A critical review and prospect of NO2 and SO2 pollution over Asia: Hotspots, trends, and sources

An unexpected increase in PM2.5 levels in Xi'an during the COVID-19 pandemic restrictions: The interplay of anthropogenic and natural factors

This study investigated the variations in summer and winter PM2.5 concentrations and chemical composition in urban Xi'an before and during the COVID-19 pandemic restrictions. During the pandemic restrictions, summer daytime PM2.5 concentrations remained comparable to pre-pandemic levels, while a reduction was noted at nighttime. Conversely, winter experienced a significant increase in both daytime and nighttime PM2.5 concentrations. Chemical composition analysis revealed reductions in secondary inorganic ion concentrations but notable increases in crustal matter concentrations during the pandemic restrictions, particularly evident in winter. The reductions in secondary inorganic ion concentrations were likely due to decreased emissions of corresponding anthropogenic precursors in summer, while linked to reductions in transformation efficiencies in winter. The heightened crustal matter concentrations were likely attributed to increased contributions of long-range air mass transport from dusty regions, especially prevalent in winter. Source apportionment using positive matrix factorization analysis provided quantitative insights into the distinct source profiles contributing to PM2.5 before and during the pandemic restrictions, with secondary inorganic-rich sources decreasing and dust-related sources increasing during the pandemic restrictions. Additionally, combustion sources, primarily from coal and biomass burning, showed higher contributions during winter. In conclusion, this study underscores the complex interplay between anthropogenic and natural factors influencing PM2.5 levels in Xi'an. Efforts to mitigate PM2.5 pollution should prioritize reducing anthropogenic emissions and implementing measures to control dust emissions, particularly when dust-related sources significantly contribute to elevated PM2.5 concentrations. These findings provide valuable insights into developing effective strategies for addressing the PM2.5 pollution problem in Xi'an.

Enhanced room-temperature detection of ultra-low level nitrogen dioxide: Improved sensitivity, selectivity and stability through MXene-modified In2O3 microspheres

To address the increasing demand for wearable sensors, the development of gas sensors with high sensitivity and environmentally friendly power consumption for monitoring NO2 at room temperature (RT) is particularly promising. In this paper, porous In2O3 microspheres are prepared via a hydrothermal method, followed by the incorporation of 2D MXene solution to synthesize In2O3@MXene composites. After characterizing the microstructures and morphology of the In2O3@MXene composites, the influence of MXene on the microstructures and NO2 gas-sensing performance at RT is discussed in detail. The results indicate that a moderate amount of MXene greatly affects the energy band structure, chemisorbed and vacancy oxygen content, and the availability of reactive sites for oxygen and NO2, thereby affecting the gas-sensing performance of the In2O3@MXene sensors. Notably, the In2O3@10MXene sensor exhibits the highest response value of 24.98 to 4 ppm NO2 at RT, which is 5.90 times higher than that of In2O3 sensor (4.23). Furthermore, the In2O3@10MXene sensor still presents a response value of 2.83-500 ppb NO2 under RT, confirming an ultra-low ppb level detection limit to NO2 gas at RT. Additionally, the In2O3@10MXene sensor demonstrates favorable gas selectivity and long-term stability. The incorporation of an appropriate amount of MXene effectively enhances the gas-sensing performance of the In2O3@MXene sensors, attributed to the formation of a Schottky heterojunction, increased surface oxygen, and more reactive sites for oxygen and NO2 from MXene.

Gate Voltage Regulation of Surface Properties in Polyethylenimine-Doped Indium Oxide Transistors for Enhanced Detection of Low-Concentration NO2 at Room Temperature

Nitrogen dioxide (NO2), a toxic environmental pollutant, requires high-performance sensors for ppb-level detection. While indium oxide thin-film transistors (In2O3 TFTs) show promise, conventional devices require costly vacuum equipment, unlike solution-processed spin-coating, which is suitable for scalable fabrication. Channel doping enhances gas sensing performance but degrades transistor output current. This work introduces polyethylenimine (PEI) as the electron dopant for solution-processed In2O3 TFTs. PEI provides abundant electrons for NO2 interaction, but the limited current-driving capability of resistive sensors fundamentally restricts their detection sensitivity to such low-amplitude signals. Gate voltage-regulated surface electronic states in thin films significantly enhance the current-driving capability, enabling ultrasensitive NO2 detection down to subppb concentrations. The 1% PEI-doped In2O3 TFT demonstrates a saturation drain current of 0.065 mA, representing a 1.91-fold enhancement over the undoped counterpart (0.034 mA). Furthermore, the optimized 1% PEI: In2O3 TFT achieves a 23% response toward 10 ppb NO2.

Metal-organic frameworks (MOFs) toward SO2 detection

Developing technology that can precisely monitor specific air pollutants in diverse settings is essential to control emissions and ensure safe exposure limits are not exceeded. Metal-organic frameworks (MOFs) are crystalline organic-inorganic hybrid materials, which are promising candidates for SO2 detection. Their chemically mutable periodic structure confers outstanding surface area, thermal stability, and a well-defined pore distribution. Moreover, MOFs have exhibited extraordinary performance for SO2 capture. Therefore, research has focused on their possible applications for SO2 sequestration due to the selective and robust chemical and physical interactions of SO2 molecules within MOFs. The variable SO2 affinity presented by MOFs enables the adsorption mechanism and preferential adsorption sites to be resolved. However, for MOF-based SO2 detection, selective SO2 capture at shallow partial pressure (0.01-0.1 bar) is required. Thus, capturing SO2 at low concentration is crucial for SO2 detection, where textural properties of MOFs, mainly the pore-limiting diameter, are essential to achieve selective detection. In this review, we discuss the fundamental aspects of SO2 detection in MOFs, providing a step-by-step methodology for SO2 detection in MOFs. We hope this review can provide valuable background around SO2 detection in MOFs and inspire further research within this new and exciting field.

