Study on Model of Indoor Air Pollution Forecast for Decoration Under Natural Ventilation Condition

To establish the model of indoor air pollution forecast for decoration. Methods The model was based on the balance model for diffusing mass. Results The data between testing concentration and estimating concentration were compared. The maximal error was less than 30% and average error was 14.6%. Conclusion The model can easily predict whether the pollution for decoration exceeds the standard and how long the room is decorated.

Natural Gas and Indoor Air Pollution: A Comparison With Coal Gas and Liquefied Petroleum Gas

Objective The study was designed to compare the combustion products of coal gas, liquefied petroleum gas and natural gas in relation to indoor air pollution. Methods Regular pollutants including B(a)P were monitored and 1-hydroxy pyrene were tested in urine of the enrolled subjects. Radon concentrations and their changes in four seasons were also monitored in the city natural gas from its source plant and transfer stations to final users. To analyze organic components of coal gas, liquefied petroleum gas and natural gas, a high-flow sampling device specially designed was used to collect their combustion products, and semi-volatile organic compounds contained in the particles were detected by gas chromatograph-mass spectrograph (GC/MS). Results Findings in the study showed that the regular indoor air pollutants particles and CO were all above the standard in winter when heating facilities were operated in the city, but they were lowest in kitchens using natural gas; furthermore, although NO2 and CO2 were slightly higher in natural gas, B(a)P concentration was lower in this group and 1-hydroxy pyrene was lowest in urine of the subjects exposed to natural gas. Organic compounds were more complicated in coal gas and liquefied petroleum gas than in natural gas. The concentration of radon in natural gas accounted for less than 1‰ of its effective dose contributing to indoor air pollution in Beijing households. Conclusion Compared to traditional fuels, gases are deemed as clean ones, and natural gas is shown to be cleaner than the other two gases.

Effectiveness of Improved Cookstoves to Reduce Indoor Air Pollution in Developing Countries. The Case of the Cassamance Natural Subregion, Western Africa

The Spanish NGO “Alianza por la Solidaridad” has installed improved cookstoves in 3000 households during 2012 and 2013 to improve energy efficiency reducing fuelwood consumption and to improve indoor air quality. The type of cookstoves were Noflaye Jeeg and Noflaye Jaboot and were installed in the Cassamance Natural Subregion covering part of Senegal, The Gambia and Guinea-Bissau. The Technical University of Madrid (UPM) has conducted a field study on a sample of these households to assess the effect of improved cookstoves on kitchen air quality. Measurements of carbon monoxide (CO) and fine particle matter (PM2.5) were taken for 24-hr period before and after the installation of improved cookstoves. The 24-hr mean CO concentrations were lower than the World Health Organization (WHO) guidelines for Guinea-Bissau but higher for Senegal and Gambia, even after the installation of improved cookstoves. As for PM2.5 concentrations, 24-hr mean were always higher than these guidelines. However, improved cookstoves produced significant reductions on 24-hr mean CO and PM2.5 concentrations in Senegal and for mean and maximum PM2.5 concentration on Gambia. Although this variability needs to be explained by further research to determine which other factors could affect indoor air pollution, the study provided a better understanding of the problem and envisaged alternatives to be implemented in future phases of the NGO project.

Are children safe indoor from outdoor air pollution? A short review

Background: Air pollution is a serious threat to children health. Given that children spend over 80% of their time indoors, understanding transport of pollutants from outdoor to indoor environments is important for assessing the impact of exposure to outdoor pollution on children health. The most common advice given during a smoke pollution episode is to stay indoors. How well this works depends on how clean the indoor air is and how pollutants from outdoor air contribute to pollutants load in indoor air. Objective: To assess the amount of outdoor air pollution coming indoors threatening children health. Methods: A Medline/EMBASE search of scientific articles was performed to evaluate the indoor-to-outdoor (I/O) concentration ratios of two main pollutants: ultrafine particles (UFP) and ozone (O3). Result: Under infiltration condition, the highest I/O ratios (0.6 - 0.9) were usually observed for larger UFP (70 - 100 nm), while the lowest I/O ratios (0.1 - 0.4) occurred typically around 10 - 20 nm. O3 I/O ratios vary according to air exchange and may be 0.6 - 0.8 for interiors having a large volume exchange with outdoor air (i.e. open windows) and 0.3 - 0.4 with conventional air conditioning systems. Conclusions: In the absence of indoor sources or activities, indoor UFP particles originate from outdoors. O3 concentration indoors may reach concentration similar to outdoors. Environmental and energy policies must also explicitly account for all the impacts of fossil fuel combustion on child health and development.

