The role of new energy in carbon neutral ZOU, Caineng; XIONG, Bo; XUE, Huaqing ...
Petroleum exploration and development,
April 2021, 2021-04-00, 2021-04-01, Letnik:
48, Številka:
2
Journal Article
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Carbon dioxide is an important medium of the global carbon cycle, and has the dual properties of realizing the conversion of organic matter in the ecosystem and causing the greenhouse effect. The ...fixed or available carbon dioxide in the atmosphere is defined as “gray carbon”, while the carbon dioxide that cannot be fixed or used and remains in the atmosphere is called “black carbon”. Carbon neutral is the consensus of human development, but its implementation still faces many challenges in politics, resources, technology, market, and energy structure, etc. It is proposed that carbon replacement, carbon emission reduction, carbon sequestration, and carbon cycle are the four main approaches to achieve carbon neutral, among which carbon replacement is the backbone. New energy has become the leading role of the third energy conversion and will dominate carbon neutral in the future. Nowadays, solar energy, wind energy, hydropower, nuclear energy and hydrogen energy are the main forces of new energy, helping the power sector to achieve low carbon emissions. “Green hydrogen” is the reserve force of new energy, helping further reduce carbon emissions in industrial and transportation fields. Artificial carbon conversion technology is a bridge connecting new energy and fossil energy, effectively reducing the carbon emissions of fossil energy. It is predicted that the peak value of China's carbon dioxide emissions will reach 110×108 t in 2030. The study predicts that China's carbon emissions will drop to 22×108 t, 33×108 t and 44×108 t, respectively, in 2060 according to three scenarios of high, medium, and low levels. To realize carbon neutral in China, seven implementation suggestions have been put forward to build a new “three small and one large” energy structure in China and promote the realization of China's energy independence strategy.
Nitrogen fertilization is considered as an important source of atmospheric N₂O emission. A seven site-year on-farm field experiment was conducted at Ottawa and Guelph, ON and Saint-Valentin, QC, ...Canada to characterize the affect of the amount and timing of N fertilizer on N₂O emission in corn (Zea mays L.) production. Using the static chamber method, gas samples were collected for 28-days after preplant and 28-days after sidedress fertilization at the seven site-year, resulting in 14 monitoring periods. For both methods of fertilization, peak N₂O flux and cumulative emission increased with the amount of N applied, with rates ranging from 30 to 900 μg N m⁻² h⁻¹. Depending on N amount and time of application, cumulative emission varied from 0.05 to 2.42 kg N ha⁻¹, equivalent to 0.03% to 1.45% of the N fertilizer applied. Differences in N₂O emission peaks among fertilizer treatments were clearly separated in 13 out of 14 monitoring periods. Total N₂O emissions may have been underestimated compared with annual monitoring in 10 out of the 49 cases because the monitoring period ended before N₂O efflux returned to the baseline level. The flux of N₂O was negligible when soil mineral N in the 0-15 cm layer was < 20 mg N kg⁻¹. While rainfall stimulated emission, soil temperature > 15 °C was likely the driving force responsible for the higher levels of N₂O found for sidedress than preplant application methods. However, caution must be taken when interpreting these later results as preplant fertilization may have continuously stimulated N₂O emissions after the 28-days monitoring period, especially in situations where N₂O effluxes have not fallen back to their baseline levels. Increasing fertilizer rates from 90 to 150 kg N ha⁻¹ resulted in slight increases in yields, but doubled cumulative N₂O emissions.
