SO2 Emission Rates Research Articles

The ghost plume phenomenon and its impact on zenith-facing remote sensing measurements of volcanic SO2 emission rates

The ghost plume phenomenon and its impact on zenith-facing remote sensing measurements of volcanic SO2 emission rates

Monitoring Earth's atmosphere with Sentinel-5 TROPOMI and Artificial Intelligence: Quantifying volcanic SO2 emissions

Identifying changes in volcanic unrest and tracking eruptive activity are fundamental for volcanic surveillance and monitoring. Magmatic gases, particularly sulphur dioxide (SO2), play a crucial role in influencing eruptive styles, making the monitoring of SO2 emissions essential. Recent advancements in satellite remote sensing technology, including higher spatial resolution and sensitivity, have enhanced our ability to detect SO2 emissions from volcanoes worldwide. However, traditional fixed-threshold algorithms struggle to automatically distinguish volcanic SO2 emissions from non-volcanic sources. Additionally, accurately quantifying SO2 emissions is challenging due to their dependence on plume height, particularly when reaching high altitudes. To address these challenges, we developed an Artificial Intelligence (AI) algorithm that detects and quantifies volcanic SO2 emissions in near real-time. Our approach utilizes a Random Forest (RF) model, a supervised Machine Learning (ML) algorithm, to identify volcanic SO2 emissions and integrates Cloud Top Height (CTH) data to enhance the accuracy of SO2 mass quantification during intense volcanic eruptions. This AI algorithm, fully implemented in Google Earth Engine (GEE), leverages data from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Copernicus Sentinel-5 Precursor (S5P) satellite to automatically retrieve daily volcanic SO2 plumes and CTH. We validated the model's performance against the Radius classifier, a state-of-the-art tool, and generalized its application across various volcanoes (Etna, Villarrica, Fuego, Pacaya, and Cumbre Vieja) with differing degassing activities, SO2 emission rates, and plume geometries. Our findings demonstrate that the proposed AI approach effectively identifies and quantifies SO2 plumes emitted by different volcanoes, enabling the investigation of SO2 emission time series that reflect magma dynamics.

SO2 emission rates and incorporation into the air pollution dispersion forecast during the 2021 eruption of Fagradalsfjall, Iceland

During the low-effusion rate Fagradalsfjall eruption (19 March – 18 September 2021), the emission of sulfur dioxide (SO2) was frequently measured using ground-based UV spectrometers. The total SO2 emitted during the entire eruption was 970 ± 540 kt, which is only about 6% of the SO2 emitted during the similar length Holuhraun eruption (2014–2015). The eruption was divided into five phases based on visual observations, including the number of active vents and the occurrence of lava fountaining. The SO2 emission rate ranged from 44 ± 19 kg/s in Phase 2 to 85 ± 29 kg/s in Phase 5, with an average of 64 ± 34 kg/s for the entire eruption. There was notable variability in SO2 on short timescales, with measurements on 11 August 2021 ranging from 17 to 78 kg/s.SO2 flux measurements were made using scanning DOAS instruments located at different distances from and orientations relative to the eruption site augmented by traverses. Four hundred and forty-four scan and traverse measurements met quality criteria and were used, along with plume height and meteorological data, to calculate SO2 fluxes while accounting for wind-related uncertainties.A tendency for stronger SO2 flux concurrent with higher amplitude seismic tremor and the occurrence of lava fountaining was observed during Phases 4 and 5 which were characterized by intermittent crater activity including observable effusion of lava and gas release interspersed with long repose times. This tendency was used to refine the calculation of the amount of SO2 emitted during variably vigorous activity. The continuous seismic tremor time series was used to quantify how long during these eruption phases strong/weak activity was exhibited to improve the calculated SO2 flux during these Phases.The total SO2 emissions derived from field measurements align closely with results obtained by combining melt inclusion and groundmass glass analyses with lava effusion rate measurements (910 ± 230 kt SO2). Specifically, utilizing the maximum S content found in evolved melt inclusions and the least remaining S content in accompanying quenched groundmasses provides an identical result between field measurements and the petrological calculations. This suggests that the maximum SO2 release calculated from petrological estimates should be preferentially used to initialize gas dispersion models for basaltic eruptions when other measurements are lacking.During the eruption, the CALPUFF dispersion model was used to forecast ground-level exposure to SO2. The SO2 emission rates measured by DOAS were used as input for the dispersion model, with updates made when a significant change was measured. A detailed analysis of one mid-distance station over the entire eruption shows that the model performed very well at predicting the presence of volcanic SO2 when it was measured. However, it frequently predicted the presence of SO2 that was not measured and the concentrations forecasted had no correlation with the concentrations measured. Various approaches to improve the model forecast were tested, including updating plume height and SO2 flux source terms based on measurements. These approaches did not unambiguously improve the model performance but suggest that improvements might be achieved in more-polluted conditions.