The Associations of Short-Term Ambient Nitrogen Dioxide Pollution with Major Cause-Specific Morbidities and the Modifying Effects by Ambient Temperature: A Nationwide Case-Crossover Study

Consistent evidence linking short-term ambient nitrogen dioxide (NO2) exposure to cause-specific morbidities is limited to asthma, and the modifying effect by ambient temperature is unclear in the context of climate change. This two-stage time-stratified case-crossover study investigated the morbidity risks and burden of short-term NO2 exposure on major cause-specific hospital admissions (HAs) for respiratory diseases (RDs), cardiovascular diseases (CVDs), and kidney diseases in 291 Chinese cities of prefecture-level or above during 2013-2017, based on 47,182,205 HA records. For each 10 μg/m3 increase in NO2 at lag01, the overall percent changes in HAs ranged from 1.15% for asthma to 3.28% for chronic renal failure. Compared to NO2 concentrations <25 μg/m3, excess risks in HAs associated with exposure to NO2 concentrations ≥25 μg/m3 at lag01 ranged from 2.14% (acute coronary syndrome, ACS) to 4.56% (acute bronchitis). Total attributable fractions associated with short-term NO2 exposure ranged from 2.01% for ACS to 4.82% for chronic renal failure. Associations of NO2 with major cause-specific HAs were generally stronger at a low temperature than at a high temperature. These findings suggest that more stringent NO2 quality guidelines and regulations are needed in the context of climate change to generate additional health benefits.

Use of a numerical model to evaluate SO2 absorption efficiency by sodium sulfite in packed and spray columns

Numerical modeling has been used extensively to simulate gas-liquid transfer of sulfur dioxide, assessing how operational parameters affect absorption efficiency in packed or spray columns. Despite individual studies on these contactors, comparative analyses on the same flue gas have been rare. This study uses a numerical model for both packed and spray columns to examine how parameters influence SO2 absorption by sodium sulfite, describing packed and spray columns, is used to investigate the influence of operational parameters on SO2 absorption by sodium sulfite. The model's predictions are validated against experimental data from an industrial pilot plant. Across varying conditions (L/G ratio, temperature, initial SO2 content or initial S(IV) concentration), the packed column achieves higher absorption efficiencies compared to the spray column, with lower assumed energy costs due to a reduced L/G ratio. Temperature proves to be a significant factor, decreasing absorption efficiency by approximately 40% between 40 and 70 °C. SO2 absorption efficiency declines with increasing concentrations of bisulfite and sulfite ions in the absorption solution, dropping to 50% at an S(IV) concentration of 2 kmol m-3 in the liquid phase. Considering the objective of producing a concentrated bisulfite solution and a clean gas, a two-column system is recommended: one for bisulfite solution concentration at acidic pH and the other for gas purification enhancement at basic pH.

Gaseous Air Pollutants and Lung Function in Fibrotic Interstitial Lung Disease (fILD): Evaluation of Different Spatial Analysis Approaches

Gaseous pollutants such as CO, NO2, O3, and SO2 are linked to adverse clinical outcomes in patients with fibrotic interstitial lung diseases (fILDs), particularly idiopathic pulmonary fibrosis. However, the effect of various exposure estimation methods on these findings remains unclear. This study aims to evaluate three spatial approaches─nearest neighbor (NN), inverse distance weighting (IDW), and Kriging─for estimating gaseous pollutant exposures and to assess how these methods affect health outcome estimates in fILD patients. A 10-fold cross-validation showed that Kriging had the lowest prediction error compared to NN and IDW, with RMSE for CO = 0.43 ppm (11%), O3 = 5.9 ppb (14%), SO2 = 2.7 ppb (12%), and NO2 = 7.6 ppb (9%), respectively. Kriging also excelled over other methods across wide spatial and temporal ranges, showing the highest spatial R2 for CO and O3 and the highest temporal R2 for SO2 and NO2. In a large cohort of patients with fILD, higher levels of CO, SO2, and NO2 exposure were associated with lower pulmonary function. The magnitude of association and its precision were higher in SO2 and CO estimated by the Kriging method. This study underscores Kriging as a robust method for estimating gaseous pollutant levels and offers valuable insights for future epidemiological studies.

Innovative process for sulphur recovery from waste incineration flue gases: production of marketable sodium bisulphite solution

This study presents an innovative process for recovering sulphur from hazardous waste incineration flue gases, designed to produce a marketable sodium bisulphite solution while ensuring complete SO2 removal. This new process is characterized by a double absorption strategy at two different pH levels. The first step, at an acidic pH, generates the desired bisulphite solution, while the second step, at a basic pH, produces the sulphite solution for recycling into the first step and ensures total SO2 removal. The process's performance and feasibility were evaluated on a laboratory scale using a batch reactor with synthetic gas. The parametric study focused on the initial sulphite concentration in the absorption solution and the reactor temperature. A removal efficiency exceeding 95% was achieved across all initial sulphite concentrations and temperature ranges, when the pH was maintained above 6. At pH 5, where bisulphites are the predominant sulphur species, the removal efficiency remained substantial at approximately 70%. The oxidation of sulphites/bisulphites by oxygen in the flue gases was minimal, with less than 5% conversion to sulphate. Additionally, pH-controlled experiments were conducted to optimize plant start-up procedures. For the basic reactor, starting with water and adjusting the pH to 8 during SO2 absorption effectively minimized sodium hydroxide consumption. In contrast, for the acidic reactor at pH 5, initiating the process with a concentrated sulphite solution resulted in more stable absorption rates. These findings underscore the process's potential for efficient sulphur recovery and highlight the importance of pH management in optimizing operational stability and chemical consumption.

