Estimate Emission Rates Research Articles

Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission

Abstract. Reducing methane (CH4) emissions from the oil and gas (O&G) sector is crucial for mitigating climate change in the near term. MethaneSAT is an upcoming satellite mission designed to monitor basin-wide O&G emissions globally, providing estimates of emission rates and helping identify the underlying processes leading to methane release in the atmosphere. MethaneSAT data will support advocacy and policy efforts by helping to track methane reduction commitments and targets set by countries and industries. Here, we introduce a CH4 retrieval algorithm for MethaneSAT based on the CO2 proxy method. We apply the algorithm to observations from the maiden campaign of MethaneAIR, an airborne precursor to the satellite that has similar instrument specifications. The campaign was conducted during winter 2019 and summer 2021 over three major US oil and gas basins. Analysis of MethaneAIR data shows that measurement precision is typically better than 2 % at a 20×20 m2 pixel resolution, exhibiting no strong dependence on geophysical variables, e.g., surface reflectance. We show that detector focus drifts over the course of each flight, likely due to thermal gradients that develop across the optical bench. The impacts of this drift on retrieved CH4 can mostly be mitigated by including a parameter that squeezes the laboratory-derived, tabulated instrument spectral response function (ISRF) in the spectral fit. Validation against coincident EM27/SUN retrievals shows that MethaneAIR values are generally within 1 % of the retrievals. MethaneAIR retrievals were also intercompared with retrievals from the TROPOspheric Monitoring Instrument (TROPOMI). We estimate that the mean bias between the instruments is 2.5 ppb, and the latitudinal gradients for the two data sets are in good agreement. We evaluate the accuracy of MethaneAIR estimates of point-source emissions using observations recorded over the Permian Basin, an O&G basin, based on the integrated-mass-enhancement approach coupled with a plume-masking algorithm that uses total variational denoising. We estimate that the median point-source detection threshold is 100–150 kg h−1 at the aircraft's nominal above-surface observation altitude of 12 km. This estimate is based on an ensemble of Weather Research and Forecasting (WRF) large-eddy simulations used to mimic the campaign's conditions, with the threshold for quantification set at approximately twice the detection threshold. Retrievals from repeated basin surveys indicate the presence of both persistent and intermittent sources, and we highlight an example from each case. For the persistent source, we infer emissions from a large O&G processing facility and estimate a leak rate between 1.6 % and 2.1 %, higher than any previously reported emission levels from a facility of its size. We also identify a ruptured pipeline that could increase total basin emissions by 2 % if left unrepaired; this pipeline was discovered 2 weeks before it was found by its operator, highlighting the importance of regular monitoring by future satellite missions. The results showcase MethaneAIR's capability to make highly accurate, precise measurements of methane dry-air mole fractions in the atmosphere, with a fine spatial resolution (∼ 20×20 m2) mapped over large swaths (∼ 100×100 km2) in a single flight. The results provide confidence that MethaneSAT can make such measurements at unprecedentedly fine scales from space (∼ 130×400 m2 pixel size over a target area measuring ∼ 200×200 km2), thereby delivering quantitative data on basin-wide methane emissions.

Aerosol‐Calibrated Matched Filter Method for Retrievals of Methane Point Source Emissions Over the Los Angeles Basin

AbstractMethane, with a global warming potential roughly 86 times greater than carbon dioxide over a 20‐year timeframe, plays a crucial role in global warming. Remote sensing retrieval is a pivotal methodology for identifying methane emission sources, with accuracy influenced largely by surface and atmospheric properties, including aerosols. In this study, we propose an Aerosol‐Calibrated Matched Filter (ACMF) algorithm to improve the traditional Matched Filter (MF) method. Our new approach incorporates an aerosol scattering correction factor to reduce the aerosol‐induced bias on methane retrievals. Validating our algorithm through simulated spectra, we demonstrate that considering the aerosol scattering effect significantly reduces retrieval errors compared to MF methods by an average of approximately 90%. We apply our newly developed algorithm to hyperspectral data obtained from the Airborne Visible/Infrared Imaging Spectrometer—Next Generation in the Los Angeles Basin and focus on 11 plumes identified through case studies. Our results reveal that ACMF estimates of emission rates and inversion uncertainties exhibit an average reduction of approximately 4% compared to corresponding MF results, with deviation increasing with aerosol optical depth (AOD).