PIXE analysis of contaminants in tree rings in proximity of the aluminum processing factory in Ladomerská Vieska (Slovakia)

The aluminum smelter in the Žiar nad Hronom region of central Slovakia was a substantial source of pollution in the past. Five trees were sampled in close proximity to the smelter and the tree rings were chemically processed and analyzed with the PIXE technique. Elevated concentrations of Mg, Al, Si, P, S, K, Ca, Fe, and Zn were observed in tree rings, however, they did not show a significant correlation with PM, HF and SO2 emission rates. Concentration trends show a significant effect of the heartwood-sapwood boundary layer, where a substantial drop or increase was observed between tree-ring sections.

Characterizing SO2 Emission Rate, Thermal Anomalies, from Opened and Closed Vent System at Agung, Bromo, and Sinabung Volcanoes in Indonesia

Agung, Bromo, and Sinabung Volcanoes have high volcanic activity over the last decade, and have different eruption characteristics. Hence, it would be fascinating to study the characteristics of their volcanic activity patterns based on SO2 emission rates and thermal anomaly correlated with the seismicity data. The SO2 emission rate measurement was carried out using the Differential Optical Absorption Spectroscopy (DOAS), and calculated based on SO 2 column density, distance of measurement, wind speed, and wind direction. In addition, SO2 emission was detected using Ozone Monitoring Instrument (OMI) images with daily global coverage. Thermal anomaly detection was performed using Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER) of Thermal Infrared (TIR) subsystem with high spatial resolution (90x90 m). ASTER TIR images were corrected for radiometric and thermal atmospheric. The emissivity and brightness temperature separation algorithm was applied to obtain surface temperature of Agung, Bromo, and Sinabung Volcanoes. All the data were correlated with the seismicity of each volcano. The SO2 emission rates correlate with the magma ascent to the shallow depth in an open system volcano (Bromo Volcano). In the closed-system volcanoes (early phase of Agung and Sinabung), SO2 emission was detected after the transition of closed to open system. Magmatic injection from the reservoir to the shallow depth was detected as thermal anomalies, such as in Agung Volcano. Whereas in Bromo Volcano, the thermal anomaly was insignificant since Bromo Volcano has an explosive eruption at a short period, so the ASTER image could not observe the thermal anomaly on the eruption time. Thermal anomaly pattern in Sinabung Volcano was the manifestation of new magmatic injection to the shallow depth. Therefore, their increase serves as indicators for the increasing magmatic activity prior to the eruptions. Keywords: SO2 emission rate, thermal anomaly, DOAS, OMI, ASTER, Open Vent, Closed Vent

Estimation of power plant SO2 emissions using the HYSPLIT dispersion model and airborne observations with plume rise ensemble runs

