Rising soil salinity poses significant challenges to Mediterranean viticulture. While some rootstocks effectively reduce salt accumulation in grafted scions, the mechanisms and performance of novel rootstocks remain largely unexplored. This study compared two novel M-series rootstocks (M2, M4) with established commercial rootstocks (1103 Paulsen, R110) to evaluate their physiological responses and salt tolerance under irrigation with varying salinity levels (0, 25, 50, and 75 mM NaCl) over 5 months. Growth parameters, photosynthetic efficiency, chlorophyll content (SPAD), ion homeostasis, and visual symptoms were monitored. Results revealed genotype-specific strategies: 1103 Paulsen exhibited robust photosynthetic efficiency and ion exclusion, maintaining growth and chlorophyll stability; M2 demonstrated superior biomass retention and moderate ion compartmentalization but showed reduced photosynthetic performance at higher salinity levels; R110 displayed effective ion management at moderate salinity but experienced significant growth reduction under severe stress; and M4 was the most sensitive, with severe reductions in growth and ion homeostasis. Organ-specific responses highlighted roots acting as primary ion reservoirs, particularly for sodium and calcium; leaves exhibited high potassium and chloride concentrations, critical for photosynthesis but prone to ionic imbalance under stress; and stems and wood played a buffering role, compartmentalizing excess sodium and minimizing damage to photosynthetic tissues. The reported findings provide valuable insights for rootstock selection and breeding programs, particularly for regions facing increasing soil and water salinization challenges.

The negative effects of PM2.5 concentration in urban development are becoming more and more prominent. Bernaola-Galvan Segmentation Algorithm (BGSA) and wavelet analysis are powerful tools for processing non-linear and non-stationary signals. First, we use BGSA that reveals there are 41 mutation points in the PM2.5 concentration in Guiyang. Then, we reveal the multi-scale evolution of PM2.5 concentration in Guiyang by wavelet analysis. In the first part, we performed one-dimensional continuous wavelet transform (CWT) on the eight monitoring points in the study area, and the results showed that they have obviously similar multi-scale evolution characteristics, with a high-energy and significant oscillation period of 190-512 days. Next, the wavelet transform coherence (WTC) reveals the mutual relationship between the PM2.5 concentration and the atmospheric pollutants and meteorological factors. PM2.5 concentration variation is closely linked to that of PM10 concentration. But, it is not to be ignored that the increase in the SO2 and NO2 concentrations will cause the PM2.5 concentration to rise on different scales. Lastly, the variation of the PM2.5 concentration can be better explained by the combination of multiple factors (2-4) using the multiple-wavelet coherence (MWC). Under the combination of the two factors, the average temperature (Avgtem) and relative humidity (ReH) have the highest AWC and PASC. In the case of the combination of four factors, CO-Avgtem-Wind-ReH plays the largest role in determining PM2.5 concentration.

Brown carbon (BrC) has been recognized as an important light-absorbing carbonaceous aerosol, yet understanding of its influence on regional climate and air quality has been lacking, mainly due to the ignorance of regional coupled meteorology-chemistry models. Besides, assumptions about its emissions in previous explorations might cause large uncertainties in estimates. Here, we implemented a BrC module into the WRF-Chem model that considers source-dependent absorption and avoids uncertainties caused by assumptions about emission intensities. To our best knowledge, we made the first effort to consider BrC in a regional coupled model. We then applied the developed model to explore the impacts of BrC absorption on radiative forcing, regional climate, and air quality in East Asia. We found notable increases in aerosol absorption optical depth (AAOD) in areas with high OC concentrations. The most intense forcing of BrC absorption occurs in autumn over Southeast Asia, and values could reach around 4 W m(-2). The intensified atmospheric absorption modified surface energy balance, resulting in subsequent declines in surface temperature, heat flux, boundary layer height, and turbulence exchanging rates. These changes in meteorological variables additionally modified near-surface dispersion and photochemical conditions, leading to changes of PM2.5 and O-3 concentrations. These findings indicate that BrC could exert important influence in specific regions and time periods. A more in-depth understanding could be achieved later with the developed model.

