Ambient Air Quality Research Articles

Simple and Low-Cost Ground Level Ozone Measurement System Based on Internet of Things

Air quality monitoring in Indonesia is still not optimal owing to the lack of ambient air quality monitoring stations. Air quality in Indonesia is expressed by the air pollution status index (ISPU). Ozone is one of the parameters with the highest intensity at ambient air quality monitoring stations which is one of the parameters of ISPU. This study aims to design an ambient air ozone concentration monitoring device connected to a wireless network using economical components. This system uses the MQ131 sensor, DHT22 sensor, STM32 Blue Pill microcontroller, and Lora module, which is equipped with a power supply and protector, and displays monitoring results that provide an overview and additional information related to the air quality of the monitoring location on the website. The designed monitoring device can record ambient air ozone levels at the monitoring location with an average value of 20.33 μg/m3 with an average percent error of 2.34%. The ISPU value obtained during the measurement was 8, and the ISPU status was categorized as good.

The effect of temperature on the Emission Factor of air emissions from pyrolysis of used tyres

Used tyres pyrolysis is an efficient solid waste management strategy for used tyres and a growing method of fuel oil production. However, the impact of air emissions associated at different temperature on ambient air quality has not been determined. To solve this problem, a pyrolysis fixed bed reactor and a condensing unit for separating liquid from produced gas were designed and constructed. 0.20 kg of used tyres were pyrolysed in the reactor and air emissions from the reactor chamber was characterized for air pollutants using the E-instrument E8500. Using a combination of measured mass of pollutants, mass of tyre pyrolzed and time taken during pyrolysis, Emission Factors of the air pollutants were established from the study at 200 °C, 300 °C and 400 °C. The concentration measured between 200 °C - 400 °C were in the range of 15 -7497 mg/m3, 0 – 4680 mg/m3, 38.25 – 103, 277.76 mg/m3 and 2 – 293 mg/m3 for CO, NOx, HC and H2S respectively. The developed emission factors were in the range of 16.52 – 8370.04 g kg-1, 0 – 4470.26 g kg-1, 42.126 – 104,055.9 g kg-1 and 2.20 – 322.69 g kg-1. The designed and constructed pyrolysis reactor and condenser unit were effective for used tyre pyrolysis while the measured air pollutants concentration were higher for all pollutants except H2S using the Federal Ministry of Environment (FEPA, 1991) standard. Hence, it is necessary to carry out further studies on air pollution control from waste tyre pyrolysis at lower temperature.

Prescribed burn related increases of population exposure to PM2.5 and O3 pollution in the southeastern US over 2013–2020

Ambient air quality across the southeastern US has improved substantially in recent decades. However, emissions from prescribed burn remain high, which may pose a substantial health threat. We employed a multistage modeling framework to estimate year-round, long-term effects of prescribed burn on air quality and premature deaths. The framework integrates a chemical transport model with a data-fusion approach to estimate 24-h average PM2.5 and maximum daily 8-h averaged O3 (MDA8-O3) concentrations attributable to prescribed burn for the period 2013–2020. The Global Exposure Mortality Model and a log-linear exposure–response functions were used to estimate the premature deaths ascribed to long-term prescribed burn PM2.5 and MDA8-O3 exposure in ten southeastern states. Our results indicate that prescribed burn contributed on annual average 0.59 ± 0.20 µg/m3 of PM2.5 (∼10 % of ambient PM2.5) over the ten southeastern states during the study period. On average around 15 % of the state-level ambient PM2.5 concentrations contributed by prescribed burn in Alabama (0.90 ± 0.15 µg/m3), Florida (0.65 ± 0.19 µg/m3), Georgia (0.91 ± 0.19 µg/m3), Mississippi (0.65 ± 0.10 µg/m3) and South Carolina (0.65 ± 0.09 µg/m3). In the extensive burning season (January–April), daily average contributions to ambient PM2.5 increased up to 22 % in those states. A large part of Alabama and Georgia experiences ≥3.5 µg/m3 prescribed burn PM2.5 over 30 days/year. Additionally, prescribed burn is responsible for an average increase of 0.32 ± 0.12 ppb of MDA8-O3 (0.8 % of ambient MDA8-O3) over the ten southeastern states. The combined effect of prescribed burn PM2.5 exposure, population growth, and increase of baseline mortality over time resulted in a total of 20,416 (95 % confidence interval (CI): 16,562–24,174) excess non-accidental premature deaths in the ten southeastern states, with 25 % of these deaths in Georgia. Prescribed burn MDA8-O3 was responsible for an additional 1,332 (95 % CI: 858–1,803) premature deaths in the ten southeastern states. These findings indicate significant impacts from prescribed burn, suggesting potential benefits of enhanced forest management strategies.