Abstract. The SO2 emission rates from three power plants in North Carolina are estimated using the HYSPLIT Lagrangian dispersion model and aircraft measurements made on 26 March 2019. To quantify the underlying modeling uncertainties in the plume rise calculation, dispersion simulations are carried out in an ensemble using a total of 15 heat release parameters. For each heat release, the SO2 emission rates are estimated using a transfer coefficient matrix (TCM) approach and compared with the Continuous Emissions Monitoring Systems (CEMS) data. An “optimal” member is first selected based on the correlation coefficient calculated for each of the six segments that delineate the plumes from the three power plants during the morning and afternoon flights. The segment influenced by the afternoon operations of Belews Creek power plant has negative correlation coefficients for all the plume rise options and is first excluded from the emission estimate here. Overestimations are found for all the segments before considering the background SO2 mixing ratios. Both constant background mixing ratios and several segment-specific background values are tested in the HYSPLIT inverse modeling. The estimation results by assuming the 25th percentile observed SO2 mixing ratios inside each of the five segments agree well with the CEMS data, with relative errors of 18 %, −12 %, 3 %, 93.5 %, and −4 %. After emission estimations are performed for all the plume rise runs, the lowest root mean square errors (RMSEs) between the predicted and observed mixing ratios are calculated to select a different set of optimal plume rise runs which have the lowest RMSEs. Identical plume rise runs are chosen as the optimal members for Roxboro and Belews Creek morning segments, but different members for the other segments yield smaller RMSEs than the previous correlation-based optimal members. It is also no longer necessary to exclude the Belews Creek afternoon segment that has a negative correlation between predictions and observations. The RMSE-based optimal runs result in much better agreement with the CEMS data for the previously severely overestimated segment and do not deteriorate much for the other segments, with relative errors of 18 %, −18 %, 3 %, −9 %, and 27 % for the five segments and 2 % for the Belews Creek afternoon segment. In addition, the RMSE-based optimal heat emissions appear to be more reasonable than the correlation-based values when they are significantly different for CPI Roxboro power plant.

Spectral Calibration for SO2 Cameras with Light Dilution Effect Correction

The detection ability of SO2 cameras has been improved effectively, while the calibration is still the main factor that limits their measurement accuracy. This paper presents a nonlinear calibration theory by considering the effect of light dilution due to the path radiance as well as the dependence of plume aerosol on scattering wavelength. This new spectral calibration method is used to retrieve the SO2 column density and emission rate of the Etna volcano. Results show that, compared with the DOAS calibration approach, the inversion error can be reduced by 13% if the new spectral calibration is adopted. The superiority of the proposed method will become more obvious for long-distance detection of optically thick plumes.

Temporal Variability in Gas Emissions at Bagana Volcano Revealed by Aerial, Ground, and Satellite Observations

AbstractBagana is a remote, highly active volcano, located on Bougainville Island in southeastern Papua New Guinea. The volcano has exhibited sustained and prodigious sulfur dioxide gas emissions in recent decades, accompanied by frequent episodes of lava extrusion. The remote location of Bagana and its persistent activity have made it a valuable case study for satellite observations of active volcanism. This remoteness has also left many features of Bagana relatively unexplored. Here, we present the first measurements of volcanic gas composition, achieved by unoccupied aerial system (UAS) flights through the volcano's summit plume, and a payload comprising a miniaturized MultiGAS. We combine our measurements of the molar CO2/SO2 ratio in the plume with coincident remote sensing measurements (ground‐ and satellite‐based) of SO2 emission rate to compute the first estimate of CO2 flux at Bagana. We report low SO2 and CO2 fluxes at Bagana from our fieldwork in September 2019, ∼320 ± 76 td−1 and ∼320 ± 84 td−1, respectively, which we attribute to the volcano's low level of activity at the time of our visit. We use satellite observations to demonstrate that Bagana's activity and emissions behavior are highly variable and advance the argument that such variability is likely an inherent feature of many volcanoes worldwide and yet is inadequately captured by our extant volcanic gas inventories, which are often biased to sporadic measurements. We argue that there is great value in the use of UAS combined with MultiGAS‐type instruments for remote monitoring of gas emissions from other inaccessible volcanoes.

