Search Results (72)

Against the backdrop of China’s “dual carbon” targets, the energy transition is accelerating. However, the expansion of onshore renewables is often constrained by land scarcity. Offshore areas thus present a promising alternative. In this study, high-resolution wind field data from 1995 to 2024 were generated using the WRF model driven by ERA5 reanalysis, enabling a 30-year spatiotemporal assessment of offshore wind power density (at 160 m hub height) and photovoltaic potential (PVP) across China’s four major seas—the Bohai Sea, Yellow Sea, East China Sea, and South China Sea. The results show clear spatial and seasonal patterns: solar PV potential decreases from south to north, with the South China Sea exhibiting the highest and most stable annual average PVP (16–18%) and summer peaks exceeding 25%. Wind energy resources are spatially heterogeneous; the East China Sea and Taiwan Strait are identified as the richest zones, where wind power density frequently reaches 800–1800 W/m² during autumn and winter. Importantly, a pronounced seasonal complementarity is observed: wind peaks in autumn/winter while solar peaks in spring/summer at representative coastal sites. This study provides, for the first time, a long-term, integrated assessment of both offshore wind and solar resources over all four Chinese seas, offering quantitative data and a scientific basis for differentiated marine energy planning, optimized siting, and the design of wind–solar hybrid systems. Full article

Increasing levels of chloride in surface water are associated with detrimental effects on water quality, aquatic ecosystems, infrastructure, and human health. Numerous mass-balance studies have inferred watershed transport processes by interpreting chloride inputs and outputs, but few represent internal dynamics explicitly. We constructed a coupled water/chloride mass balance model to gain insights into storage, residence time, and transport processes in a 10-km² urban watershed. The model, which operates over a 10-year period at a daily time scale, represents storage in a dynamic soil-moisture reservoir, quick-flow runoff from storm events, and slow-flow runoff that sustains streamflow in dry weather. The calibrated model accurately represented (a)the observed transition from a streamflow enrichment regime in cold months to a dilution regime in warmer months, (b) the observed tendency for late-summer concentrations to be higher after winters with heavy snowfall, and (c) a period-of-record downward trend in chloride concentration likely associated with a downward trend in annual snowfall. Estimated chloride inputs averaged 195 metric tons per year, while the average output was 270 metric tons per year. In contrast, estimated storage was only 107 metric tons. The estimated mean residence time in groundwater was 1.27 years. This short residence time indicates that efforts to reduce inputs will manifest as decreased concentrations in streamflow on a management-relevant time scale of several years. The coupled mass balance model yielded insights into internal watershed dynamics that would not be possible from simple input/output analysis; such models can be useful tools for gaining insight into small watershed hydrology and pollutant transport. Full article

Rapid urban growth in South Indian coastal cities such as Chennai has intensified the Urban Heat Island (UHI) effect, with paved parking lots, walkways, and open spaces acting as major heat reservoirs. This study specifically compares conventional construction materials with natural and low-thermal-inertia alternatives to evaluate their relative ability to mitigate Surface Urban Heat Island (SUHI) effects. Unlike previous studies that examine isolated materials or single seasons, this pilot provides a unified, multi-season comparison of nine urban surfaces, offering new evidence on their comparative cooling performance. To assess practical mitigation strategies, a field pilot was conducted using nine surface types commonly employed in the region—concrete, interlocking tiles, parking tiles, white cooling tiles, white-painted concrete, natural grass, synthetic turf, barren soil, and a novel 10% coconut-shell biochar concrete. The rationale of this comparison is to evaluate how conventional, reflective, vegetated, and low-thermal-inertia surfaces differ in their capacity to reduce surface heating, thereby identifying practical, material-based strategies for SUHI mitigation in tropical cities. Surface temperatures were measured at four times of day (pre-dawn, noon, sunset, night) across three months (winter, transition, summer). Results revealed sharp noon-time contrasts: synthetic turf and barren soil peaked above 45–70 °C in summer, while reflective coatings and natural grass remained 25–35 °C cooler. High thermal-mass materials such as concrete and interlocked tiles retained heat into the evening, whereas grass and reflective tiles cooled rapidly, lowering late-day and nocturnal heat loads. Biochar concrete performed thermally similarly to conventional concrete but offered co-benefits of ~10% cement reduction, carbon sequestration, and sustainable reuse of locally abundant coconut shell waste. Full article

