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Numerical weather prediction (NWP), when accessible, is a crucial input to short-term solar power forecasting. WRF-Solar, the first NWP model specifically designed for solar energy applications, has shown promising predictive capability. Nevertheless, few attempts have been made to investigate its performance under high aerosol loading, which attenuates incoming radiation significantly. The North China Plain is a polluted region due to industrialization, which constitutes a proper testbed for such investigation. In this paper, aerosol direct radiative effect (DRE) on three surface shortwave radiation components (i.e., global, beam, and diffuse) during five heavy pollution episodes is studied within the WRF-Solar framework. Results show that WRF-Solar overestimates instantaneous beam radiation up to 795.3 W m−2 when the aerosol DRE is not considered. Although such overestimation can be partially offset by an underestimation of the diffuse radiation of about 194.5 W m−2, the overestimation of the global radiation still reaches 160.2 W m−2. This undesirable bias can be reduced when WRF-Solar is powered by Copernicus Atmosphere Monitoring Service (CAMS) aerosol forecasts, which then translates to accuracy improvements in photovoltaic (PV) power forecasts. This work also compares the forecast performance of the CAMS-powered WRF-Solar with that of the European Centre for Medium-Range Weather Forecasts model. Under high aerosol loading conditions, the irradiance forecast accuracy generated by WRF-Solar increased by 53.2% and the PV power forecast accuracy increased by 6.8%. Significance Statement: Numerical weather prediction (NWP) is the "go-to" approach for achieving high-performance day-ahead solar power forecasting. Integrating time-varying aerosol forecasts into NWP models effectively captures aerosol direct radiation effects, thereby enhancing the accuracy of solar irradiance forecasts in heavily polluted regions. This work not only quantifies the aerosol effects on global, beam, and diffuse irradiance but also reveals the physical mechanisms of irradiance-to-power conversion by constructing a model chain. Using the North China Plain as a testbed, the performance of WRF-Solar on solar power forecasting on five severe pollution days is analyzed. This version of WRF-Solar can outperform the European Centre for Medium-Range Weather Forecasts model, confirming the need for generating high spatial–temporal NWP. [ABSTRACT FROM AUTHOR]

Satellite precipitation products (SPPs) have emerged as an alternative to estimate rainfall erosivity. However, prior studies showed that SPPs tend to underestimate rainfall erosivity but without reported bias-correction methods. This study evaluated the efficacy of two SPPs, namely, GPM_3IMERGHH (30-min and 0.1°) and GPM_3IMERGDF (daily and 0.1°), in estimating two erosivity indices in mainland China: the average annual rainfall erosivity (R-factor) and the 10-year event rainfall erosivity (10-yr storm EI), by comparing with that derived from gauge-observed hourly precipitation (Gauge-H). Results indicate that GPM_3IMERGDF yields higher accuracy than GPM_3IMERGHH, though both products generally underestimate these indices. The Percent Bias (PBIAS) is −55.48% for the R-factor and −56.38% for the 10-yr storm EI using GPM_3IMERGHH, which reduces to −10.86% and −32.99% with GPM_3IMERGDF. A bias-correction method was developed based on the systematic difference between SSPs and Gauge-H. A five-fold cross validation shows that with bias-correction, the accuracy of the R-factor and 10-yr storm EI for both SPPs improve considerably, and the difference between two SSPs is reduced. The PBIAS using GPM_3IMERGHH decreases to −0.06% and 0.01%, and that using GPM_3IMERGDF decreases to −0.33% and 0.14%, respectively, for the R-factor and 10-yr storm EI. The rainfall erosivity estimated with SPPs with bias-correction shows comparable accuracy to that obtained through Kriging interpolation using Gauge-H and is better than that interpolated from gauge-observed daily precipitation. Given their high temporal and spatial resolution, and timely updates, GPM_3IMERGHH and GPM_3IMERGDF are viable data products for rainfall erosivity estimation with bias correction. [ABSTRACT FROM AUTHOR]