China experiences severe particulate matter (PM) pollution. Although a monitoring network for PM2.5 (diameter < 2.5 mu m) has been set up in more than 100 major Chinese cities, insufficient spatial coverage of observations limits the study of the temporal and spatial characteristics, influencing factors, and component of PM2.5. In this study, we conducted a one year air quality simulation using a regional climate-chemistry model and evaluated the simulation's performance based on in situ observations concerning meteorological elements and PM2.5 concentrations. The simulated results showed that, higher PM2.5 concentrations appeared in northern China and the Sichuan Basin, and the maximal value occurred in winter. Furthermore, Vertical PM2.5 concentrations presented a gradual decreasing trend from the surface, whereas in southern coastal cities the profiles were unsteady with a secondary peak in the lower layer. Meteorological conditions were conducive to both pollutant diffusion and removal in summer, whereas stagnant conditions appeared in winter, characterized by high sea level pressure (SLP), the lowest planetary boundary layer height (PBLH), and 2-m temperature (T2). In provincial capital cities, PM2.5 was positively correlated with residential emissions but negatively correlated with precipitation, 10-m wind speed, T2, PBLH, and industrial emissions. Finally, we utilized the simulation results to investigate the component variations of PM2.5. Results indicated that primary PM2.5 components had significantly higher concentrations in northern China where residential heating is the major source of PM2.5 emissions, whereas they had lower concentrations in southern China. Secondary components played a crucial role in PM2.5 mass in eastern China. This study provided a clear perspective of seasonal variations, horizontal and vertical distributions of PM2.5 and its components and influence factors, which could be used in subsequent studies to investigate the formation mechanism and emission sources of PM2.5.

In this study, air pollutants were analyzed at a low-industry city on the Silk Road Economic Belt of Northwestern China from 2015 to 2018. The results show that SO2 and CO had a decreasing trend and NO2, O-3, PM2.5, and PM10 had an increasing trend during the study period. The primary characteristic pollutants were PM2.5 and PM10, which were higher than China's Grade II standard. SO2, NO2, CO, PM2.5, and PM10 concentrations showed similar seasonal variation patterns: the highest pollutant concentration was in winter and the lowest in summer. Those pollutants showed a similar diurnal pattern with two peaks, one at 7:00 to 9:00 and another at 21:00 to 22:00. However, O-3 concentration was highest in summer and lowest in winter, with a unimodal diurnal variation pattern. The annual average pollution concentrations in Tianshui in 2017 were substantially lower than the concentrations reported by most cities in China. By examining the meteorological conditions at a daily scale, we found that Tianshui was highly influenced by local emissions and a southwest wind. Potential source contributions and concentration weighted trajectory analyses indicated that the pollution from Gansu, Sichuan, Qinghai, and Shaanxi Province could affect the pollution concentration in Tianshui. The results provide directions for the government to take in formulating regional air pollution prevention and control measures and to improve air quality.

Soil erosion caused by rain and runoff is a global issue that keeps getting worse over time. Damage caused by this phenomenon includes accelerated silting of dams. Considering that the storage capacity of major hydraulic structures gradually degrades owing to cumulative sedimentation, Tunisia faces severe environmental threats due to the annual decrease in reservoir capacity. Plant cover and land use are the most significant factors influencing the severity of soil erosion. In this vein, this study investigated the effect of soil cover on erosion at two agricultural sites in the El Kbir watershed, north Tunisia, using the cesium-137 (Cs-137) radioisotope tracer method. This radioactive element has been successfully used for investigating rates and patterns of soil erosion. The cesium-137 inventory obtained for the reference site is about 1341 Bq m-2. For study plots cultivated with olive trees and cereal crops, Cs-137 inventories are about 1036.37 Bq m-2 and 426.82 Bq m-2, respectively. The results show that the net erosion rate estimated by the mass balance model 2 (MBM2) was significantly higher in the cereal cultivated plot with 28.95 t ha-1 year-1 than in the olive cultivated plot with 7.16 t ha-1 year-1. The difference in net erosion rates between the two fields reveals the crucial role of the soil cover, as olive trees showed better resistance to erosive effects because of their system of roots. In contrast, culture of cereal crops, which occupy around 50% of the total area in the region, does not effectively protect and maintain the soil against erosion, which in turn induces intensive erosion of soil, resulting in sedimentation in dams. Soil erosion can therefore be reduced by adapting land use and increasing adequate vegetation cover.

In the early 21st century, Southwest China (SWC) frequently experienced extreme droughts and severe haze pollution events. Although the meteorological causes of these extreme droughts have been widely investigated, previous studies have yet to understand the causes of haze pollution events over SWC. Moreover, the associations between winter atmospheric teleconnections during drought and haze pollution event across SWC has received negligible attention and therefore warrants investigation. This study examines the associations between the atmospheric teleconnections with respect to winter droughts and winter haze pollution over SWC. Our main conclusions are as follows. (1) Winter precipitation and winter haze days (WHD) over SWC had three major fluctuations from 1959 to 2016. (2) The atmospheric circulation pattern over the Eurasian (EU) continent associated with WHD over SWC resembled that of winter droughts over SWC, where both can be characterized by an EU teleconnection pattern. The Arctic Oscillation (AO) mainly induced the atmospheric circulation pattern over the EU continent that is associated with WHD over SWC. (3) The sea surface temperature (SST) and low circulation anomalies in the Pacific and north Atlantic associated with WHD were similar to those associated with winter droughts over SWC. La Nina events and negative phases of the North Atlantic Oscillation (NAO) may induce winter drought and increase the WHD over SWC. (4) Compared with winter drought over SWC, the variation in the WHD was more complex and the factors affecting WHD were more diverse, and winter drought and its related atmospheric circulations were important factors that induced haze pollution over SWC. Overall, this study not only fills a gap in the literature with respect to the associations between the atmospheric teleconnections of winter drought and winter haze pollution over SWC, but also provides an important scientific basis for the development of potential predictions of local monthly haze pollution, which improves the forecast accuracy of local short-term haze pollution and enriches the theoretical understanding of the meteorological causes of local haze pollution. (C) 2020 Elsevier B.V. All rights reserved.

PM2.5 impacts the atmospheric temperature structure through scattering or absorbing solar radiation, whose concentration and composition can affect the impact. This study calculated the effect of PM2.5 on the temperature structures in the urban centre and the suburbs of Nanjing, as well as their differences. The results show that the optical parameters, atmospheric heating rate, radiative forcing, and temperature are all impacted by the concentration and composition of PM2.5. The uneven distribution of PM2.5 influences the differences in those factors between the urban centre and suburbs. In spring, summer, autumn, and winter, surface temperatures in the urban centre were approximately 283 K, 285 K, 305 K, and 277 K, while those in the suburbs were approximately 282 K, 283 K, 304 K, and 274 K. The urban heat island intensity has been reduced by 0.1-0.4 K due to the presence of PM2.5 in Nanjing. Due to the black carbon component's warming effect on the top of the boundary layer, the impact of PM2.5 on the urban heat island intensity profile drops quickly at the 0.75-1.25 km. PM2.5 may mask the warm city problem and have a more complex impact on the urban climate.

Sichuan Basin is encircled by high mountains and plateaus with the heights ranging from 1 km to 3 km, and is one of the most polluted regions in China. However, the dominant chemical species and light absorption properties of aerosol particles is still not clear in rural areas. Chemical composition in PM1 (airborne particulate matter with an aerodynamic diameter less than 1 mu m) and light-absorbing properties were determined in Chengdu (urban) and Sanbacun (rural) in western Sichuan Basin (WSB), Southwest China. Carbonaceous aerosols and secondary inorganic ions (NH4+, NO3- and SO42-) dominate PM1 pollution, contributing more than 85% to PM1 mass at WSB. The mean concentrations of organic and elemental carbon (OC, EC), K+ and Cl- are 19.69 mu g m(-3), 8.00 mu g m(-3), 1.32 mu g m(-3),1.16 mu g m(-3) at the rural site, which are 26.2%, 65.3%, 34.7% and 48.7% higher than those at the urban site, respectively. BrC (brown carbon) light absorption coefficient at 405 nm is 63.90 +/- 27.81 M m(-1) at the rural site, contributing more than half of total absorption, which is about five times higher than that at urban site (10.43 +/- 4.74 M m(-1)). Compared with secondary OC, rural BrC light absorption more depends on primary OC from biomass and coal burning. The rural MAE(Brc) (BrC mass absorption efficiency) at 405 nm ranges from 0.6 to 5.1 m(2) g(-1) with mean value of 3.5 +/- 0.8 m(2) g(-1), which is about three times higher than the urban site. (C) 2021 Elsevier Ltd. All rights reserved.

Air pollutants can be transported to the pristine regions such as the Tibetan Plateau, by monsoon and stratospheric intrusion. The Tibetan Plateau region has limited local anthropogenic emissions, while this region is influenced strongly by transport of heavy emissions mainly from South Asia. We conducted a comprehensive study on various air pollutants (PM2.5, total gaseous mercury, and surface ozone) at Nam Co Station in the inland Tibetan Plateau. Monthly mean PM2.5 concentration at Nam Co peaked in April before monsoon season, and decreased during the whole monsoon season (June-September). Monthly mean total gaseous mercury concentrations at Nam Co peaked in July and were in high levels during monsoon season. The Indian summer monsoon acted as a facilitator for transporting gaseous pollutants (total gaseous mercury) but a suppressor for particulate pollutants (PM2.5) during the monsoon season. Different from both PM2.5 and total gaseous mercury variabilities, surface ozone concentrations at Nam Co are primarily attributed to stratospheric intrusion of ozone and peaked in May. The effects of the Indian summer monsoon and stratospheric intrusion on air pollutants in the inland Tibetan Plateau are complex and require further studies. (C) 2021 China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V.