Search

Sulfur trioxide (SO 3) is one of the major air pollutants in the flue gas of Fluid catalytic cracking (FCC) units during the regeneration process in refineries. However, it is difficult to remove SO 3 with the existing desulfurization systems. Nowadays, alkaline adsorbent spraying technology has been a promising method to remove SO 3. However, there is no relevant application research in the field of FCC regeneration flue gas. Therefore, in this paper, The SO 3 removal characteristics from FCC flue gas by activated carbon modified red mud adsorbent were studied, including modification method, reaction temperature and flue gas components. Combined with characterization analysis of adsorbents, the mechanism of SO 3 removal was studied. It was found that when the AC mass ratio is 10% and modification temperature is 400 ℃, the best LBRMAC adsorbent was achieved. When particle size is 0.096–0.125 mm and reaction temperature is 400 ℃, the highest SO 3 adsorption efficiency is up to 83.4%. The addition of NO has little influence on the adsorption efficiency of SO 3. The addition of SO 2 leads to competitive adsorption between SO 3 and SO 2 , resulting in a rapid decline in the removal efficiency of SO 3. Meanwhile, the characterization analysis proves that the SO 3 adsorption process mainly include chemical kinetics control stage and product layer diffusion stage. • Best modification of LBRMAC was achieved when the AC mass ratio is 10%. • Reaction temperature of 400 ℃ is optimal for SO 3 adsorption. • Particle size and SO 3 concentration have effects on SO 3 adsorption except NO. • There exists competitive adsorption between SO 2 and SO 3. • Chemical kinetics control stage and product layer diffusion stage mainly dominate SO 3 adsorption. [ABSTRACT FROM AUTHOR]

To meet the requirements of the update for the supersonic landing and take-off (LTO) cycle standard, a methodology for studying the LTO supersonic standard based on pollutant emission characteristics is proposed in this paper to analyze the thrust and time of the LTO. In this study, three distinct supersonic engine models were developed based on subsonic engine cores. Subsequently, the pollutant emission calculation models were developed to calculate the pollutant emission index (I e) of supersonic engines and analyze the pollutant emission characteristics. Findings confirmed the presence of a correlation between standard formulations and pollutant emissions. Finally, considering that the current LTO standard leads to excessive noise during the climb phase and inefficient combustion during the taxi/ground idle phase, the LTO supersonic standard was analyzed for the trade-off, which resulted in the more applicable and fairer standard being formulated. The results indicate that the LTO supersonic standard formulated in this paper proves to be more reasonable than the current LTO standard and accurately represents the pollutant emission characteristics of distinct supersonic engines during both the climb and taxi/ground idle phases. Consequently, this study's results have guiding significance for formulating the future LTO supersonic standard and predicting pollutant emissions from supersonic engines. • Outdated supersonic landing and take-off cycle standards are updated. • A trade-off analysis of the supersonic standard is developed. • More comprehensive supersonic engine models and supersonic emission calculation methods are developed. • The updated supersonic climb standard more closely approximates the emissions from the noise-reducing climb trajectory. • The updated supersonic taxi/ground idle standard is better able to meet the combustion efficiency requirements. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has reinforced an interest in the relationship between air pollution and respiratory viral infections, indicating that their burden can be increased under poor air quality. This paper reviews the pathways through which air pollutants can enhance susceptibility to such infections and aggravate their clinical course and outcome. It also summarizes the research exploring the links between various viral infections and exposure to solid and gaseous pollution in Poland, a region characterized by poor air quality, especially during a heating season. The majority of studies focused on concentrations of particulate matter (PM; 86.7%); the other pollutants, i.e., BaP, benzene, CO, NO x , O 3 , and SO 2, were studied less often and sometimes only in the context of a particular infection type. Most research concerned COVID-19, showing that elevated levels of PM and NO 2 correlated with higher morbidity and mortality, while increased PM 2.5 and benzo[a]pyrene levels were related to worse clinical course and outcome in hospitalized, regardless of age and dominant SARS-CoV-2 variant. PM 10 and PM 2.5 levels were also associated with the incidence of influenza-like illness and, along with NO 2 concentrations, with a higher rate of children's hospitalizations due to lower respiratory tract RSV infections. Higher levels of air pollutants also increased hospitalization due to bronchitis (PM, NO x , and O 3) and emergency department admission due to viral croup (PM 10 , PM 2.5 , NO x , CO, and benzene). Although the conducted studies imply only correlations and have other limitations, as discussed in the present paper, it appears that improving air quality through reducing combustion processes in energy production in Poland should be perceived as a part of multilayered protection measures against respiratory viral infections, decreasing the healthcare costs of COVID-19, lower tract RSV infections, influenza, and other respiratory viral diseases prevalent between autumn and early spring, in addition to other health and climate benefits. [Display omitted] • Polluted air may increase the severity of respiratory viral infections. • Poland is a PM and BaP pollution hot spot in Europe. • Air pollution is associated with a higher burden of respiratory viral infections. • Improving the air quality should be a protection measure against infections. • Further studies are encouraged to explore the relationships with other pathogens. [ABSTRACT FROM AUTHOR]

Docked vessels in ports can be one of the dirtiest emitters in terms of local air pollutants. This paper evaluates whether the regulation of Emission Control Areas in China reduces air pollutants emissions in port cities. The transboundary spillovers of air pollution, induced by meteorological conditions, results in air pollution concentrations at specific locations encompassing both locally generated pollutants and those originating from elsewhere. Therefore, it is challenging to discern the emission reduction effects of environmental regulatory policies through air pollutant monitoring concentrations. This paper develops an approach to isolate transboundary spillovers induced by the wind, estimate locally produced pollution, and utilize the concentrations of locally produced pollution to identify the treatment effects of the Chinese Emission Control Areas policy. The results find that the policy has significantly reduced the locally produced sulfur dioxide concentrations by 3.41% in port cities. However, the omission of transboundary spillovers could yield contrasting results, suggesting that ignoring the pollution transport could lead to erroneous conclusions. The research findings of this study hold significant policy implications, highlighting the importance of accounting for transboundary transport of air pollution in evaluating the local government's environmental efforts and implementing supra-city environmental policies to prevent air pollution. • We investigate the efficacy of marine fuel restrictions policy. • We develop a new approach to account for the transboundary air pollution spillovers. • The policy significantly reduced local sulfur dioxide concentrations in ports. • Ignoring pollutant spillovers may bias the estimate of environmental policy effects. [ABSTRACT FROM AUTHOR]