Evidence-driven indoor air quality improvement: An innovative and interdisciplinary approach to improving indoor air quality.

Indoor air pollution is a recognized emerging threat, claiming millions of lives annually. People are constantly exposed to ambient and indoor air pollution. The latest research shows that people in developed countries spend up to 90% of their time indoors and almost 70% at home. Although impaired IAQ represents a significant health risk, it affects people differently, and specific populations are more vulnerable: children, the elderly, and people with respiratory illnesses are more sensitive to these environmental risks. Despite rather extensive research on IAQ, most of the current understanding about the subject, which includes pollution sources, indoor-outdoor relationships, and ventilation/filtration, is still quite limited, mainly because air quality monitoring in the EU is primarily focused on ambient air quality and regulatory requirements are lacking for indoor environments. Therefore, the EDIAQI project aims to improve guidelines and awareness for advancing the IAQ in Europe and beyond by allowing user-friendly access to information about indoor air pollution exposures, sources, and related risk factors. The solution proposed with EDIAQI consists of conducting a characterization of sources and routes of exposure and dispersion of chemical, biological, and emerging indoor air pollution in multiple cities in the EU. The project will deploy cost-effective/user-friendly monitoring solutions to create new knowledge on sources, exposure routes, and indoor multipollutant body burdens. The EDIAQI project brings together 18 organizations from 11 different European countries that provide interdisciplinary skills and expertise in various fields, including environmental science and technology, medicine, and toxicology, as well as policy design and public engagement.

Spatial Analysis of Sulfur Dioxide (SO2) and Nitrogen Dioxide (NO2) Distribution Using Getis-Ord Gi* in DKI Jakarta Region, Indonesia

Abstract The increasing mobility of population and industry is the main problem in this study, so it will affect the spatial pattern in the distribution of pollutants. The parameters to measure air quality are Sulfur Dioxide and Nitrogen Dioxide. This study aims to (1) analyze air quality distribution patterns with SO2 and NO2 concentration parameters in the DKI Jakarta area in 2021, (2) analyze ambient air quality distribution patterns based on air quality threshold values, and (3) analyze the spatial distribution of SO2 and NO2 in the DKI Jakarta area in 2021. The data used for this research is the average concentration data of SO2 and NO2 pollutants in DKI Jakarta in 2021. This research uses the interpolation method using Inverse Distance Weighting and Getis-Ord Gi*. The results of this research show that the concentration of pollutants that have been interpolated using Inverse Distance Weighting produces higher NO2 than SO2. From the interpolated image, a Hot Spot analysis (Getis-Ord Gi*) was conducted. This analysis showed significant clustering of nearest neighbors, with high concentrations of SO2 in East Jakarta and NO2 in West Jakarta. Therefore, air quality needs to be monitored and managed to maintain environmental stability.

Characterization and source apportionment of ambient VOC concentrations: Assessing ozone formation potential in the Barnett shale oil and gas region

Atmospheric concentration and distribution of volatile organic compounds (VOC) are influenced by localized emissions and the fate and transport of secondary products formed through photochemical reactions. This study identifies the sources of VOC and its contribution to ozone formation in the Barnett Shale region, specifically in Denton, Texas, during the ozone seasons of 2015 through 2022. A total of 31 critical ozone precursor VOC compounds were observed at this site with an average total VOC concentration of 146 ppb-C, with n-alkanes from extensive oil and gas activities in the area contributing to 96.64% of the total VOC. Source apportionment using dispersion normalized positive matrix factorization (DN-PMF) identified eight VOC sources, with natural gas emissions (72%) being the dominant source followed by a combined source of natural gas combustion and aviation emissions (8.3%). Ozone formation potential (OFP) by VOC species was calculated using the propylene-equivalent concentration (propy-equiv) method. OFP calculated for all the apportioned sources highlighted that natural gas sources contributed significantly to the ozone formation in this region besides isoprene from biogenic sources and reactive alkenes from urban and industrial activities. This study underscores the critical role of slow-reacting n-alkanes along with other highly reactive VOC from urban and industrial sources influencing ambient air quality and it identifies strategies for mitigating ground-level ozone in urban areas affected by oil and gas extraction and production.

