Statistical modeling of O3, NOx, CO, PM2.5, VOCs and noise levels in commercial complex and associated health risk assessment in an academic institution

Emission characteristics of volatile organic compounds from consumer spray products based on product type, spray method, and distance

Consumer spray products (CSPs) are widely used in daily life, yet it is challenging to find products that fully disclose all components posing health risks. Existing studies primarily focus on product components or VOC quantities emitted during use. Therefore, this study aimed to measure the VOC concentrations emitted by CSPs at varying distances. 47 CSPs available in the Korean market were selected, spanning three spray groups: antiseptics/insecticides (11), aromatic deodorants (16), and coating/polishing agents (20). VOC in air samples were collected using Tenax TA tube at a distance of 1 and 3 m from the sprayed CSPs and then analyzed by thermal desorption-gas chromatography-mass spectrometry system. Discrepancies were found between labeled and actual product components. Aromatic deodorants exhibited the highest total VOCs (TVOCs), while antiseptic/insecticide sprays exhibited the lowest. In the antiseptic/insecticide group and coating/polishing agent group, benzene as a propellant had a maximum concentration (30.9 ± 25.6 ppb), and as trigger, its concentration was 33.7 ± 30.7 ppb. Quantitative analysis using advanced analytical instruments only explained 26.1 ± 20.4% of toluene-equivalent TVOCs, suggesting the presence of additional substances. Concentrations varied by distance due to substance volatility and usage. Maintaining a distance of at least 1 m from CSPs is recommended.

Effects of massive desiccation of olive waste residues on air quality

New industries are proliferating in the recovery of agri-food wastes, such as those involved in the revaluation of alperujo, generated in the production of olive oil. Despite the potential environmental benefits, their activity is not exempt from new forms of emissions, aggravated by the massification of waste treatments. This work reports a six-month field campaign carried out in an alperujo desiccation plant which can serve as a proxy for these emerging industries in the Mediterranean countries. The study focused on air quality parameters, covering criteria pollutants, metals and microbiological load of particulate matter and the characterization of volatile organic compounds (VOCs). The results show a slight contribution of the factory to the NOx levels in the surroundings (3.0-12.5 μg/m3). Statistically significant effects were not observed for ozone, CO, SO2, or PM10. Concerning the levels of metals, concentrations were low and calculated health risk indexes indicated safe conditions in the area. The most abundant elements were Na (6.5 × 102 ng/m3), K (4.0 × 102 ng/m3), Al (2.7 × 102 ng/m3), Zn (2.1 × 102 ng/m3), Ca (2.16 × 102 ng/m3), Fe (3.6 × 101 ng/m3) and Mg (3.2 × 101 ng/m3). Bacterial counts, with a mean value of 15.9 CFU/m3, showed a seasonal shift, mainly explained by weather (air moisture and temperature) and PM2.5 concentration. The genomic analysis showed Cutibacterium as the dominant genus during the cold months while Bacillus predominated in the warm season. The VOCs with higher average concentrations were acetic acid (130 μg/m3), nonanoic acid (124 μg/m3), benzoic acid (29.7 μg/m3), octanoic acid (19.9 μg/m3) and nonanal (4.70 μg/m3), with the rest of compounds in concentrations below 4 μg/m3. Odorant pollutants with the greatest contribution to olfactory nuisance were aldehydes (from pentanaldehyde to decanaldehyde), acetic acid and phenol. Although the observable effects of the waste treatments were low, several parameters showed an influence on the environment which should be assessed to foresee and prevent long-term consequences.

New Methodology to Evaluate and Optimize Indoor Ventilation Based on Rapid Response Sensors

The recent pandemic increased attention to the need for appropriated ventilation and good air quality as efficient measures to achieve safe and healthy indoor air. This work provides a novel methodology for continuously evaluating ventilation in public areas using modern rapid response sensors (RRS). This methodology innovatively assesses the ventilation of a space by combining a quantitative estimation of the real air exchange in the space-obtained from CO2 experimental RRS measurements and the characteristics of and activity in the space-and indoor and outdoor RRS measurements of other pollutants, with healthy recommendations from different organisations. The methodology allows space managers to easily evaluate, in a continuous form, the appropriateness of their ventilation strategy, thanks to modern RRS measurements and direct calculations (implemented here in a web app), even in situations of full activity. The methodology improves on the existing standards, which imply the release of tracer gases and expert intervention, and could also be used to set a control system that measures continuously and adapts the ventilation to changes in indoor occupancy and activity, guaranteeing safe and healthy air in an energy-efficient way. Sample public concurrence spaces with different conditions are used to illustrate the methodology.