Outdoor air pollution exposure and the risk of type 2 diabetes mellitus: A systematic umbrella review and meta-analysis

The association between different air pollutants and Type 2 Diabetes Mellitus (T2DM) is a growing topic of interest in public health research. This umbrella review and meta-analysis aimed to consolidate current literature on the association between various outdoor air pollutants and T2DM. Subgroups and dose-response relationships were also analyzed to further quantify the association, especially by the factors such as the type of pollutants, duration of exposure, and geographical variation, etc. A thorough literature search of three databases revealed a total of 71 records for umbrella review and 1524 records for meta-analysis where 8 studies were included in the final review of umbrella review and 46 studies for meta-analysis. The evaluation of the study's quality in umbrella review and meta-analysis were conducted using the AMSTAR 2 criteria and the Newcastle-Ottawa Scale (NOS), respectively. Exposure to Particulate Matter (PM) 2.5, PM10, Nitrogen dioxides (NO2) and Ozone (O3) were significantly associated with the risk of T2DM [OR = 1.12 (95% Confidence Interval (CI): 1.09, 1.15), 1.12 (95% CI: 1.06, 1.18), 1.09 (95%CI: 1.07, 1.12), 1.05 (95%CI: 1.03, 1.08), respectively] and subgroup analysis further revealed that PM2.5, PM10, and NO2 associations were confounded by factors such as ages, study design, regions of exposure and air pollution concentration levels. Lastly, only exposure to PM10 had a significant dose-response relationship with the risk of T2DM (p-value = 0.000). These findings further emphasized the need for standardized methods in conducting air pollution research and additional research on other air pollutants to further explore the relationships between these air pollutants and T2DM.

Influence of top-down adjusted upwind emissions on PM2.5 concentrations: The case of long-range transport in South Korea

Understanding the impact of long-range transport (LTI) on concentrations of particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) is crucial for accurately assessing air quality in affected areas. We developed an integrated approach combining emissions adjustment and model bias correction to improve the replication of observed PM2.5 concentrations and estimate LTI contributions in South Korea, a representative downwind area in Northeast Asia. Using ground observations, we first adjusted emissions of sulfur dioxide, nitrogen oxides, and primary PM2.5 in China, which is upwind of South Korea. Refining factors were applied to further reduce systematic biases in estimating upwind PM2.5 concentrations and enhance LTI calculations. The results demonstrated that our approach reduced both random and systematic biases in simulated PM2.5 concentrations in China, achieving a correlation coefficient of 0.99 between the observed and simulated concentrations. These results were used to refine LTI estimates in South Korea, leading to reduced mean bias between observed and simulated concentrations. The improvements aligned well with observed PM2.5 concentration trends in both countries, highlighting the critical role of accurate LTI estimates in understanding air pollution dynamics in South Korea. Moreover, this approach was effective for assessing both short- and long-term population exposure, enhancing the accuracy of identifying "unhealthy" PM2.5 days and calculating population-weighted concentrations in South Korea. By analyzing PM2.5 concentrations, long-term trends, changes in local emission impacts, and population exposure in areas influenced by long-range transport, this method has substantial potential for broader applicability.

Adsorption Removal of NO2 Under Low-Temperature and Low-Concentration Conditions: A Review of Adsorbents and Adsorption Mechanisms

The efficient mitigation of harmful nitrogen oxides (NOx) under ambient conditions remains a challenging task. Selective adsorption offers a viable solution for the capture of low-concentration NOx from the polluted stream at low temperatures. This review summarizes recent progress in the development of NO2 adsorbents, delves into the understanding of adsorption mechanisms, and discusses the criteria for evaluating their performance. First, the present NO2 adsorbents are categorized according to their distinct characteristics. This review then provides insights into the mechanisms of adsorption, highlighting the interaction between active sites and NO2, drawing from both experimental and theoretical research. The performance of these adsorbents is also assessed, focusing on their capacity, reusability, stability and selectivity. Finally, perspectives are proposed to address the significant challenges and explore potential advancements for NO2 adsorbents, aiming to enhance their suitability for diverse practical application scenarios.

Te@Se Core-Shell Heterostructures with Tunable Shell Thickness for Ultra-Stable NO2 Detection

An effective long-term nitrogen dioxide (NO2) monitoring at trace concentration is critical for protecting the ecological environment and public health. Tellurium (Te), as a recently discovered 2D elemental material, is promising for NO2 detection because of its suitable band structure for gas adsorption and charge mobility. However, the high activity of Te leads to poor stability in ambient and harsh conditions, limiting its application as a gas-sensitive material. Herein, 2D single-elemental Te@Se heterostructures with a core-shell structure are prepared using a solvothermal method. The Te@Se heterostructures demonstrate an extremely high response of 622% to 1 ppm of NO2 at room temperature, with ultrafast response/recovery times of 10 s/30 s. Moreover, the core-shell heterostructures exhibit excellent stability in NO2 sensing performance over a period of 90 days. The success relies on the ultrathin Se shell with a thickness of 4-6 nm on Te, which enables the efficient redistribution and transport of interfacial charges. These findings reveal the potential of single-element core-shell heterojunctions to achieve high-performance gas sensing, paving the way for advancements in NO2 detection materials.

Spontaneous Catalytic Reaction of a Surfactant in the Interfacial Microenvironment of Colloidal Gold Nanoparticles

The performance of nanomaterials is significantly determined by the interfacial microenvironment, in which a surfactant plays an essential role as the adsorbent, but its involvement in the interfacial reaction is often overlooked. Here, it was discovered that citrate and ascorbic acid, the two primarily used surfactants for colloidal gold nanoparticles (Au NPs), can spontaneously undergo catalytic reaction with trace-level nitrogenous residue under ambient environment to form oxime, which is subsequently cleaved to generate CN- or a compound containing the -CN group. Such a catalytic reaction shows wide universality in both reactants, including various carbonaceous and nitrogenous sources, and metal catalysts, including Au, Ag, Fe, Cu, Ni, Pt, and Pd NPs. Furthermore, with the removal of this reaction, adsorbed CO with diverse adsorption configurations was observed via surface-enhanced Raman spectroscopy under ambient conditions without an applied potential. Our work highlights the non-negligible significance of surfactants in interfacial microenvironments and provides crucial insights into the fundamental understanding of interfacial chemical reactions.

Nanogenerators for gas sensing applications

Gas sensors are now widely employed in many industries due to the rapid speed of industrialization and the growth of the Internet of Things. However, the wearability and mobility of traditional gas sensors are limited by their high reliance on external power sources. Nanogenerators (NGs) can compensate for their power source limitations when paired with gas sensors by transforming the environment's widely dispersed low-frequency energy into electrical energy, allowing for self-powered gas detection. The paper thoroughly examines the advancements made in the field of NG-based self-powered gas sensor research in recent years. A systematic description is given of the two main types of NG-based self-powered gas sensors. Lastly, the evolution of sensor use in a few typical gas sensing applications is highlighted, and the field's future development trend is anticipated.