Effectiveness of an Indoor Air Pollution (IAP) Intervention on Reducing IAP and Improving Women’s Health Status in Rural Areas of Gansu Province, China

Given the deleterious health effects associated with indoor air pollution (IAP), this study was conducted to evaluate an IAP intervention in rural areas in Gansu, one of the poorest provinces of China. We selected 371 rural households to take part in intervention measures including stove improvement and health education. Eight of 371 households were selected to conduct IAP sampling. Four hundred and thirteen women in these households completed a questionnaire and 49 women took part in lung function tests. After the intervention, PM4 levels reduced from 455 μg/m3 to 200 μg/m3 and CO reduced from 3.40 ppm to 2.90 ppm in indoor air. The percentage of predicted value of FEV1 and FVC improved to some degree after the intervention, but all the parameters of lung function assessment did not show a significant change. Prevalence rates of several symptoms associated with IAP significantly declined in the study population, compared with baseline levels. Intervention measures combining stove improvement with health education were effective in reducing IAP levels. Women’s health status, including eye and respiratory symptoms, also showed improvement. However, the effect on lung function was not apparent and warranted additional follow-up. Similarly, evaluation of the long term effects of the IAP intervention will require future studies.

Assessment of Health Effects Related to the Use of Biomass Fuel and Indoor Air Pollution in Kapkokwon Sub-Location, Bomet Country, Kenya

Biomass Fuel (BMF) refers to burned plant or animal material;wood, charcoal, dung and crop residues which account for more than half of domestic energy in most developing countries and for as much as 95% in low income countries. It is estimated that about 3 billion people in the world rely on biomass fuel for cooking, heating and lighting. The biomass fuel chain includes gathering, transportation, processing and combustion. These processes are predominantly managed by women where they work as gatherers, processors, carriers or transporters and also as end-users or cooks. Thus, they suffer health hazards at all stages of the biomass fuel chain. The main objective was to assess health effects related to the use of Biomass fuel and indoor air pollution in Kapkokwon Sub-location, Kericho County, Kenya from March to May, 2013. The study area was Kapkokwon sub location, Bomet County, Kenya. The study population was 202 households. Primary females of the household were the target group as they managed the biomass chain. A quantitative descriptive cross-sectional study design was adopted to assess the health effects associated to the use of biomass fuel and indoor air pollution. The research revealed that women suffer different type of physical ailments due to the biomass fuel chain. Physical exhaustion (86%), neck aches (78%), headaches (34%), knee aches (30%) and back aches (16%) were reported as the principal health effects associated with the third stage of the biomass fuel chain. Irritation of the mucus membrane of the eyes, nose and throat (100%), coughing (100%), burns (42%), shortness of breath (38%) and exacerbation of asthma (2%) were identified as principal health effects associated with the fourth stage of the biomass fuel chain (cooking). As a result of the detrimental impact of indoor air pollution (IAP) on health and mortality, many governments, non-governmental organization and international organizations should develop strategies aimed at reducing indoor air pollution. The strategies to include subsidization of cleaner fuel technologies, development, promotion and subsidization of improved cooking stoves, use of solar thermal cookers and solar hot water heaters, processing biomass fuel to make them cleaner, modifying user behavior and improved household design.

Use of Ventilation-Index in the Development of Exposure Model for Indoor Air Pollution—A Review

In indoor environment, emission factor of the cooking fuel plays a vital role in determining correlation between exposure assessment and health effects. Both indoor and outdoor air pollution exposures are widely influenced by the ventilation status. An optimum control of the air change rate has also significant impact on the exposure pattern. A number of studies revealed that the indoor particulates and gaseous exposures, resulting from the combustion of various cooking fuels, are associated with significant adverse health effects on pregnant mothers and new born babies. The impacts of ventilation status on air pollution exposure in households’ kitchens or living rooms have not been explored enough. Except a few studies with concrete rooms, especially in industries, no other studies have been established on the correlation between the ventilation index and air pollution exposure. The intent of this review is to discuss reported findings focused on the ventilation and exposure to air pollution. This will obviously help better understanding to modulate exposure profile in household condition using simple tool of ventilation measurement.