Weak degassing from remote Alaska volcanoes characterized with a new airborne imaging DOAS instrument and a suite of in situ sensors

Gas emissions from volcanoes occur when volatile species exsolve from magmatic and hydrothermal systems and make their way to the surface. Measurements of emitted gases therefore provide insights into volcanic processes. On 16 July 2021, we made airborne measurements of weak gas plumes emitted from four remote Alaska volcanoes: Iliamna Volcano, Mount Douglas, Mount Martin, and Mount Mageik. Integrated into a small fixed-wing aircraft, a new Imaging Differential Optical Absorption Spectroscopy (DOAS) instrument was used to map the spatial extent of SO2 plumes as they drifted downwind. Contrary to conventional Mobile DOAS instruments, which provide only a single viewing direction, the Imaging DOAS simultaneously measures SO2 column density along 48 individual viewing directions oriented in a swath above or below the aircraft. Each of the individual measurements have a comparable precision and sensitivity to those obtained by conventional instruments. Together, they provide high resolution 2D imagery of the volcanic plumes and allow calculation of limited emission rate time series information. Although zenith-facing DOAS measurements achieve greater accuracy and are performed here, the application of the Imaging DOAS in a nadir-facing setup is also discussed and compared to satellite observations made in similar geometries. Also onboard the aircraft, a suite of electrochemical and optical sensors measured the relative abundances of the six major volcanic volatile species H2O, CO2, SO2, H2S, HCl, and HF as the aircraft passed through the plumes. Mean SO2 emission rates of 90 ± 10, 20 ± 3, and 13 ± 3 t/d were measured at Iliamna Volcano, Mount Douglas, and Mount Martin, respectively. SO2 emissions were below the DOAS detection limit at Mount Mageik but CO2 and H2S could be measured with the in situ sensors. The information gleaned from these measurements was used to assess and compare activity at these volcanoes, all of which were found to be in a state of background degassing but whose emissions pointed to different source conditions ranging from mixed magmatic-hydrothermal to purely hydrothermal in character. Additional measurements at Mount Spurr, Redoubt Volcano, and Augustine Volcano failed to detect the very weak gas concentrations downwind of these persistently degassing vents.

Evolution of the magmatic-hydrothermal system at Lastarria volcano (Northern Chile) between 2006 and 2019: Insights from fluid geochemistry

One of the major problems in the volcanic surveillance is how data from several techniques can be correlated and used to discriminate between possible precursors of volcanic eruptions and changes related to non-eruptive processes. Gas chemical surveys and measurements of SO2 emission rates performed in the past (2006–2019) at Lastarria volcano in Northern Chile have revealed a persistent increment of magmatic sourced gas emissions since late November 2012, following a 13 years period of intense ground uplift. In this work, we provide new insights into the gas-chemical evolution of Lastarria’s fumarolic discharges obtained from direct sampling (2006–2019) and SO2 emission rates using UV camera and DOAS instruments (2018–2019) and link these to pre-existing information on ground deformation (1998–2016) in order to determine the origin of observed degassing and ground deformation processes. We revise the four mechanisms originally proposed as alternatives by Lopez et al. (Geosphere, 2018, 14 (3), 983–1007) to explain the changes observed in the fluid geochemistry and ground deformation between 2009 and 2012, in order to explain major changes in gas-geochemistry over an extended period between 1998 and 2019. We hypothesize that a continuous sequence of processes explains the evolution in the fluid geochemistry of fumarolic discharges. Two mechanisms are responsible of the changes in the gas composition during the studied period, corresponding to a 1) deep magma chamber (7–15 km depth) pressurized by volatile exsolution (1998–2020), which is responsible of the large-scale deformation; followed by 2) a crystallization-induced degassing (2001–2020) and pressurization of the hydrothermal system (2003-early November 2012), where the former process induced the changes in the gas composition from hydrothermal-dominated to magmatic-dominated, whereas the last produced the small-scale deformation at Lastarria volcano. The changes in the gas composition since late November 2012, which were strongly dominated by magmatic volatiles, produced two consecutive processes: 1) acidification (late November 2012–2020) and 2) depletion (2019–2020) of the hydrothermal system. In this work we have shown that a long-term surveillance of the chemistry of fluid discharges provides valuable insights into underlying magmatic/volcanic processes, and consequently, for forecasting future eruptions.

Unusually high SO2 emissions and plume height from Piton de la Fournaise volcano during the April 2020 eruption

Piton de la Fournaise volcano, La Réunion, France, erupted between the 2 and 6 April 2020, one of a series of eruptive phases which occur typically two or three times per year. Here, we use back trajectory analysis of satellite data from the TROPOMI instrument to determine that gas emissions during the June 2020 eruption were of unusually high intensity and altitude, producing 34.9 ± 17.4 kt of SO2 and plume heights up to 5 km a.s.l. The early stages of the eruption (2–4 April 2020) were characterised by relatively low SO2 emission rates despite strong low frequency tremor (LFT); the latter phase followed an increase in intensity and explosivity in the early hours of 5 April 2020. This period included lava fountaining, significantly increased SO2 emission rates, increased high frequency tremor (HFT) and decreased LFT. Using the PlumeTraj back trajectory analysis toolkit, we found the peak SO2 emission rate was 284 ± 130 kg/s on the 6 April. The plume altitude peaked at ~ 5 km a.s.l. on 5 April, in the hours following a sudden increase in explosivity, producing one of the tallest eruption columns recorded at Piton de la Fournaise. PlumeTraj allowed us to discriminate each day’s SO2, which otherwise would have led to a mass overestimate due to the plumes remaining visible for more than 24 h. The eruption exhibited a remarkable decoupling and anti-correlation between the intensity of the LFT signal and that of the magma and gas emission rates. LFT intensity peaked during the first phase with low magma and SO2 emissions, but quickly decreased during the second phase, replaced by unusually strong HFT. We conclude that the observation of strong HFT is associated with higher intensity of eruption, degassing, and greater height of neutral buoyancy of the plume, which may provide an alert to the presence of greater hazards produced by higher intensity eruptive activity. This might be particularly useful when direct visual observation is prevented by meteorological conditions. This eruption shows the importance of combining multiple data sets when monitoring volcanoes. Combining gas and seismic data sets allowed for a much more accurate assessment of the eruption than either could have done alone.

Emission Characteristics of Fine Particles in Relation to Precursor Gases in Agricultural Emission Sources: A Case Study of Dairy Barns

Recently, precursor gases such as ammonia have sparked a growing interest in the secondary formation of particulate matter (PM). Most studies focus on urban areas and scientific data. Studies on precursor gases and PM emitted from agricultural sources are insufficient; thus, this paper presents a field monitoring study conducted from agricultural sources. To estimate the effect of precursor gases for PM2.5 from naturally ventilated dairy barns, correlation analyses were conducted using real-time monitoring data on the mass concentrations of PM2.5, NH3, SO2, NO2, and H2S and meteorological data. In addition to mass concentration, the emission and loading rates were used to closely analyze pollution status. The mass concentrations of PM2.5 and gaseous compounds did not correlate well, whereas the mass emission rates for PM2.5 and gaseous compounds (SO2, NH3, and NO2) correlated well because the unit of the emission rate reflected the ventilation factor. The correlation coefficients between PM2.5 and precursor gas emission rates ranged from 0.72 to 0.89 (R), with the SO2 emission rate exhibiting the highest correlation coefficient (R = 0.89). This correlation implies that SO2 from dairy farms is a dominant species among the gaseous precursors influencing the secondary formation of PM2.5; alternatively, SO2 and PM2.5 are produced from the same sources. The ambient PM2.5 loading rate and barn PM2.5 emission rate—estimated by multivariate linear regression using the gaseous independent variables NH3, SO2, and NO2—revealed high-correlation coefficients (0.60 and 0.92, respectively) with the measured data. At present, most studies investigating the precursor gases of PM in agricultural fields have focused on NH3; however, this study suggests that SO2 is a key factor in PM2.5 pollution. To elucidate the secondary formation of PM from precursor gases in agricultural sources, particulate ammonium, sulfate, nitrate, and chloride, which were not measured in this study, as well as oxidants and intermediates, should be considered in future research.