Solar‐Induced Chlorophyll Fluorescence as a Potential Proxy for Gross Primary Production and Methane Emission in a Cool‐Temperate Bog in Northern Japan

AbstractWetlands play an essential role in the global greenhouse gas budget via carbon dioxide sequestration as well as methane emission. In recent decades, solar‐induced chlorophyll fluorescence (SIF) has been recognized as a remotely sensed proxy of gross primary productivity (GPP), which generates substrates for methane production. To examine the suitability of SIF for estimation of these two fluxes, we conducted ground tower‐based SIF observation with an ultrafine‐resolution spectroradiometer in conjunction with eddy covariance measurement in a cool‐temperate bog. The daily SIF retrieved in the red (687 nm) and far‐red (760 nm) bands (SIFred and SIFfar‐red, respectively) increased nonlinearly with GPP and linearly with absorbed photosynthetically active radiation (APAR). The relatively weak correlation between apparent SIF yield (ΦSIF = SIF/APAR) and light use efficiency implied that both APAR and plant physiology constrained the SIF emission in this wetland. The SIFred/SIFfar‐red ratio showed a significant negative relationship with vegetation greenness indices, and the similar seasonal variation in SIFred and SIFfar‐red indicated that the SIFred reabsorption effect only weakly influenced the SIFred–GPP relationship. Episodic temporal reduction in the water table did not distinctly influence SIF and ΦSIF. Estimation of the methane emission rate was subtly improved by incorporating SIF, which was substituted for GPP as the methanogenesis substrate, in a multivariable regression analysis together with two environmental factors: soil temperature and water table depth. This study illustrates the potential of both SIFred and SIFfar‐red to monitor GPP and to predict methane emission in wetlands.

Point Sensor Networks Struggle to Detect and Quantify Short Controlled Releases at Oil and Gas Sites.

This study evaluated multiple commercially available continuous monitoring (CM) point sensor network (PSN) solutions under single-blind controlled release testing conducted at operational upstream and midstream oil and natural gas (O&G) sites. During releases, PSNs reported site-level emission rate estimates of 0 kg/h between 38 and 86% of the time. When non-zero site-level emission rate estimates were provided, no linear correlation between the release rate and the reported emission rate estimate was observed. The average, aggregated across all PSN solutions during releases, shows 5% of the mixing ratio readings at downwind sensors were greater than the site's baseline plus two standard deviations. Four of seven total PSN solutions tested during this field campaign provided site-level emission rate estimates with the site average relative error ranging from -100% to 24% for solution D, -100% to -43% for solution E, -25% for solution F (solution F was only at one site), and -99% to 430% for solution G, with an overall average of -29% across all sites and solutions. Of all the individual site-level emission rate estimates, only 11% were within ±2.5 kg/h of the study team's best estimate of site-level emissions at the time of the releases.

CO2 concentration retrieval and emission rate estimation over Indian thermal power plants using radiative transfer approach and AVIRIS-NG data