The transition from conventional fossil-fueled buses to electric buses (EBs) is accelerating in the global public transportation sector. However, owing to the limitations of battery lifespan and capacity, EBs have a shorter driving range than conventional buses, and their power consumption is highly variable depending on the ambient temperature. In addition, battery lifespans are affected by charging and discharging cycles and battery age over time in all situations, which requires a method of operation that considers these factors. In this study, we estimated the driving, heating, and cooling energy consumptions based on the dispatch schedule and actual power consumption of EBs. The estimated energy consumption was then used as an input to plan the amount of charging power by time of day to optimize the charging and battery degradation costs. The optimization methodology employed mixed-integer linear programming (MILP), which facilitates discrete charging decision-making and ensures an optimum solution for operation costs by taking cost factors into account. In this phase, the scenarios were configured according to the time-of-use (TOU) charging cost and whether or not battery degradation. Battery degradation can be divided into cycle and calendar aging. The scenarios that considered both TOU and battery degradation reduced the average operating costs by approximately 1.43, 12.3, and 5.69% in spring/fall, summer, and winter, respectively, compared with scenarios that did not consider either. Full article

Atmospheric electricity measurements are very sensitive to weather conditions. Fair weather for atmospheric electricity in Kamchatka (Russia) was determined by the method of expert assessment at an observatory. After the transition to automated digital methods for measuring meteorological parameters, the necessity to determine the criteria of fair weather appeared. In this paper we developed the criteria for fair weather based on digital measurements in summer and winter observation periods in view of a limited set of meteorological instruments. A database of fair weather since 2009 up to the present was created. We suggest the algorithm to determine fog during a day on the basis of air humidity measurements. The morning convective generator effect occurs sometimes in diurnal variations in atmospheric electricity. The morning convection maximum is determined by the sunrise time. This entails the problems of averaging the electric field diurnal variation over a long time period. We suggest taking into account the days with morning convective generator effect and the days without this effect separately when processing a long series of data. Full article

Amid the combined pressures of global carbon-reduction in architecture and the imperative of cultural heritage conservation, new courtyard-style buildings in hot-summer and cold-winter regions face a dual challenge of reconciling historical morphological constraints with contemporary comfort requirements. At the same time, the prevailing energy-efficiency codes in these regions, emphasizing high airtightness and strong insulation, have revealed shortcomings such as poor indoor air quality and insufficient summer ventilation. This study takes the Lu Residence in Dongyang, Jinhua, Zhejiang Province, as the primary case. It systematically examines the coupling mechanisms between the geometric configurations of transitional space in traditional courtyard dwellings and their environmental physical parameters using field surveys, multi-parameter environmental monitoring, and computer simulations. The results identify the optimal orientations and geometric parameters that balance summer ventilation with winter thermal buffering in hot-summer and cold-winter regions. The primary conclusions of this research are as follows: (1) The optimal orientation for axial buildings lies between 15° west of south and 15° east of south, as well as 30–60° east or west of south, with an angle of 45–60° in relation to the prevailing annual wind direction for all buildings. (2) The optimal height-to-width ratio of the courtyard is less than 1:2.5, while the range of the length-to-width ratio extends from 1:0.5 to 1:0.7. (3) The optimal eave depth varies from 900 to 1500 mm, effectively balancing winter heat retention and summer shading; however, a depth of 2400 mm is primarily advantageous for shading purposes. Furthermore, these findings are applied to the design of a new guesthouse within the conservation area of the Xu Zhen Er Gong Ancestral Hall in Yongkang, establishing a climate–geometry matching mechanism for transitional spaces. The study demonstrates that transitional space can serve as effective passive regulators, offering a scientific and sustainable pathway for the adaptive continuation of traditional courtyard architecture. Full article

Accurately quantifying the impact of weather on dynamic grid carbon intensity is crucial for power system decarbonization. This study proposes a novel, interpretable machine learning framework integrating tree-based models with SHapley Additive exPlanations (SHAP) to quantify this impact across multiple timescales via a standardized “Weather Share” metric. Applied to city-level hourly data from China, the analysis reveals that meteorological variables collectively explain 21.64% of the hourly variation in carbon intensity, with air temperature and solar irradiance being the dominant drivers. Significant temporal variations are observed: the weather share is higher in summer (29.8%) and winter (23.5%) than in transition seasons and increases markedly to 32.7% during extreme high-temperature events. The proposed framework provides a robust, quantitative tool for grid operators, offering actionable insights for weather-aware carbon reduction strategies and highlighting critical time windows for targeted interventions. Full article

Reliable long-term runoff prediction for Wudongde and Three Gorges reservoirs, two major reservoirs in the upper Yangtze River basin, is crucial for optimal operation of cascade reservoirs and hydropower generation planning. This study develops a data-driven model that integrates large-scale climate factors with a Gated Recurrent Unit (GRU) neural network to enhance runoff forecasting at lead times of 7–18 months. Key climate predictors were systematically selected using correlation analysis and stepwise regression before being fed into the GRU model. Evaluation results demonstrate that the proposed model can skillfully predict the variability and magnitude of reservoir inflow. For Wudongde Reservoir, the model achieved a mean correlation coefficient (CC) of 0.71 and Kling–Gupta Efficiency (KGE) of 0.57 during the training period, and values of 0.69 and 0.53 respectively during the testing period. For Three Gorges Reservoir, the CC was 0.67 (training) and 0.66 (testing), and the KGE was 0.52 and 0.49 respectively. The model exhibited robust forecasting capabilities across a range of lead times but showed distinct seasonal variations, with superior performance in summer and winter compared to transitional months (April and October). This framework provides a valuable tool for long-term runoff forecasting by effectively linking large-scale climate signals to local hydrological responses. Full article

Traditional pumped storage capacity configuration uses static, year-targeted approaches, leading under-capacity in the early planning stages—wasting renewable energy—and over-capacity in later stages, thus wasting resources. In order to solve the above problems, this article innovatively proposes a dynamic, time-sequenced construction timeline and annual capacity configuration strategy, synchronized with new energy and load development, enhancing sustainability through optimized investment allocation and efficient resource utilization. It presents a two-layer model that considers multiple scenario operational dispatch. The upper layer aims to minimize the curtailment of wind and solar energy, providing a planning scheme to the lower layer, which focuses on multi-scenario economic dispatch, taking into account the peak-valley difference indicators. The models co-iterate: lower-layer operational outcomes feed back to refine the upper-layer’s capacity plan. This process continues until the predicted curtailment calculated by the upper layer aligns closely with that observed in the lower-layer operational simulations, or until capacity changes stabilize, ultimately determining the optimal time-phased capacity configuration. Simulations on a provincial power grid during three typical scenarios in winter, transitional seasons, and summer, as well as extreme weather scenarios, confirm that timely, dynamic configuration strategy significantly enhances renewable absorption, proving the model’s effectiveness. Full article

Based on the panel data of daily meteorological stations and winter wheat yield in Henan Province from 2000 to 2023, this study comprehensively used the Mann–Kendall trend test, wavelet coherence analysis (WTC), and other methods to reveal the temporal and spatial evolution of extreme precipitation and its multi-scale stress mechanism on grain yield. The results showed the following: (1) Extreme precipitation showed the characteristics of ‘frequent fluctuation-gentle trend-strong spatial heterogeneity’, and the maximum daily precipitation in spring (RX1DAY) showed a significant uplift. The increase in rainstorm events (R95p/R99p) in the southern region during the summer is particularly prominent; at the same time, the number of consecutive drought days (CDDs > 15 d) in the middle of autumn was significantly prolonged. It was also found that 2010 is a significant mutation node. Since then, the synergistic effect of ‘increasing drought days–increasing rainstorm frequency’ has begun to appear, and the short-period coherence of super-strong precipitation (R99p) has risen to more than 0.8. (2) The spatial pattern of winter wheat in Henan is characterized by the three-level differentiation of ‘stable core area, sensitive transition zone and shrinking suburban area’, and the stability of winter wheat has improved but there are still local risks. (3) There is a multi-scale stress mechanism of extreme precipitation on winter wheat yield. The long-period (4–8 years) drought and flood events drive the system risk through a 1–2-year lag effect (short-period (0.5–2 years) medium rainstorm intensity directly impacted the production system). This study proposes a ‘sub-scale governance’ strategy, using a 1–2-year lag window to establish a rainstorm warning mechanism, and optimizing drainage facilities for high-risk areas of floods in the south to improve the climate resilience of the agricultural system against the background of climate change. Full article