Photochemical air quality models (AQMs) are a vital tool for atmospheric pollution research and have been widely used in various applications, such as air quality prediction and evaluation of pollution control strategies. Before using these models for further studies, it is essential to thoroughly evaluate their reliability and accuracy. While previous guidelines and benchmarks have primarily focused on fine particulate matter (PM 2.5) and ozone (O 3), there is still a lack of benchmarks for evaluating the model performance on primary criteria pollutants such as sulfur dioxide (SO 2), nitrogen dioxide (NO 2), carbon monoxide (CO), and particulate matter with aerodynamic diameter less than or equal to 10 μm (PM 10). The use of air quality models in China has increased significantly in the past decades. However, there is still a lack of standardized benchmarks for the performance evaluation of these models. Building upon our previous work on PM 2.5 and its chemical species, we propose a set of benchmarks for evaluating the performance of the aforementioned four air pollutants. Initially, we identified a total of 475 papers published during 2007–2019 that utilized at least one of the five commonly used AQMs in China. From these papers, we selected 164 articles that provided model performance evaluation (MPE) results of the four primary air pollutants. The three most frequently used Model Performance Evaluation (MPE) metrics were selected to analyse the impact of different model configurations on the reported statistics, including modelling region, season, and emission inventory. Lastly, three commonly used statistical indicators, including normalized mean bias (NMB), normalized mean error (NME), and correlation coefficient (R), were proposed for the validation of simulated NO 2 , SO 2 , CO, and PM 10. Two sets of benchmarks are given, including the "goal" and "criteria". The "goal" represents the best range of performance that a model can be expected to achieve, and the "criteria" represents performance that the majority of studies have achieved. We recommend R values above 0.50, 0.35, 0.45, and 0.40 for NO 2 , SO 2 , PM 10 , and CO, respectively, in order to meet the "criteria" benchmark. If the "goal" benchmark is to be achieved, the corresponding R values are 0.60, 0.55, 0.60, and 0.60. The "goal" benchmarks of NMB for NO 2 , SO 2 , PM 10 , and CO are within ±20%, ±25%, ±20%, and ±25%, respectively; while the "goal" benchmarks of NME for the four pollutants are less than 40%, 45%, 45%, and 60%, respectively. These benchmarks supplement our previous benchmarks for PM 2.5 and its components and provide a more comprehensive guideline for the air quality modelling community in China. • A set of benchmarks for evaluation of the NO 2 , SO 2 , CO and PM 10 simulation over China are proposed. • Three commonly used statistical indicators (NMB, NME, and R) were proposed for the validation of the four pollutants. • The goal benchmarks of NMB for NO 2 , SO 2 , PM 10 , and CO are <20%, <25%, <20% and <25%, respectively. [ABSTRACT FROM AUTHOR]

[Display omitted] • The influence of co-firing ratio of ammonia in coal-fired process on the formation of CPM was explored. • The total FPM decreased when the ammonia co-firing ratio increased from 0 to 50%. • The conversion of sulfur from coal to CPM was promoted when the ammonia was mixed in coal combustion process under the same total calorific value. In this paper, the influence of zero-carbon ammonia co-firing ratio during coal/ammonia combustion on the generation of condensable particulate matter(CPM) was investigated. 0%, 10%, 20%, 30% and 50% ammonia were mixed into the coal combustion according to the energy input ratio to collect the discharged CPM and FPM in laboratory and the composition of flue gas was tested. The results show that mixing ammonia into coal combustion had little impact on the total concentration of CPM. The main reason is that the ammonia co-firing into coal can promote the formation of inorganic matter of CPM, and the concentration of organic matter decreased. The mass of FPM decreased when the proportion of ammonia is increased. In addition, co-combustion of ammonia inhibited the formation of SO 2 that discharge to the atmosphere. The main reason is that the mass of coal decreased with the increasing of calorific value of ammonia. In addition, the co-firing of ammonia can promote the conversion of S to FPM and CPM. The reason is that H came from NH 3 burned to produce water vapor, then water vapor can combine with sulfur dioxide. Peak areas of some organic substances are drawn with the variety of ammonia co-firing ratio. Most of the substances in alkanes are N-alkanes. The conclusions in this paper are of great significance to the further understanding of migration and transformation of pollutants under the influence of ammonia co-combustion. In addition, the research in this paper provides a theoretical basis for achieving the goal of carbon neutrality. [ABSTRACT FROM AUTHOR]

The flue gas pollutants emitted from industrial flue gas and automobile exhaust have serious harm to atmospheric environment and human health. Therefore, it is important to study the control and purification of flue gas pollutants. At present, adsorption and catalytic methods are extensively employed for the elimination of flue gas pollutants. Clay minerals, as a kind of substances widely existing in nature, have unique physical and chemical properties that make them great application in many fields, especially in the field of flue gas pollutants removal. This review presents the types and structures of common clay minerals and their modification methods. It depicts recent advances in the use of modified clay materials to remove flue gas pollutants, highlighting the adsorption performance and adsorption mechanism for CO 2 , SO 2 and VOCs, as well as the catalytic performance and catalytic mechanism for NO x and VOCs of modified clay materials. In addition, this paper also focuses on the recycling of polluted gases and their conversion into value-added products. Finally, the current challenges and future prospects of clay mineral materials in flue gas pollutant removal are introduced. This review provides new insights into using clay materials as adsorption and catalytic materials for flue gas pollutants removal. [Display omitted] • Clay-based adsorbents and catalysts for removal of flue gas pollutants are reviewed. • The types and modification methods for clay-based materials are discussed. • Various air pollutants removal performance and mechanism are briefed. • Challenges and future development of clay-based materials are proposed. [ABSTRACT FROM AUTHOR]

In the past few years, there has been significant progress in developing sensors for indoor air quality (IAQ) monitoring. Thanks to their miniaturization, low cost, and growing concerns for people's well-being, these sensors have become increasingly important. This paper reviews the latest metal oxide semiconductor (MOS)-based gas sensors published since 2019 for the WHO-priority gas pollutants. While MOS-based gas sensors initially had limitations, including low selectivity, high operating temperatures leading to high power consumption, and interference from humidity, these challenges have been overcome. Currently, MOS-based sensors can detect some of the WHO-priority target gases at room temperature, achieving guideline values established for human safety. This progress in MOS-based gas sensors instills optimism for their future role in IAQ monitoring despite the challenges that still need to be addressed. • Past 5 years MOS-based gas sensors for indoor air evaluation have been revised. • Sensors operating at room temperature with low limits of detection are now accessible. • Challenges, including long-term stability and humidity, still remained. • Sensors for SO 2 , naphthalene, tri-and tetrachloroethylene are foreseen. [ABSTRACT FROM AUTHOR]

Polycyclic aromatic hydrocarbons (PAHs), which are widely present in incompletely combusted air particulate matter <2.5 μm (PM2.5), tobacco and other organic materials, can enter the human body through various routes and are a class of environmental pollutants with neurotoxic effects. PAHs exposure can lead to abnormal development of the nervous system and neurobehavioral abnormalities in animals, including adverse effects on the nervous system of children and adults, such as a reduced learning ability, intellectual decline, and neural tube defects. After PAHs enter cells of the nervous system, they eventually lead to nervous system damage through mechanisms such as oxidative stress, DNA methylation and demethylation, and mitochondrial autophagy, potentially leading to a series of nervous system diseases, such as Alzheimer's disease. Therefore, preventing and treating neurological diseases caused by PAHs exposure are particularly important. From the perspective of the in vitro and in vivo effects of PAHs exposure, as well as its effects on human neurodevelopment, this paper reviews the toxic mechanisms of action of PAHs and the corresponding prevention and treatment methods to provide a relevant theoretical basis for preventing the neurotoxicity caused by PAHs, thereby reducing the incidence of diseases related to the nervous system and protecting human health. Sources of polycyclic aromatic hydrocarbons, neurotoxic effects and their mechanisms of action. [Display omitted] • PAHs are a class of environmental pollutants, which have a negative impact on nervous system. • PAHs can harm the nervous system by causing oxidative stress, altering DNA methylation, and impacting mitochondrial autophagy. • PAHs have been found to induce aberrant neurological development and neurobehavioral abnormalities in animal models. • Exposure to PAHs adversely affects the nervous system in children and adults. [ABSTRACT FROM AUTHOR]