Promotion of SO2 resistance of Ce-La/TiO2 denitrification catalysts by V doping

Conventional cerium-based denitrification catalysts show good catalytic activity at moderate and high temperatures, but their denitrification performance may be decreased due to poisoning by SO2 in the flue gas. In this paper, V was introduced into Ce-La/TiO2 catalysts by a ball-milling method, and the effects of the V content on catalyst denitrification performance and SO2 resistance were investigated. Fourier-transform diffuse reflectance in situ infrared spectroscopy was used to examine the denitrification mechanism and evaluate the catalysts for surface acidity, redox characteristics, and SO2 adsorption. After introducing V, Brønsted acids played the dominant role in the catalytic reaction by increasing the number of acidic sites on the catalyst surface, adsorbing NH3 to participate in the reaction, and improving the sulfur resistance by inhibiting SO2 poisoning. The Ce3+ and O ratio on the catalyst surface were also enhanced by V doping, which reduced interactions between SO2 and the primary metal oxide active ingredients. The modified catalyst inhibited the formation of sulfate species on the catalyst surface and prevented the generation of additional nitrate species on the surface, which protected the main active sites. After V doping, the NH3-SCR reaction on the catalyst surface followed the Langmuir-Hinshelwood mechanism.

Indoor Volatile Organic Compounds: Concentration Characteristics and Health Risk Analysis on a University Campus

Volatile organic compounds (VOCs) are major indoor air pollutants that contain several toxic substances. However, there are few studies on health risk assessments of indoor VOCs in China. This study aimed to determine the concentration characteristics of VOCs on college campuses by collecting VOC samples from different locations on campus during different seasons combined with the exposure times of college students in each location obtained from a questionnaire survey to assess the possible health risks. The highest total VOC concentration (254 ± 101 µg/m³) was in the dormitory. The seasonal variation of TVOC concentrations was related to the variation of emission sources in addition to temperature. Health risk assessments of VOCs were evaluated using non-carcinogenic and carcinogenic risk values, represented by hazard quotient (HQ) and lifetime cancer risk (LCR), respectively. The non-carcinogenic risks at all sampling sites were within the safe range (HQ < 1). Dormitories had the highest carcinogenic risk, whereas the carcinogenic risk in the other three places was low (with LCR < 1.0 × 10^-6). Moreover, 1,2-dichloroethane was identified as a possible carcinogenic risk substance in the dormitory due to its high LCR (1.95 × 10^-6). This study provides basic data on health risks in different locations on campus and a basis for formulating measures to improve people's living environments.

A systematic review on mitigation of common indoor air pollutants using plant-based methods: a phytoremediation approach

Environmental pollution, especially indoor air pollution, has become a global issue and affects nearly all domains of life. Being both natural and anthropogenic substances, indoor air pollutants lead to the deterioration of the ecosystem and have a negative impact on human health. Cost-effective plant-based approaches can help to improve indoor air quality (IAQ), regulate temperature, and protect humans from potential health risks. Thus, in this review, we have highlighted the common indoor air pollutants and their mitigation through plant-based approaches. Potted plants, green walls, and their combination with bio-filtration are such emerging approaches that can efficiently purify the indoor air. Moreover, we have discussed the pathways or mechanisms of phytoremediation, which involve the aerial parts of the plants (phyllosphere), growth media, and roots along with their associated microorganisms (rhizosphere). In conclusion, plants and their associated microbial communities can be key solutions for reducing indoor air pollution. However, there is a dire need to explore advanced omics technologies to get in-depth knowledge of the molecular mechanisms associated with plant-based reduction of indoor air pollutants.

Substantial Changes in Selected Volatile Organic Compounds (VOCs) and Associations with Health Risk Assessments in Industrial Areas during the COVID-19 Pandemic

During the COVID-19 pandemic, governments in many countries worldwide, including India, imposed several restriction measures, including lockdowns, to prevent the spread of the infection. COVID-19 lockdowns led to a reduction in gaseous and particulate pollutants in ambient air. In the present study, we investigated the substantial changes in selected volatile organic compounds (VOCs) after the outbreak of the coronavirus pandemic and associations with health risk assessments in industrial areas. VOC data from 1 January 2019 to 31 December 2021 were collected from the Central Pollution Control Board (CPCB) website, to identify percentage changes in VOC levels before, during, and after COVID-19. The mean TVOC levels at all monitoring stations were 47.22 ± 30.15, 37.19 ± 37.19, and 32.81 ± 32.81 µg/m³ for 2019, 2020, and 2021, respectively. As a result, the TVOC levels gradually declined in consecutive years due to the pandemic in India. The mean TVOC levels at all monitoring stations declined from 9 to 61% during the pandemic period as compared with the pre-pandemic period. In the current study, the T/B ratio values ranged from 2.16 (PG) to 26.38 (NL), which indicated that the major pollutant contributors were traffic and non-traffic sources during the pre-pandemic period. The present findings indicated that TVOC levels had positive but low correlations with SR, BP, RF, and WD, with correlation coefficients (r) of 0.034, 0.118, 0.012, and 0.007, respectively, whereas negative correlations were observed with AT and WS, with correlation coefficients (r) of -0.168 and -0.150, respectively. The lifetime cancer risk (LCR) value for benzene was reported to be higher in children, followed by females and males, for the pre-pandemic, pandemic, and post-pandemic periods. A nationwide scale-up of this study's findings might be useful in formulating future air pollution reduction policies associated with a reduction in health risk factors. Furthermore, the present study provides baseline data for future studies on the impacts of anthropogenic activities on the air quality of a region.

Statistical analysis, source apportionment, and toxicity of particulate- and gaseous-phase PAHs in the urban atmosphere

Introduction

The concentrations of particulate and gaseous Polycyclic Hydrocarbons Carbon (PAHs) were determined in the urban atmosphere of Delhi in different seasons (winter, summer, and monsoon).

