Sequence stratigraphy and coal petrology can be used to comprehensively analyze the mechanism of extremely thick coal seams under the influence of the paleo-climate, paleo-environment, and accommodation space during a coal-forming period. Based on the vertical variations in coal quality, macerals, and lithology, key sequence surfaces were identified, including the terrestrialization surface (TeS), paludification surface (PaS), give-up transgressive surface (GUTS), accom-modation reversal surface (ARS), exposure surface (ExS), and flooding surface (FS) in thick coal seams of the Middle Jurassic Dameigou Formation in the Saishiteng Coalfield, northern Qaidam Basin. Using these key sequence surfaces, thick terrestrial coal seams can be divided into several wetting-up and drying-up cycles. In general, the vitrinite content, vitrinite/inertinite ratio (V/I), and gelification index (GI) increased from bottom to top, whereas the inertinite content decreased in the wetting-up cycles. The vertical stacking pattern considers the PaS as the bottom boundary, and the GUTS or ARS as the top boundary, representing an increasing trend in the accommodation space. However, the vitrinite content, V/I, and GI values decreased from the bottom to the top, whereas the inertinite content increased during the drying-up cycle. Another vertical stacking pattern started from the TeS, with the ExS or ARS as the top boundary, representing a decreasing trend in the accommodation space. The thick coal seams at the edge of the Saishiteng Coalfield are blocked by a large number of clastic sediments, whereas relatively few clastic sediments are found in the coalfield center; thus, a single extremely thick coal seam with good continuity can be formed. Based on the coal petrology and sequence stratigraphic analyses, a model of extremely thick coal seams superimposed on multiple peatlands was established from the basin margin to the basin center. Four to five drying-up and wetting-up cycles were predicted in accumulation variation. During a water transgression stage, new peat accumulates on the land, corresponding to a wetting-up cycle. In a water regression stage, new peat accumulates in the basin center, corresponding to a drying-up cycle. Analysis of the genesis of thick coal seams is important for the in-depth excavation of geological information during the coal-forming period and for coal resource exploration in terrestrial basins.

An early Late Cretaceous NW-SE compressional event that induced the uplift of the coastal mountains was recognized among the overall extensional regime in east China. While previous studies have explored the paleoelevation, paleogeographical extent, and possible climatic effects of coastal mountains, the exact timing of initial uplift has remained elusive. In this study, we applied detrital zircon U-Pb geochronology to sandstones from the Dasheng Group in the Yishu Rift Basin, east China. Our results suggest that the primary provenance of the Dasheng Group is intermediate-basic volcanic rocks (800–500 Ma, 330–215 Ma, and 150–122 Ma) derived from the Luxi Uplift and Sulu Orogenic Belt, and the secondary provenance is Mesoproterozoic-Paleozoic metamorphic rocks (2500–2300 Ma and 1850–1600 Ma) derived from the Jiaobei Terrane. The zircon age peaks of the Dasheng Group in the Yishu Rift Basin are nearly the same as those of the Lower Cretaceous Laiyang Group in the Jiaolai Basin. However, the proportion of pre-Mesozoic zircons decreases. For the Mesozoic zircons, although their main age peak is close to that of the Laiyang Group, their secondary age peak is similar to that of the Wangshi Group. We infer that the transitional characteristic of the Dasheng Group was caused by the initial uplift of the coastal mountains. Therefore, we speculate that the initial uplift of the coastal mountains occurred during the deposition of the Dasheng Group, and limit the maximum depositional age (MDA) of the Dasheng Group to 100–95 Ma.

Carbon and water fluxes of savannas and grasslands have large seasonal dynamics and inter-annual variation. In this study, we selected five savanna and grassland sites, each of them having 10+ years (11−21 years) of eddy covariance (EC) data, and a total of 85 site-years at these five sites which offers a unique opportunity for data analyses and model evaluation. We ran a long-term simulation (2000−2021) of the vegetation photosynthesis model (VPM, v3.0) and vegetation transpiration model (VTM, v2.0) to investigate the seasonal dynamics, interannual variation, and decadal trends of modeled gross primary production (GPP_VPM) and transpiration (T_VTM) at these sites. The seasonal dynamics of daily GPP_VPM and T_VTM track well with the seasonal dynamics of EC-based GPP (GPP_EC, R²: 0.76−0.93) and evapotranspiration (ET_EC, R²: 0.69−0.92). The inter-annual variation of annual GPP_VPM tracked well that of annual GPP_EC, with the linear regression slopes for GPP_EC versus GPP_VPM-EC ranging from 0.89 to 1.11. The simulation results of GPP_VPM and T_VTM using two different climate data sets (in situ climate data and European Center for Medium-Range Weather Forecasts Reanalysis v5 data set (ERA5)) were similar, suggesting that ERA5 data can be used for VPM/VTM simulations at large spatial scales. From 2000 to 2021, annual GPP_VPM and T_VTM had no significant inter-annual trends at one savanna and three grassland sites but increased significantly at one savanna site. The results demonstrate the potential of using VPM (v3.0) and VTM (v2.0) to predict the seasonal dynamics and inter-annual variation of GPP and T in savannas and grasslands.