Ships present a significant source of air pollution, contributing to environmental degradation and posing health risks. Boilers are a significant part of the vessels in which the water is heated to evaporate and generate steam. The boilers emit pollutants such as hazardous air pollutants (HAPs), particle pollution, and volatile organic compounds (VOC). This paper conducts an extended risk analysis for air pollution due to boiler operation on ships. An improved Z -numbers theory and Fault Tree Analysis (FTA) are adopted to predict risk. Whilst improved Z-number theory is capable of handling uncertainties inherent in risk assessment, the FTA presents systematically the causal relationships among various factors contributing to the risk of air pollution on ships. The findings show that the failure probability of air pollution during ship boiler operation is 2.08E-05 and BE-12 is the most significant event. Results provide valuable data to maritime stakeholders in fostering environmentally sustainable practices. • A risk analysis of air pollution due to boiler operation on ships is presented. • Risk analysis is carried out through improved Z-number and fault tree analysis. • The findings provide information to understand and mitigate air pollution risk. [ABSTRACT FROM AUTHOR]

Formaldehyde (HCHO) poses a significant threat as a common indoor air pollutant, leading to various health issues. However, effectively addressing HCHO removal at room temperature remains a considerable challenge. This paper presents the preparation of a robust, eco-friendly, and biodegradable composite cellulose nanofiber film, incorporating CeO 2 -Ag@MnO 2 catalysts and TEMPO-oxidized cellulose nanofiber (TOCNF), for high-efficiency HCHO removal at room temperature. A CeO 2 -Ag@MnO 2 ternary catalyst with a core–shell structure was constructed to enhance the catalytic oxidation activity and stability. This structure increased the number of active sites on the catalyst surface and enhanced the interfacial synergistic effect of Ce-Ag-Mn. The TOCNF physically adsorbed HCHO in the composite film, while the catalyst oxidized it to CO 2 and water. The composite films, particularly those with 20 wt% CeO 2 -Ag@MnO 2 catalyst, exhibited high HCHO removal rates of 91.2 % at 20 °C and 99.6 % at 60 °C. Furthermore, the TOCNF/20 CAM composite films demonstrated excellent mechanical properties and degradability. This composite film offers an efficient and eco-friendly solution for the catalytic oxidation of HCHO at room temperature. [Display omitted] • We propose a novel cellulose nanofiber composite film for high-efficiency HCHO removal at room temperature. • The composite films with 20 wt.% CeO 2 -Ag@MnO 2 catalyst, exhibit high HCHO removal rates of 91.2% at 20 °C and 99.6% at 60 °C. • The ternary catalysts with core–shell structure enhance the interfacial synergistic effect of Ce-Ag-Mn. • The TOCNF/20 CAM composite films demonstrated excellent mechanical properties and degradability. [ABSTRACT FROM AUTHOR]

• Assessment of ship emission performance under diverse decarbonization measures. • Technical options reduce more carbon and air pollutant emissions than operational. • Trade-offs between air pollutant reduction and decarbonization strategies. • Contribution in policies for reducing both carbon emissions and air pollutants. Shipping emits Greenhouse Gases (GHG), contributing to climate change and various air pollutants, posing risks on human health. To address GHG, maritime has responded with increasingly stringent legislations, including recent commitments to achieve net-zero emissions by 2050. Substantial investments have been made in cutting-edge technologies, alternative fuels and operational strategies ensuring emissions regulations compliance. This paper aims to quantitatively evaluate the emission performance of diverse decarbonization options, focusing on assessing their potential to mitigate GHG and addressing air pollutants. Our analysis utilizes a new set of load-dependent Emission Factors and employs Automatic Identification System data for 5 ship classes. While operational measures moderately reduce emissions, fuel shift to alternatives and on-board carbon capture and storage offer a more promising pathway towards decarbonization and air pollutants reduction. The outcomes intend to provide insights into the effectiveness of measures in reducing external costs, while serving as a valuable resource for regulatory authorities. [ABSTRACT FROM AUTHOR]

The increase in air pollution has posed numerous new challenges for human society, making the exploration of an effective method for predicting air pollutant concentrations highly significant. The current research faces several primary challenges: the neglect of non-Euclidean characteristics of site distribution on data and the strong spatiotemporal dependencies in the dispersion process of pollutants. To address these issues, this paper constructs a spatiotemporal hybrid prediction model – the MGAtt-LSTM method – for predicting PM 2.5 concentrations, which employs the dynamic multi-graph attention module (MGAtt) to tackle spatial dependencies and Long Short-Term Memory networks (LSTM) to address temporal dependencies. Additionally, extensive experiments are conducted by using historical air pollutant monitoring data and meteorological data from the Beijing-Tianjin-Hebei region. The results demonstrate that the proposed MGAtt-LSTM model achieved superior performance in concentration prediction compared to existing benchmark models. • The neural network consists of multi-graph attention network and LSTM network. • Air pollution data in North China and meteorological data are used to forecast. • The uneven distribution of pollutant sites is considered to predict PM 2.5 concentrations precisely. • The use of multi-graph attention networks addresses the issue of traditional GCN methods relying on fixed graph structures. [ABSTRACT FROM AUTHOR]

Accurate prediction of air pollutant concentrations can be effective in controlling and preventing air pollution, which is crucial for both the government's policy response and the public's reasonable ability to avoid air pollution. In this study, we propose a model based on the principle of big data correlation and deep learning techniques for predicting the concentration of air pollutant concentrations. The proposed model, named STARes-SaLSTM, consists of a residual neural network with spatiotemporal attention (STAResNet) and a temporal self-attention based on long short-term memory network (SaLSTM). The spatiotemporal attention module in STAResNet enhances the original input information by weighting it in both spatial and temporal dimensions, meanwhile the features of the spatial distribution of pollutant and meteorological information across many cities are deeply extracted using ResNet. A novel self-attention method known as temporal self-attention is developed to extract the temporal dependency of air pollutants. LSTM is used as a sequence encoder in this temporal attention method to calculate queries, keys, and values to acquire a more comprehensive temporal dependence than is possible with normal self-attention. The STARes-SaLSTM model successfully predicts air pollution concentrations in the target city for the future by extracting spatiotemporal correlation of feature sequence. In comparison to previous neural network models and conventional methods, the model increases the accuracy of pollutant concentration prediction. The suggested prediction model works well for the one to 3 h prediction job, with a root mean square error (RMSE) ranging from 6.716 to 11.648. Furthermore, even for the 1–24 h prediction assignment, we executed multi-scale prediction in the target city and obtained a reasonable performance, with an average RMSE value of 20.576. • This paper solves the problem of difficult extraction of spatiotemporal features. • ResNet allows for the extraction of spatially relevant features; • The spatiotemporal attention mechanism is used to spatiotemporal extract features; • The temporal self-attention mechanism obtain temporal dependence of data. [ABSTRACT FROM AUTHOR]

