Atmospheric Climate Change Research Articles

A new perspective on the spatial, temporal, and vertical distribution of biomass burning: quantifying a significant increase in CO emissions

A variance-maximization approach based on 19 years of weekly measurements of pollution in the troposphere carbon monoxide (CO) measurements quantifies the spatial-temporal distribution of global biomass burning. Seven regions consistent with existing datasets are discovered and shown to burn for longer, over a more widespread area. Each region has a unique and recurring burning season, with three dominated by inter- and intra-annual variation. The CO is primarily lofted to the free troposphere from where it spreads downwind at 800 to 700 mb with three exceptions: The Maritime Continent and South America where there is spread at 300 mb consistent with deep- and pyro-convection; and Southern Africa which reaches to 600 mb. The total mass of CO lofted into the free troposphere ranges from 46% over Central Africa to 92% over Australia. The global, annual emissions made using two different techniques lead to an increase of biomass burning CO emissions of 47TgCO/year and 99TgCO/year respectively. The larger increase is mainly due to two factors: first, a large amount of the emissions is lofted rapidly upwards over the biomass burning region and subsequently transported downwind, therefore not appearing near the biomass source in space and time and second, an increase in inter-annual variability. Consistently, there is an increase in variability year-to-year and during peak events, from which 35% to more than 80% of the total emissions is lofted into the free troposphere. The results demonstrate a significantly higher CO emission from biomass burning, a larger impact on the global atmospheric composition, and likely impacts on atmospheric chemistry and climate change.

The Political Economy of Pandemic Policy, COVID-19 and Climate Change. Why Market Fundamentalism and the Trump Administration Fail to Protect Public Health and the Economy

The Political Economy of Pandemic Policy, COVID-19 and Climate Change. Why Market Fundamentalism and the Trump Administration Fail to Protect Public Health and the Economy

Understanding Eunice Foote's 1856 experiments: heat absorption by atmospheric gases

The contribution of Eunice Foote (1819–1888) to early understanding of the relationship between atmospheric gases and climate change has become a focus of interest in the scholarly community and more widely on social media. In this article we offer a detailed interpretation of both of her known published papers, focusing particularly on her first and most significant paper of 1856, in which she related changes in the types and amounts of atmospheric gases, including carbon dioxide, to warming and changes in climate. We trace the derivation of her ideas and explore how she constructed, carried out, and interpreted her experiments.

Half a century of Scots pine forest ecosystem monitoring reveals long-term effects of atmospheric deposition and climate change.

At two forest sites in Germany (Pfaffenwinkel, Pustert) stocked with mature Scots pine (Pinus sylvestris L.), we investigated changes of topsoil chemistry during the recent 40years by soil inventories conducted on replicated control plots of fertilization experiments, allowing a statistical analysis. Additionally, we monitored the nutritional status of both stands from 1964 until 2019 and quantified stand growth during the monitoring period by repeated stand inventories. Moreover, we monitored climate variables (air temperature and precipitation) and calculated annual climatic water balances from 1991 to 2019. Atmospheric nitrogen (N) and sulfur (S) deposition between 1964 and 2019 was estimated for the period 1969-2019 by combining annual deposition measurements conducted in 1985-1987 and 2004 with long-term deposition records from long-term forest monitoring stations. We investigated interrelations between topsoil chemistry, stand nutrition, stand growth, deposition, and climate trends. At both sites, the onset of the new millennium was a turning point of important biogeochemical processes. Topsoil acidification turned into re-alkalinization, soil organic matter (SOM) accumulation stopped, and likely turned into SOM depletion. In the new millennium, topsoil stocks of S and plant-available phosphorus (P) as well as S and P concentrations in Scots pine foliage decreased substantially; yet, age-referenced stand growth remained at levels far above those expected from yield table data. Tree P and S nutrition as well as climate change (increased temperature and drought stress) have replaced soil acidification as major future challenges for both forests. Understanding of P and S cycling and water fluxes in forest ecosystems, and consideration of these issues in forest management is important for successfully tackling the new challenges. Our study illustrates the importance of long-term forest monitoring to identify slow, but substantial changes of forest biogeochemistry driven by natural and anthropogenic global change.