A continuous tropospheric and stratospheric vertically resolved ozone time series, from 1850 to 2099, has been generated to be used as forcing in global climate models that do not include interactive ...chemistry. A multiple linear regression analysis of SAGE I+II satellite observations and polar ozonesonde measurements is used for the stratospheric zonal mean dataset during the well-observed period from 1979 to 2009. In addition to terms describing the mean annual cycle, the regression includes terms representing equivalent effective stratospheric chlorine (EESC) and the 11-yr solar cycle variability. The EESC regression fit coefficients, together with pre-1979 EESC values, are used to extrapolate the stratospheric ozone time series backward to 1850. While a similar procedure could be used to extrapolate into the future, coupled chemistry climate model (CCM) simulations indicate that future stratospheric ozone abundances are likely to be significantly affected by climate change, and capturing such effects through a regression model approach is not feasible. Therefore, the stratospheric ozone dataset is extended into the future (merged in 2009) with multi-model mean projections from 13 CCMs that performed a simulation until 2099 under the SRES (Special Report on Emission Scenarios) A1B greenhouse gas scenario and the A1 adjusted halogen scenario in the second round of the Chemistry-Climate Model Validation (CCMVal-2) Activity. The stratospheric zonal mean ozone time series is merged with a three-dimensional tropospheric data set extracted from simulations of the past by two CCMs (CAM3.5 and GISS-PUCCINI) and of the future by one CCM (CAM3.5). The future tropospheric ozone time series continues the historical CAM3.5 simulation until 2099 following the four different Representative Concentration Pathways (RCPs). Generally good agreement is found between the historical segment of the ozone database and satellite observations, although it should be noted that total column ozone is overestimated in the southern polar latitudes during spring and tropospheric column ozone is slightly underestimated. Vertical profiles of tropospheric ozone are broadly consistent with ozonesondes and in-situ measurements, with some deviations in regions of biomass burning. The tropospheric ozone radiative forcing (RF) from the 1850s to the 2000s is 0.23 W m−2, lower than previous results. The lower value is mainly due to (i) a smaller increase in biomass burning emissions; (ii) a larger influence of stratospheric ozone depletion on upper tropospheric ozone at high southern latitudes; and possibly (iii) a larger influence of clouds (which act to reduce the net forcing) compared to previous radiative forcing calculations. Over the same period, decreases in stratospheric ozone, mainly at high latitudes, produce a RF of −0.08 W m−2, which is more negative than the central Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) value of −0.05 W m−2, but which is within the stated range of −0.15 to +0.05 W m−2. The more negative value is explained by the fact that the regression model simulates significant ozone depletion prior to 1979, in line with the increase in EESC and as confirmed by CCMs, while the AR4 assumed no change in stratospheric RF prior to 1979. A negative RF of similar magnitude persists into the future, although its location shifts from high latitudes to the tropics. This shift is due to increases in polar stratospheric ozone, but decreases in tropical lower stratospheric ozone, related to a strengthening of the Brewer-Dobson circulation, particularly through the latter half of the 21st century. Differences in trends in tropospheric ozone among the four RCPs are mainly driven by different methane concentrations, resulting in a range of tropospheric ozone RFs between 0.4 and 0.1 W m−2 by 2100. The ozone dataset described here has been released for the Coupled Model Intercomparison Project (CMIP5) model simulations in netCDF Climate and Forecast (CF) Metadata Convention at the PCMDI website (http://cmip-pcmdi.llnl.gov/).
In December 11, 2018, the fall armyworm (FAW), Spodoptera frugiperda invaded China and has since impacted local maize, sorghum and other crops. Here, we draw on laboratory experiments to show how ...different host crops (i.e., maize, sorghum, wheat and rice) and artificial diet affect larval growth and adult reproduction of one local FAW strain. Larval diet affected development duration, pupation rate, survival and emergence rate of pupae, and S. frugiperda adult fecundity. FAW attained the slowest larval development (19.4 days) on sorghum and the fastest (14.1 days) on artificial diet, with larvae attaining 99.6% survival on the latter food item. On rice, FAW larvae attained survival rate of 0.4% and were unable to pupate successfully. Pupation rate and pupal survival varied substantially between artificial diet and live plantlets at different phenological stages. Pupal weight was the highest (0.26 g) on artificial diet and the lowest (0.14 g) on sorghum, while FAW females reached the highest fecundity (699.7 eggs/female) on 2-leaf stage maize. Egg hatching rate equaled 93.6% on 4- or 5-leaf stage maize and 36.6% on artificial diet. FAW intrinsic rate of natural increase and the finite rate of increase varied between larval diets, reflecting how young maize leaves are the most suitable diet. Our findings can help to refine laboratory rearing protocols, devise population forecasting models or guide the deployment of ‘area-wide’ integrated pest management (IPM) modules in FAW-invaded areas of China and other Asian countries.
Patients with metastatic castration-resistant prostate cancer (mCRPC) and BRCA alterations have poor outcomes. MAGNITUDE found patients with homologous recombination repair gene alterations (HRR+), ...particularly BRCA1/2, benefit from first-line therapy with niraparib plus abiraterone acetate and prednisone (AAP). Here we report longer follow-up from the second prespecified interim analysis (IA2).
Patients with mCRPC were prospectively identified as HRR+ with/without BRCA1/2 alterations and randomized 1 : 1 to niraparib (200 mg orally) plus AAP (1000 mg/10 mg orally) or placebo plus AAP. At IA2, secondary endpoints time to symptomatic progression, time to initiation of cytotoxic chemotherapy, overall survival (OS) were assessed.