Carbon dioxide (CO2) emissions from thermal power plants (TPPs) are regarded as the primary source of CO2 at the boundary-level atmosphere. The first step toward mitigating these emissions is to improve emission estimation methods at the facility level and establish a reliable emission reporting system. This study aims to establish a transparent and reliable methodology for detecting point source CO2 emissions from TPP and estimating the emission rate released from the stakes of TPP. A remote sensing method continuum interpolated band ratio (CIBR) has been utilized to detect and estimate CO2 emissions over Indian TPPs using Airborne Visible/InfraRed Imaging Spectrometer - Next Generation (AVIRIS-NG) data acquired by the ISRO-NASA joint campaign over India in 2015 and 2018. MODerate resolution atmospheric TRANsmission (MODTRAN) 5.3 radiative transfer (RT) model simulations were carried out for TPP sites to develop a CIBR algorithm for CO2 retrieval. Two AVIRIS-NG short-wave infrared (SWIR) bands were utilized for CO2 concentration retrieval, and the results from each band were compared based on their emission detection capabilities. Comparatively, SWIR-2 (1960–2120 nm) bands show higher sensitivity of CO2 than SWIR-1 (1560–1640 nm). Therefore, we utilize SWIR-2 results for the CO2 retrieval and emission rate estimation. Maximum CO2 emissions of 53.10, 46.36, 96.84, and 53.49 ppmv were detected at Maithon, Dhariwal, Udupi, and Parangipettai TPPs. The study includes one USA-based TPP to compare emission results for validation and test the method in diverse atmospheric conditions. In addition, we compared CO2 estimation results with AVIRIS-NG benchmark data. The simple band ratio method uses only three SWIR bands and operates with minimal computational facility, making it suitable for CO2 retrieval in hyperspectral data. Further, the integrated mass enhancement (IME) method has been used for emission rate estimation using CO2 concentration values from SWIR-2 retrieval results and wind speed at the sites. Yearly 5.96, 6.82, 2.29, and 3.52 Mt emissions were estimated for Maithon, Dhariwal, Udupi, and Parangipettai TPPs, respectively. The emission results have been validated by establishing a relationship between TPP's coal consumption and CO2 emissions. Further, estimated emission rates have been validated with former investigations and the CO2 baseline emission database of India's Central Electricity Authority (CEA) reports. Not having in-situ measurements and uncertainty in wind data may limit the study.

Methane emission rate estimates of offshore oil platforms in Newfoundland and Labrador, Canada

Methane emission rate estimates of offshore oil platforms in Newfoundland and Labrador, Canada

Indoor air concentrations of PM2.5 quartz fiber filter-collected ionic PFAS and emissions to outdoor air: findings from the IPA campaign.

Per- and polyfluoroalkyl substances (PFAS) are prevalent in consumer products used indoors. However, few measurements of ionic PFAS exist for indoor air. We analyzed samples collected on PM2.5 quartz fiber filters (QFFs) in 11 North Carolina homes 1-3 times in living rooms (two QFFs in series), and immediately outside each home (single QFF), for 26 ionic PFAS as part of the 9 months Indoor PFAS Assessment (IPA) Campaign. All targeted PFAS, except for PFDS and 8:2 monoPAP, were detected indoors. PFBA, PFHpA, PFHxA, PFOA, PFOS, and 6:2 diPAP were detected in >50% of indoor samples. PFHxA, PFOA, and PFOS had the highest detection frequency (DF = 80%; medians = 0.5-0.7 pg m-3), while median PFBA concentrations (3.6 pg m-3; DF = 67%) were highest indoors. Residential indoor air concentrations (sum of measured PFAS) were, on average, 3.4 times higher than residential outdoor air concentrations, and an order of magnitude higher than regional background concentrations. Indoor-to-outdoor emission rate estimates suggest that emissions from single unit homes could be a meaningful contributor to PFBA, PFOA, and PFOS emissions in populated areas far from major point sources. Backup QFFs were observed to adsorb some targeted PFAS from the gas-phase, making reported values upper-bounds for particle-phase and lower-bounds for total air (gas plus particle) concentrations. We found that higher concentrations of carbonaceous aerosol were associated with a shift in partitioning of short chain PFCAs and long chain PFSAs toward the particle phase.

A Preliminary Methane Emission Study of Typical Coalbed Methane Production Areas Based on Multi-satellites Remote Sensing Data

The monitoring of methane emission is helpful for reducing the concentration of atmospheric greenhouse gases. A preliminary methane emission study of typical coalbed methane production areas based on multi-satellites remote sensing data was proposed. Methane monitoring for typical coalbed methane production areas in Shanxi Province, methane anomaly analysis, associated gas flaring identification as well as emission estimation were carried out, using Sentinel-5P TROPOMI (TROPOspheric Monitoring Instrument) CH4 data, Sentinel-2 false color images and VIIRS (Visible Infrared Imaging Radiometer Suite) active fire data. The research showed that typical coalbed methane production areas in Shanxi Province were featured with high CH4 concentration in the southeast and low concentration in the northwest. The maximum methane anomaly of about 80 ppb was discovered and the emission rate was estimated to be approximately 20 t/h-23 t/h for the identified associated gas flaring location. The estimation was consistent with the results from PRISMA data for the Shanxi coal mining region. The research demonstrated the capability of satellite observation to support the coalbed methane production emission source identification from space and indicated the method provided was favorable for methane anomaly analysis, emission identification as well as emission rate estimation for coalbed methane production areas.

