Atmospheric SO2 Concentrations Research Articles

Measuring The Spatio-Temporal Distribution of Sulfur Dioxide (SO2) with Copernicus Sentinel-5P Near Real Time in Medan City

This study aims to monitor the impact of sulfur dioxide (SO2), a significant contributor to atmospheric corrosion and associated with air pollution, in urban and industrial areas through empirical models of spatial distribution and temporal estimation in Medan. Datasets of Sentinel 5P NRTI are worth using to monitor the formation of sulfate aerosols or SO2 emissions from natural sources and anthropogenic origin in near real-time from 2019 until 2023 on the local scale, Medan. The source dataset covers 1,11 km of spatial image resolution on orbital in daily revisit time with a spectral bound between the ultraviolet and the shortwave infrared. The measurement of atmospheric SO2 concentrations is generated by enumerating the SO2 vertical column density technique at the soil surface with the cloud-based platform The Earth Engine (EE) Code Editor to handle large data sizes and produce interactive mapping. Based on the availability of auxiliary results, the number of spreading SO2 concentrations fell from 0,92 mmol/m2 in 2019 to 0,41 mmol/m2 in 2023, a reduction of 49.98 percent. The average of SO2 concentrations has decreased substantially over the years. Consequently, these pollutants have recorded long-term health and meteorological parameters impact that substances can rise or reduce acid rain.Keywords: Air pollution, Meteorological parameters, Sentinel 5P NRTI, SO2

Environmental science through orbiters. An example of Sentinel-5P on how the Covid-19 pandemic impacted the air quality

Due to the lockdown caused by the SARS-CoV-2 coronavirus disease (a.k.a. COVID-19) pandemic in 2020, most industrial and social activity drastically stopped. This drastic fall in human and industrial activity might have caused a drastic fall in the concentration of important atmospheric pollutants. This study investigates whether the atmospheric concentration of NO2, CO, HCOOH, CH4, SO2 and O3 changed during this extraordinary situation. Secondly, this manuscript demonstrates how orbiter data can be freely used to endeavour any research question and the usefulness of multivariate data analysis in analyzing such data. The data used was the European Space Agency Copernicus Sentinel-5P satellite (SP5). Besides, the molecular concentration found with S5P was compared with the ground meteorological stations of the Basque Government, Spain. Concerning the individual evolution of the molecular concentrations found with SP5, no significant differences were obtained for the abovementioned molecules for the same period (from January until June) in different years (2019 and 2020) using ANOVA. The average concentration between years and their respective relative standard deviations were in the same range. Nevertheless, Principal Component Analysis applied to the time series demonstrated significant changes in the overall behaviour of the monitored pollutants.

Forest growth responds more to air pollution than soil acidification.

The forests of central Europe have undergone remarkable transitions in the past 40 years as air quality has improved dramatically. Retrospective analysis of Norway spruce (Picea abies) tree rings in the Czech Republic shows that air pollution (e.g. SO2 concentrations, high acidic deposition to the forest canopy) plays a dominant role in driving forest health. Extensive soil acidification occurred in the highly polluted "Black Triangle" in Central Europe, and upper mineral soils are still acidified. In contrast, acidic atmospheric deposition declined by 80% and atmospheric SO2 concentration by 90% between the late 1980s and 2010s. In this study we oserved that annual tree ring width (TRW) declined in the 1970s and subsequently recovered in the 1990s, tracking SO2 concentrations closely. Furthermore, recovery of TRW was similar in unlimed and limed stands. Despite large increases in soil base saturation, as well as soil pH, as a result of repeated liming starting in 1981, TRW growth was similar in limed and unlimed plots. TRW recovery was interrupted in 1996 when highly acidic rime (originating from more pronounced decline of alkaline dust than SO2 from local power plants) injured the spruce canopy, but recovered soon to the pre-episode growth. Across the long-term site history, changes in soil chemistry (pH, base saturation, Bc/Al soil solution ratio) cannot explain observed changes in TRW at the two study sites where we tracked soil chemistry. Instead, statistically significant recovery in TRW is linked to the trajectory of annual SO2 concentrations or sulfur deposition at all three stands.

Investigating the hygroscopicities of calcium and magnesium salt particles aged with SO2 using surface plasmon resonance microscopy

The hygroscopicities of calcium and magnesium salts strongly affect the environment and climate, but the aging products of these salts at high relative humidities (RHs) are still poorly understood. In this study, surface plasmon resonance microscopy (SPRM) was used to determine the hygroscopic growth factors (GFs) of Ca(NO3)2 and Mg(NO3)2 separately or mixed with galactose at different mass ratios at different RHs before and after aging. For all particles, the measured GFs showed no indication of deliquescence across the range of RHs tested, and overall hygroscopicity was clearly lower after than before aging. The Ca(NO3)2 and Mg(NO3)2 GFs at 90 % RH were 1.80 and 1.66, respectively, before aging and 1.33 and 1.42, respectively, after 4 h aging, meaning aging decreased the GFs by 26.11 % and 14.46 %, respectively. Aging decreased the hygroscopicity because insoluble or sparingly soluble substances (CaSO3, CaSO4, MgSO3) formed and strongly changed the overall hygroscopicity. For bicomponent aerosols with different mass ratios, the GFs (calculated using the Zdanovskii-Stokes-Robinson method) of the other components except galactose at 90 % RH after 1 h aging were all lower, respectively, than the measured GFs of pure Ca(NO3)2 and Mg(NO3)2 after aging for 1 h, especially with the mass ratio of 1:2, their GFs have decreased by 14.63 % and 7.50 %, respectively. Subsequently, Ion chromatograms indicated that the peak area ratio of SO42− to NO3− ratios were higher for the aged bicomponent particles than aged single-component particles, possibly because adding galactose improved the gas–liquid state stability during drying after the aging process and therefore promoted nitrate consumption and sulfate formation. The results indicated that organic components may play important roles in heterogeneous reactions between trace gases and multicomponent aerosols and should be considered in evaluating the impacts on submicron aerosol composition of high atmospheric SO2 concentrations at high humidities.

Modelling land use/land cover (LULC) change dynamics, future prospects, and its environmental impacts based on geospatial data models and remote sensing data.

The dynamic change in land use/land cover (LULC) caused by rapid urbanizationhas become a major concern in Lahore, causing a variety of socioeconomic and environmental issues relating to air quality. As a result, it is important to monitor existing LULC change detection, future projection, and the increase in atmospheric pollutants in Lahore. This research work makes use of Landsat, GIOVANNI, SRTM DEM, and vector data. The four key steps of the research approach are as follows: (i) LULC classification from 2000 to 2020 using Lansat data and semi-automatic classification plugin (SCP); (ii) simulation of future prediction using Modules of Land Use Change Evaluation (MOLUSCE) prediction model; (iii) assessment of effects of land use change on air quality using GIOVANNI-NASA product; and (iv) monitoring, change detection, and result interpretation. According to the research findings, there was an increase in metropolitan areas and a decrease in vegetation, barren land, and water bodies for both historical and future projections. The findings also indicated that from 2000 to 2020, about 27.41% of the urban area expanded, with a decline of 42.13% in vegetation, 2.3% in the barren land, and 6.51% in water bodies, respectively. Between 2020 and 2040, the urban area is predicted to increase by 23.15%, while vegetation, barren land, and water bodies are expected to decrease by 28.05%, 1.8%, and 12.31%, respectively. Also, the atmospheric pollutants have been increased including NO2 (1.60%), SO2 (1.02%), CO2 (0.71%), CO (1.56%), O3 (0.15%), and CH4 (0.20%), respectively. And it is projected that by 2040, the average annual atmospheric concentration of NO2, SO2, CO2, CO, O3, and CH4 will be increased by 28.80%, 18.36%, 12.78%, 28.08%, 2.70%, and 3.60%, respectively. In addition, it was also observed that the majority of the city's urban area expansion was found in the city's eastern and southern regions. Therefore, government should focus on natural resource conservation especially vegetation cover to reduce air pollutants concentration and the LULC effect.

Shift of major driver for chemical weathering from the natural control to human dominance since 1980s in the Taihu watershed, China.

