Heavy Episodes Research Articles

Elevated von Willebrand factor levels during heavy menstrual bleeding episodes limit the diagnostic utility for von Willebrand disease

BackgroundHeavy menstrual bleeding (HMB) is often the first bleeding symptom for female individuals with inherited bleeding disorders. Guidelines recommend performing the hemostatic evaluation at HMB presentation. Von Willebrand factor (VWF) levels increase with stress, making it unclear if VWF studies during acute bleeding are beneficial in diagnosing von Willebrand disease (VWD). ObjectivesTo determine the utility of testing for VWD during acute HMB. Patients/MethodsThis retrospective cohort study evaluated VWF levels of individuals presenting to the emergency department (ED) with HMB from January 1, 2017, to December 31, 2018, after prospective implementation of a clinical practice guideline recommending hemostatic evaluation in the ED. We compared VWF and factor VIII (FVIII) levels between acute presentation and follow‐up visit after bleeding resolution. We compared the diagnostic accuracy of initial and follow‐up labs. ResultsDuring the study period, 221 individuals were seen in the ED for acute HMB, and 39 had VWD testing at both time points. Median FVIII and VWF levels were higher during acute bleeding than at follow‐up. The difference in VWF levels between visits was negligible when initial FVIII value was normal. Overall incidence of VWD was 7.5%; 69% of those with VWD had low VWF levels during acute HMB. ConclusionVWD testing during acute HMB detects the majority of individuals with VWD but also leads to elevated levels of VWF, potentially limiting at the accuracy of diagnostic labs during acute bleeding episodes. Delayed testing until resolution of anemia and active bleeding may provide more accurate diagnostic evaluation for VWD.

Development of Three‐Dimensional Variational Data Assimilation Method of Aerosol for the CMAQ Model: An Application for PM2.5 and PM10 Forecasts in the Sichuan Basin

AbstractA three‐dimensional variational (3DVAR) data assimilation method for the aerosol variables of the community multiscale air quality (CMAQ) model was developed. This 3DVAR system uses PM2.5 and PM2.5‐10 (the difference between PM10 and PM2.5) as control variables and used the AERO6 aerosol chemical mechanism in the CMAQ model. Two parallel experiments (one with and one without data assimilation [DA]) were performed to evaluate the assimilating effects of surface PM2.5 and PM10 during a heavy haze episode from January 13 to 16, 2018 in the Sichuan Basin (SCB) region. The results show that simulations without DA clearly underestimated PM2.5 and PM10 concentrations, and the analysis field with aerosol DA is skillful at fitting the observations and effectively improving subsequent forecasts of PM2.5 and PM10. For the analysis fields of PM2.5 and PM10 after DA comparing with those without DA, the correlation coefficient (CORR) of PM2.5 and PM10 increased by 0.59 and 0.65, the bias (BIAS) increased by 82.29 and 125.41 μg/m3, and the root mean square error (RMSE) declined by 73.69 and 116.30 μg/m3, respectively. Improvement of subsequent 24‐h forecasts of PM2.5 and PM10 with DA is also significant. Statistical results of forecasting improvement with DA indicated that the CORR, BIAS, and RMSE for PM2.5 and PM10 at 78% and 89% of stations in the SCB region are improved, respectively. From the perspective of assimilation duration time, the improvement of PM2.5 and PM10 can be maintained for ∼24 h.

Heavy ozone pollution episodes in urban Beijing during the early summertime from 2014 to 2017: Implications for control strategy