Methodology

The samples were collected using instrument air metric (particulate phase) and charcoal tube (gaseous phase) and analyzed through Gas chromatography. The principal component and correlation were used to identify the sources of particulate and gaseous PAHs during different seasons.

Results and discussion

The mean concentration of the sum of total PAHs (TPAHs) for particulate and gaseous phases at all the sites were found to be higher in the winter season (165.14 ± 50.44 ng/m3 and 65.73 ± 16.84 ng/m3) than in the summer season (134.08 ± 35.0 ng/m3 and 43.43 ± 9.59 ng/m3), whereas in the monsoon season the concentration was least (68.15 ± 18.25 ng/m3 and 37.63 1 13.62 ng/m3). The principal component analysis (PCA) results revealed that seasonal variations of PAHs accounted for over 86.9%, 84.5%, and 94.5% for the summer, monsoon, and winter seasons, respectively. The strong and positive correlation coefficients were observed between B(ghi)P and DahA (0.922), B(a)P and IcdP (0.857), and B(a)P and DahA (0.821), which indicated the common source emissions of PAHs. In addition to this, the correlation between Nap and Flu, Flu and Flt, B(a)P, and IcdP showed moderate to high correlation ranging from 0.68 to 0.75 for the particulate phase PAHs. The carcinogenic health risk values for gaseous and particulate phase PAHs at all sites were calculated to be 4.53 × 10-6, 2.36 × 10-5 for children, and 1.22 × 10-5, 6.35 × 10-5 for adults, respectively. The carcinogenic health risk for current results was found to be relatively higher than the prescribed standard of the Central Pollution Control Board, India (1.0 × 10-6).

Substantial changes in Gaseous pollutants and health effects during COVID-19 in Delhi, India

Background

Coronavirus disease has affected the entire population worldwide in terms of physical and environmental consequences. Therefore, the current study demonstrates the changes in the concentration of gaseous pollutants and their health effects during the COVID-19 pandemic in Delhi, the national capital city of India.

Methodology

In the present study, secondary data on gaseous pollutants such as nitrogen dioxide (NO₂), carbon monoxide (CO), sulfur dioxide (SO₂), ammonia (NH₃), and ozone (O₃) were collected from the Central Pollution Control Board (CPCB) on a daily basis. Data were collected from January 1, 2020, to September 30, 2020, to determine the relative changes (%) in gaseous pollutants for pre-lockdown, lockdown, and unlockdown stages of COVID-19.

Results

The current findings for gaseous pollutants reveal that concentration declined in the range of 51%-83% (NO), 40%-69% (NOx), 31%-60% (NO₂), and 25%-40% (NH₃) during the lockdown compared to pre-lockdown period, respectively. The drastic decrease in gaseous pollutants was observed due to restricted measures during lockdown periods. The level of ozone was observed to be higher during the lockdown periods as compared to the pre-lockdown period. These gaseous pollutants are linked between the health risk assessment and hazard identification for non-carcinogenic. However, in infants (0-1 yr), Health Quotient (HQ) for daily and annual groups was found to be higher than the rest of the exposed group (toddlers, children, and adults) in all the periods.

Conclusion

The air quality values for pre-lockdown were calculated to be "poor category to "very poor" category in all zones of Delhi, whereas, during the lockdown period, the air quality levels for all zones were calculated as "satisfactory," except for Northeast Delhi, which displayed the "moderate" category. The computed HQ for daily chronic exposure for each pollutant across the child and adult groups was more than 1 (HQ > 1), which indicated a high probability to induce adverse health outcomes.

Noise Exposure Assessment at a Secondary School in a City of Pulau Pinang, Malaysia

Schools are considered sensitive areas to noise pollution. The objective of this study is to ascertain the sound level in schools with respect to different sampling time sessions and sampling points. Five sampling points, consisting of two classrooms (Classroom A and Classroom B), a canteen, a staffroom and a field, were chosen to obtain an overview of the noise level within the whole school in three different time sessions (morning, afternoon and evening), as well as 8-h continuous sampling in both classrooms and the staffroom. The average noise level (L_Aeq,10min) obtained in this school was found to be in the range of 48.8 dBA to 83.7 dBA, where most of the values exceeded the permissible maximum sound pressure level set by the Malaysian Department of Environment (DOE). Classroom B recorded the highest average noise level (L_Aeq,8h) of 77.9 dBA, which exceeded the maximum value set by the Department of Environment.

The excellent photocatalytic NO removal performance relates to the synergistic effect between the prepositive NaOH solution and the g-C3N4 photocatalysis

Photocatalysis technology is used to remove the low concentration NO in recent years. However, the effect of this process is not very satisfactory. In this study, it was found that the prepositive NaOH solution could significantly improve the photocatalytic NO removal activity of g-C₃N₄. The apparent quantum yield of g-C₃N₄ in the NO removal process was increased 3.5 times by the prepositive NaOH solution. The reason is that there was a synergistic effect formed between the prepositive NaOH solution and the photocatalytic NO removal process. The prepositive NaOH solution not only could increase the humidity and pH value in the photocatalytic unit, but also could improve the adsorption ability of g-C₃N₄ for the H₂O, NO, and O₂. Moreover, the prepositive NaOH solution reduced the difficulty of the photogenerated carriers' transport and the ·OH generation. This study provided a new idea for the removal of low-concentration NOx.