Hybrid Deep Learning and Sensitivity Operator-Based Algorithm for Identification of Localized Emission Sources

Hybrid approaches combining machine learning with traditional inverse problem solution methods represent a promising direction for the further development of inverse modeling algorithms. The paper proposes an approach to emission source identification from measurement data for advection–diffusion–reaction models. The approach combines general-type source identification and post-processing refinement: first, emission source identification by measurement data is carried out by a sensitivity operator-based algorithm, and then refinement is done by incorporating a priori information about unknown sources. A general-type distributed emission source identified at the first stage is transformed into a localized source consisting of multiple point-wise sources. The second, refinement stage consists of two steps: point-wise source localization and emission rate estimation. Emission source localization is carried out using deep learning with convolutional neural networks. Training samples are generated using a sensitivity operator obtained at the source identification stage. The algorithm was tested in regional remote sensing emission source identification scenarios for the Lake Baikal region and was able to refine the emission source reconstruction results. Hence, the aggregates used in traditional inverse problem solution algorithms can be successfully applied within machine learning frameworks to produce hybrid algorithms.

Methane point source quantification using MethaneAIR: a new airborne imaging spectrometer

Abstract. The MethaneSAT satellite instrument and its aircraft precursor, MethaneAIR, are imaging spectrometers designed to measure methane concentrations with wide spatial coverage, fine spatial resolution, and high precision compared to currently deployed remote sensing instruments. At 12 960 m cruise altitude above ground (13 850 m above sea level), MethaneAIR datasets have a 4.5 km swath gridded to 10 m × 10 m pixels with 17–20 ppb standard deviation on a flat scene. MethaneAIR was deployed in the summer of 2021 in the Permian Basin to test the accuracy of the retrieved methane concentrations and emission rates using the algorithms developed for MethaneSAT. We report here point source emissions obtained during a single-blind volume-controlled release experiment, using two methods. (1) The modified integrated mass enhancement (mIME) method estimates emission rates using the total mass enhancement of methane in an observed plume combined with winds obtained from Weather Research Forecast driven by High-Resolution Rapid Refresh meteorological data in Large Eddy Simulations mode (WRF-LES-HRRR). WRF-LES-HRRR simulates winds in stochastic eddy-scale (100–1000 m) variability, which is particularly important for low-wind conditions and informing the error budget. The mIME can estimate emission rates of plumes of any size that are detectable by MethaneAIR. (2) The divergence integral (DI) method applies Gauss's theorem to estimate the flux divergence fields through a series of closed surfaces enclosing the sources. The set of boxes grows from the upwind side of the plume through the core of each plume and downwind. No selection of inflow concentration, as used in the mIME, is required. The DI approach can efficiently determine fluxes from large sources and clusters of sources but cannot resolve small point emissions. These methods account for the effects of eddy-scale variation in different ways: the DI averages across many eddies, whereas the mIME re-samples many eddies from the LES simulation. The DI directly uses HRRR winds, while mIME uses WRF-LES-HRRR wind products. Emissions estimates from both the mIME and DI methods agreed closely with the single-blind volume-controlled experiments (N = 21). The York regression between the estimated emissions and the released emissions has a slope of 0.96 [0.84, 1.08], R = 0.83 and N = 21, with 30 % mean percentage error for the whole dataset, which indicates that MethaneAIR can quantify point sources emitting more than 200 kg h−1 for the mIME and 500 kg h−1 for the DI method. The two methods also agreed on methane emission estimates from various uncontrolled sources in the Permian Basin. The experiment thus demonstrates the powerful potential of the MethaneAIR instrument and suggests that the quantification method should be transferable to MethaneSAT if it meets the design specifications.

