Emission Characteristics Of Sources Research Articles

Numerical study on the gas-solid diffusion characteristics of airflow and dust particles in metal mine blasting excavation under three hybrid ventilation modes

Dust pollution has long been a challenge in the blasting excavation of underground metal mines, and uncontrolled diffusion of dust particles seriously endangers the health and safety of workers as well as the environment in underground space. Most existing research on dust diffusion focuses on fully mechanized coal mining face or borehole drilling, where the dust source emission characteristics differ significantly from metal mine blasting excavation. Furthermore, it is still unclear how the ventilation modes of Far-Pressing-Far-Absorption (FPFA), Near-Pressing-Far-Absorption (NPFA), and Far-Pressing-Near-Absorption (FPNA) affect the mechanism of dust diffusion in the breathing zone. In this work, gas-solid flow characteristics in a typical metal mine blasting tunnel are numerically studied based on Euler-Lagrange method. The interphase forces between airflow and dust particles are comprehensively modeled, and the particle diffusion effect caused by fluid turbulence is described by the discrete random walk model. Five typical regions for airflow disorder phenomena in the working tunnel are predicted, including the jet development region, the return airflow core region, the airflow reversal region, the airflow recirculation region, and the secondary flow region. The spatial distribution of dust exhibits nonuniform characteristics under turbulent airflow transport. The time results of the monitored dust concentration reveal that the junction of the working tunnel and the return airway is a key area of focus for the prevention and control of dust pollution. Among the three ventilation modes, the Far-Pressing-Near-Absorption (FPNA) ventilation mode has the best dust removal efficiency. The supply vent further from the blasting face allows the jet to fully develop, while the exhaust vent closer to the blasting face allows dust particles to be drawn in and discharged earlier. Under the condition of fixed total power consumption for the supply and exhaust fans, a larger exhaust airflow velocity helps remove dust from the breathing zone.

Deep learning models for air quality forecasting based on spatiotemporal characteristics of data

Deep learning models for air quality forecasting based on spatiotemporal characteristics of data

Automatic identification of factor profiles can be achieved by improved machine learning model

The identification of factor profiles is a pivotal step in the source apportionment model. Currently, this process heavily relies on human experience, resulting in high subjectivity in the results and requiring a time-consuming procedure. In this study, a pseudo label extra trees classifier model was proposed to facilitate the automated identification of factor profiles. The source profiles serve as domain knowledge to train the model, as they accurately reflect the distinctive characteristics of emission sources. The findings indicate that the recognition rate of seven factors is 94.3%, significantly outperforming four factors (25%), five factors (30%), six factors (60%). Significantly, the model demonstrates its proficiency in determining the optimal number of factors. And the factor profiles identified using this approach demonstrate complete concurrence with manual recognition. For offline datasets, the model is also proficient at identifying factor profiles and exhibits excellent generalization. This approach facilitates the identification of emission sources in intricate environments and advances the model's capacity to automatically discern source categories by utilizing domain knowledge characteristics.

Seasonal and Emission Characteristics of PAHs in the Ambient Air of Industrial Complexes

Particulate and gaseous polycyclic aromatic hydrocarbon (PAHs) samples (n = 108) were measured every six days from January to December 2022 at a representative point in the Korean Banwol National Industrial Complex. The measurement results revealed that the concentration of particulate Σ18 PAHs was 7.92 ± 4.04 ng/Sm3 in winter, 1.83 ± 1.99 ng/Sm3 in spring, 1.43 ± 0.95 ng/Sm3 in summer, and 2.58 ± 2.14 ng/Sm3 in autumn. The concentration of gaseous Σ18 PAHs was 3.32 ± 3.72 ng/Sm3 in winter, 6.34 ± 5.95 ng/Sm3 in spring, 8.33 ± 8.13 ng/Sm3 in summer, and 3.88 ± 1.71 ng/Sm3 in autumn. The results of the correlation analysis showed that particulate PAHs have positive relationships with PM10 and PM2.5 and negative relationships with temperature and O3. The diagnostic ratio and PAHs component slope showed that the emission source characteristics of the Banwol National Industrial Complex were dominated by biomass coal combustion over four seasons; however, the influence of petroleum combustion (automobile emissions) was not negligible. As for coal combustion, bituminous coal was the most influential, and lignite was relevant in summer and autumn.