Development and Field Deployment of a ppb-Level SO2/NO2 Dual-Gas Sensor System for Agricultural Early Fire Identification

Sulfur dioxide (SO2) and nitrogen dioxide (NO2) are chemical indicators of crop straw combustion as well as significant atmospheric pollutants. It is challenging to promptly detect natural "wildfires" during agricultural production, which often lead to uncontrollable and substantial economic losses. Moreover, both "wildfires" and artificial "straw burning" practices pose severe threats to the ecological environment and human health. Consequently, developing sensors capable of rapid and high-precision quantitative analysis of SO2/NO2 is essential and urgent for detecting early fires in agricultural activities. Here, we demonstrate an incoherent broadband cavity-enhanced absorption spectroscopy (IBBCEAS) sensing system utilizing a 366 nm ultraviolet light emitting diode, designed for real-time, high-precision monitoring of SO2 and NO2 and is used for early fire detection validation. The optical resonant cavity is constructed within a 60 mm cage system mechanical structure, achieving a maximum optical path length of nearly 2 km with a length of ∼460 mm. The output light carrying information about the species and concentration of the analyte molecules is coupled into the miniaturized grating spectrometer via a fiber, and continuous spectral fitting and concentration inversion are performed on the computer. We propose a spectral analysis and concentration inversion model based on an improved particle swarm optimization-support vector machine (IPSO-SVM) algorithm. By discrimination of the absorption spectral characteristics of SO2/NO2, we achieve superior prediction accuracy. Experimental results indicate that the detection limits of SO2 and NO2 under the optimized averaging time are 77.5 parts per billion by volume (ppbv) and 0.037 ppbv, respectively. The field deployment of the sensor in scenarios such as continuous outdoor air pollution monitoring, in situ combustion feature identification, and early fire mobile detection has demonstrated the superior reliability and sensitivity of this sensor system.

Comprehensive Investigation of Epoxy Adhesives for Structural Applications in Saudi Arabia: Mechanical Performance, Environmental Impacts, and Analysis on Health

Epoxy adhesives possess excellent mechanical properties, durability, and stability in harsh environments, making them suitable for producing engineering materials. This study selects four commercially available epoxy adhesives in Saudi Arabia: Epotec YD 128; Sikadur®-52 LP; Sikadur®-31 CF; and Sikadur®-42 MP Slow. Firstly, a comparison of their storage, application, and service temperatures was made, detailing the hazard identification and prevention measures established in accordance with the Occupational Safety and Health Administration (OSHA) guidelines. Subsequently, test samples of the four adhesives were produced, and tensile, compressive, and shear tests were conducted to compare their fundamental mechanical properties. Finally, a gas analyzer assessed the major harmful gases emitted by these epoxy adhesives 120 min after mixing the epoxy resins and curing agents. The results show that Sika 42 exhibits the highest tensile and compressive strengths among other types of adhesives, reaching 75.7 MPa and 133.8 MPa, respectively. It also has the longest pot life of 48 min at elevated temperatures (40 °C), making it suitable for the climatic conditions in Saudi Arabia. However, as a three-component adhesive, its application is complex and associated with the most identified hazards. Sika 31 presents a tensile modulus of up to 10.4 GPa, at least 3.8 times higher than the other adhesives, making it practical for controlling tensile deformation. Additionally, its ultimate shear strain reaches 10.7%, at least 6.6 times higher than the other samples, highlighting its suitability for constructing ductile bonds. After mixing of epoxy resins with curing agents, the presence of NO2 and SO2 were detected. However, no harmful gases were detected after 120 min, possibly due to the complete curing of the adhesives.

COVID-19 lockdown measures affect polycyclic aromatic hydrocarbons distribution and sources in sediments of Chaohu Lake, China

The COVID-19 pandemic has profoundly impacted human activities and the environment globally. The lockdown measures have led to significant changes in industrial activities, transportation, and human behavior. This study investigates how the lockdown measures influenced the distribution of polycyclic aromatic hydrocarbons (PAHs) in the sediments of Chaohu Lake, a semi-enclosed lake. Surface sediment samples were collected in summer of 2020 (lockdown have just been lifted) and 2022 and analyzed for 16 priority PAHs. The range of ΣPAHs concentrations remained similar between 2020 (158.19-1693.64 ng·g-1) and 2022 (148.86-1396.54 ng·g-1). Among the sampling sites, the west lake exhibited similar PAHs concentrations characteristics over the two years, with higher levels observed in areas near Hefei City. However, the east lake exhibited increased ΣPAHs concentrations in 2022 compared to 2020, especially the area near ship factory. PAHs source analysis using principal component analysis-multiple linear regression (PCA-MLR) revealed an increased proportion of petroleum combustion sources in 2022 compared to 2020. The isotope analysis results showed that organic matter (OM) sources in the western lake remained relatively stable over the two years, with sewage discharge dominating. In contrast, the eastern lake experienced a shift in OM sources from sewage to C3 plants, potentially contributing to the increased PAH levels observed in the eastern lake sediments. Ecological risk assessment revealed low to moderate risk in both 2020 and 2022. Health risk evaluation indicated little difference in incremental lifetime cancer risk (ILCR) values between the two years, with only benzo[a]pyrene (BaP) posing a high risk among the carcinogenic PAHs. Children generally faced higher health risks compared to adults. This study reveals pandemic-induced changes in PAH pollution and sources in lake sediments, offering new insights into the impact of human activities on persistent organic pollutants, with implications for future pollution control strategies.

A real-time assessment of hazardous atmospheric pollutants across cities in China and India

China and India are two of the fastest-growing developing economies covering about 35 % of the world's population. Due to the extensive prevalence of air pollution across cities in China and India, contemporary assessment of atmospheric pollution through real-time and remote sensing observations is inadequate. The study aims to determine the spatial distribution and temporal variation of hazardous atmospheric pollutants across cities in China (Shanghai, Nanjing, Jinan, Zhengzhou and Beijing) and India (Kolkata, Asansol, Patna, Kanpur and Delhi). Ground observation data on CO, O3, PM2.5, PM10, NO2 and SO2 along with remote sensing data on AOD, CO, O3, BC, NO2, SO2 and dust surface mass concentrations are used to assess atmospheric pollution. This study examines daily, zonal and longitudinal pollutant distributions using Sentinel-5 P data and surface mass concentrations over the vertical column evaluated from NASA satellite data. The Mann-Kendall test and relative change methods have been implemented to assess pollutant trends while Sen's Slope identifies the magnitude of change. The similarity test and data validation methods including NRMSE, PC and MBias have been employed to ensure consistency in analysing annual trends for each air pollutant in the datasets. Additionally, multiple correlation matrix analysis has been used to examine the associations among different pollutants from both datasets based on their annual averages. Remote sensing data reveals that eastern China and north-eastern India have the highest aerosol, BC, CO, NO2 and SO2 while western China and southern India lowest. Dust peaks in the west while O3 levels are highest in the northern part of China and India. Ground observation data indicates that Chinese cities have higher annual mean SO2 and O3 concentrations with yearly declines in PM2.5, PM10, NO2, SO2 and CO notably SO2. Indian cities witnessed overall increases in PM2.5, PM10, NO2 and SO2 from 2012 to 2019 with a slight decline in 2020 followed by a resurgence in 2023. The findings provide insights for implementing regional policy measures to reduce air pollution based on changes in pollutant behaviour. The study suggests that addressing atmospheric pollutants, particularly NO2, CO, PM2.5, PM10, and SO2 requires a comprehensive environmental policy framework involving central and state governments and enforcing stringent environmental protection laws.

Air quality in different urban hotspots in a metropolitan city in India and the environmental implication

This research study investigates hourly data on concentrations of five major air pollutants such as particulate matter (PM10, PM2.5) and gaseous pollutants (SO2, NO2, CO) measured during 2022 at four hotspot sites (industrial site, traffic site, commercial site, harbour, and one residential site) in Chennai, India. The analysis encompasses temporal variations spanning annual, seasonal, and diurnal variations in the pollutants. Notably, PM10 and CO emerge as the predominant pollutants, with the highest concentrations at industrial and traffic sites (PM10: 67.64 ± 40.77 µg/m3, CO: 1.41 ± 0.84 mg/m3; traffic site: PM10: 58.67 ± 20.05 µg/m3, CO: 0.99 ± 0.57 mg/m3). Seasonal dynamics reveal prominent winter spikes in particulate matter (PM10, PM2.5) and carbon monoxide (CO) concentrations, while nitrogen dioxide (NO2) and sulphur dioxide (SO2) levels peak during the summer season, particularly in the harbour area. The proximity to roadways exerts a discernible influence on diurnal patterns, with traffic sites showcasing broader rush hour peaks compared to sharper spikes observed at other sites. Furthermore, distinct bimodal patterns are evident for PM10 and PM2.5 concentrations in residential and harbour areas. A common lognormal distribution pattern is identified across the studied sites, suggesting consistent air quality trends despite contrasting locations. The conditional probability function (CPF) is used in conjunction with local meteorological conditions for identifying key pollution sources in each location. The implementation of polar plots emphasizes industries as principal local sources of pollution, at industrial sites significantly contributing to PM10, SO2, and NO2 concentrations under specific wind conditions. The main objective of the present study is to facilitate a good understanding of pollutant dynamics, pollution sources, and their intricate interplay with meteorological factors, thereby contributing to the formulation and implementation of effective air pollution control and mitigation strategies.

Bioavailability and ecological risk assessment of metal pollutants in ambient PM2.5 in Beijing

Metal pollutants in fine particulate matter (PM2.5) are physiologically toxic, threatening ecosystems through atmospheric deposition. Biotoxicity and bioavailability are mainly determined by the active speciation of metal pollutants in PM2.5. As a megacity in China, Beijing has suffered severe particulate pollution over the past two decades, and the health effects of metal pollutants in PM2.5 have received significant attention. However, there is a limited understanding of the active forms of metals in PM2.5 and their ecological risks to plants, soil or water in Beijing. It is essential that the ecological risks of metal pollutants in PM2.5 are accurately evaluated based on their bioavailability, identifying the key pollutants and revealing historic trends to future risks control. A two-year project measured the chemical speciation of pollution elements (As, Cd, Cu, Cr, Ni, Mn, Pb, Sb, Sr, Ti, and Zn) in PM2.5 in Beijing, in particular their bioavailability, assessing ecological risks and identifying key pollutants. The mass concentrations of total and active species of pollution elements were 199.12 ng/m3 and 114.97 ng/m3, respectively. Active fractions accounted for 57.7 % of the total. Cd had the highest active proportion. Based on the risk assessment code (RAC), most pollution elements except Ti had moderate or high ecological risk, with RAC exceeding 30 %. Cd, with an RAC of 70 %, presented the strongest ecological risk. Comparing our data with previous research shows that concentrations of pollution elements in PM2.5 in Beijing have decreased over the past decade. However, although the total concentrations of Cd in PM2.5 have decreased by >50 % over the past decade, based on machine model simulation, its ecological risk has reduced by only 10 %. Our research shows that the ecological risks of pollution elements remain high despite their decreasing concentrations. Controlling the active species of metal pollutants in PM2.5 in Beijing in the future is vital.

Relationship between short-term exposure to sulfur dioxide and emergency ambulance dispatches due to cardiovascular disease

Background

The relationship between sulfur dioxide (SO2) and cardiovascular disease (CVD) remains inconclusive. We aimed to clarify the association between short-term exposure to SO2 and emergency ambulance dispatches (EADs) due to CVD.

Methods

We collected daily data on the number of EADs due to CVD, air pollutants, and meteorological factors between October 2013 and June 2018 in Guangzhou, China. We used the quasi-Poisson generalized additive model combined with a distributed lag nonlinear model to estimate the short-term effect of SO2 on EADs due to CVD in multivariable models. Subgroup and sensitivity analyses were also performed.

