Analysis of risk factors related to acute exacerbation in patients with chronic pancreatitis: a retrospective study of 313 cases from a single center in China.

Background: Acute on chronic pancreatitis(ACP) is a common cause of treatment in patients with chronic pancreatitis(CP). However, as far as we know, research on ACP has been few, and the quality may vary. This study intended to explore the risk factors related to acute exacerbation in patients with chronic pancreatitis.

Changes in factor profiles deriving from photochemical losses of volatile organic compounds: Insight from daytime and nighttime positive matrix factorization analyses.

Substantial effects of photochemical reaction losses of volatile organic compounds (VOCs) on factor profiles can be investigated by comparing the differences between daytime and nighttime dispersion-normalized VOC data resolved profiles. Hourly speciated VOC data measured in Shijiazhuang, China from May to September 2021 were used to conduct study. The mean VOC concentration in the daytime and at nighttime were 32.

Optimizing BenMAP health impact assessment with meteorological factor driven machine learning models.

This study aims to address accuracy challenges in assessing air pollution health impacts using Environmental Benefits Mapping and Analysis Program (BenMap), caused by limited meteorological factor data and missing pollutant data. By employing data increment strategies and multiple machine learning models, this research explores the effects of data volume, time steps, and meteorological factors on model prediction performance using several years of data from Tianjin City as an example. The findings indicate that increasing training data volume enhances the performance of Random Forest Regressor (RF) and Decision Tree Regressor (DT) models, especially for predicting CO, NO, and PM.

Aerosol in global oceanic regions: Four-decade trends, spatial patterns, and policy implications.

High aerosol loadings are observed not only in megacities on continents but also in oceanic regions like the Bohai Sea. This work provides a comprehensive analysis of the spatial and temporal variations in Aerosol Optical Depth (AOD) across different ocean regions worldwide over the past four decades, using remote sensing reanalysis data. The mean AOD value across all oceanic grids is approximately 0.

Characterizing carbonaceous aerosols in residential coal combustion: Insights from thermal/spectral carbon analyzer coupled with photoionization mass spectrometry analysis.

This study aims to identify unique signatures from residential coal combustion in China across various combustion conditions and coal types. Using a Thermal/Spectral Carbon Analyzer with a Photoionization Time-of-Flight Mass Spectrometer (TSCA-PI-TOF-MS), we focus on the optical properties and organic mass spectra of the emissions. Bituminous coal emerged as the primary emitter of total carbon, releasing 729 μg C/mg PM under smoldering and 894 μg C/mg PM under flaming.

Assessing emission-driven changes in health risk of source-specific PM-bound heavy metals by adjusting meteorological covariates.

Heavy metals (HMs) in PM gain much attention for their toxicity and carcinogenic risk. This study evaluates the health risks of PM-bound HMs, focusing on how meteorological conditions affect these risks against the backdrop of PM reduction trends in China. By applying a receptor model with a meteorological normalization technique, followed by health risk assessment, this work reveals emission-driven changes in health risk of source-specific HMs in the outskirt of Tianjin during the implementation of China' second Clean Air Action (2018-2020).

[Spatial Variability and Source Apportionment of PM Carbon Components in Tianjin].

The contents of eight carbonaceous subfractions were determined by simultaneously collecting PM samples from four sites in different functional areas of Tianjin in 2021. The results showed that the organic carbon (OC) concentration was 3.7 μg·m to 4.

Spatial source apportionment of airborne coarse particulate matter using PMF-Bayesian receptor model.

Ambient particulate matter (PM and PM), has been extensively monitored in numerous urban areas across the globe. Over the past decade, there has been a significant improvement in PM air quality, while improvements in PM levels have been comparatively modest, primarily due to the limited reduction in coarse particle (PM) pollution. Unlike PM, PM predominantly originates from local emissions and is often characterized by pronounced spatial heterogeneity.

High aerosol loading over the Bohai Sea: Long-term trend, potential sources, and impacts on surrounding cities.

