The main objectives of this study were (1) investigation of the temporal variations of ambient fine particulate matter (PM2.5) and ground level ozone (O3) concentrations in Tehran megacity, the ...capital and most populous city in Iran, over a 10-year period from 2006 to 2015, and (2) estimation of their long-term health effects including all-cause and cause-specific mortality. For the first goal, the data of PM2.5 and O3 concentrations, measured at 21 regulatory monitoring network stations in Tehran, were obtained and the temporal trends were investigated. The health impact assessment of PM2.5 and O3 was performed using the World Health Organization (WHO) AirQ+ software updated in 2016 by WHO European Centre for Environment and Health. Local baseline incidences in Tehran level were used to better reveal the health effects associated with PM2.5 and O3. Our study showed that over 2006–2015, annual mean concentrations of PM2.5 and O3 varied from 24.7 to 38.8 μg m−3 and 35.4 to 76.0 μg m−3, respectively, and were significantly declining in the recent 6 years (2010–2015) for PM2.5 and 8 years (2008–2015) for O3. However, Tehran citizens were exposed to concentrations of annual PM2.5 exceeding the WHO air quality guideline (WHO AQG) (10 μg m−3), U.S. EPA and Iranian standard levels (12 μg m−3) during entire study period. We estimated that long-term exposure to ambient PM2.5 contributed to between 24.5% and 36.2% of mortality from cerebrovascular disease (stroke), 19.8% and 24.1% from ischemic heart disease (IHD), 13.6% and 19.2% from lung cancer (LC), 10.7% and 15.3% from chronic obstructive pulmonary disease (COPD), 15.0% and 25.2% from acute lower respiratory infection (ALRI), and 7.6% and 11.3% from all-cause annual mortality in the time period. We further estimated that deaths from IHD accounted for most of mortality attributable to long-term exposure to PM2.5. The years of life lost (YLL) attributable to PM2.5 was estimated to vary from 67,970 to 106,706 during the study period. In addition, long-term exposure to O3 was estimated to be responsible for 0.9% to 2.3% of mortality from respiratory diseases. Overall, long-term exposure to ambient PM2.5 and O3 contributed substantially to mortality in Tehran megacity. Air pollution is a modifiable risk factor. Appropriate sustainable control policies are recommended to protect public health.
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•Long-term trends and health impacts of PM2.5 and O3 in Tehran were evaluated from 2006–2015.•Tehran citizens were exposed to annual PM2.5 approximately 2 to 4 times higher than the WHO guideline level at all times.•Annual mean O3 concentrations declined significantly over the whole period study.•In 2015, approximately 3800 deaths (> 10 per day) were attributable to long-term exposure to ambient PM2.5 in Tehran.
Brain activity continuously fluctuates over time, even if the brain is in controlled (e.g., experimentally induced) states. Recent years have seen an increasing interest in understanding the ...complexity of these temporal variations, for example with respect to developmental changes in brain function or between‐person differences in healthy and clinical populations. However, the psychometric reliability of brain signal variability and complexity measures—which is an important precondition for robust individual differences as well as longitudinal research—is not yet sufficiently studied. We examined reliability (split‐half correlations) and test–retest correlations for task‐free (resting‐state) BOLD fMRI as well as split‐half correlations for seven functional task data sets from the Human Connectome Project to evaluate their reliability. We observed good to excellent split‐half reliability for temporal variability measures derived from rest and task fMRI activation time series (standard deviation, mean absolute successive difference, mean squared successive difference), and moderate test–retest correlations for the same variability measures under rest conditions. Brain signal complexity estimates (several entropy and dimensionality measures) showed moderate to good reliabilities under both, rest and task activation conditions. We calculated the same measures also for time‐resolved (dynamic) functional connectivity time series and observed moderate to good reliabilities for variability measures, but poor reliabilities for complexity measures derived from functional connectivity time series. Global (i.e., mean across cortical regions) measures tended to show higher reliability than region‐specific variability or complexity estimates. Larger subcortical regions showed similar reliability as cortical regions, but small regions showed lower reliability, especially for complexity measures. Lastly, we also show that reliability scores are only minorly dependent on differences in scan length and replicate our results across different parcellation and denoising strategies. These results suggest that the variability and complexity of BOLD activation time series are robust measures well‐suited for individual differences research. Temporal variability of global functional connectivity over time provides an important novel approach to robustly quantifying the dynamics of brain function.
Practitioner Points
Variability and complexity measures of BOLD activation show good split‐half reliability and moderate test–retest reliability.
Measures of variability of global functional connectivity over time can robustly quantify neural dynamics.
Length of fMRI data has only a minor effect on reliability.
