Exposure to Particulate Matter and CO2 in indoor conditions at IIT(ISM) Dhanbad

The air quality of the living area influences human health to a certain extent. Therefore, it is particularly important to detect the quality of indoor air. However, traditional detection methods mainly depend on chemical analysis, which has long been criticized for its high time cost. In this research, a rapid air detection method for the indoor environment using laser-induced breakdown spectroscopy (LIBS) and machine learning was proposed. Four common scenes were simulated, including burning carbon, burning incense, spraying perfume and hot shower which often led to indoor air quality changes. Two steps of spectral measurements and algorithm analysis were used in the experiment. Moreover, the proposed method was found to be effective in distinguishing different kinds of aerosols and presenting sensitivity to the air compositions. In this paper, the signal was isolated by the forest, so the singular values were filtered out. Meanwhile, the spectra of different scenarios were analyzed via the principal component analysis (PCA), and the air environment was classified by K-Nearest Neighbor (KNN) algorithm with an accuracy of 99.2%. Moreover, based on the establishment of a high-precision quantitative detection model, a back propagation (BP) neural network was introduced to improve the robustness and accuracy of indoor environment. The results show that by taking this method, the dynamic prediction of elements concentration can be realized, and its recognition accuracy is 96.5%.

/pdf/analysis-and-dynamic-monitoring-of-indoor-air-quality-based-3qyzlij8.pdf

Analysis and Dynamic Monitoring of Indoor Air Quality Based on Laser-Induced Breakdown Spectroscopy and Machine Learning

http://manuscript.elsevier.com/S1309104222000617/pdf/S1309104222000617.pdf

Quantifying indoor PM2.5 levels and its sources in schools: What role does location, chalk use, and socioeconomic equity play ?

High level of particulate matter in an office building is one of the prime concerns for occupant's health and their work performance. The present study focuses on the evaluation of the distribution pattern of airborne particles in three office buildings in Delhi City. The study includes the Assessment of PM10, PM2.5 and PM1 in the different indoor environments, their particle size distribution, I/O ratio, a correlation between pollutants their sources and management practices. The features of buildings I, II, and III are old infrastructure, new modern infrastructure, and an old building with good maintenance. The results indicate that the average concentrations of PM10, PM2.5, and PM1 are found in the range of 55-150 ?g m-3, 41-104 ?g m-3 and 37-95 ?g m-3, respectively in Building I, 33-136 ?g m-3, 30-84 ?g m-3 and 28-73 ?g m-3, respectively in Building II and 216-330 ?g m-3, 188-268 ?g m-3 and 171-237 ?g m-3, respectively in Building III. The maximum proportion of the total mass contributed by PM0.25-1.0 i.e., up to 75%, 86%, and 76% in the meeting room of Building I, II and III, respectively. The proportion of ultrafine particles was found higher in the office area where the movement was minimum and vice versa. The higher I/O indicates the contribution of the presence of indoor sources for ultra-fine and finer particles. Further, possible strategies for indoor air pollution control are also discussed.

/pdf/evaluation-of-particulate-matter-pollution-in-micro-4r2lpimcdg.pdf

Evaluation of Particulate Matter Pollution in Micro-Environments of Office Buildings—A Case Study of Delhi, India

The research activity in the field of monitoring indoor quality systems has become an unavoidable challenge facing many researchers. Monitoring closed areas can reduce health-related risks due to poor or contaminated air quality. In the current COVID pandemic, we have observed that improving ventilation in a closed space can significantly reduce infection risk. In this paper, several researchers’ protocols and the methodology for monitoring indoor air-quality systems are presented. The majority of the reviewed works are aimed to reduce air pollution levels in the atmosphere. The partial access of sensed data, expensive and non-expansible of traditional air-quality monitoring systems, led to the adoption of IoT and WSN to create a genuine system capable of producing many high-quality services. Furthermore, ad hoc approaches are predominantly used to help society change its attitude and impose corrective actions to improve air quality. This paper provides a brief but fully review of several researchers’ works with different approaches to ecological trend analysis capabilities, drawing on existing literature works. Overall, this study highlights the need for developing systematic protocols for these systems and establishes smart air-quality monitoring systems capable of measuring pollutant concentrations in the air.

Indoor Air Quality Monitoring Systems: A Comprehensive Review of Different IAQM Systems

Delhi ranks highest among the most polluted city in the world in terms of air pollution. Its health impact may include diseases like asthma, lung cancer, COPD, increased long-term risk of cardiopulmonary mortality. Degraded indoor air quality inside commercial buildings such as offices may affect the health of the workers and can indirectly affect their productivity. In the present study, indoor air quality has been studied in four different air-conditioned office buildings located in Delhi NCR for the criteria pollutant PM2.5 and the CO2 as ventilation parameter. The total hazard ratio indicator has also been calculated from the data of PM2.5 and CO2 for all selected office premises. The results of the study show the highest concentration of PM2.5 in building A1 (116.5 ± 67 µg/m3) and highest CO2 concentration in building A2 (1600 + 30.5 ppm). Higher concentration of PM2.5 in building A1 could be due to its maximum proximity to urban busy roads and poorly maintained HVAC ducting system, which may lead to infiltration and more leakages of PM2.5 from outdoors. Similarly, the highest concentration of CO2 in building A2 could be due to insufficient ventilation condition. In each studied building, the concentration of CO2 and PM2.5 are recorded to be higher than the NAAQS and ASHRAE standards. The health hazard ratio indicates that both CO2 and PM2.5 plays an important role in determining the health of the building and its occupants. However, the health impacts of increased PM2.5 could be more severe than CO2 depending upon the sources of PM2.5.

Radha Goyal

Papers

Environmental Monitoring of PM 2.5 and CO 2 in Indoor Office Spaces of Delhi, India