Atmospheric Carbon Concentrations Research Articles

Atmospheric aerosol optical properties and trends over Antarctica using in-situ measurements and MERRA-2 aerosol products

Columnar aerosol loading and surface level atmospheric black carbon (BC) concentration over the Antarctic are examined using the measurements carried out at the Indian Antarctic stations, Bharati and Maitri, as part of the 36th Indian Scientific Expedition (2016–17) to Antarctica (ISEA). The mean aerosol optical depth (AOD) at wavelength 500 nm at Bharati is observed to be 0.101 ± 0.01, whereas that at Maitri is 0.047 ± 0.003. Columnar aerosol loading at Bharati is found to be more than two times that measured at Maitri. The daily mean surface level atmospheric BC concentration at Bharati in the Austral summer from December 2016 to February 2017 is 24 ± 16.5 ngm−3. Comparison of this measurement with earlier reported values over the same region indicates an increase in surface-level atmospheric BC concentration. Long-term (1997–2017) trend analysis carried out using MERRA-2 aerosol reanalysis data also corroborates the increasing trend in AOD and BC concentration with 0.005 (0.007) yr−1 and 0.3 (0.27) ngm−3 yr−1 over Bharati (Maitri) respectively. Spectral variations of aerosol absorption coefficients show absorption angstrom exponent values (AAE) close to unity (1.096 ± 0.029), which indicates that fossil fuel emission is the primary source of absorbing aerosols over this region. During the study period, air mass back trajectory analysis indicates that the sources are from the Antarctic, coastal, and southern ocean regions with no long-range transport from other continents in the southern hemisphere.

Estimates of Global Forest Fire Carbon Emissions Using FY-3 Active Fires Product

Carbon emissions from forest fires release large amounts of carbon and have important implications for the global and regional carbon cycle and atmospheric carbon concentrations. Considering the significant spatial and temporal variations in different forest fires, this study explores the relationship between different forests and carbon emissions from forest fires. This study developed a high-resolution (0.05° × 0.05°) daily global inventory of carbon emissions from biomass burning during 2016–2022. The inventory estimates of carbon emissions from biomass burning are based on the newly released FY-3 data product, satellite and observational data of biomass density, and spatial and temporal variable combustion factors. Forest fire carbon emissions were assessed using active fire data from FY-3 series satellites from 2016 to 2022, and it was linearly compared with GFED, FEER, and GFAS data on time and spatial scales with R2 of 0.7, 0.73, and 0.69, respectively. The results show spatial patterns of forest cover and carbon emissions, with South America, Africa, South-East Asia, and northern Asia as high-emission zones. The analysis shows an overall upward trend in global forest fire carbon emissions over the study period. Different types of forests exhibited specific emission patterns and temporal variations. For example, most needleleaf forest fires occur in areas with low tree cover, while broadleaf forest fires tend to occur in areas with high tree cover. The study showed that there was a relationship between inter-annual trends in forest fire carbon emissions and land cover, with biomass burning occurring mainly in the range of 60–70% tree cover. However, there were also differences between evergreen broadleaf forest, evergreen needleleaf forest, deciduous broadleaf forest, deciduous needleleaf forest, and mixed forest indicating the importance of considering differences in forest types when estimating emissions. This study identifies the main sources of carbon emissions from forest fires globally, which will help policymakers to take more targeted measures to reduce carbon emissions and provide a reliable basis for appropriate measures and directions in future carbon mitigation actions.