Ground-level ozone (O3) has become the principal air pollutant in Beijing during recent summers. In this context, an investigation of ambient concentrations and variation characteristics of O3 and its precursors in May and June from 2014 to 2017 in a typical urban area of Beijing was carried out, and the formation sensitivity and different causes of heavy O3 pollution (HOP, daily maximum 8-h O3 (MDA8h O3)>124 ppbv) were analyzed. The results showed that the monthly assessment values of the O3 concentrations (the 90th percentile MDA8h O3 within one month) were highest in May or June from 2014 to 2017, and the values presented an overall increasing trend. During this period, the number of O3 pollution days (MDA8h O3 > 75 ppbv) also showed an increasing trend. During the HOP episodes, the concentrations of volatile organic compounds (VOCs), nitrogen oxides (NOX), and carbon monoxide (CO) were higher than their respective mean values in May and June, and the meteorological conditions were more conducive to atmospheric photochemical reactions. The HOP episodes were mainly caused by local photochemical formation. From 2014 to 2017, O3 formation during the HOP episodes shifted from VOC and NOX mixed-limited to VOC-limited conditions, and O3 formation was most sensitive to anthropogenic VOCs. Six categories of VOC sources were identified, among which vehicular exhaust contributed the most to anthropogenic VOCs. The VOC concentrations and OFPs of anthropogenic sources have decreased significantly in recent years, indicating that VOC control measures have been effective in Beijing. Nevertheless, NOX concentrations did not show an evident decreasing trend in the same period. Therefore, more attention should be devoted to O3 pollution control in May and June; control measure adjustments are needed according to the changes in O3 precursors, and coordinated control of VOCs and NOX should be strengthened in long-term planning.

Impacts of Aerosol-Radiation Interactions on the Wintertime Particulate Pollution under Different Synoptic Patterns in the Guanzhong Basin, China

The effects of aerosol–radiation interactions (ARI) are not only important for regional and global climate, but they can also drive particulate matter (PM) pollution. In this study, the ARI contribution to the near-surface fine PM (PM2.5) concentrations in the Guanzhong Basin (GZB) is evaluated under four unfavorable synoptic patterns, including “north-low”, “transition”, “southeast-trough”, and “inland-high”, based on WRF-Chem model simulations of a persistent heavy PM pollution episode in January 2019. Simulations show that ARI consistently decreases both solar radiation reaching down to the surface (SWDOWN) and surface temperature (TSFC), which then reduces wind speed, induces sinking motion, and influences cloud formation in the GZB. However, large differences under the four synoptic patterns still exist. The average reductions of SWDOWN and daytime TSFC in the GZB range from 15.2% and 1.04°C in the case of the “transition” pattern to 26.7% and 1.69°C in the case of the “north-low” pattern, respectively. Furthermore, ARI suppresses the development of the planetary boundary layer (PBL), with the decrease of PBL height (PBLH) varying from 18.7% in the case of the “transition” pattern to 32.0% in the case of the “north-low” pattern. The increase of daytime near-surface PM2.5 in the GZB due to ARI is 12.0%, 8.1%, 9.5%, and 9.7% under the four synoptic patterns, respectively. Ensemble analyses also reveal that when near-surface PM2.5 concentrations are low, ARI tends to lower PM2.5 concentrations with decreased PBLH, which is caused by enhanced divergence or a transition from divergence to convergence in an area. ARI contributes 15%–25% toward the near-surface PM2.5 concentrations during the severe PM pollution period under the four synoptic patterns.

IMDAA: High Resolution Satellite-era Reanalysis for the Indian Monsoon Region

AbstractA high resolution regional reanalysis of the Indian Monsoon Data Assimilation and Analysis (IMDAA) project is made available to researchers for deeper understanding of the Indian monsoon and its variability. This 12 km resolution reanalysis covering the satellite-era from 1979 to 2018 using 4D-Var data assimilation method and the UK Met Unified Model is presently the highest resolution atmospheric reanalysis carried out for the Indian monsoon region. Conventional and satellite observations from different sources are used, including Indian surface and upper air observations, of which some were not used in any previous reanalyses. Various aspects of this reanalysis, like quality control and bias correction of observations, data assimilation system, land surface analysis, and verification of reanalysis products, are presented in this paper. Representation of important weather phenomena of each season over India in the IMDAA reanalysis verifies reasonably well against India Meteorological Department (IMD) observations and compares closely with ERA5. Salient features of the Indian summer monsoon are found to be well represented in the IMDAA reanalysis. Characteristics of major semi-permanent summer monsoon features (e.g., Low-level Jet and Tropical Easterly Jet) in IMDAA reanalysis are consistent with ERA5. The IMDAA reanalysis has captured the mean, inter-annual, and intra-seasonal variability of summer monsoon rainfall fairly well. IMDAA produces a slightly cooler winter and a hotter summer than the observations; the reverse for ERA5. IMDAA captured the fine-scale features associated with a notable heavy rainfall episode over complex terrain. In this study, the fine grid spacing nature of IMDAA is compromised due to the lack of comparable resolution observations for verification.