Modernising Australia's old truck fleet and adopting a more stringent standard to reduce emissions and air pollutants is a primary objective for the Australian truck sector. Various strategies worldwide have been introduced to cut emissions and pollutants in the truck sector, such as a low-emission strategy supported by strict diesel standards and a zero-emission strategy to shift to battery-electric or hydrogen trucks. The paper focuses on emissions and local air pollutants of trucks under various transition scenarios at both the tailpipe and the wider supply chain including domestic power generation and hydrogen production. In contrast, for diesel, we focus on tailpipe outputs following fuel standards in Australia, given diesel is imported other than in some limited refineries. We compare and recommend actions that government and truck operators may take in the near to longer term in transitioning to cleaner energy. We tested a number of scenarios using a decision support system incorporating all the latest information on costs and emissions for all truck classes using diesel, electric or hydrogen. A key finding from our scenario tests is that the current electricity mix has high carbon emissions and air pollutants due to fossil fuel-fired sources for power generation. Without improvement in using renewable energy sources in the future, transitioning to electric trucks implies more carbon emissions and air pollutants in the atmosphere from power plants, even though electric trucks generate zero tailpipe emissions. The main motivation for switching to zero-emission trucks is energy cost savings. We urge the government to decide on a clear roadmap for the truck sector before the sector is in a position to take action to shift to low or zero-emission trucks without totally relying on the likely reduction of emission intensity in electricity and renewable energy production. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) are crucial air pollutants in indoor environments, emitted from building materials, furniture, consumer products, cleaning products, smoking, fuel combustion, cooking, and other sources. VOCs are also emitted from human beings via breath and whole-body skin. Some VOCs cause dermal/ocular irritation as well as gastrointestinal, neurological, cardiovascular, and/or carcinogenic damage to human health. Because people spend most of their time indoors, active control of indoor VOCs has garnered attention. Phytoremediation and microbial remediation, based on plant and microorganism activities, are deemed sustainable, cost-effective, and public-friendly technologies for mitigating indoor VOCs. This study presents the major sources of VOCs in indoor environments and their compositions. Various herbaceous and woody plants used to mitigate indoor VOCs are summarized and their VOCs removal performance is compared. Moreover, this paper reviews the current state of active phytoremediation and microbial remediation for the control of indoor VOCs, and discusses future directions. [Display omitted] • With well-known sources, humans are notable indoor VOCs sources. • Various herbaceous/woody plants are employed to mitigate indoor VOCs. • Most studies on phyto- & microbial remediation for indoor VOCs remains at Lab-scales. • Synergistic interaction of plant-microbe can enhance indoor VOCs removal. • Long-term field tests are needed to innovate biotechnology for indoor VOCs control. [ABSTRACT FROM AUTHOR]

Nowadays, air pollution has become one of the most serious environmental problems facing humanity and an inescapable obstacle limiting the sustainable development of cities and society. Although air quality sensing and management systems based on artificial intelligence and signal analysis are evolving as essential parts of intelligent cities, the mixture of local emission sources and regional transport of air pollutants still makes PM 2.5 long-term prediction challenging, especially under complex geographical and climatic conditions. In this paper, the complete ensemble empirical mode decomposition based multi-stream informer (CEEMD-MsI) is proposed to predict the hourly PM 2.5 concentration, and extensive testing and comparisons are carried out in four typical cities in Shandong, China. Firstly, CEEMD is used for signal pre-processing to construct the intrinsic mode functions (IMFs) based multi-channel representations. Then MsI is specifically designed to learn both temporal and spatial features, and complete the PM 2.5 concentration prediction. To the best of our knowledge, this is the first attempt to predict long-term PM 2.5 concentrations using a deep learning model driven by data collected from monitoring stations spanning long distances and diverse terrains. Finally, test results demonstrate that CEEMD-MsI achieves the best PM 2.5 prediction performance by comparing it with state-of-the-art methods. [ABSTRACT FROM AUTHOR]

South Asian air pollutants exert substantial effect on the climate and environment change over the Tibetan Plateau (TP). This paper investigates the trans-boundary transport of PM 10 , PM 2.5 , and O 3 from South Asia to the TP via WRF-Chem sensitive analysis. It is found that PM 10 , PM 2.5 , and O 3 over South Asia are mainly sourced from anthropogenic sources. South Asian emissions contribute up to 54% of PM 10 (PM 2.5) in the TP in the pre-monsoon season. For O 3 , the highest contribution of 18.13% is in the monsoon season, while the lowest contribution of 8.67% is in the winter season. To evaluate the respective contributions of anthropogenic and biomass burning emissions in South Asia to PM 10 , PM 2.5 , and O 3 in the TP, anthropogenic and biomass burning emissions in South Asia are considered separately. The results show that the largest percentage contribution of PM 10 (PM 2.5) from South Asian anthropogenic emissions to PM 10 (PM 2.5) in the TP with value of 35.86% (37.77%) occurs in winter, while the lowest percentage contribution of 16.52% (16.77%) appears in the monsoon season. For O 3 , the largest contribution of 17.74% from South Asian anthropogenic emissions appears in the monsoon season, whereas the lowest contribution of 8.59% occurs in winter. Compared to the anthropogenic emissions, the biomass burning emissions in South Asia have a relative less contribution to PM 10 , PM 2.5 , and O 3 in the TP. The largest contribution of PM 10 (PM 2.5) from South Asian biomass burning emissions to PM 10 (PM 2.5) in the TP is 20.04% (18.37%) in the pre-monsoon season. Conversely, the lowest contribution of 0.58% (0.53) appears in the monsoon season. O 3 from South Asian biomass burning emissions contributes <1% to O 3 in the TP in each season, implying that the biomass burning emissions in South Asia have little effect on O 3 in the TP. This study is of great significance to the ecological environment protection for the TP. • Contributions of South Asian emissions to PM 10 , PM 2.5 , and O 3 in the TP are quantified. • Anthropogenic emissions in South Asia have a larger contribution to PM 10 , PM 2.5 , and O 3 in the TP. • O 3 from South Asian biomass burning emissions contributes <1% to O 3 in the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

In 2015, the Chinese government set ultra-low emission standards for thermal power to alleviate the pressure of increasing total pollutants from energy demand. This paper analyzes the policy effect of ultra-low emission in different regions based on panel data of 1202 thermal power enterprises, and the results of hierarchical linear model show that the total amount of air pollutants emitted by thermal power enterprises showed a decreasing trend during 2017–2021, realizing the dual control of concentration and total amount. Due to the differences in primary energy structure, industrial structure and economic development level of different regions, the total emission reduction of thermal power pollutants is affected differently. First, the proportion of the region's secondary industry in the region's GDP is negatively correlated with the decrease of the total pollutant emission of local thermal power enterprises. Second, the higher the per capita GDP of the region, the more significant the decrease in the total amount of pollutants, economic development is conducive to pollutant emission reduction. Third, the higher the proportion of thermal power in local energy, the more obvious the reduction of total pollutant emissions of thermal power enterprises, indicating that the implementation of ultra-low emission policies in these regions is more thorough. In addition, the environmental protection tax plays a positive role in the total emission reduction, and the higher the sulfur dioxide tax rate, the more significant the reduction of total pollutants of thermal power enterprises. To further reduce the total amount of pollutants in thermal power, more coordinated efforts of environmental and economic policies are needed. [Display omitted] • The ultra-low emission policy can achieve dual control of pollutants. • The total pollutant emission reduction has obvious regional differences. • Environmental protection tax can reduce the total amount of pollutants. • The coordinated emission reduction of different pollutants is not obvious. [ABSTRACT FROM AUTHOR]

Air pollution is one of the most threatening risk factors for human health. The epidemiological literature has widely proved that exposure to high levels of PM 10 is associated with an increase in cardiovascular and respiratory events. In this paper, we investigate the relationship between air pollution and emergency department visits for cardiovascular and respiratory diseases. Since the relationship between air pollution and emergency care access is complex and may be subject to regime switches, especially due to the COVID-19 pandemic, we propose to use a threshold autoregressive model where the regime-switching mechanism is driven by temporal evolution. This allows us to identify one or more structural breaks and estimate the regime-changing relationship between emergency care accesses and PM 10. Moreover, we propose a novel way to account for long-term dependence in the dependent variable. Using daily data from the metropolitan area of Bologna (Italy), we show that the effect of the air pollutant changes over time, mostly due to the outbreak of the COVID-19 pandemic. • The relationship between air pollution and health is nonlinear. • PM 10 increases emergency visits for respiratory diseases. • Post-lockdown, the association between PM 10 and emergency visits worsens. [ABSTRACT FROM AUTHOR]

