, and it reduces information loss by residual connections. The results show that the main environmental factors affecting indoor PM concentration are the indoor heat index, indoor wind chill, wet bulb temperature and relative humidity. Comparing with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) approaches, LATCN systematically reduced the prediction error rate (19.7% ~ 28.1% for the NAE, and 16.4% ~ 21.5% for the RMSE) and improved the model running speed (30.4% ~ 81.2%) over these classical sequence prediction models. Our study can inform the active prevention of indoor air pollution, and provides a theoretical basis for indoor environmental standards, while laying the foundations for developing novel air pollution prevention equipment in the future.

Feasibility of Multi-Zone Simulation for Estimating Contributions of Outdoor Particulate Pollution to Indoor Particulate Matter Concentration

As concerns about the health effects of particulate matter (PM) are growing, controlling indoor PM has become vital for ensuring occupants’ health. Active strategies, such as air purification and high-performance filtering, are widely implemented to control indoor PM. However, passive strategies, including air-tightness and compartmentalization, are promising alternatives, as demonstrated by recent studies. To enhance the implementation of passive strategies, an appropriate evaluation method for passive designs must be established. The objective of this study was to investigate whether a multi-zone-based method is suitable for the evaluation of passive strategies. Multi-zone simulations were performed for four seasons, and indoor/outdoor concentration (I/O) ratios were obtained for the exterior, interior, and corridor on every floor of the reference building. The I/O ratios at different locations indicated that the outdoor particle transport in the building was accurately estimated according to the airflow rate and path. Moreover, in addition to the effects of changes in the outdoor temperature on PM transport through the building envelope, the particle size is a significant factor affecting indoor PM concentrations. The results of this study indicated that the multi-zone method can effectively estimate the number of outdoor particles that penetrate the building envelope in different seasons and the indoor particle concentration at different indoor locations.

Numerical investigation on particle removal and energy consumption of supplied and recirculated ventilation for industrial workshop

In the weld back-cleaning process, many high-concentration pollutants are produced, which can lead to health problems after prolonged exposure. In this study, a novel recirculating stratified ventilation system is proposed that combines supply and recirculating ventilation. It reduces indoor particulate concentration and exhausts air volume based on the air gouging process in a casting workshop. The influences of the supplied and recirculated air velocities on the particle removal efficiency and energy consumption were investigated and compared with those of a traditional exhaust system. The computational fluid dynamics-discrete phase model coupling method was adopted. First, the feasibility of the model was verified using previously published experimental data. The concentration of the unsteady particles was then simulated with different supplied and recirculated air velocities in the ventilation system. The particles were dispersed owing to the influence of the heat-source temperature. With an increasing supplied air velocity and constant recirculated air velocity, the average particle concentration was decreased. The results show that the particle removal efficiency can be improved by approximately 100%, and 90% of the energy can be saved to achieve the same removal efficiency as a traditional ceiling exhaust system.

Effects of Outdoor Air Pollutants on Indoor Environment Due to Natural Ventilation

This study measured ventilation volumes and particle concentrations in indoor environments with open windows and doors. In addition, the effect of the airflow mode of the air conditioner on the ventilation volume and indoor particle concentration variations was also measured. The ventilation fan could only provide approximately 43% of the ventilation volume during the design phase. The amount of ventilation differed depending on the opening area in windows and doors. The ventilation volume was increased by opening multiple windows or doors, even when the area of the opening was the same. No significant change in the ventilation rate was observed, although the air conditioner was expected to promote the ventilation rate in the room when set on blow mode. It was confirmed that both 0.3 and 1 μm particles could enter through the gaps around the windows and doors. Although most of the 5 μm particles were from the outdoor air, when the air conditioner was operated in airflow mode, the removal of 5 μm particles was performed by the air conditioner filter. The use of medium-performance or HEPA filters is expected to remove smaller particulates.

