Duff burning from wildfires in a moist region: different impacts on PM_2.5 and ozone

Wildfires can significantly impact air quality and human health. However, little is known about how different fuel bed components contribute to these impacts. This study investigates the air quality impacts of duff and peat consumption during wildfires in the southeastern United States, with a focus on the differing contributions of fine particulate matter less than 2.5 µm in size (PM2.5) and ozone (O3) to air quality episodes associated with the four largest wildfire events in the region during this century. The emissions of duff burning were estimated based on a field measurement of a 2016 southern Appalachian fire. The emissions from the burning of other fuels were obtained from the Fire INventory from NCAR (FINN). The air quality impacts were simulated using a three-dimensional regional air quality model. The results show the duff burning emitted PM2.5 comparable to the burning of the above-ground fuels. The simulated surface PM2.5 concentrations due to duff burning increased by 61.3 % locally over a region approximately 300 km within the fire site and by 21.3 % and 29.7 % in remote metro Atlanta and Charlotte during the 2016 southern Appalachian fires and by 131.9 % locally and by 17.7 % and 24.8 % in remote metro Orlando and Miami during the 2007 Okefenokee Fire. However, the simulated ozone impacts from the duff burning were negligible due to the small duff emission factors of ozone precursors such as NOx. This study suggests the need to improve the modeling of PM2.5 and the air quality, human health, and climate impacts of wildfires in moist ecosystems by including duff burning in global fire emission inventories.

Recent advances and perspectives in the resistance of SO2 and H2O of Cerium-based catalysts for NOx selective catalytic reduction with ammonia

NOx is one of the most serious air contaminations, which mainly comes from fixed sources and have great negative impact on public health and regional air quality. The treatment of...

The effect of national protest in Ecuador on PM pollution

Particulate matter (PM) accounts for millions of premature deaths in the human population every year. Due to social and economic inequality, growing human dissatisfaction manifests in waves of strikes and protests all over the world, causing paralysis of institutions, services and circulation of transport. In this study, we aim to investigate air quality in Ecuador during the national protest of 2019, by studying the evolution of PM2.5 (PM ≤ 2.5 µm) concentrations in Ecuador and its capital city Quito using ground based and satellite data. Apart from analyzing the PM2.5 evolution over time to trace the pollution changes, we employ machine learning techniques to estimate these changes relative to the business-as-usual pollution scenario. In addition, we present a chemical analysis of plant samples from an urban park housing the strike. Positive impact on regional air quality was detected for Ecuador, and an overall − 10.75 ± 17.74% reduction of particulate pollution in the capital during the protest. However, barricade burning PM peaks may contribute to a release of harmful heavy metals (tire manufacture components such as Co, Cr, Zn, Al, Fe, Pb, Mg, Ba and Cu), which might be of short- and long-term health concerns.

Duff burning from wildfires in a moist region: different impacts on PM_2.5 and Ozone

Wildfires can significantly impact air quality and human health. However, little is known about how duff and peat burning contributes to these impacts. This study investigates the air quality impacts of duff consumption during the four largest wildfire events this century in southeastern United States, with a focus on the different impacts on fine particulate matter less than 2.5 μm in size (PM2.5) and ozone (O3). The emissions of duff burning were estimated based on a field measurement. The emissions from the burning of other fuels were obtained from the Fire INventory from NCAR (FINN). The air quality impacts were simulated using a 3-D regional air quality model. The results show the duff burning emitted PM2.5 comparable to the burning of the above-ground fuels. The simulated surface PM2.5 concentrations due to duff burning increased by 61.3 % locally over a region approximately 300 km within the fire site and by 21.3 % and 29.7 % in the remote metro Atlanta and Charlotte during the 2016 southern Appalachian fires, and by 131.9 % locally and by 17.7 % and 24.8 % in the remote metro Orlando and Miami during the 2007 Okefenokee fire. However, the simulated ozone impacts from the duff burning were negligible due to the small duff emission factors of ozone precursors such as NOx. This study suggests the need to improve the modeling of PM2.5 and the air quality, human health, and climate impacts of wildfires in moist ecosystems by including duff burning in global fire emission inventories.

Satellite Observation of Spatio-temporal Variations in Nitrogen Dioxide over West Africa and Implications for Regional Air Quality