A kinetic model of gas-particle mass transfer in aerosol: Application to phase state in aerosol

Aerosol plays a vital role in atmosphere pollution, climate change, and health hazard. The mass transfer process between the aerosol particles and their ambient gas critically affects the evolution of aerosol particles and their phase states. A novel kinetic model is proposed to describe the gas-particle mass transfer among a particle bulk, a gas-particle interface and the ambient sources, based on Maxwell-Stefan relations and Langmuir adsorption theory. Two kinds of typical aerosol, which are respectively consisted of oxalic acid solution (aqueous solutions) and sucrose solution (easily to form a glassy state in a special condition), are chosen to demonstrate the feasibility of this proposed kinetic model, along with the available experimental data. The results showed that aerosol particles, which could kinetically form amorphous states during evaporation, are limited by the bulk viscosity. In contrast, the bulks consisting of aqueous solutions are controlled by the surface adsorption and desorption of molecules during mass transport.

Impact of environmental changes and land management practices on wheat production in India

Abstract. Spring wheat is a major food crop that is a staple for a large number of people in India and the world. To address the issue of food security, it is essential to understand how the productivity of spring wheat varies with changes in environmental conditions and agricultural management practices. The goal of this study is to quantify the role of different environmental factors and management practices on wheat production in India in recent years (1980 to 2016). Elevated atmospheric CO2 concentration ([CO2]) and climate change are identified as two major factors that represent changes in the environment. The addition of nitrogen fertilizers and irrigation practices are the two land management factors considered in this study. To study the effects of these factors on wheat growth and production, we developed crop growth processes for spring wheat in India and implemented them in the Integrated Science Assessment Model (ISAM), a state-of-the-art land model. The model is able to simulate the observed leaf area index (LAI) at the site scale and observed production at the country scale. Numerical experiments are conducted with the model to quantify the effect of each factor on wheat production on a country scale for India. Our results show that elevated [CO2] levels, water availability through irrigation, and nitrogen fertilizers have led to an increase in annual wheat production at 0.67, 0.25, and 0.26 Mt yr−1, respectively, averaged over the time period 1980–2016. However, elevated temperatures have reduced the total wheat production at a rate of 0.39 Mt yr−1 during the study period. Overall, the [CO2], irrigation, fertilizers, and temperature forcings have led to 22 Mt (30 %), 8.47 Mt (12 %), 10.63 Mt (15 %), and −13 Mt (−18 %) changes in countrywide production, respectively. The magnitudes of these factors spatially vary across the country thereby affecting production at regional scales. Results show that favourable growing season temperatures, moderate to high fertilizer application, high availability of irrigation facilities, and moderate water demand make the Indo-Gangetic Plain the most productive region, while the arid north-western region is the least productive due to high temperatures and lack of irrigation facilities to meet the high water demand.

Process Controls of the Live Root Zone and Carbon Sequestration Capacity of the Sundarbans Mangrove Forest, Bangladesh

The conservation of coastal wetland ecosystems, like mangrove forests and salt marshes, represents a critical strategy for mitigating atmospheric emissions and climate change in the 21st century. Yet the existence of these environments is threatened by human-induced disturbances, namely deforestation and accelerated sea-level rise. Coastal systems maintain surface elevation in response to sea-level rise through a combination of physical and biological processes both above and below the ground surface. The quantification and relative contribution of belowground process controls (e.g., seasonal water content, organic matter decomposition) on surface elevation change is largely unexplored but crucial for informing coastal ecosystem sustainability. To address this knowledge deficit, we integrated measurements of surface elevation change of the live root zone (0.5 to 1 m depth) with geotechnical data from co-located sediment cores in the Sundarbans mangrove forest (SMF) of southwest Bangladesh. Core data reveal that the primary belowground controls on surface elevation change include seasonal fluctuations in pore-water content and the relative abundance of fine-grained sediments capable of volumetric expansion and contraction, supporting an elevation gain of ~2.42 ± 0.26 cm year−1. In contrast to many mangrove environments, the soils of the SMF contain little organic matter and are dominantly composed (>90%) of inorganic clastic sediments. The mineral-rich soil texture likely leads to less compaction-induced subsidence as compared to organic-rich substrates and facilitates surface equilibrium in response to sea level rise. Despite a relatively high soil bulk density, soil carbon (C) density of the SMF is very low owing to the dearth of preserved organic content. However, rates of C accumulation are balanced out by locally high accretion rates, rendering the SMF a greater sink of terrestrial C than the worldwide mangrove average. The findings of this study demonstrate that C accumulation in the SMF, and possibly other alluvial mangrove forests, is highly dependent on the continued delivery of sediment to the mangrove platform and associated settings.