Overall, 212 HRR+ patients received niraparib plus AAP (BRCA1/2 subgroup, n = 113). At IA2 with 24.8 months of median follow-up in the BRCA1/2 subgroup, niraparib plus AAP significantly prolonged radiographic progression-free survival {rPFS; blinded independent central review; median rPFS 19.5 versus 10.9 months; hazard ratio (HR) = 0.55 95% confidence interval (CI) 0.39-0.78; nominal P = 0.0007} consistent with the first prespecified interim analysis. rPFS was also prolonged in the total HRR+ population HR = 0.76 (95% CI 0.60-0.97); nominal P = 0.0280; median follow-up 26.8 months. Improvements in time to symptomatic progression and time to initiation of cytotoxic chemotherapy were observed with niraparib plus AAP. In the BRCA1/2 subgroup, the analysis of OS with niraparib plus AAP demonstrated an HR of 0.88 (95% CI 0.58-1.34; nominal P = 0.5505); the prespecified inverse probability censoring weighting analysis of OS, accounting for imbalances in subsequent use of poly adenosine diphosphate-ribose polymerase inhibitors and other life-prolonging therapies, demonstrated an HR of 0.54 (95% CI 0.33-0.90; nominal P = 0.0181). No new safety signals were observed.
MAGNITUDE, enrolling the largest BRCA1/2 cohort in first-line mCRPC to date, demonstrated improved rPFS and other clinically relevant outcomes with niraparib plus AAP in patients with BRCA1/2-altered mCRPC, emphasizing the importance of identifying this molecular subset of patients.
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•Niraparib + AAP reduced risk of radiographic progression/death by 45% in BRCA1/2-altered mCRPC (median follow-up 24.8 mo).•Niraparib + AAP improved secondary endpoints and patient-reported outcomes in the BRCA1/2 subgroup.•Adverse events of niraparib + AAP were tolerable, manageable, and consistent with previous reports; no new safety signals.•MAGNITUDE second interim analysis continues to support niraparib + AAP for mCRPC and HRR alterations, especially BRCA1/2.•MAGNITUDE supports genomic testing for BRCA1/2 alterations in mCRPC due to poor outcomes and emerging treatment options.
Floral resources, such as carbohydrate-rich nectar or pollen, can bolster fitness and raise reproductive output of adult lepidopterans. Here, we used laboratory experiments to assess how those ...plant-derived foods impact adult fecundity, reproductive physiology and flight performance of an invasive strain of the fall armyworm, Spodoptera frugiperda (FAW; Lepidoptera: Noctuidae) in China. More specifically, supplementary feeding on bee pollen and honey enhanced FAW flight duration, testis size, ovarian development, longevity and adult fecundity. FAW adults attained the longest pre-oviposition (10.8 days) and oviposition period (6.8 days) and longevity (19.2 days) on 5% acacia honey. Upon access to 2.5% acacia honey and 2.5‰ pine pollen, S. frugiperda attained the highest mating rate (79.7%), fecundity (644.9 eggs/female) and egg hatching rate (82.3%). Feeding on honey further delayed decay of male testes, while ovarian development was enhanced when female moths were allowed access to 2.5% honey and 2.5‰ pine pollen. Upon feeding on 5% honey solution, S. frugiperda engaged in flight over the longest duration (9.5 h), distance (29.9 km) and speed (3.1 km h−1). Honey had a comparatively greater effect on the above parameters than pollen. Our findings help decipher FAW invasion patterns and population dynamics, facilitate the development of nutritional attractants, and contribute to integrated pest management of this newly-invasive pest in eastern Asia.
Abstract
Contamination from galaxy fragments, identified as sources, is a major issue in large photometric galaxy catalogs. In this paper, we prove that this problem can be easily addressed with ...computer vision techniques. We use image cutouts to train a convolutional neural network (CNN) to identify cataloged sources that are in reality just star-formation regions and/or shreds of larger galaxies. The CNN reaches an accuracy ∼98% on our testing data sets. We apply this CNN to galaxy catalogs from three among the largest surveys available today: the Sloan Digital Sky Survey, the DESI Legacy Imaging Surveys, and the Panoramic Survey Telescope and Rapid Response System Survey. We find that, even when strict selection criteria are used, all catalogs still show a ∼5% level of contamination from galaxy shreds. Our CNN gives a simple yet effective solution to clean galaxy catalogs from these contaminants.