To understand soil biodiversity we need to know how soil communities are assembled. However, the relationship between soil community assembly and environmental factors, and the linkages between soil microbiota taxonomic groups and their body sizes, remain unexplored in tropical seasonal rainforests. Systematic and stratified random sampling was used to collect 243 soil and organism samples across a 20‐ha plot in a tropical seasonal rainforest in southwestern China. High‐throughput sequencing, variation analysis and principal coordinates of neighbourhood matrices were performed. Soil community composition, spatial distribution and assembly processes based on propagule size (including archaea, bacteria, fungi and nematodes) were investigated. The results showed that: (i) the community assembly of small soil microorganisms (bacteria, fungi) was mostly influenced by stochastic processes while that of larger soil organisms (nematodes) was more deterministic; (ii) the independent effects of habitat (including soil and topographic variables) and its interaction with plant attributes for community structure significantly decreased with increasing body size; and (iii) plant leaf phosphorus directly influenced the spatial distribution of soil‐available phosphorus, which indicates their indirect impact on the assembly of the soil communities. Our data suggest that the assembly of multitrophic soil communities can be explained to some extent by changes in above‐ground plant attributes. This highlights the importance of above‐ and below‐ground linkages in influencing multitrophic soil microbiota community assembly. [ABSTRACT FROM AUTHOR]

China's recently announced directive on tackling climate change, namely, to reach carbon peak by 2030 and to achieve carbon neutrality by 2060, has led to an unprecedented nationwide response among the academia and industry. Under such a directive, a rapid increase in the grid penetration rate of solar in the near future can be fully anticipated. Although solar radiation is an atmospheric process, its utilization, as to produce electricity, has hitherto been handled by engineers. In that, it is thought important to bridge the two fields, atmospheric sciences and solar engineering, for the common good of carbon neutrality. In this überreview, all major aspects pertaining to solar resource assessment and forecasting are discussed in brief. Given the size of the topic at hand, instead of presenting technical details, which would be overly lengthy and repetitive, the overarching goal of this review is to comprehensively compile a catalog of some recent, and some not so recent, review papers, so that the interested readers can explore the details on their own. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) are consumed by photochemical reactions during transport, leading to inaccuracies in estimating the local ozone (O 3) formation mechanism and its subsequent strategy for O 3 attainment. To comprehensively quantify the deviations in O 3 formation mechanism by consumed VOCs (C–VOCs), a 5-month field campaign was conducted in a typical industrial city in Northern China over incorporating a 0-D box model (implemented with MCMv3.3.1). The averaged C–VOCs concentration was 6.8 ppbv during entire period, and Alkenes accounted for 62% dominantly. Without considering C–VOCs, the relative incremental reactivity (RIR) of anthropogenic VOCs (AVOC, overestimated by 68%–75%) and NO x (underestimated by 137%–527%) demonstrated deviations at multiple scenarios, and the RIR deviations for precursors in High-O 3 -periods (HOP) were lower than Low-O 3 -periods (LOP). The RIR deviations from individual species involved C–VOCs calculation did not impact the identification for the high-ranking-RIR AVOC species but non-negligible. Monthly comparisons showed that higher C–VOCs concentrations would lead to higher RIR deviations. The daily maximum of net O x production rate (P(O x)) and the regional transport O x (Trans(O x)) without C–VOCs were underestimated by 56%–194% and 81%–243%, respectively. After considering C–VOCs, the contribution of HO 2 +NO for O x gross production (G(O x)) decreased by 7% (LOP) and 7% (HOP), but OH + NO 2 for O x destruction (D(O x)) decreased by 16% (LOP) and 23% (HOP), and alkenes + O 3 increased for D(O x) by 12% (LOP) and 22% (HOP). This implies that VOCs-NO x -O 3 sensitivity was deviated between with/without C–VOCs, and severe O 3 pollution rendered deviations in O 3 formation, especially via NO x -driving chemistry. Based on RIR(NO x)/RIR(AVOC) with/without C–VOCs, the sensitivity regime shifted from VOCs-limited (−0.93) to transition (1.38) at LOP, and from VOCs-limited (0.19) to NO x -limited (3.79) at HOP. Our results reflected that the NO x limitation degree was underestimated without constraint C–VOCs, especially HOP, and provided implication to more precise O 3 pollution control strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

