Nitrous Oxide Emission Fluxes in Coffee Plantations during Fertilization: A Case Study in Costa Rica

The main source of N2O emissions is agriculture, and coffee monocultures have become an important part of these emissions. The demand for coffee has increased in the last five decades. Thus, its production in agricultural fields and the excess of fertilizers have increased. This study quantified N2O emissions from different dose applications and types of nitrogen fertilizer in a region of major coffee production in Costa Rica. A specific methodology to measure N2O fluxes from coffee plants was developed using Fourier-transform infrared spectroscopy (FTIR). Measurements were performed in a botanical garden in Germany and plots in Costa Rica, analyzing the behavior of a fertilizer in two varieties of coffee (Catuai and Geisha), and in a field experiment, testing two types of fertilizers (chemical (F1) and physical mixture (F2)) and compost (SA). As a result, the additions of synthetic fertilizer increased the N2O fluxes. F2 showed higher emissions than F1 by up to 90% in the field experiment, and an increase in general emissions occurred after a rain event in the coffee plantation. The weak levels of N2O emissions were caused by a rainfall deficit, maintaining low water content in the soil. Robust research is suggested for the inventories.

Supplemental Material: Contemporary and future dust sources and emission fluxes from gypsum- and quartz-dominated eolian systems, New Mexico and Texas, USA

Methods and Tables S1–S3.<br>

Towards an improved representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model RegCM4.6

Mitigation of carbonaceous aerosol emissions is expected to provide climate and health co-benefits. The accurate representation of carbonaceous aerosols in climate models is critical for reducing uncertainties in their climate feedbacks. In this regard, emission fluxes and aerosol life-cycle processes are the two primary sources of uncertainties. Here we demonstrate that incorporating a dynamic ageing scheme and emission estimates that are updated for the local sources improve the representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model, RegCM, compared to its default configuration. The mean BC and OC surface concentrations in 2010 are estimated to be 4.25 and 10.35 μg m−3, respectively, over the Indo-Gangetic Plain (IGP), in the augmented model. The BC column burden over the polluted IGP is found to be 2.47 mg m−2, 69.95 % higher than in the default model configuration and much closer to available observations. The anthropogenic AOD increases by more than 19 % over the IGP due to the model enhancement, also leading to a better agreement with observed AOD. The top-of-the-atmosphere, surface, and atmospheric anthropogenic aerosol shortwave radiative forcing are estimated at −0.3, −9.3, and 9.0 W m−2, respectively, over the IGP and −0.89, −5.33, and 4.44 W m−2, respectively, over Peninsular India. Our results suggest that both the accurate estimates of emission fluxes and a better representation of aerosol processes are required to improve the aerosol life cycle representation in the climate model.

Greenhouse gas emission fluxes from peat bogs in the Arak Lake Basin in 2021

Climate change has an important impact on greenhouse gas emissions from wetland ecosystems. The static box-meteorological chromatography method was used to determine the CO2 and CH4 emission fluxes of hummocky and hollow in the peat bogs in the Arak Lake Basin during the growing season in 2021. The results showed that the peaks of the CO2 and CH4 emission fluxes in the growing seasons of the hummocky and hollow appeared in July, and their value in May is the lowest. The average C02 emission flux (376.39±56.14 mg-m-2-h-1) during the growing season of hummocky is higher than that of hollow (167.36 mg-m-2-h-1), while the average emission flux of CH4 during the growing season of hummocky (2.00±0.31 mg-m-2-h-1) is lower than that of hollow (3.04 mg-m-2-h-1). The climatic fluctuations have caused differences in the CO2 and CH4 emission fluxes of the same micro-topography in the study area during the growing season between 2020 and 2021.