Summertime Airborne Measurements of Ammonia Emissions From Cattle Feedlots and Dairies in Northeastern Colorado

AbstractPhase One of the Transportation and Transformation of Ammonia (TRANS2Am) field campaign took place in northeastern Colorado during the summer of 2021. One of the goals of TRANS2Am was to measure ammonia (NH3) emissions from cattle feedlots and dairies. Most of these animal husbandry facilities are co‐located within oil and gas development, an important source of methane (CH4) and ethane (C2H6) in the region. Phase One of TRANS2Am included 12 near‐source research flights. We present estimates of NH3 emissions ratios with respect to CH4 (NH3 EmR), with and without correction of CH4 from oil and gas, for 29 feedlots and dairies in the region. The data shows larger emissions ratios than previously reported in the literature with a large range of values (i.e., 0.1–2.6 ppbv ppbv−1). Facilities housing cattle and dairy had a mean (std) of 1.20 (0.63) and 0.29 (0.08) ppbv ppbv−1, respectively. We also found that only 15% of the total ammonia (NHx) is in the particle phase (i.e., ) near major sources during the warm summertime months. We examined the evolution of NH3 in one plume that was sampled at different distances and altitudes up to 25 km downwind and estimated the NH3 lifetime against deposition and partitioning to the particle phase to be 87–120 min. Finally, we calculated estimates of NH3 emission rates from four optimally sampled facilities. These ranged from 4 to 29 g NH3 · h−1 · hd−1.

Intercomparison of detection and quantification methods for methane emissions from the natural gas distribution network in Hamburg, Germany

Abstract. In August and September 2020, three different measurement methods for quantifying methane (CH4) emissions from leaks in urban gas distribution networks were applied and compared in Hamburg, Germany: the “mobile”, “tracer release”, and “suction” methods. The mobile and tracer release methods determine emission rates to the atmosphere from measurements of CH4 mole fractions in the ambient air, and the tracer release method also includes measurement of a gaseous tracer. The suction method determines emission rates by pumping air out of the ground using soil probes that are placed above the suspected leak location. The quantitative intercomparison of the emission rates from the three methods at a small number of locations is challenging because of limitations of the different methods at different types of leak locations. The mobile method was designed to rapidly quantify the average or total emission rate of many gas leaks in a city, but it yields a large emission rate uncertainty for individual leak locations. Emission rates determined for individual leak locations with the tracer release technique are more precise because the simultaneous measurement of the tracer released at a known rate at the emission source eliminates many of the uncertainties encountered with the mobile method. Nevertheless, care must be taken to properly collocate the tracer release and the leak emission points to avoid biases in emission rate estimates. The suction method could not be completed or applied at locations with widespread subsurface CH4 accumulation or due to safety measures. While the number of gas leak locations in this study is small, we observe a correlation between leak emission rate and subsurface accumulation. Wide accumulation places leaks into a safety category that requires immediate repair so that the suction method cannot be applied to these larger leaks in routine operation. This introduces a sampling bias for the suction method in this study towards the low-emission leaks, which do not require immediate repair measures. Given that this study is based on random sampling, such a sampling bias may also exist for the suction method outside of this study. While an investigation of the causal relationship between safety category and leak size is beyond the scope of this study, on average higher emission rates were observed from all three measurement-based quantification methods for leaks with higher safety priority compared to the leaks with lower safety concern. The leak locations where the suction method could not be applied were the biggest emitters, as confirmed by the emission rate quantifications using mobile and tracer methods and an engineering method based on the leak's diameter, pipeline overpressure, and depth at which the pipeline is buried. The corresponding sampling bias for the suction technique led to a low bias in derived emission rates in this study. It is important that future studies using the suction method account for any leaks not quantifiable with this method in order to avoid biases, especially when used to inform emission inventories.