Trends of Atmospheric Black Carbon Concentration over the Bengaluru

This study investigates the spatial and temporal variations of atmospheric black carbon (BC) concentrations in Bangalore, focusing on the period from June 2018 to May 2020. BC mass concentrations were measured using a portable micro-Aethalometer (model: AethLabs AE-51) at seven different locations, representing a range of land use types from rural to urban areas. The study aimed to assess BC pollution levels, identify hotspots, and understand the factors influencing BC concentrations. The results revealed significant variations in BC concentrations among the different locations. The highest BC concentrations were observed in urban traffic and industrial areas, with average concentrations of 6.21 µg/m³ and 6.78 µg/m³, respectively. Urban centres also exhibited high BC levels, with an average concentration of 7.40 µg/m³. In contrast, rural areas recorded the lowest BC concentrations, with an average of 2.51 µg/m³. These findings highlight the influence of anthropogenic activities and land use patterns on BC pollution levels. Diurnal variations in BC concentrations exhibited distinct patterns, with significant peaks during morning and evening hours, primarily associated with increased traffic emissions. The study also identified seasonal trends, with higher BC concentrations observed during winter months, attributed to stable atmospheric conditions and increased fuel consumption for heating purposes. Notably, BC concentrations were generally lower during summer months due to higher wind speeds and increased vertical mixing of pollutants. The findings of this study emphasize the need for targeted mitigation strategies to reduce BC pollution in Bangalore. The identified hotspots, such as urban traffic and industrial areas, require specific attention to mitigate the adverse health and environmental effects of BC emissions. Furthermore, the study underscores the importance of comprehensive air pollution management approaches that consider both local emissions and meteorological factors to effectively tackle BC pollution.

Carbon Capture and Storage: From Global Cycles to Global Solutions

Anthropogenic carbon emissions have overwhelmed the natural carbon cycle, leading to a dramatic increase in atmospheric CO2 concentration. The rate of this increase may be unprecedented in Earth’s history and is leading to a substantial increase in global temperatures, ocean acidification, sea level rise and potentially human health challenges. In this Geochemical Perspectives we review the natural carbon cycle and its link to global climate. Notably, as directly observed by field observations summarised in this volume, there is a natural negative feedback loop between increasing global temperature, continental weathering rates, and CO2 that has tended to limit Earth climate changes over geological time scales. Due to the rapid increase in atmospheric carbon concentrations, global average temperatures have increased by more than 1.2 °C since the start of the industrial revolution. One way to slow or even arrest this increasing global average temperature is through Carbon Capture and Storage (CCS). Carbon dioxide can be captured either from large industrial point sources or directly from the atmosphere. Taking account of the natural carbon cycle, the most secure approach to storing captured CO2 is by reacting it with mafic or ultramafic rocks to form stable carbonate minerals, a process referred to as “mineral carbonation”. Although mineral carbonation can occur and be accelerated at the Earth’s surface, due to the required scale and required time frames it is most effective in the subsurface. This subsurface mineralisation approach was developed into an industrial scale process through an academic-industrial collaboration called CarbFix. The history of CarbFix, from its beginnings as a concept through its installation as an industrial process is presented in detail. This Geochemical Perspectives concludes with an assessment of the future of subsurface mineralisation as a means to help address the global warming challenge, as well as a detailed list of potential research directions that need to be addressed to further upscale and optimise this carbon storage approach.

The Four-Dimensional Carbon Cycle of the Southern Ocean.

The Southern Ocean plays a fundamental role in the global carbon cycle, dominating the oceanic uptake of heat and carbon added by anthropogenic activities and modulating atmospheric carbon concentrations in past, present, and future climates. However, the remote and extreme conditions found there make the Southern Ocean perpetually one of the most difficult places on the planet to observe and to model, resulting in significant and persistent uncertainties in our knowledge of the oceanic carbon cycle there. The flow of carbon in the Southern Ocean is traditionally understood using a zonal mean framework, in which the meridional overturning circulation drives the latitudinal variability observed in both air-sea flux and interior ocean carbon concentration. However, recent advances, based largely on expanded observation and modeling capabilities in the region, reveal the importance of processes acting at smaller scales, including basin-scale zonal asymmetries in mixed-layer depth, mesoscale eddies, and high-frequency atmospheric variability. Assessing the current state of knowledge and remaining gaps emphasizes the need to move beyond the zonal mean picture and embrace a four-dimensional understanding of the carbon cycle in the Southern Ocean.