Dominance of the residential sector in Chinese black carbon emissions as identified from downwind atmospheric observations during the COVID-19 pandemic

Emissions of black carbon (BC) particles from anthropogenic and natural sources contribute to climate change and human health impacts. Therefore, they need to be accurately quantified to develop an effective mitigation strategy. Although the spread of the emission flux estimates for China have recently narrowed under the constraints of atmospheric observations, consensus has not been reached regarding the dominant emission sector. Here, we quantified the contribution of the residential sector, as 64% (44–82%) in 2019, using the response of the observed atmospheric concentration in the outflowing air during Feb–Mar 2020, with the prevalence of the COVID-19 pandemic and restricted human activities over China. In detail, the BC emission fluxes, estimated after removing effects from meteorological variability, dropped only slightly (− 18%) during Feb–Mar 2020 from the levels in the previous year for selected air masses of Chinese origin, suggesting the contributions from the transport and industry sectors (36%) were smaller than the rest from the residential sector (64%). Carbon monoxide (CO) behaved differently, with larger emission reductions (− 35%) in the period Feb–Mar 2020, suggesting dominance of non-residential (i.e., transport and industry) sectors, which contributed 70% (48–100%) emission during 2019. The estimated BC/CO emission ratio for these sectors will help to further constrain bottom-up emission inventories. We comprehensively provide a clear scientific evidence supporting mitigation policies targeting reduction in residential BC emissions from China by demonstrating the economic feasibility using marginal abatement cost curves.

A tracer release experiment to investigate uncertainties in drone-based emission quantification for methane point sources

Mapping trace gas emission plumes using in-situ measurements from unmanned aerial vehicles (UAV) is an emerging and attractive possibility to quantify emissions from localized sources. Here, we present the results of an extensive tracer-release experiment in Dübendorf, Switzerland, which was conducted to develop an optimal quantification method and to determine the related uncertainties under various environmental and sampling conditions. Atmospheric methane mole fractions were simultaneously measured using a miniaturized fast-response Quantum Cascade Laser Absorption Spectrometer (QCLAS) and an Active AirCore system mounted on a commercial drone. Emission fluxes were estimated using a mass-balance method by flying the drone-based system through a vertical cross-section downwind of the point-source perpendicular to the main wind direction at multiple altitudes. A refined kriging framework, called cluster-based kriging, was developed to spatially map individual methane measurement points into the whole measurement plane, while taking into account the different spatial scales between background and enhanced methane values in the plume. We found that the new kriging framework resulted in better quantification compared to ordinary kriging. The average bias of the estimated emissions was −1 % and the average residual of individual errors was 54 %. Direct comparison of QCLAS and AirCore measurements shows that AirCore measurements are smoothened by 20 s and temporally shifted and stretched by 7 s and 0.06 seconds for every second of QCLAS measurement, respectively. Applying these corrections to the AirCore measurements and successively calculating an emission estimate shows an enhancement of the accuracy by 3 % as compared to its uncorrected counterpart. Optimal plume sampling, including the downwind measurement distance, depends on wind- and turbulence conditions and it is furthermore limited by numerous parameters such as the maximum flight time, and the measurement accuracy. Under favorable measurement conditions, emissions could be quantified with an uncertainty of 30 %. Uncertainties increase when wind speeds are below 2.3 m s−1 and directional variability is above 33°, and when the downwind distance is above 75 m. In addition, the flux estimates were also compared to estimates from the well-established OTM-33A method involving stationary measurements. A good agreement was found, both approaches being close to the true-release and uncertainties of both methods usually capturing the true-release.

Supplemental Material: Contemporary and future dust sources and emission fluxes from gypsum- and quartz-dominated eolian systems, New Mexico and Texas, USA

Methods and Tables S1–S3.<br>

Supplemental Material: Contemporary and future dust sources and emission fluxes from gypsum- and quartz-dominated eolian systems, New Mexico and Texas, USA

Methods and Tables S1–S3.<br>

Estimating aerosol emission from SPEXone on the NASA PACE mission using an ensemble Kalman Smoother: Observing System Simulation Experiments (OSSEs)