A novel method for spatial allocation of volatile chemical products emissions: A case study of the Pearl River Delta

The spatial allocation of volatile chemical products (VCPs) emissions is often inaccurate, which hampers the evaluation and improvement of models and the study of urban secondary pollution and exposure risk. This work developed a 1 km grid spatial allocation factors dataset based on the actual emission characteristics of each VCPs sector. For the industrial VCPs sector, we used industrial output per unit firm as the spatial allocation factors. For the non-industrial VCPs sector, we used specific datasets (e.g., GDP (Gross Domestic Product) for personal care products use, etc.) as the spatial allocation factors. Our work accounted for the high emission characteristics of industrial point sources and the dependence conditions of non-industrial VCPs use. Using this methodology, we developed a 1 km gridded emission inventory (denoted by Mo-E) of VCPs in the Pearl River Delta (PRD, Excluding Hong Kong Special Administrative Region (SAR) and Macau SAR) region in 2017. The results show that the non-methane volatile organic compounds (NMVOCs) emissions of VCPs in the PRD region in 2017 were 1046.7 Kt, with coatings (567.3 Kt) and personal care products (225.5 Kt) being the key sectors for emission control. Different cities in the PRD region have different VCPs control strategies. The industrial VCPs sector was the dominant VCPs emitter in high-emitting cities (64.9%–72.2%), while the non-industrial VCPs sector was the main contributor in low-emitting cities (43.3%–58.4%). More VCPs emissions were allocated to medium-population-density areas (37.6% higher than before) and within 3 km of the urban-rural fringe (41.4% higher than before), compared with the spatial characteristics of VCPs emissions from Multi-resolution Emission Inventory for China (MEIC), due to the relocation of industrial VCPs enterprises and the architectural activities during urban expansion. Meanwhile, the uniform distribution pattern caused by population density allocation in these areas was corrected, and the point-source high-emission feature was tracked. The VCPs emissions in high-population-density areas were overestimated (31.4%), with personal care products (57.9%) as the main emission sources in these areas. We compared the Mo-E inventory with an inventory (Mo-M) derived using MEIC's spatial allocation factors, and found a maximum difference in emissions per unit grid of +14,602 t and a minimum of −880 t. Finally, we discuss the uncertainties in the emissions from each VCP sector (±30–80%) and the spatial emission patterns, which resulted from the spatial allocation dataset (±10.4–20%) and the spatial analysis methods (−6.9-+7.8%).

Microphysical characteristics of black carbon from various emission sources

The complex microphysical characteristics of black carbon aerosol (BC) results in large uncertainties in the evaluation of BC's climatic and environmental effects. In this study, the microphysical properties were investigated in fresh BC emitted from traffic sources (gasoline vehicle and diesel) and aged BC emitted from solid fuel burning sources (coal, cotton stem, rice stem and mulberry). For the BC core size distribution, the number size distribution of traffic sources peaks at a lower value than that of aged solid fuel burning sources. Although traffic sources emit a greater number of small BC cores, traffic sources could also emit BC aerosols with large BC cores (diameter larger than 400 nm) not found in solid fuel sources. The coating thickness of BC from traffic sources is significantly lower than that of aged BC from solid fuel sources. Such differences in size distribution and coating thickness cause large variations in other microphysical parameters, such as light absorption and hygroscopicity, for these two types of BC. The mass absorption cross section (MAC) of aged BC from cotton stems reached 11.69 m2/g, nearly 2 times higher than the MAC (6.08 m2/g) of fresh BC from gasoline vehicles. The hygroscopicity of aged BC from solid fuel burning is also much higher than that of fresh BC from traffic. The critical supersaturation needed to activate BC to become cloud droplets is 0.03% for the former and 0.42% for the latter. This study reports the BC emission characteristics of traffic sources and emphasizes the large property difference between fresh traffic emission BC and aged solid fuel burning BC. The microphysical properties of BC should be carefully considered to better resolve BC concentrations and optical properties in climatic models.