Background. Nitrogen dioxide (NO2) is known to affect human health, causing heart and cardiovascular diseases, and it has been shown that locations with long term NO2 pollution recorded a high number of fatalities due to the COVID-19 pandemic. There are no ground stations monitoring emissions of NO2 over West Africa. The present study aimed to use satellite observations to examine pollutant trends over this region. Objective. To examine the trend of NO2 over the entire West Africa sub region in relationship to contributions to environmental emissions using satellite-derived data. This enables the assessment of West Africa regional air pollution hot spots in relationship to enhancing atmospheric factors. The results from this study will also be useful guidance for setting air quality standards for air pollution controls to minimize health hazards. Methods. The present study examined thirteen years of average monthly values of nitrogen dioxide (NO2) to determine the spatio-temporal variation of this pollutant over West Africa. Satellite data for NO2 between 2005 and 2017 were used to determine the variation in pollution levels over West Africa. Correlations between NO2 and meteorological variables (wind speed, rainfall and air temperature) were obtained to explain the influence of West African weather on the region's pollution accumulation. Results. The present study observed that NO2 concentrations varied from place to place and from season to season. Nitrogen dioxide concentrations during the dry season were higher (sometimes 200% higher) than values observed in the wet season which ranged between 0.5 and 6×1015 molec/cm2. Nitrogen dioxide north-south oscillation during the course of a year is largely controlled by the inter-tropical discontinuity (ITD) zone as high concentrations of NO2 are found in the vicinity of the ITD where wind speeds and horizontal vorticity approaches zero. Correlation analysis between NO2 and some atmospheric variables indicated NO2 concentrations are well influenced by atmospheric variables showing bipolar signals depending on the season. An increasing trend of NO2 was also found over selected cities of the region. This indicated that regional air quality is gradually deteriorating. Conclusions. The implications of worsening regional air quality were examined in the light of the prevailing COVID-19 pandemic. The dominant atmospheric factor determining pollution episodes in the region is the inter-tropical discontinuity line which marks the meeting point between the two wind regimes over the region. Densely populated areas are characteristically prone to elevated pollution and have experienced high fatalities during the COVID-19 pandemic. Competing Interests. The authors declare no competing financial interests.

Surface And Aloft NO2 Pollution Over The Greater Tokyo Area Observed By Ground-Based And MAX-DOAS Measurements Bridged By Regional Air Quality Modeling

To advance our understanding of surface and aloft nitrogen dioxide (NO2) pollution, this study extensively evaluated NO2 concentrations simulated by the regional air quality modeling system with a horizontal grid resolution of 1.3 km by using the Atmospheric Environmental Regional Observation System (AEROS) ground-based observation network and aloft measurement by multi-axis differential optical absorption spectroscopy (MAX-DOAS) over the greater Tokyo area. Observations are usually limited to the surface level, and gaps remain in our understanding of the behavior of air pollutants above the near-surface layer, particularly within the planetary boundary layer (PBL). Therefore, MAX-DOAS measurement was used, which observes scattered sunlight in the ultraviolet/visible range at several elevation angles between the horizon and zenith to determine the aloft NO2 pollution averaged over 0-1 km. In total, four MAX-DOAS measurement systems at Chiba University (35.63°N, 140.10°E) systematically covered the north, east, west, and south directions to capture the aloft NO2 pollution over the greater Tokyo area. The target period was Chiba-Campaign 2015 conducted from 9 to 23 November 2015. The evaluations showed that the air quality modeling system can generally capture the observed behavior of both surface and aloft NO2 pollution in terms of spatial and temporal coverage. The diurnal variation, which typically showed an increase from evening to early morning without daylight and a decrease during the daytime, was also captured by the model. During Chiba-Campaign 2015, two cases of episodic higher NO2 concentration were identified: one during the nighttime and the other during the daytime as different diurnal patterns. These were related to a stagnant wind field, with the latter also connected to a lower PBL height in cloudy conditions. Comparison of the modeled surface and aloft NO2 concentrations showed that aloft NO2 concentration exhibited a strong linear correlation with surface NO2 concentration, with the aloft value scaled to 0.4-0.5-fold the surface value, irrespective of whether the day was clean or polluted. This scaling value was lower during the nighttime and higher during the daytime. Based on this synergetic analysis of surface and aloft observation bridged by modeling simulation, this study contributes to fostering understanding of aloft NO2 pollution.

SAMIRA-SAtellite Based Monitoring Initiative for Regional Air Quality

The satellite based monitoring initiative for regional air quality (SAMIRA) initiative was set up to demonstrate the exploitation of existing satellite data for monitoring regional and urban scale air quality. The project was carried out between May 2016 and December 2019 and focused on aerosol optical depth (AOD), particulate matter (PM), nitrogen dioxide (NO2), and sulfur dioxide (SO2). SAMIRA was built around several research tasks: 1. The spinning enhanced visible and infrared imager (SEVIRI) AOD optimal estimation algorithm was improved and geographically extended from Poland to Romania, the Czech Republic and Southern Norway. A near real-time retrieval was implemented and is currently operational. Correlation coefficients of 0.61 and 0.62 were found between SEVIRI AOD and ground-based sun-photometer for Romania and Poland, respectively. 2. A retrieval for ground-level concentrations of PM2.5 was implemented using the SEVIRI AOD in combination with WRF-Chem output. For representative sites a correlation of 0.56 and 0.49 between satellite-based PM2.5 and in situ PM2.5 was found for Poland and the Czech Republic, respectively. 3. An operational algorithm for data fusion was extended to make use of various satellite-based air quality products (NO2, SO2, AOD, PM2.5 and PM10). For the Czech Republic inclusion of satellite data improved mapping of NO2 in rural areas and on an annual basis in urban background areas. It slightly improved mapping of rural and urban background SO2. The use of satellites based AOD or PM2.5 improved mapping results for PM2.5 and PM10. 4. A geostatistical downscaling algorithm for satellite-based air quality products was developed to bridge the gap towards urban-scale applications. Initial testing using synthetic data was followed by applying the algorithm to OMI NO2 data with a direct comparison against high-resolution TROPOMI NO2 as a reference, thus allowing for a quantitative assessment of the algorithm performance and demonstrating significant accuracy improvements after downscaling. We can conclude that SAMIRA demonstrated the added value of using satellite data for regional- and urban-scale air quality monitoring.