Impact of air pollution on urbanization:evidence at China’s city level

This paper investigates the effect and transmission mechanism of air pollution on urbanization based on data from China’s 107 cities during 2005–2018.In order to identify the impact of air pollution on China’s urbanization,we utilized night light data to represent the level of urbanization and used temperature inversion as an instrumental variable to mitigate endogeneity within the two-stage least squares framework.The results suggest that air pollution significantly slowed China’s urbanization process with economic growth acting as the transmission mechanism.The heterogeneity analyses revealed that air pollution had a greater negative impact on urbanization in northern regions than that in southern regions,and a greater negative impact in resource-oriented cities than that in non-resource-based cities.We also find that air pollution was to the detriment of urbanization in larger cities,which have more than 3 million residents,while it did not have a significant impact on Type II large cities,which have fewer than 3 million residents.

The Influence of Air Pollution Concentrations on Solar Irradiance Forecasting Using CNN-LSTM-mRMR Feature Extraction

Maintaining a steady power supply requires accurate forecasting of solar irradiance,since clean energy resources do not provide steady power.The existing forecasting studies have examined the limited effects of weather conditions on solar radiation such as temperature and precipitation utilizing convolutional neural network(CNN),but no comprehensive study has been conducted on concentrations of air pollutants along with weather conditions.This paper proposes a hybrid approach based on deep learning,expanding the feature set by adding new air pollution concentrations,and ranking these features to select and reduce their size to improve efficiency.In order to improve the accuracy of feature selection,a maximum-dependency and minimum-redundancy(mRMR)criterion is applied to the constructed feature space to identify and rank the features.The combination of air pollution data with weather conditions data has enabled the prediction of solar irradiance with a higher accuracy.An evaluation of the proposed approach is conducted in Istanbul over 12 months for 43791 discrete times,with the main purpose of analyzing air data,including particular matter(PM10 and PM25),carbon monoxide(CO),nitric oxide(NOX),nitrogen dioxide(NO_(2)),ozone(O₃),sulfur dioxide(SO_(2))using a CNN,a long short-term memory network(LSTM),and MRMR feature extraction.Compared with the benchmark models with root mean square error(RMSE)results of 76.2,60.3,41.3,32.4,there is a significant improvement with the RMSE result of 5.536.This hybrid model presented here offers high prediction accuracy,a wider feature set,and a novel approach based on air concentrations combined with weather conditions for solar irradiance prediction.

Ensemble Deep Learning Based Air Pollution Prediction for Sustainable Smart Cities

Big data and information and communication technologies can be important to the effectiveness of smart cities.Based on the maximal attention on smart city sustainability,developing data-driven smart cities is newly obtained attention as a vital technology for addressing sustainability problems.Real-time monitoring of pollution allows local authorities to analyze the present traffic condition of cities and make decisions.Relating to air pollution occurs a main environmental problem in smart city environments.The effect of the deep learning(DL)approach quickly increased and penetrated almost every domain,comprising air pollution forecast.Therefore,this article develops a new Coot Optimization Algorithm with an Ensemble Deep Learning based Air Pollution Prediction(COAEDL-APP)system for Sustainable Smart Cities.The projected COAEDL-APP algorithm accurately forecasts the presence of air quality in the sustainable smart city environment.To achieve this,the COAEDL-APP technique initially performs a linear scaling normalization(LSN)approach to pre-process the input data.For air quality prediction,an ensemble of three DL models has been involved,namely autoencoder(AE),long short-term memory(LSTM),and deep belief network(DBN).Furthermore,the COA-based hyperparameter tuning procedure can be designed to adjust the hyperparameter values of the DL models.The simulation outcome of the COAEDL-APP algorithm was tested on the air quality database,and the outcomes stated the improved performance of the COAEDL-APP algorithm over other existing systems with maximum accuracy of 98.34%.

