Concentrations Of Indoor Air Pollutants Research Articles

Effects of indoor air pollution from household solid fuel use on the risk of gastrointestinal and liver diseases in middle aged and elderly adults

Solid fuels are widely used in China and increase the concentrations of indoor air pollutants. Nevertheless, there is limited longitudinal evidence linking solid fuel use and Gastrointestinal (GI) and liver diseases. This study aimed to prospectively investigate the association between household solid fuel use and the risk of GI and liver diseases in middle aged and elderly adults. This work was based on the China Health and Retirement Longitudinal Study (CHARLS). Longitudinal data incorporate with cross-sectional data were analyzed. Compared with individuals using clean fuel for cooking, solid fuel users were observed to have higher risk of GI diseases (OR in 2011, 2013, 2015, 2018 wave separately: 1.37, 95 % CI: 1.24–1.50, P < 0.001; 1.24, 95 % CI: 1.11–1.39, P < 0.001; 1.18, 95 % CI: 1.06–1.33, P < 0.001; 1.23, 95 % CI: 1.04–1.45, P < 0.05). The associations between solid fuel use and liver diseases were not significant in most of the groups. Participants transforming from solid to clean cooking fuels had lower risk of GI and liver diseases than persistent solid fuel users. Moreover, biomass cooking fuel users were at a significant higher risk of both liver and GI diseases compared with clean fuel users. Overall, household solid fuel use, especially for cooking, was related to higher risk of GI and liver diseases, while switching from solid to clean fuels could reduce this risk. Using biomass for cooking was identified to be more associated with the increasing risk of GI and liver diseases than cooking with coal.

Indoor Microclimatic Conditions and Air Pollutant Concentrations in the Archaeological Museum of Abdera, Greece

Indoor microclimate conditions and air pollutant concentrations (O3, TVOC, CO, CO2, and particulate matter mass concentrations in six size bins) were measured in the Greek Archaeological Museum of Abdera, which houses priceless works of art from the birthplace of the ancient philosopher Democritus. The monitoring campaign took place during the spring and summer months, when there were the greatest number of visitors. In the exhibition rooms, daily variations in relative humidity ranged from 4% to 10%, and daily variations in air temperature ranged from 0.9 °C to 2.6 °C. These uncontrolled changes may endanger the housed antiquities. The microclimate in the storage rooms varied substantially less than in the exhibition halls due to dehumidifiers and the lack of visitors. Concerning air pollution, indoor O3 concentrations were higher than the recommended limit values for the conservation of artwork. Even more worrisome are particulate matter mass concentrations above the air quality guidelines. Despite the fact that the building is well insulated and that only artificial lighting is used in the exhibition halls, it is difficult to achieve adequate conditions for the protection of the works of art.

Energy-efficient operation of portable air cleaners based on real-time prediction of non-uniform concentrations of indoor air pollutants in open offices

In an open office environment with high occupant density and random occupancy patterns, excessive energy consumption is often observed because mechanical ventilation (MV) is usually designed and operated assuming a full-occupancy-based ventilation rate (VR). Considering the duo challenges of post-pandemic and climate change, this study proposes a real-time monitoring and optimization approach for operating portable air cleaners (PACs) to assist and reduce the energy consumption of the MV while maintaining the minimal VR and improving indoor air quality (IAQ). The approach was as follows. First, by assuming four VRs and 36 different emission sources, numerical simulations were conducted and validated based on an actual open office on non-uniform concentrations of a surrogate for indoor air pollutants (IAPs) throughout the breathing zone. Second, the pre- and post-purified IAP distributions were obtained using a limited number of sensors and trained by two artificial neural networks. Third, the real-time optimization of PACs’ on/off operation and placements was accomplished by the particle swarm optimization algorithm to balance energy output and improve IAQ simultaneously. Results showed that by deploying four sensors, the predictions of post-purifying concentrations were in acceptable accuracy (i.e., CV-RMSE <2.0%) within 30–40s. Using at most three PACs resulted in a significant decline in local IAP concentration levels. Meanwhile, an average reduction of total energy consumption of MV and PACs was 34.6% compared to using MV to reach the same levels. Overall, this study supports the use of PACs to assist MV in achieving energy efficiency and good IAQ.