Large sub-regional differences of ammonia seasonal patterns over India reveal inventory discrepancies

Ammonia (NH3) is a key precursor of haze particles and fine particulate matter (PM2.5) and its spatiotemporal variabilities are poorly constrained. In this study, we present measurements of NH3 over the Indian subcontinent region from the Infrared Atmospheric Sounder Interferometer (IASI) and Cross-track Infrared Sounder (CrIS) satellite instruments. This region exhibits a complex emission profile due to the number of varied sources, including crop burning, fossil fuel combustion, fertilizer application, livestock and industrial sources. Observations from the CrIS and IASI instruments are oversampled to a resolution of 0.02° × 0.02°. Five regions with distinct spatiotemporal NH3 profiles are determined using k-means clustering. Maximum NH3 columns are seen in July over the western India with column densities of 6.2 × 1017 mol cm−2 and 7.2 × 1017 mol cm−2 respectively for IASI and CrIS. The seasonality of measured NH3 columns show annual maxima occurring in spring in Eastern India and Bangladesh and in mid-summer for the western Indo-Gangetic plain. Our observational constraints suggest that the impact of local farming practices on NH3 emissions is not well captured in emission inventories such as Coupled Model Intercomparison Project Phase 6 (CMIP6), which exhibits peaks in the late spring and autumn. The spatial variability in the seasonal patterns of NH3 is also not captured by the single emissions profile used in CMIP6 for India. The high-resolution maps obtained from these measurements can be used to improve NH3 emission inventories in order to understand its sources for more accurate predictions of air quality in the Indian subcontinent. Our study points to the need for regionally specific emissions inventories for short-lived species such as NH3 that have heterogeneous emissions profiles due to specific agricultural practices and other emission source characteristics.

Has the Three-Year Action Plan improved the air quality in the Fenwei Plain of China? Assessment based on a machine learning technique

A Three-Year Action Plan was implemented in 2018 to improve air quality in the Fenwei Plain. Yet, the effectiveness of this action plan is not clear, which is of great concern to the public and policymakers. Meteorological differences between years may lead us to misestimate the effect of pollutant reduction policies. Here we quantitatively assess the effectiveness of the Three-Year Action Plan in the Fenwei Plain using a meteorological normalization technique based on a machine learning model. To reduce the uncertainty of the model itself, we performed the optimization of hyperparameters and the selection of the optimal model. Ultimately, our study results showed that after removing the impact of meteorology on air quality, the true concentrations of PM2.5, PM10, O3, SO2, NO2, and CO in the Fenwei Plain decreased by 29, 29, 2, 61, 20, and 42% from 2017 to 2020, respectively. The normalized concentrations of all pollutants decreased less than the observed concentrations, implying that if we focus only on the observed data, we could overestimate the effectiveness of the Three-Year Action Plan in the Fenwei Plain. Besides, combining the different decreases in concentrations of six pollutants and the emission characteristics of different pollution sources, we can conclude the improvement in air quality in the Fenwei Plain during 2017–2020 was mainly driven by the residential and industrial sectors. Our work could help the public and policymakers review the effectiveness of the Three Action Plan in the Fenwei Plain and provided a useful reference for the evaluation and formulation of pollutant emission reduction policies.

Long-term reproducibility of emission characteristics of high-current diamond-graphite sources of electrons with field emission under non-stationary vacuum operating conditions

The results of a study of the long-term reproducibility of the emission characteristics of electron sources with field emission density of up to 1000 A/cm2 of based on composite nanocarbon films are presented. It was found that high-current field emission is accompanied by the sputtering of residual gas ions from atoms of the cathode material and its sedimentation on the anode. The results can be used to predict the durability of high-current diamond-graphite cathodes with field emission when operating in unsteady temperature-vacuum conditions. Keywords: diamond-graphite nanocomposite, high-current field emission, reproducibility of field emission parameters, service life of cathode with field emission.

Dynamic of Particulate Matter for Quotidian Aerosol Sources in Indoor Air

A correlation between the mass concentration of particulate matter (PM) and the occurrence of health-related problems or diseases has been confirmed by several studies. However, little is known about indoor PM concentrations, their associated risks or their impact on health. In this work, the PM1, PM2.5 and PM10 produced by different indoor aerosol sources (candles, cooking, electronic cigarettes, tobacco cigarettes, mosquito coils and incense) are studied. The purpose is to quantify the emission characteristics of different indoor particle sources. The mass concentration, the numerical concentration, and the size distribution of PM from various sources were determined in an examination room 65 m3 in volume. Sub-micrometer particles and approximations of PM1, PM2.5 and PM10 concentrations were measured simultaneously using a diffusion aerosol spectrometer (DAS). The ultrafine particle concentration for the studied indoor aerosol sources was approximately 7 × 104 particles/cm3 (incense, mosquito coils and electronic cigarettes), 1.2 × 105 particles/cm3 for candles and cooking and 2.7 × 105 particles/cm3 for tobacco cigarettes. The results indicate that electronic cigarettes can raise indoor PM2.5 levels more than 100 times. PM1 concentrations can be nearly 55 and 30 times higher than the background level during electronic cigarette usage and tobacco cigarette burning, respectively. It is necessary to study the evaluation of indoor PM, assess the toxic potential of internal molecules and develop and test strategies to ensure the improvement of indoor air quality.

