ALBERT

Description: Twenty-nine different fuel types used in residential dwellings in northern India were collected from across Delhi (76 samples in total). Emission factors of a wide range of non-methane volatile organic compounds (NMVOCs) (192 compounds in total) were measured during controlled burning experiments using dual-channel gas chromatography with flame ionisation detection (DC-GC-FID), two-dimensional gas chromatography (GC × GC-FID), proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) and solid-phase extraction two-dimensional gas chromatography with time-of-flight mass spectrometry (SPE-GC × GC–ToF-MS). On average, 94 % speciation of total measured NMVOC emissions was achieved across all fuel types. The largest contributors to emissions from most fuel types were small non-aromatic oxygenated species, phenolics and furanics. The emission factors (in g kg−1) for total gas-phase NMVOCs were fuelwood (18.7, 4.3–96.7), cow dung cake (62.0, 35.3–83.0), crop residue (37.9, 8.9–73.8), charcoal (5.4, 2.4–7.9), sawdust (72.4, 28.6–115.5), municipal solid waste (87.3, 56.6–119.1) and liquefied petroleum gas (5.7, 1.9–9.8). The emission factors measured in this study allow for better characterisation, evaluation and understanding of the air quality impacts of residential solid-fuel combustion in India.

Description: Biomass burning emits significant quantities of intermediate-volatility and semi-volatile organic compounds (I/SVOCs) in a complex mixture, probably containing many thousands of chemical species. These components are significantly more toxic and have poorly understood chemistry compared to volatile organic compounds routinely quantified in ambient air; however, analysis of I/SVOCs presents a difficult analytical challenge. The gases and particles emitted during the test combustion of a range of domestic solid fuels collected from across Delhi were sampled and analysed. Organic aerosol was collected onto Teflon (PTFE) filters, and residual low-volatility gases were adsorbed to the surface of solid-phase extraction (SPE) discs. A new method relying on accelerated solvent extraction (ASE) coupled to comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC × GC–ToF-MS) was developed. This highly sensitive and powerful analytical technique enabled over 3000 peaks from I/SVOC species with unique mass spectra to be detected. A total of 15 %–100 % of gas-phase emissions and 7 %–100 % of particle-phase emissions were characterised. The method was analysed for suitability to make quantitative measurements of I/SVOCs using SPE discs. Analysis of SPE discs indicated phenolic and furanic compounds were important for gas-phase I/SVOC emissions and levoglucosan to the aerosol phase. Gas- and particle-phase emission factors for 21 polycyclic aromatic hydrocarbons (PAHs) were derived, including 16 compounds listed by the US EPA as priority pollutants. Gas-phase emissions were dominated by smaller PAHs. The new emission factors were measured (mg kg−1) for PAHs from combustion of cow dung cake (615), municipal solid waste (1022), crop residue (747), sawdust (1236), fuelwood (247), charcoal (151) and liquefied petroleum gas (56). The results of this study indicate that cow dung cake and municipal solid waste burning are likely to be significant PAH sources, and further study is required to quantify their impact alongside emissions from fuelwood burning.

Description: Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the Boreal–Arctic Wetland and Lake Dataset (BAWLD), a land cover dataset based on an expert assessment, extrapolated using random forest modelling from available spatial datasets of climate, topography, soils, permafrost conditions, vegetation, wetlands, and surface water extents and dynamics. In BAWLD, we estimate the fractional coverage of five wetland, seven lake, and three river classes within 0.5 × 0.5∘ grid cells that cover the northern boreal and tundra biomes (17 % of the global land surface). Land cover classes were defined using criteria that ensured distinct methane emissions among classes, as indicated by a co-developed comprehensive dataset of methane flux observations. In BAWLD, wetlands occupied 3.2 × 106 km2 (14 % of domain) with a 95 % confidence interval between 2.8 and 3.8 × 106 km2. Bog, fen, and permafrost bog were the most abundant wetland classes, covering ∼ 28 % each of the total wetland area, while the highest-methane-emitting marsh and tundra wetland classes occupied 5 % and 12 %, respectively. Lakes, defined to include all lentic open-water ecosystems regardless of size, covered 1.4 × 106 km2 (6 % of domain). Low-methane-emitting large lakes (〉10 km2) and glacial lakes jointly represented 78 % of the total lake area, while high-emitting peatland and yedoma lakes covered 18 % and 4 %, respectively. Small (〈0.1 km2) glacial, peatland, and yedoma lakes combined covered 17 % of the total lake area but contributed disproportionally to the overall spatial uncertainty in lake area with a 95 % confidence interval between 0.15 and 0.38 × 106 km2. Rivers and streams were estimated to cover 0.12  × 106 km2 (0.5 % of domain), of which 8 % was associated with high-methane-emitting headwaters that drain organic-rich landscapes. Distinct combinations of spatially co-occurring wetland and lake classes were identified across the BAWLD domain, allowing for the mapping of “wetscapes” that have characteristic methane emission magnitudes and sensitivities to climate change at regional scales. With BAWLD, we provide a dataset which avoids double-accounting of wetland, lake, and river extents and which includes confidence intervals for each land cover class. As such, BAWLD will be suitable for many hydrological and biogeochemical modelling and upscaling efforts for the northern boreal and arctic region, in particular those aimed at improving assessments of current and future methane emissions. Data are freely available at https://doi.org/10.18739/A2C824F9X (Olefeldt et al., 2021).