Anthropogenic acidification has become a concerned problem in the Taihu region; however, how it affected the regional weathering rate, especially at the different sub-watershed levels has hardly been studied. To reveal the impact of human activities on watershed weathering and water chemistry in Taihu sub-watersheds, historical water chemistry data (1950s-1970s) and recent water samples (2018-2021) of the local river systems, as well as sediment samples of Taihu lake were collected and analyzed, and a linear addition mass balance method was used to determine the weathering rate at the sub-watershed level. The results indicated that, compared with 60years ago, the current weathering rate of carbonates and silicates in the Taoge water system (TG) was the highest, reaching 67.2 and 11.4 t·km-2·a-1, increasing by 4.1 and 2.7-folds, respectively; and meanwhile the carbonate and silicate weathering rates increased by 3.1 and 4.9-folds in the Nanhe water system (NH), and 5.2 and 3.4-folds in the Tiaoxi water system (TX), respectively. The increasing rate was significantly correlated to the atmospheric SO2 concentration in different sub-watersheds and was affected by the sub-watershed lithology, e.g., TX had a higher increase rate of silicate weathering due to the wider distribution of silicates in this sub-watershed than the other two. The sediment evidence of Na/K and Ca/Al on the profile in different lake parts, which was influenced by different influx river systems, confirmed that the overall intensity of watershed weathering was higher in TG than in the TX sub-watershed and was higher in the recent decade than 50-60years ago. The accelerated weathering rate was found to present a definite consistency with the social and economic development in the watershed. Combined analyses of the accelerated weathering rate in the watershed and sedimentation evidence indicated that the major driving force for the watershed weathering has shifted from carbonic acid under the natural condition to human-induced sulfuric acid since 1980s.

Greenwashing in the US metal industry? A novel approach combining SO2 concentrations from satellite data, a plant-level firm database and web text mining

This study deals with the issue of greenwashing, i.e. the false portrayal of companies as environmentally friendly. The analysis focuses on the US metal industry, which is a major emission source of sulfur dioxide (SO2), one of the most harmful air pollutants. One way to monitor the distribution of atmospheric SO2 concentrations is through satellite data from the Sentinel-5P programme, which represents a major advance due to its unprecedented spatial resolution. In this paper, Sentinel-5P remote sensing data was combined with a plant-level firm database to investigate the relationship between the US metal industry and SO2 concentrations using a spatial regression analysis. Additionally, this study considered web text data, classifying companies based on their websites in order to depict their self-portrayal on the topic of sustainability. In doing so, we investigated the topic of greenwashing, i.e. whether or not a positive self-portrayal regarding sustainability is related to lower local SO2 concentrations. Our results indicated a general, positive correlation between the number of employees in the metal industry and local SO2 concentrations. The web-based analysis showed that only 8% of companies in the metal industry could be classified as engaged in sustainability based on their websites. The regression analyses indicated that these self-reported ”sustainable” companies had a weaker effect on local SO2 concentrations compared to their “non-sustainable” counterparts, which we interpreted as an indication of the absence of general greenwashing in the US metal industry. However, the large share of firms without a website and lack of specificity of the text classification model were limitations to our methodology.

Environmental Effects among Differently Located and Fertile Sites on Forest Basal-Area Increment in Temperate Zone

Environmental properties differently influence the growth of forest tree species. The antagonistic effects of variable environmental properties classify the forest response according to various tree compositions among different sites. The division of the forest response was assessed in 52 stands arranged into 26 types of 13 site management populations (MPs) in 5 areas in the Czech Republic territory. The assessment was performed using time-series multiple regressions of basal-area increment from pure immature stands of Norway spruce (Picea abies), Scots pine (Pinus sylvestris), oaks (Quercus sp.), ash (Fraxinus excelsior) and willows (Salix sp.) dependent on the interpolated average temperatures, annual precipitation, atmospheric concentrations of SO2, NOx and O3 and soil properties over the period 1971–2008 at p < 0.05. Site MPs differentiated the forest response to a greater extent than tree species. The response of the forests was significantly distributed by means of the montane, upland and waterlogged sites. The multiple determination index (r2) ≥ 0.6 indicated an adaptable tree increment but an interval of r2 between 0.80–0.92 implied forest sensitivity to variability in environmental properties on non-waterlogged sites. The index r2 < 0.6 suggested a fluctuating forest increment that reflects environmental variability inconsistently. The fluctuating increment most affected the spruce and pine stands grown from upland to submontane locations. Montane spruce stands, as well as rock pines, appeared to be one of the most sensitive ones to environmental change. Floodplain forests seemed as adaptable to variable environmental properties.