Statistical source analysis of recurring sulfur dioxide pollution events in a chemical industrial park

The whole process of a retrospective source analysis for a historical SO2 pollution scenario in a chemical industrial park occurred during 2016–2017 is introduced. The case was a recurring SO2 pollution event at one of the monitoring sites (M1) in the park. A total of 68 samples for the SO2 pollution scenario were identified from the measurements at M1. The pollution scenario was identified as a single-source event based on pollution characteristics analysis. The main challenge was that the first-hand support data was only the measurements at one monitor while having many more sources. Statistical source analysis based on Kalman filter algorithm and CALPUFF model together with emission rate constraints and tracer species for source verification were incorporated in the final analysis strategy. Results show that the source of SO2 pollution belonged to a catalytic cracking production unit. The cumulative matching rate of the real source was about 37%, and the average emission rate of SO2 was 47.94 ± 73.27 g/s. It is evident that the comprehensive source analysis strategy established in this study was effective for improving certainty of source localization. The effectiveness of this strategy and the feasibility of simplified source simulation in the absence of detailed source data are discussed in detail.

Wind Speed as a Dominant Source of Periodicities in Reported Emission Rates of Volcanic SO2

AbstractVolcanoes have been found to display periodicities or cyclic trends in a wide range of phenomena. These include the eruptive activity itself, but also in the time series of geophysical and geochemical monitoring data such as volcanic degassing. Here, we test the existence of periodicities of volcanic degassing at 32 volcanoes using the time series of sulfur dioxide (SO2) emission rates from data of the Network for Observation of Volcanic and Atmospheric Change (NOVAC). We use the Lomb‐Scargle periodogram to analyze the SO2 data which allows efficient computation of a Fourier‐like power spectrum from unevenly sampled data. We were able to calculate False‐Alarm Probabilities in 28 of the 32 volcanoes, and we identified significant periodicities in the SO2 emission rates in 17 of the 28 volcanoes. However, we find that most of these periodicities are also present in the plume speeds used to determine SO2 emission rates. Periodicities at about 30–70, ∼120, and ∼180 days were identified at volcanoes located between 16°N and 16°S and are related to intraseasonality and interseasonality in global trade winds and not volcanic in origin. Periodicities between 30 and 70 days in both plume speed and SO2 emission rates are associated to the Madden‐Julian Oscillation that is responsible for intraseasonal variability in the tropical atmosphere. Our study highlights the importance of using local wind data for deriving realistic SO2 emissions and the identification of short‐term periodicity in volcanic behavior.

ASSESSMENT OF AIR POLLUTION SCENARIO IN CEMENT FACTORY: THE MONGLA PORT INDUSTRIAL ESTATE OF BANGLADESH AS A CASE STUDY

Cement industries are responsible for huge amount of air pollution, which is harmful for relevant workers health. This study was carried out to measure the emission rate of SPM, SO2 and NO2 and impact on the workers health of cement factories of the Mongla Port Industrial Estate of Bangladesh. It has been found that the emission rate of SPM, SO2 and NO2 is above the acceptable limit of the Environmental Conservation Rule, 1997 of Bangladesh Government. As a result of air pollution, most of the workers between 15 to 50 years age groups are affected by asthma (34%) and respiratory infection (35%). Bronchitis is a major threat to the workers of above 50 years age. Again, the workers working for the long time in the cement factories are highly susceptible to the diseases like bronchitis, asthma. Except respiratory infection, female workers are more at risk of diseases happened by air pollution than male workers. The results of the study imply that immediate remedial actions are crucial to minimize the air pollution of cement factories and its impact on the workers health.

Forecasting explosions at Sinabung Volcano, Indonesia, based on SO2 emission rates

Dome-building volcanic eruptions are often associated with frequent Vulcanian explosions, which constitute a substantial threat to proximal communities. One proposed mechanism driving such explosions is the sealing of the shallow volcanic system followed by pressurization due to gas accumulation beneath the seal. We investigate this hypothesis at Sinabung Volcano (Sumatra, Indonesia), which has been in a state of eruption since August 2010. In 2013, the volcano began erupting a lava dome and lava flow, and frequent explosions produced eruptive columns that rose many kilometers into the atmosphere and at times sent pyroclastic density currents down the southeast flanks. A network of scanning Differential Optical Absorption Spectrometers (DOAS) was installed on the volcano’s eastern flank in 2016 to continuously monitor SO2 emission rates during daytime hours. Analysis of the DOAS data from October 2016 to September 2017 revealed that passive SO2 emissions were generally lower in the 5 days leading up to explosive events (∼100 t/d) than was common in 5-day periods leading up to days on which no explosions occurred (∼200 t/d). The variability of passive SO2 emissions, expressed as the standard deviation, also took on a slightly wider range of values before days with explosions (0–103 t/d at 1-sigma) than before days without explosions (43–117 t/d). These observations are consistent with the aforementioned seal-failure model, where the sealing of the volcanic conduit blocks gas emissions and leads to pressurization and potential Vulcanian explosions. We develop a forecasting methodology that allows calculation of a relative daily explosion probability based solely on measurements of the SO2 emission rate in the preceding days. We then calculate forecast explosion probabilities for the remaining SO2 emissions dataset (October 2017—September 2021). While the absolute accuracy of forecast explosion probabilities is variable, the method can inform the probability of an explosion occurring relative to that on other days in each test period. This information can be used operationally by volcano observatories to assess relative risk. The SO2 emissions-based forecasting method is likely applicable to other open vent volcanoes experiencing dome-forming eruptions.

Chemical characterization, source apportionment, and health risk assessment of PM2.5 in a typical industrial region in North China.

To clarify the chemical characteristics, source contributions, and health risks of pollution events associated with high PM2.5 in typical industrial areas of North China, manual sampling and analysis of PM2.5 were conducted in the spring, summer, autumn, and winter of 2019 in Pingyin County, Jinan City, Shandong Province. The results showed that the total concentration of 29 components in PM2.5 was 53.4 ± 43.9μg·m-3, including OC/EC, water-soluble ions, inorganic elements, and metal elements. The largest contribution was from the NO3- ion, at 14.6 ± 14.2μg·m-3, followed by organic carbon (OC), SO42-, and NH4+, with concentrations of 9.3 ± 5.5, 9.1 ± 6.4, and 8.1 ± 6.8μg·m-3, respectively. The concentrations of OC, NO3-, and SO42- were highest in winter and lowest in summer, whereas the NH4+ concentration was highest in winter and lowest in spring. Typical heavy metals had higher concentrations in autumn and winter, and lower concentrations in spring and summer. The annual average sulfur oxidation rate (SOR) and nitrogen oxidation rate (NOR) were 0.30 ± 0.14 and 0.21 ± 0.12, respectively, with the highest SO2 emission and conversion rates in winter, resulting in the SO42- concentration being highest in winter. The average concentration of secondary organic carbon in 2019 was 2.8 ± 1.9μg·m-3, and it comprised approximately 30% of total OC. The concentrations of 18 elements including Na, Mg, and Al were between 2.3 ± 1.6 and 888.1 ± 415.2ng·m-3, with Ni having the lowest concentration and K the highest. The health risk assessment for typical heavy metals showed that Pb poses a potential carcinogenic risk for adults, whereas As may pose a carcinogenic risk for adults, children, and adolescents. The non-carcinogenic risk coefficients for all heavy metals were lower than 1.0, indicating that the non-carcinogenic risk was negligible. Positive matrix factorization analysis indicated that coal-burning emissions contributed the largest fraction of PM2.5, accounting for 35.9% of the total. The contribution of automotive emissions is similar to that of coal, at 32.1%. The third-largest contributor was industrial sources, which accounted for 17.2%. The contributions of dust and other emissions sources to PM2.5 were 8.4% and 6.4%, respectively. This study provides reference data for policymakers to improve the air quality in the NCP.

Estimation of ship emission rates at a major shipping lane by long-path DOAS measurements

Abstract. Ships are an important source of SO2 and NOx, which are key parameters of air quality. Monitoring of ship emissions is usually carried out using in situ instruments on land, which depend on favourable wind conditions to transport the emitted substances to the measurement site. Remote sensing techniques such as long-path differential optical absorption spectroscopy (LP-DOAS) measurements can supplement those measurements, especially in unfavourable meteorological conditions. In this study 1 year of LP-DOAS measurements made across the river Elbe close to Hamburg (Germany) have been evaluated. Peaks (i.e. elevated concentrations) in the NO2 and SO2 time series were assigned to passing ships, and a method to derive emission rates of SO2, NO2 and NOx from those measurements using a Gaussian plume model is presented. A total of 7402 individual ship passages have been monitored, and their respective NOx, SO2 and NO2 emission rates have been derived. The emission rates, coupled with the knowledge of the ship type, ship size and ship speed, have been analysed. Emission rates are compared to emission factors from previous studies and show good agreement. In contrast to emission factors (in grams per kilogram fuel), the derived emission rates (in grams per second) do not need further knowledge about the fuel consumption of the ship. To our knowledge this is the first time emission rates of air pollutants from individual ships have been derived from LP-DOAS measurements.