We systematically investigate split‐half and test–retest reliability for several different variability and complexity measures derived from fMRI data under task‐free (resting‐state; shown here) and seven different task conditions. Temporal variability of BOLD activity and global functional connectivity over time provides important approaches to robustly quantifying the dynamics of brain function.
Forest canopies are the functional interface between ecosystem and the atmospheric nitrogen (N) deposition. However, the sources of spatio‐temporal variability and intra‐event variation of N ...deposition via throughfall (TF) remain ambiguous. Here, we analysed TF samples for concentrations and fluxes of ammonium (NH4+) and nitrate (NO3−) using an array of 20 fixed‐position collectors on an event and within event basis throughout the 2019 growing season in a Chinese pine plantation, Northern China. Results showed that the volume weighted mean concentrations of NH4+ and NO3− in TF were significantly higher than those in bulk precipitation (BP) during the study period. A canopy budget model indicated that canopy uptake was more dominant than dry deposition for NH4+, while the reverse was true for NO3−. This caused a comparable TF NH4+ flux but an enhanced TF NO3− fluxes compared to BP. The intra‐event trend and magnitude of TF NH4+ and NO3− concentrations were influenced by the antecedent dry period and rainfall intensity, and indicated that biological nitrification may occur in the canopies. In addition, due to the larger of canopy NH4+ uptake that counteracted the amplifying effect of dry deposition, the spatial variability of TF NH4+ concentration was significantly lower than that of TF NO3− concentration, and exhibited more temporal persistence. No relationship was found between the spatial distribution of TF NH4+ concentration and the TF amount, the distance to the nearest trunk, nor the canopy cover, whereas the TF NO3− concentration was significantly related to the TF amount and the canopy cover. These findings can enhance our understanding of N processes within canopies, and have important implications for evaluating the impacts of N deposition in forest ecosystems.
Canopy modification of atmospheric inorganic nitrogen deposition in a pine plantation.
Knowledge of the spatial–temporal variability of soil water content is critical for water management and restoration of vegetation in semi‐arid areas. Using the temporal stability method, we ...investigated soil water relations and spatial–temporal variability of volumetric soil water content (VSWC) in the grassland–shrubland–forest transect at a typical semi‐arid subalpine ecosystem in the Qilian Mountains, northwestern China. The VSWC was measured on 48 occasions to a depth of 70 cm at 50 locations along a 240‐m transect during the 2016–2017 growing seasons. Results revealed that temporal variability in VSWC in the same soil layer in the three vegetation types and averaged across vegetation types tended to exhibit similar patterns of a decrease with increasing soil depth. Temporal stability in each vegetation type was stronger with an increase in soil depth. However, the results of temporal stability determined with standard deviation of relative difference (SDRD) disagreed with those based on the Spearman's rank correlation coefficient; the forest site had the highest Spearman rank correlation coefficient while the shrubland—the smallest SDRD in the 0–20 cm soil layer. Correlation analyses of VSWCs between two vegetation types indicated that soil water was related among all three vegetation types at the 0–20, and 0–70 cm soil layer, but in the 20–40 and 40–70 cm soil layers, significant correlation (p < .01) occurred only between adjacent vegetation types. In the upper soil layer (0–20 cm), soil water relations were mainly affected by surface runoff. In the lower soil layer (20–40 and 40–70 cm), soil water relations among the three vegetation types were highly complex, and probably resulting from a combination of root distribution and activity, interflow, and the impact of deep soil freeze–thaw dynamics. These results suggest that the factors affecting soil water are complex, and further research should address the relative importance of and interactions among different determining factors.
Soil water relations and spatial–temporal variability were analysed in a typical ecosystem.
Soil water relations between adjacent vegetation types only existed at certain soil depths.
Factors affecting soil water relations among vegetation types are complex at the transect scale.
Abstract
In this paper we quantify the temporal variability and image morphology of the horizon-scale emission from Sgr A*, as observed by the EHT in 2017 April at a wavelength of 1.3 mm. We find ...that the Sgr A* data exhibit variability that exceeds what can be explained by the uncertainties in the data or by the effects of interstellar scattering. The magnitude of this variability can be a substantial fraction of the correlated flux density, reaching ∼100% on some baselines. Through an exploration of simple geometric source models, we demonstrate that ring-like morphologies provide better fits to the Sgr A* data than do other morphologies with comparable complexity. We develop two strategies for fitting static geometric ring models to the time-variable Sgr A* data; one strategy fits models to short segments of data over which the source is static and averages these independent fits, while the other fits models to the full data set using a parametric model for the structural variability power spectrum around the average source structure. Both geometric modeling and image-domain feature extraction techniques determine the ring diameter to be 51.8 ± 2.3
μ
as (68% credible intervals), with the ring thickness constrained to have an FWHM between ∼30% and 50% of the ring diameter. To bring the diameter measurements to a common physical scale, we calibrate them using synthetic data generated from GRMHD simulations. This calibration constrains the angular size of the gravitational radius to be
4.8
−
0.7
+
1.4
μ
as, which we combine with an independent distance measurement from maser parallaxes to determine the mass of Sgr A* to be
4.0
−
0.6
+
1.1
×
10
6
M
⊙
.