Temporary reduction in VOCs associated with health risk during and after COVID-19 in Maharashtra, India

A novel coronavirus has affected almost all countries and impacted the economy, environment, and social life. The short-term impact on the environment and human health needs attention to correlate the Volatile organic compounds (VOCs) and health assessment for pre-, during, and post lockdowns. Therefore, the current study demonstrates VOC changes and their effect on air quality during the lockdown. The findings of result, the levels of the mean for total VOC concentrations were found to be 15.45 ± 21.07, 2.48 ± 1.61, 19.25 ± 28.91 µg/m³ for all monitoring stations for pre-, during, and post lockdown periods. The highest value of TVOCs was observed at Thane, considered an industrial region (petroleum refinery), and the lowest at Bandra, which was considered a residential region, respectively. The VOC levels drastically decreased by 52%, 89%, 80%, and 97% for benzene, toluene, ethylbenzene, and m-xylene, respectively, during the lockdown period compared to the previous year. In the present study, the T/B ratio was found lower in the lockdown period as compared to the pre-lockdown period. This can be attributed to the complete closure of non-traffic sources such as industries and factories during the lockdown. The Lifetime Cancer Risk values for all monitoring stations for benzene for pre-and-post lockdown periods were higher than the prescribed value, except during the lockdown period.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10874-022-09440-5.

Measurement and minutely-resolved source apportionment of ambient VOCs in a corridor city during 2019 China International Import Expo episode

In this study, real-time measurement of Volatile Organic Compounds (VOCs) was conducted at an urban site in Changzhou, a typical corridor city in the Yangtze River Delta (YRD) region in China, by Proton-Transfer-Reaction Time-of-Flight Mass Spectrometry (PTR-ToF-MS) during 2019 China International Import Expo (CIIE) episode. An improved method based on Air Quality Index (AQI) value is applied to identify polluted and clean periods. Diurnal pattern of VOC levels revealed elevated photochemical reactivity during polluted periods. Five VOC sources were identified by Positive Matrix Factorization (PMF) model, including secondary formation (22.71 ± 12.33%), biogenic (21.50% ± 11.76%), solvent usage (20.50 ± 10.07%), vehicle exhaust (18.32 ± 8.32%), and industrial process and fuel usage (16.96 ± 13.21%). The mean contribution of vehicular exhaust was 10.84% higher during the nighttime than the daytime under polluted days. The biogenic source contributed more during clean periods, while the secondary formation presented the opposite. Spatial analysis displayed that the VOC concentration was higher in the S and SSE. In terms of the regional transport, short-distance air masses from the northeast and the south within the YRD region led to high VOC levels and biogenic VOC derived from the ocean might affect the entire region. Stringent emission control policies enforced over the YRD for 2019 CIIE provided an excellent opportunity to determine the source-receptor response. As joint control area, the VOC level of Changzhou exhibited a substantial reduction and the VOC amounts emitted by solvent usage showed the biggest decrease (-58%). The findings of this study highlight the superiority of high time-resolved data in identifying the dynamic variation pattern (with the change of time and wind) of VOC levels and emission intensities.

A wavelet-based random forest approach for indoor BTEX spatiotemporal modeling and health risk assessment

This study reports on BTEX concentrations in one of the largest parking garages in Iran with a peak traffic flow reaching up to ~9300 vehicles in the last few days of the Nowruz holidays. Samples were obtained on different days of the week at three main locations in the Zaer Parking Garage. A novel wavelet-based random forest model (WRF) was trained to estimate BTEX concentrations by decomposing temperature, day of the week, sampling location, and relative humidity data with a maximal overlap discrete wavelet transform (MODWT) function and subsequently inputted into the WRF model. The results suggested that the WRF model can reasonably estimate BTEX trends and variations based on high R2 values of 0.96, 0.95, and 0.98 for training, validation, and test data subsets, respectively. The carcinogenic (LTCR) and non-carcinogenic health risk (HI) assessment results indicated a definite carcinogenic risk of benzene (LTCR = 2.22 × 10-4) and high non-carcinogenic risk (HI = 4.51) of BTEX emissions. The results of this study point to the importance of BTEX accumulation in poorly ventilated areas and the utility of machine learning in forecasting air pollution in diverse airsheds such as parking garages.

A state-of-the-art review on indoor air pollution and strategies for indoor air pollution control

Indoor air pollution has traditionally received less attention than outdoors pollution despite indoors pollutant levels are typically twice higher, and people spend 80-90% of their life in increasing air-tight buildings. More than 5 million people die every year prematurely from illnesses attributable to poor indoor air quality, which also causes multi-millionaire losses due to reduced employee's productivity, material damages and increased health system expenses. Indoor air pollutants include particulate matter, biological pollutants and over 400 different chemical organic and inorganic compounds, whose concentrations are governed by several outdoor and indoor factors. Prevention of pollutant is not always technically feasible, so the implementation of cost-effective active abatement units is required. Up to date no single physical-chemical technology is capable of coping with all indoor air pollutants in a cost-effective manner. This problem requires the use of sequential technology configurations at the expenses of superior capital and operating costs. In addition, the performance of conventional physical-chemical technologies is still limited by the low concentrations, the diversity and the variability of pollutants in indoor environments. In this context, biotechnologies have emerged as a cost-effective and sustainable platform capable of coping with these limitations based on the biocatalytic action of plants, bacteria, fungi and microalgae. Indeed, biological-based purification systems can improve the energy efficiency of buildings, while providing additional aesthetic and psychological benefits. This review critically assessed the state-of-the-art of the indoor air pollution problem and prevention strategies, along with the recent advances in physical-chemical and biological technologies for indoor pollutants abatement.