Results

A total of 37,889 EADs due to CVD were documented during the study period. The average daily SO2 concentration was 12.5 μg/m3. A significant relationship between SO2 and EADs due to CVD was found, with a relative risk of 1.04 (95% confidence interval: 1.02, 1.06) with each 10 μg/m3 increment of SO2 at lag 0-1. The relationship was stronger in males, for participants aged ≥65 years, and in the cold season; however, no significant modification by subgroup was found in the association between SO2 and EADs due to CVD. Similar results from sensitivity analyses to the main findings were observed.

Conclusions

Short-term exposure to SO2 was significantly associated with increased EADs due to CVD.

Spatial and temporal changes of air quality in Shandong Province from 2016 to 2022 and model prediction

This study investigates the spatial and temporal dynamics of air quality in Shandong Province from 2016 to 2022. The Air Quality Index (AQI) showed a seasonal pattern, with higher values in winter due to temperature inversions and heating emissions, and lower values in summer aided by favorable dispersion conditions. The AQI improved significantly, decreasing by approximately 39.4 % from 6.44 to 3.90. Coastal cities exhibited better air quality than inland areas, influenced by industrial activities and geographical features. For instance, Zibo's geography restricts pollutant dispersion, resulting in poor air quality. CO levels remained stable, while O3 increased seasonally due to photochemical reactions in summer, with correlation coefficients indicating a strong positive correlation with temperature (r = 0.65). Winter saw elevated NO2 levels linked to heating and vehicular emissions, with an observed increase in correlation with AQI (r = 0.78). PM2.5 and PM10 concentrations were higher in colder months due to heating and atmospheric dust, showing a significant decrease of 45 % and 40 %, respectively, over the study period. Predictive modeling forecasts continued air quality improvements, contingent on sustained policy enforcement and technological advancements. This approach provides a comprehensive framework for future air quality management and improvement.

From port to planet: Assessing NO2 pollution and climate change effects with Sentinel-5p satellite imagery in maritime zones

The growing effects of climate change on Malaysia's coastal ecology heighten worries about air pollution, specifically caused by urbanization and industrial activity in the maritime sector. Trucks and vessels are particularly noteworthy for their substantial contribution to gas emissions, including nitrogen dioxide (NO2), which is the primary gas released in port areas. The application of advanced analysis techniques was spurred by the air pollution resulting from the combustion of fossil fuels such as fuel oil, natural gas and gasoline in vessels. The study utilized satellite photos captured by the Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5P satellite to evaluate the levels of NO2 gas pollution in Malaysia's port areas and exclusive economic zone. Before the COVID-19 pandemic, unrestricted gas emissions led to persistently high levels of NO2 in the analyzed areas. The temporary cessation of marine industry operations caused by the pandemic, along with the halting of vessels to prevent the spread of COVID-19, resulted in a noticeable decrease in NO2 gas pollution. In light of these favourable advancements, it is imperative to emphasize the need for continuous investigation and collaborative endeavours to further alleviate air contamination in Malaysian port regions, while simultaneously acknowledging the wider consequences of climate change on the coastal ecology. The study underscores the interdependence of air pollution, maritime activities and climate change. It emphasizes the need for comprehensive strategies that tackle both immediate environmental issues and the long-term sustainability and resilience of coastal ecosystems in the context of global climate challenges.

Geospatial modelling of ambient air pollutants and chronic obstructive pulmonary diseases at regional scale in Pakistan

Pakistan is among the South Asian countries mostly vulnerable to the negative health impacts of air pollution. In this context, the study aimed to analyze the spatiotemporal patterns of chronic obstructive pulmonary disease (COPD) incidence and its relationship with air pollutants including aerosol absorbing index (AAI), carbon monoxide, sulfur dioxide (SO2), and nitrogen dioxide. Spatial scan statistics were employed to identify temporal, spatial, and spatiotemporal clusters of COPD. Generalized linear regression (GLR) and random forest (RF) models were utilized to evaluate the linear and non-linear relationships between COPD and air pollutants for the years 2019 and 2020. The findings revealed three spatial clusters of COPD in the eastern and central regions, with a high-risk spatiotemporal cluster in the east. The GLR identified a weak linear relationship between the COPD and air pollutants with R2 = 0.1 and weak autocorrelation with Moran's index = -0.09. The spatial outcome of RF model provided more accurate COPD predictions with improved R2 of 0.8 and 0.9 in the respective years and a very low Moran's I = -0.02 showing a random residual distribution. The RF findings also suggested AAI and SO2 to be the most contributing predictors for the year 2019 and 2020. Hence, the strong association of COPD clusters with some air pollutants highlight the urgency of comprehensive measures to combat air pollution in the region to avoid future health risks.

NO2-Sensitive SnO2 Nanoparticles Prepared Using a Freeze-Drying Method

The n-type semiconductor SnO2 with a wide band gap (3.6 eV) is massively used in gas-sensitive materials, but pure SnO2 still suffers from a high operating temperature, low response, and tardy responding speed. To solve these problems, we prepared small-sized pure SnO2 using hydrothermal and freeze-drying methods (SnO2-FD) and compared it with SnO2 prepared using a normal drying method (SnO2-AD). The sensor of SnO2-FD had an ultra-high sensitivity to NO2 at 100 °C with excellent selectivity and humidity stability. The outstanding gas sensing properties are attributed to the modulation of energy band structure and the increased carrier concentration, making it more accessible for electron exchange with NO2. The excellent gas sensing properties of SnO2-FD indicate its tremendous potential as a NO2 sensor.

Treatment and Resource Utilization of Gaseous Pollutants in Functionalized Ionic Liquids

With the rapid development of science, technology, and the economy of human society, the emission problem of gas pollutants is becoming more and more serious, which brings great pressure to the global ecological environment. At the same time, the natural resources that can be exploited and utilized on Earth are also showing a trend of exhaustion. As an innovative and environmentally friendly material, functionalized ionic liquids (FILs) have shown great application potential in the capture, separation, and resource utilization of gaseous pollutants. In this paper, the synthesis and characterization methods of FILs are introduced, and the application of FILs in the treatment and recycling of gaseous pollutants is discussed. The future development of FILs in this field is also anticipated, which will provide new ideas and methods for the treatment and recycling of gaseous pollutants and promote the process of environmental protection and sustainable development.

