Impact of forest fires on particulate matter and ozone levels during the 2003, 2004 and 2005 fire seasons in Portugal

Effects of forest fire smoke deposition on soil physico-chemical properties and bacterial community

The number of forest fires has increased globally, together with considerable smoke emission that significantly impacts the atmospheric environment and associated ecosystems. Most current studies have focused on the in situ effects of fire on the forest ecosystem. However, the mechanisms by which smoke particles affect adjacent ecosystems are largely unexplored. In this study, a simulated forest fire combustion system was developed to evaluate the effect of different smoke concentrations (control, low and high) on soil physico-chemical properties of adjacent farmland at two soil depths. The abundance and diversity of bacterial community were also determined. The results showed that smoke deposition increased the contents of total carbon (TC), total nitrogen (TN), and total phosphorus (TP) in the 0-10 cm soil layer; however, no significant changes in soil water content (SWC) and pH values was observed. The ACE(Abundance Coverage-based Fastimator) and Chao1 diversity indices of bacterial community generally showed a downward trend whereas the PD_whole_ tree diversity index increased after 180 d of smoke deposition. The relative abundance of Proteobacteria remained stable, while abundance of Firmicutes in soil decreased after 180 d of smoke deposition. Smoke deposition slightly affected the physical and chemical properties of the 10-20 cm soil, but the range of variation of the relative abundance and diversity dominant bacteria exceeded that of the 0-10 cm soil. A significant positive correlation was found between the soil properties and the alpha diversity indices during the first 30 d after smoke deposition; the correlation then decreased gradually. Redundancy analysis revealed that Proteobacteria, Firmicutes, and Actinobacteria were generally positively correlated with TC, TN, and SWC. As a whole, the study reveals that the effects of smoke deposition on soil physico-chemical properties and bacterial community depends on smoke concentration where relatively low concentration appears to be beneficial to soil bacterial community.

Estimating annual GHG and particulate matter emissions from rural and forest fires based on an integrated modelling approach

Rural and forest fires represent one of the most significant sources of emissions in the atmosphere of trace gases and aerosol particles, which significantly impact carbon budget, air quality, and human health. This paper aims to illustrate an integrated modelling approach combining spatial and non-spatial inputs to provide and enhance the estimation of GHG and particulate matter emissions from surface fires using Italy as a case study over the period 2007-2017. Three main improvements characterize the approach proposed in this work: (i) the collection and development of comprehensive and accurate data inputs related to burned area; (ii) the use of the most recent data on fuel type and load; and (iii) the modelling application to estimate fuel moisture, burning efficiency, and fuel consumption considering meteorological factors and combustion phases. On average, Italy's GHG and particulate matter emissions were 2621 Gg yr-1, ranging from a minimum of 772 Gg yr-1 in 2013 to a maximum of 7020 Gg yr-1 in 2007. Emissions from fire disturbances in broadleaf forests, shrublands, and agricultural fuel types account for about 76 % of the total. Results were compared with global and national inventories and showed good agreement, especially considering CO2 and particulate matter. The approach of this study added confidence in emission estimates, and the results can be utilized in decision support systems to address air quality management and fire impact mitigation policies.

Health and economic burden of wildland fires PM2.5-related pollution in Portugal - A longitudinal study

Portugal has been affected by wildland fires that destroy thousands of hectares of forest, causing damage to the environment and to the exposed populations. This study aims to assess the influence of wildland fire emissions on air quality, its effect on population health and the related costs, between 2015 and 2018 in Portugal. The cause-specific mortality due to PM2.5 was calculated considering the exposure for five endpoints in adults, twelve age groups for adults and considering children under five years old. The contribution of wildfire emissions to PM2.5 concentrations in Portugal was assessed through EMEP-MSC/W model. Results showed that the average annual fire emissions of PM2.5, CO, CH4, CO2 and NO2 a significant and continuous increase was observed during the first three years (2015, 2016 and 2017) for all pollutants, followed by a decrease in 2018, with values lower than those observed in 2015. Regarding the long-term exposure to PM2.5 emitted by fires a total of 32, 93, 189 and 31 deaths, corresponding to a cost of 59, 174, 360 and 60 million EUR in 2015, 2016, 2017 and 2018, respectively, were estimated. On the other hand, in the first three years an increase in years of life lost (YLL) values of 496, 1608 and 3092 was observed, corresponding to a cost of 16, 54 and 105 million EUR, respectively, followed by a decrease in 2018 with a YLL of 480, corresponding to a cost of 17 M€.

Examining the status of forest fire emission in 2020 and its connection to COVID-19 incidents in West Coast regions of the United States