Climate change,ambient air pollution,and students'mental health

The impact of global climate change and air pollution on mental health has become a crucial public health issue.Increased public awareness of health,advancements in medical diagnosis and treatment,the way media outlets report environmental changes and the variation in social resources affect psychological responses and adaptation methods to climate change and air pollution.In the context of climate change,extreme weather events seriously disrupt people's living environments,and unstable educational environments lead to an increase in mental health issues for students.Air pollution affects students'mental health by increasing the incidence of diseases while decreasing contact with nature,leading to problems such as anxiety,depression,and decreased cognitive function.We call for joint efforts to reduce pollutant emissions at the source,improve energy structures,strengthen environmental monitoring and governance,increase attention to the mental health issues of students,and help student groups build resilience;by establishing public policies,enhancing social support and adjusting lifestyles and habits,we can help students cope with the constantly changing environment and maintain a good level of mental health.Through these comprehensive measures,we can more effectively address the challenges of global climate change and air pollution and promote the achievement of the United Nations Sustainable Development Goals.

Analysis of Characteristics and Meteorological Influencing Factors of Air Pollution in Luojiang District,Deyang City

Based on the monitoring data of ambient air quality and meteorological observation data,the characteristics and meteorological influencing factors of air pollution in Luojiang District of Deyang City from 2018 to 2022 were analyzed.The results show that from 2018 to 2022,the main air pollutants affecting the air quality of Luojiang District of Deyang City were PM_(2.5) and PM_(10),and the primary pollutant on heavy pollution days was basically PM_(2.5).PM_(2.5) and PM_(10) pollution showed obvious seasonal differences,and PM_(2.5) concentration exceeded the limit mainly in spring and winter,among which it was the most serious in early spring,especially in January and February,followed by December.PM_(10) exceeding the standard had a high seasonal correlation with PM_(2.5) exceeding the standard,mainly in spring and winter,among which it was the most serious in winter,especially in December,followed by January.PM_(2.5) and PM_(10) pollution showed an overall weakening trend.PM_(2.5) and PM_(10) concentration were closely related to meteorological factors such as temperature,relative humidity,wind speed,precipitation and air pressure,and were mainly affected by rainfall.

Enhancing Patients Outcomes and Infection Control through Smart Indoor Air Quality Monitoring Systems

Air pollution poses a critical threat to public health and environmental sustainability globally, and Nigeria is no exception. Despite significant economic growth and urban development, Nigeria faces substantial air quality challenges, particularly in urban centers. While outdoor air pollution has received considerable attention, the issue of indoor air quality remains underexplored yet equally critical. This study aims to develop a reliable, cost-effective, and user-friendly solution for continuous monitoring and reporting of indoor air quality, accessible from anywhere via a web interface. Addressing the urgent need for effective indoor air quality monitoring in urban hospitals, the research focuses on designing and implementing a smart indoor air quality monitoring system using Arduino technology. Employing an Arduino Uno, ESP8266 Wi-Fi module, and MQ135 gas sensor, the system collects real-time air quality data, transmits it to the ThingSpeak cloud platform, and visualizes it through a user-friendly web interface. This project offers a cost-effective, portable, and reliable solution for monitoring indoor air quality, aiming to mitigate health risks and promote a healthier living environment.

Indoor Air Pollution and Its Determinants in Household Settings in Jaipur, India

Individuals spend 90% of their time indoors, primarily at home or at work. Indoor environmental factors have a significant impact on human well-being. It was a longitudinal study that assessed the major factors that reduce indoor air quality, namely particulate matter, and bio-aerosols, using low-cost sensors and the settle plate method, respectively also to determine the effect of atmospheric parameters and land use patterns in households of commercial, industrial, residential, slum, and rural areas of the city. PM2.5 concentration levels were similar in most parts of the day across all sites. PM10.0 concentration levels increased indoors in a commercial area. PM2.5 concentration showed a negative correlation with temperature and a positive correlation with relative humidity in some areas. Very high values of PM2.5 concentration and PM10.0 concentration have been observed in this study, inside households of selected rural and urban areas. Pathogenic gram-positive cocci, gram-positive rods, Aspergillus, and Mucor species were the most common bacterial and fungal species respectively found inside households. This study examined particulate matter concentration along with bio-aerosols, as very less studies have been conducted in Jaipur the capital of Rajasthan, a state in the western part of India which assessed both of these factors together to determine the indoor air quality. Rural households surrounding the periphery of the city were found to have similar pollution levels as urban households. So, this study may form the basis for reducing pollution inside households and also for taking suitable measures for the reduction of pollution in the indoor environment.

Comprehensive Review on Air Pollution Control Measures for Non-Attainment Cities of Uttar Pradesh, India

Introduction: The Indian state of Uttar Pradesh (UP) for the past many years has been reported to have many cities with highly polluted air quality. The state has been taking meticulous steps in combating air pollution in the form of action plans, introduced especially in its 17 non-attainment cities (NAC). To assess the progress and development of these action plans in UP, the present study has done an in-depth analysis and review of the state’s action plans and city micro action plans. Materials and Methods: In this research study, the analysis of the latest action plan reports, micro action plan reports as well as the recommendations for combating air pollution-related issues in the 17 NAC of the UP state has been well documented. Uttar Pradesh Pollution Control Board (UPPCB) has prepared these reports to highlight the progress of the plans in response to the growing air pollution in these cities. The information present in the reports has been used to further study sector-specific, category-specific action plans, institutional responsibility, and the present status of the action plans. Results: On average, the highest weightage in action plans was given to sector-specific categories such as Road dust and construction activities (24%). It was also observed that Urban local bodies (~50%) were majorly responsible to implement the action points and 56% of the action points were jointly implemented by multiple agencies.

Recent Progress in Atmospheric Chemistry Research in China: Establishing a Theoretical Framework for the “Air Pollution Complex”

Atmospheric chemistry research has been growing rapidly in China in the last 25 years since the concept of the“air pollution complex”was first proposed by Professor Xiaoyan TANG in 1997.For papers published in 2021 on air pollution(only papers included in the Web of Science Core Collection database were considered),more than 24000 papers were authored or co-authored by scientists working in China.In this paper,we review a limited number of representative and significant studies on atmospheric chemistry in China in the last few years,including studies on(1)sources and emission inventories,(2)atmospheric chemical processes,(3)interactions of air pollution with meteorology,weather and climate,(4)interactions between the biosphere and atmosphere,and(5)data assimilation.The intention was not to provide a complete review of all progress made in the last few years,but rather to serve as a starting point for learning more about atmospheric chemistry research in China.The advances reviewed in this paper have enabled a theoretical framework for the air pollution complex to be established,provided robust scientific support to highly successful air pollution control policies in China,and created great opportunities in education,training,and career development for many graduate students and young scientists.This paper further highlights that developing and low-income countries that are heavily affected by air pollution can benefit from these research advances,whilst at the same time acknowledging that many challenges and opportunities still remain in atmospheric chemistry research in China,to hopefully be addressed over the next few decades.

Type 2 diabetes and thyroid cancer:Synergized risk with rising air pollution

Diabetes is a complex condition,and the causes are still not fully understood.However,a growing body of evidence suggests that exposure to air pollution could be linked to an increased risk of diabetes.Specifically,exposure to certain pollutants,such as particulate Matter and Ozone,has been associated with higher rates of diabetes.At the same time,air pollution has also been linked to an increased risk of thyroid cancer.While there is less evidence linking air pollution to thyroid cancer than to diabetes,it is clear that air pollution could have severe implications for thyroid health.Air pollution could increase the risk of diabetes and thyroid cancer through several mechanisms.For example,air pollution could increase inflammation in the body,which is linked to an increased risk of diabetes and thyroid cancer.Air pollution could also increase oxidative stress,which is linked to an increased risk of diabetes and thyroid cancer.Additionally,air pollution could increase the risk of diabetes and thyroid cancer by affecting the endocrine system.This review explores the link between diabetes and air pollution on thyroid cancer.We will discuss the evidence for an association between air pollution exposure and diabetes and thyroid cancer,as well as the potential implications of air pollution for thyroid health.Given the connections between diabetes,air pollution,and thyroid cancer,it is essential to take preventive measures to reduce the risk of developing the condition.