Airborne microbial community structure and potential pathogen identification across the PM size fractions and seasons in the urban atmosphere

As a vital component of airborne bioaerosols, bacteria and fungi seriously endanger human health as pathogens and allergens. However, comprehensive effects of environmental variables on airborne microbial community structures remain poorly understood across the PM sizes and seasons. We collected atmospheric PM1.0, PM2.5, and PM10 samples in Hefei, a typical rapidly-developing city in East China, across three seasons, and performed a comprehensive analysis of airborne microbial community structures using qPCR and high-throughput sequencing. Overall the bacterial and fungal abundances in PM1.0 were one to two orders of magnitude higher than those in PM2.5 and PM10 across seasons, but their α-diversity tended to increase from PM1.0 to PM10. The bacterial gene abundances showed a strong positive correlation (P < 0.05) with atmospheric SO2 and NO2 concentrations and air quality index. The bacterial gene abundances were significantly higher (P = 0.001) than fungi, and the bacterial diversity showed stronger seasonality. The PM sizes influenced distribution patterns for airborne microbial communities within the same season. Source-tracking analysis indicated that soils, plants, human and animal feces represented important sources of airborne bacteria with a total relative abundance of more than 60% in summer, but total abundance from the unidentified sources surpassed in fall and winter. Total 10 potential bacterial and 12 potential fungal pathogens were identified at the species level with the highest relative abundances in summer, and their abundances increased with the PM sizes. Together, our results indicated that a complex set of environmental factors, including water-soluble ions in PM, changes in air pollutant levels and meteorological conditions, and shifts in the relative importance of available microbial sources, acted to control the seasonal compositions of microbial communities in the urban atmosphere.

Research on two methods of atmospheric environmental impact assessment a case study of lead zinc smelter

Two methods of atmospheric environmental impact assessment for enterprises were discussed in this paper. One was the pollutant contribution rate assessment based on regional maximum value point and sensitive sites, the other was the global pollutant contribution rate assessment method based on all grids in the region. The emission contributions to the atmospheric SO2 concentrations from the lead zinc smelting enterprise were simulated by AERMOD using 100m scale grids within 25 square kilometres in 2018. The results showed that the change of environmental benefits caused by the increase of chimney height presented different trends by using the two assessment method, and the regional assessment method was disturbed by the terrain factor. The further research should be doing in order to reflect the pollution diffusion of emission contributions better.

Comparison of static MLP and dynamic NARX neural networks for forecasting of atmospheric PM10 and SO2 concentrations in an industrial site of Turkey

This study aims to compare performances of two static and one dynamic neural networks used for prediction of hourly ambient air quality concentrations in an industrial site of Turkey. Two air pollutants (PM10 and SO2) and three meteorological parameters (ambient air temperature, relative humidity, and wind speed) were used as input variables. The predictions of the dynamic nonlinear autoregressive exogenous (NARX) model were compared with the predictions of the static multilayer perceptron (MLP) neural network model. The results showed that the predictions of the NARX neural network were obviously better than the predictions of MLP networks. The coefficient of determination (R2), index of agreement and efficiency between the observed and predicted air pollutant concentrations by the NARX model were 0.9773, 0.994, and 0.977 for PM10, respectively while the same parameters were 0.9984, ≈1, and ≈1 for SO2. The MBEs (mean bias errors) were also approximately zero for both pollutants that indicate the adequacy of the model. The values of RMSE (root mean squared error) were also fractional as 0.0191 and 0.0087 for both pollutants. The NARX model predicted SO2 concentrations better than PM10 concentrations. In comparison with MLP network structures, NARX network exhibits faster convergence. The model suggested in this study could be used to support and improve air quality management practices.

Road impact in a protected area with rich biodiversity: the case of the Sebitoli road in Kibale National Park, Uganda.