Process Controls of the Live Root Zone and Carbon Sequestration Capacity of the Sundarbans Mangrove Forest, Bangladesh

The conservation of coastal wetland ecosystems, like mangrove forests and salt marshes, represents a critical strategy for mitigating atmospheric emissions and climate change in the 21st century. Yet the existence of these environments is threatened by human-induced disturbances, namely deforestation and accelerated sea-level rise. Coastal systems maintain surface elevation in response to sea-level rise through a combination of physical and biological processes both above and below the ground surface. The quantification and relative contribution of belowground process controls (e.g., seasonal water content, organic matter decomposition) on surface elevation change is largely unexplored but crucial for informing coastal ecosystem sustainability. To address this knowledge deficit, we integrated measurements of surface elevation change of the live root zone (0.5 to 1 m depth) with geotechnical data from co-located sediment cores in the Sundarbans mangrove forest (SMF) of southwest Bangladesh. Core data reveal that the primary belowground controls on surface elevation change include seasonal fluctuations in pore-water content and the relative abundance of fine-grained sediments capable of volumetric expansion and contraction, supporting an elevation gain of ~2.42 ± 0.26 cm yr−1. In contrast to many mangrove environments, the soils of the SMF contain little organic matter and are dominantly composed (>90%) of inorganic clastic sediments. The mineral-rich soil texture likely leads to less compaction-induced subsidence as compared to organic-rich substrates and facilitates surface equilibrium in response to sea level rise. Despite a relatively high soil bulk density, soil carbon (C) density of the SMF is very low owing to the dearth of preserved organic content. However, rates of C accumulation are balanced out by locally high accretion rates, rendering the SMF a greater sink of terrestrial C than the worldwide mangrove average. The findings of this study demonstrate that C accumulation in the SMF, and possibly other alluvial mangrove forests, is highly dependent on the continued delivery of sediment to the mangrove platform and associated settings.

A Multi-Index Evaluation of Drought Characteristics in the Yarlung Zangbo River Basin of Tibetan Plateau, Southwest China

The Yarlung Zangbo River (YZR) basin occupies a crucial position in the formation and development of atmospheric circulation and climate change in the Tibetan Plateau, where is the potential trigger and amplifier in global climate fluctuations. Previous studies mainly focused on meteorological drought induced by variations of precipitation and temperature. In this study, a multi-index evaluation of drought characteristics from the perspective of meteorology and agriculture was implemented. GLDAS (Global Land Data Assimilation System) precipitation, surface air temperature and soil moisture data from 1982 to 2015 were used to calculate the meteorological drought index (Standardized Precipitation Evapotranspiration Index) and agricultural drought index (Soil Water Deficit Index), respectively. Meanwhile, the scPDSI (self-calibrating Palmer Drought Severity Index) dataset provided by CRU (Climate Research Unit) was also utilized to represent the meteorological drought, with the aim of comprehensively investigating the spatiotemporal evolution characteristics of drought in the YZR basin. Results indicated that although there was a slightly wetting tendency of the whole basin from 1982 to 2015, drought condition from the perspective of meteorology and agriculture at both annual and growing seasonal scales showed a transition from alleviation to aggravation during 1982–2015, with an abrupt change from wetting to drying occurring at the year of 2000 detected by multiple statistical tests including Mann-Kendall test, Moving t-test and Yamamoto test. Specifically, since the 21st century, the meteorological drought in the YZR basin has changed from moderate wet to moderate dry, while the agricultural drought relieved to moderate dry from severe dry with a much more complicated fluctuation. From the perspective of spatial pattern, the annual and growing season variation trends of all three drought indices were identically consistent during 1982–2015. Areas with extremely significant decreasing trend (2.24%~21.09%) were mostly distributed in the west upstream and southwest downstream dominating the overall wetting trend of the YZR basin during the period of 1982–2015, while the transition from wet to dry after 2000 was attributed to the aggravating drought of the western upstream and southeastern downstream. Results of this study have important implications for drought monitoring and eco-environmental sustainability in alpine regions.

