Exposure to urban greenspace and pathways to respiratory health: An exploratory systematic review

The Science of The Total Environment, Год журнала: 2022, Номер 829, С. 154447 - 154447

Опубликована: Март 11, 2022

Urban greenspace may have a beneficial or adverse effect on respiratory health. Our objective was to perform an exploratory systematic review synthesise the evidence and identify potential causal pathways relating urban health.We followed PRISMA guidelines reviews searched five databases for eligible studies during 2000-2021. We incorporated broad range of health search terms, including both observational experimental studies. Screening, data extraction, risk bias, assessed using Navigation Guide criteria, were performed independently by two authors. narrative synthesis discuss suggested identified 108 papers (n = 104 observational, n 4 experimental). The most common indicators overall greenery vegetation (also known as greenness), green land use/land cover physical area classes (e.g., parks, forests), tree canopy cover. A wide studied, with asthma prevalence being common. Two thirds 195) associations in these positive (i.e., beneficial) health, 31% 91) statistically significant; only 9% 25) reported negative adverse) significant. consistent apparent mortality. There 35 (32%) 'probably low' 73 (68%) high' ratings bias. Hypothesised benefits included lower air pollution, more physically active populations, exposure microbial diversity; mechanisms poorer pollen other aeroallergens.Many showed association between especially mortality; this is suggestive, but not conclusive, effects. Results underscore importance contextual factors, metric employed, bias subtle selection which should be explored further.

Язык: Английский

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Human health risk assessment of PM2.5-bound heavy metal of anthropogenic sources in the Khon Kaen Province of Northeast Thailand

Heliyon, Год журнала: 2022, Номер 8(6), С. e09572 - e09572

Опубликована: Июнь 1, 2022

The study aimed to assess the human health risk of PM

Язык: Английский

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Health risk and disease burden attributable to long-term global fine-mode particles

Chemosphere, Год журнала: 2021, Номер 287, С. 132435 - 132435

Опубликована: Окт. 2, 2021

Язык: Английский

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Combining Machine Learning and Numerical Simulation for High-Resolution PM_2.5 Concentration Forecast

Environmental Science & Technology, Год журнала: 2022, Номер 56(3), С. 1544 - 1556

Опубликована: Янв. 12, 2022

Forecasting ambient PM2.5 concentrations with spatiotemporal coverage is key to alerting decision makers of pollution episodes and preventing detrimental public exposure, especially in regions limited ground air monitoring stations. The existing methods rely on either chemical transport models (CTMs) forecast spatial distribution nontrivial uncertainty or statistical algorithms concentration time series at locations without continuous coverage. In this study, we developed a framework by combining the robust Random Forest algorithm publicly accessible global CTM product, NASA's Goddard Earth Observing System "Composition Forecasting" (GEOS-CF), providing spatiotemporally forecasts for next 5 days 1 km resolution. Our experiment was conducted region Central China including populous polluted Fenwei Plain. 2 had an overall validation R2 0.76 0.64, respectively; around 0.5 following 3 days. Spatial cross-validation showed similar metrics. model, normalized mean bias close 0, substantially reduced large biases GEOS-CF. proposed requires minimal computational resources compared running CTMs urban scales, enabling near-real-time resource-restricted environments.

Язык: Английский

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A Hybrid Spatiotemporal Deep Model Based on CNN and LSTM for Air Pollution Prediction