Mitigating indoor air pollution in UAE's high-rise apartment buildings: a study on eco-friendly materials and adsorbents

PurposeThis study aims to evaluate the efficiency of various techniques for enhancing indoor air quality (IAQ) in construction. It analyzed the alterations in the concentration of indoor air pollutants over time for each product employed in controlling pollution sources and removing it, which included eco-friendly substances and adsorbents. The study will provide more precise and dependable data on the effectiveness of these control methods, ultimately supporting the creation of more efficient and sustainable approaches for managing indoor air pollution in buildings.Design/methodology/approachThe research investigates the impact of eco-friendly materials and adsorbents on improving indoor air quality (IAQ) in Dubai's tall apartment buildings. Field experiments were conducted in six units of The Gate Tower, comparing the IAQ of three units built with “excellent” grade eco-friendly materials with three built with “good” grade materials. Another experiment evaluated two adsorbent products (H and Z) in the Majestic Tower over six months. Results indicate that “excellent” grade materials significantly reduced toluene emissions. Adsorbent product Z showed promising results in pollutant reduction, but there is concern about the long-term behavior of adsorbed chemicals. The study emphasizes further research on household pollutant management.FindingsThe research studied the effects of eco-friendly materials and adsorbents on indoor air quality in Dubai's new apartments. It found that apartments using “excellent” eco-friendly materials had significantly better air quality, particularly reduced toluene concentrations, compared to those using “good” materials. However, high formaldehyde (HCHO) emissions were observed from wood products. While certain construction materials led to increased ethylbenzene and xylene levels, adsorbent product Z showed promise in reducing pollutants. Yet, there is a potential concern about the long-term rerelease of these trapped chemicals. The study emphasizes the need for ongoing research in indoor pollutant management.Research limitations/implicationsThe research, while extensive, faced limitations in assessing the long-term behavior of adsorbed chemicals, particularly the potential for rereleasing trapped pollutants over time. Despite the study spanning a considerable period, indoor air pollutant concentrations in target households did not stabilize, making it challenging to determine definitive improvement effects and reduction rates among products. Comparisons were primarily relative between target units, and the rapid rise in pollutants during furniture introduction warrants further examination. Consequently, while the research provides essential insights, it underscores the need for more prolonged and comprehensive evaluations to fully understand the materials' and adsorbents' impacts on indoor air quality.Practical implicationsThe research underscores the importance of choosing eco-friendly materials in new apartment constructions for better IAQ. Specifically, using “excellent” graded materials can significantly reduce harmful pollutants like toluene. However, the study also highlights that certain construction activities, such as introducing furniture, can rapidly elevate pollutant levels. Moreover, while adsorbents like product Z showed promise in reducing pollutants, there is potential for adsorbed chemicals to be rereleased over time. For practical implementation, prioritizing higher-grade eco-friendly materials and further investigation into furniture emissions and long-term behavior of adsorbents can lead to healthier indoor environments in newly built apartments.Originality/valueThe research offers a unique empirical assessment of eco-friendly materials' impact on indoor air quality within Dubai's rapidly constructed apartment buildings. Through field experiments, it directly compares different material grades, providing concrete data on pollutant levels in newly built environments. Additionally, it explores the efficacy of specific adsorbents, which is of high value to the construction and public health sectors. The findings shed light on how construction choices can influence indoor air pollution, offering valuable insights to builders, policymakers and residents aiming to promote public health and safety in urban living spaces.

Indoor Air Sources of Outdoor Air Pollution: Health Consequences, Policy, and Recommendations: An Official American Thoracic Society Workshop Report.