China's climate and environmental problems remained prominent. Energy transition was the key to improve climate and pollution, and it was at a critical period. Previous studies mostly focused on the impact of climate policies on the reduction of air pollutants and the environmental health impacts of individual sector or pathway policies. Thus, focusing on the synergistic abatement of CO 2 and air pollutants and health effects of energy transition in carbon neutrality was significant for building beautiful and healthy China. LEAP-HEA model was constructed to project energy demand, CO 2 and air pollutants, and assess energy transition's environmental health effects from 2020 to 2060. LMDI model was adopted to decompose the abatement contribution. Synergistic assessment index was used to estimate the coordinated abatement effects. Cost-effectiveness of energy transition and regional heterogeneity of PM 2.5 toxicity were not considered. The results indicated: (1) energy demand would decrease and structure would be optimized significantly under deep energy transition scenario. (2) Deep energy transition could promote earlier realization of carbon neutrality. It would contribute significantly to CO 2 and air pollutants abatement with strong synergistic effects. (3) Energy transition would reduce health risks with large economic benefits. Recommendations were proposed based on the conclusions. The framework of LEAP-HEA model. [Display omitted] • The synergistic abatement and health effect of energy transition were explored. • The models of LEAP, LMDI, exposure-response and the data of 2020 were used. • Energy transition would have significant synergistic abatement and health effect. • The paper has significance for promoting carbon neutrality and healthy China. [ABSTRACT FROM AUTHOR]

[Display omitted] • Composite of py-pAMHS-NH 3 +-ph with rGO can be facilely prepared by π-π stacking interaction. • The rGO-py-pAMHS-NH 3 +-ph could efficiently eliminate HCHO via chemical reaction with the only by-product of water. • 206.41 mg HCHO could be effectively removed within 4 h by 1.0 g rGO-py-pAMHS-NH 3 +-ph. • Removal of HCl/H 2 S could be achieved by amine groups tethered rGO-py-pAMHS-NH 2 -ph via ion-bonding interactions. • The rGO-py-pAMHS-NH 3 +-ph shows a good cycle stability, thus has promising application prospect. In this paper, the contribution of self-assembled composite material of bifunctional polymer prepared by RAFT polymerization and rGO to the removal of low concentration HCHO and acids from air were systematically studied. Experimental results demonstrate that the condensation reaction between HCHO and the protonated amino group at the terminal of the rGO-py-pAMHS-NH 3 +-ph chain effectively can eliminate HCHO chemically, resulting in the release of H 2 O as the sole by-product following oxime bonds formation. rGO alone is incapable of chemically removing gaseous HCHO, but when combined with the py-pAMHS-NH 3 +-ph, efficient HCHO conversion can be achieved, well elucidating the remarkable HCHO removal capability via rGO-py-pAMHS-NH 3 +-ph. The HCHO chemical removal performance of composite is evaluated by a self-made device at the 1000 mL/min N 2 velocity under 25 °C and 50 % RH and it is found that 206.41 mg of HCHO can be removed in approximately 4 h by using 1.0 g of rGO-py-pAMHS-NH 3 +-ph. In addition, cycling experiments demonstrate the rGO-py-pAMHS-NH 3 +-ph possesses good durability. We also find that the rGO-py-pAMHS-NH 2 -ph has the ability to remove acids when the terminal protonated amino groups have been converted into amine functionalities. This green and zero-carbon emission methodology for chemical removal of HCHO degradation and acid pollutants could provide valuable reference for developing other efficient strategies to remove other pollutants such as VOCs etc. [ABSTRACT FROM AUTHOR]

Landfill is a huge pathogen reservoir and needs special attention. Herein, the distribution and spread risk of pathogen were assessed in excavated landfill scenario. The results show that landfill excavation will greatly increase the risk of environmental microbial contamination. The highest total concentration of culturable bacteria among landfill refuse, topsoil and plant leaves was found to be as high as 1010 CFU g−1. Total coliforms , Hemolytic bacteria , Staphylococcus aureus , Salmonella , Enterococci , and Fecal coliforms were detected in the landfill surrounding environment. Notably, pathogens were more likely to adhere to plant leaves, making it an important source of secondary pathogens. The culturable bacteria concentration in the air samples differed with the landfill zone with different operation status, and the highest culturable bacteria concentration was found in the excavated area of the landfill (3.3 × 104 CFU m−3), which was the main source of bioaerosol release. The distribution of bioaerosols in the downwind outside of the landfill showed a tendency of increasing and then decreasing, and the highest concentration of bioaerosols outside of the landfill (6.56 × 104 CFU m−3) was significantly higher than that in the excavated area of the landfill. The risk of respiratory inhalation was the main pathway leading to infection, whereas the HQ in (population inhalation hazardous quotient) at 500 m downwind the excavation landfill was still higher than 1, indicating that the neighboring residents were exposed to airborne microbial pollutants. The results of the study provide evidence for bioaerosols control protective measures taken to reduce health risk from the excavated landfill. [Display omitted] • Microbe from landfill are more likely to attach to wood, paper, and plastic. • Landfill surrounding plants are greater barrier for microbial containment. • Excavation process will increase the emission of microbial. • Aerosol dispersion model shows effectively simulation results. [ABSTRACT FROM AUTHOR]

The power sector significantly contributes to global greenhouse gas emissions, making its transition to low-carbon energy crucial for achieving carbon neutrality. Zhengzhou, recognized as one of the China's "National Central Cities", has a high energy demand. Its power sector, which is primarily reliant on coal, is responsible for half of the city's CO 2 emissions. The low emissions analysis platform (LEAP) model serves as an effective tool for exploring the power sector's transition to low-carbon sources. However, studies on the combined reduction in air pollutants and CO 2 at the city level are scarce. This study focuses on Zhengzhou's power sector, examining the power composition, coal usage, CO 2 and air pollutant emissions, social costs, and employment effects across five scenarios using LEAP. The five scenarios are the business-as-usual scenario, the reference scenario, the carbon neutrality scenario, and two optimization scenarios with different carbon peak and carbon neutrality time. CO 2 emissions will peak in 2030 at 34.6 Mt in the reference scenario, and in 2022 at 32.4 Mt in the carbon neutrality scenario. Emissions in the reference and carbon neutrality scenarios will decrease by 64.8% and 75.2%, respectively, from those in the business-as-usual scenario due to emission reduction strategies. In the carbon neutrality scenario, coal power reformation is the most significant measure, accounting for 45.7% of the total CO 2 reduction compared to that in the business-as-usual scenario, followed by the integration of external electricity (17.8%) and solar energy (13.6%). This scenario also demonstrated a strong synergistic effect on reducing air pollutants and CO 2 emissions. Although the carbon neutrality scenario incurs costs 60.4 billion yuan higher than those of the reference scenario, its CO 2 mitigation cost is 66.1 yuan/t lower. This indicated that more rapid CO 2 reduction, despite higher economic inputs, is justified by ambitious CO 2 reduction goals and environmental benefits. Enhancing the use of renewable energy technologies for research and development to lower costs could increase the economic feasibility of the carbon neutrality scenario. In the two optimization scenarios, complete elimination of CO 2 and air pollutant emissions is achieved by 2060, with all the electricity generated from renewable sources, although issues of uncertainty and stability need to be addressed. The study also highlights that renewable energy development will significantly boost employment, with an estimated 1.19 million jobs in 2060 in the carbon neutrality scenario. Finally, the paper concludes with a sensitivity analysis and offers policy recommendations for the power sector's low-carbon transition. [Display omitted] • Low-carbon transition paths of Zhengzhou power sector are investigated by scenario analysis. • Coal power reformation and external electricity are effective measures for CO 2 reduction. • Synergistic reduction of air pollutants and CO 2 is achieved in the CAN scenario. • The CAN scenario has a good cost-effectiveness of CO 2 mitigation. • Policy recommendations for Zhengzhou power sector are proposed. [ABSTRACT FROM AUTHOR]

