ABSTRACT
CO2 emissions from power plants are the dominant source of global CO2 emissions, thus in the context of global warming, accurate estimation of CO2 emissions from power plants is essential for the effective control of carbon emissions. Based on the XCO2 retrievals from the Orbiting Carbon Observatory 2 (OCO-2) and the Gaussian Plume Model (GPM), a series of studies have been carried out to estimate CO2 emission from power plants. However, the GPM is an ideal model, and there are a number of assumptions that need to be made when using this model, resulting in large uncertainties in the inverted emissions. Here, based on 6 cases of power plant plumes observed by the OCO-2 satellite over the Yangtze River Delta, China, we use an inline plume rise module coupled in the Community Multi-scale Air Quality model (CMAQ) to simulate the plumes and invert the emissions, and compare the simulated plumes and inverted emissions using the GPM model. We found that CO2 emissions can be significantly overestimated or underestimated based on the GPM simulations, and that the CMAQ inline plume simulation could significantly improve the estimates. However, the simulation bias in wind speed can significantly affect the inversion results. These results indicate that accurate meteorological field and plume simulations are critical for future inversion of point source emissions.
ABSTRACT
Recent rapid warming has caused uneven impacts on the composition, structure, and functioning of northern ecosystems. It remains unknown how climatic drivers control linear and non-linear trends in ecosystem productivity. Based on a plant phenology index (PPI) product at a spatial resolution of 0.05° over 2000-2018, we used an automated polynomial fitting scheme to detect and characterize trend types (i.e., polynomial trends and no-trends) in the yearly-integrated PPI (PPIINT) for northern (> 30°N) ecosystems and their dependence on climatic drivers and ecosystem types. The averaged slope for the linear trends (p < 0.05) of PPIINT was positive across all the ecosystems, among which deciduous broadleaved forests and evergreen needle-leaved forests (ENF) showed the highest and lowest mean slopes, respectively. More than 50% of the pixels in ENF, arctic and boreal shrublands, and permanent wetlands (PW) had linear trends. A large fraction of PW also showed quadratic and cubic trends. These trend patterns agreed well with estimates of global vegetation productivity based on solar-induced chlorophyll fluorescence. Across all the biomes, PPIINT in pixels with linear trends showed lower mean values and higher partial correlation coefficients with temperature or precipitation than in pixels without linear trends. Overall, our study revealed the emergence of latitudinal convergence and divergence in climatic controls on the linear and non-linear trends of PPIINT, implying that northern shifts of vegetation and climate change may potentially increase the non-linear nature of climatic controls on ecosystem productivity. These results can improve our understanding and prediction of climate-induced changes in plant phenology and productivity and facilitate sustainable management of ecosystems by accounting for their resilience and vulnerability to future climate change.
Subject(s)
Ecosystem , Forests , Temperature , Arctic Regions , Plants , Climate Change , SeasonsABSTRACT
Agricultural ecosystem water use efficiency (WUE) is an important indicator reflecting carbon-water coupling, but its control mechanisms in managed fields remain unclear. In order to reveal the influencing factors of WUE in the agricultural field under mulched drip irrigation (DM), we carried out the 8-year continuous observations in a maize field from Northwestern China. The structural equation model, relative importance analysis and principal component analysis were used to quantify the regulation effects of environmental and biological factors on WUE at different time scales, in different growth stages and under different hydrothermal conditions. The results showed that annual WUE varied between 2.18 g C Kg-1 H2O and 3.60 g C Kg-1 H2O, with a multi-year mean of 2.91 g C Kg-1 H2O. The total effects of air temperature on the daily WUE in the whole growth period, the vegetative growth stage, the warm and dry years, the cold and wet years, and the warm and wet years were the largest, with values of 0.61, 0.80, 0.70, 0.70 and 0.91 respectively. However, vapor pressure deficit and net radiation had the largest total effect in the cold and dry years (-0.63) and the reproductive growth stage (-0.49), respectively. Leaf biomass played a leading role in regulating the daily and interannual WUE, and the relative importance of leaf biomass to WUE in the vegetative growth stage was up to 75 %. In the warm and wet years, the relative importance of root biomass to WUE was 33 %, slightly higher than that of leaf biomass (31 %). At the same time, we found that Ta has the potential to increase WUE under future climate warming. Our results improve the understanding of carbon-water coupling mechanisms and provide important enlightenment on how crop ecosystems should adapt to future climate change.
Subject(s)
Water , Zea mays , Ecosystem , Biomass , Carbon , Agricultural Irrigation/methodsABSTRACT
Sudden mega natural gas leaks of two Nord Stream pipelines in the Baltic Sea (Denmark) occurred from late September to early October 2022, releasing large amounts of methane into the atmosphere. We inferred the methane emissions of this event based on surface in situ observations using two inversion methods and two meteorological reanalysis datasets, supplemented with satellite-based observations. We conclude that approximately 220 ± 30 Gg of methane was released from September 26 to October 1, 2022.