Based on standardized precipitation index data, a systematic analysis was conducted of the spatiotemporal variations of drought events in China from 1978 to 2018. Drought events were identified using the run theory applied to the standardized precipitation index data set, and key variables such as drought frequency, duration, and intensity were quantified. Additionally, drought vulnerability, exposure, and resilience were calculated to comprehensively assess the regional drought risk. The spatiotemporal transmission characteristics and pathways of drought risk were further explored using the Markov chain model and its extended version based on spatial lag theory. The results revealed significant differences in the spatial and temporal distribution of drought events across China, with north-west China experiencing a particularly high frequency, duration, and intensity of droughts. Overall, the pattern of drought risk presented a gradient, being higher in the north-west and lower in the south-east. The risk was relatively stable from year to year, with few large fluctuations. Moreover, a strong spatial similarity in drought risk was observed among neighboring provinces, but there was no obvious spatial lag effect. This study provides a valuable scientific foundation for effective drought disaster risk management and the formulation of response measures.

Electricity constitutes a fundamental pillar of both the national economy and contemporary lifestyles. Monitoring electric power consumption (EPC) has important implications for energy planning, energy conservation and emission reduction, energy security, and smart city development. However, the current monitoring and evaluation of EPC is less accurate and does not allow for real-time monitoring and evaluation of EPC. This study established an EPC assessment model based on EPC data, nighttime light remote sensing technology, and GIScience methodology, aiming to analyze the spatiotemporal variation of EPC in three major urban agglomerations of China from 2012 to 2020 and estimate EPC in 2025. Furthermore, the spatial correlation of EPC was explored using Moran’ s I spatial analysis method. The results indicate that the established model has an average accuracy of 77.56% and can be used for accurate and real-time estimation of EPC. The EPC showed an increasing trend from 2012 to 2020, with the Yangtze River Delta urban agglomeration (YRD) exhibiting the highest growth rate, as high as 49.60%. The EPC in the Beijing-Tianjin-Hebei urban agglomeration (BTH) showed a negative spatial correlation. However, the YRD and the Guangdong-Hong Kong-Macao Greater Bay Area urban agglomeration (GBA) exhibited significant positive spatial correlation in EPC. The findings of this study serve a scientific basis and reference data for the development of energy policies and strategies. Furthermore, this study can help to achieve the “carbon peaking and carbon neutrality goals” proposed by the Chinese government.

Policies designed to reduce transportation emissions are known to be co-beneficial due to reductions in planet-warming greenhouse gases like carbon dioxide (CO₂) and health-harmful air pollutants, such as nitrogen dioxide (NO₂). The growing recognition of persistent racial and ethnic disparities in air pollution exposure and associated health impacts has increased demand for policy interventions aimed at systematically reducing such inequities. Here, we use a regulatory-grade air quality model focused on the Chicago region to find that medium- and heavy-duty vehicle (MHDV) tailpipe emissions account for ~22% of the area’s ambient NO₂ concentrations. Exposure to MHDV-tailpipe NO₂ in our domain is associated with 1330 (95% confidence interval (CI): 330, 2000) annual premature deaths and 1580 (95% CI: −310, 3870) new cases of pediatric asthma, disproportionately affecting census tracts with higher percentages of residents of color. Given the inequitable impacts of MHDV NO₂ exposure, we also use our model to assess the air quality, health, and equity outcomes if a policy scenario based on California’s Advanced Clean Trucks (ACT) regulation were instantaneously adopted in Illinois. We find that ACT adoption would lead to ~48% of on-road MHDVs having zero tailpipe emissions by 2050; an instantaneous transition to this policy would reduce annual mean population-weighted NO₂ concentrations by 0.98 ppb (parts per billion) (−8.4%), resulting in reductions of 500 (95% CI: −120, −750) premature deaths and 600 (95% CI: 120, −1440) fewer new pediatric asthma cases annually – with the largest health benefits observed in neighborhoods with higher percentages of residents of color. Our study highlights the benefits of implementing policy interventions focused on zero-emission MHDVs to address air pollution exposure and health impact disparities.