[Display omitted] Particulate matter (PM) is an important air pollutant in subway systems. Exposure to high PM concentrations poses a threat to human health and raises concerns. Piston effect can provide the outdoor fresh air to subway stations through station exits, but it also brings PM from tunnels to platforms when the train enters the station. In this paper, a transient numerical model is developed according to an actual subway station and validated by field tests. The model is used to investigate PM 10 concentration at platform induced by train movement. The cumulative PM 10 concentration at platform in one day is calculated according to the train schedule. Platform screen door (PSD) with adjustable vents is studied to control the PM 10 level at platform and energy saving in 27 cities of five climatic zones in China are discussed. The results show that adjustable vent height should be less than 0.70 m to ensure that PM 10 concentrations at platform can be maintained at an acceptable level and the requirement of fresh air can be met. Moreover, energy consumption can be reduced by more than 70 % in different cities compared with the conventional mechanical ventilation system. The optimized adjustable vent can provide an important reference for improving indoor air quality (IAQ) and saving energy consumption of ventilation systems in underground facilities. [ABSTRACT FROM AUTHOR]

[Display omitted] • Electronegativity of the A species in ACu-CeO 2 affect catalytic activity for CO-SCR reaction. • CuCo-CeO 2 exhibited 100% NO conversion and 100% N 2 selectivity in CO-SCR. • The addition of species A promotes the electron/ion transfer between metals in the catalyst. • The CO-SCR reaction mechanisms was proposed based on in situ DRIFTS. Transition metal-based nanomaterials have gained significant attention as highly active and cost-effective catalysts for the selective catalytic reduction (SCR) of NO with CO. Using a simple wet impregnation method, the catalyst composition and active sites can be modulated. In this paper, we present a novel cerium-based co-solvent catalyst, A-site doped ACu-CeO 2 (A = Co, Fe, Mn), for CO-SCR of NO. The doping of A-site elements induces structural changes and enhances catalytic performance. Among the doped catalysts, CoCu-CeO 2 exhibits a wide temperature window for operation and high selectivity towards nitrogen, achieving 100% NO conversion at 200 °C. Furthermore, A-site modulation not only promotes electron/ion transfer within the catalyst but also enables uniform and dispersed distribution of the active metal species, particularly copper, in the CoCu-CeO 2 catalyst. This provides reaction centers for the selective reduction of NO by CO and enhances the adsorption capacity of the catalyst for NO. The ACu-CeO 2 catalyst demonstrates excellent CO-SCR catalytic performance and resistance to vapor. Characterization techniques such as XPS, Raman spectroscopy, and in situ DRIFTS elucidate the reaction mechanism of the ACu-CeO 2 cerium-based co-solvate in the CO-SCR reaction. This study furthers our understanding and improvement of catalyst design, while also providing an efficient and straightforward denitrification catalyst for controlling air pollutants. [ABSTRACT FROM AUTHOR]

The production of biofuels to be used as bioenergy under combustion processes generates some gaseous emissions (CO, CO 2 , NO x , SO x , and other pollutants), affecting living organisms and requiring careful assessments. However, obtaining such information experimentally for data evaluation is costly and time-consuming and its in situ obtaining for regional biomasses (e.g. , those from Northeast Brazil (NEB) is still a major challenge. This paper reports on the application of artificial neural networks (ANNs) for the prediction of the main air pollutants (CO, CO 2 , NO, and SO 2) produced during the direct biomass combustion (N 2 /O 2 :80/20%) with the use of ultimate analysis (carbon, hydrogen, nitrogen, sulfur, and oxygen). 116 worldwide biomasses were used as input data, which is a relevant alternative to overcome the lack of experimental resources in NEB and obtain such information. Cross-validation was conducted with k-fold to optimize the ANNs and performance was analyzed with the use of statistical errors for accuracy assessments. The results showed an acceptable statistical performance for all architectures of ANNs, with 0.001–12.41% MAPE, 0.001–5.82 mg Nm−3 MAE, and 0.03–52.30 mg Nm−3 RMSE, highlighting the high precision of the emissions studied. On average, the differences between predicted and real values for CO, CO 2 , NO, and SO 2 emissions from NEB biomasses were approximately 0.01%, 10−6%, 0.14%, and 0.05%, respectively. Pearson coefficient provided consistent results of concentration of the ultimate analysis in relation to the emissions studied and effectiveness of the test set in the developed models. [Display omitted] • Assembly of a worldwide database with different lingocellulosic biomasses. • Prediction of main air pollutants (CO, CO 2 , NO, and SO 2) for the selected samples. • Information obtained on Brazilian biomasses without the need for many experiments. • Use of different evaluation metrics to validate the established models. • The ANN's showed differences between predicted and estimated values below 1.0%. [ABSTRACT FROM AUTHOR]

The study on high-temperature oxidation kinetics and kinetic modeling of acetylene (C 2 H 2) has significant importance for its engineering applications. In this paper, the first-principles molecular dynamics method is used to simulate the C 2 H 2 oxidation under high temperatures for the first time. Our results show that there are 38 intermediates and 225 elementary reactions in the process of C 2 H 2 oxidation. The formation mechanisms of "prompt" CO 2 , as well as gas pollutants CHOCHO and HCOOH are revealed in depth. Four intermediates, CHCHO, CHOCO, CHOCHO and HCOOH, which have significant controversy in current kinetic models, are verified. And a new intermediate, CHOCO 2 , is discovered. Meanwhile, our simulation also shows that radicals, such as HO 2 , OH, O, etc. play a key role in promoting the oxidation of intermediates in the early stage of C 2 H 2 oxidation. Combined with quantum chemical calculations, a detailed chemical kinetic model of C 2 H 2 /air (FP-C 2 H 2) is built and verified by simulating ignition delay time, species concentration in the flow reactor and premixed laminar flame speed. Our studies provide novel insight for understanding the complex chemical reaction kinetics, and environmental and human health threats from air pollutant formation during C 2 H 2 combustion. [Display omitted] ● The formation mechanism of gas pollutants CHOCHO and HCOOH are revealed. ● Intermediates CHOCO, HCOOH, CHOCHO and CHCHO are key species to C 2 H 2 combustion. ● The decomposition of new intermediate CHOCO 2 explains the prompt CO 2 formation. ● 38 intermediates and 225 elementary reactions are discovered by FPMD simulation. ● A detailed chemical kinetic model of C 2 H 2 combustion is constructed and verified. [ABSTRACT FROM AUTHOR]