Atmospheric inverse estimates of CO emissions from Zhengzhou, China

Carbon monoxide (CO) is an important gas that affects human health and causes air pollution. However, the estimates of CO emissions in China are still subject to large uncertainties. Based on the CO mass concentration and the coupled Weather Research and Forecast (WRF) and Stochastic Time-Inverted Lagrangian Transport (STILT) model (WRF-STILT), this study estimates the CO emissions over Zhengzhou, China. The results show that the mean CO mass concentration was 1.17 mg m^-3 from November 2017 to February 2018, with a clear diurnal variation. There were two periods of rapidly increasing CO concentration in the diurnal variation, which are 06:00-09:00 and 16:00-20:00 local time. The footprint analysis shows that the observation site is highly influenced by local emissions. The most influential regions to the site observations are northeast and northwest Zhengzhou, which are associated with the geographical barrier of the Taihang Mountains in the north and narrow Fenwei Plain in the west. The inversion result shows that the actual emissions are lower than the inventory estimates. Using the optimal scaling factors, the WRF-STILT simulations of CO concentration agree closely with the CO measurements with the linear fitting regression equation y = 0.87x + 0.15. The slopes of the linear fitting regressions between the WRF-STILT-simulated CO concentrations determined using the optimal emissions and the observations range from 0.72 to 0.89 for four months, and all the fitting results passed the significance test (P < 0.001). These results indicate that the new optimal emissions derived with the scaling factors could better represent the real emission conditions than the a priori emissions if the WRF-STILT model is assumed to be reliable.

Assessment of noise pollution and associated subjective health complaints and psychological symptoms: analysis through structure equation model

Road traffic noise is affecting the exposed population through its detrimental effects. This study was conducted in urban zones of Peshawar, Khyber Pakhtunkhwa, Pakistan, to analyze causal relationship between noise and subjective health complaints with a special focus on psychological symptoms. A 12-h (LAeq) noise survey conducted at different locations (n = 57) indicated a noise range of 46.3-86.3 dB (A). A questionnaire survey was conducted from local residents (n = 500), students (n = 500), policemen (n = 500), shopkeepers (n = 500), and drivers (n = 500) exposed to road traffic noise and analyzed through structure equation modeling (SEM). Different models were prepared and a modified model obtained the acceptable model fit, i.e., chi-square 0.093, χ²/df 1.286, comparative fit index 0.986, goodness of fit index 0.966, normed fit index 0.943, Tucker-Lewis index 0.977, and root mean square error of approximation 0.034. The modified model gives not only the information about direct but also indirect effects of noise on the exposed population. Adding on, the model clearly indicates that sensitivity to noise has strong relationship with subjective health complaints (headache, exhaustion, and psychological symptoms such as annoyance, difficulty concentrating, ill temper, and anxiety) than profession, age, location, and gender. Duration of exposure to road traffic noise has an important role in increasing the frequency of subjective health issues. The model is important in depicting that sensitivity to noise may produce subjective health complaints (standardized parameter estimates of 0.12 and 0.29) but the mediator has much stronger positive path estimates (0.59). The modified model sought to discover and explicate the underlying mechanism of an observed relationship existing between the selected dependent and an independent variable through the identification of the mediator variables.

Simultaneous removal of SO2 and NO by FeII(EDTA) solution: promotion of Mn powder and mechanism of reduction

The effect of Mn powder addition on the simultaneous removal of SO₂ and NO coupled with Fe^II(EDTA) absorption was investigated in this work. In the NO absorption system with Fe^II(EDTA), SO₂ reduced Fe^II(EDTA)-NO to Fe^II(EDTA) with a reduction efficiency reaching 88.5% under the conditions of 4000 mg/m³ SO₂, pH 8.0, 44 °C, and the flow rate of 1.2 L/min within 60 min. Introducing 0.1 M Mn powder with SO₂ increased the Fe^II(EDTA)-NO reduction efficiency to 96.8% within 5 min. SO₂ was also removed by reducing Fe^II(EDTA)-NO and converted into SO₄^2- at a removal efficiency of 100%. After adding Mn powder, NO was removed through the following reaction: [Formula: see text]. Mn powder functioned as a reductant to regenerate the absorption of solution, and the coordinated NO in Fe^II(EDTA)-NO was reduced to NH₄⁺. The resource utilization rate of N reached approximately 77.2%. The integrated technology is a potential solution for flue gas treatment in industrial sectors with coal-fired power plants and industrial boiler. Graphical abstract.