Uncovering the characteristics of air pollutants emission in industrial parks and analyzing emission reduction potential: case studies in Henan, China

Industrial parks contribute greatly to China’s economic development while emitting huge air pollutants. It is necessary to study the characteristics of air pollutant emissions in industrial parks. In this study, emission inventories for 11 industrial parks were established. Meanwhile, the source emission and spatial distribution characteristics of the industrial park were analyzed. The cluster analysis was used to classify these parks into “4Hs”, “Mixed” and “4Ls” parks. “4Hs”, “Mixed” and “4Ls” represent that the levels of energy intensity, economic proportion of energy-intensive industries, coal proportion and pollution performance value are high, medium and low in turn. Then three emission reduction measures were set up to estimate the emission reduction potential and environmental impacts. The results show that: (1) the emissions of SO2, NOx, CO, PM10, PM2.5, VOCs and NH3 of 11 industrial parks in 2017 were 11.2, 23.1, 30.8, 8.3, 3.5, 5.1, and 1.1 kt, respectively. (2) Power plants were the largest source of SO2 and NOx emissions, and industrial processes were the largest emission source of CO, PM10, PM2.5, VOCs and NH3. (3) “4Hs” parks with traditional energy-intensive industries as the leading industries should be the emphasis of air pollutant emission reduction. (4) Through the optimal emission reduction measures, SO2, NOx, PM10, PM2.5 and VOCs were reduced by 81, 46, 51, 46 and 77%, respectively. Environmental impact reductions include 1.6 kt SO2eq acidified gas emissions, 1.4 kt PO43−eq eutrophication substances, 4.2 kt PM10eq atmospheric particulate emissions, 7.0 kt 1,4-DCEeq human toxic substances, and 5.2 kt PM2.5 eq breathing Inorganic. This study is helpful to understand the characteristics of air pollutants emissions in industrial parks and promotes the proposal and implementation of air pollutant emissions reduction strategies.

Assessment of ambient air quality, meteorological parameters, and emission source characteristics of Çanakkale, Turkey

Assessment of ambient air quality, meteorological parameters, and emission source characteristics of Çanakkale, Turkey

A newly integrated dataset of volatile organic compounds (VOCs) source profiles and implications for the future development of VOCs profiles in China

Volatile organic compounds (VOCs) source profiles can be used for a number of purposes, such as creating speciated air pollutant emission inventories and providing inputs to receptor and air quality models. In this study, we first collected and schematically evaluated more than 500 Chinese domestic source profiles from literature and field measurements, and then established a most up-to-date dataset of VOCs source profiles in China by integrating 363 selective VOCs profiles into 101 sector-based source profiles. The profile dataset covers eight major source categories and contains 447 VOCs species including non-methane hydrocarbons (NMHCs) species and oxygenated VOCs (OVOCs) species. The results shown that (1) VOCs composition characteristics exhibit variations for most Level-II source sectors and Level-III sub-sectors even under the same Level-I source category; (2) OVOCs, which were significantly missing in previous profiles, account for more than 95% in cooking and 20– 40% in non-road mobile, biomass burning and solvent use sources; (3) aromatics account for 20%–40% in most emission sources except cooking source, alkenes and alkynes account for ~20% in combustion sources (stationary combustion, mobile source and biomass burning), alkanes are abundant in gasoline-related emission sources(on-road mobile source and fuel oil storage and transportation); (4) missing OVOCs species could bring 30%–50% to ozone formation potentials in most emission sources; and (5) there are considerable differences in VOCs chemical groups and individual species for most emission sources between this dataset and the widely used U.S. SPECIATE database, indicating the importance of developing domestic VOCs source profiles. The dataset developed in this study can help support reactive VOCs species-based ozone control strategy and provide domestic profile data for source apportionment and air quality modeling in China and other countries or regions with similar emission source characteristics.