Characterization and impact of airborne particulate matter over Varanasi: A year-long study on concentration, morphology, and elemental composition

Air pollution is an important worldwide issue, especially pronounced in metropolitan and suburban regions, significantly affecting both public health and surroundings. This study investigates the particles' morphology and elemental analysis in Varanasi, a highly inhabited metropolis in the Indo-Gangetic Plain. The research was conducted over a year, from April 2019 to March 2020, utilizing Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy, Ion Chromatography, and Atomic Absorption Spectroscopy to analyse particulate matter. Results indicated that mean values of PM2.5 and PM10 were 106.5 ± 67.2μg/m³ and 180.8 ± 71.4 μg/m³, respectively. Often, these amounts exceeded the National Ambient Air Quality Standards. SEM-EDX analysis revealed diverse particle morphologies, with significant contributions from both manmade sources including industrial activities and vehicle emissions, and natural sources, like soil dust. Elemental analysis identified major components, including Carbon, Oxygen, Fluorine, Aluminium, and Silicon. IC analysis highlighted dominant ionic species, such as Ca++, SO4−-, NO3−, and Cl−, with monthly variations reflecting different emission sources. Heavy metals concentrations such as Ni, Cd, Cr, Mn, Cu, Pb, Zn, and Fe were quantified, with concentrations varying significantly across months. The findings underscore the complex nature of aerosols in Varanasi and highlight the immediate need for targeted control over air quality measures to minimize the particulate matter's detrimental effects on the local population and ecosystem.

Detached eddy simulation of traffic-induced air pollution in an urban highway with complex surrounding morphology

Air pollution caused by traffic is a major contributor to unhealthy ambient air quality in the vicinity of urban highways and puts the health of residents and pedestrians at risk. Therefore, it is imperative to examine local pollution reduction methods. The present paper is concerned with Detached Eddy Simulation (DES) of an urban area with high concentration of air pollutants. As an example of a complex surrounding morphology, the studied domain encompasses a 2.5 km stretch of high-traffic highway, a bus terminal, and the nearby residential buildings. The numerical procedure is validated with some benchmark wind tunnel and numerical data. The locations of pollution accumulation have been identified and the effect of the ambient wind speed on the change of the maximum pollution concentration points has been investigated. Furthermore, potential pollution reduction strategies for such complex morphologies have been proposed based on the geometry change to prevent the formation of critical zones of pollution accumulation. The results show that critical zones are generally formed behind the walls of upstream buildings, adjacent to the upstream wall of the highway, and in front of the walls of downstream buildings. It was also found that changes in the ambient wind speed do not significantly alter the location of these critical zones. Furthermore, increasing the distance between adjacent buildings and the highway from 21 m to 30 m, can result in an average reduction of 76% in maximum carbon monoxide concentration values. An investigation into the impact of upstream buildings height indicates that reducing the height of certain buildings can effectively diminish pollution concentration to zero in residential areas and surrounding sidewalks. Additionally, increasing the depth of the highway and erecting 2 m solid barriers on either side of the highway are identified as two other effective techniques for reducing pollution concentration on both sides of the highway. The findings can be utilised to develop novel strategies aimed at enhancing air quality for residents and pedestrians.