Meteorological factors, ambient air pollution, and daily hospital admissions for depressive disorder in Harbin: A time-series study

BACKGROUND The literature has discussed the relationship between environmental factors and depressive disorders;however,the results are inconsistent in different studies and regions,as are the interaction effects between environmental factors.We hypo-thesized that meteorological factors and ambient air pollution individually affect and interact to affect depressive disorder morbidity.AIM To investigate the effects of meteorological factors and air pollution on depressive disorders,including their lagged effects and interactions.METHODS The samples were obtained from a class 3 hospital in Harbin,China.Daily hos-pital admission data for depressive disorders from January 1,2015 to December 31,2022 were obtained.Meteorological and air pollution data were also collected during the same period.Generalized additive models with quasi-Poisson regre-ssion were used for time-series modeling to measure the non-linear and delayed effects of environmental factors.We further incorporated each pair of environ-mental factors into a bivariate response surface model to examine the interaction effects on hospital admissions for depressive disorders.RESULTS Data for 2922 d were included in the study,with no missing values.The total number of depressive admissions was 83905.Medium to high correlations existed between environmental factors.Air temperature(AT)and wind speed(WS)significantly affected the number of admissions for depression.An extremely low temperature(-29.0℃)at lag 0 caused a 53%[relative risk(RR)=1.53,95%confidence interval(CI):1.23-1.89]increase in daily hospital admissions relative to the median temperature.Extremely low WSs(0.4 m/s)at lag 7 increased the number of admissions by 58%(RR=1.58,95%CI:1.07-2.31).In contrast,atmospheric pressure and relative humidity had smaller effects.Among the six air pollutants considered in the time-series model,nitrogen dioxide(NO_(2))was the only pollutant that showed significant effects over non-cumulative,cumulative,immediate,and lagged conditions.The cumulative effect of NO_(2) at lag 7 was 0.47%(RR=1.0047,95%CI:1.0024-1.0071).Interaction effects were found between AT and the five air pollutants,atmospheric temperature and the four air pollutants,WS and sulfur dioxide.CONCLUSION Meteorological factors and the air pollutant NO_(2) affect daily hospital admissions for depressive disorders,and interactions exist between meteorological factors and ambient air pollution.

Air Pollution, Global Warming and Difficulties to Replace Fossil Fuel with Renewable Energy

Since the Industrial Revolution, greenhouse gas (GHG) emissions have greatly increased with the increased use of fossil fuels, leading to air pollution and global warming. We present the researches on air pollution and the use of fossil fuels in north China, the economic zone of Changsha-Zhuzhou-Xiangtan and the economic zone of the Pearl River Delta region. Researches indicate that the use of fossil fuels has been the main source of air pollution in the three regions. We present researches on global mean surface temperature (GMST) with the rise of carbon dioxide concentration (CDC) and global fossil fuel consumption (GFFC);researches indicate that the rise in CDC can account for 91% of the rise in GMST, and GFFC can account for 90% of the rise in GMST. We analyse the factors that bring about air pollution and temperature rise, they are the use of fossil fuels and deforestation. It is critically important to replace fossil fuels with clean energy, but renewable energy has also disadvantages. The world faces difficulties in solving air pollution and global warming, so governments of the world should cooperate to solve the technologies of clean energy, and preserve the forests and the natural environment.

Green Walls as Mitigation of Urban Air Pollution:A Review of Their Effectiveness

Mitigation of urban air pollution has been constrained by the availability of urban spaces for greening.Green walls offer the prospect of greening spaces and surfaces without requiring large areas.Green walls can largely be divided into green facades where the aboveground parts of plants rooted in soil and pots grow directly on,and living walls holding bags,planter tiles,trays and vessels containing substrates in which plants are grown.Green facades and living walls can be continuous or modular with repeating units that can be assembled for extension.This review aims to pres­ent the effectiveness of green walls in removing different types of air pollutants in indoor and outdoor environments.It examined more than 45 peer-reviewed recently published scholarly articles to achieve the aim.It highlights that most of the studies on green walls focus on particulate matter removal and green walls could effectively remove particu­late matter though the effectiveness varies with plant types,air humidity,rainfall and its intensity,leaf area index and contact angle,green wall surface coverage ratio,as well as the height of green walls.Increasing the height of green walls and optimizing their distance from roadsides could promote the deposition of particulate matter.Washing off could regenerate plant surfaces for capturing pollutants.Green walls are also effective in removing NO2,O3,SO2 and CO.Indoor active living walls,when properly designed,could have air purifying performance comparable to a HVAC system.The performance of green walls could be optimized through polycultures,selection of plants,surface coverage and height,and air inflow.