A multi-year and high-resolution inventory of biomass burning emissions in tropical continents from 2001–2017 based on satellite observations

Biomass burning in the tropics significantly impacts the regional and global atmospheric budget, climate change, and air pollution. This study developed a multi-year (2001–2017), high-resolution (0.1° × 0.1°), monthly biomass burning emissions inventory covering all land types in tropical continents (Americas, Africa, and Asia). The emissions inventory was based on the updated MCD64A1 burned area product, MODIS fire radiative power (FRP) data, satellite and observational data of aboveground biomass density, spatiotemporal variable combustion efficiency, a conversion ratio, and emission factors. The results showed that the average annual emissions in tropical continents for 2001–2017 were 1.73 Tg BC, 10.85 Tg CH4, 261.41 Tg CO, 6083.69 Tg CO2, 3.60 Tg NH3, 39.75 Tg NMOC, 11.99 Tg NOx, 18.40 Tg OC, 29.63 Tg PM2.5, and 2.19 Tg SO2. Taking CO2 as an example, woody savanna/shrubland fire was the largest contributor, accounting for 52% (3.16 × 103 Tg a−1) of total CO2 emissions, followed by fires in savanna/grassland (27%), forest (17%), cropland (3%), and peatland (1%). Africa was the largest emitter (3.77 × 103 Tg a−1), larger than Asia (1.20 × 103 Tg a−1) and the Americas (1.11 × 103 Tg a−1). The dominant fire types of vegetation burning were savanna/grassland in the Americas, woody savanna/shrubland in Africa, and forest in Asia. Moreover, biomass burning CO2 emissions exhibited considerable interannual variations, with high values in 2004, 2007, 2010, and 2015. Extensive savanna/grassland burning in the Americas in September and woody savanna/shrubland fires in Africa in August jointly led to peak CO2 emissions in August–September. This multi-year and high-resolution inventory for biomass burning emissions could be used in studies on global and regional biogeochemical circulation, atmospheric simulation, and air quality modeling.

The Paris agreement on Global Climate change cannot be fully enforced, because this is an incomplete agreement

In 2007, billionaire Richard Branson launched a contest with a prize of $ 25 million to choose a feasible solution to protect the Earth’s atmosphere and combat global climate change [1].The contest lasts 5 years, divided into 2 phase, the first phase from 2007 to 2010. By the end of 2010 the organizers will conduct a preliminary review, if a winner is found, the competition is considered to be over. But in fact after the first round, no winners, so the organizers had to conduct phase 2 from 2010 to 2012 to finish. What a pity after 5 years with the participation of millions of scientists, scientific collectives, all over the world, without finding a winner.

Process Controls of the Live Root Zone and Carbon Sequestration Capacity of the Sundarbans Mangrove Forest, Bangladesh