Under the dual challenges of global energy crisis and climate change, the building sector, as a major carbon emitter consuming 33% of global primary energy, has seen its energy efficiency optimization become a critical pathway towards achieving carbon neutrality goals. The Window-to-Wall Ratio (WWR), serving as a core parameter in building envelope design, directly influences building energy consumption, with its optimized design playing a decisive role in balancing natural daylighting, ventilation efficiency, and thermal comfort. This study focuses on the traditional One-Seal dwellings (Yikeyin) in Kunming, China, establishing a dynamic wind field-thermal environment coupled analysis framework to investigate the impact mechanism of window dimensions (WWR and aspect ratio) on indoor thermal comfort under natural wind conditions in transitional climate zones. Utilizing the Grasshopper platform integrated with Ladybug, Honeybee, and Butterfly plugins, we developed parametric models incorporating Kunming’s Energy Plus Weather meteorological data. EnergyPlus and OpenFOAM were employed, respectively, for building heat-moisture balance calculations and Computational Fluid Dynamic (CFD) simulations, with particular emphasis on analyzing the effects of varying WWR (0.05–0.20) on temperature-humidity, air velocity, and ventilation efficiency during typical winter and summer weeks. Key findings include, (1) in summer, the baseline scenario with WWR = 0.1 achieves a dynamic thermal-humidity balance (20.89–24.27 °C, 65.35–74.22%) through a “air-permeable but non-ventilative” strategy, though wing rooms show humidity-heat accumulation risks; increasing WWR to 0.15–0.2 enhances ventilation efficiency (2–3 times higher air changes) but causes a 4.5% humidity surge; (2) winter conditions with WWR ≥ 0.15 reduce wing room temperatures to 17.32 °C, approaching cold thresholds, while WWR = 0.05 mitigates heat loss but exacerbates humidity accumulation; (3) a symmetrical layout structurally constrains central ventilation, maintaining main halls air changes below one Air Change per Hour (ACH). The study proposes an optimized WWR range of 0.1–0.15 combined with asymmetric window opening strategies, providing quantitative guidance for validating the scientific value of vernacular architectural wisdom in low-energy design. Full article

Electric buses (EBs) are increasingly adopted for their environmental and operational benefits, yet their real-world efficiency is influenced by climate, route characteristics, and auxiliary energy demands. While most existing research identifies winter as the most energy-intensive season due to cabin heating and reduced battery performance, this study presents a contrasting perspective based on a three-year longitudinal analysis of the LYMMO fleet in Orlando, Florida—a subtropical U.S. region. The findings reveal that summer is the most energy-intensive season, primarily due to sustained HVAC usage driven by high ambient temperatures—a seasonal pattern rarely reported in the current literature and a key regional contribution. Additionally, idling time exceeds driving time across all seasons, with HVAC usage during idling emerging as the dominant contributor to total energy consumption. To mitigate these inefficiencies, a proxy-based HVAC energy estimation method and an optimization model were developed, incorporating ambient temperature and peak passenger load. This approach achieved up to 24% energy savings without compromising thermal comfort. Results validated through non-parametric statistical testing support operational strategies such as idling reduction, HVAC control, and seasonally adaptive scheduling, offering practical pathways to improve EB efficiency in warm-weather transit systems. Full article

The absence of standardized time zones has profound implications, influencing social, economic, and energy dynamics. It also disrupts personal aspects, such as sleep patterns and family routines. One specific dimension of this issue is the transition to daylight saving time (DST), which entails shifting between standard time (winter) and daylight saving time (summer). This practice has sparked global debates due to its varying impacts across regions and sectors. Although DST primarily aims to optimize energy consumption by leveraging natural daylight, much attention has focused on its broader societal effects. However, the energy performance of commercial buildings under DST remains an underexplored yet equally significant area. This article presents a literature review to critically evaluate the effects of the winter-to-summer time shift on commercial buildings, concentrating on three key factors: energy consumption, where seasonal variations in lighting, heating, and cooling demands may alter anticipated energy savings; occupant thermal comfort, as time changes can disrupt the circadian rhythms of building occupants, impacting productivity and well-being; and operational considerations, as building systems like HVAC and automated controls must adjust to shifting daylight schedules. Accordingly, this review seeks to offer a comprehensive understanding of how the winter–summer time transition affects commercial buildings by analyzing energy consumption patterns, occupant comfort levels, and operational challenges. In doing so, it contributes to optimizing building management practices under varying daylight conditions to enhance energy efficiency and occupant satisfaction. Full article

