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Migration and diffusion characteristics of air pollutants and meteorological influences in Northwest China: a case study of four mining areas.

ABSTRACT: In the process of exploiting mineral resources, dust enters the environment through air suspended particles and surface runoff, which has a serious impact on the atmospheric environment and human health. From all-year and seasonal scenarios, the migration trajectories and cumulative concentration based on the secondary development of Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) in four mining areas (SF, BC, SJZ, and MJT) in Northwest China are studied. The convergent cross mapping (CCM) method is used to study the causal relationship between concentration and meteorological factors. In this process, the problem of missing non-station meteorological data is solved with the help of the inverse distance weighted interpolation method, and the problem in which the convergence requirements of the CCM algorithm cannot meet the requirements is solved with the bootstrap method. The results indicated that the short path has the characteristics of slow movement, short migration path, low altitude(< 1 km), and high contribution rate, while the long path has the opposite characteristics. Furthermore, the results demonstrated that the concentration is centered on the pollution source and diffuses around, with a diffusion radius of 220-270 km, showing a serious pollution center and slight gradient settlement on the edge, but the overall distribution of accumulated concentration is uneven. The results also show that temperature (TEMP and S_TEMP), evaporation, and air pressure are the main meteorological factors affecting the all-year concentration. The concentration and meteorological factors in the four mining areas also show significant seasonal characteristics, and the correlation in spring, summer, and autumn is stronger than that in winter. This study not only provides a reference for the green and sustainable exploitation of mineral resources but also provides theoretical support for the joint prevention and control of transboundary pollution.

SUBMITTER: Su J

PROVIDER: S-EPMC8936387 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveTo determine the association of meteorological factors and air pollutants (MFAPs) with fracture and to estimate the effect size/time lag.DesignThis is a nationwide population-based ecological study from 2008 to 2017.SettingEight large metropolitan areas in Korea.ParticipantsOf 8 093 820 patients with fractures reported in the Korea National Health Insurance database, 2 129 955 were analysed after the data set containing patient data (age, sex and site of fractures) were merged with MFAPs. Data on meteorological factors were obtained from the National Climate Data Center of the Korea Meteorological Administration. Additionally, data on air pollutants (atmospheric particulate matter ≤2.5 µm in diameter (PM2.5), PM10, ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide) were obtained from the Air Korea database.Primary and secondary outcome measuresWe hypothesised that there would be an association between MFAPs and the incidence of fracture. A generalised additive model was used while factoring in the non-linear relationship between MFAPs and fractures as well as a time lag ≤7 days. Multivariate analysis was performed. Backward elimination with an Akaike information criterion was used to fit the multivariate model.ResultsOverall, in eight urban areas, 2 129 955 patients with fractures were finally analysed. These included 370 344, 187 370, 173 100, 140 358, 246 775, 6501, 228 346, 57 183 and 719 978 patients with hip, knee, shoulder, elbow, wrist, hand, ankle, foot and spine fractures, respectively. Various MFAPs (average temperature, daily rain, wind speed, daily snow and PM2.5) showed significant association with fractures, with positive correlations at time lags 7, 5-7, 5-7, 3-7 and 6-7 days, respectively.ConclusionsVarious MFAPs could affect the occurrence of fractures. The average temperature, daily rain, wind speed, daily snow and PM2.5 were most closely associated with fracture. Thus, improved public awareness on these MFAPs is required for clinical prevention and management of fractures.

Project description:Coronavirus disease 2019 (COVID-19) was first detected in December 2019 in Wuhan, China, with 11,669,259 positive cases and 539,906 deaths globally as of July 8, 2020. The objective of the present study was to determine whether meteorological parameters and air quality affect the transmission of COVID-19, analogous to SARS. We captured data from 29 provinces, including numbers of COVID-19 cases, meteorological parameters, air quality and population flow data, between Jan 21, 2020 and Apr 3, 2020. To evaluate the transmissibility of COVID-19, the basic reproductive ratio (R0) was calculated with the maximum likelihood "removal" method, which is based on chain-binomial model, and the association between COVID-19 and air pollutants or meteorological parameters was estimated by correlation analyses. The mean estimated value of R0 was 1.79 ± 0.31 in 29 provinces, ranging from 1.08 to 2.45. The correlation between R0 and the mean relative humidity was positive, with coefficient of 0.370. In provinces with high flow, indicators such as carbon monoxide (CO) and 24-h average concentration of carbon monoxide (CO_24 h) were positively correlated with R0, while nitrogen dioxide (NO2), 24-h average concentration of nitrogen dioxide (NO2_24 h) and daily maximum temperature were inversely correlated to R0, with coefficients of 0.644, 0.661, -0.636, -0.657, -0.645, respectively. In provinces with medium flow, only the weather factors were correlated with R0, including mean/maximum/minimum air pressure and mean wind speed, with coefficients of -0.697, -0.697, -0.697 and -0.841, respectively. There was no correlation with R0 and meteorological parameters or air pollutants in provinces with low flow. Our findings suggest that higher ambient CO concentration is a risk factor for increased transmissibility of the novel coronavirus, while higher temperature and air pressure, and efficient ventilation reduce its transmissibility. The effect of meteorological parameters and air pollutants varies in different regions, and requires that these issues be considered in future modeling disease transmissibility.