AN EVALUATION OF THE GANGA RIVER’S CARBON FLOW AND ITS IMPACT ON INDIA’S NUTRITIONAL AND CLIMATE CHANGE

<p>Changes in weather patterns and the global climate are a result of global warming, which has been linked to rising carbon dioxide concentrations. Understanding the mechanisms on earth that have an impact on atmospheric carbon concentrations and its cycling—collectively referred to as the "Carbon cycle"—is essential for estimating carbon budgets. Studies on carbon budgets have largely ignored the role of inland waterways in the carbon cycle, yet rivers play an active role by absorbing/releasing carbon into the atmosphere and transferring dissolved carbon into oceans. In tropical parts of the planet, it is anticipated that water bodies, like as rivers, would contribute to carbon emissions to a greater extent newline Although there are many studies on the impact of human activity on the Ganga River, there are very few that take an ecological viewpoint. In light of these facts, the following was designed as the study's hypothesis: newline The Ganga River has positive feedbacks as a result of human activity, which alters the environment at a level significantly greater than what has previously been projected.The current investigation was conducted in a significant tropical, non-perennial river of the Ganga. In order to calculate the carbon flow of the Ganga river newline, it is important to understand the interaction between geological processes and the concentration of different ions in groundwater and surface water.</p>

Modeling Land Use and Climate Change Effects on Soil Organic Carbon Storage under Different Plantation Systems in Mizoram, Northeast India

Soil carbon sequestration is vital to reduce the atmospheric carbon concentration, which is expected to increase within future climatic scenarios. The present study aims to investigate the effects of land use changes to different plantation systems on SOC stocks, and simulate these changes using the RothC model in Mizoram, India. With this aim, four land uses, viz., secondary forest, oil palm, orange, and arecanut plantations, established on degraded shifting cultivation lands, and a control natural forest were selected for this study. The soils were sampled 0–30 cm in the secondary forest, plantations, and the natural forest, at an interval of five years. Measured SOC stocks were the highest in the secondary forest (67.0 Mg C ha−1) and the lowest under the oil palm plantation (37.4 Mg C ha−1), 10 years after land use conversion. The climate change projections for 2021–2035 and 2036–2050 indicated that temperature and rainfall changes, projected to increase by 0.8 and 2.0 °C, and 5.9 and 5.4%, respectively, will affect SOC stocks in the future differently, depending on the land use and carbon input from vegetation. Baseline climate simulations under land use change showed the highest increase in the SOC stock under the secondary forest (116%), and the lowest in the oil palm plantation (27%). Overall, the model predicted that SOC stocks would increase, but the rate of change (0.23–1.86 Mg C ha−1 yr−1) varied with different land uses, plant species, and land management practices. The model results indicated that restoring secondary forest following the abandonment of a shifting cultivation and orange plantations are the best options to improve SOC stocks within future climate change scenarios. Conversely, arecanut and oil palm need to be reduced because the SOC storage is lower.

Using Orbiting Carbon Observatory-2 (OCO-2) column CO2 retrievals to rapidly detect and estimate biospheric surface carbon flux anomalies

Abstract. The global carbon cycle is experiencing continued perturbations via increases in atmospheric carbon concentrations, which are partly reduced by terrestrial biosphere and ocean carbon uptake. Greenhouse gas satellites have been shown to be useful in retrieving atmospheric carbon concentrations and observing surface and atmospheric CO2 seasonal-to-interannual variations. However, limited attention has been placed on using satellite column CO2 retrievals to evaluate surface CO2 fluxes from the terrestrial biosphere without advanced inversion models at low latency. Such applications could be useful to monitor, in near real time, biosphere carbon fluxes during climatic anomalies like drought, heatwaves, and floods, before more complex terrestrial biosphere model outputs and/or advanced inversion modelling estimates become available. Here, we explore the ability of Orbiting Carbon Observatory-2 (OCO-2) column-averaged dry air CO2 (XCO2) retrievals to directly detect and estimate terrestrial biosphere CO2 flux anomalies using a simple mass-balance approach. An initial global analysis of surface–atmospheric CO2 coupling and transport conditions reveals that the western US, among a handful of other regions, is a feasible candidate for using XCO2 for detecting terrestrial biosphere CO2 flux anomalies. Using the CarbonTracker model reanalysis as a test bed, we first demonstrate that a well-established mass-balance approach can estimate monthly surface CO2 flux anomalies from XCO2 enhancements in the western United States. The method is optimal when the study domain is spatially extensive enough to account for atmospheric mixing and has favorable advection conditions with contributions primarily from one background region. We find that errors in individual soundings reduce the ability of OCO-2 XCO2 to estimate more frequent, smaller surface CO2 flux anomalies. However, we find that OCO-2 XCO2 can often detect and estimate large surface flux anomalies that leave an imprint on the atmospheric CO2 concentration anomalies beyond the retrieval error/uncertainty associated with the observations. OCO-2 can thus be useful for low-latency monitoring of the monthly timing and magnitude of extreme regional terrestrial biosphere carbon anomalies.

Assessment of the Spatial Structure of Black Carbon Concentrations in the Near-Surface Arctic Atmosphere

The results of the research are numerical estimates of the average fields of black carbon mass concentration in the surface layer of the atmosphere of the Arctic region obtained using the numeric technology referred to as fluid location of the atmosphere (FLA). The modelling has been based on measurements of the black carbon concentrations in the near-surface atmosphere obtained during the two cruises of the Professor Multanovskiy (28 July–7 September 2019) and Akademik Mstislav Keldysh (31 July–24 August 2020) research vessels. These measurements have been supplemented by measurements at stationary monitoring points located on the Spitsbergen and the Severnaya Zemlya archipelagoes. The simulation in the summertime demonstrates that areas of increased black carbon concentrations were observed over Northern Europe and, in 2019, also over the Laptev Sea basin. The obtained spatial distribution of mass concentrations of black carbon qualitatively agreed with the same data derived from the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) but showed quantitative differences. The average values of mass concentrations of black carbon in the modelling zones are as follows: 85.3 ng/m3 (2019) and 53.6 ng/m3 (2020) for fields reconstructed by the FLA technology; and 261.69 ng/m3 (2019) and 131.8 ng/m3 (2020) for the MERRA-2 data.

Quantifying mineral-associated organic matter in wetlands as an indicator of the degree of soil carbon protection

As atmospheric carbon (C) concentrations increase, so too has interest in understanding the mechanisms that preserve C within the soil organic matter (SOM). Mineral-associated organic matter (MAOM) is one pool of SOM recently shown to protect soil organic C from mineralization. However, most MAOM research has been in agriculture and forest mineral soils. Given the magnitude of soil C stored in wetlands, this study sought to determine the abundance of MAOM in wetlands. A standard method for quantifying MAOM in terrestrial soils was tested, modified, and optimized with three unique wetland soils. Using a physical fractionation method followed by a density fractionation, it was concluded that field moist soils and a dispersant were necessary for fractionating wetland soils (0–50 cm). The Bayhead Swamp soil had the greatest total C (484.07 ± 1.25 mg C g soil -1), but the smallest MAOM pool (0.63 %); most of the C was in the light fraction as particulate organic matter (POM, >98 %). The sandy-peat Cypress Dome soil also lacked MAOM (1.09 %) and was dominated by POM (66.26 %). The silt-rich Brackish Marsh had the least total C (94.37 ± 1.67 mg C g soil -1), but the largest fraction of protected C (24.60 % MAOM). Nitrogen (N) followed similar trends to C, except in the Brackish Marsh where nearly half the total N was MAOM. This research represents the first step in evaluating the role of MAOM in C persistence in organic-rich wetland soils; future work should consider C physical fraction, in addition to C quantity.