Indoor Air-Quality Data-Monitoring System: Long-Term Monitoring Benefits

Indoor air pollution has been ranked among the top five environmental risks to public health. Indoor Air Quality (IAQ) is proven to have significant impacts on people’s comfort, health, and performance. Through a systematic literature review in the area of IAQ, two gaps have been identified by this study: short-term monitoring bias and IAQ data-monitoring solution challenges. The study addresses those gaps by proposing an Internet of Things (IoT) and Distributed Ledger Technologies (DLT)-based IAQ data-monitoring system. The developed data-monitoring solution allows for the possibility of low-cost, long-term, real-time, and summarized IAQ information benefiting all stakeholders contributing to define a rich context for Industry 4.0. The solution helps the penetration of Industrial Internet of Things (IIoT)-based monitoring strategies in the specific case of Occupational Safety Health (OSH). The study discussed the corresponding benefits OSH regulation, IAQ managerial, and transparency perspectives based on two case studies conducted in Spain.

Urban VOC profiles, possible sources, and its role in ozone formation for a summer campaign over Xi'an, China

To insight the urban volatile organic compound (VOC) profiles and its contribution to ozone, four-time per day (8:00-9:00, 15:00-16:00, 19:00-20:00, and 23:00-24:00) off-line VOC samples were collected from 16th July to 28th July 2018 for a summer investigation campaign over Xi'an, China. The diurnal variation was significant that the lowest TVOC concentrations were observed in the midnight period (28.4 ± 25.6 ppbv) while the highest was shown in the morning (49.6 ± 40.1 ppbv). The differences of total non-methane VOCs (TVOCs) between weekdays and weekend were also significant that the weekend showed significantly high VOC levels than weekdays (p < 0.05) but did not lead to significant ambient O₃ increase (p > 0.05). Isopentane, a general marker for vehicle exhaust, showed descending concentrations from morning to midnight and good correlation with vehicle numbers on road, indicating a potential source to the VOCs at this site. The results from PMF proved that vehicular exhaust was the largest source to the VOCs in this study (64.4%). VOC categories showed a reverse sequence in abundance of concentrations and OFP contributions that alkenes showed the highest OFPs although with the lowest abundance in TOVCs due to their high reactivity in photochemical reactions. High OFPs from ethylene and isopentane indicated that vehicular emissions could be the largest potential OFP source in this site. OFPs from isoprene (from 1.85 to 13.4 ppbv) indicated that biogenic VOCs should not be negligible in urban Xi'an city when controlling O₃ pollutants. Comparison of two OFP methods was conducted and MIR method was proved to be more reasonable and scientific in summer Xi'an. Therefore, vehicular emission, the largest contributor to ambient VOCs and also OFPs, as well as biological source should be priority controlled in guiding VOC emissions and reducing O₃ control policies.

Land Use Regression models for 60 volatile organic compounds: Comparing Google Point of Interest (POI) and city permit data

Land Use Regression (LUR) models of Volatile Organic Compounds (VOC) normally focus on land use (e.g., industrial area) or transportation facilities (e.g., roadway); here, we incorporate area sources (e.g., gas stations) from city permitting data and Google Point of Interest (POI) data to compare model performance. We used measurements from 50 community-based sampling locations (2013-2015) in Minneapolis, MN, USA to develop LUR models for 60 VOCs. We used three sets of independent variables: (1) base-case models with land use and transportation variables, (2) models that add area source variables from local business permit data, and (3) models that use Google POI data for area sources. The models with Google POI data performed best; for example, the total VOC (TVOC) model has better goodness-of-fit (adj-R²: 0.56; Root Mean Square Error [RMSE]: 0.32 μg/m³) as compared to the permit data model (0.42; 0.37) and the base-case model (0.26; 0.41). Area source variables were selected in over two thirds of models among the 60 VOCs at small-scale buffer sizes (e.g., 25 m-500 m). Our work suggests that VOC LUR models can be developed using community-based sampling and that models improve by including area sources as measured by business permit and Google POI data.

Species and release characteristics of VOCs in furniture coating process

Volatile organic compounds (VOCs) are an important factor affecting ambient air quality, and furniture production is one of the important sources of VOC pollution. High VOC concentrations have adverse effects on the environment and worker welfare in furniture factories. In order to control VOC emissions in a furniture workshop, the VOC species and concentration distributions were examined. Qualitative analysis of VOC species was carried out by headspace gas chromatography/mass spectrometry. The results showed that VOCs from a furniture workshop were mainly 12 substances including acetate, toluene, and xylene compounds. The heights and representative positions of VOCs released during the coating process were determined, and the results showed that VOC concentrations depended on environmental and height factors. The concentration of VOCs decreased with increasing altitude and reached a maximum concentration at 0.4 m above the ground. Because the concentration of VOCs varied with temperature, humidity, air pressure, and amount of spray paint, this paper established functional relationships between VOC concentrations and temperature, humidity, air pressure, and amount of spray paint. These results provide a theoretical basis for furniture workshops to automatically monitor and control VOCs. MAIN FINDING OF THIS WORK: VOCs from the furniture workshop were mainly composed of 10 substances including acetate, toluene, and xylene compounds.