Some Issues Quantifying Low-carbon of an Achievement Energy and Industry

In this work, for use as a unified tool within the framework of ISO 50001, a methodology for rating assessment of the processing of emissions with global pollutants is proposed, which was developed by the authors and recommended for use by state documents of the Republic of Tatarstan, Russia. It is distinguished by the absence of not transparences elements. As the initial data, the actual background concentrations (according to WMO data), the annual ceiling of greenhouse gas emissions and the maximum permissible emissions of toxic compounds, information on the characteristics of emission sources are taken for the enterprise, and as operational constants, the global warming potentials of greenhouse gases (GWP100) and officially approved values of maximum permissible concentrations of toxic compounds (MPC). The method is based on the equation (presented here at annotation in a simplified form), which gives a numerical indicator (rating) R of the efficiency of a production facility in terms of hazardous emissions into the atmosphere, taking into account greenhouse gases and energy costs arising from their removal. Currently, the technique is adapted to the energy sector; for wider adaptation to various industries, a low-carbon rating program has been drawn up for boiler houses, thermal power plants and industrial enterprises. It also meets the needs of understanding and predicting possible deviations of emission parameters from the standardized indicators. Therefore, it can serve as a tool within the framework of ISO 50001, providing objective control over the choice of means to ensure compliance with the requirements for harmful components emissions including greenhouse gases in the design and modernization of production facilities. The developed program is embedded for Russian enterprises in the shell of the ‘1C: Enterprise’ platform – a software product for automating accounting and management at enterprises. The program can also be used in the software shell of the automated accounting of the activities of a particular organization in a one or the other country.

Долговременная воспроизводимость эмиссионных характеристик алмазографитовых полевых источников электронов в нестационарных вакуумных условиях эксплуатации

The results of a study of the long-term reproducibility of the emission characteristics of electron sources with field emission density of up to 1000 A/cm2 of based on composite nanocarbon films are presented. It was found that high-current field emission is accompanied by the sputtering of residual gas ions from atoms of the cathode material and its sedimentation on the anode. The results can be used to predict the durability of high-current diamond-graphite cathodes with field emission when operating in unsteady temperature-vacuum conditions.

Inflammatory responses of urban air PM modulated by chemical composition and different air quality situations in Nanjing, China

The health risks of air pollutants and ambient particulate matter (PM) are widely known. PM composition and toxicity have shown substantial spatiotemporal variability. Yet, the connections between PM composition and toxicological and health effects are vaguely understood. This is a crucial gap in knowledge that needs to be addressed in order to establish air quality guidelines and limit values that consider the chemical composition of PM instead of the current assumption of equal toxicity per inhaled dose. Here, we demonstrate further evidence for varying toxicological effects of urban PM at equal mass concentrations, and estimate how PM composition and emission source characteristics influenced this variation.We exposed a co-culture model mimicking alveolar epithelial cells and macrophages with size-segregated urban ambient PM collected before, during, and after the Nanjing Youth Olympic Games 2014. We measured the release of a set of cytokines, cell cycle alterations, and genotoxicity, and assessed the spatiotemporal variations in these responses by factorial multiple regression analysis. Additionally, we investigated how a previously identified set of emission sources and chemical components affected these variations by mixed model analysis.PM-exposure induced cytokine signaling, most notably by inducing dose-dependent increases of macrophage-regulating GM-CSF and proinflammatory TNFα, IL-6, and IL-1β concentrations, modest dose-dependent increase for cytoprotective VEGF-A, but very low to no responses for anti-inflammatory IL-10 and immunoregulatory IFNγ, respectively. We observed substantial differences in proinflammatory cytokine production depending on PM sampling period, location, and time of day. The proinflammatory response correlated positively with cell cycle arrest in G1/G0 phase and loss of cellular metabolic activity. Furthermore, PM0.2 caused dose-dependent increases in sub-G1/G0 cells, suggesting increased DNA degradation and apoptosis. Variations in traffic and oil/fuel combustion emissions contributed substantially to the observed spatiotemporal variations of toxicological responses.

The Impacts of Urban Air Pollution Emission Density on Air Pollutant Concentration Based on a Panel Model

In terms of urban planning, the impact of urbanization and high density on the environment is a major issue. This study intended to analyze the effect of spatial density characteristics of urban air pollution sources on urban air pollution concentration using a panel model. As the total population density, the number of cars registered per capita, and the total emission facility density increased, together with a closer distance to a thermal power plant, the nitrogen dioxide(NO2) concentration increased. Net population density was also found to have the greatest impact on the structure and density of emission sources of ozone(O3) followed by the number of cars registered per person and the total emission facility density. It was confirmed that particular matter(PM10) concentrations are strongly influenced in positive directions by the spatial density characteristics of emission sources that show significant differences between regions.