ABSTRACT
China, the Unite States (US), the European Union (EU), India, and Russia are the world's top 5 fossil fuel and cement CO2 (FFC) emitting countries or regions (CRs). It is very important to understand their status of carbon neutrality, and to monitor their future changes of net carbon fluxes (NCFs). In this study, we implemented a well-established global carbon assimilation system (GCAS, Version 2) to infer global surface carbon fluxes from May 2009 to December 2019 using both GOSAT and OCO-2 XCO2 retrievals. The reductions of flux uncertainty and XCO2 bias, and the evaluation of posterior flux show that GCAS has comparable and good performance in the 5 CRs. The results suggest that Russia has achieved carbon neutrality, but the other 4 are still far from being carbon neutral, especially China. The mean annual NCFs in China, the US, the EU, India, and Russia are 2.33 ± 0.29, 0.82 ± 0.20, 0.42 ± 0.16, 0.50 ± 0.12, and -0.33 ± 0.23 PgC yr-1, respectively. From 2010 to 2019, the NCFs showed an increasing trend in the US and India, a slight downward trend after 2013 in China, and were stable in the EU. The changes of land sinks in China and the US might be the main reason for their trends. India's trend was mainly due to the increase of FFC emission. The relative contributions of NCFs to the global land net carbon emission of China and the EU have decreased, while those of the US and India have increased, implying the US and India must take more active measures to control carbon emissions or increase their sinks. This study indicates that satellite XCO2 could be successfully used to monitor the changes of regional NCFs, which is of great significance for major countries to achieve greenhouse gas control goals.
ABSTRACT
Our study suggests that the global CO2 fertilization effect (CFE) on vegetation photosynthesis has declined during the past four decades. The Comments suggest that the temporal inconsistency in AVHRR data and the attribution method undermine the results' robustness. Here, we provide additional evidence that these arguments did not affect our finding and that the global decline in CFE is robust.
Subject(s)
Carbon Dioxide , Photosynthesis , FertilizationABSTRACT
Assessing the transport of natural radionuclides in the atmosphere provides a powerful tool to study air mass circulation. Here, we investigated the seasonal atmospheric distribution of the naturally produced 7Be in surface air over Europe between 40° N and 68° N during the period 1975-2018. The results suggest that the inter-annual variability of 7Be reflects production rates of the radionuclide induced by solar modulation of cosmic rays. Further analysis of the meteorological influences indicates that the meteorological influences on 7Be concentrations are geographically and seasonally dependent. We found that, in general, the tropopause pressure plays an important factor influencing 7Be activity for winter and spring seasons while the sea level pressure and temperature are more dominant during summer and autumn seasons. The combination of tropospheric production rates and meteorological parameters explains 24%-79% variances of the seasonal 7Be activity. We further applied a three-box model to study the influence of stratosphere-troposphere exchanges on 7Be concentrations. The simulation supports that the seasonal cycle of 7Be in Europe is controlled by two main factors: the changing height of the troposphere (seasonality of the tropopause height) and seasonal variations of the stratosphere-troposphere exchanges.
Subject(s)
Air Pollutants, Radioactive , Atmosphere , Air Pollutants, Radioactive/analysis , Europe , Meteorology , SeasonsABSTRACT
The enhanced vegetation productivity driven by increased concentrations of carbon dioxide (CO2) [i.e., the CO2 fertilization effect (CFE)] sustains an important negative feedback on climate warming, but the temporal dynamics of CFE remain unclear. Using multiple long-term satellite- and ground-based datasets, we showed that global CFE has declined across most terrestrial regions of the globe from 1982 to 2015, correlating well with changing nutrient concentrations and availability of soil water. Current carbon cycle models also demonstrate a declining CFE trend, albeit one substantially weaker than that from the global observations. This declining trend in the forcing of terrestrial carbon sinks by increasing amounts of atmospheric CO2 implies a weakening negative feedback on the climatic system and increased societal dependence on future strategies to mitigate climate warming.
Subject(s)
Carbon Cycle , Carbon Dioxide/metabolism , Global Warming , Photosynthesis , Atmosphere/chemistry , Carbon Dioxide/analysisABSTRACT
The magnitude of soil and sediment erosion and accumulation processes can profoundly affect landscape development and hamper efficient management of natural resources. Consequently, estimating the rates and causes of these processes is essential, particularly in remote regions, for prediction of changes in landform and river evolution and protection of local ecosystem. We here present the results of a soil and sediment erosion investigation in the Source Area of the Yellow River (SAYR), northeast Qinghai-Tibet Plateau based on a combined analysis of 10Be cosmogenic isotope and Soil and Water Assessment Tool (SWAT) simulation modelling. The data reveal variable soil erosion trends that range between 103 and 830â¯t km-2 a-1. The low values occur in the western part of the basin that are associated with low sediment yield, while the high values appear in the dominant sediment export part of the basin along the main stream of the Yellow River in the east. Generally, soil and sediment accumulation is characterized by high 10Be concentration in the western part and the northwest of Ngöring Lake. The style of landform development by the erosion/accumulation processes is closely linked to the distribution and degradation extent of the permafrost in the study region. Soil surface erosion increases with more permafrost degradation from the western to the eastern part of the basin, and surface soil particles are dominantly removed from the surface rather than deeper layers.