A simple model for predicting dispersion characteristics of high-temperature airflow and particle distribution during smelting process in a thermally stratified foundry shop

The flow-field characteristics of high-temperature airflow and particle distributions generated from the running furnace during smelting process in foundry shop were studied by on-site measurements and theoretical analysis in this work. A theoretical model was proposed to describe the dispersion characteristics of the high-temperature buoyant jet flow and plume induced by the furnace with two typical opening modes. The coupling effects of the heat source features and environmental factors were emphatically discussed by comparing the trajectory, cross-section diameter, velocity and temperature decay, and volumetric flow rate during the dispersion process. Results show that in the large foundry shop with natural ventilation, there is a vertical temperature gradient of 0.1–0.4 °C/m, which can make the pollutant locked in the workshop and weaken the entrainment of the thermal flow. The crossflow is a non-negligible factor, which causes the dispersion trajectory of the pollutant flatter and induces a long travelling distance along the horizontal direction. The indoor particle concentration when the furnace opens concentration seriously exceeds the limits in the existing indoor air quality standard of China. This work is expected to give suggestions on ventilation designs and arrangements of the exhaust port or device in industrial environments.

Impact of ventilation methods on indoor particle concentrations in a daycare center.

The objective of this study was to quantify the influence of ventilation methods on children's exposure to indoor particles in a daycare center located in an urban area. The ventilation methods applied to the center were monitored for 1 year. It appears that indoor PM10 and PM2.5 concentrations of the center were basically determined by outdoor conditions. The fluctuations in outdoor particle concentration also affected the ventilation behavior during class. The windows and doors of the classroom were frequently closed during both class hours and nights when the outdoor particle concentrations were at high levels. Statistically significant differences in the I/O ratios were found among the ventilation methods. The PM10 I/O ratio with the closed windows was significantly higher (p < 0.01) than that with the open windows, and when the mechanical fans were operated, the I/O ratio dramatically decreased (p < 0.01). The I/O ratio of PM2.5 showed a similar trend to that of PM10 except for the mechanical fan operation. The filters rated lower than MERV 11 appear to be insufficient to remove submicron particles from the mechanically supplied outdoor air when the PM2.5 concentrations are high, such as during the heating period.

Experimental and numerical analysis of indoor air quality affected by outdoor air particulate levels (PM1.0, PM2.5 and PM10), room infiltration rate, and occupants' behaviour

This study conducted an experimental analysis of how indoor air quality (IAQ) is influenced by the outdoor air pollutants levels, infiltration rate, and occupants' behaviours. The impacts of these factors on IAQ were analyzed using on-site measurements and numerical simulations. The results contribute to a better understanding of how to control the Indoor Particulate Level (IPL) for the specific conditions of the studied building. Results showed that occupant behaviour was the primary factor in determining the IPL, significantly changing the number of outdoor particles introduced to the building. Moreover, it was found that the IPL was exponentially correlated to the Outdoor Particulate Level (OPL). Based on numerical simulations, this study concluded that smaller particles do not always have more chance than larger particles of accessing the indoor environment through the building envelope. Meanwhile, a steady-state indoor particle concentration numerical model was established and verified using the 4-fold cross-validation method. Finally, simulation results identified that the room infiltration rate had a positive linear impact on IAQ if the OPL was under 30 μg/m3. This is because the increased air exchange rate can help to dilute indoor air pollutants when the outdoor air is relatively clean.