Environmental Quality in Industrial Areas: Case Study of a Company in Banyuasin Regency, South Sumatra Province

With the emergence of industry in the Banyuasin district area, especially in Gasing Village, there are more job opportunities for residents and Banyuasin residents. However, the industry's rapid growth in the Banyuasin district can also hurt the environment, including air and water pollution. This research was carried out through descriptive observations of environmental conditions at the case study site. Data is collected and evaluated based on environmental elements, especially ambient air, emissions, noise and wastewater. At the case study location at an agro-industrial company in the Banyuasin district, the quality of ambient air, noise, emissions and wastewater from the WWTP was tested, and samples were taken. The test results show that the quality of ambient air, noise, emissions and wastewater produced by the WWTP around the factory area is classified as good, and all parameters meet the standards. If the measurement results of this research are looked at, there is no critical threshold value that attracts attention. This research shows that the industry must monitor the quality of the environment to make improvements and reduce the company's negative impact on the environment and the surrounding community's health.

Bibliometric analysis of Indian research trends in air quality forecasting research using machine learning from 2007–2023 using Scopus database

Machine-learning air pollution prediction studies are widespread worldwide. This study examines the use of machine learning to predict air pollution, its current state, and its expected growth in India. Scopus was used to search 326 documents by 984 academics published in 231 journals between 2007 and 2023. Biblioshiny and Vosviewer were used to discover and visualise prominent authors, journals, research papers, and trends on these issues. In 2018, interest in this topic began to grow at a rate of 32.1 percent every year. Atmospheric Environment (263 citations), Procedia Computer Science (251), Atmospheric Pollution Research (233) and Air Quality, Atmosphere, and Health (93 citations) are the top four sources, according to the Total Citation Index. These journals are among those leading studies on using machine learning to forecast air pollution. Jadavpur University (12 articles) and IIT Delhi (10 articles) are the most esteemed institutions. Singh Kp's 2013 "Atmospheric Environment" article tops the list with 134 citations. The Ministry of Electronics and Information Technology and the Department of Science and Technology are top Indian funding agency receive five units apiece, demonstrating their commitment to technology. The authors' keyword co-occurrence network mappings suggest that machine learning (127 occurrences), air pollution (78 occurrences), and air quality index (41) are the most frequent keywords. This study predicts air pollution using machine learning. These terms largely mirror our Scopus database searches for "machine learning," "air pollution," and "air quality," showing that these are among the most often discussed issues in machine learning research on air pollution prediction. This study helps academics, professionals, and global policymakers understand "air pollution prediction using machine learning" research and recommend key areas for further research.

Association of ambient air pollution and Air Quality Index with risk of sudden sensorineural hearing loss: a cross-sectional study

ObjectivesTo explore the associations of air pollutants and Air Quality Index (AQI) with risk of sudden sensorineural hearing loss (SSNHL)DesignCross-sectional studySettingMedical record data and local population data collected between 2014...

Impact of construction activities on the air quality of Agra city, Uttar Pradesh, India

The current research work was carried out to comprehensively assessed the impact of construction activities on the air quality. Seven sites were chosen along the metro line construction in Agra, Uttar Pradesh, India, to meet the study's goals. The monitoring was performed for 24 hours at each site using the respirable dust sampler (RDS) with a gaseous sampling attachment. The raw data was processed to calculate the Air Quality Index (AQI). The data obtained indicate that all the examined sites had PM10 (particulate matter having the diameter less than or equal to 10 micron) values above the National Ambient Air Quality Standards (NAAQ) values of 100 µg/m3, while SS-05 and SS-06 had PM2.5 (particulate matter having the diameter less than or equal to 2.5 micron) values above the NAAQ values of 60 µg/m3. Values of CO, SO2, and NO2 were discovered to be lower than the NAAQ standard limits. Because PM10's sub index (Si) was found to be the greatest across all locations, it was determined to be the criterion pollutant among all the metrics. Based on the AQI value, the research area's overall air quality was determined to be moderately polluted. At every location, a variety of management techniques, including mist guns, water spraying, and planting, are regularly used to reduce air pollution. Effective implementation of applied air pollution control measures is required to make the air clean and safe for breathing.

Long term analysis of air quality parameters for Ludhiana, India: sources, trends and health impact.