We present a top-down approach for aerosol emission estimation from SPEXone polarimetric retrievals related to the aerosol amount, size, and absorption using a fixed-lag ensemble Kalman smoother (LETKS) in combination with the ECHAM-HAM model. We assess the system by performing Observing System Simulation Experiments (OSSEs), in order to evaluate the ability of the future multi-angle polarimeter instrument, SPEXone, as well as a satellite with near perfect global coverage. In our OSSEs, the Nature Run (NAT) is a simulation by the global climate aerosol model ECHAM-HAM with altered aerosol emissions. The Control (CTL) and the data assimilation (DAS) experiments are composed of an ensemble of ECHAM-HAM simulations, where the default aerosol emissions are perturbed with factors taken from a Gaussian distribution. Synthetic observations, specifically Aerosol Optical Depth at 550 nm (AOD550), Angstrom Exponent from 550 nm to 865 nm (AE550-865) and Single Scattering Albedo at 550 nm (SSA550) are assimilated in order to estimate the aerosol emission fluxes of desert dust (DU), sea salt (SS), organic carbon (OC), black carbon (BC) and sulphate (SO4), along with the emission fluxes of two SO4 precursor gases (SO2, DMS). The synthetic observations are sampled from the NAT according to two satellite observing systems, with different spatial coverages. The first is the sensor SPEXone, a hyperspectral multi-angle polarimeter with a narrow swath (~100 km), that will be a part of the NASA PACE mission. The second is an idealized sensor that can retrieve observations over the whole globe even under cloudy conditions. The prior emission global relative Mean Absolute Error (MAE) before the assimilation ranges from 33 % to 117 %. Depending on the species, the assimilated observations sampled using the idealized sensor, reduce this error to equal to or lower than 5 %. Despite its limited coverage, the SPEXone sampling bares similar results, with somewhat larger errors for DU and SS (both having a MAE equal to 11 %). Further, experiments show that doubling the measurement error, increases the global relative MAE to 22 % for DU and SS. The emission estimation of the other species is not affected as much by these changes. In addition, the role of biased meteorology on emission estimation was quantified by using two different datasets (ERA-5 and ERA-interim) to nudge the U and V wind components of the model. The results reveal that when the wind of DAS uses a different reanalysis dataset than the NAT the estimated SS emissions are negatively affected the most, while the estimated emissions of DU, OC, BC and SO2 are negatively affected to a smaller extent. If the DAS uses dust or sea salt emission parametrisations that are very different from the NAT, posterior emissions can still be successfully estimated but this experiment revealed that the source location is important for the estimation of dust emissions. This work suggests that the upcoming SPEXone sensor will provide observations related to aerosol amount, size and absorption with sufficient coverage and accuracy, in order to estimate aerosol emissions.

Quantification and assessment of methane emissions from offshore oil and gas facilities on the Norwegian Continental Shelf

The oil and gas (O&amp;G) sector is a significant source of methane (CH4) emissions. Quantifying these emissions remains challenging, with many studies highlighting discrepancies between measurements and inventory-based estimates. In this study, we present CH4 emission fluxes from 21 offshore O&amp;G facilities collected in 10 O&amp;G fields over two regions of the Norwegian Continental Shelf in 2019. Emissions of CH4 derived from measurements during 13 aircraft surveys were found to range from 2.6 to 1200 t year−1 (with a mean of 211 t year−1 across all 21 facilities). Comparing this with aggregated operator-reported facility emissions for 2019, we found excellent agreement (within 1σ uncertainty), with mean aircraft-measured fluxes 16 % lower than those reported by operators. We also compared aircraft-derived fluxes with facility fluxes extracted from a global gridded fossil fuel CH4 emission inventory compiled for 2016. We found that the measured emissions were 42 % larger than the inventory for the area covered by this study, for the 21 facilities surveyed (in aggregate). We interpret this large discrepancy not to reflect a systematic error in the operator-reported emissions, which agree with measurements, but rather the representivity of the global inventory due to the methodology used to construct it and the fact that the inventory was compiled for 2016 (and thus not representative of emissions in 2019). This highlights the need for timely and up-to-date inventories for use in research and policy. The variable nature of CH4 emissions from individual facilities requires knowledge of facility operational status during measurements for data to be useful in prioritizing targeted emission mitigation solutions. Surveys of individual facilities may always require this. However, for field-aggregated emissions, our results show that an accurate estimate of total field-level emissions simply requires a sufficiently large and representative sample of facilities, to yield meaningful comparisons and flux statistics, irrespective of operational status information. In summary, this study demonstrates the importance and accuracy of detailed, facility-level emission accounting and reporting by operators and the use of measurement approaches to validate bottom-up accounting.