Avoiding methane emission rate underestimates when using the divergence method

Methane is a powerful greenhouse gas, and a primary target for mitigating climate change in the short-term future due to its relatively short atmospheric lifetime and greater ability to trap heat in Earth’s atmosphere compared to carbon dioxide. Top-down observations of atmospheric methane are possible via drone and aircraft surveys as well as satellites such as the TROPOspheric Monitoring Instrument (TROPOMI). Recent work has begun to apply the divergence method to produce regional methane emission rate estimates. Here we show that when the divergence method is applied to spatially incomplete observations of methane, it can result in negatively biased time-averaged regional emission rates. We show that this effect can be counteracted by adopting a procedure in which daily advective fluxes of methane are time-averaged before the divergence method is applied. Using such a procedure with TROPOMI methane observations, we calculate yearly Permian emission rates of 3.1, 2.4 and 2.7 million tones per year for the years 2019 through 2021. We also show that highly-resolved plumes of methane can have negatively biased estimated emission rates by the divergence method due to the presence of turbulent diffusion in the plume, but this is unlikely to affect regional methane emission budgets constructed from TROPOMI observations of methane. The results from this work are expected to provide useful guidance for future implementations of the divergence method for emission rate estimation from satellite data—be it for methane or other gaseous species in the atmosphere.

Size-resolved emission rates of episodic indoor sources and ultrafine particle dynamics

Indoor airborne ultrafine particles (UFPs) are mainly originated from occupant activities, such as candle burning and cooking. Elevated exposure to UFPs has been found to increase oxidative stress and cause DNA damage. UFPs originating from indoor sources undergo dynamic aerosol transformation mechanisms. This study investigates the dynamics of UFPs following episodic indoor releases of the six distinct emission sources: 1) candle, 2) gas stove, 3) clothes dryer, 4) tea & toast, 5) broiled fish, and 6) incense. Based on the analytical model of aerosol dynamic processes, this study reports size-resolved source emission rates along with relative contributions of coagulation, deposition, and ventilation to the particle size distribution dynamics. The study findings indicate a significant variation in the geometric mean diameter (GMD) and size-resolved number concentration over time for the sources that emit a substantial amount of UFPs smaller than 10 nm. As the emission progresses, the UFP number concentrations increase in a log-normal distribution, while the GMD shows a tendency to increase over time. The observed result suggests that coagulation can have a considerable impact on UFP number concentration and size, even during the indoor UFP emission. The estimated emission rates of the six indoor sources appear to follow a log-normal distribution while the emission rate ranges from 107 min−1 to 1012 min−1. The indoor UFP concentration and size distribution dynamics are substantially affected by the interplay of the three aerosol loss mechanisms that compete with each other, and this impact varies according to the source type and the indoor environmental conditions. Ultimately, using the aerosol transformation mechanisms examined in this study, researchers can refine exposure assessment for epidemiological studies on indoor ultrafine particles.

Wide range in estimates of hydrogen emissions from infrastructure

Hydrogen holds tremendous potential to decarbonize many economic sectors, from chemical and material industries to energy storage and generation. However, hydrogen is a tiny, leak-prone molecule that can indirectly warm the climate. Thus, hydrogen emissions from its value chain (production, conversion, transportation/distribution, storage, and end-use) could considerably undermine the anticipated climate benefits of a hydrogen economy. Several studies have identified value chain components that may intentionally and/or unintentionally emit hydrogen. However, the amount of hydrogen emitted from infrastructure is unknown as emissions have not yet been empirically quantified. Without the capacity to make accurate direct measurements, over the past two decades, some studies have attempted to estimate total value chain and component-level hydrogen emissions using various approaches, e.g., assumptions, calculations via proxies, laboratory experiments, and theory-based models (simulations). Here, we synthesize these studies to provide an overview of the available knowledge on hydrogen emissions across value chains. Briefly, the largest ranges in estimated emissions rates are associated with liquefaction (0.15%–10%), liquid hydrogen transporting and handling (2%–20%), and liquid hydrogen refueling (2%–15%). Moreover, present and future value chain emission rate estimates vary widely (0.2%–20%). Field measurements of hydrogen emissions throughout the value chain are critically needed to sharpen our understanding of hydrogen emissions and, with them, accurately assess the climate impact of hydrogen deployment.