Project description:BackgroundTransmission intensity for mosquito-borne diseases are highly heterogenous and multi-factorial. Understanding risk factors associated to disease transmission allow the optimization of vector control. This study sets out to understand and compare the combined anthropogenic and environmental risk factors of four major mosquito-borne diseases, dengue, malaria, chikungunya and Japanese encephalitis in Thailand.MethodsAn integrated analysis of mosquito-borne diseases, meteorological and ambient air pollutants of 76 provinces of Thailand was conducted over 2003-2021. We explored the use of generalized linear models and generalized additive models to consider both linear and non-linear associations between meteorological factors, ambient air pollutants and mosquito-borne disease incidence. Different assumptions on spatio-temporal dependence and nonlinearity were considered through province-specific and panel models, as well as different spline functions. Disease-specific model evidence was assessed to select best-fit models for epidemiological inference downstream.ResultsAnalyses indicated several findings which can be generally applied to all diseases explored: (1) higher AH above mean values was positively associated with disease case counts (2) higher total precipitation above mean values was positively associated with disease case counts (3) extremely high temperatures were negatively associated with disease case counts (4) higher SO2 and PM2.5 surface concentrations were negatively associated with disease case counts. However, the relationships between disease and RH, non-extreme temperatures and CO surface concentration were more mixed, with directions of associations changing across the different diseases considered.ConclusionsThis study found protective and enhancing effects of meteorological and ambient air pollutant factors on mosquito-borne diseases burdens in Thailand. Further studies should employ these factors to understand and predict risk factors associated with mosquito-borne disease transmission.

Project description:BackgroundThe effects of meteorological factors and air pollutants on respiratory diseases (RDs) were various in different populations according to the demographic characteristics, and children were considered a vulnerable population. Previous studies were mainly based in cities with serious air pollution. This study aimed to qualify the lag effects of meteorological factors and air pollution on respiratory diseases among children under 18 years old in Fuzhou.MethodsMeteorological data, air pollutants concentrations and hospital admission data of Fujian Maternity and Child Health Hospital between 2015 and 2019 were collected. A Distributed Lag Nonlinear Model (DLNM) was used to evaluate the nonlinear and lagged effect of meteorological factors and air pollutants on daily RDs number. A subgroup analysis was also conducted to evaluate the effect on different sex groups and age groups.ResultsA total number of 796 125 RDs visits was included during the study period. For meteorological factors, lower mean temperature and relative humidity were significantly associated with daily RDs number (peak relative risk (RR) = 1.032 (95% confidence interval (CI) = 1.011-1.053) and 1.021 (95% CI = 1.013-1.029)), while lower wind speed showed a significant association at low range (peak RR = 0.995 (95% CI = 0.992-0.999)). Temperature warming was a significant protective factor for RDs (peak RR = 0.989 (95% CI = 0.986-0.993)). For air pollutants, SO2, NO2, PM10 and PM2.5 were all significantly associated with RDs (peak RR = 1.028 (95% CI = 1.022-1.035), 1.024 (95% CI = 1.013-1.034), 1.036 (95% CI = 1.025-1.047), 1.028 (95% CI = 1.019-1.037)), and the relationship had no threshold. The estimated RR and peak lag day did not change extremely between subgroups.ConclusionsThe findings provide statistical evidence for the prevention of child RDs. In addition, our findings suggested that even at low concentrations, air pollutants still have negative effects on the respiratory system.

Project description:As a result of the lockdown (LD) control measures enacted to curtail the COVID-19 pandemic in Wuhan, almost all non-essential human activities were halted beginning on January 23, 2020 when the total lockdown was implemented. In this study, changes in the concentrations of the six criteria air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) in Wuhan were investigated before (January 1 to 23, 2020), during (January 24 to April 5, 2020), and after the COVID-19 lockdown (April 6 to June 20, 2020) periods. Also, the relationships between the air pollutants and meteorological variables during the three periods were investigated. The results showed that there was significant improvement in air quality during the lockdown. Compared to the pre-lockdown period, the concentrations of NO2, PM2.5, PM10, and CO decreased by 50.6, 41.2, 33.1, and 16.6%, respectively, while O3 increased by 149% during the lockdown. After the lockdown, the concentrations of PM2.5, CO and SO2 declined by an additional 19.6, 15.6, and 2.1%, respectively. However, NO2, O3, and PM10 increased by 55.5, 25.3, and 5.9%, respectively, compared to the lockdown period. Except for CO and SO2, WS had negative correlations with the other pollutants during the three periods. RH was inversely related with all pollutants. Positive correlations were observed between temperature and the pollutants during the lockdown. Easterly winds were associated with peak PM2.5 concentrations prior to the lockdown. The highest PM2.5 concentrations were associated with southwesterly wind during the lockdown, and northwesterly winds coincided with the peak PM2.5 concentrations after the lockdown. Although, COVID-19 pandemic had numerous negative effects on human health and the global economy, the reductions in air pollution and significant improvement in ambient air quality likely had substantial short-term health benefits. This study improves the understanding of the mechanisms that lead to air pollution under diverse meteorological conditions and suggest effective ways of reducing air pollution in Wuhan.

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Migration and diffusion characteristics of air pollutants and meteorological influences in Northwest China: a case study of four mining areas.

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