Modeling of CO Emissions from Traffic Vehicles Using Artificial Neural Networks

Traffic emissions are considered one of the leading causes of environmental impact in megacities and their dangerous effects on human health. This paper presents a hybrid model based on data mining and GIS models designed to predict vehicular Carbon Monoxide (CO) emitted from traffic on the New Klang Valley Expressway, Malaysia. The hybrid model was developed based on the integration of GIS and the optimized Artificial Neural Network algorithm that combined with the Correlation based Feature Selection (CFS) algorithm to predict the daily vehicular CO emissions and generate prediction maps at a microscale level in a small urban area by using a field survey and open source data, which are the main contributions to this paper. The other contribution is related to the case study, which represents the spatial and quantitative variations in the vehicular CO emissions between toll plaza areas and road networks. The proposed hybrid model consists of three steps: the first step is the implementation of the correlation-based Feature Selection model to select the best model’s predictors; the second step is the prediction of vehicular CO by using a multilayer perceptron neural network model; and the third step is the creation of micro scale prediction maps. The model was developed using six traffic CO predictors: number of vehicles, number of heavy vehicles, number of motorbikes, temperature, wind speed and a digital surface model. The network architecture and its hyperparameters were optimized through a grid search approach. The traffic CO concentrations were observed at 15-min intervals on weekends and weekdays, four times per day. The results showed that the developed model had achieved validation accuracy of 80.6 %. Overall, the developed models are found to be promising tools for vehicular CO simulations in highly congested areas.

Characterization of BTEX group of VOCs and inhalation risks in indoor microenvironments at small enterprises

Concentrations of BTEX group (benzene, toluene, ethylbenzene and xylene) were measured in indoor and outdoor environments at four printing shops and two photocopy centers in Sakaka city, KSA. Fifty four BTEX samples were collected using passive diffusion monitors (SKC VOC 575) and analyzed by GC-MS. The results showed that toluene was the most prevailing compound within the BTEX group and its indoor levels were much higher than outdoor. The average indoor concentrations (μg/m³) ranged from 2.45 to 14.66, 81.59 to 955.65, 11.19 to 97.35, 35.66 to 291.88 and 3.90 to 28.39 for benzene, toluene, ethylbenzene, m/p-xylene and o-xylene, respectively. The indoor/outdoor ratios of concentrations of BTEX species were more than one in most cases, indicating the effect of indoor emission sources. Based on (Toluene/Benzene) ratios, all sites were affected by the traffic emissions. Ventilation efficiency, ink type and outdoor pollutant concentration are responsible for results disparity. Cancer and non-cancer risks were assessed in the indoor environments by calculating the lifetime cancer risk (LCR) and hazard ratio (HR), respectively. For benzene and ethylbenzene measured concentrations, LCR values were more than the acceptable USEPA risk level of 1 × 10^-6. HR values for BTEX species were in general lower than the threshold limit of one.

Vehicular CO Emission Prediction Using Support Vector Regression Model and GIS

Transportation infrastructures play a significant role in the economy as they provide accessibility services to people. Infrastructures such as highways, road networks, and toll plazas are rapidly growing based on changes in transportation modes, which consequently create congestions near toll plaza areas and intersections. These congestions exert negative impacts on human health and the environment because vehicular emissions are considered as the main source of air pollution in urban areas and can cause respiratory and cardiovascular diseases and cancer. In this study, we developed a hybrid model based on the integration of three models, correlation-based feature selection (CFS), support vector regression (SVR), and GIS, to predict vehicular emissions at specific times and locations on roads at microscale levels in an urban areas of Kuala Lumpur, Malaysia. The proposed model comprises three simulation steps: first, the selection of the best predictors based on CFS; second, the prediction of vehicular carbon monoxide (CO) emissions using SVR; and third, the spatial simulation based on maps by using GIS. The proposed model was developed with seven road traffic CO predictors selected via CFS (sum of vehicles, sum of heavy vehicles, heavy vehicle ratio, sum of motorbikes, temperature, wind speed, and elevation). Spatial prediction was conducted based on GIS modelling. The vehicular CO emissions were measured continuously at 15 min intervals (recording 15 min averages) during weekends and weekdays twice per day (daytime, evening-time). The model’s results achieved a validation accuracy of 80.6%, correlation coefficient of 0.9734, mean absolute error of 1.3172 ppm and root mean square error of 2.156 ppm. In addition, the most appropriate parameters of the prediction model were selected based on the CFS model. Overall, the proposed model is a promising tool for traffic CO assessment on roads.

Risk assessment of occupational exposure to benzene using numerical simulation in a complex geometry of a reforming unit of petroleum refinery

There has been an increasing concern about the continuous and the sudden release of volatile organic pollutants from petroleum refineries and occupational and environmental exposures. Benzene is one of the most prevalent volatile compounds, and it has been addressed by many authors for its potential toxicity in occupational and environmental settings. Due to the complexities of sampling and analysis of benzene in routine and accidental situations, a reliable estimation of the benzene concentration in the outdoor setting of refinery using a computational fluid dynamics (CFD) could be instrumental for risk assessment of occupational exposure. In the present work, a computational fluid dynamic model was applied for exposure risk assessment with consideration of benzene being released continuously from a reforming unit of a refinery. For simulation of benzene dispersion, GAMBIT, FLUENT, and CFD post software are used as preprocessing, processing, and post-processing, respectively. Computational fluid dynamic validation was carried out by comparing the computed data with the experimental measurements. Eventually, chronic daily intake and lifetime cancer risk for routine operations through the two seasons of a year are estimated through the simulation model. Root mean square errors are 0.19 and 0.17 for wind speed and concentration, respectively. Lifetime risk assessments of workers are 0.4-3.8 and 0.0096-0.25 per 1000 workers in stable and unstable atmospheric conditions, respectively. Exposure risk is unacceptable for the head of shift work, chief engineer, and general workers in 141 days (38.77%) in a year. The results of this study show that computational fluid dynamics is a useful tool for modeling of benzene exposure in a complex geometry and can be used to estimate lifetime risks of occupation groups in a refinery setting.