Air pollution over the oceans has received less attention compared to densely populated urban areas of continents. The Bohai Sea, a semi-enclosed sea in northern China, is surrounded by thirteen industrial cities that have experienced significant improvements in air quality over the past decade. However, the changes in air pollution over the Bohai Sea and its impacts on surrounding cities remain poorly understood.

Source apportionment of consumed volatile organic compounds in the atmosphere.

Conventional source apportionments of ambient volatile organic compounds (VOCs) have been based on observed and initial concentrations after photochemical correction. However, these results have not been related to ozone (O) and secondary organic aerosol (SOA) formation. Thus, the apportioned contributions could not effectively support secondary pollution control development.

Changes in source apportioned VOCs during high O periods using initial VOC-concentration-dispersion normalized PMF.

Ambient volatile organic compounds (VOCs) concentrations are affected by emissions, dispersion, and chemistry. This work developed an initial concentration-dispersion normalized PMF (ICDN-PMF) to reflect the changes in source emissions. The effects of photochemical losses for VOC species were corrected by estimating the initial data, and then applying dispersion normalization to reduce the impacts of atmospheric dispersion.

[Spatial-temporal Variation and Driving Factors of Ozone in China from 2019 to 2021 Based on EOF Technique and KZ Filter].

Based on the hourly O concentration data of 337 prefectural-level divisions and simultaneous surface meteorological data in China, we applied empirical orthogonal function (EOF) analysis to analyze the main spatial patterns, variation trends, and main meteorological driving factors of O concentration in China from March to August in 2019-2021. In this study, a KZ (Kolmogorov-Zurbenko) filter was used to decompose the time series of O concentration and simultaneous meteorological factors into corresponding short-term, seasonal, and long-term components in 31 provincial capitals.Then, the stepwise regression was used to establish the relationship between O and meteorological factors.

Trends of source apportioned PM in Tianjin over 2013-2019: Impacts of Clean Air Actions.

A long-term (2013-2019) PM speciation dataset measured in Tianjin, the largest industrial city in northern China, was analyzed with dispersion normalized positive matrix factorization (DN-PMF). The trends of source apportioned PM were used to assess the effectiveness of source-specific control policies and measures in support of the two China's Clean Air Actions implemented nationwide in 2013-2017 and 2018-2020, respectively. Eight sources were resolved from the DN-PMF analysis: coal combustion (CC), biomass burning (BB), vehicular emissions, dust, steelmaking and galvanizing emissions, a mixed sulfate-rich factor and secondary nitrate.

Attribution of Air Quality Benefits to Clean Winter Heating Policies in China: Combining Machine Learning with Causal Inference.

Heating is a major source of air pollution. To improve air quality, a range of clean heating policies were implemented in China over the past decade. Here, we evaluated the impacts of winter heating and clean heating policies on air quality in China using a novel, observation-based causal inference approach.

Effect of photochemical losses of ambient volatile organic compounds on their source apportionment.

Photochemical losses of ambient volatile organic compounds (VOCs) substantially affect source apportionment analysis. Hourly speciated VOC data measured from April to August 2020 in Tianjin, China were used to analyze the photochemical losses of VOC species and assess the impacts of photochemical losses on source apportionment by comparing the positive matrix factorization (PMF) results based on observed and initial concentration data (OC-PMF and IC-PMF). The initial concentrations of the VOC species were estimated using a photochemical age-based parameterization method.

Impacts of meteorology and precursor emission change on O variation in Tianjin, China from 2015 to 2021.

Deterioration of surface ozone (O) pollution in Northern China over the past few years received much attention. For many cities, it is still under debate whether the trend of surface O variation is driven by meteorology or the change in precursors emissions. In this work, a time series decomposition method (Seasonal-Trend decomposition procedure based on Loess (STL)) and random forest (RF) algorithm were utilized to quantify the meteorological impacts on the recorded O trend and identify the key meteorological factors affecting O pollution in Tianjin, the biggest coastal port city in Northern China.

Spatio-temporally differentiated impacts of temperature inversion on surface PM in eastern China.

Temperature inversion (TI) is one of the meteorological conditions that significantly affect regional air quality. Knowledge gap regarding the impacts of TI on surface PM in different topographies still existed. In the present study, the occurrence frequency, temperature lapse rate (TLR), depth, and the diurnal variations of TI, surface-based TI (SBTI), elevated TI (ElTI), and multiple layers of TIs (MultiTI) and their impacts on near-surface PM concentrations over eastern China that covers a range of topographies and climates, are systematically investigated based on global reanalysis ERA5 and the nationwide monitoring PM dataset from 2014 to 2020.

The role of sources and meteorology in driving PM-bound chlorine.

The role of chloride in atmospheric chemistry received increased attention over recent years. Given the primary and chemical-active nature of PM-bound chlorine (p-Cl), it makes sense to get to know the sources and processes of p-Cl. The temporal behavior of observed p-Cl concentration based on 1-h high resolution exhibited seasonal variation of high in winter, low in summer and diurnal variation of high in the morning, low in afternoon.

Marginal reduction in surface NO attributable to airport shutdown: A machine learning regression-based approach.

Emissions from aviation and airport-related activities degrade surface air quality but received limited attention relative to regular transportation sectors like road traffic and waterborne vessels. Statistically, assessing the impact of airport-related emissions remains a challenge due to the fact that its signal in the air quality time series data is largely dwarfed by meteorology and other emissions. Flight-ban policy has been implemented in a number of cities in response to the COVID-19 spread since early 2020, which provides an unprecedented opportunity to examine the changes in air quality attributable to airport closure.

Understanding Sources and Drivers of Size-Resolved Aerosol in the High Arctic Islands of Svalbard Using a Receptor Model Coupled with Machine Learning.

Atmospheric aerosols are important drivers of Arctic climate change through aerosol-cloud-climate interactions. However, large uncertainties remain on the sources and processes controlling particle numbers in both fine and coarse modes. Here, we applied a receptor model and an explainable machine learning technique to understand the sources and drivers of particle numbers from 10 nm to 20 μm in Svalbard.

Global review of source apportionment of volatile organic compounds based on highly time-resolved data from 2015 to 2021.

Highly time-resolved data for volatile organic compounds (VOCs) can now be monitored. Source analyses of such high time-resolved concentrations provides key information for controlling VOC emissions. This work reviewed the literature on VOCs source analyses published from 2015 to 2021, and assesses the state-of-the-art and the existing issues with these studies.

Evaluating the performance of chemical transport models for PM source apportionment: An integrated application of spectral analysis and grey incidence analysis.

Evaluating the performance of source apportionment (SA) models is difficult due to the non-observable nature of source contribution in reality. Here we propose a new approach to assess the performance of Chemical Transport Models (CTMs) for SA based on wavelet time-frequency spectral analysis and Grey Incidence Analysis (GIA). For each source category, certain species that better reflect the periodic characteristics of the emission sources were selected as the chemical tracers.

Improved positive matrix factorization for source apportionment of volatile organic compounds in vehicular emissions during the Spring Festival in Tianjin, China.

Photochemical losses of volatile organic compounds (VOCs) and uncertainties in calculated factor profiles can reduce the accuracy of source apportionment by positive matrix factorization (PMF). We developed an improved PMF method (termed ICLP-PMF) that estimated the reaction-corrected ("initial") concentrations of VOCs. Source profiles from literature provided constraints.

Impact of sand and dust storms on the atmospheric environment and its source in Tianjin-China.

Sand and dust storms (SDS) frequently hit northern China and adversely impact both environment and health. The carbonaceous components, inorganic elements, water-soluble ions, and meteorological parameters of several severe SDS episodes have been measured in a supersite in Tianjin, which is a big and representative city located in SDS transmission pathway in northern China. Six SDS episodes were identified in Spring, 2021.