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1.
J Environ Sci (China) ; 141: 215-224, 2024 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-38408822

RESUMO

The complex air pollution driven by both Ozone (O3) and fine particulate matter (PM2.5) significantly influences the air quality in the Sichuan Basin (SCB). Understanding the O3 formation during autumn and winter is necessary to understand the atmospheric oxidative capacity. Therefore, continuous in-site field observations were carried out during the late summer, early autumn and winter of 2020 in a rural area of Chongqing. The total volatile organic compounds (VOCs) concentration reported by a Proton-Transfer-Reaction Time-of-Flight Mass Spectrometry (PTR-ToF-MS) were 13.66 ± 9.75 ppb, 5.50 ± 2.64 ppb, and 9.41 ± 5.11 ppb in late summer, early autumn and winter, respectively. The anthropogenic VOCs (AVOCs) and biogenic VOCs (BVOCs) were 8.48 ± 7.92 ppb and 5.18 ± 2.99 ppb in late summer, 3.31 ± 1.89 ppb and 2.19 ± 0.93 ppb in autumn, and 6.22 ± 3.99 ppb and 3.20 ± 1.27 ppb in winter. A zero-dimensional atmospheric box model was employed to investigate the sensitivity of O3-precursors by relative incremental reactivity (RIR). The RIR values of AVOCs, BVOCs, carbon monoxide (CO), and nitrogen oxides (NOx) were 0.31, 0.71, 0.09, and -0.36 for late summer, 0.24, 0.59, 0.22, and -0.38 for early autumn, and 0.30, 0.64, 0.33 and -0.70 for winter, and the results showed that the O3 formation of sampling area was in the VOC-limited region, and O3 was most sensitive to BVOCs (with highest RIR values, > 0.6). This study can be helpful in understanding O3 formation and interpreting the secondary formation of aerosols in the winter.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Ozônio , Compostos Orgânicos Voláteis , Ozônio/química , Compostos Orgânicos Voláteis/análise , Poluentes Atmosféricos/análise , China , Poluição do Ar/análise , Monitoramento Ambiental/métodos
2.
Sci Total Environ ; 934: 173193, 2024 Jul 15.
Artigo em Inglês | MEDLINE | ID: mdl-38744393

RESUMO

O3 pollution in China has become prominent in recent years, and it has become one of the most challenging issues in air pollution control. We used data on atmospheric pollutants and meteorology from 2019 to 2021 to build an interpretable random forest (RF) model, applying this model to predict O3 concentration in 2022 in five cities in the Southwest North China Plain. The model was also used to identify and explain the influence of various factors on O3 formation. The correlation coefficient R2 between the predicted O3 concentration and observed O3 concentration was 0.82, the MAE was 15.15 µg/m3, and the RMSE was 20.29 µg/m3, indicating that the model can effectively predict O3 concentration in the studying area. The results of correlation analysis, feature importance, and the driving factor analysis from SHapley Additive exPlanations (SHAP) model indicated that temperature (T), NO2, and relative humidity (RH) are the top three features affecting O3 prediction, while the weights of wind speed and wind direction were relatively low. Thus, O3 in the southwestern North China Plain may mainly come from the formation of local photochemical activities. The dominant factors behind O3 also varied in different seasons. In spring and autumn, O3 pollution is more likely to occur under high NO2 concentration and high-temperature conditions, while in summer, it is more likely to occur under high-temperature and precipitation-free weather. In winter, NO2 is the dominant factor in O3 formation. Finally, the interpretable RF model is used to predict future O3 concentration based on features provided by Community Multiscale Air Quality (CMAQ) and Weather Research & Forecast (WRF) model, and the simulation performance of CMAQ on O3 concentration is enhanced to a certain extent, improving the prediction of future O3 pollution situations and guiding pollution control.