Indoor sources of air pollution worsen indoor and outdoor air quality. Thus, identifying and reducing indoor pollutant sources would decrease both indoor and outdoor air pollution, benefit public health, and help address the climate crisis. As outdoor sources come under regulatory control, unregulated indoor sources become a rising percentage of the problem. This American Thoracic Society workshop was convened in 2022 to evaluate this increasing proportion of indoor contributions to outdoor air quality. The workshop was conducted by physicians and scientists, including atmospheric and aerosol scientists, environmental engineers, toxicologists, epidemiologists, regulatory policy experts, and pediatric and adult pulmonologists. Presentations and discussion sessions were centered on 1) the generation and migration of pollutants from indoors to outdoors, 2) the sources and circumstances representing the greatest threat, and 3) effective remedies to reduce the health burden of indoor sources of air pollution. The scope of the workshop was residential and commercial sources of indoor air pollution in the United States. Topics included wood burning, natural gas, cooking, evaporative volatile organic compounds, source apportionment, and regulatory policy. The workshop concluded that indoor sources of air pollution are significant contributors to outdoor air quality and that source control and filtration are the most effective measures to reduce indoor contributions to outdoor air. Interventions should prioritize environmental justice: Households of lower socioeconomic status have higher concentrations of indoor air pollutants from both indoor and outdoor sources. We identify research priorities, potential health benefits, and mitigation actions to consider (e.g., switching from natural gas to electric stoves and transitioning to scent-free consumer products). The workshop committee emphasizes the benefits of combustion-free homes and businesses and recommends economic, legislative, and education strategies aimed at achieving this goal.

Characteristics of air exposure in welding workshop workers

Welding activities contribute to Indoor Air Pollution (IAP), and without proper control measures, they can pose health risks to workers. The goal of this research is to analyze indoor air quality, including CO, CO2, humidity, temperature, Total Suspended Particulate (TSP), and heavy metal composition, during 8 hours of welding activities. This study employed an experimental method using personal dust monitoring equipment worn by workers during 8 hour welding shifts. Environmental parameters such as CO2, CO, temperature, and humidity were measured using Si-AQ Pro. The results indicated that CO2, CO, temperature, and humidity concentrations in location 1 were higher than in location 2 but remained below the permissible exposure limits based on occupational health and safety regulations (Minister of Manpower and Transmigration Regulation No. 13/Year/x/2011) for carbon monoxide. The dominant heavy metal exposures during welding were Fe and Zn, with other heavy metals including Al, Ca, Ti, Cr, Mn, Cu, Zn, and Pb. These nine heavy metals remained below the ACGIH threshold limits. In conclusion, preventive measures such as improved ventilation can effectively reduce indoor air pollutant concentrations.

INCHEM-Py v1.2: a community box model for indoor air chemistry

Abstract. The Indoor CHEMical model in Python, INCHEM-Py, is an open-source and accessible box model for the simulation of the indoor atmosphere and is a refactor (rewrite of source code) and significant development of the INdoor Detailed Chemical Model (INDCM). INCHEM-Py creates and solves a system of coupled ordinary differential equations that include gas-phase chemistry, surface deposition, indoor–outdoor air change, indoor photolysis processes and gas-to-particle partitioning for three common terpenes. It is optimised for ease of installation and simple modification for inexperienced users, while also providing unfettered access to customise the physical and chemical processes for more advanced users. A detailed user manual is included with the model and updated with each version release. In this paper, INCHEM-Py v1.2 is introduced, and the modelled processes are described in detail, with benchmarking between simulated data and published experimental results presented, alongside discussion of the parameters and assumptions used. It is shown that INCHEM-Py achieves excellent agreement with measurements from an experimental campaign which investigate the effects of different surfaces on the concentrations of different indoor air pollutants. In addition, INCHEM-Py shows closer agreement to experimental data than INDCM. This is due to the increased functionality of INCHEM-Py to model additional processes, such as deposition-induced surface emissions. A comparative analysis with a similar zero-dimensional model, AtChem2, verifies the solution of the gas-phase chemistry. Published community use cases of INCHEM-Py are also presented to show the variety of applications for which this model is valuable to further our understanding of indoor air chemistry.

Understanding the patterns and health impact of indoor air pollutant exposures in Bradford, UK: a study protocol

IntroductionRelative to outdoor air pollution, there is little evidence examining the composition and concentrations of indoor air pollution and its associated health impacts. The INGENIOUS project aims to provide the...