The conservation of coastal wetland ecosystems, like mangrove forests and salt marshes, represents a critical strategy for mitigating atmospheric emissions and climate change in the 21st century. Yet the existence of these environments is threatened by human-induced disturbances, namely deforestation and accelerated sea-level rise. Coastal systems maintain surface elevation in response to sea-level rise through a combination of physical and biological processes both above and below the ground surface. The quantification and relative contribution of belowground process controls (e.g., seasonal water content, organic matter decomposition) on surface elevation change is largely unexplored but crucial for informing coastal ecosystem sustainability. To address this knowledge deficit, we integrated measurements of surface elevation change of the live root zone (0.5 to 1 m depth) with geotechnical data from co-located sediment cores in the Sundarbans mangrove forest (SMF) of southwest Bangladesh. Core data reveal that the primary belowground controls on surface elevation change include seasonal fluctuations in pore-water content and the relative abundance of fine-grained sediments capable of volumetric expansion and contraction. In contrast to many mangrove environments, the soils of the SMF contain little organic matter and are dominantly composed (>90%) of inorganic clastic sediments. The mineral-rich soil texture likely leads to less compaction-induced subsidence as compared to organic-rich substrates and facilitates surface equilibrium in response to sea level rise. Despite a relatively high soil bulk density, soil carbon (C) density of the SMF is very low owing to the dearth of preserved organic content. However, rates of C accumulation are balanced out by locally high accretion rates, rendering the SMF a greater sink of terrestrial C than the worldwide mangrove average. The findings of this study demonstrate that C accumulation in the SMF, and possibly other alluvial mangrove forests, is highly dependent on the continued delivery of sediment to the mangrove platform and associated settings.

Detecting Trace Gases at Ppm Levels with Low Temperature Plasma Optical Emission Spectroscopy

The detection of trace levels of molecular gases has gained increasing attention in many fields from atmospheric pollution and climate change monitoring to industrial safety and breath analysis for clinical diagnosis. Established techniques e.g. mass spectrometry, gas chromatography, electrochemical offer accuracy but are bulky and expensive. Apart from improving limits of detection (LOD) and increasing the number of target species, there is a major drive towards system miniaturisation and cost reduction in order to enhance field deployment e.g. for rapid continuous environmental monitoring via autonomous distributed networks or point of care clinical breath screening. Tuneable diode laser IR absorption spectroscopy (TLDAS) and atomic emission spectroscopy ICP-AES are routine laboratory spectroscopic techniques where future miniaturisation research includes, for example, microwave, photoacoustic-MEMS, broadband tuneable quantum cascade lasers or supercontinuum IR lasers, high sensitivity nanomaterials, among others. The advent of non-equilibrium low-temperature (NELT) atmospheric pressure plasmas opens up the possibility of using plasma optical emission spectroscopy (OES) for portable and/or low-cost detection in a diverse range of applications. However the poor quality of the spectra from these plasmas requires additional machine learning techniques to develop accurate models based on optical emission training samples. Our original work involving unsupervised principal component analysis indicated significant cluster separation even at sub-ppm levels of e.g. NO impurity gases. Recently we have investigated supervised learning using Partial Least Squares Discriminant Analysis (PLS-DA) using a dataset of He-CH4 spectra where the CH4 concentration varies from 0 – 100 ppm. Methane is a important hydrocarbon gas found in a number of fields from breath analysis to natural gas production and research is ongoing into accurate environmental CH4 detectors in the ppm range.The spectra were obtained from a small RF capillary plasma, 0.7mm in diameter and 5mm long. Spectra were obtained using a Ocean Optics HR4000CG-UV-NIR spectrometer in the wavelength range 194 – 1122 nm (interval 0.25 nm) Data is collected across 3648 variables (wavelengths) with up to 720 samples per dataset, and up to 9 CH4 concentration categories (0 to 100 ppm). Spectral features corresponding to He, hydrogen, carbon-related and impurities (N2, O2, OH/H2O) were observed. No peak can be assigned unambiguously to any particular species. The dominant peaks for 100% He (587.95nm, 707.08nm) varied by ~26% (std. dev). On introduction of CH4, their intensity remained constant (within 1 std. dev) up to ~23 ppm, falling thereafter. In these small atmospheric plasmas, the gas temperature remains cold and hydrocarbon fragmentation is thought to be minimal. Minor peaks indicative of possible CH and C2 fragments were observed but mainly at the higher concentrations. Atomic hydrogen is a possible CH4 fragment, although a contribution from H2O impurity fragmentation is also likely. The other impurity peaks, although of low intensity, have been found to play an important role in algorithm recognition.Predictive models were generated using PLS-DA with two general approaches explored, namely (i) 2-class and (ii) 8-class. In the former, for a threshold of 2 ppm CH4, the model accuracy was > 95% with < 10 latent variables (LV). In the 8-class model, the initial accuracy struggled to reach 60%, despite a range of standard pre-processing approaches employed. Our OES spectra represent high dimensionality collinear data with inherent pattern variability, temporal drift and low resolution as a penalty for the simple low-cost construction. This presents a serious challenge to developing robust machine learning algorithms. Variable Importance in Projection (VIP) outputs the relative significance of each wavelength variable to model’s predictive accuracy and provides insight into how algorithms function and their sensitivity to OES features and plasma chemistry. Using VIP-informed wavelength feature selection and peak modification we obtain high predictive accuracy (>90%) for separate training and test session data with a LOD of 1 ppm. Analysis shows that of the 12 most significant peaks, 6 are due to impurity transitions while the three possible CH4 fragment related transitions are noticeable only at high CH4 concentration. While high temperature plasma techniques (e.g. ICP) rely on molecular fragmentation, this is unlikely to occur in NELT plasmas due to the low energy density. We believe instead, the introduction of the target molecule into the plasma impacts on the low energy side of the electron energy distribution function, affecting electron density and temperature, which in turn is visible in the excitation and vibrational/rotational transitions of carrier and impurity gases. The development of more sophisticated machine learning algorithms capable of handling spectral data from greater complexity target mixtures will provide both an insight into and progress in tandem with improved understanding of NELT plasma physics and chemistry parameters. Figure 1