Abstract
We present “Extending the Satellites Around Galactic Analogs Survey” (xSAGA), a method for identifying low-
z
galaxies on the basis of optical imaging and results on the spatial ...distributions of xSAGA satellites around host galaxies. Using spectroscopic redshift catalogs from the SAGA Survey as a training data set, we have optimized a convolutional neural network (CNN) to identify
z
< 0.03 galaxies from more-distant objects using image cutouts from the DESI Legacy Imaging Surveys. From the sample of >100,000 CNN-selected low-
z
galaxies, we identify >20,000 probable satellites located between 36–300 projected kpc from NASA-Sloan Atlas central galaxies in the stellar-mass range
9.5
<
log
(
M
⋆
/
M
⊙
)
<
11
. We characterize the incompleteness and contamination for CNN-selected samples and apply corrections in order to estimate the true number of satellites as a function of projected radial distance from their hosts. Satellite richness depends strongly on host stellar mass, such that more-massive host galaxies have more satellites, and on host morphology, such that elliptical hosts have more satellites than disky hosts with comparable stellar masses. We also find a strong inverse correlation between satellite richness and the magnitude gap between a host and its brightest satellite. The normalized satellite radial distribution between 36–300 kpc does not depend on host stellar mass, morphology, or magnitude gap. The satellite abundances and radial distributions we measure are in reasonable agreement with predictions from hydrodynamic simulations. Our results deliver unprecedented statistical power for studying satellite galaxy populations and highlight the promise of using machine-learning for extending galaxy samples of wide-area surveys.
Climate change severely impacts agricultural production, which jeopardizes food security. China is the second largest maize producer in the world and also the largest consumer of maize. Analyzing the ...impact of climate change on maize yields can provide effective guidance to national and international economics and politics. Panel models are unable to determine the group-wise heteroscedasticity, cross-sectional correlation and autocorrelation of datasets, therefore we adopted the feasible generalized least square (FGLS) model to evaluate the impact of climate change on maize yields in China from 1979–2016 and got the following results: (1) During the 1979–2016 period, increases in temperature negatively impacted the maize yield of China. For every 1°C increase in temperature, the maize yield was reduced by 5.19 kg 667 m–2 (1.7%). Precipitation increased only marginally during this time, and therefore its impact on the maize yield was negligible. For every 1 mm increase in precipitation, the maize yield increased by an insignificant amount of 0.043 kg 667 m–2 (0.014%). (2) The impacts of climate change on maize yield differ spatially, with more significant impacts experienced in southern China. In this region, a 1°C increase in temperature resulted in a 7.49 kg 667 m–2 decrease in the maize yield, while the impact of temperature on the maize yield in northern China was insignificant. For every 1 mm increase in precipitation, the maize yield increased by 0.013 kg 667 m–2 in southern China and 0.066 kg 667 m–2 in northern China. (3) The resilience of the maize crop to climate change is strong. The marginal effect of temperature in both southern and northern China during the 1990–2016 period was smaller than that for the 1979–2016 period.
•PEO processing of an Al–Cu–Li alloy in silicate electrolytes is investigated.•Brownish-red coatings, due to cuprite species, improved the corrosion resistance of the alloy.•Bi-layered coatings ...formed in dilute electrolyte gave superior wear resistance.•Both the outer and inner layers of the coatings contribute to the wear resistance.•A modified model of PEO was proposed for coating formation in dilute silicate electrolyte.
Coatings have been produced on an 2A97 Al–Cu–Li alloy by plasma electrolytic oxidation (PEO) using dilute and concentrated sodium silicate solutions with pulsed electrical regimes. Brownish red coatings were formed, especially in the dilute silicate solution. The colour is attributed to cuprite, formed by oxidation of copper in the alloy. The main phases of the coatings formed in the dilute and concentrated electrolytes are γ-Al2O3 and mullite, respectively. A bi-layer coating is formed in the dilute electrolyte, with large pores between the layers. The outer layer contains a small amount of δ-Al2O3 and α-Al2O3. Coatings formed using both electrolytes provided good corrosion resistance. The wear resistance was superior for the coating formed in the dilute electrolyte, since the outer layer is compact and of high strength and after the removal of the outer layer, a more adherent inner layer, with a hardness of 9–12GPa, provides excellent protection. Based on the coating microstructure, a modified model of coating growth was proposed.
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