Observationally constrained mass balance box model analysis of aerosol mitigation potential using fan powered filters

Indoor air pollution contributes significantly as a world-wide environmental issue, impacting health and livelihood. To quantify benefits of filtration on indoor air quality, it is essential to understand the relationships between the various factors impacting the concentrations of indoor air pollutants. This work uses a mass-conserving 2-box model, high-frequency observations of aerosol number concentration, and a home-made, low-cost, 3-layer non-woven fabric filter, powered by a standard ventilation fan to quantify the effectiveness aerosol reduction in multiple indoor environments. The data shows that aerosol loading is effectively reduced under both steady-state and extreme event conditions, although there are significant and important differences between simultaneous observations both indoor and outside. To obtain a proper accounting, the following must be considered: the usage or not of the fan filter, whether windows are opened or closed, the state of outdoor air is pollution, and the strength and duration of indoor emissions. The experiments are applied in residential indoor environments in four cities in eastern (Xuzhou), central (Zhoukou), and southern (Zhuhai and Shunde) China. Photographic evidence of the altered fan filter state under both conditions show that while usually dark/black aerosols dominate, there are conditions when yellow aerosols also dominate. The observations are based on multiple, independent, continuous low-cost sensors which have been calibrated against a GRIMM-180 over the number concentration range from 0.3 to 1.0 microns, and yield a removal rate due to the fan-filter of 46%, 80%, 81%, and 36% respectively across the four cities. A corresponding rate to return from an extreme event to steady-state, is computed outdoors and indoors respectively from: 14.−44. minutes, 6.6–21. minutes, 16.−33. minutes, and 24.−58. minutes. The most important factors contributing to the removal efficiency and decay gradient are observed as keeping windows closed and reducing leakiness, the apartment/classroom size, and the outdoor air pollution loading.

Inequalities in exposure to indoor environmental hazards across England and Wales – can more energy efficient homes help?

Housing is an important modifier of outdoor environmental hazards due to features such as the amount of passive and active ventilation a dwelling receives, the proportion of the façade that is glazed and the building’s thermal insulation levels. Using Artificial Neural Networks based on an indoor building physics model, we simulate indoor temperature and air pollution concentrations in ~15 million English and Welsh dwellings and assess how exposure to indoor hazards varies for different population groups. The model is derived using simulations from the dynamic thermal modelling tool EnergyPlus, taking a spatially-distributed housing stock as input. Results are linked to the latest 2021 Census data on area-measures of population demographics to assess if vulnerable subgroups bear a disproportionate risk from indoor environmental hazards. We find neighbourhoods in England and Wales with a higher proportion of infants, ethnic minorities and income-deprived populations experience higher two-day maximum indoor temperatures in summertime; whilst more ethnically diverse areas have elevated annual average indoor concentrations of outdoor-sourced PM2.5. Areas with a higher proportion of those aged 65+ had a lower standardised indoor temperature (SIT) in winter, increasing the risk of fuel poverty. We then implement a stock-wide, home energy retrofit, in line with national decarbonisation targets. Results suggest energy-efficient building interventions may exacerbate heat inequalities without the provision of external shading, but improve population exposure to winter indoor temperatures and indoor concentrations of ambient-sourced PM2.5.

Private benefits from ambient air pollution reduction policies: Evidence from the household heating stove replacement program in Chile

We estimate the key private benefits from a program to improve ambient air quality during winter in central Chile by replacing inefficient wood-fired home heating stoves with more efficient pellet stoves. We are interested in the private benefits to households, because they represent additional value of the program and likely drive adoption. Combining electronic stove surface temperature and air pollution monitoring with household surveys, we estimate the effects of adoption on household fuel expenditures, indoor temperatures and indoor air pollution concentrations (PM2.5) when the stoves are in use. We also explore heterogeneous effects of the program by income group and energy poverty status. Our results suggest that, after controlling for observable characteristics of individuals and dwellings, users of pellet stoves on average enjoy 14 % lower indoor PM2.5 concentrations during hours in which stoves are in use compared with those who use traditional stoves during the same periods of time. Lower-income and energy-poor households receive much greater than average improvements in indoor air pollution than those with higher-incomes, driving the overall estimate and indicating that the program is progressive in this dimension. The improved heating stove has significantly higher operating costs, however, and we find that these costs are most salient for low-income and energy-poor households.