Nearly five-year continuous atmospheric measurements of black carbon over a suburban area in central France

Atmospheric black carbon (BC) concentration over a nearly 5 year period (mid-2017–2021) was continuously monitored over a suburban area of Orléans city (France). Annual mean atmospheric BC concentration were 0.75 ± 0.65, 0.58 ± 0.44, 0.54 ± 0.64, 0.48 ± 0.46 and 0.50 ± 0.72 μg m−3, respectively, for the year of 2017, 2018, 2019, 2020 and 2021. Seasonal pattern was also observed with maximum concentration (0.70 ± 0.18 μg m−3) in winter and minimum concentration (0.38 ± 0.04 μg m−3) in summer. We found a different diurnal pattern between cold (winter and fall) and warm (spring and summer) seasons. Further, fossil fuel burning contributed >90 % of atmospheric BC in the summer and biomass burning had a contribution equivalent to that of the fossil fuel in the winter. Significant week days effect on BC concentrations was observed, indicating the important role of local emissions such as car exhaust in BC level at this site. The behavior of atmospheric BC level with COVID-19 lockdown was also analyzed. We found that during the lockdown in warm season (first lockdown: 27 March–10 May 2020 and third lockdown 17 March–3 May 2021) BC concentration were lower than in cold season (second lockdown: 29 October–15 December 2020), which could be mainly related to the BC emission from biomass burning for heating. This study provides a long-term BC measurement database input for air quality and climate models. The analysis of especially weekend and lockdown effect showed implications on future policymaking toward improving local and regional air quality as well.

Implementation and initial calibration of carbon-13 soil organic matter decomposition in the Yasso model

Abstract. Soils account for the largest share of carbon found in terrestrial ecosystems, and their status is of considerable interest for the global carbon cycle budget and atmospheric carbon concentration. The decomposition of soil organic matter depends on environmental conditions and human activities, which raises the question of how permanent are these carbon storages under changing climate. One way to get insight into carbon decomposition processes is to analyse different carbon isotope concentrations in soil organic matter. In this paper we introduce a carbon-13-isotope-specific soil organic matter decomposition add-on into the Yasso soil carbon model and assess its functionality. The new 13C-dedicated decomposition is straightforward to implement and depends linearly on the default Yasso model parameters and the relative carbon isotope (13C/12C) concentration. The model modifications are based on the assumption that the heavier 13C atoms are not as reactive as 12C. The new formulations were calibrated using fractionated C, 13C and δ13 measurements from litterbags containing pine needles and woody material, which were left to decompose in natural environment for 4 years. The introduced model modifications considerably improve the model behaviour in a 100-year-long simulation, where modelled δ13 is compared against fractionated peat column carbon content. The work presented here is a proof of concept and enables 13C to be used as a natural tracer to detect changes in the underlying soil organic matter decomposition.

Conserving biodiversity in the face of rapid climate change requires a shift in priorities

AbstractThe field of conservation aims to protect biodiversity—the diversity of life on earth in all its forms. Traditional conservation objectives and measures have already been expanded and modified in response to shifting social values and climate‐related challenges. As climate change progresses, we argue that these changes will need to be accelerated. First, an even greater fraction of conservation objectives will need to prioritize the basic well‐being of humans, especially in areas where humans are strongly dependent on their natural surroundings. For example, urban biodiversity and low‐impact forms of agriculture and forestry that reconcile biodiversity and contributions to humans should increasingly be viewed as compatible with conservation objectives. Second, more conservation measures will need to allow for, and even foster, changes in biodiversity. Indeed, changing species' characteristics and biotic community composition are not only adaptive responses to inevitable climate change but will, in many instances, also be necessary to maintain functioning ecosystems. Conversely, attempts to maintain biodiversity in a historical state will likely become increasingly difficult, expensive, and possibly counterproductive. Finally, in addition to continuing climate adaptation work, conservation efforts will need to focus more on reducing atmospheric carbon concentrations. We explore how collectively these changes are transforming the field of conservation and how they have the potential to lead to a more just and sustainable world despite impending climate change.This article is categorized under: Climate, Ecology, and Conservation > Conservation Strategies Climate, Nature, and Ethics > Comparative Environmental Values Climate and Development > Sustainability and Human Well‐Being