Potential of stochastic methods for improving convection-permitting ensemble forecasts of extreme events over the Western Mediterranean

The design of convection-permitting ensemble prediction systems capable of producing accurate forecasts of disruptive events is an extraordinarily challenging effort. The difficulties associated with the detection of extreme events found at these scales motivates the research of methodologies that efficiently sample relevant uncertainties. This study investigates the potential of multiple techniques to account for model uncertainty. The performance of various stochastic schemes is assessed for an exceptional heavy precipitation episode which occurred in eastern Spain. In particular, the stochastic strategies are compared to a multiphysics approach in terms of both spread and skill. The analyzed techniques include stochastic parameterization perturbation tendency and perturbations to influential parameters within the microphysics scheme. The introduction of stochastic perturbations to the microphysics processes results in a larger ensemble spread throughout the entire simulation. Conversely, modifications to microphysics parameters generate small-scale perturbations that rapidly grow over areas with high convective instability, in contrast to the other methods, which produce more widespread perturbations. A conclusion of specific interest for the western Mediterranean, where deep moist convection and local orography play an important role, is that stochastic methods are shown to outperform a multiphysics-based ensemble for this case, indicating the potential positive impact of stochastic parameterizations for the forecast of extreme events in the region.

Mitigating NOX emissions does not help alleviate wintertime particulate pollution in Beijing-Tianjin-Hebei, China.

Stringent mitigation measures have reduced wintertime fine particulate matter (PM2.5) concentrations by 42.2% from 2013 to 2018 in the Beijing-Tianjin-Hebei (BTH) region, but severe PM pollution still frequently engulfs the region. The observed nitrate aerosols have not exhibited a significant decreasing trend and constituted a major fraction (about 20%) of the total PM2.5, although the surface-measured NO2 concentration has decreased by over 20%. The contributions of nitrogen oxides (NOX) emissions mitigation to the nitrate and PM2.5 concentrations and how to alleviate nitrate aerosols efficiently under the current situation still remains elusive. The WRF-Chem model simulations of a persistent and heavy PM pollution episode in January 2019 in the BTH reveal that NOX emissions mitigation does not help lower wintertime nitrate and PM2.5 concentrations under current conditions in the BTH. A 50% reduction in NOX emissions only decreases nitrate mass by 10.3% but increases PM2.5 concentrations by 3.2%, because the substantial O3 increase induced by NOX mitigation offsets the HNO3 loss and enhances sulfate and secondary organic aerosols formation. Our results are further consolidated by the occurrence of severe PM pollution in the BTH during the COVID-19 outbreak, with a significant reduction in NO2 concentration. Mitigation of NH3 emissions constitutes the priority measure to effectively lower the nitrate and PM2.5 concentrations in the BTH under current conditions, with 35.5% and 12.7% decrease, respectively, when NH3 emissions are reduced by 50%.

Evaluation of WRF-Chem simulations on vertical profiles of PM2.5 with UAV observations during a haze pollution event

Accurate simulation of PM2.5 vertical distribution is crucial to understand the formation, transport, and dispersion mechanisms of aerosols, and protect the public from exposure to high levels of air pollutants. While most of the current model evaluations are limited to near-surface variables, vertical profiles of simulated PM2.5 are rarely evaluated. In this study, the measurements with unmanned aerial vehicle (UAV) are used to evaluate the WRF-Chem simulated vertical profiles of PM2.5, potential temperature, water vapor, and winds while surface meteorological fields and air pollutants are evaluated with various observational data during a heavy aerosol pollution episode that occurred on December 22–25, 2017 in Nanjing, China. Results show that the simulated surface meteorology and air quality agree well with the observations. Vertical profile shapes and magnitude of PM2.5 are reasonably captured by the model under the convective conditions during the daytime, but not in the nighttime. It is noticed that a well-mixed vertical structure of PM2.5 concentration, a typical feature of the daytime convective boundary layer is observed in the nocturnal boundary layer (NBL) but not captured by the WRF-Chem model and PM2.5 concentrations are over-predicted significantly during the nighttime. The over-predictions of surface PM2.5 and vertical profiles are improved substantially by increasing the minimum value of eddy diffusivity. This study indicates the importance of refinement of parameterization schemes in reproducing the ABL vertical structures and PM2.5 concentrations, especially for the NBL with heavy pollution conditions.