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The Sudokwon landfill (SL) in the Seoul metropolitan area, South Korea, is among the world’s largest landfills, striving to curtail landfill gas (LFG) emissions and achieve carbon ...neutrality by 2050. Since 2005, the SL Management Corporation (SLC) has measured LFG emissions (i.e., methane (CH4) and carbon dioxide (CO2)) using a dynamic flux chamber proposed by the US EPA. However, uncertainty prevails in validating the reduction of LFG emissions due to the limited spatiotemporal data coverage. In 2020, an eddy covariance (EC) system was installed to enhance measurements, revealing highly fluctuating LFG emissions driven by waste layer LFG production, LFG collection, and atmospheric pressure changes. During the study period, the annual CH4 emission increased slightly from 465.0 ± 4.2 to 485.5 ± 6.4 g C m−2, while that of CO2 decreased by 2/3 (from 408.7 ± 16.5 to 270.6 ± 18.8 g C m−2), primarily due to the doubled CO2 uptake by the vegetated topsoil. Our first long-term (March 2020 to February 2022) quasi-continuous monitoring using EC (with a gap-filling and partitioning technique based on Random Forest) emphasizes the difficulty of temporal upscaling of discontinuously observed surface emissions to quantify the LFG inventory and the need for continuous observations or suitable proxies (e.g., atmospheric CH4 concentration).
Regional‐scale soil moisture estimates are essential for several hydrological applications and for validating remote sensing‐based soil moisture products. Characterization of the regional‐scale soil ...moisture variability requires a robust in situ monitoring strategy at point scale to balance between representativeness and minimization of monitoring cost. In this study an optimal sampling design was determined to capture the spatiotemporal variability of soil moisture at watershed scale. The study was conducted for the typical Indian conditions of extreme seasonal variability that leads to very wet (during monsoon) to dry (during hot summer) in the eastern India. Soil moisture monitoring was done at 83 locations in an agricultural watershed of 500 km2 for 56 days of field campaigns across a year. Based on the analyses of 41,832 measurements collected during field campaigns, it was found that maximum numbers of required locations necessary to estimate watershed‐mean soil moisture within ±2% accuracy are 30. Moreover, five randomly selected locations were found to be sufficient for capturing the temporal variability of watershed‐mean soil moisture with an accuracy of ±3%. In addition, five most representative locations identified through time stability analysis can provide robust estimate of watershed‐mean soil moisture with accuracy of ±2%. Further, soil properties and topography are identified as significant physical parameters that jointly control the spatiotemporal persistence and variability of soil moisture in the Indian watershed. These findings will be quite useful to provide guidelines for optimizing short‐term soil moisture campaigns by sampling at few selected points representative of the watershed‐mean behavior.
Plain Language Summary
Soil moisture observations and their spatiotemporal analysis are critical for many hydrologic applications. However, few studies have ever been conducted in tropical watersheds of India. Rice cultivation and monsoon precipitation of the region creates a different hydroclimatic scenario for soil moisture dynamics as compared to other regions of the world. Using 56 ground‐based soil moisture monitoring campaigns at 83 locations in an agricultural watershed of 500 km2 across a year, this study provides insight to the soil moisture spatiotemporal variability and temporal stability features. Based on 41,832 measurements collected during field campaigns, it was found that maximum numbers of required locations necessary to estimate watershed‐mean soil moisture within ±2% accuracy are 30. Moreover, five randomly selected locations were found to be sufficient for capturing the temporal variability of watershed‐mean soil moisture with an accuracy of ±3%. In fact, five most representative locations identified through time stability analysis can provide robust estimate of watershed‐mean soil moisture with accuracy of ±2%. These findings will be quite useful to provide guidelines for optimizing short‐term soil moisture campaigns by sampling at few selected points representative of the watershed‐mean behavior.