Air quality in a revitalized special economic zone at the center of an urban monocentric agglomeration

In this study, we have examined the air quality within a revitalized, post-industrial urban area in Łódź, Poland. The use of Dron technology with mobile measurement equipment allowed for accurate assessment of air quality (particulate matter and gaseous pollutants) and factors influencing air quality (wind speed and direction) on a local scale in an area of 0.18 km2 and altitudes from 2 to 50 m. The results show that the revitalization carried out in the Lodz special economic zone area contributed to eliminate internal air pollution emitters through the use of ecological and effective heat sources. The exceedances permissible concentration values were local, and concerned mainly the higher measurement zones of the troposphere (more than 30 m above ground level). In the case of gaseous pollutants, higher wind speeds were associated with a decrease in the concentration of SO2 and an increase in H2S concentration. In both cases, the wind contributed to the occurrence of local areas of accumulation of these gaseous pollutants in the spaces between buildings or wooded areas.

Spatio-temporal evaluation of air pollution using ground-based and satellite data during COVID-19 in Ecuador

The concentration of gases in the atmosphere is a topic of growing concern due to its effects on health, ecosystems etc. Its monitoring is commonly carried out through ground stations which offer high precision and temporal resolution. However, in countries with few stations, such as Ecuador, these data fail to adequately describe the spatial variability of pollutant concentrations. Remote sensing data have great potential to solve this complication. This study evaluates the spatiotemporal distribution of nitrogen dioxide (NO2) and ozone (O3) concentrations in Quito and Cuenca, using data obtained from ground-based and Sentinel-5 Precursor mission sources during the years 2019 and 2020. Moreover, a Linear Regression Model (LRM) was employed to analyze the correlation between ground-based and satellite datasets, revealing positive associations for O3 (R2 = 0.83, RMSE = 0.18) and NO2 (R2 = 0.83, RMSE = 0.25) in Quito; and O3 (R2 = 0.74, RMSE = 0.23) and NO2, (R2 = 0.73, RMSE = 0.23) for Cuenca. The agreement between ground-based and satellite datasets was analyzed by employing the intra-class correlation coefficient (ICC), reflecting good agreement between them (ICC ≥0.57); and using Bland and Altman coefficients, which showed low bias and that more than 95% of the differences are within the limits of agreement. Furthermore, the study investigated the impact of COVID-19 pandemic-related restrictions, such as social distancing and isolation, on atmospheric conditions. This was categorized into three periods for 2019 and 2020: before (from January 1st to March 15th), during (from March 16th to May 17th), and after (from March 18th to December 31st). A 51% decrease in NO2 concentrations was recorded for Cuenca, while Quito experienced a 14.7% decrease. The tropospheric column decreased by 27.3% in Cuenca and 15.1% in Quito. O3 showed an increasing trend, with tropospheric concentrations rising by 0.42% and 0.11% for Cuenca and Quito respectively, while the concentration in Cuenca decreased by 14.4%. Quito experienced an increase of 10.5%. Finally, the reduction of chemical species in the atmosphere as a consequence of mobility restrictions is highlighted. This study compared satellite and ground station data for NO2 and O3 concentrations. Despite differing units preventing data validation, it verified the Sentinel-5P satellite's effectiveness in anomaly detection. Our research's value lies in its applicability to developing countries, which may lack extensive monitoring networks, demonstrating the potential use of satellite technology in urban planning.

Air pollution analysis in Northwestern South America: A new Lagrangian framework

This study examines the spatiotemporal variations of PM2.5, PM10, SO2, O3, NO, and NO2 concentrations in Northwestern South America (NWSA). We assess the efficacy of existing policies, identify underlying phenomena, and highlight areas for further research. Significant findings have emerged by analyzing reanalysis and in-situ data, employing the WRF-Chem model, and utilizing a new Lagrangian framework designed to overcome some drawbacks common to analysis of pollution Long-Range Transport. Wildfires in the first half of the year and volcanic activity (for SO2) in July-August contribute to over 90 % of the pollutant's advection, leading to high pollution levels in urban areas. SO2 volcanic emissions contribute to secondary PM, explaining the peak in PM concentrations in Cali in July. In the second half of the year, pollutant behavior varies based on factors such as city characteristics, vehicular-volume, air temperature, wind speed, and boundary layer height, and O3 is influenced by solar radiation and the NO/NO2 ratio. Diurnal variations of PM and NOx correlate with vehicular density, SO2 with industrial activity, and O3 depends on solar radiation. Trend analysis reveals decreasing PM10 levels except in three Cundinamarca cities and Cali suggesting the need to implement/evaluate control plans in those locations. Although data is limited, NO and NO2 levels show an increasing trend due to the rising number of vehicles. SO2 levels are decreasing, except in Cali, potentially influenced by the nearby industrial and polluted city of Yumbo. O3 displays a downward trend in most cities, except Bogotá, due to the NO/NO2 ratio favoring O3 increase. These findings provide a starting point for further research to deepen our understanding of NWSA air pollution. Such investigations are essential before modifying existing policies or enacting new ones. Collaborative efforts at the international, regional, and inter-city levels are crucial for effective air quality management.

Association Between Air Pollution and Cardiovascular Disease Hospitalizations in Lanzhou City, 2013-2020: A Time Series Analysis

Extensive evidence has shown that air pollution increases the risk of cardiovascular disease (CVD) admissions. We aimed to explore the short-term effect of air pollution on CVD admissions in Lanzhou residents and their lag effects. Meteorological data, air pollution data, and a total of 309,561 daily hospitalizations for CVD among urban residents in Lanzhou were collected from 2013 to 2020. Distributed lag non-linear model was used to analyze the relationship between air pollutants and CVD admissions, stratified by gender, age, and season. PM2.5, NO2, and CO have the strongest harmful effects at lag03, while SO2 at lag3. The relative risks of CVD admissions were 1.0013(95% CI: 1.0003, 1.0023), 1.0032(95% CI: 1.0008, 1.0056), and 1.0040(95% CI: 1.0024, 1.0057) when PM2.5, SO2, and NO2 concentrations were increased by 10 μg/m³, respectively. Each 1 mg/m3 increase in CO concentration was associated with a relative risk of cardiovascular hospitalization of risk was 1.0909(95% CI: 1.0367, 1.1479). We observed a relative risk of 0.9981(95% CI: 0.9972, 0.9991) for each 10 μg/m³ increase in O3 for CVD admissions at lag06. We found a significant lag effects of air pollutants on CVD admissions. NO2 and CO pose a greater risk of hospitalization for women, while PM2.5 and SO2 have a greater impact on men. PM2.5, NO2, and CO have a greater impact on CVD admissions in individuals aged <65 years, whereas SO2 affects those aged ≥65 years. Our research indicates a possible short-term impact of air pollution on CVD. Local public health and environmental policies should take these preliminary findings into account.