Description: Vehicular emissions contribute a significant portion to fine particulate matter (PM2.5) air pollution in urban areas. Knowledge of the relative contribution of gasoline- versus diesel-powered vehicles is highly relevant for policymaking, and yet there is a lack of an effective observation-based method to determine this quantity, especially for its robust tracking over a period of years. In this work, we present an approach to track separate contributions of gasoline and diesel vehicles through the positive matrix factorization (PMF) analysis of online monitoring data measurable by relatively inexpensive analytical instruments. They are PM2.5 organic and elemental carbon (OC and EC), C2–C9 volatile organic compounds (VOCs) (e.g., pentanes, benzene, xylenes, etc.), and nitrogen oxide concentrations. The method was applied to monitoring data spanning more than 6 years between 2011 and 2017 in a roadside environment in Hong Kong. We found that diesel vehicles accounted for ∼70 %–90 % of the vehicular PM2.5 (PMvehicle) over the years and the remainder from gasoline vehicles. The diesel PMvehicle during truck- and bus-dominated periods showed declining trends simultaneous with control efforts targeted at diesel commercial vehicles and franchised buses in the intervening period. The combined PMvehicle from diesel and gasoline vehicles by PMF agrees well with an independent estimate by the EC-tracer method, both confirming PMvehicle contributed significantly to the PM2.5 in this urban environment (∼4–8 µg m−3, representing 30 %–60 % in summer and 10 %–20 % in winter). Our work shows that the long-term monitoring of roadside VOCs and PM2.5 OC and EC is effective for tracking gaseous and PM pollutants from different vehicle categories. This work also demonstrates the value of an evidence-based approach in support of effective control policy formulation.

Description: In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

Description: Coastal systems can act as filters for anthropogenic nutrient input into marine environments. Here, we assess the processes controlling the removal of phosphorus (P) and nitrogen (N) for four sites in the eutrophic Stockholm archipelago. Bottom water concentrations of oxygen (O2) and P are inversely correlated. This is attributed to the seasonal release of P from iron-oxide-bound (Fe-oxide-bound) P in surface sediments and from degrading organic matter. The abundant presence of sulfide in the pore water and its high upward flux towards the sediment surface (∼4 to 8 mmol m−2 d−1), linked to prior deposition of organic-rich sediments in a low-O2 setting (“legacy of hypoxia”), hinder the formation of a larger Fe-oxide-bound P pool in winter. This is most pronounced at sites where water column mixing is naturally relatively low and where low bottom water O2 concentrations prevail in summer. Burial rates of P are high at all sites (0.03–0.3 mol m−2 yr−1), a combined result of high sedimentation rates (0.5 to 3.5 cm yr−1) and high sedimentary P at depth (∼30 to 50 µmol g−1). Sedimentary P is dominated by Fe-bound P and organic P at the sediment surface and by organic P, authigenic Ca-P and detrital P at depth. Apart from one site in the inner archipelago, where a vivianite-type Fe(II)-P mineral is likely present at depth, there is little evidence for sink switching of organic or Fe-oxide-bound P to authigenic P minerals. Denitrification is the major benthic nitrate-reducing process at all sites (0.09 to 1.7 mmol m−2 d−1) with rates decreasing seaward from the inner to outer archipelago. Our results explain how sediments in this eutrophic coastal system can remove P through burial at a relatively high rate, regardless of whether the bottom waters are oxic or (frequently) hypoxic. Our results suggest that benthic N processes undergo annual cycles of removal and recycling in response to hypoxic conditions. Further nutrient load reductions are expected to contribute to the recovery of the eutrophic Stockholm archipelago from hypoxia. Based on the dominant pathways of P and N removal identified in this study, it is expected that the sediments will continue to remove part of the P and N loads.

Description: Vertical structures of aerosol single scattering albedo (SSA), from near the surface through the free troposphere, have been estimated for the first time at distinct geographical locations over the Indian mainland and adjoining oceans, using in situ measurements of aerosol scattering and absorption coefficients aboard the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 aircraft during the South West Asian Aerosol Monsoon Interactions (SWAAMI) campaign from June to July 2016. These are used to examine the spatial variation of SSA profiles and also to characterize its transformation from just prior to the onset of Indian Summer Monsoon (June 2016) to its active phase (July 2016). Very strong aerosol absorption, with SSA values as low as 0.7, persisted in the lower altitudes (

Description: Atmospheric climate monitoring requires observations of high quality that conform to the criteria of the Global Climate Observing System (GCOS). Radio occultation (RO) data based on Global Positioning System (GPS) signals are available since 2001 from several satellite missions with global coverage, high accuracy, and high vertical resolution in the troposphere and lower stratosphere. We assess the consistency and long-term stability of multi-satellite RO observations for use as climate data records. As a measure of long-term stability, we quantify the structural uncertainty of RO data products arising from different processing schemes. We analyze atmospheric variables from bending angle to temperature for four RO missions, CHAMP, Formosat-3/COSMIC, GRACE, and Metop, provided by five data centers. The comparisons are based on profile-to-profile differences aggregated to monthly medians. Structural uncertainty in trends is found to be lowest from 8 to 25 km of altitude globally for all inspected RO variables and missions. For temperature, it is

Description: Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget,