Sanchezbirch4631

The proliferation of modern vegetable plastic greenhouses (VPGS) supplies more and more vegetables for food all over the world. The airborne bacteria and fungi induce more exposure opportunities for workers toiling in confined plastic greenhouses. Culture-independent approaches by qPCR and high-throughput sequencing technology were used to study the airborne particulates microbiota in typic VPGS in Shandong, a large base of vegetables in China. The result revealed the mean airborne bacteria concentrations reached 1.67 × 103 cells/m3 (PM2.5) and 2.38 × 103 cells/m3 (PM10), and the mean airborne fungal concentrations achieved 1.49 × 102 cells/m3 (PM2.5) and 3.19 × 102 cells/m3 (PM10) in VPGS. The predominant bacteria in VPGS included Ralstonia, Alcanivorax, Pseudomonas, Bacillus, and Acinetobacter. Botrytis, Alternaria, Fusarium, Sporobolomyces, and Cladosporium were frequently detected fungal genera in VPGS. A higher Chao1 of bacteria in PM10 was significantly different from PM2.5 in VPGS. The potential pathogens in VPGS include Raltonia picketti, Acinetobacter lwoffii, Bacillus anthracis, Botrytis cinerea, and Cladosporium sphaerospermum. The network analysis indicated that airborne microbiota was associated with soil microbiota which was affected by anthropologic activities. The predicted gene functions revealed that bacterial function mainly involved metabolism, neurodegenerative diseases, and fungal trophic mode dominated by Pathotroph-Saprotroph in VPGS. These findings unveiled airborne microbiomes in VPGS so that a strategy for improving air quality can be applied to safeguard health and vegetation.With the raising awareness of environmental protection, straw burning ban has been implemented to control straw burning phenomenon in China. It has received significant achievement by reducing the fire spots remarkably, but fire spots still cannot be eliminated in farmland. Although considerable papers and reviews on straw burning have been conducted, there is still a lack of comprehensive and systematic review of exploring the status, obstacles, implications, and motivations of this phenomenon, especially revealing the unique circumstance and experience in China. The review first summarizes the reasons as well as hazards of straw burning in China, and then explores the dilemma of straw burning ban in terms of farmers' endowments. And then, the review discusses the limitations of subsidy from financial expenditure and suggests two alternative innovative incentives transferred payment from stakeholders and carbon trading. It is hoped that policy suggestion about straw burning and innovative incentives can enlighten researchers and policymakers who intend to implement straw burning ban effectively in the future.Swampy/septic odor caused by thioethers has become the main taste and odor (T&O) problem in drinking water of China. Improving its removal performance by commonly traditional water treatment process is significant. In our study, we have found that pre-oxidation could modify the background dissolved organic matter (DOM) properties and thus improve the coagulation performance of thioethers, increasing the coagulation removal rates by 1.5-3 times. Particularly, after pre-ozonation only protein-like substances remained, and thioethers removal was 1.5 times higher than that after pre-chlorination (only coagulation not including oxidation). Compared with humic acid (HA), the thioethers compounds removal efficiencies under bovine serum albumin (BSA) as background DOM was increased by 0.3-3 times. Through Freundlich model analysis, the binding strength of BSA (KF = 20.712, at 298 K) to dimethyl disulfide (DMDS) was enhanced by 60 % compared to HA (KF = 12.778, at 298 K). According to thermodynamic parameters, the binding effect between HA/BSA and thioethers compounds was mainly van der Waals forces and hydrogen bond. BSA with more amino structure and oxygen groups was more easily to adsorb DMDS through hydrogen bond and thus achieved better coagulation performance. Therefore, pre-ozonation combined with coagulation was suggested to be more suitable for thioethers compounds control.Soybean is an important oil crop in China, and the national focus of soybean production is Northeast China. Crop yield is affected by climate, cultivars and agricultural management practices. Optimizing the composite impacts of these factors on soybean yield and yield gaps is crucial for the local agricultural community. In this study, we used the DSSAT-CROPGRO-Soybean model (validated based on longer-than-20-years agro-meteorological experiments data) to simulate the potential yield (Yp), attainable yield (Ya), and potential farmer's yield (Ypf) of soybean for 56 counties from 1981 to 2017 in Northeast China. Combined with actual farmer's yield (Yf), we computed different types of yield gaps. Furthermore, we optimized cultivars, agricultural management practices, and those interactions on soybean yield and yield gaps. On county-level, the Yp, Ya, Ypf and Yf averaged 5528.9, 4762.9, 3786.8 and 1918.8 kg ha-1, respectively. The total yield gap between Yf and Yp was 63.8 % of Yp. The yield gap between Ya and Yp was 12.8 %, which caused by uncontrollable factors; the yield gap between Ypf and Ya was 17.6 %, which caused by agronomic factors; and the yield gap between Yf and Ypf was 33.5 %, which caused by socioeconomic factors. During 1981-2017, climate, cultivar, sowing date and plant density change affected Ypf by -7.5, 4.5, -3.0 and - 2.0 %, respectively. By optimizing cultivar, sowing date and plant density, Ypf would increase by 13.1, 7.9 and 3.1 % and yield gap would close by 9.2, 5.6 and 2.1 %, respectively. By comprehensively optimizing cultivar, sowing date and plant density, Ypf would increase by 19.4 % and yield gap would close by 13.7 %. This work has practical significance for understanding climate, cultivar and agricultural management impacts on soybean yield, and demonstrates an effective approach, by optimizing cultivars and agricultural management practices to address climate change, increase yield and close yield gaps.In acid sulfate (AS) soils, organic rich topsoil and subsoil horizons with highly variable acidity and moisture conditions and interconnected reactions of sulfur and nitrogen make them potential sources of greenhouse gases (GHGs). Subsoil liming can reduce the acidification of sulfidic subsoils in the field. However, the mitigation of GHG production in AS subsoils by liming, and the mechanisms involved, are still poorly known. We limed samples from different horizons of AS and non-AS soils to study the effects of liming on the N2O and CO2 production during a 56-day oxic and subsequent 72-h anoxic incubation. Liming to pH ≥ 7 decreased oxic N2O production by 97-98 % in the Ap1 horizon, 38-50 % in the Bg1 horizon, and 34-36 % in the BC horizon, but increased it by 136-208 % in the C horizon, respectively. Liming decreased anoxic N2O production by 86-94 % and 78-91 % in Ap1 and Bg1 horizons, but increased it by 100-500 % and 50-162 % in BC and C horizons, respectively. Liming decreased N2O/(N2O + N2) in anoxic denitrification in most horizons of both AS and non-AS soils. Liming significantly increased the cumulative oxic and anoxic CO2 production in AS soil, but less so in non-AS soil due to the initial high soil pH. Higher carbon and nitrogen contents in AS soil compared to non-AS soil agreed with the respectively higher cumulative oxic N2O production in all horizons, and the higher CO2 production in the subsoil horizons of all lime treatments. Pargyline Overall, liming reduced the proportion of N2O in the GHGs produced in most soil horizons under oxic and anoxic conditions but reduced the total GHG production (as CO2 equivalents) only in the Ap1 horizon of both soils. The results suggest that liming of subsoils may not always effectively mitigate GHG emissions due to concurrently increased CO2 production and denitrification.As global climate change is altering the distribution range of macroalgae across the globe, it is critical to assess its impact on species range shifts to inform the biodiversity conservation of macroalgae. Latitude/environmental gradients could cause intraspecific variability, which may result in distinct responses to climate change. It remains unclear whether geographical variation occurs in the response of species' populations to climate change. We tested this assumption using the brown alga Sargassum thunbergii, a habitat-forming macroalgae encompassing multiple divergent lineages along the Northwest Pacific. Previous studies revealed a distinct lineage of S. thunbergii in rear-edge populations. Given the phylogeographic structure and temperature gradients, we divided these populations into the southern and northern groups. We assessed the physiological responses of the two groups to temperature changes and estimated their niche differences using n-dimensional hypervolumes. A higher photosynthetic rate and antioxidative abilities were detected in the southern group of S. thunbergii than in the northern group. In addition, significant niche differentiation was detected between the two groups, suggesting the possibility for local adaptation. Given these results, we inferred that the southern group (rear-edge populations) may be more resilient to climate change. To examine climate-driven range shifts of S. thunbergii, we constructed species- and lineage-level species distribution models (SDMs). Predictions of both levels showed considerable distribution contracts along the Chinese coasts in the future. For the southern group, the lineage-level model predicted less habitat loss than the species-level model. Our results highlight the importance of considering intraspecific variation in climate change vulnerability assessments for coastal species.Air pollution hinders technological innovation, but the causal effects of air pollution on technology transfer are overlooked. We use thermal inversion as an instrumental variable for addressing air pollution endogeneity. The empirical results show that a one-unit increase in air pollution reduces technology transfer strength by 4.5 %. However, air pollution has a strong asymmetry in two directions of technology transfer strength. We find that those cities with worse pollution have an intention to transfer their technologies to cities in other provinces. In the PLFC model, heterogeneity varying with GDP can be addressed to estimate the marginal effect between them. Findings suggest that the marginal effects of air pollution on technology transfer can be divided into two parts based on GDP levels. Within the thresholds (lngdp = 11), the effect of environmental regulations will keep increasing and keep stable beyond the thresholds. In addition, different effects on different cities are also discussed.With a remarkable increase in industrialization among fast-developing countries, air pollution is rising at an alarming rate and has become a public health concern. The study aims to examine the effect of air pollution on patient's hospital visits for respiratory diseases, particularly Acute Respiratory Infections (ARI). Outpatient hospital visits, air pollution and meteorological parameters were collected from March 2018 to October 2021. Eight machine learning algorithms (Random Forest model, K-Nearest Neighbors regression model, Linear regression model, LASSO regression model, Decision Tree Regressor, Support Vector Regression, X.G. Boost and Deep Neural Network with 5-layers) were applied for the analysis of daily air pollutants and outpatient visits for ARI. The evaluation was done by using 5-cross-fold confirmations. The data was randomly divided into test and training data sets at a scale of 12, respectively. Results show that among the studied eight machine learning models, the Random Forest model has given the best performance with R2 = 0.