3.
Sci Total Environ ; 914: 169878, 2024 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-38190917

RESUMO

Forty-six percent of the world's population resides in rural areas, the majority of whom belong to vulnerable groups. They mainly use cheap solid fuels for cooking and heating, which release a large amount of PM2.5 and cause adverse effects to human health. PM2.5 exhibits urban-rural differences in its health risk to the respiratory system. However, the majority of research on this issue has focused on respiratory diseases induced by atmospheric PM2.5 in urban areas, while rural areas have been ignored for a long time, especially the pathogenesis of respiratory diseases. This is not helpful for promoting environmental equity to aid vulnerable groups under PM2.5 pollution. Thus, this study focuses on rural atmospheric PM2.5 in terms of its chemical components, toxicological effects, respiratory disease types, and pathogenesis, represented by PM2.5 from rural areas in the Sichuan Basin, China (Rural SC-PM2.5). In this study, organic carbon is the most significant component of Rural SC-PM2.5. Rural SC-PM2.5 significantly induces cytotoxicity, oxidative stress, and inflammatory response. Based on multiomics, bioinformatics, and molecular biology, Rural SC-PM2.5 inhibits ribonucleotide reductase regulatory subunit M2 (RRM2) to disrupt the cell cycle, impede DNA replication, and ultimately inhibit lung cell proliferation. Furthermore, this study supplements and supports the epidemic investigation. Through an analysis of the transcriptome and human disease database, it is found that Rural SC-PM2.5 may mainly involve pulmonary hypertension, sarcoidosis, and interstitial lung diseases; in particular, congenital diseases may be ignored by epidemiological surveys in rural areas, including tracheoesophageal fistula, submucous cleft of the hard palate, and congenital hypoplasia of the lung. This study contributes to a greater scientific understanding of the health risks posed by rural PM2.5, elucidates the pathogenesis of respiratory diseases, clarifies the types of respiratory diseases, and promotes environmental equity.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Transtornos Respiratórios , Doenças Respiratórias , Humanos , Poluentes Atmosféricos/toxicidade , Poluentes Atmosféricos/análise , Material Particulado/toxicidade , Material Particulado/análise , Monitoramento Ambiental , Poluição do Ar/análise , Transtornos Respiratórios/induzido quimicamente , Doenças Respiratórias/induzido quimicamente , Doenças Respiratórias/epidemiologia , População Rural , China/epidemiologia
4.
Sci Total Environ ; 879: 163022, 2023 Jun 25.
Artigo em Inglês | MEDLINE | ID: mdl-36966844

RESUMO

PM2.5 seriously endangers human health, and its mutagenicity is considered an important pathogenic mechanism. However, the mutagenicity of PM2.5 is mainly determined by traditional bioassays, which are limited in the large-scale identification of mutation sites. Single nucleoside polymorphisms (SNPs) can be used for the large-scale analysis of DNA mutation sites but have not yet been used on the mutagenicity of PM2.5. The Chengdu-Chongqing Economic Circle is one of China's four major economic circles and five major urban agglomerations, and the relationship between the mutagenicity of PM2.5 and ethnic susceptibility in this circle remains unclear. In this study, the representative samples are PM2.5 from Chengdu in summer (CDSUM), Chengdu in winter (CDWIN), Chongqing in summer (CQSUM) and Chongqing in winter (CQWIN) respectively. PM2.5 from CDWIN, CDSUM and CQSUM induce the highest levels of mutation in the regions of exon/5'Utr, upstream/splice site and downstream/3'Utr respectively. PM2.5 from CQWIN, CDWIN and CDSUM induce the highest ratio of missense, nonsense and synonymous mutation respectively. PM2.5 from CQWIN and CDWIN induce the highest transition and transversion mutations respectively. The ability of PM2.5 from the four groups to induce disruptive mutation effects is similar. For ethnic susceptibility, PM2.5 in this economic circle is more likely to induce DNA mutation in Chinese Dai from Xishuangbanna among Chinese ethnic groups. PM2.5 from CDSUM, CDWIN, CQSUM and CQWIN may particularly tend to induce Southern Han Chinese, Dai in Xishuangbanna, Dai in Xishuangbanna and Southern Han Chinese respectively. These findings may assist in the development of a new method for analyzing the mutagenicity of PM2.5. Moreover, this study not only promotes attention to ethnic susceptibility to PM2.5, but also introduces public protection policies for the susceptible population.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Humanos , Poluentes Atmosféricos/toxicidade , Poluentes Atmosféricos/análise , Material Particulado/toxicidade , Material Particulado/análise , Poluição do Ar/análise , Mutagênicos/toxicidade , Mutagênicos/análise , Monitoramento Ambiental/métodos , China , Cidades
5.
Huan Jing Ke Xue ; 42(6): 2648-2658, 2021 Jun 08.
Artigo em Chinês | MEDLINE | ID: mdl-34032064

RESUMO

Oxygenated volatile organic compounds (OVOCs) are important intermediates in the troposphere and the most important sources of ozone. Proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS) was used to measure VOCs in the Chengdu Plain, Southwestern China. The diurnal variations, photochemical reactivity, O3 formation potential, and sources were also investigated. The mixing ratios of ten kinds of VOCs (acetaldehyde, acetone, isoprene, Methyl ethyl ketone, Methyl vinyl ketone and Methacrolein, benzene, toluene, styrene, C8 aromatics, and C9 aromatics) were (10.97±4.69)×10-9. The concentrations of OVOCs, aromatic hydrocarbons, and biogenic VOCs were (8.54±3.44)×10-9, (1.53±0.93)×10-9, and (0.90±0.32)×10-9, respectively. Isoprene, acetaldehyde, and m-xylene were the top three photochemically active species with the greatest O3 formation potentials. The dominant three OVOCs species (acetaldehyde, acetone, and MEK) were mainly derived from local biogenic sources and anthropogenic secondary sources, and acetone had a strong regional background level, indicating that pollution in this area is significantly affected by regional transmission. This study deepens the understanding of regional O3 formation mechanisms in southwest China and provides a basis for the scientifically informed control of O3 pollution.

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