While road network expansion is crucial for economic development, it can cause a notable disturbance of fauna, especially in protected area in terms of habitat fragmentation, risk of collision, and also indirect threat such as pollution. In this study, we monitored the 4.6-km long tarmac road crossing the Kibale National Park in Uganda, home to a rich variety of wild species including the endangered chimpanzees. We evaluated the effects of collisions and pollution, as well as the impact of the renovation process in terms of disturbance and the mitigation measures deployed. This survey reports the death of 24 wild animals killed by cars, including two chimpanzees. The atmospheric concentrations of O3, NO2, SO2, and BTEX did not exceed recommended limits. More than 5000 plastic bottles were collected along the road within 4 months, and for the first time, the presence of BPA and BPS was detected in the hairs of wild chimpanzees. The road bisecting the Kibale National Park poses a high danger in terms of traffic and an underestimated risk related to plastic pollution. Measures (signpost, speed bumps) should be urgently deployed to decrease the risk posed by the renovated road for emblematic species such as chimpanzees, which are crucial for tourism and economy in Uganda.

Interaction of spatial sulfur patterns between urban air and woody species of the Pearl River Delta, southern China

Sulfur (S) uptakes by woody plants might indicate the presence of urban air pollution in the form of sulfur dioxide (SO2), which is one of the most important pollutants worldwide. The present study detected total carbon (C) and S contents in the leaf and stem (dry mass) of 53 common woody species in representative forest plots in five cities across the Pearl River Delta (PRD), a densely urbanized region in Southern China. Coupling analysis explored whether spatial patterns of S content in woody species were relatively consistent with atmospheric SO2 concentration in the five PRD cities. Total S content varied in leaves and stems with averages of 2.0 g/kg and 0.8 g/kg, respectively, while air SO2 concentration ranged from 9.0 to 108.0 g/m3. However, total C content was relatively constant among all the species across the diverse forest plots, with an average of 443.5 g/kg and a median of 448.0 g/kg in leaves and 437.0 g/kg in stems. This suggests that air SO2 pollution did not influence tree growth, so afforestation may be an effective method of eliminating urban air pollution in the PRD.

Surface lanthanide activator doping for constructing highly efficient energy transfer-based nanoprobes for the on-site monitoring of atmospheric sulfur dioxide.

The sensitive and on-site detection of sulfur dioxide (SO2) is in great demand in the fields of food safety and environmental protection. Here, we developed a novel upconversion nanoprobe based on the luminescence energy transfer mechanism for monitoring the atmospheric SO2 concentrations. The lanthanide emitters, Tm3+ ions, were optimized to be doped on the surface layer of the upconversion nanoparticles to improve their energy transfer efficiency by minimizing the distance between the emitters and the surface quencher, a cyanine dye. As a proof-of-concept, the optimal nanoprobe was utilized to detect SO2 water derivatives, bisulfite ions, exhibiting a linear luminescence increase in the range of 1 nM to 10 nM. Furthermore, we assembled the cyanine-modified upconversion nanoparticles onto a test paper, and used a smartphone-based detection platform to achieve portable and visual detection of SO2. The test paper showed a strong luminescence stability, homogeneity and good anti-interference. The limit of detection for SO2 gas was found to be 1 ng L-1. This novel upconversion test paper was also demonstrated to directly monitor the concentration of SO2 gas in atmosphere.

The oxygen and sulfur isotopic compositions of soluble sulfate in the needles of Pinus massoniana Lamb.: Source discrimination and contribution estimation