Decrease of atmospheric black carbon and CO2 concentrations due to COVID-19 lockdown at the Mt. Waliguan WMO/GAW baseline station in China

The Coronavirus Disease 2019 (COVID-19) lockdown policy reduced anthropogenic emissions and impacted the atmospheric chemical characteristics in Chinese urban cities. However, rare studies were conducted at the high mountain site. In this work, in-situ measurements of light absorption by carbonaceous aerosols and carbon dioxide (CO2) concentrations were conducted at Waliguan (WLG) over the northeastern Tibetan Plateau of China from January 3 to March 30, 2020. The data was employed to explore the influence of the COVID-19 lockdown on atmospheric chemistry in the background-free troposphere. During the sampling period, the light absorption near-infrared (>470 nm) was mainly contributed by BC (>72%), however, BC and brown carbon (BrC) contributed equally to light absorption in the short wavelength (∼350 nm). The average BC concentrations in the pre-, during and post-lockdown were 0.28 ± 0.25, 0.18 ± 0.16, and 0.28 ± 0.20 μg m−3, respectively, which decreased by approximately 35% during the lockdown period. Meanwhile, CO2 also showed slight decreases during the lockdown period. The declined BC was profoundly attributed to the reduced emissions (∼86%), especially for the combustion of fossil fuels. Moreover, the declined light absorption of BC, primary and secondary BrC decreased the solar energy absorbance by 35, 15, and 14%, respectively. The concentration weighted trajectories (CWT) analysis suggested that the decreased BC and CO2 at WLG were exclusively associated with the emission reduction in the eastern region of WLG. Our results highlighted that the reduced anthropogenic emissions attributed to the lockdown in the urban cities did impact the atmospheric chemistry in the free troposphere of the Tibetan Plateau.

Overestimation of prokaryotic production by leucine incorporation—and how to avoid it

AbstractProkaryotes play a central role in aquatic ecosystems by consuming approximately half of the organic matter produced by aquatic primary production, of which a fraction is used for growth. Accurately measuring this prokaryotic biomass production is key to understanding aquatic carbon and nutrient cycles, since it is instrumental in driving biogeochemical processes that control parameters such as atmospheric carbon content. Aquatic prokaryotic biomass production is typically estimated from incorporation rates of the amino acid leucine during radiotracer experiments—a method widely used since the 1980s. Here we evaluate the underlying assumptions of the method with a focus on the associated conversion factors and review them in the context of empirical data. We demonstrate that the commonly used theoretical conversion factors fail to account for leucine's use as precursor for de novo protein synthesis and its respiration. As a consequence, prokaryotic biomass production is likely considerably overestimated when applying the standard conversion factors. Most severely affected are open‐ocean, mesopelagic and benthic environments, where 25% of the estimates are likely to be overestimated by at least a factor of 6.1, 4.9, and 6.5, respectively. We propose a refined carbon‐to‐leucine conversion factor and make recommendations for improving and selecting appropriate experimental protocols.

Magnifying Focusing Events: Global Smoke Plumes and International Construal Connections in Newspaper Coverage of 2020 Wildfire Events

As climate policy focusing events, wildfires are distinct from hurricanes, floods, and tornados because they also result in the release of massive smoke plumes that contribute to the concentration of atmospheric carbon. However, unlike melting glaciers, wildfires may be easier to dismiss as individual acts of human error, spontaneous acts of mother nature, and/or necessary ecological processes of agricultural renewal. This paper presents a mixed-methods analysis of 150 international and domestic English language newspaper articles related to wildfire events occurring in Australia, Canada, Germany, Greece, Italy, Spain, the United Kingdom, and the United States during the year 2020. The analysis examines how news coverage of wildfire events might focus or diffuse attention to international climate policy and anthropogenic global warming. The quantitative findings provide evidence to suggest that 30% of wildfire coverage is attributed to climate change. However, qualitative analysis suggests that climate change is acknowledged as a blame frame that is often only inferentially attributed to anthropogenic origins. The mixed-methods analysis finds that only 6% of news coverage related wildfire events to emission contributions. The analysis of these exemplar articles suggests that the international travel of wildfire smoke may serve as a focusing event from which to emphasize wildfires as both a consequence of and contributor to, global warming. Findings indicate that environmental coalitions and scientific experts’ engagement with the press are integral to creating frames that link the increasing frequency, duration, and range of wildfire events to climate policy needs.