Ludhiana, a pollution hot spot in North India, has seen a rapid deterioration in air quality over the years due to urbanization and industrialization. This study interprets the variations of particulate matter (PM) and gaseous pollutants (Nitrogen oxide, Nitrogen dioxide, NOX, Sulphur dioxide, Carbon monoxide, Benzene, Toluene, Ozone, and Ammonia) for the data observed from 2017 to 2023 in Ludhiana. This also covers the analysis focused on capturing the changes that occurred at the times of lockdown imposed during the Coronavirus Disease (COVID-19). The maximum 24-h averaged mass concentration values exceeded the National Ambient Air Quality Standards (NAAQS) of 100µg/m3 for PM10 concentration and 60µg/m3 for PM2.5 concentration in 2018 by the factor of 5 and 8. With the onset of the COVID-19 lockdown in 2020year, PM10 and PM2.5 reached the minimum level while CO, T, O3, and NO2 increased by the factor of 3.9, 1.9, 1.4, and 1.3 from their previous year. This NO2 is a precursor of ozone formation, a higher NO2 to NO ratio observed during the lockdown, confirms the role of nitrogen compounds in the higher ozone formation rate. Based on the NO2/NO ratio, the probability rate of ozone formation determined using survival analysis is observed to be 94% from 2017 to 2023. The local sources' contribution to these air pollutants during Pre-Lockdown, Lockdown, and Post-Lockdown are analyzed using principal component analysis. The impact of the lockdown on ozone concentration sources has been observed. During the Pre- and Post-Lockdown phases, three sources (PC1, PC2, and PC3) were positively identified. Ozone levels are linked to PC3 in these phases, but during the lockdown, a negative loading in PC3 and positive loadings in PC1 and PC2 indicate a decrease in ozone from reduced emissions and an increase from secondary reactions involving nitrogen compounds. Moreover, the Toluene to Benzene concentration ratio is > 2, indicating the source of their origin from industrial emission or other non-traffic sources. Health assessment for the years 2017-2019 reveals a significant decrease in the number of cases of all-cause mortality, ischemic heart disease, stroke, and chronic obstructive pulmonary disease associated with reducing PM2.5 concentrations to national and international standards.

Application of AERMOD dispersion model for assessment PM10 concentrations from mobile sources in Kuala Lumpur Metropolitan City, Malaysia.

Deterioration of air quality in Kuala Lumpur caused by mobile sources and traffic-related activities with interaction with climatic conditions and dispersion in the atmosphere. This study was focused on predicting the averaged 1-h concentration of particulate matter (PM10) that was emitted from private cars in Kuala Lumpur by applying the air dispersion model American Meteorological Society (AMS)/United States Environmental Protection Agency (EPA) Regulatory Model (AERMOD) in 2014. The AERMOD model indicates that private cars in Kuala Lumpur recorded 1-h concentration of PM10 below the Malaysian Ambient Air Quality Guidelines (RMAQG) in 2014. The highest concentration was 59.2µg/m3 in 2014 and mainly concentrated around the city center and highway networks. The highest concentrations are recorded in early morning and late at night, with the highest concentrations at 4 am and 2 am and 48.68µg/m3 and 38.42µg/m3, respectively. Late night to early morning is identified as the dominant time interval for pollutant dispersion. The findings demonstrated that air quality had a significant impact on the 1-h concentration of PM10 emitted from private cars in Kuala Lumpur.