In order to identify the sources of sulfate in plant leaves, needles of Pinus massoniana Lamb. were collected from Guiyang (an area seriously affected by acid rain) and Yunnan areas (where acid rain barely occurred) in southwestern China to measure the isotopic compositions of the water-soluble sulfate (δ34SSO4 and δ18OSO4) and leaf water (δ18OH2O). Compared to atmospheric sulfate, all needle samples were quite depleted in 18O, indicating that sulfate in needles was rarely derived from atmospheric sulfate. The δ18OSO4 values in the needles (−5.3‰) were similar to those in the soil (−5.2‰) in the uncontaminated mountain area of Jinning, suggesting that sulfate in needles originated mainly from soil sulfate in barely SO2 pollution areas. However, the δ18OSO4 values in the needles were significantly more negative than that of soil in most areas with relatively severe SO2 pollution, and the δ18OSO4 values in the needles were positively correlated with the δ18OH2O values of leaf water, indicating that a substantial part of the sulfate in the needles might be derived from atmospheric SO2 oxidation in polluted areas. The estimated contributions of atmospheric SO2 oxidation to the sulfate in the needles increased significantly with increasing atmospheric SO2 and needle sulfate concentration. When the atmospheric SO2 concentrations were >30 μg m−3, the contributions of SO2 to needle sulfate were >50%. The δ18OSO4 values in needles decreased obviously with the increase of the distance from both the Steel Plant and the Power Plant, implying that part of needle sulfate likely to be derived from primary sulfate which generated in the industrial plant flues and secondary sulfate which generated in atmosphere.

Deposition, abatement and environmental fate of pollutants in urban green ecosystems: Suggestions from long-term studies in Siena (Central Italy)

Long-term biomonitoring of atmospheric pollutants in Siena shows that organisms in urban ecosystems are an overlooked source of information on the deposition and environmental fate of chemicals that are not measured by automatic monitoring devices. Quercus ilex leaves and epiphytic lichens intercept airborne particulates and can be used as reliable quantitative biomonitors of metal deposition. Soils beneath holm oak trees have an enhanced sink capacity for metals and a noteworthy faunal diversity. Earthworms and land snails inhabiting those soils can help to evaluate metal bioavailability, their potential trophic transfer and health risks. Biological crusts, mosses and mollusks from vegetated urban walls appear even more reliable biomonitors of metal deposition. Although Siena is a town with its own architectural and climatic features and moderate atmospheric pollution mainly caused by vehicular traffic and domestic heating, our overview offers suggestions and guidance that can be adapted across different urban contexts, for enhancing the role of urban green ecosystems in the abatement and monitoring of atmospheric pollutants. Comparisons among the capabilities of different tree species to improve urban air quality indicate that in Mediterranean towns it would be difficult to select a better alternative to Q. ilex, although this species emits VOCs and contributes to O3 formation, a pollutant now of major concern. Due to the decreased atmospheric concentrations of SO2 and the scarce sensitivity of lichens to O3, in many towns lichen biodiversity seems no longer a valid indicator of air quality.

Application of ensemble learning techniques to model the atmospheric concentration of SO2.

In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. For model validation, results were compared against widely known single base classifiers such as support vector machine, multilayer perceptron, linear regression and regression tree using M5 algorithm. The prediction of Sulphur dioxide was based on atmospheric pollutants and meteorological parameters. While, the model performance was assessed by using four evaluation measures namely Correlation coefficient, mean absolute error, root mean squared error and relative absolute error. The results obtained suggest that 1) homogenous ensemble classifier random forest performs better than single base statistical and machine learning algorithms; 2) employing single base classifiers within bagging as base classifier improves their prediction accuracy; and 3) heterogeneous ensemble algorithm voting have the capability to match or perform better than homogenous classifiers (random forest and bagging). In general, it demonstrates that the performance of ensemble classifiers random forest, bagging and voting can outperform single base traditional statistical and machine learning algorithms such as linear regression, support vector machine for regression and multilayer perceptron to model the atmospheric concentration of sulphur dioxide.

Changes in United States deposition of nitrogen and sulfur compounds over five decades from 1970 to 2020

Evaluating long-term air quality and deposition trends can demonstrate effectiveness of control strategies and guide future air quality management planning. Observations show a reduction of atmospheric concentrations of NOx and SOx species and their wet and dry deposition since monitoring began in 1978 and 1987, respectively, although deposition observations are sparse. This study used a regional model (CAMx) nested within a global model (GEOS-Chem) to characterize regional changes in sulfur and nitrogen deposition due to intercontinental transport and local/regional anthropogenic emissions representing six modeling years spanning five decades (1970–2020). The meteorological year and the natural emissions were fixed at 2005 to isolate the effects of changing anthropogenic emissions. The downward trend from 1970 to 2020 of mean atmospheric SO2 concentration is 1.5–1.8%; of total S deposition is 1.0–1.7%; and of SO2 emissions is 1.4–1.8% per year. The rate of decline in NOy deposition of 0.6–1.4% per year is similar to the 0.5–1.6% per year reduction in NOx emissions, thus showing that the changes in deposition have tracked changes in emissions of SO2 and NOx emissions quite well. Further reducing N deposition could face some challenges due to increasing NHx contribution from NH3 emissions and the expectation of these to increase globally. Our study also examined the transference ratios of NOy and SOx in the context of the secondary NAAQS for NOx and SOx and found them to be sensitive to emission reductions over the study period.