In the realm of urban development, the issue of Urban Sprawl (USL) is increasingly being recognized as a significant externality, profoundly influencing Urban Safety Resilience (USR). This study addresses the dearth of research on the implications of USL within the context of New Infrastructure (NI) development and its impact on USR. Using panel data from 259 prefecture-level cities in China from 2009 to 2020, an USR index was constructed, encompassing social, infrastructure, economic, and environmental components. Applying the System Generalized Method of Moments (GMM) and panel threshold models, the study thoroughly examines the influences of USL and NI on USR. The findings reveal a significant negative correlation between USL and USR, while NI contributes positively to USR with a time-lagged effect. These results are robust across stability tests. Furthermore, the study uncovers a double threshold effect of USL on USR, with NI acting as the threshold variable. Heterogeneity analysis indicates that the central and western regions of China experience a stronger negative impact of USL on USR. This research provides valuable theoretical insights into the relationship between USL and USR, offering guidelines for promoting safer urban development. • Confirms USL's negative correlation with USR in Chinese cities • Identifies NI as a positive counter to USL's adverse effects on USR • Discovers a double threshold effect of USL on USR, with NI as a moderator • Highlights greater USL impacts on USR in central/western China than eastern [ABSTRACT FROM AUTHOR]

The stochastic weather generator CLIGEN can simulate long-term weather sequences as input to WEPP for erosion predictions. Its use, however, has been somewhat restricted by limited observations at high spatial–temporal resolutions. Long-term daily temperature, daily, and hourly precipitation data from 2405 stations and daily solar radiation from 130 stations distributed across mainland China were collected to develop the most critical set of site-specific parameter values for CLIGEN. Ordinary kriging (OK) and universal kriging (UK) with auxiliary covariables, i.e., longitude, latitude, elevation, and the mean annual rainfall, were used to interpolate parameter values into a 10km×10km grid, and the interpolation accuracy was evaluated based on the leave-one-out cross-validation. Results showed that UK generally outperformed OK. The root mean square error between UK-interpolated and observed temperature-related parameters was ≤0.88 ∘ C (1.58 ∘ F). The Nash–Sutcliffe efficiency coefficient for precipitation- and solar-radiation-related parameters was ≥0.87 , except for the skewness coefficient of daily precipitation, which was 0.78. In addition, CLIGEN-simulated daily weather sequences using UK-interpolated and observed parameters showed consistent statistics and frequency distributions. The mean absolute discrepancy between the two sequences for temperature was <0.51 ∘ C, and the mean absolute relative discrepancy for solar radiation, precipitation amount, duration, and maximum 30 min intensity was <5 % in terms of the mean and standard deviation. These CLIGEN parameter values at 10 km resolution would meet the minimum data requirements for WEPP application throughout mainland China. The dataset is available at http://clicia.bnu.edu.cn/data/cligen.html (last access: 20 May 2021) and 10.12275/bnu.clicia.CLIGEN.CN.gridinput.001 (Wang et al., 2020). [ABSTRACT FROM AUTHOR]

• Gridded daily data underestimates rainfall erosivity due to scaling differences. • Bias-correction factors: medians of 0.80 (R-factor) and 0.66 (10-year storm EI). • Future china is expected to experience rising rainfall erosivity by 14% ∼ 47%. • Increasing erosivity mainly due to the rising probability of extreme precipitation. This study focuses on improving the accuracy of projections for future rainfall erosivity by selecting five CMIP6-based and bias-adjusted Global Climate Models (GCMs) in China. These models provide more precise estimations of rainfall erosivity under two future periods (2041–2065 and 2076–2100) and two emission scenarios (SSP1-RCP2.6 and SSP5-RCP8.5). The evaluation of the models' performance involved comparing their estimations of two erosivity indices, namely the annual average rainfall erosivity (R-factor) and the extreme storm EI 30 with a 10-year return period (10-year storm EI), with reference erosivity maps of China interpolated from hourly observations at 2381 stations. The results indicate that three models, GFDL-ESM4, IPSL-CM6A-LR, and UKESM1-0-LL, outperform the others in terms of higher Nash-Sutcliffe efficiencies and better spatial correlation, especially in regions prone to water erosion. However, it was observed that the R-factor and 10-year storm EI estimated using Multi-Model Ensembles (MMEs) were significantly underestimated for the historical period due to scaling differences. To address this issue, bias-correction factors were determined for each grid cell to improve future projections. The medians of these correction factors were found to be 0.80 for the R-factor and 0.66 for the 10-year storm EI. Overall, the study projects an increase in rainfall erosivity for most regions in China. Under the SSP1-RCP2.6 and SSP5-RCP8.5 scenarios, the R-factor is expected to rise by 18.9% and 19.8% for the near-term and 26.0% and 46.5% for the long-term, respectively. Similarly, the 10-year storm EI is projected to increase by 14.2% and 17.4% for the near-term and 14.9% and 45.0% for the long-term, respectively. These projected increases are primarily attributed to the elevated probability of extreme precipitation events, highlighting the need for enhanced soil and water conservation measures in China to mitigate the challenges posed by global warming. [ABSTRACT FROM AUTHOR]

The effects of rainfall intensity on erosion processes for intra-storm variations are extensively investigated based on rainfall simulation experiments. However, there is a distinction between natural and simulated rainfall. Soil loss data from a total of 84 erosive storms from 2006 through 2013 with hyetograph rainfall data were collected from five plots located in Beijing, each with soils from different Chinese zones, to investigate the effects of erosive storm patterns on soil loss under natural rainfall conditions and to detect if this influence was consistent among the five soil types. The storms were divided into four patterns according to the period of the most concentrated rainfall, including advanced, intermediate, delayed, and uniform patterns. The results indicate that 1) the prevalent storm pattern in Beijing is advanced, which accounts for 43% of storms and contributes the most to total soil loss (approximately 55 to 68%). 2) Storm pattern significantly affected soil loss, with the delayed pattern yielding more soil loss than the other three patterns after taking into account EI 30 . 3) The effect of storm patterns on soil loss was consistent between the five soil types. 4) Coefficients for quantifying the effects of storm pattern on soil loss were not significantly different among these five soils, but exhibited significant differences among the storm patterns, e.g., the coefficient for the delayed pattern was 2.07, for the uniform pattern was 0.42, and for the advanced and the intermediate patterns were approximately 1. Rainfall erosivity generated by an erosive storm with a known pattern could be estimated by multiplying the corresponding adjustment coefficient, which would further improve the accuracy of soil erosion prediction, especially for storm level prediction. [ABSTRACT FROM AUTHOR]

• High platelet reactivity and gastric mucosal injury after aspirin (ASA) treatment compromise clinical efficacy. • Adding Panax notoginseng saponin (PNS) to ASA potentiates platelet inhibition without increased bleeding. • PNS alleviates ASA-related dyspepsia symptoms and mitigates ASA-induced gastric mucosal injury. • These effects are associated with intraplatelet and gastric arachidonic acid metabolism modulation by lipidomic analysis. High platelet reactivity and gastric mucosal injury after aspirin (ASA) treatment are associated with poor compliance and an increased risk of cardiovascular events. Panax notoginseng saponins (PNS) have been widely used for the treatment of coronary heart disease (CHD) in addition to antiplatelet drugs in China; however, the joint effect and possible mechanism of PNS in addition to ASA on platelet activation and gastric injury remain unclear. This study was designed to investigate the combinational effects of PNS with ASA, and to explore the underlying mechanism via arachidonic acid (AA) metabolism pathway using lipidomic analysis. In a randomized, assessor-blinded trial, 42 patients with stable coronary heart disease (SCHD) and chronic gastritis were randomly assigned to receive ASA (n = 21) or PNS + ASA (n = 21) for 2 months. Compared with ASA alone, PNS + ASA further inhibited CD62p expression, GPIIb-IIIa activation and platelet aggregation and led to increased platelet inhibition rate. PNS + ASA suppressed the activity of platelet cyclooxygenase (COX)-1, and decreased the production of TXB 2 , PGD 2 , PGE 2 , 11-HETE, the downstream oxylipids of AA/COX-1 pathway in platelets, compared with ASA alone. The severity of dyspepsia assessment (SODA) results showed that patients in PNS + ASA group exhibited relieved dyspeptic symptoms as compared with those in ASA group, which might be associated with enhanced secretion of gastrin and motilin. In vivo study of myocardial infarction rats demonstrated that PNS attenuated ASA-induced gastric mucosal injury, which was related to markedly boosted gastric level of 6,15-diketo-13,14-dihydro-prostaglandin (PG)F1α, 13,14-dihydro-15-keto-PGE 2 and PGE 2 from AA/PG pathway in response to PNS + ASA compared with ASA alone. In summary, our study demonstrated that the combination of PNS and ASA potentiated the antiplatelet effect of ASA via AA/COX-1/TXB 2 pathway in platelets, and mitigated ASA-related gastric injury via AA/PG pathway in gastric mucosa. [ABSTRACT FROM AUTHOR]