Mangrove forests are significant ecosystems worldwide and play a crucial role in maintaining the biodiversity of intertidal zones in tropical and subtropical regions. However, most mangroves have experienced large-scale losses due to anthropogenic activities and natural stress from environmental factors. Here, the dynamic changes in mangroves in the Dandou Sea (DDS) of the Beibu Gulf between 1987 and 2021 were analyzed via multispectral satellite remote sensing data from the Google Earth Engine Platform. The results indicated that the area of mangroves in the DDS increased from 225.90 ha in 1987 to 451.76 ha in 2021. Throughout this period, the overall mangrove area in the DDS, as well as in its western and central parts, underwent a rapid growth phase from 1987 to 1996, followed by a slow growth phase from 1997 to 2011, and eventually entered a stagnation phase from 2013 to 2021. Moreover, due to the biological invasion caused by Spartina alterniflora, the mangrove forests in this area tended toward fragmentation. Moreover, S. alterniflora suppressed the spread of mangrove forests, accounting for up to 41.69% of the total loss. In a similar vein, the local high-intensity economic activities within the tidal flat accounted for 32.55% of the mangrove loss. Additionally, the expansion of aquaculture ponds and construction land directly accounted for 9.45% and 7.91% of the mangrove loss, respectively. Furthermore, the establishment of mangrove nature reserves played a positive role in the restoration and expansion of mangroves in the DDS. Our results also demonstrated that sea level rise had little impact on mangrove retreat.

Nitrogen (N), one of the essential mineral elements, is involved in many biochemical processes and ultimately closely relates to agronomic yield. Our ability to monitor N concentrations in plants through direct tissue sampling or remote sensing has rapidly evolved as technology has advanced. However, functional relationships between morphological and physiological processes and tissue N have yet to be widely published and are needed to advance precision and predictive agricultural technologies further. Therefore, an experiment was conducted to determine the relationships between tissue N concentration and corn (Zea mays L.) morphological and physiologic characteristics. Plants were grown in pots under optimal conditions in sunlit controlled-environment chambers but with varying N supplies. Plant growth, developmental, and physiologic properties were monitored weekly. Shoot N content differed among treatments and declined over time for all treatment levels. Photosynthesis declined as N content decreased, but these decreases were largely non-stomatal limiting. Reductions in N content were due to declining chlorophyll and N balance index values and increasing flavonoids and anthocyanins. Stem elongation and leaf expansion were highly sensitive to declining N content. Below the soil surface, root growth and development rates fell and held a quadratic relationship with N content. Roots were less sensitive at low N stress levels than plant growth above the soil surface. The functional relationships produced from this study could help update crop simulation models and apply them to emerging precision agriculture technologies.

The hydrogen isotope composition of leaf wax n-alkanes (δ²H_alk) has been used to reconstruct hydroclimate conditions, yet the factors that influence it are not fully understood, particularly the control of soil pore water δ²H. This study monitored the temporal and vertical variations of peat pore water δ²H (δ²H_pw) from 2015 to 2019 in the Dajiuhu peatland, central China. Results showed that δ²H_pw was highly variable in the surface layers (0−10 cm; avg. −47‰, 1σ = 11‰) and remained almost constant in deeper depths (below 50 cm; avg. −56‰, 1σ = 2‰). The δ²H_pw of the 0−10 cm layer was strongly correlated with the preceding month’s precipitation δ²H (δ²H_p) in the adjacent area (r = 0.7, p < 0.01), indicating that δ²H_p is the main factor affecting the temporal variations of δ²H_pw in the upper layers. Moreover, the surface (0−10 cm) peat pore water slightly deviated from the local meteoric water line, suggesting that evaporation may also have an effect on the δ²H_pw. These findings emphasize the importance of precipitation isotope composition in interpreting the δ²H_alk in peat deposits under subtropical climates.