Key Points
Spatiotemporal analysis of soil moisture is based on 41,832 in situ measurements at watershed scale (500 km2)
Soil moisture measurements at few locations are sufficient for estimation of watershed‐mean soil moisture
Significant physical parameters that jointly control the spatiotemporal variability of soil moisture are soil properties and topography
ABSTRACT
The near‐surface air temperature lapse rate (TLR), wind speed gradient (WSG), and precipitation gradient (PG) provide crucial parameters used in models of mountain climate and hydrology. The ...complex mountain terrain and vast area of the Tibetan Plateau (TP) make such factors particularly important. With daily data from 161 meteorological stations over the past 43 years (1970–2012), we analyse the spatio‐temporal variations of TLRs, WSGs, and PGs over and around TP, derived using linear regression methods and dividing the study area into zones based on spatial variations. Results of this study include: (1) The observed TLR varies from −0.46 to −0.73 °C (100 m)−1, with averaged TLRs of −0.60, −0.62, and −0.59 °C (100 m)−1 for Tmax, Tmin, and Tmean, respectively. The averaged TLR is slightly less than the global mean of −0.65 °C (100 m)−1. The spatial variability of TLR relates to climate conditions, wherein the TLR increases in dry conditions and in cold months (October–April), while it lessens in humid regions and during warm months (May–September). (2) The estimated annual WSG ranges from 0.07 to 0.17 m s−1 (100 m)−1. Monthly WSGs show a marked seasonal shift, in which higher WSGs can be explained by the high intensity of prevailing wind. (3) Positive summer PGs vary from 12.08 in the central TP to 26.14 mm (100 m)−1 in northeastern Qinghai and the southern TP, but a reverse gradient prevails in Yunnan and parts of Sichuan Province. (4) The regional warming over TP is more evident in winter, and Tmin demonstrated the most prominent warming compared with Tmax and Tmean. Environments at high elevations experience more rapid changes in temperatures (Tmax, Tmin, and Tmean) than those at low elevations, which is especially true in winter and for Tmin. Furthermore, inter‐annual variation of TLRs is linked to elevation‐dependent warming.
ABSTRACT
The mean climatology, inter‐model variability and spatio‐temporal patterns of temperature and precipitation over West Africa from Coupled Model Intercomparison Project 5 (CMIP5), ...CMIP5_SUBSET ensemble of global climate models driving COordinated Regional climate Downscaling EXperiment (CORDEX) and CORDEX multi‐model ensembles are evaluated and intercompared for the monsoon season (June–September). We find that, while CORDEX fails to outperform the simulated mean climatology of temperature by the CMIP5 ensembles, it substantially improves precipitation and provides more realistic fine‐scale features tied to local topography and landuse. This improved performance over the region is found to depend more on the internal models physics than the driving boundary conditions and results from a more consistent and realistic simulation of monsoon precipitation across the various regional climate models (RCMs). Rotated empirical orthogonal function (REOF) analysis indicates that the CORDEX ensemble captures better the spatio‐temporal variability of both temperature and precipitation (first REOF mode), in particular depicting the warming and Sahel precipitation recovery in recent decades over West Africa. On the other hand, the spatial patterns and associated time series of the last two REOF modes in CORDEX mostly follow the CMIP5_SUBSET pointing towards a strong role of the boundary forcing in the RCM simulation of precipitation variability.
Reliable and complete knowledge of the historical floods is necessary for understanding the extreme hydrological dynamics of the rivers, their natural variability and anthropic changes. In this work ...we reconstruct the most important floods of the Ebro basin during the last 400 years in different areas of the basin. The analysis is based on four different areas: the Ebro River at Zaragoza, the Cinca River at Fraga, the Segre River at Lleida, and the Ebro River near its mouth at Tortosa.
Based on a documentary research, we have first obtained relevant information about the initial conditions (rainfall duration and distribution, snow cover influence) and the maximum flood heights that allow to reconstruct the maximum peak flows by using hydraulic models and to calculate the subbasins contributions.
The results show four main types of extreme floods: a) those affecting simultaneously all the subbasins with the highest peak discharges (Ebro at Tortosa in 1787: 0.15 m3 s−1 km−2); b) those originated at the western basin, upstream from Zaragoza, with an Atlantic origin, presenting moderate maximum peak flows, caused by persistent winter rainfall and where snowmelt significantly contributes to the flood; c) those originating at the central Pyrenean subbasins, with Mediterranean origin, occurring, with high peak discharges. These mainly occur during autumn as a consequence of rainfalls of different duration (between 3 days and 1 month), and without significant snow thawing and d) finally, less frequent but very intense flash floods events centered in the Lower Ebro area with low peak flows.
In terms of frequency, two different periods can be distinguished: from 1600 until 1850, the frequency of events is low; since 1850 the frequency of events is clearly higher, due to an increase of the climatic variability during last stages of the Little Ice Age. From the 1960's reservoirs construction modifies discharges regime.
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•Analysis of the major floods on the Ebro river since 1600.•Spatial and temporal distribution of the floods in the whole basin.•Contributions of the different main tributaries at the mouth.•Patterns and type of precipitation dominating the different subbasins.•Role of the synoptic and large scale atmospheric systems and climatic variability.
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