A custom, low-cost, continuous flow chamber built for experimental Sargassum seaweed decomposition and exposure of small rodents to generated gaseous products

Since 2011, Sargassum events have increased in frequency along the Caribbean and Atlantic coasts. The accumulation and decomposition of large amounts of Sargassum seaweed on beaches pose socio-economic, ecological, and health risks due to the emission of hydrogen sulfide (H2S), methane, and ammonia. However, limited research exists on the emission processes and the health effects of subchronic and chronic exposure to low levels of H2S. Additionally, the absence of emission factor data for Sargassum decomposition on-site makes health risk assessments challenging. This study aimed to create a custom chamber to simulate real-world Sargassum decomposition, exposing experimental animals to the generated gases. Metal content was analyzed, and emission rates were estimated in a controlled environment. The decomposition-exposure system replicated reported environmental gas emissions from the Caribbean region, except for NH3. H2S bursts were observed during the decomposition process at intervals of 2–10 days, with higher frequency associated with larger masses of decomposing Sargassum. The decomposed gas was transferred to the exposure chamber, resulting in an 80–87% reduction in H2S concentration. The maximum H2S emission was 156 ppm, with a concentration ranging from 50.4 to 56.5 ppm. An estimated emission rate of 7–8 g/h for H2S was observed, and significant levels of lead, arsenic, and aluminum were found in beached Sargassum from the northeast coast of Brazil. This study's developed model provides an opportunity to investigate the effects and risks to human health associated with exposure to gases produced during the environmental decomposition of Sargassum seaweed.

Estimation of Particle Emission Rates and Calculation of Human Dose from Arc Welding and Cutting of Stainless Steel in a Simulated Confined Workspace

The objective of this study was to estimate the particle emission rates, human dose and retention from two arc welding processes and cutting of stainless steel. The two arc welding processes were Shielded Metal Arc Welding (SMAW) and Tungsten Inert Gas (TIG). In a simulated confined workspace of experimental chamber under controlled conditions, four different scenarios were considered, including the use of filtering face piece respirator (FFR), leaving or staying in the workspace after the emission. Deposited and retained dose in the respiratory tract was assessed for the different regions of the human respiratory tract using a dosimetry model (ExDoM2). The three investigated processes generated high particle number concentrations ranging from 2.4 to 3.6 × 106 particles/cm3 and were the highest during TIG. Among all three processes, PM10 concentrations from cutting reached the highest levels [11 and 22 (× 103) μg/m3], while SMAW had the highest contribution of fine particles [~ 4.1 (× 103) μg/m3], consisting mostly of PM1–2.5. The examination of different scenarios revealed that there is only a slight difference in respect to deposited dose while staying in the workspace for the entire investigated time period (4 h) with or without use of Filtering Facepiece Respirator (FFR). It would be more beneficial in respect to deposited dose if the exposed subject was not wearing a FFR during the emission process and would leave the polluted workspace immediately after the emission period. In the first two scenarios (staying 4 h in the polluted workspace with and without FFR), both welding processes had higher cumulative deposited (~ 23%) and retained dose (~ 20%) in thoracic region compared to cutting (~ 9% and ~ 7%). These results demonstrate that even a short emission period can cause a considerable increase in concentrations of harmful respirable particles, thus increasing the human dose. The approach applied in this study could be used for the determination of personal exposure and dose to particles of known composition particularly in confined workspaces.