Characteristics and Health Risk Assessment of PM2.5-Bound PAHs during Heavy Air Pollution Episodes in Winter in Urban Area of Beijing, China

PM2.5 level has decreased significantly in Beijing in recent years due to the strict air quality control measures taken in Jingjinji Region and the surrounding areas. However, the variation characteristics of the concentrations of PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) in Beijing in recent years are still not so clear. In order to understand the pollution status of PM2.5-bound PAHs in Beijing, fifteen PAHs were measured in a typical urban area of Beijing from 1 March to 20 March 2018. The average mass concentration of the 15 PAHs was 21 ng/m3 and higher in the nighttime than that in the daytime. The proportion of 4-ring PAHs in 15 PAHs was highest (43%), while 6-ring PAHs was lowest (10%). The levels of PAHs were higher during heavy pollution episodes than those in non-heavy pollution episodes, and the proportions of 5- and 6-ring PAHs were increased during a heavy pollution episode. PAHs posed obvious carcinogenic risks to the exposed populations, and the risk was higher during heavy pollution episodes than the average value of the whole monitoring period. The main sources of PAHs were traffic emissions and coal/biomass burning. Air masses from the south-southeast had a great influence on the PM2.5 levels during a heavy pollution episode. It is recommended that not only the PM2.5 levels but also the PAHs levels bounded in PM2.5 should be controlled to protect human health in Beijing.

Domain-specific consideration of future consequences and early alcohol use: a bivariate and person-centered analysis

Research into temporal psychology, and in particular its relationship with health behaviors, has grown exponentially in recent years. Accordingly, studies have shown that how individuals think and feel about the past, present, and future, is significantly related to alcohol-use behaviors. This has been shown to be particularly true where studies have applied person-centered analyses rather than just bivariate analyses. The present study sought to examine the relationship between scores on one temporal psychology measure (The Domain-Specific Consideration of Future Consequences [CFC] scale) and alcohol use behaviors in a large sample of adolescents in the United Kingdom (N = 2,199; 42.4% female). Scores on the CFC measure were operationalized both domain-specifically, and by means of cluster analyses. In bivariate analyses, reduced likelihood of past month consumption of a full drink and Heavy Episodic Drinking were significantly associated with CFC-scores, but did not appear to be domain-specific. In unadjusted analyses, CFC cluster membership was significantly related to alcohol use variables. However, when adjusted for sex, location, and sensation seeking, the result for Heavy Episodic Drinking became non-significant. Results are discussed in the context of current temporal psychology.

Observing a severe flooding over southern part of India in monsoon season of 2019

Kerala is one of the most flood prone states of India due to its geographical location and topography. In recent decades, the frequency and intensity of flood has significantly increased in Kerala. Floods that occurred in the year 2007, 2009, 2014 and 2018 resulted in heavy damage in the form of lives and properties. This research focuses on exploring a recent flood event of Kerala in July–August 2019 using observations from space. Enhanced convective activities over Kerala were resulted due to movement of a low-pressure system westwards from Bay of Bengal towards coastal Arabian Sea under favourable conditions. Results report that excess cumulative rainfall resulting from multi-day extreme precipitation events due to enhanced convection during July and August resulted in catastrophic flood events over various parts of Kerala. Kannur, Wayanad, Kozhikode and Palakkad districts of north Kerala were affected more as compared to other region. Kannur district received a cumulative rainfall of about 1300 mm from multiple rainy spells during July and August of 2019. Peak rainfall was recorded on August 08, 2019. A peak hourly rainfall of about 60 mm/h was recorded at 1230 UTC on August 08 over Kannur district. These multiple heavy to very heavy rainfall episodes led to severe flooding over Kerala resulting in huge damage. Present research emphasizes on the importance of space-borne satellite remote sensing in monitoring of flood events in order to envisage preparedness and mitigation in flood scenarios.

Proportional Trends of Continuous Rainfall in Indian Summer Monsoon

A comprehensive study on the Indian summer monsoonal rainfall (ISMR) is performed in the light of decadal changes in the continuous rainfall events and the number of rainy days using 68 years (1951–2018) of gridded rain gauge data. Non-parametric Mann–Kendall’s test is applied on total rainfall amount, the number of rainy days, number of continuous rainfall events, and rainfall magnitude to find trends over different climatic zones of India for the two periods, 1951–1984 and 1985–2018. Our results found a decreasing trend for more than 4-days of continuous rainfall events during the recent 34 years (1985–2018) compared to 1951–1984. The rate of increase/decrease in extreme/continuous rainfall events does not follow a similar trend in number of continuous rainfall events and magnitude. Moreover, the rainfall is shifted towards a lesser number of continuous rainfall days with higher magnitudes during 1985–2018. During the crop’s sow season (i.e., the first 45 days from the onset date of Indian monsoon), the total number of rainy days decreased by a half day during the last 34 years. Over the Central and North East regions of India, the number of rainfall days decreased by ~0.1 days/yr and ~0.3 days/yr, respectively, during 1985–2018. Overall, the decreasing trends in continuous rainfall days may escalate water scarcity and lead to lower soil moisture over rain-fed irrigated land. Additionally, an upsurge in heavy rainfall episodes will lead to an unexpected floods. On a daily scale, rainfall correlates with soil moisture and evaporation up to 0.87 over various land cover and land use regions of India. Continuous light-moderate rainfall seems to be a controlling factor for replenishing soil moisture in upper levels. A change in rainfall characteristics may force the monsoon-fed rice cultivation period to adopt changing rainfall patterns.

Concurrent validity of the Alcohol Purchase Task for measuring the reinforcing efficacy of alcohol: an updated systematic review and meta-analysis.

An early meta-analysis testing the concurrent validity of the Alcohol Purchase Task (APT), a measure of alcohol's relative reinforcing value, reported mixed associations, but predated a large number of studies. This systematic review and meta-analysis sought to: (1) estimate the relationships between trait-based alcohol demand indices from the APT and multiple alcohol indicators, (2) test several moderators and (3) analyze small study effects. A meta-analysis of 50 cross-sectional studies in four databases (n=18 466, females=43.32%). Sex, year of publication, number of APT prices and index transformations (logarithmic, square root or none) were considered as moderators. Small study effects were examined by using the Begg-Mazumdar, Egger's and Duval & Tweedie's trim-and-fill tests. Alcohol indicators were quantity of alcohol use, number of heavy drinking episodes, alcohol-related problems and hazardous drinking. APT indices were intensity (i.e. consumption at zero cost), elasticity (i.e. sensitivity to increases in costs), Omax (i.e. maximum expenditure), Pmax (i.e. price associated to Omax ) and breakpoint (i.e. price at which consumption ceases). All alcohol demand indices were significantly associated with all alcohol-related outcomes (r=0.132-0.494), except Pmax , which was significantly associated with alcohol-related problems only (r=0.064). The greatest associations were evinced between intensity in relation to alcohol use, hazardous drinking and heavy drinking and between Omax and alcohol use. All the tested moderators emerged as significant moderators. Evidence of small-study effects was limited. The Alcohol Purchase Task appears to have concurrent validity in alcohol research. Intensity and Omax are the most relevant indices to account for alcohol involvement.

Impacts of meteorology and emission variations on the heavy air pollution episode in North China around the 2020 Spring Festival.

