Poor air quality is increasingly linked to gastrointestinal diseases, suggesting a potential correlation with human intestine health. However, this relationship remains largely unexplored due to limited research. This study used a controlled mouse model exposed to cooking oil fumes (COFs) and metagenomics, transcriptomics, and metabolomics to elucidate interactions between intestine microbiota and host metabolism under environmental stress. Our findings reveal that short-term COF inhalation induces pulmonary inflammation within 3 days and leads to gastrointestinal disturbances, elucidating a pathway connecting respiratory exposure to intestinal dysfunction. The exposure intensity significantly correlates with changes in intestinal tissue integrity, microbial composition, and metabolic function. Extended exposure of 7 days disrupts intestine microbiota and alters tryptophan metabolism, with further changes observed after 14 days, highlighting an adaptive response. These results highlight the vulnerability of intestinal health to airborne pollutants and suggest a pathway through which inhaled pollutants may affect distant organ systems.

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.

Chinese diesel trucks are the main contributors to NOx and particulate matter (PM) vehicle emissions. An increase in diesel trucks could aggravate air pollution and damage human health. The Chinese government has recently implemented a series of emission control technologies and measures for air quality improvement. This paper summarizes recent control technologies and measures for diesel truck emissions in China and introduces the comprehensive application of control technologies and measures in Beijing-Tianjin-Hebei and surrounding regions. Remote online monitoring technology has been adopted according to the China VI standard for heavy-duty diesel trucks, and control measures such as transportation structure adjustment and heavy pollution enterprise classification control continue to support the battle action plan for pollution control. Perspectives and suggestions are provided for promoting pollution control and supervision of diesel truck emissions: adhere to the concept of overall management and control, vigorously promote the application of systematic and technological means in emission monitoring, continuously facilitate cargo transportation structure adjustment and promote new energy freight vehicles. This paper aims to accelerate the implementation of control technologies and measures throughout China. China is endeavouring to control diesel truck exhaust pollution. China is willing to cooperate with the world to protect the global ecological environment.

The photolysis of particulate nitrate (pNO3-) has been suggested to be an important source of nitrous acid (HONO) in the troposphere. However, determining the photolysis rate constant of pNO3- (jpNO3-) suffers from high uncertainty. Prior laboratory measurements of jpNO3- using aerosol filters have been complicated by the \"shadow effect\"─a phenomenon of light extinction within aerosol layers that potentially skews these measurements. We developed a method to correct the shadow effect on the photolysis rate constant of pNO3- for HONO production (jpNO3- → HONO) using aerosol filters with identical chemical compositions but different aerosol loadings. We applied the method to quantify jpNO3- → HONO over the North China Plain (NCP) during the winter haze period. After correcting for the shadow effect, the normalized average jpNO3- → HONO at 5 °C increased from 5.89 × 10-6 s-1 to 1.72 × 10-5 s-1. The jpNO3- → HONO decreased with increasing pH and nitrate proportions in PM2.5 and had no correlation with nitrate concentrations. A parametrization for jpNO3- → HONO was developed for model simulation of HONO production in NCP and similar environments.

The pollutant emissions of diesel-powered heavy-duty trucks (HDTs) seriously damage the air quality. The promotion of hydrogen fuel cell HDTs through purchase subsidy policy to reduce emissions has become an important approach to control air pollution. This study focuses on the impact of hydrogen fuel cell HDT purchase subsidies on air quality in the context of China, covering the panel data of 31 Chinese cities from 2014 to 2021 and applying a two-way fixed effects model to analyze the contribution of purchase subsidies and hydrogen refueling station construction subsidies to air quality. Results show that (1) the increase in purchase subsidies could improve the air quality by around 6.1% and there is a lag effect. (2) Purchase subsidies make a larger contribution to air quality compared with construction subsidies. (3) Purchase subsidies can improve air quality by reducing carbon emissions in transport industry. In sight of these results, policy makers should emphasize the implementation of purchase subsidies and hydrogen refueling station construction subsidies and stimulate manufacturers to improve the performance of hydrogen fuel cell so as to contribute more to the environment.

There is growing interest in the contribution of ultrafine particles to air quality, climate, and human health. Ultrafine particles are of central significance for the influence of radiative forcing of climate change by involving in the formation of clouds and precipitation. Moreover, exposure to ultrafine particles can enhance the disease burden. The determination of those effects of ultrafine particles strongly depends on their chemical composition and physicochemical properties. This review focuses on the advanced techniques for the characterization of chemical composition and physicochemical properties of ultrafine particles in the past five years. The current analytical methodologies are broadly classified into electron and X-ray microscopy, optical spectroscopy and microscopy, electrical mobility, and mass spectrometry, and then described and discussed its operation principle, advantages, and limitations. Besides measurements, application of the state-of-the-art techniques is briefly reviewed to help us to promote a better understanding of atmospheric ultrafine particles relevant to air quality, climate, and health.