While concentrations of most air pollutants have been decreasing in Europe over the last 20 years, O 3 is showing variable trends, with increasing average and decreasing peak concentrations. The complexity of O 3 chemistry adds to the difficulty of understanding both the trends observed and how concentrations can be mitigated. This paper tries to answer the following questions: which emission sectors should be targeted and what levels of reduction could be achieved? To address these reflections, an Atlas of O 3 chemical regimes has been constructed. For this Atlas, 22 European cities were selected and the surrogate model Air Control Toolbox (ACT) was used to evaluate the simulated changes in several ozone metrics as a result of reductions in road transport and industrial emissions. O 3 chemical regimes have been classified and put in perspective with meteorological and emission data at each city location and around. The O 3 sensitivity to road transport and industrial emissions differ from one city to another, but also for the same city when considering different ozone metrics and seasons (e.g., annual means versus SOMO35 or summer peaks). Counterproductive impacts yielding O 3 increase when emissions are reduced are mainly encountered in regions or periods where O 3 concentration are relatively low. In terms of meteorological factors, O 3 chemical regimes are mostly impacted by the amount of solar radiation received but wind speed also has a considerable impact. Most cases show a higher sensitivity to emission reductions from road transport or equal sensitivity to emission reductions from road transport and industry. Very few cases are more sensitive to emissions from the industrial sector. However, the response of annual or seasonal average O 3 metrics to industrial and road transport emissions can be considered relatively low with a maximum reduction of 33% for a 100% reduction of both industrial and road transport emissions. This is because anthropogenic emission can only mitigate ozone above a substantial natural tropospheric background. It is precisely this incremental anthropogenic ozone, which should be targeted by efficient policies as we also demonstrate that none of the cities studied would exceed the European target value with a 100% reduction in emissions. • An atlas of ozone chemical regimes has been constructed for 22 European cities. • O 3 sensitivity to road transport and industrial emissions differ when considering different ozone metrics and different periods of the year. • Counterproductive effects of precursors emission reductions on ozone are a concern where and when ozone concentrations are low. • On the contrary, significant reductions of precursor emissions are found to reduce the number of exceedances of the EU target limit value. • In most cities, mitigation of road transport yields larger benefit to ozone air pollution than mitigation of the industrial sector. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are pivotal in the progression toward sustainable transportation. However, a growing body of recent studies has challenged the often-assumed notion that electric vehicles are often considered to be net-zero emissions. These studies suggest that electric vehicles could potentially generate substantial emissions due to their reliance on fossil fuels to generate electricity, especially when receiving fast charging services. This phenomenon has been mitigated with the use of renewable energy sources in the power system. However, due to the intermittent nature of renewable energy sources, additional requirements have arisen. To address this situation, this paper presents an interdisciplinary study of collaborative fast-charging stations (FCS) and distributed renewable energy planning based on the interactions between traffic and power networks in order to increase the adoption rate of electric vehicles and reduce emissions caused by traffic and power systems. The locations and sizing of fast-charging stations, distributed photovoltaic generation, and renewable energy power supply for electric vehicles are determined in the proposed strategy through multi-objective integer programming. The proposed planning strategy considers heterogeneous electric vehicle driving range constraints, the operation security of the power distribution system, the reliability and expansion of the current power distribution, as well as different types of air pollutant classifications resulting from the charging behaviors. To guarantee the feasibility and accuracy of the planning results, an interactive algorithm is applied to solve the multi-objective integer model. Several cases are conducted to validate the proposed approach. The results demonstrate that the proposed planning strategy has good performance in the planning of fast-charging stations and distributed renewable energy integration. • A joint planning approach is proposed. • Optimize the locations and sizing of the fast-charging stations and distributed renewable energy. • Quantify different types of air pollutant emissions during charging services to promote the adoption of EVs and renewable energy. • An integer multi-objective model with an interactive algorithm is proposed. • The results demonstrate that the proposed method confers significant advantages to the application of EVs and renewable energy. [ABSTRACT FROM AUTHOR]

By implementing Principal Component Analysis (PCA) of multitemporal satellite data, this paper presents modeling solutions for air pollutant variation in three scenarios related to COVID-19 lockdown: pre, during, and after lockdown. Tropospheric NO 2 satellite data from Sentinel-5P was used. Two novel PCA-models were developed: Weighted Principal Component Analysis (WPCA) and Rescaled Principal Component Analysis (RPCA). Model results were tested for goodness-of-fit to empirical NO 2 data. The models were used to predict actual near-surface NO 2 concentrations. Model-predicted NO 2 concentrations were validated with NO 2 data acquired at ground monitoring stations. Besides, meteorological bias affecting NO 2 was assessed. It was found that the weather component had substantial impact on NO 2 built-ups, propitiating air pollutant decrease during lockdown and increase after. WPCA and RPCA models well fitted to observed NO 2. Both models accurately estimated near-surface NO 2 concentrations. Modeled NO 2 variation results evidenced the prolongated effect of the total lockdown (up to half a year). Model-predicted NO 2 concentrations were found to highly correlate with monitoring station NO 2 data collected on the ground. It is concluded that PCA is reliable in identifying and predicting air pollution variation patterns. The implementation of PCA is recommended when analyzing other pollutant gases. [Display omitted] • PCA is reliable for identifying and predicting air pollution variation. • WPCA and RPCA models well fitted observed NO 2. • Both models accurately estimated near-surface NO 2 concentrations. • Total lockdown had prolongated effect on NO 2 concentrations. • Weather conditions propitiated air pollutant decrease during lockdown and increase after. [ABSTRACT FROM AUTHOR]

The Air Quality Index (AQI), developed by the United States Environmental Protection Agency (USEPA), has been providing the public with crucial information regarding the status of contamination of the atmosphere for the past 45 years. Prior to introduction of the AQI, only a handful of metropolitan areas reported on air quality, and each region decided on its own metric. The inception of a single AQI helped homogenize the air quality metrics across the nation and indeed served as an important future template for other governmental and regulatory agencies across the world. The formulators had the foresight to recognize that our understanding of air pollution and its effects may change over time, which are likely to change regulatory limits. They used a dynamic framework to define the AQI, such that the broad definition or principle does not need to change with every change in regulatory limits or policy, and the fundamental goal of alerting the public to deleterious air quality is not affected. The establishment of the AQI increased public awareness of the importance of clean air and has helped muster support for air quality and emission regulations. The National Ambient Air Quality Standards (NAAQS) set forth by the USEPA provides acceptable levels of criteria pollutants – namely carbon monoxide, lead, nitrogen dioxide, ozone, particulate matter, and sulfur dioxide. A comparison of the actual levels, as compared to the regulatory limits (since the cessation of leaded gasoline, lead is no longer included in the index), are used as the basis for the AQI. As the regulatory limits change, so does the exact evaluation of the AQI, making it a living index. In this paper, we provide a historical overview of the Air Quality Index, the Federal Reference Methods (FRMs) vs. Federal Equivalent Methods (FEMs) for measuring them, and as an illustrative example, we discuss the air quality for Dallas-Ft. Worth, currently the fourth most populous metropolitan region in the United States, vis-a-vis the reported AQI. [Display omitted] • Origin and formulation of the Air Quality Index. • The pollutants forming the basis of the AQI and official methods to measure them. • Accessing back trajectories and other meteorological data to assess mesoscale transport. [ABSTRACT FROM AUTHOR]

In recent years, photocatalytic cement-based materials have demonstrated a positive impact on reducing air pollutants. However, challenges arise from the aggregation of photocatalysts and the intricate internal environment of cement-based materials, resulting in diminished photocatalytic efficiency. To address these issues, the TiO 2 @SiO 2 photocatalyst which reduced agglomeration and was easy to disperse was prepared by sol-gel method, and the TiO 2 @SiO 2 photocatalyst was added into γ-C 2 S carbonated cementitious material system by surface loading and blending to prepare the photocatalytic carbonation coating. In this paper, the TiO 2 @SiO 2 photocatalyst synthesized at solution pH 4.16 had the highest photocatalytic degradation efficiency of nitrogen oxides. The photocatalytic efficiency of the prepared carbonated coating was evaluated through the degradation efficiency of nitrogen oxide and rhodamine B. When the content of TiO 2 @SiO 2 was 7%, the photocatalytic carbonation coating had the highest photon removal efficiency for NO (0.17%), and the degradation rate for rhodamine B was 32.94% after 7 h illumination. The photocatalytic effect of the photocatalytic carbonated coating prepared with surface loaded TiO 2 @SiO 2 was better than that of the doped coating. When the surface loading was 1.5 g/m2, the photocatalytic efficiency of the coating on NO reached 0.81%, and the degradation rate of rhodamine B after 7 h illumination was 36.92%. This method introduced a novel concept for the future application of photocatalytic building materials, contributing to carbon sequestration and energy conservation efforts. • A novel photocatalytic carbonation coating has been prepared. • The novel coating had excellent photocatalytic degradation performance. • It provides a new idea for air purification and carbon reduction. [ABSTRACT FROM AUTHOR]