Based on the Weather Research and Forecasting model and the Models-3 community multi-scale air quality model (WRF-CMAQ), this study analyzes the impacts of meteorological conditions and changes in air pollutant emissions on the heavy air pollution episode occurred over North China around the 2020 Spring Festival (January to Februray 2020). Regional reductions in air pollutant emissions required to eliminate the PM2.5 heavy pollution episode are also quantified. Our results found that meteorological conditions for the Beijing-Tianjin-Hebei and surrounding “2+26” cities are the worst during the heavy pollution episode around the 2020 Spring Festival as compared with two other typical heavy pollution episodes that occurred after 2015. However, because of the substantial reductions in air pollutant emissions in the “2+26” cities in recent years, and the 32% extra reduction in emissions during January to February 2020 compared with the baseline emission levels of the autumn and winter of 2019 to 2020, the maximum PM2.5 level during this heavy pollution episode around the 2020 Spring Festival was much lower than that in the other two typical episodes. Yet, these emission reductions are still not enough to eliminate regional heavy pollution episodes. Compared with the actual emission levels during January to February 2020, a 20% extra reduction in air pollutant emissions in the “2+26” cities (or a 45% extra reduction compared with baseline emission levels of the autumn and winter of 2019 to 2020) could help to generally eliminate regionwide severe pollution episodes, and avoid heavy pollution episodes that last three or more consecutive days in Beijing; a 40% extra reduction in emissions (or a 60% extra reduction compared with baseline emission levels of the autumn and winter of 2019 to 2020) could help to generally eliminate regionwide and continuous heavy pollution episodes. Our analysis finds that during the clean period after the heavy pollution episode around the 2020 Spring Festival, the regionwide heavy pollution episode would only occur with at least a 10-fold increase in air pollutant emissions.

Behavioral economics and the aggregate versus proximal impact of sociality on heavy drinking

BackgroundBehavioral economic theory predicts decisions to drink are cost benefit analyses, and heavy episodic drinking occurs when benefits outweigh costs. Social interaction is a known benefit associated with alcohol use. Although heavy drinking is typically considered more likely during more social drinking events, people who drink heavily in isolation tend to report greater severity of use. This study explicitly disaggregates between-person and within-person effects of sociality on heavy episodic drinking and examines behavioral economic moderators. MethodsWe used day-level survey data over an 18-week period in a community adult sample recruited through crowdsourcing (mTurk; N = 223). Behavioral economic indices were examined to determine if macro person-level variables (alcohol demand, delay discounting, proportionate alcohol-related reinforcement [R-ratio]) interact with event-level social context to predict heavy drinking episodes. ResultsMixed effect models indicated significant between-person and within-person social context associations. Specifically, people with a higher proportion of total drinking occasions in social contexts had decreased odds of heavy drinking, whereas being in a social context for a specific drinking occasion was associated with increased odds of heavy drinking. Person-level R-Ratio, demand elasticity, and breakpoint variables interacted with social context to predict heavy episodic drinking, such that the event-level social context association was stronger when R-Ratios, alcohol price insensitivity, and demand breakpoints were high. ConclusionsThese results demonstrate an ecological fallacy, in which the size and direction of effects were divergent at different levels of analysis, and highlight the potential for merging behavioral economic variables with proximal contextual effects to predict heavy drinking.

Heavy Pollution Episode in Tianjin Based on UAV Meteorological Sounding and Numerical Model