Fengyun-4A (FY-4A), which is the latest-generation Chinese geostationary meteorological satellite, measures solar reflection and thermal emission with high temporal, spatial, and spectral resolutions. It is expected to be highly beneficial for solar resource assessment and forecasting in China. This study is the first to estimate, using FY-4A and a random forest model, the global horizontal irradiance (GHI) at a 4-km–15-min spatio-temporal resolution over China, as a means to arrive at a solar photovoltaic (PV) resource map. In terms of GHI estimates, the root mean square error and mean bias error between hourly measured and retrieved values are 147.02 (35.2%), −5.64 W/m2 (−1.4%), respectively, whereas the values of daily estimates are 29.20 (18.0%), −2.97 W/m2 (−1.3%). The retrieval accuracy is found much better for instances with solar zenith angles smaller than 60°. Relatively larger errors are found at locations in the Sichuan Basin and northeastern China, which can be attributed to bright surfaces and/or strong cloud transients. With the retrieved irradiance, PV resource is derived through a physical model chain. The annual mean PV resource map suggests that, over most of the west areas, the annual mean effective irradiance exceeds 1700 kWh/m2, with the highest value found in Tibet (around 2000 kWh/m2 per annum). Eastern China has an annual effective irradiance of only 1300–1500 kWh/m2. The region with poorest solar resource is the Sichuan Basin (less than 1100 kWh/m2 per annum). • Solar PV resource map based on FY-4A over China is established for the first time. • An accurate model chain is used to derive PV potential from hourly irradiance estimates. • High-resolution FY-4A-based GHI map sheds new light on PV resourcing over China. [ABSTRACT FROM AUTHOR]

Background: Paying attention to and improving the mental health of the informal caregivers of disabled elders has become a global public health priority. This study focused on low-income female Uyghur and Kazakh informal caregivers of disabled elders residing in China’s far west. It investigated the prevalence of and the major related factors of depressive emotion. Methods: A cross-sectional study was performed from September 2013 to January 2014 in Shawan Prefectures, Tuokexun Prefectures, Bole Prefecture and Urumchi city. Shawan Prefecture has the highest proportion of Kazakhs, whereas Tuokexun Prefectures, Bole Prefecture and Urumchi city have the highest proportion of Uyghurs in Muslim ethnic Uygur and Kazakh communities. Xinjiang Uyghur Autonomous Region is located in remote western China; this area is approximately 3,105 km (1,929 miles) away from Beijing. A total of 444 female Uyghur and Kazakh informal caregivers of disabled elders participated in this study. The self-rating depression scale, the Zarit burden interview, and the SF-36 questionnaire were used to evaluate the state of caregiver depression, caregiver burden, and quality of life (QOL), respectively. Statistical analyses were performed using multivariate logistic regression analyses, correlation with Spearman’s rho and independent-sample t-tests; a P-value of <0.05 was considered statistically significant. Results: Up to 38.5% (n = 217) of informal caregivers reported having depression, whereas 61.5% (n = 273) of them reported a lack of depression. Age of disabled elders more than 60 years old, total hours spent on caring daily≥8h, duration of caring≥5 years, negative self-evaluation of health condition, having caregiver burden, elders’ medium degree of disability and elders’ heavy degree of disability had a higher risk of caregiver depression. By contrast, daughter/daughter-in-law of disabled elders; unemployed carers, family’s per capita income >US$235.48(1500 yuan), high social support, and high QOL of disabled elders were each associated with a lower risk of depressive emotion. Moreover, informal caregivers with depression obtained high care burden scores; at the same time, disabled elders who were looked after by caregivers with depression obtained low QOL scores. Conclusions: Our findings suggest that the demographics characteristics of informal caregivers, and caregiver burden, and the disabled elders’ degree of disability and QOL had the most significant correlation with depressive emotion among women informal caregivers. The results had a enlighten that these variables should be considered while planning interventions to improve depression of informal caregivers. [ABSTRACT FROM AUTHOR]

Highlights: [•] Higher level of diversity within the captive populations than the reintroduced population. [•] Genetic differentiation was detected among populations. [•] Inbreeding coefficients were generally higher in the reintroduced population. [•] Temporal estimates of both pedigree and microsatellite data showed a high, but decreasing level inbreeding. [•] More than 100 individuals to retain approximately 90% of its current, already depauperate, genetic diversity. [Copyright &y& Elsevier]