Emission Inventory and Characteristics of Anthropogenic Air Pollution Sources Based on Second Pollution Source Census Data in Sichuan Province

In this research, the activity data of Sichuan Province were collected using bottom-up and top-down methods. According to the second survey of pollution sources, the activity data of industrial source includes information of 11020 boilers and 60078 industrial enterprises. Data of 19152 industrial enterprises were collected in Chengdu, accounting for 32% of the total number of enterprises in Sichuan Province. The anthropogenic air pollutant emission inventory of 9 km×9 km was developed for Sichuan Province in 2017 with the use of appropriate emission estimation methods. The results showed that the total emission of SO2,NOx,CO,PM10,PM2.5,BC,OC,VOCs, and NH3 in Sichuan were 308.6×103, 725.7×103, 3131.2×103, 927.6×103, 422.4×103, 30.2×103, 72.0×103, 600.9×103, and 887.1×103 t. The fixed combustion source and process source mainly contributed as sources of SO2. The main source of CO was the process source and mobile source. Further, the dust source and process source were the main sources of PM10 and PM2.5, and the dust source was the largest source of BC and OC contributions. The emission sources of the VOCs were primarily the process sources, mobile sources and solvent use sources. The NH3 emissions were mainly from livestock and poultry breeding and nitrogen fertilizer applications. The spatial distribution results showed that the pollutants were mainly concentrated in the densely populated Sichuan basin and Panzhihua region, where industry and agriculture were relatively developed. The high value points are concentrated along the Deyang-Chengdu-Meishan-Leshan line in Chengdu Plain. The emission inventory established in this study still has certain uncertainties, and the accuracy of activity level data acquisition should be further enhanced. Moreover, pollutant emission factor testing should be carried out for typical pollution sources, and grid emission inventory should be improved to provide scientific support for the prevention and control of air pollution in Sichuan Province in the future.

Emission spectroscopic diagnostics of weakly ionized argon-diluted plasmas: glow discharge and inductively coupled plasma

An extensive study of Mn, Fe, Ti, Cr, Cu emission spectra from a Grimm-type glow discharge (GDOES) and an inductively coupled plasma (ICP), in argon, was performed, using the formalism of population functions (experimental Boltzmann plots) and transition rate diagrams. Emission characteristics of both spectral sources were compared, with the following results: in both discharges the excitation of neutral metal atoms (Me I) is dominated by electron impact (EI), however, in the excitation of singly charged ions (Me II) the charge transfer between Ar+ ions and Me I plays a significant role, especially in GDOES. Relative populations of singly charged excited ions compared to the population of excited neutral atoms of the same element are much higher in ICP than GDOES. Deviations from local thermodynamic equilibrium were identified. Besides charge transfer reactions with Ar+ ions they are caused by a low electron density in the plasma. The experimental ‘excitation temperatures’ follow a pattern predicted by computer simulations with a collisional-radiative model: they are lower than the actual electron temperature, while this deviation is greater for the Me I system than Me II.

Building Materials as Potential Emission Sources of VOC in the Indoor Environment of Buildings

People spend most of their time in various indoor spaces and their health is exposed to different kinds of air pollutants. Volatile organic compounds (VOCs) belong to a group of chemical substances polluting the indoor environment. They come into the interior of buildings mainly from internal sources in the form of building materials, flooring, composite wood products, adhesives and other consumer products. Their presence in indoor air is monitored, due to their carcinogenic and mutagenic effects on human health. Many studies of indoor environment contaminated by VOC have been published during the last years. The present study provides general overview of the occurrence and emission sources of VOCs in the indoor environment of different types of buildings. The most frequently monitored indoor organic pollutants in terms of their occurrence and health risk are BTEX (benzene, toluene, ethylbenzene and xylenes), terpenes (α-pinene and d-limonene) and aldehydes (formaldehyde, acetaldehyde and benzaldehyde). Their concentrations in different indoor environments are variable and depend on factors such as emission characteristics of sources, microclimatic and ventilation conditions. Formaldehyde and toluene levels increased significantly with increasing room temperature. Benzene enters the indoor environment of buildings from external sources, especially from traffic or industrial areas. Formaldehyde, α-pinene and d-limonene originate from indoor sources as a part of building materials, furniture and household products.