Faced with the current challenges of the energy transition and the quest for sustainable materials, biobased materials are attracting growing interest for their environmental and thermal properties. Cob is well known for regulating humidity and improving thermal comfort in buildings. A building’s thermal inertia can be increased by integrating phase-change materials (PCMs), enabling energy storage. This study explores the integration of microencapsulated PCMs into biobased materials considering realistic environmental conditions during experimental tests. The results show a homogeneous thermal distribution with low temperature variation at different locations. The relative humidity results confirm a one-dimensional thermal and hygroscopic distribution. The material with PCMs exhibits better thermal regulation. It retains more heat on the outside and reduces indoor temperature variations, improving thermal insulation. Measurements show that PCM integration contributes to reducing wall thermal conductivity and increases its thermal capacity, reaching 2.6 times during phase transition. The simulation is conducted with real 96 h Normandy climate data (January and August) for conventional and biobased walls incorporating PCMs. The results show that winter heat losses are highest for conventional walls (−44.08 kWh/m²), low for cob walls (−24.17 kWh/m²), and lowest for cob walls with PCMs (−13.17 kWh/m²). In summer, all walls exhibit the lowest heat gain, while adding PCMs stabilizes heat flux, reducing peak summer heat flux from 150 W/m² to 50 W/m². The results show that the addition of PCMs significantly improves thermal and hygroscopic performance. Full article

This study presents the longest time series of aerosol optical properties and Precipitable Water Vapor (PW) from two AERONET sites in the Indo-Gangetic Plains (IGP). Analyzing 22 years of data (2001–2022) from Kanpur and 16 years (2007–2023) from Gandhi College, the study focuses on Aerosol Optical Depth (AOD), Ångström Exponent (α), Single Scattering Albedo (SSA), and Precipitable Water Vapor (PW). Significant variability in aerosol properties is observed across monthly, seasonal, and annual scales. The highest mean AOD₅₀₀ values, coupled with higher α_440–870 during post-monsoon and winter, indicate the dominance of fine-mode aerosols. A decrease in SSA with wavelength during these seasons further highlights the absorbing nature of these fine-mode aerosols, driven by fossil fuels and biomass burning. In contrast, summer and pre-monsoon have relatively lower mean AOD₅₀₀, lowest α_440–870, and increased SSA with wavelength, suggesting the dominance of coarse-mode scattering dust aerosols. PW exhibits a seasonal cycle, reaching its peak during the monsoon due to moisture transport from the Arabian Sea and Bay of Bengal, then decreasing post-monsoon as drier conditions prevail. Long-term annual trends reveal increasing aerosol concentrations, with AOD₅₀₀ rising by 18% at Kanpur and 29% at Gandhi College, suggesting faster aerosol loading at the latter. Sub-period analysis indicates a slowdown in AOD₅₀₀ increase during 2012–2023 at Kanpur, indicating potential stabilization post-industrialization, while Gandhi College’s more pronounced AOD₅₀₀ and α_440–870 increase underscores the growing impact of fine aerosols in rural IGP areas. Kanpur shows a sustained SSA increase, though at a slower rate in recent years, indicating dominant scattering aerosols. In contrast, Gandhi College has transitioned from moderate SSA increases to declines at longer wavelengths, suggesting enhanced fine-mode absorbing aerosols. At Gandhi College, the decline in PW reduces atmospheric moisture, limiting wet scavenging and likely contributing to the rise in fine-mode aerosols, especially during the monsoon and post-monsoon seasons. Our findings highlight the evolving aerosol sources in the IGP, with Kanpur stabilizing and rural areas like Gandhi College seeing continued increases in pollution. Full article