PROTECTION OF ATMOSPHERIC AIR AND AIRSPACE OF UKRAINE: LEGAL, REGULATORY, ENVIRONMENTAL AND ECONOMIC ASPECTS

The study uses general scientific and special methods, the main of which are: abstract-logical, deductive, inductive, historical, modelling and forecasting, methods of system-structural, system-functional analysis, economic and statistical (grouping, comparison, etc.). The use of system analysis methods made it possible to structure the constituent elements of the regulatory and legal support of public administration in the field of protection of atmospheric air and airspace of Ukraine. The purpose of the article is to characterise the protection of atmospheric air and airspace of Ukraine in the regulatory, legal, environmental and economic aspects. It is determined that the regulatory framework for regulating the principles of atmospheric air safety is a component of the mechanism for ensuring environmental safety. The article emphasises that for the first time the principles of environmental safety were enshrined in the Declaration of State Sovereignty of Ukraine, where the principles of environmental safety were established at the level of a separate section. It is emphasised that the functional content of the administrative and legal protection of atmospheric air includes: ensuring air pollution within the limits of the maximum permissible emission standards in order to ensure the right of a person to a safe and quality environment; greening of production; introduction of ecological fuel quality standards; greening of the energy cluster of the economy, including through the introduction of the principles of decentralisation of the country's energy system; establishment of information interaction between the participants of legal relations in order to ensure the transparency of economic activities related to environmental pollution; formation of a high level of environmental legal awareness, etc. The article draws a conclusion that ensuring proper quality of atmospheric air is a component of the mechanism for ensuring environmental safety. The authors underline that the understanding of the system of regulatory and legal regulation of atmospheric air and airspace protection should be functionally aimed at ensuring compliance with environmental standards for the operation of such facilities in accordance with economic feasibility and social justification. The paper concludes that atmospheric air safety and airspace safety are part of the national security system, where the former is a component of environmental safety and the latter is a component of state security, and should be understood as the state of atmospheric air and the integrity of the air environment, for which physical, chemical and biological properties are established which create favourable and sufficient conditions for the vital activity of people and settlements.

Ozone sensitivity to high energy demand day electricity and onroad emissions during LISTOS

ABSTRACT Using a high-resolution, 1.33 km by 1.33 km coupled Weather Research and Forecasting-Community Multi-scale Air Quality Model (WRF-CMAQ), we quantify the impact of emissions of nitrogen oxides (NOx) from high energy demand day (HEDD) electricity generating units (EGU) and onroad vehicles on ambient ozone air quality in the Long Island Sound Tropospheric Ozone Study (LISTOS) region covering New York City (NYC); Long Island, NY; coastal Connecticut; and neighboring areas. We test sensitivity scenarios to quantify HEDD EGU NOx contributions to ozone: (1) zero out HEDD EGU emissions, (2) dispatch HEDD EGUs starting with the lowest NOx emitting units first, (3) reduce onroad emissions by 90%, (4) combine zero out HEDD EGU emissions and reducing onroad emissions by 90%, and (5) dispatch HEDD EGUs starting with the lowest emitting units coupled with a reduction in onroad emissions by 90%. Results determine that HEDD EGUs lead to highly localized impacts on ambient concentrations of ozone while onroad emission reductions lead to large-scale regional concentration impacts. Further, reducing onroad emissions by 90% leads to spatially smaller VOC-limited regions and spatially larger transitional and NOX-limited regions around NYC. Despite the limited scale at which the EGU emission reductions occur, modifying HEDD EGU NOX emissions still provides substantial benefits in reducing ozone concentrations in the region, particularly at elevated ozone concentrations above 70 ppb. Implications: High-resolution coupled meteorology-chemistry modeling was used to quantify the impacts of high energy demand day (HEDD) electricity generating units (EGUs) and onroad transportation emissions changes on ozone air quality in the LISTOS region. Despite being highly localized and variable, HEDD EGUs NOX emissions sensitivity tests led to quantifiable changes in ozone. Further, reducing onroad emissions by 90% produced large decreases in ozone concentrations and led to a more NOX-sensitive ozone photochemical regime. With a transition to greater NOX-sensitivity, urban NOX-titration weakens and ozone is more likely to decline with the removal of additional NOX from sources like HEDD EGUs.

The improvement of Beijing ambient air quality resulting from the upgrade of vehicle emission standards

The improvement of Beijing ambient air quality resulting from the upgrade of vehicle emission standards

Emerging Scientific Approaches for Identifying Ecologically Adverse Effects of Air Pollution.

Now more than ever, complex socio-ecological challenges require timely and integrated responses from scientists and policymakers. Air quality is one such challenge. Under the Clean Air Act, the U.S. Environmental Protection Agency establishes ambient air quality standards to protect public welfare from known or anticipated adverse effects of air pollutants. As our understanding of the environment and awareness of social values grow, there is a need to improve characterization of "adversity to the public welfare." Scientific assessment can link ecological effects to public welfare using modern scientific approaches that incorporate ecological complexity and multiple value systems held by the public. We propose ideas for the future of scientific assessments meant to inform air quality and other environmental decision-making, including concrete ways we can focus on vulnerable species and ecosystems, incorporate a multiplicity of values, climate and multiple stressors, and partner to diversify the knowledge upon which protective policies are based.