Pollution occurs in the boundary layer, and the thermal and dynamic vertical structure of the boundary layer has a significant influence on the formation of heavy pollution episodes. Based on unmanned aerial vehicle (UAV) sounding, ground-based remote sensing and numerical modeling, this paper analyzes the vertical structure of the boundary layer and the causes of pollution during the heavy pollution episode in Tianjin from January 10 to 15, 2019, with a view to strengthening the understanding of the influence law of boundary layer processes on heavy pollution in northern coastal cities and improving the accuracy of weather forecasts and heavy pollution warnings. The results show that atmospheric temperature stratification had a significant influence on the formation, persistence, and dissipation of heavy pollution episodes. During an episode, accompanied by the development and dissipation of the inversion layer, a high PM2.5 concentration area developed to the upper atmosphere with a height of over 300 m in the daytime and compressed to the ground at night with a height about 100 m. When fog appeared and continued in the daytime, the vertical structure characteristics of the boundary layer changed. A temperature inversion above the fog restrained the diffusion of pollutants to the upper air and made the contribution of turbulence vertical mixing process decrease significantly in the daytime, leading to the persistence and development of heavy pollution near the surface. Regional pollution transport accounted for 66.6% during the episode, which was closely related to regional pollution transport. Regional pollution transport mainly appeared at the top of the boundary layer and above the fog inversion layer where high wind speeds occurred. Pollutants were transported to the ground by a sinking motion as the boundary layer and fog height changed. This is how regional pollution transport occurred when Tianjin was controlled by a weak high pressure field in the north. The vertical structure of the boundary layer also affected the improvement of air quality by cold air. The strong temperature inversion at the top of the fog resulted in the failure of the cold air to transmit to the ground through turbulent shear stress in the S3 stage. There was an obvious difference in wind speed between the upper and lower air. The influence of cold air on the ground was delayed, and the effect of it was weakened. Thus, the heavy pollution episode could not be alleviated completely.

Flood Hazard Mapping in Rural Area: Case of Ephemeral Watercourses in SidiBoulenouar Zone

The eastern region of Morocco is characterized by an arid to semi-arid climate. It is often confronted with heavy rainfall episodes that can generate floods that can cause adverse human and property damage. This work studies hydrological risk in the SidiBoulenouar area (Oujda province) to model floods and map risk areas. The method used is to determine the watersheds and their watercourses, then to calculate the flows with the mathematical formulas. Topographic data were extracted from a 12.5-m resolution DEM derived from the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer). GDEM (Global DEM). The DEM was used to delimit the hydrographic network with ArcMap software. The use of HEC RAS 1D was necessary to delimit the flooding area. The results of the 1D hydraulic modeling of the centennial flood showed that four ephemeral watercourses landlock the rural area of SidiBoulenouar at the time of the floods.

Characteristics, evolution, and potential source regions of submicron aerosol in Beijing, China

Atmospheric fine particulate pollution has been a dramatically environmental concern in all seasons in the megacity Beijing in recent years. A long-term real-time monitoring campaign of non-refractory submicron aerosol (NR-PM1) at a southeastern urban site in Beijing from July 13, 2017 to May 26, 2018 using an Aerodyne Aerosol Chemical Speciation Monitor (ACSM) was carried out to investigate the characteristics and evolution processes of NR-PM1 and its potential source effects. The annual average concentration of NR-PM1 during the entire study period was 40.8 μg/m3, lower than that of NR-PM1 from July 2011 to June 2012, and its seasonal variation presented the order of autumn and spring > winter > summer. The average concentration of organic species Org in the entire study was 15.1 μg/m3 and accounted for 37% of NR-PM1, being consistently a significant component of NR-PM1 in the four seasons. The average concentrations of SO42− and NO3− were 8.6 and 11.1 μg/m3, respectively, accounting for 21% and 27% of NR-PM1, and NO3− and its contribution to NR-PM1 exceeded those of SO42−, suggesting that secondary nitrate became a more dramatic pollutant. Note that SO42− in summer accounted for 27% of NR-PM1, higher than those in the other seasons, indicating that secondary sulfate formation was greatly important in summer, however, NO3− in summer accounted for 22% of NR-PM1, lower than those in the other seasons, more likely due to relatively high temperature in summer being favorable for dissociation of nitrate. NH4+ and Cl− species presented lower mass concentrations and mass fractions, and the seasonal variation of NH4+ was similar to NO3−, yet Cl− presented a typical seasonal change related to intense fossil fuel combustion during the heating period in winter and biomass burning in autumn with an order of winter > autumn > spring > summer. All aerosol species exhibited different diurnal cycles, of which Org presented a bimodal mode, SO42− and Cl− showed a flatter diurnal pattern, however, NO3− and NH4+ displayed more similar single-peak patterns. The conversion of SO2 to SO42− presented an obvious seasonal variation with summer > autumn > spring > winter driven by different factors. The conversion of NO2 to NO3− also showed a significant seasonal change characterized by autumn > summer and spring > winter controlled by different factors. Relative humidity, temperature and wind speed during the study period were significant meteorological elements influencing NR-PM1 and its species, and heavy haze pollution episodes largely occurred under high relative humidity and low wind speed. High potential source regions influencing NR-PM1 pollution in Beijing in all seasons presented dramatically distributions related to wind directions.