Methane emissions decline from reduced oil, natural gas, and refinery production during COVID-19

In the summer of 2020, the AVIRIS-NG airborne imaging spectrometer surveyed California’s Southern San Joaquin Valley and the South Bay (Los Angeles County) to identify anthropogenic methane (CH4) point source plumes, estimate emission rates, and attribute sources to both facilities and emission sectors. These flights were designed to revisit regions previously surveyed by the 2016–2017 California Methane Survey and to assess the socioeconomic responses of COVID-19 on emissions across multiple sectors. For regions flown by both the California Methane Survey and the California COVID campaigns, total CH4 point source emissions from the energy and oil & natural gas sectors were 34.8% lower during the summer 2020 flights, however, emission trends varied across sector. For the energy sector, there was a 28.2% decrease driven by reductions in refinery emissions consistent with a drop in production, which was offset in part with increases from powerplants. For the oil & natural gas sector, CH4 emissions declined 34.2% and significant variability was observed at the oilfield scale. Emissions declined for all but the Buena Vista and Cymric fields with an observed positive relationship between production and emissions. In addition to characterizing the short-term impact of COVID-19 on CH4 emissions, this study demonstrates the broader potential of remote sensing with sufficient sensitivity, spatial resolution, and spatio-temporal completeness to quantify changes in CH4 emissions at the scale of key sectors and facilities.

Validation study of WindTrax reverse dispersion model coupled with a sensitivity analysis of model-specific settings

In last years, atmospheric dispersion models have reached considerable popularity in environmental research field. In this regard, given the difficulties associated to the estimation of emission rate for some kind of sources, and due to the importance of this parameter for the reliability of the results, Backward dispersion models may represent promising tools. In particular, by knowing a measured downwind concentration in ambient air, they provide a numerical value for the emission rate. This paper discusses a critical validation of the WindTrax Backward model: the investigation does not only deal with the strict reliability of the model but also assesses under which conditions (i.e. stability class, number, and location of the sensors) the model shows the greatest accuracy. For this purpose, WindTrax results have been compared to observed values obtained from available experimental datasets. In addition, a sensitivity study regarding model-specific parameters required by WindTrax to replicate the physics and the random nature of atmospheric dispersion processes is discussed. This is a crucial point, since, for these settings, indications on the numerical values to be adopted are not available. From this study, it turns out that the investigated model specific settings do not lead to a significant output variation. Concerning the validation study, a general tendency of the model to predict the observed values with a good level of accuracy has been observed, especially under neutral atmospheric conditions. In addition, it seems that WindTrax underestimates the emission rate during unstable stratification and overestimates during stable conditions. Finally, by the definition of alternative scenarios, in which only a portion of the concentration sensors was considered, WindTrax performance appears better than acceptable even with a small number of concentration sensors, as long as the positioning is in the middle of the plume and not in the strict vicinity of the source.

Microplastic sampling strategies in urban drainage systems for quantification of urban emissions based on transport pathways

AbstractTracking waterborne microplastic (MP) in urban areas is a challenging task because of the various sources and transport pathways involved. Since MP occurs in low concentrations in most wastewater and stormwater streams, large sample volumes need to be captured, prepared, and carefully analyzed. The recent research in urban areas focused mainly on MP emissions at wastewater treatment plants (WWTPs), as obvious entry points into receiving waters. However, important transport pathways under wet‐weather conditions are yet not been investigated thoroughly. In addition, the lack of comprehensive and comparable sampling strategies complicated the attempts for a deeper understanding of occurrence and sources. The goal of this paper is to (i) introduce and describe sampling strategies for MP at different locations in a municipal catchment area under dry and wet‐weather conditions, (ii) quantify MP emissions from the entire catchment and two other smaller ones within the bigger catchment, and (iii) compare the emissions under dry and wet‐weather conditions. WWTP has a high removal rate of MP (>96%), with an estimated emission rate of 189 kg/a or 0.94 g/[population equivalents (PEQ · a)], and polyethylene (PE) as the most abundant MP. The specific dry‐weather emissions at a subcatchment were ≈30 g/(PEQ · a) higher than in the influent of WWTP with 23 g/(PEQ · a). Specific wet‐weather emissions from large sub‐catchment with higher traffic and population densities were 1952 g/(ha · a) higher than the emissions from smaller catchment (796 g/[ha · a]) with less population and traffic. The results suggest that wet‐weather transport pathways are likely responsible for 2–4 times more MP emissions into receiving waters compared to dry‐weather ones due to tire abrasion entered from streets through gullies. However, more investigations of wet‐weather MP need to be carried out considering additional catchment attributes and storm event characteristics.