A slight increase in soil pH benefits soil organic carbon and nitrogen storage in a semi-arid grassland

Grassland soil organic carbon and nitrogen storage (SOC storage and SNC storage) have been regarded as indicators to evaluate impacts of global climate change on ecosystem functions due to their significant impact on atmospheric carbon (C) concentration. The variations in vegetation and soil properties in diverse vegetation patch types may change soil C and nitrogen (N) sequestration capacity. However, the quantities of SOC and SNC stored and the mechanisms behind the variation in this storage under diverse vegetation patches in grassland ecosystems are still unclear. Here we conducted a field experiment to measure the variations in vegetation composition, soil properties and SOC storage and SNC storage among five common vegetation patch types in the Eastern Eurasian steppe. Then we investigated the link between vegetation variation and the SOC and SNC storage. The results showed that (1) the combined effects of competitive ability and physiological stress drove the unimodal relationship between species diversity and soil pH. (2) Biomass production did not reach its maximum in patch types with the greatest plant diversity due to saline-alkaline stress, but the live vegetation N storage reached its maximum in these highly diverse patches due to complementary resource utilization effects. (3) Although biomass production of patches with the greatest biodiversity did not reach a maximum due to a slight increase in soil pH, the largest SOC and SNC storage values were found in the highly diverse patches. Our study implies that in natural grassland, high levels of species diversity may accelerate the decomposition rate, resulting in more recalcitrant organic C and N are released into the soil. At the same time, our observation that reductions in the area of the originally dominant patch type due to the expansion of other species during grassland degradation suggests that comprehensive measurements of SOC and SNC storage in different vegetation patches should be undertaken for accurate evaluation of the C and N sequestering capacity of grasslands. Our results can also help policy makers determine how to achieve sustainable development of grasslands based on C and N sequestration.

Direct and Inverse Reduced-Form Models for Reciprocal Calculation of BC Emissions and Atmospheric Concentrations.

Atmospheric black carbon (BC) concentrations are governed by both emissions and meteorological conditions. Distinguishing these effects enables quantification of the effectiveness of emission mitigation actions by excluding meteorological effects. Here, we develop reduced-form models in both direct (RFDMs) and inverse (RFIMs) modes to estimate ambient BC concentrations. The models were developed based on outputs from multiyear simulations under three conditional scenarios with realistic or fixed emissions and meteorological conditions. We established a set of probabilistic functions (PFs) to quantify the meteorological influences. A significant two-way linear relationship between multiyear annual emissions and mean ambient BC concentrations was revealed at the grid cell scale. The correlation between them was more significant at grid cells with high emission densities. The concentrations and emissions at a given grid cell are also significantly correlated with emissions and concentrations of the surrounding areas, respectively, although to a lesser extent. These dependences are anisotropic depending on the prevailing winds and source regions. The meteorologically induced variation at the monthly scale was significantly higher than that at the annual scale. Of the major meteorological parameters, wind vectors, temperature, and relative humidity were found to most significantly affect variation in ambient BC concentrations.