Sustainability, Год журнала: 2022, Номер 14(9), С. 5104 - 5104

Опубликована: Апрель 23, 2022

Nowadays, air pollution is an important problem with negative impacts on human health and the environment. The forecast can provide information to all affected sides, allows appropriate measures be taken. In order address problems of filling in missing values time series used for forecasts, automation allocation optimal subset input variables, dependency quality at a particular location conditions surrounding environment, as well model’s optimization, this paper proposes deep spatiotemporal model based 2D convolutional neural network long short-term memory predicting pollution. utilizes automatic selection variables optimization hyperparameters by genetic algorithm. A hybrid strategy value imputation combination linear interpolation using average between previous same other years. determine best architecture model, are optimized algorithm modified crossover operator solutions variable lengths. Additionally, trained models included various ensembles further improve prediction performance—these include comprising obtained evolutionary diverse k optimization. experimental results Beijing Multi-Site Air-Quality Data Set show that proposed forecasting provides good consistent results. comparison suggested NN shows satisfactory results, performance according MAE, station Wanliu (16.753 ± 0.384). Most architectures have one layer small number kernels kernel size; layers followed max-pooling layer, or two LSTM utilized dropout regularization applied p (0.1, 0.2 0.3). utilization from improves surpasses learning models, MAE RMSE metrics. enhances especially data clear seasonality, produces better compared hour day month also reveal random searching simple effective selecting variables. Furthermore, inclusion spatial data, local neighborhood significantly predictive model. demonstrate benefits including many stations possible, much historical possible.

Язык: Английский

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Simulating daily PM2.5 concentrations using wavelet analysis and artificial neural network with remote sensing and surface observation data

Chemosphere, Год журнала: 2023, Номер 340, С. 139886 - 139886

Опубликована: Авг. 21, 2023

Язык: Английский

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Effect of PM2.5 air pollution on the global burden of lower respiratory infections, 1990–2019: A systematic analysis from the Global Burden of Disease Study 2019

Journal of Hazardous Materials, Год журнала: 2023, Номер 459, С. 132215 - 132215

Опубликована: Авг. 3, 2023

Particulate matter (PM) air pollution is closely related to lower respiratory infections (LRIs). However, the global LRI burden attributable PM remains unclear. Here, we provide a comprehensive assessment of PM2.5-attributable using data from Global Burden and Disease Study (GBD) 2019. We found that PM2.5 contributed approximately 0.7 million deaths 37.6 disability-adjusted life years (DALYs) LRIs in The has decreased 1990 2019, with more pronounced decrease household than ambient PM2.5. Unlike decreasing trend due worldwide, nearly one fifth countries experienced an increase was unevenly distributed less developed countries, mainly Sub-Saharan Africa. All age groups burden, most significant children younger 10 years. Notably, individuals aged 20-84 Males had higher females elder SDI regions. This study provided evidence-based guidance for prevention control pollution.

Язык: Английский

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Ecological security assessment and ecological management zoning based on ecosystem services in the West Liao River Basin

Ecological Engineering, Год журнала: 2023, Номер 192, С. 106973 - 106973

Опубликована: Апрель 5, 2023

Язык: Английский

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Global burden and epidemiological prediction of polycystic ovary syndrome from 1990 to 2019: A systematic analysis from the Global Burden of Disease Study 2019

PLoS ONE, Год журнала: 2024, Номер 19(7), С. e0306991 - e0306991

Опубликована: Июль 18, 2024

Objective To comprehensively assess the global, regional and national burden of polycystic ovary syndrome (PCOS) in incidence, prevalence, years lived with disability (DLYs) based on Global Burden Disease Study (GBD) 2019. Methods This was a cross-sectional descriptive study. Data PCOS DLYs from 1990 to 2019 were obtained GBD study According commonwealth income, WHO region, sociodemographic index, estimates demonstrated along estimated annual percentage change (EAPC). The EAPC data analyzed by four levels hierarchical clustering displayed world map. Autoregressive Integrated Moving Average (ARIMA) Bayesian age-period-cohort (BAPC) model used predict next 20 years. Results From 2019, number incidence one year increased 1.4 million 2.1 (54.3%). Only Region Americas decreased, their aged-standardized rate (ASIR) values highest There no significant correlation between human development index (HDI) EAPC. However, when HDI < 0.7, prevalence positively correlated HDI, > negatively HDI. Countries middle level have increasing trend ASIR age-standardized (ASPR). 10 19 old group had counts globally. Besides, ARIMA BAPC showed consistent PCOS. Conclusion In order better promote early diagnosis treatment, expert consensus criteria should be formulated according characteristics different ethnic groups or regions. It is necessary emphasize screening actively develop targeted drugs for

Язык: Английский

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An update on adverse health effects from exposure to PM2.5

Environmental Advances, Год журнала: 2024, Номер unknown, С. 100603 - 100603

Опубликована: Ноя. 1, 2024

Язык: Английский

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