Impact of roof shape on indoor gaseous pollutant level for natural ventilation buildings in a street canyon: Numerical simulation

Introduction: Coupling the indoor and outdoor airflow of roadside buildings in a street canyon, the impact of flat and triangular roofs on indoor air pollutant concentration and ventilation rates of naturally ventilated buildings is studied using numerical simulation methods.&#x0D; Materials and methods: The flow and pollutant diffusion control equations are solved by using ANSYS Fluent. In simulation, RNG k-ε turbulence model is adopted. The numerical model is validated using the three-dimensional street canyon test data from the wind tunnel experiment at University of Karlsruhe.&#x0D; Results: The flow and pollutant concentration distributions under different roof shapes are obtained. The ventilation rates with different air flow resistances and pollution level indoors are provided.&#x0D; Conclusion: Ventilation direction through windows of roadside buildings determines the level of indoor air polluted by vehicle emissions in street canyon. When the building main height equals to the width of the street, flat roofs make the indoor concentration basically consistent with that near the external walls of the canyon. The higher the triangular roofs, the higher the ventilation rate and the lower the indoor concentration. The ventilation rate is influenced not only by roofs, but also by the floor location and indoor ventilation resistance.v

Cleaner Cooking with Charcoal in Kibera Informal Settlement in Nairobi, Kenya, and Its Implications for Livelihoods and the Environment

Woodfuel that is unsustainably sourced and inefficiently used results in negative environmental and health impacts. This study assessed charcoal use and resultant concentrations of indoor air pollutants (IAP) in an urban informal settlement while cooking with a Jikokoa stove (an improved branded charcoal stove) and medium and small-sized artisanal Kenya Ceramic Jikos (KCJs). Fuel stacking was prevalent with charcoal and kerosene being used by 25% of the studied households. Cooking with a Jikokoa stove reduced charcoal consumption by 6.4% and 26% compared to small and medium-sized KCJs, respectively. The small-sized KCJ reduced charcoal consumption by 21% compared to the medium-sized KCJ. The Jikokoa stove reduced concentrations of carbon monoxide (CO) by 10% and 50% and fine particulate matter (PM2.5) by 6% and 77% compared to small-sized and medium-sized KCJs, respectively. The Jikokoa stove reduced carbon dioxide (CO2) concentrations by 15.6% compared to the medium-sized KCJ. The small-sized KCJ reduced CO and PM2.5 concentrations by 45% and 75%, respectively, compared to the medium-sized KCJ. In summary, small-sized KCJs are more effective than medium-sized ones, and Jikokoa stoves more effective than small-sized KCJs, making it the stove of choice. The more efficient charcoal stoves are, the more charcoal consumption and IAP can be reduced, mitigating environmental degradation, climate change and health problems associated with smoke in the kitchen. There is need for participatory research to scale improved stoves and upgrade local practices as they are cheaper and already embedded in the cooking culture.

Construction and evaluation of hourly average indoor PM2.5 concentration prediction models based on multiple types of places.

People usually spend most of their time indoors, so indoor fine particulate matter (PM2.5) concentrations are crucial for refining individual PM2.5 exposure evaluation. The development of indoor PM2.5 concentration prediction models is essential for the health risk assessment of PM2.5 in epidemiological studies involving large populations. In this study, based on the monitoring data of multiple types of places, the classical multiple linear regression (MLR) method and random forest regression (RFR) algorithm of machine learning were used to develop hourly average indoor PM2.5 concentration prediction models. Indoor PM2.5 concentration data, which included 11,712 records from five types of places, were obtained by on-site monitoring. Moreover, the potential predictor variable data were derived from outdoor monitoring stations and meteorological databases. A ten-fold cross-validation was conducted to examine the performance of all proposed models. The final predictor variables incorporated in the MLR model were outdoor PM2.5 concentration, type of place, season, wind direction, surface wind speed, hour, precipitation, air pressure, and relative humidity. The ten-fold cross-validation results indicated that both models constructed had good predictive performance, with the determination coefficients (R2) of RFR and MLR were 72.20 and 60.35%, respectively. Generally, the RFR model had better predictive performance than the MLR model (RFR model developed using the same predictor variables as the MLR model, R2 = 71.86%). In terms of predictors, the importance results of predictor variables for both types of models suggested that outdoor PM2.5 concentration, type of place, season, hour, wind direction, and surface wind speed were the most important predictor variables. In this research, hourly average indoor PM2.5 concentration prediction models based on multiple types of places were developed for the first time. Both the MLR and RFR models based on easily accessible indicators displayed promising predictive performance, in which the machine learning domain RFR model outperformed the classical MLR model, and this result suggests the potential application of RFR algorithms for indoor air pollutant concentration prediction.