Chemical characteristics and source apportionment of PM2.5 in a petrochemical city: Implications for primary and secondary carbonaceous component

To study the pollution features and underlying mechanism of PM2.5 in Luoyang, a typical developing urban site in the central plain of China, 303 PM2.5 samples were collected from April 16 to December 29, 2015 to analyze the elements, water soluble inorganic ions, organic carbon and elemental carbon. The annual mean concentration of PM2.5 was 142.3 μg/m3, and 75% of the daily PM2.5 concentrations exceeded the 75 μg/m3. The secondary inorganic ions, organic matter and mineral dust were the most abundant species, accounting for 39.6%, 19.2% and 9.3% of the total mass concentration, respectively. But the major chemical components showed clear seasonal dependence. SO42− was most abundant specie in spring and summer, which related to intensive photochemical reaction under high O3 concentration. In contrast, the secondary organic carbon and ammonium while primary organic carbon and ammonium significantly contributed to haze formation in autumn and winter, respectively. This indicated that the collaboration effect of secondary inorganic aerosols and carbonaceous matters result in heavy haze in autumn and winter. Six main sources were identified by positive matrix factorization model: industrial emission, combustion sources, traffic emission, mineral dust, oil combustion and secondary sulfate, with the annual contribution of 24%, 20%, 24%, 4%, 5% and 23%, respectively. The potential source contribution function analysis pointed that the contribution of the local and short-range regional transportation had significant impact. This result highlighted that local primary carbonaceous and precursor of secondary carbonaceous mitigation would be key to reduce PM2.5 and O3 during heavy haze episodes in winter and autumn.

Characterization of multiple atmospheric pollutants during haze and non-haze episodes in Beijing, China: Concentration, chemical components and transport flux variations

Characteristics of submicron particulate matter, including its components, during December 5–30, 2016, were comprehensively investigated in Beijing. The surface transport flux was calculated as well as the cross-border transport influence of Beijing and the North China Plain (NCP) on Beijing University of Technology (BJUT) based on the non-refractory submicron particles (NR-PM1) and species, PM2.5, and gaseous pollutant observations, together with wind vectors. The Weather Research & Forecasting (WRF) and Comprehensive Air Quality Model with Extension (CAMx) were applied to demonstrate the vertical PM2.5 flux distribution. These results showed that the monthly average concentration of NR-PM1 was 86.1 ± 86.5 μg m−3, with organics forming the major fraction (49.2 ± 11.1%), followed by NO3− (19.1 ± 6.3%), SO42− (15.8 ± 6.4%), NH4+ (10.8 ± 2.6%), and Cl− (5.1 ± 2.9%). The accumulation and dissipation of pollutants were related to the wind vector, with higher concentrations in the southern and eastern directions with low wind speed (WS), and lower concentrations in the northwestern direction with high WS. The net flux intensities were stronger from WB to BJUT for particulate matter and species, from EB to BJUT for gaseous pollutants and from NB to BJUT for all pollutants, which might attribute to the mutual influence of the pollutant concentration and wind vector. All the pollutant flux intensities were generally stronger in the heavy pollution episodes (HPEs) and red alert episodes (RAEs) than those in the non-polluted episodes (NPEs). Moreover, the PM2.5 net flux varied with the height; the maximum total net flux occurred at a height of 252 m. The variations in PM2.5 flux at the high-altitude layer were similar to those at the low-altitude layer, in which the former was approximately 1.5–2 times the latter. Furthermore, the external transport could exert important influence before reaching the most severe stage of pollution, while the local emissions had a greater potential to form heavy pollution extremes. Overall, the aforementioned results could provide the scientific support for proposing effective joint control measures and mitigating the adverse effects of heavy pollution in NCP.