Spatiotemporal Variation in Precipitation during Rainy Season in Beibu Gulf, South China, from 1961 to 2016

The spatiotemporal variation in precipitation is an important part of water cycle change, which is directly associated with the atmospheric environment and climate change. The high-resolution spatiotemporal change of precipitation is still unknown in many areas despite its importance. This study analyzed the spatiotemporal variation in precipitation in Beibu Gulf, South China, during the rainy season (from April to September) in the period of 1961–2016. The precipitation data were collected from 12 national standard rain-gauge observation stations. The spatiotemporal variation in precipitation was evaluated with incidence rate and contribution rate of precipitation. The tendency of variations was analyzed using the Mann–Kendall method. The precipitation in the rainy season contributed 80% to the total annual precipitation. In general, there was an exponential decreasing tendency between the precipitation incidence rate and increased precipitation durations. The corresponding contribution rate showed a downward trend after an initial increase. The precipitation incidence rate decreased with the rising precipitation grades, with a gradual increase in contribution rate. The precipitation incidence rate and contribution rate of 7–9 d durations showed the significant downward trends that passed the 95% level of significance test. The results provide a new understanding of precipitation change in the last five decades, which is valuable for predicting future climate change and extreme weather prevention and mitigation.

A climatology of surface–air temperature difference over the Tibetan Plateau: Results from multi‐source reanalyses

AbstractThe Tibetan Plateau (TP), known as earth's “Third Pole,” influences regional and even global weather and climate systems through its mechanical and thermal‐dynamical forcing. Near‐surface (2 m) air temperature (Ta) and surface (skin) temperature (Ts) are two crucial parameters of land–atmosphere interactions and climate change. Their difference (ΔT = Ts − Ta) determines the heating source over the TP that drives the Asian summer monsoon. This study focuses on climatology, inter‐annual variability, and long‐term trend of ΔT over the TP in the last four decades (1979–2018), based on four latest reanalysis datasets including ERA‐Interim, ERA5, MERRA2, and JRA55, along with observational data. We show that ΔT‐based different datasets display fairly different climatology in terms of seasonality, spatial distribution, and long‐term trend. ΔT exhibits a clear seasonality with negative value in winter and positive ones in summer despite different strengths and timings presented by the reanalyses. Along with global warming, all reanalyses except JRA55 exhibit obvious downwards trends of ΔT in a spatially non‐uniform way. The median ΔT among the four reanalyses features uniform decreases in all seasons, with the most distinct area on the northern TP, as well as the largest and least decreases in autumn and spring, respectively. Further analysis shows that the differences in ΔT are most likely associated with discrepancies in radiation forcing, snow cover, wind speed, and boundary layer height within the reanalyses. The present findings highlight the difficulty for the state‐of‐the‐art reanalyses to represent the climate change over the TP and point to possible factors behind the deficiencies identified.

Repeatability and Reproducibility of Measures of Bovine Methane Emissions Recorded Using a Laser Detector.

Simple SummaryThe collection of phenotypes related to livestock methane emissions is hampered by costly and time-demanding techniques. In the present research, a laser methane detector was used to measure several novel phenotypes, including mean and aggregate of methane records, and mean and number of methane peak records, considering Simmental heifers as a case study. Phenotypes showed satisfactory repeatability and reproducibility for log-transformed data. The number of emission peaks had great variability across animals and thus it is a promising candidate to discriminate between high and low emitters.Methane (CH4) emissions represent a worldwide problem due to their direct involvement in atmospheric warming and climate change. Ruminants are among the major players in the global scenario of CH4 emissions, and CH4 emissions are a problem for feed efficiency since enteric CH4 is eructed to the detriment of milk and meat production. The collection of CH4 phenotypes at the population level is still hampered by costly and time-demanding techniques. In the present study, a laser methane detector was used to assess repeatability and reproducibility of CH4 phenotypes, including mean and aggregate of CH4 records, slope of the linear equation modelling the aggregate function, and mean and number of CH4 peak records. Five repeated measurements were performed in a commercial farm on three Simmental heifers, and the same protocol was repeated over a period of three days. Methane emission phenotypes expressed as parts per million per linear meter (ppm × m) were not normally distributed and, thus, they were log-transformed to reach normality. Repeatability and reproducibility were calculated as the relative standard deviation of five measurements within the same day and 15 measurements across three days, respectively. All phenotypes showed higher repeatability and reproducibility for log-transformed data compared with data expressed as ppm × m. The linear equation modelling the aggregate function highlighted a very high coefficient of determination (≥0.99), which suggests that daily CH4 emissions might be derived using this approach. The number of CH4 peaks resulted as particularly diverse across animals and therefore it is a potential candidate to discriminate between high and low emitting animals. Results of this study suggest that laser methane detector is a promising tool to measure bovine CH4 emissions in field conditions.

Assessment and Improvement of Global Gridded Sea Surface Temperature Datasets in the Yellow Sea Using In Situ Ocean Buoy and Research Vessel Observations

The sea surface temperature (SST) is essential data for the ocean and atmospheric prediction systems and climate change studies. Five global gridded sea surface temperature products were evaluated with independent in situ SST data of the Yellow Sea (YS) from 2010 to 2013 and the sources of SST error were identified. On average, SST from the gridded optimally interpolated level 4 (L4) datasets had a root mean square difference (RMSD) of less than 1 °C compared to the in situ observation data of the YS. However, the RMSD was relatively high (2.3 °C) in the shallow coastal region in June and July and this RMSD was mostly attributed to the large warm bias (&gt;2 °C). The level 3 (L3) SST data were frequently missing in early summer because of frequent sea fog formation and a strong (&gt;1.2 °C/12 km) spatial temperature gradient across the tidal mixing front in the eastern YS. The missing data were optimally interpolated from the SST observation in offshore warm water and warm biased SST climatology in the region. To fundamentally improve the accuracy of the L4 gridded SST data, it is necessary to increase the number of SST observation data in the tidally well mixed region. As an interim solution to the warm bias in the gridded SST datasets in the eastern YS, the SST climatology for the optimal interpolation can be improved based on long-term in situ observation data. To reduce the warm bias in the gridded SST products, two bias correction methods were suggested and compared. Bias correction methods using a simple analytical function and using climatological observation data reduced the RMSD by 19–29% and 37–49%, respectively, in June.