Distribution of VOCs in urban and rural atmospheres of subtropical India: Temporal variation, source attribution, ratios, OFP and risk assessment

This paper reports the first study which comprises the seasonal, diurnal variability, source characterization, ozone forming potential and risk assessment of volatile organic compounds (VOCs) at three sites (two urban and one rural) in the National Capital Territory of Delhi, India. The study was performed during three seasons of the year 2013-14 and two different categories of VOCs (aromatics and halogenated) have been selected. The study used the sampling and analytical procedures of NIOSH methods. Results showed that the mean concentration of sum of VOCs (∑VOC) is significantly higher at urban sites (110.0 and 137.4μg/m³ for JN and CP, respectively) as compared to the rural site, DP (56.5μg/m³). The contribution of individual to total VOC concentrations is noticed to be very similar at all the three sites. Most of the VOCs are observed to be significantly higher in winter followed by summer and autumn. Diurnal cycles of aromatic VOCs are highly influenced by the vehicular traffic and photochemical oxidations which showed higher and lower levels during morning/evening and daytime, respectively. Diagnostic ratios of the toluene/benzene (ranged from 0.65 to 13.9) infers the vehicular traffic might be the main contributing source in the urban sites while xylene/benzene ratio (ranged from 0.7 to 2.8) confirms the VOCs are transported to rural site from the nearby urban areas. Correlation and factor analysis suggested the sources are group of different species (traffic emissions, solvent usage and industrial) rather than single gas. The analysis of reactivity in terms of Prop-Equiv concentrations and ozone forming potential indicated that m/p-xylene and toluene are the main VOC contributing to the total ozone formation in urban and rural sites, respectively. Hazard ratios and lifetime cancer risk values exceeded the permissible standards established by USEPA and WHO suggests that the people are at significant risk.

Observations of atmospheric pollutants at Lhasa during 2014-2015: Pollution status and the influence of meteorological factors

Atmospheric pollutants including SO₂, NO₂, CO, O₃ and inhalable particulate matter (PM_2.5 and PM₁₀) were monitored continuously from March 2014 to February 2015 to investigate characteristics of air pollution at Lhasa, Tibetan Plateau. Species exhibited similar seasonal variations except O₃, with the peaks in winter but low valleys in summer. The maximum O₃ concentration was observed in spring, followed by summer, autumn, and winter. The positive correlation between O₃ and PM₁₀ in spring indicated similar sources of them, and was assumed to be turbulent transport. Temperature was the dominant meteorological factor for most species in spring. High temperature accelerates O₃ photochemistry, and favors air disturbance which is conductive to dust resuspension in spring. Relative humidity (RH) and atmospheric pressure were the main meteorological factors in summer. RH showed negative correlations with species, while atmospheric pressure posed opposite situation. Wind speed (WS) was the dominant meteorological factor in autumn, the negative correlations between WS and species indicated diffusion by wind. Most species showed non-significant correlations with meteorological factors in winter, indicating the dependence of pollution on source emission rather than restriction by meteorology. Pollution weather character indicated that emissions were from biomass burning and dust suspension, and meteorological factors also played an important role. Air stream injection from the stratosphere was observed during O₃ pollution period. Air parcels from Southwest Asia were observed during air pollution period in winter. An enhancement in air pollutants such as O₃ would be expected in the future, more attention should be given to countermeasures for prevention of air pollution in the future.

Environmental analysis of a potential district heating network powered by a large-scale cogeneration plant

Among the solutions for the achievement of environmental sustainability in the energy sector, district heating (DH) with combined heat and power (CHP) systems is increasingly being used. The Italian city of Turin is in a leading position in this field, having one of the largest DH networks in Europe. The aim of this work is the analysis of a further development of the network, addressed to reduce the presence of pollutants in a city that has long been subject to high concentration levels. The environmental compatibility of this intervention, especially in terms of nitrogen oxides (NO_x) and particulate matter (PM) emissions, is evaluated. The pollutants dispersion is estimated using the CALPUFF model. The forecasting scenario is created firstly by simulating the energy production of the main generation plants in response to the estimated heat demand, and secondly by investigating the amount and the dispersion of pollutants removed due to the elimination of the centralized residential heaters. The results show a future reduction in ground level average NO_x concentration ranging between 0.2 and 4 μg/m³. The concentration of PM remains almost unchanged. Measures are then taken to lower the uncertainty in the simulation scenarios. This study provides important information on the effects of a change of the energy configuration on air quality in an urban area. The proposed methodological approach is comprehensive and repeatable.