LSTM Deep Learning Models for Virtual Sensing of Indoor Air Pollutants: A Feasible Alternative to Physical Sensors

Monitoring individual exposure to indoor air pollutants is crucial for human health and well-being. Due to the high spatiotemporal variations of indoor air pollutants, ubiquitous sensing is essential. However, the cost and maintenance associated with physical sensors make this currently infeasible. Consequently, this study investigates the feasibility of virtually sensing indoor air pollutants, such as particulate matter, volatile organic compounds (VOCs), and CO2, using a long short-term memory (LSTM) deep learning model. Several years of accumulated measurement data were employed to train the model, which predicts indoor air pollutant concentrations based on Building Management System (BMS) data (e.g., temperature, humidity, illumination, noise, motion, and window state) as well as meteorological and outdoor pollution data. A cross-validation scheme and hyperparameter optimization were utilized to determine the best model parameters and evaluate its performance using common evaluation metrics (R2, mean absolute error (MAE), root mean square error (RMSE)). The results demonstrate that the LSTM model can effectively replace physical indoor air pollutant sensors in the examined room, with evaluation metrics indicating a strong correlation in the testing set (MAE; CO2: 15.4 ppm, PM2.5: 0.3 μg/m3, VOC: 20.1 IAQI; R2; CO2: 0.47, PM2.5: 0.88, VOC:0.87). Additionally, the transferability of the model to other rooms was tested, with good results for CO2 and mixed results for VOC and particulate matter (MAE; CO2: 21.9 ppm, PM2.5: 0.3 μg/m3, VOC: 52.7 IAQI; R2; CO2: 0.45, PM2.5: 0.09, VOC:0.13). Despite these mixed results, they hint at the potential for a more broadly applicable approach to virtual sensing of indoor air pollutants, given the incorporation of more diverse datasets, thereby offering the potential for real-time occupant exposure monitoring and enhanced building operations.

Evolution of coalescent agent-free ultra-low VOC paint with formaldehyde capturing properties

The majority of people spend a significant portion of their waking lives indoors, they are continually exposed to a higher concentration of indoor air pollutants. As new technologies emerge and more people become aware of the issue, it has become crucial to discover new methods for cleaning up polluted indoor air and minimizing people's exposure to it.This research aims to develop a waterborne, low-VOC, formaldehyde-capturing formulation for interior paint. In paint formulation, biocides, coalescing agents, ammonia, binders, and liquid phase additives are all possible sources of volatile organic compounds. In this study, formulations of coalescing agent-free and formaldehyde-free waterborne coatings with high performance characteristics and ultra-low VOC content were created by chemically adsorbing formaldehyde using an active ingredient. The colorimetric method, which is developed based on the color concentration change, and the cabin method test methods, which monitor the change of formaldehyde concentration in the interior environment, were developed within the scope of the study in order to test the effect of the product. The final formulation complies with the A + French VOC labeling and the Indoor Air Comfort Gold criteria for VOC emissions, and tests demonstrated an 87% decrease in ambient formaldehyde concentrations within 24 h of application (ISO 16000–9:2006, EN 16516:2017).

Accumulation and Diffusion of PM from Outdoor to Indoor by Clothing under Haze Conditions: A Case Study of Zhengzhou, China

Clothing can absorb fine particulate pollutants from the atmosphere outdoors and then release them after entering the room in a form similar to three-handed smoke. In this study, the experimental site in Zhengzhou, a typical city with heavy pollution in central China, was used to investigate the adsorption and diffusion patterns of three different fabrics of polyester, polyester-cotton, and cotton clothing for fine particle pollutants, to guide people’s behavior patterns and indoor air distribution, and to reduce indoor pollution exposure. The results showed that when garments of three different fabrics were exposed to moderate and heavy PM2.5 pollution for 1 h, 2 h, and 3 h, respectively, and then transferred to the diffusion chamber, polyester always released the highest PM2.5 concentration to indoor air during the same release cycle, followed by cotton and polyester-cotton. In addition, the concentration of indoor air pollutants will be periodically affected by the diffusion of fine particulate adsorbed by clothing fabrics. With the increase in outdoor pollution and exposure duration, the indoor PM2.5 concentration takes longer to stabilize at certain levels after the clothing is transferred to the indoor side. Finally, the comparison of natural ventilation experiments proved that it is not feasible to rely solely on natural ventilation to improve the influence of clothing pollution sources on indoor air quality.

Development of ASTM International D8405—Standard Test Method for Evaluating PM2.5 Sensors or Sensor Systems Used in Indoor Applications

Sensors and sensor systems for monitoring fine particles with aerodynamic diameters smaller than 2.5 µm can provide real-time feedback on indoor air quality and thus can help guide actions to manage indoor air pollutant concentrations. Standardized verification of the performance and accuracy of sensors and sensor systems is crucial for predicting the efficacy of such monitoring. A new ASTM International standard test method (ASTM D8405) was created for this need and is the most exacting laboratory protocol published to date for evaluating indoor air quality sensors and sensor systems measuring particles smaller than 2.5 µm in diameter. ASTM D8405 subjects sensors and sensor systems to five test phases: (1) an initial particle concentration ramp; (2) exposure to various temperature and humidity conditions; (3) exposure to interfering particles; (4) temperature cycling; and (5) a final particle concentration ramp to assess drift. This paper discusses the development of the standard test method, key aspects of the testing process, example evaluation results, and a comparison of this standard test method against peer evaluation protocols.

The Changes in Indoor Air Pollutant Concentration in Nursery in Dubai, United Arab Emirates

Recent statistics indicate that as indoor pollutants' effects on the human body become a severe issue in Dubai, the need for systematic IAQ (indoor air quality) management is increasing. This paper aims to identify the IAQ pollution status according to the characteristics of nursery rooms and playrooms and suggest ventilation methods. As a methodology, indoor temperature and humidity and indoor air pollutants (Carbon Dioxide (CO2), PM10, Formaldehyde (CH2O), TVOC (Total volatile organic compounds) were measured in two different scales nurseries. The result showed that CO2 was measured below the maintenance standards of KHDA regulation at all measurement points, nursery A at 870 ppm and nursery B at 860 ppm. PM10 has exceeded the maintenance standard of 100 μg/m3 in the playroom and nursery room of nursery A due to less cleaning times and ventilation. TVOC was 1,504 μg/m3 and 723 μg/m3 in both facilities, exceeding the recommended standard of 400 μg/m3 in the nursery room. CH2O concentration was below the maintenance standard at all measurement sites. This study will serve as primary data for further investigation of indoor air pollution in nurseries according to the size and type.

Optimisation of Building Green Performances Using Vertical Greening Systems: A Case Study in Changzhou, China

The benefits of greening systems on buildings have been frequently examined using experimental methods. However, few studies have adopted dynamic monitoring of real operational buildings to quantify the effects of greening systems on multiple building green performance indexes, such as thermal comfort, indoor air quality, and energy consumption. In this study, a type of multi-in-one indoor environmental quality monitoring device was adopted for vertical greening systems in a green-certified building in Changzhou, China, with real-time data collection through an Internet of Things platform. Measurements of the indoor thermal environment and air quality were recorded from four testing points during a 90 day period from spring to summer in 2021. For comparison, the testing points were divided into group A (office zone) and group B (exhibition zone). Our results demonstrated that, in the presence of a vertical greening system, the seasonal average indoor temperatures decreased by up to 0.7 °C. The green facade outperformed the ordinary exterior wall, optimising both indoor thermal comfort and thermal inertia. Furthermore, judicious indoor greening designs significantly reduced the indoor air-pollutant concentrations, such as particulate matter, carbon dioxide, and organic pollutants. The median values for particulate matter 10 and formaldehyde concentration decreased by 20.7% and 33.3%, respectively, thus improving the indoor air quality. Lastly, the annual electricity consumption of the building with vertical greening systems was about 25% lower than that of similar buildings, underlining the potential contribution of vertical greening systems to building energy conservation. Such findings collectively demonstrate that greening systems offer quantifiable benefits for building parameters such as thermal properties, indoor air quality, and energy conservation.