On the Ship Particle Number Emission Index: Size‐Resolved Microphysics and Key Controlling Parameters

AbstractShipping particle number emission is important as it can influence cloud condensation nuclei abundance and thus indirectly affect clouds and perturb the Earth's radiation budget. Here, we integrate a size‐resolved Advanced Particle Microphysics module with a photochemical BOX MOdeling eXtension to the Kinetic PreProcessor and employ the resulting model to understand the microphysical and chemical characteristics of ship plumes. Simulated concentrations of key gaseous species and particle numbers are in good agreement compared with measurements from the NOAA Intercontinental Transport and Chemical Transformation (ITCT) 2K2 field study off the California coast. Further analysis reveals that significant new particle formation can occur in the plume and the growth of these secondary particles to 5–20 nm generally dominates the total particle numbers. We show that wind speed, emission rates of SO2 and NOx, solar irradiation, ambient temperature, and background [NH3] have strong nonlinear effects on the ship particle number emission index (EIPN). Depending on the ambient air and meteorological conditions, the model simulations show that EIPN can range from ∼2.5 × 1014 no. kg−1 fuel (dominated by primary particles) to ∼3.0 × 1018 no. kg−1 fuel (dominated by secondary particles). In consideration of the current worldwide expansion of Emission Control Areas, we systematically study how the EIPN decreases with reduction of fuel sulfur content to 0.1%. Our study highlights the necessity of accounting for the nonlinear dependence of secondary particle formation on key controlling parameters in calculating shipping particle number emissions, which is important for determining aerosol indirect climate effects.

A multi-purpose, multi-rotor drone system for long-range and high-altitude volcanic gas plume measurements

Abstract. A multi-rotor drone has been adapted for studies of volcanic gas plumes. This adaptation includes improved capacity for high-altitude and long-range, real-time SO2 concentration monitoring, long-range manual control, remotely activated bag sampling and plume speed measurement capability. The drone is capable of acting as a stable platform for various instrument configurations, including multi-component gas analysis system (MultiGAS) instruments for in situ measurements of SO2, H2S, and CO2 concentrations in the gas plume and portable differential optical absorption spectrometer (MobileDOAS) instruments for spectroscopic measurement of total SO2 emission rate, remotely controlled gas sampling in bags and sampling with gas denuders for posterior analysis on the ground of isotopic composition and halogens. The platform we present was field-tested during three campaigns in Papua New Guinea: in 2016 at Tavurvur, Bagana and Ulawun volcanoes, in 2018 at Tavurvur and Langila volcanoes and in 2019 at Tavurvur and Manam volcanoes, as well as in Mt. Etna in Italy in 2017. This paper describes the drone platform and the multiple payloads, the various measurement strategies and an algorithm to correct for different response times of MultiGAS sensors. Specifically, we emphasize the need for an adaptive flight path, together with live data transmission of a plume tracer (such as SO2 concentration) to the ground station, to ensure optimal plume interception when operating beyond the visual line of sight. We present results from a comprehensive plume characterization obtained during a field deployment at Manam volcano in May 2019. The Papua New Guinea region, and particularly Manam volcano, has not been extensively studied for volcanic gases due to its remote location, inaccessible summit region and high level of volcanic activity. We demonstrate that the combination of a multi-rotor drone with modular payloads is a versatile solution to obtain the flux and composition of volcanic plumes, even for the case of a highly active volcano with a high-altitude plume such as Manam. Drone-based measurements offer a valuable solution to volcano research and monitoring applications and provide an alternative and complementary method to ground-based and direct sampling of volcanic gases.