Atmospheric reactive nitrogen (Nr) deposition has been modified significantly by human activities such as agriculture and fossil fuel combustion. Understanding the changes in Nr deposition is essential for maintaining the functionality and sustainability of ecosystems. Taking Beijing as a case study, we report long-term measurements of wet Nr deposition from 1999 to 2022 and dry Nr deposition from 2010 to 2022 and their relationship with China\'s air pollution control. Total Nr deposition to Beijing decreased by 34 % during 2010-2022, mainly caused by a decrease in dry N deposition by 54.27 %, from 47.86 kg N ha-1 yr-1 in 2010-2014 to 21.89 kg N ha-1 yr-1 in 2018-2022; reduced and oxidized N in dry deposition decreased by 29.93 % and 72.05 %, respectively. This was a result of the \"Action Plan for Prevention and Control of Air Pollution (APCP)\" and the implementation of the \"Zero Growth in Fertilizer Use by 2020\" in 2015. Our ground-based measurements provide evidence to support recent achievements in air pollution control and a reference and guidance for other regions of China and other countries for abating Nr pollution.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death worldwide, with air pollution posing significant risks to cardiovascular health. The effect of air quality on heart failure (HF) readmission in acute myocardial infarction (AMI) patients is unclear.The aim of this study was to evaluate the role of a single measure of air pollution exposure collected on the day of first hospitalization.
METHODS: We retrospectively analyzed data from 12,857 acute coronary syndrome (ACS) patients (January 2015-March 2023). After multiple screenings, 4023 AMI patients were included. The air pollution data is updated by the automatic monitoring data of the national urban air quality monitoring stations in real time and synchronized to the China Environmental Monitoring Station. Cox proportional hazards regression assessed the impact of air quality indicators on admission and outcomes in 4013 AMI patients. A decision tree model identified the most susceptible groups.
RESULTS: After adjusting for confounders, NO2 (HR 1.009, 95% CI 1.004-1.015, P = 0.00066) and PM10 (HR 1.006, 95% CI 1.002-1.011, P = 0.00751) increased the risk of HF readmission in ST-segment elevation myocardial infarction (STEMI) patients. No significant effect was observed in non-STEMI (NSTEMI) patients (P > 0.05). STEMI patients had a 2.8-fold higher risk of HF readmission with NO2 > 13 μg/m3 (HR 2.857, 95% CI 1.439-5.670, P = 0.00269) and a 1.65-fold higher risk with PM10 > 55 μg/m3 (HR 1.654, 95% CI 1.124-2.434, P = 0.01064).
CONCLUSIONS: NO2 and PM10 are linked to increased HF readmission risk in STEMI patients, particularly when NO2 exceeds 13 μg/m3 and PM10 exceeds 55 μg/m3. Younger, less symptomatic male STEMI patients with fewer underlying conditions are more vulnerable to these pollutants.

Growing environmental challenges necessitate increased focus on sustainability education. This study examines the effects of environmental education programs in China on air and water quality perception, waste reduction, and energy consumption reduction. A comparative quantitative design with 650 participants divided into four groups was employed. Data were collected using the Environmental Sustainability Assessment Survey (ESAS) instrument to assess environmental awareness and behavior changes. Statistical tests were used to identify significant differences between groups. Findings showed significant improvements in perceived air and water quality, with web-based programs demonstrating particular success. Waste reduction efforts also varied, with web-based education again proving effective. Energy consumption reduction was most evident in the corporate sector, where leadership in electric vehicles and sustainable transportation played a key role. Supportive government policies and environmental NGOs further highlighted the power of informed environmental decision-making. This study emphasizes the critical role of environmental education in addressing sustainability challenges. It empowers individuals and communities to actively engage in environmental conservation actively, fostering a harmonious relationship between humans and the environment. Our findings have global implications, highlighting education\'s vital role in shaping a sustainable future.

Most studies analyzing the effects of air pollution on disadvantaged populations use ground air quality measurements. However, ground stations are generally limited, with nearly 40% of countries having no official PM2.5 stations, not allowing air quality analysis for a significantly large share of the world\'s population. Furthermore, limited studies analyze community data from a geodemographic perspective, in other words, to delineate the sociodemographic profiles and geographically locate the socioeconomic groups more exposed to ambient air pollution. Therefore, a significant question arises: How can we trace vulnerable communities to air pollution in areas lacking air-quality ground data? Here, we propose a novel methodology to respond to this question. We use NO2, SO2, CO, and HCHO tropospheric column air-quality data from Sentinel-5P, a satellite that quantifies concentrations of atmospheric species from space operationally. We integrate them with census and environmental data and apply the local fuzzy geographically weighted clustering spatial machine learning method for segmentation analysis. Our findings for Bali, Indonesia, provide quantitative evidence for the benefits of this methodology in tracing and delineating the profiles of the communities most exposed to air pollution. For example, results show that communities with highly disadvantaged populations, such as unemployed (over 27.8%), low educated (over 27.9%), and children (over 22.1%) (mainly located around Bali\'s south and north coast touristic areas), exhibit very high values (over the 75th quartile) across the pollutants studied. The proposed method is reproducible easily, quickly, and at low cost, as it is based on freely available satellite data and not on costly ground station measurements. This will hopefully assist decision-makers in tracing the most vulnerable subpopulations, even in areas with inadequate air-quality monitoring networks, thus allowing local governments around the globe (even those that are financially weak) to achieve environmental justice and their sustainable development goals.