• The development of LUR approaches over the last decade was reviewed. • LCMs, mobile, and satellite data increase the spatiotemporal resolution of inputs. • Advanced statistics can better fit data with complex relationships and interactions. • LURs in the spatial form have been complemented by spatiotemporal models. • New developments to break through LUR methodologies were discussed. Land use regression (LUR) models are widely used in epidemiological and environmental studies to estimate humans' exposure to air pollution within urban areas. However, the early models, developed using linear regressions and data from fixed monitoring stations and passive sampling, were primarily designed to model traditional and criteria air pollutants and had limitations in capturing high-resolution spatiotemporal variations of air pollution. Over the past decade, there has been a notable development of multi-source observations from low-cost monitors, mobile monitoring, and satellites, in conjunction with the integration of advanced statistical methods and spatially and temporally dynamic predictors, which have facilitated significant expansion and advancement of LUR approaches. This paper reviews and synthesizes the recent advances in LUR approaches from the perspectives of the changes in air quality data acquisition, novel predictor variables, advances in model-developing approaches, improvements in validation methods, model transferability, and modeling software as reported in 155 LUR studies published between 2011 and 2023. We demonstrate that these developments have enabled LUR models to be developed for larger study areas and encompass a wider range of criteria and unregulated air pollutants. LUR models in the conventional spatial structure have been complemented by more complex spatiotemporal structures. Compared with linear models, advanced statistical methods yield better predictions when handling data with complex relationships and interactions. Finally, this study explores new developments, identifies potential pathways for further breakthroughs in LUR methodologies, and proposes future research directions. In this context, LUR approaches have the potential to make a significant contribution to future efforts to model the patterns of long- and short-term exposure of urban populations to air pollution. [ABSTRACT FROM AUTHOR]

The potential use of low-carbon renewable fuel molecules, such as short chain alcohols, as a substitute or extender for fossil fuels, offers an opportunity to address pollutant emissions from transport and the sustainability of energy sources. Moreover, it may help reduce pollutants detrimental to air quality and human health, of which particulate matter (PM) is a significant contributor. To this end, the pyrolysis of three renewable alcohol fuels, methanol, ethanol, and butanol, has been studied in a laminar flow reactor at a sample inlet temperature range of 869 0C to 1120 0C. All the tested fuels were injected into a nitrogen carrier gas stream at a fixed concentration of 10,000 ppm on a carbon atom basis. A range of pyrolysis temperatures and residence times were selected so as to gain insight into the pyrolytic decomposition of short chain alcohol fuels to intermediate species important to the subsequent formation of benzene rings, larger polycyclic aromatic hydrocarbons (PAH), and particulate matter. In this paper, the presence of ten intermediary species that may aid in the formation of benzene rings and the growth of PAHs were quantified, with an emphasis on probable routes of first ring formation from the alcohols of varying chain length. Gaseous samples were collected from the pyrolyser at different temperatures and residence times using a novel high-temperature air-cooled ceramic sampling probe. The identification and quantification of intermediate gaseous species were undertaken by Gas Chromatography-Flame Ionization Detection (GC-FID). During methanol pyrolysis, only a tenth of the supplied carbon was detected as hydrocarbon gaseous species (mainly methane), with no benzene found, highlighting that methanol pyrolysis does not readily result in polyaromatic hydrocarbons and soot. Ethanol and butanol pyrolysis produced substantial amounts of ethylene and acetylene, suggesting a role in benzene and soot formation. Uniquely, pyrolysis of the longest chain alcohol, butanol, produced appreciable levels of C3 and C4 hydrocarbons, in addition to C1 and C2 hydrocarbons, suggesting additional reaction pathways for benzene formation and growth in comparison with ethanol. • Pyrolysis of short chain alcohols and speciation of intermediate gas species. • Butanol pyrolysis is constrained more by temperature than by residence time. • Breakdown of ethanol and butanol was dominated by C-C cleavage. • Range of intermediates and potential benzene formation routes increased with carbon chain length. [ABSTRACT FROM AUTHOR]

Since the outbreak of COVID-19, microbial pollutants in the air have attracted people's attention. Existing air filters can only intercept microorganisms but cannot inactivate them. Thus, there is an urgent need to design air filters with antibacterial properties. In this study, we used vacuum-assisted filtration to adjust the pore structure of the traditional glass fiber air filter with cellulose nanofiber (CNF) and tempo-oxidized nanocellulose (TNF), and constructed a graded air filter (GCT) with gradient pore structure and Janus structure. At the same time, the addition of nanofibers increased the mechanical properties of the glass fiber air filter. Finally, the filters were endowed with good photothermal properties and stable antibacterial properties by adding antibacterial agents from previous studies (GCT/Ag-3). GCT/Ag-3 responded under near-infrared light, achieving a 99.9 % antibacterial rate against E. coli and S. aureus within 90s, and maintaining this high efficiency after 6 cycles, which provides a feasibility for the design of antibacterial air filter. [Display omitted] • A filtration aerogel with gradient hierarchical and Janus structures was prepared. • The structures formed improved mechanical property and efficiency of the filter. • The filter had highly effective antibacterial property (90s, 99.9 %). • The filter could remain high antibacterial efficiency (99.9 %) after 6 cycles. [ABSTRACT FROM AUTHOR]

Air pollution is a major environmental and public health issue. Each year, large amounts of particulate matter (PM) and other harmful pollutants are released into the atmosphere. Conventional polymer nanofiber filters lack the functionality to capture ultrafine PM. As a sustainable alternative, this work developed titanium dioxide (TiO 2) nanoparticle surface-modified cellulose nanofiber (CNF) aerogels for PM 2.5 filtration. CNFs were extracted via mechanical disintegration to diameters below 100 nm. The nanofibers were functionalized with 1.0–2.5 wt% TiO 2 nanoparticles using citric acid cross-linking. Cylindrical aerogels were fabricated by freezing and lyophilizing aqueous suspensions. Structural, morphological, thermal, and mechanical properties were characterized. TiO 2 modification increased density (11.8–19.7 mg/cm3), specific surface area (287–370 m2/g), and Young's modulus (33.5–125.5 kPa) but decreased porosity (99.6 %–97.7 %), pore size (20.2–15.6 nm) and thermal stability compared to unmodified cellulose aerogels. At 2.5 wt% loading, the optimized aerogels achieved 100 % absorption of 0.1–5 μm particulates owing to reduced pore size. Despite enhanced filtration capabilities, the modified CNF aerogels retained inherent biodegradability, degrading over 70 % within one month of soil burial. This pioneering research establishes TiO 2 functionalized CNF aerogels as promising sustainable alternatives to traditional petroleum-based air filters, representing an innovative approach to creating next-generation nanofiltration materials capable of effectively capturing fine and ultrafine particulate matter pollutants. [ABSTRACT FROM AUTHOR]