Changes and Potential Sources of Atmospheric Black Carbon Concentration in Shanghai over the Past 40 Years Based on MERRA-2 Reanalysis Data

As an important component of atmospheric aerosols, black carbon (BC) has a great influence on the regional and global radiation balance, climate, and human health due to its small particle size, large specific surface area, and radiative forcing potential. Here, the spatio-temporal characteristics of atmospheric BC were investigated based on modern-era retrospective analysis for research and applications version 2 (MERRA-2) reanalysis data and ground observation data during 1980-2019 in Shanghai, a highly urbanized city in mainland China. The influences of local emissions and regional transmission on regional-scale BC concentrations were examined using the M-K trend test, backward trajectory analysis, and the potential source contribution function (PSCF). The results showed that:① MERRA-2 BC and ground observation datasets showed good consistency (R∈[0.68, 0.72]), indicating that MERRA-2 reanalysis data can be used to reveal long-term changes in ground-level atmospheric BC concentrations; ② Atmospheric BC concentrations in Shanghai over the past 40 years can be divided into three stages:a "low value" stage of slow growth[1980-1986, (1.75±0.17) μg·m-3], a relatively stable "median value" stage[1987-1999, (2.18 ±0.07) μg·m-3], and a fluctuating "high value" stage[2000-2019, (3.07±0.31) μg·m-3]. Seasonally, Shanghai's BC concentrations generally show a "U" pattern with low concentrations in summer and high concentrations in winter. As a result of black carbon emissions from marine diesel engines and other engines used for water transportation, a small peak also occurs in July; ③ The diagnostic quality ratio of air pollutants and the bivariate correlation analysis[R(BC-NO2)>R(BC-CO)>R(BC-SO2)] indicated that traffic emissions were the main sources of atmospheric BC in Shanghai, especially by heavy diesel vehicles; ④ The backward trajectory and PSCF analyses found that the air mass of Shanghai in summer was dominated by a clean sea breeze, accounting for 77.18%. In contrast, during the other seasons, more than 50% of the air mass came from the north. The potential source regions of atmospheric BC in Shanghai are mainly distributed in eastern China, expanding outwards and centering on the Yangtze River Delta, and the expansion direction is consistent with the directions of the backward trajectories.

A climate sensitive mixed-effects diameter class mortality model for Prince Rupprecht larch (Larix gmelinii var. principis-rupprechtii) in northern China

Forest mortality is an important variable commonly included as one of the predictors in the growth and yield models that are the fundamental decision-making tools in forest management. The existing forest mortality models for Larch (Larix gmelinii var. principis-rupprechtii) forest, which plays key roles in maintaining forest ecosystem functions and reducing atmospheric carbon concentration through the sequestration, are based on the traditional modeling methods, and these models do not account for the effects of climate on the forest mortality. Developing climate sensitive mortality models are useful for formulating effective forest management strategies in the context of climate change. We developed the diameter class mortality models using the data of 102 temporary sample plots distributed across the Guandi Mountain National Forest Park and Wutai Mountain Boqiang State-owned Forest Farm in the Shanxi Province of northern China. Four commonly used mortality functions were used to fit the data. Among many climatic and dendrometric variables evaluated, number of trees per diameter class (NC), mean annual precipitation (MAP); median diameter class (MDC), and mean temperature difference (DT) contributed significantly highly to the mortality variations. Then, these variables were selected as predictors to develop the two-level nonlinear mixed-effects mortality models applicable to the diameter class levels. The random effects at the levels of both the sample plots and stands with different site quality (blocks) were taken into account to build the models. Compared to other three models derived from the Poisson; Zero-inflated Poisson; Hurdle Poisson functions, the two-level Logistic mixed-effects mortality model better explained the effects of climate variables on the forest mortality of Larch. Tree mortality increased with increasing NC and MAP, however, MDC and DT had the opposite effects with diameter class increasing. Modeling the random effects at the block-level alone led to significantly high correlations among the residuals, and correlations were significantly reduced when the random effects were modeled at both the block- and sample plot-levels. Excessive rain during the growing season decreased the rate of tree mortality, especially for diameter classes with high number of trees. Findings from this study can be combined with the knowledge of the adaptive management to reduce the risks and uncertainties associated with forest management decision.