Effects of an Intrinsic Magnetic Field on Ion Loss From Ancient Mars Based on Multispecies MHD Simulations

AbstractIon loss to space has played an important role in atmospheric escape and climate change on Mars because of intense solar activity during a younger, more active phase of the Sun. Although the existence of an intrinsic magnetic field on ancient Mars is also a key factor in ion loss, its effect remains unclear. Based on multispecies magnetohydrodynamics (MHD) simulations, we investigated processes and rates of ion loss from Mars under extreme solar conditions and the existence of a dipole field with different strengths. The effects of a dipole field on ion loss depend on whether the dipolar magnetic pressure is strong enough to sustain the solar wind dynamic pressure. When the dipole field is existent but weak, it facilitates the cusp outflow and increases the loss rates of molecular ions (O2+ and CO2+) by a factor of 6 through the high‐latitude magnetotail. When the dipole field is strong enough, the loss rates of molecular ions are decreased by 2 orders of magnitude, and peaks of the escape flux are located near the equatorial plane due to the magnetic reconnection in the northern‐dusk or southern‐dawn lobe regions. The pickup process on the extended oxygen corona created by the strong EUV flux contributes to the total O+ loss. Therefore, the effects of the dipole field are less pronounced for O+. Under more moderate solar EUV conditions, the effects on O+ loss can be stronger and thus contribute to climate change.

Net carbon ecosystem exchange during 24 years in the Sorø Beech Forest – relations to phenology and climate

The carbon sequestration of plants through photosynthesis is responsible for removal of a substantial amount of the man-made CO2 emissions to the atmosphere. In recent years this so-called land-sink has removed about 30% of the man-made emissions to the atmosphere, with forests being the most important sinks. The land-sink is, however, vulnerable to changes in the environment, such as the atmospheric composition, climate change, and extreme events like storms and droughts. It is therefore important to study the effects of such change on terrestrial ecosystems to provide the basis for predicting the future of the sink. We here report the results of continuous CO2 flux measurements over a Danish beech forest during the years 1996–2019. Over the years the forest acted as a sink of CO2 with a net carbon sequestration ranging from about zero to 400 g C m–2 yr−1. We found significant trends in net ecosystem exchange (NEE) (increasing in absolute terms with 15 g C m–2 yr2), gross ecosystem exchange (GEE) (increasing with 25 g C m–2 yr–2), and ecosystem respiration (RE) (increasing with 10 g C m–2 yr–2). A prolonged growing season explained 73% of the increase in NEE. The increasing CO2 concentration in the atmosphere and a subsequent increase in photosynthetic capacity together with warming are the most likely main causes of the increased carbon uptake. The severe drought in the summer of 2018 resulted in a reduction of the annual NEE of 25%.

Фотосинтетичні індикатори стану забруднення атмосферного повітря Покутсько-Буковинських Карпат

Досліджено взаємозв'язок стану атмосферного повітря та показників фотосинтетичного апарату представників дендрофлори Покутсько-Буковинських Карпат бука звичайного (Fagus silvatica L.) та тополі пірамідальної (Topulus pyramidalis Moenoh.), що вегетують в умовах різного антропогенного навантаження. Зразки листків відбирали із чотирьох екотопів, що відрізняються рівнем функціонального призначення та забруднення атмосферного повітря. Вивчено вміст хлорофілів та їх співвідношення, а також інтенсивність процесів світлової фази фотосинтезу. Встановлено, що зменшення відносного вмісту хлорофілу "b" в умовах забруднення атмосферного повітря тісно корелює із швидкістю переносу електронів по електрон-транспортному ланцюгу (реакція Хілла). У порівняно чистих, за показниками атмосферного повітря, територіях (заповідній зоні та зоні стаціонарної рекреації національного природного парку) існує тісна позитивна кореляція між вмістом легких негативних аероіонів, нагромадженням зелених пігментів та активністю фотофізичних процесів. Побудовано кореляційну матрицю взаємозалежності показників активності фотосинтетичного апарату рослин та стану атмосферного повітря досліджених територій. Обґрунтовано доцільність використання фотосинтетичних показників дендрофлори заповідної зони об'єктів природоохоронних територій як індикаторів стану екологічної безпеки атмосферного повітря. Результати досліджень опрацьовано статистично.