Experiment and numerical investigation of inhalable particles and indoor environment with ventilation system

After the outbreak of COVID-19, the indoor environment has become particularly important in closed spaces, being a common concern in environmental science and public health, and of great significance for the building environment. To improve the indoor air quality and control the spread of viruses, the analysis of inhalable particles in indoor environments is critical. In this research, we study standards focused on inhalable particles and indoor environmental quality, as well as analyzing the movement and diffusion of indoor particles. Based on our analysis, we conduct an experimental study to determine the distribution of indoor inhalable particles of different sizes before and after diffusion under the conditions of underfloor air distribution. Furthermore, the mathematical modeling method is adopted to simulate the indoor flow field, particle trajectories, and pollutant dispersion process. The k-ε two-equation model is applied as the turbulence model in the numerical simulation, while the Lagrangian discrete phase model is adopted to trace the motion of particles and analyze the distribution characteristics of indoor particles. The results demonstrate that fine particles (i.e., those with size less than 0.5 μm) have a significant impact on the indoor particle concentration, while coarse particles (i.e., with size above 2.5 μm) have a greater influence on the total mass concentration of indoor particles. Small-sized particles can easily follow the airflow and diffuse to upper parts of the room. Overall, the effects of indoor particles on indoor air quality, including the potential threat of aerosol transmission of respiratory infectious diseases, are non-negligible. Application of the presented research can contribute to improving the health-related aspects of the building environment.

Predicting spatio-temporal distribution of indoor multi-phase phthalates under the influence of particulate matter

Due to the complexity of phthalates spatial and temporal distribution in indoor environment, mechanistic that govern indoor phthalates concentrations and fates need to be explored. A dynamic partition model of phthalates considering the dynamic behavior and segmented emission of size-resolved particulate matter is developed to investigate the distribution of phthalates in the gas phase, airborne particles, and settled dust and on the fixed surface. The impacts of outdoor and indoor particle source on the multi-phase concentrations of phthalates are analyzed. Outdoor haze can suddenly increase indoor particle concentration and particle-phase concentration of Di-2-ethylhexyl phthalate (DEHP). However, the haze decreases gas-phase and dust-phase concentration of DEHP. The particle emission rate Sp for cooking affects the maximum concentration of indoor particle, while cooking frequency has no effect on it. When cooking frequency increases, gas-phase concentration and particle-phase peak concentration of DEHP decreases significantly, which means the particulate matter may be a good carrier for DEHP removal. Increasing emission rate Sp of particles can significantly reduce the minimum gas-phase concentration of DEHP, nevertheless it can increase particle-phase maximum concentration of DEHP. Overall, the proposed model considering interactions of particle and phthalate can improve further understanding of phthalates’ fate and transport in residential environment, which is beneficial to the implementation of control strategy.

Levels of indoor particulate matter and association with asthma in children in Benin City, Nigeria.

The relationship between indoor particulate matter and asthma in children was assessed in this study. Forty-five (45) locations were randomly selected across the five local government areas in Benin City, Edo State, for air quality assessment. Indoor and outdoor particulates (PM1.0, PM2.5, and PM10) were monitored monthly using a handheld BLATN particulate sampler (Br-Smart-126S series). Reported clinical cases of asthma in children from 2008 to 2017 were collected from two major hospitals in the metropolis. The data obtained were analysed with SPSS for Windows version 21.0. The average concentrations of indoor and ambient PM ranged between 10.7-26.2 and 19.0-49.4µg/m3 (PM1.0), 27.4-59.6 and 45.6-93.0µg/m3 (PM2.5), and 33.5-67.9 and 60.9-106.1µg/m3 (PM10) in the wet and dry seasons. PM2.5 and PM10 concentrations were observed above the WHO standards. Indoor particulate concentration was significantly (p = 0.001-0.012) higher in the dry season across the locations. Outdoor PM correlated positively (R = 0.568-0.855, p < 0.05; R2 = 0.322-0.724, p < 0.001) with their corresponding indoor PM concentration. The hazard ratio (HR) values of PM2.5 and PM10 exceeded 1 in all the sampling locations during the dry season, while the mean total hazard ratio (THR) of both PM metrics was considerably higher during the dry season than in the wet season. Indoor PM concentrations showed a significant positive correlation with reported cases of asthma (R = 0.498-0.542, p < 0.001) and accounted for 40.6% of the asthma cases during the dry season. The study showed that children in the selected households are at risk of increased asthma exacerbation due to exposure to particulate matter pollution.