A citizen science approach for monitoring volcanic emissions and promoting volcanic hazard awareness at Sulphur Springs, Saint Lucia in the Lesser Antilles arc

Sulphur Springs Park (SSP), Saint Lucia in the Lesser Antilles is a popular geothermal area with a vigorous passively degassing hydrothermal field. Visitors, staff, and management of the Park have raised concerns about the volcanic emissions and their possible effects on their health. As part of the responsibility of The University of the West Indies Seismic Research Centre (UWI-SRC) to provide volcanic surveillance through its geothermal monitoring programme, a monitoring network was established for quantifying the ambient SO2 concentrations at the Park to assess the potential risk of unsafe exposure. This required the development of a participatory citizen science effort with researchers training local personnel in field sampling and basic analytical techniques to measure SO2 concentrations. The operation of a citizen science network required engagement and collaboration with local stakeholders in Saint Lucia to ensure that the research addressed the needs of all partners. This participatory approach was an effective option for scientists to engage local stakeholders and the wider community as partners in geoscience hazards education.Ambient SO2 concentrations obtained with handmade active air samplers (titrimetric hydrogen peroxide traps) showed that when the atmospheric concentrations of SO2 was lower, the data from the diffusion tubes and the handmade samplers followed a similar pattern. The ambient concentrations measured using the handmade samplers cannot be used as absolute values due to uncertainties related to the input parameters needed for the calculation of SO2 concentrations. However, the data may be useful in identifying areas exposed to elevated SO2 concentrations of potential concern to public health. The samplers proved useful as a tool to promote volcanic hazard awareness and education among the local stakeholders and citizen scientists. Important lessons learned by the research team from participant surveys were that time constraints and personal motivation of volunteers are key factors in the success of the operations of this monitoring network.

Atmospheric concentrations of SO2, NO2, ozone and VOCs in Düzce, Turkey using passive air samplers: Sources, spatial and seasonal variations and health risk estimation

In this research, seasonal and spatial distributions of inorganic and organic pollutants (sulphur dioxide (SO 2 ), nitrogen dioxide (NO 2 ) and ozone (O 3 ) and also volatile organic compounds (VOCs)), were determined by passive sampling technique. Fifty sampling sites were selected considering possible sources in the study area. The sampling area were classified as urban (n = 23), industrial (n = 17) and rural (n = 10) regions. Sampling campaigns were carried out for two-week periods in fall, winter, spring and summer seasons in all regions. Benzene and toluene concentrations were found to be the highest in winter at the traffic-dense sites and lowest concentrations were measured at rural sampling sites in summer. Concentrations of NO 2 were higher at sampling sites with high traffic density in winter. A much uniform distribution was observed for SO 2 in all seasons. However higher levels were observed in winter compared to other seasons due to use of coal for domestic heating. Low O 3 concentrations were measured in winter while higher concentrations were measured in summer. Based on principal component analysis (PCA), four factors (gasoline vehicle emissions, diesel vehicle emissions, industrial emissions and fossil fuel combustion) were identified that could explain about 78% of the system variance of the measured pollutants in the city. Health risk assessment revealed that the safe level of 1 × 10 −6 (United States Environmental Protection Agency's (USEPA) acceptable risk value) was exceeded for benzene in all sampling sites in whole region, but non-carcinogenic risk values were at safe level. • Air pollution in a city surrounded by the mountains in Turkey was investigated. • NO 2 , SO 2 , ozone and VOC concentrations were measured by passive sampling method. • Spatial and seasonal distributions of the pollutants were evaluated by using GIS. • Four factors were identified by PCA. • Cancer risks associated with inhalation of benzene were estimated.