A critical review of sustainable application of biochar for green remediation: Research uncertainty and future directions

Biochar, a carbon-rich material produced from the pyrolysis of organic biomass, has gained significant attention as a potential solution for sustainable green remediation practices. Several studies analyze biomass-derived biochar techniques and environmental applications, but comprehensive assessments of biochar limitations, uncertainty, and future research directions still need to be improved. This critical review aims to present a comprehensive analysis of biochar's efficacy in environmental applications, including soil, water, and air, by sequentially addressing its preparation, application, and associated challenges. The review begins by delving into the diverse methods of biochar production, highlighting their influence on physical and chemical properties. This review explores the diverse applications of biochar in remediating contaminated soil, water, and air while emphasizing its sustainability and eco-friendly characteristics. The focus is on incorporating biochar as a remediation technique for pollutant removal, sequestration, and soil improvement. The review highlights the promising results obtained from laboratory-scale experiments, field trials, and case studies, showcasing the effectiveness of biochar in mitigating contaminants and restoring ecosystems. The environmental benefits and challenges of biochar production, characterization, and application techniques are critically discussed. The potential synergistic effects of combining biochar with other remediation methods are also explored to enhance its efficacy. A rigorous analysis of the benefits and drawbacks of biochar for diverse environmental applications in terms of technical, environmental, economic, and social issues is required to support the commercialization of biochar for large-scale uses. Finally, future research directions and recommendations are presented to facilitate the development and implementation of biochar-based, sustainable green remediation strategies.

Impact of NO2 emissions from household heating systems with wall-mounted gas stoves on indoor and ambient air quality in Chinese urban areas

Nitrogen dioxide (NO2) has been discussed as a typical indoor pollutant for decades. As an increasingly popular heating method, household heating system (HHS) with wall-mounted natural gas stoves has led to a continuous increase in the emission of NO2. The absence of legal regulations and strict limits for NO2 emissions from wall-mounted gas stoves has led to a significant exceedance of indoor NO2 concentrations beyond the permissible value. However, this issue is rarely taken into consideration. In this study, we present the first report on NO2 emissions from wall-mounted gas stoves for household heating and their impact on indoor and ambient air quality in Chinese urban areas based on in-situ measurements and numerical simulations. On heating days, the observed indoor NO2 concentration is within 80-200 μg/m3, much higher than the outdoor atmospheric concentration. With a low emission grade of the wall-mounted gas stoves, it is estimated that >10 % of residents in a typical residential building area are exposed to a high NO2 concentration of >200 μg/m3, and >50 % of residents are exposed to a concentration of >80 μg/m3. In addition, the indoor NO2 concentration shows an obvious non-uniform distribution with the floor in residential buildings. The NO2 emission from residential natural gas heating also shows an obvious impact on the microenvironment around buildings, which is primarily determined by the emission grade of the stoves. The findings highlight that HHS has become a non-negligible source of indoor NO2 pollution in China. It is urgently necessary to formulate NO2 emission limit standards for wall-mounted gas stoves in Chinese urban areas and upgrade traditional natural gas heaters with efficient emission reduction technologies.

Seasonal correlation of aerosols with soil moisture, evapotranspiration, and vegetation over Pakistan using remote sensing

Aerosols have a severe impact on the Earth's climate, human health, and ecosystem. To understand the impacts of aerosols on climate, human health, and the ecosystem we must need to understand the variability of aerosols and their optical properties. Therefore, we used Aqua-MODIS retrieved aerosol optical depth (AOD) (550 nm) and Angstrom exponent (AE) (440/870) data to analyze the Spatio-temporal seasonal variability of aerosols and their relationship with different meteorological parameters over Pakistan from 2002 to 2021. High (>0.5) AOD values were observed during the summer season and low (<0.8) in the spring season. AE values were observed to be high (>1) in the northern regions of Pakistan indicating the dominance of fine mode particles during the winter season. Moreover, AOD showed a positive correlation with Relative Humidity (RH), Evapotranspiration, Wind speed (WS), and Temperature. On the other hand, it showed a negative correlation with Soil moisture (SM), Normalized difference vegetation index (NDVI), and precipitation over Pakistan. Therefore, considering the outcomes of this study will help policymakers to understand the spatiotemporal variability of aerosols and their seasonal correlation with different meteorological parameters.

Assessing lake water quality during COVID-19 era using geospatial techniques and artificial neural network model

The present study evaluates the impact of the COVID-19 lockdown on the water quality of a tropical lake (East Kolkata Wetland or EKW, India) along with seasonal change using Landsat 8 and 9 images of the Google Earth Engine (GEE) cloud computing platform. The research focuses on detecting, monitoring, and predicting water quality in the EKW region using eight parameters-normalized suspended material index (NSMI), suspended particular matter (SPM), total phosphorus (TP), electrical conductivity (EC), chlorophyll-α, floating algae index (FAI), turbidity, Secchi disk depth (SDD), and two water quality indices such as Carlson tropic state index (CTSI) and entropy‑weighted water quality index (EWQI). The results demonstrate that SPM, turbidity, EC, TP, and SDD improved while the FAI and chlorophyll-α increased during the lockdown period due to the stagnation of water as well as a reduction in industrial and anthropogenic pollution. Moreover, the prediction of EWQI using an artificial neural network indicates that the overall water quality will improve more if the lockdown period is sustained for another 3 years. The outcomes of the study will help the stakeholders develop effective regulations and strategies for the timely restoration of lake water quality.