Factors Affecting the Indoor Air Quality and Occupants’ Thermal Comfort in Urban Agglomeration Regions in the Hot and Humid Climate of Pakistan

The World Air Quality Index indicates that Pakistan ranks as the third most polluted country, regarding the average (Particulate Matter) PM2.5 concentration, which is 14.2 times higher than the World Health Organization’s annual air quality guideline. It is crucial to implement a program aimed at reducing PM2.5 levels in Pakistan’s urban areas. This review paper highlights the importance of indoor air pollution in urban regions such as Lahore, Faisalabad, Gujranwala, Rawalpindi, and Karachi, while also considering the effects of outdoor air temperature on occupants’ thermal comfort. The study aims to evaluate past methodological approaches to enhance indoor air quality in buildings. The main research question is to address whether there are statistical correlations between the PM2.5 and the operative air temperature and whether other indoor climatic variables have an impact on the thermal comfort assessment in densely built urban agglomeration regions in Pakistan. A systematic review analysis method was employed to investigate the effects of particulate matter (PM2.5), carbon oxides (COx), nitrogen oxides (NOx), sulfur oxides (SOx), and volatile organic compounds (VOCs) on residents’ health. The Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) protocol guided the identification of key terms and the extraction of cited studies. The literature review incorporated a combination of descriptive research methods to inform the research context regarding both ambient and indoor air quality, providing a theoretical and methodological framework for understanding air pollution and its mitigation in various global contexts. The study found a marginally significant relationship between the PM2.5 operative air temperature and occupants’ overall temperature satisfaction, Ordinal Regression (OR) = 0.958 (95%—Confidence Interval (CI) [0.918, 1.000]), p = 0.050, Nagelkerke − Regression (R2) = 0.042. The study contributes to research on the development of an evidence-based thermal comfort assessment benchmark criteria for the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Global Thermal Comfort Database version 2.1.

A hybrid approach for integrating micro-satellite images and sensors network-based ground measurements using deep learning for high-resolution prediction of fine particulate matter (PM2.5) over an indian city, lucknow

The detrimental impacts of fine particulate matter (PM2.5) on human health, climate, ecosystems, crops, and building materials are well-established. However, there remain unresolved inquiries regarding the precise location of the sources of PM2.5. This study is the first attempt to use a calibrated sensors-based ambient air quality monitoring network (SAAQM network) and regulatory government monitors to train micro-satellite images for high spatial-resolution air pollution field determination of PM2.5 in Lucknow, Uttar Pradesh, India. A hybrid approach is developed to integrate three different datasets that include microsatellite images, PM2.5 ground measurements, and supporting information (meteorological parameters and geographical coordinates), to be fed into a Random Trees-Random Forest- Convolutional Neural Network (RT-RF-CNN) joint model to estimate PM2.5 concentrations at a sub-km level. The RT-RF-CNN joint model can derive PM2.5 concentrations at a spatial resolution of 500 m with statistically significant indicators such as spatial r of 0.9, a low root-mean-square error of 26.9 μg/m3 and a mean absolute error of 17.2 μg/m3. Based on our approach, the PM2.5 prediction maps using micro-satellite images (spatial resolution of 3m/pixel) and RT-RF-CNN joint model were generated for each day throughout the study period (December 2021–December 2022). The inter-grid comparison of these maps revealed the intra-urban local hotspots and coolspots at a fine-granular level seasonally, monthly, and daily. It is observed that the monsoon season has the highest number of coolspots (67%), while winter (0.1%), post-monsoon (0.5%) and summer (11%) have fewer. It is noted that the high temporal-spatial information of PM2.5 estimates from our integrated approach is not achievable by ground-based measurements and other existing satellite-based estimates alone. The findings of this study have potential applications on a diverse array, encompassing near real-time daily PM2.5 predicted maps, specific air pollution hotspot identification, PM2.5 exposure assessment at the neighbourhood level, and integration of remote sensing-based micro-satellite images and ground-based measurements.