Forest fires impact on soil, water, and biota resources. The current forest fires in the West Coast of the United States (US) profoundly impacted the atmosphere and air quality across the ecosystems and have caused severe environmental and public health burdens. Forest fire led emissions could significantly exacerbate the air pollution level and, therefore, would play a critical role if the same occurs together with any epidemic and pandemic health crisis. Limited research is done so far to examine its impact in connection to the current pandemic. As of October 21, nearly 8.2 million acres of forest area were burned, with more than 25 casualties reported so far. In-situ air pollution data were utilized to examine the effects of the 2020 forest fire on atmosphere and coronavirus (COVID-19) casualties. The spatial-temporal concentrations of particulate matter (PM_2.5 and PM₁₀) and Nitrogen Dioxide (NO₂) were collected from August 1 to October 30 for 2020 (the fire year) and 2019 (the reference year). Both spatial (Multiscale Geographically Weighted Regression) and non-spatial (Negative Binomial Regression) analyses were performed to assess the adverse effects of fire emission on human health. The in-situ data-led measurements showed that the maximum increases in PM_2.5, PM₁₀, and NO₂ concentrations (μg/m³) were clustered in the West Coastal fire-prone states during August 1 - October 30, 2020. The average concentration (μg/m³) of particulate matter (PM_2.5 and PM₁₀) and NO₂ was increased in all the fire states severely affected by forest fires. The average PM_2.5 concentrations (μg/m³) over the period were recorded as 7.9, 6.3, 5.5, and 5.2 for California, Colorado, Oregon, and Washington in 2019, increasing up to 24.9, 13.4, 25.0, and 17.0 in 2020. Both spatial and non-spatial regression models exhibited a statistically significant association between fire emission and COVID-19 incidents. Such association has been demonstrated robust and stable by a total of 30 models developed for analyzing the spatial non-stationary and local association. More in-depth research is needed to better understand the complex relationship between forest fire emission and human health.

Atmospheric pollution and mortality in Portugal: Quantitative assessment of the environmental burden of disease using the AirQ+ model

In Portugal, data on mortality rate attributed to household and ambient air pollution are not reported due to shortness and irregularity of the available data series, and therefore, the disclosure of the national progress in reducing the number of deaths and illnesses from air contamination in exposures to multiple pollutants is incomplete. The present work describes the application of the AirQ+ model developed by the WHO to calculate how much of specific health outcomes is attributable to long-term exposure to atmospheric NO₂, PM_2.5, and O₃ in the population of various municipalities in Portugal, from 2010 to 2019. Linear Mixed Models were used for data analysis and have shown that (i) approximately 5000 deaths per year are attributable to exposure to mixtures of NO₂ and PM_2.5; (ii) the spatial distribution of the proportion of deaths attributable to NO₂, PM_2.5 and O₃ shows significant differences between locations, and (iii) that AirQ+ is a useful tool for the purpose of effective Public Health policymaking and reporting on the national progress to implement the 2030 Agenda.

GIS-Based Forest Fire Risk Model: A Case Study in Laoshan National Forest Park, Nanjing

Fire risk prediction is significant for fire prevention and fire resource allocation. Fire risk maps are effective methods for quantifying regional fire risk. Laoshan National Forest Park has many precious natural resources and tourist attractions, but there is no fire risk assessment model. This paper aims to construct the forest fire risk map for Nanjing Laoshan National Forest Park. The forest fire risk model is constructed by factors (altitude, aspect, topographic wetness index, slope, distance to roads and populated areas, normalized difference vegetation index, and temperature) which have a great influence on the probability of inducing fire in Laoshan. Since the importance of factors in different study areas is inconsistent, it is necessary to calculate the significance of each factor of Laoshan. After the significance calculation is completed, the fire risk model of Laoshan can be obtained. Then, the fire risk map can be plotted based on the model. This fire risk map can clarify the fire risk level of each part of the study area, with 16.97% extremely low risk, 48.32% low risk, 17.35% moderate risk, 12.74% high risk and 4.62% extremely high risk, and it is compared with the data of MODIS fire anomaly point. The result shows that the accuracy of the risk map is 76.65%.

Gis and fuzzy logic applied to modelling forest fire risk

Fire risk mapping is a basic planning and protection element. This study presents the application of fuzzy logic in a geographic information system (GIS) as an alternative multi-criteria analysis for determining the areas of highest risk of forest fire in natural forest remnants in the Brazil. In the decision-making process, a set of factors that are relevant to fire safety were identified in the study area. For each input variable chosen for the model, a pertinence function was defined that best described its influence on fire risk. Subsequently, the variables were combined for the presentation of the final fire risk map. Concluded in the study that an increased risk of fire occurs at the wildland - urban interface. A strong relationship was observed between the fire ignition points and proximity to roads and urban areas. The proposed model was efficient to integrate the variables and determine areas of greatest risk.

Population exposure to particulate-matter and related mortality due to the Portuguese wildfires in October 2017 driven by storm Ophelia

In October 2017, hundreds of wildfires ravaged the forests of the north and centre of Portugal. The fires were fanned by strong winds as tropical storm Ophelia swept the Iberian coast, dragging up smoke (together with Saharan dust from north-western Africa) into higher western European latitudes. Here we analyse the long-range transport of particulate matter (PM₁₀) and study associations between PM₁₀ and short-term mortality in the Portuguese population exposed to PM₁₀ due to the October 2017 wildfires, the worst fire sequence in the country over the last decades. We analysed space- and ground-level observations to track the smoke plume and dust trajectory over Portugal and Europe, and to access PM₁₀ concentrations during the wildfires. The effects of PM₁₀ on mortality were evaluated using satellite data for exposure and Poisson regression models. The smoke plume covered most western European countries (including Spain, France, Belgium and the Netherlands), and reached the United Kingdom, where the population was exposed in average to an additional PM₁₀ level of 11.7 µg/m³ during seven smoky days (three with dust) in relation to the reference days (days without smoke or dust), revealing the impact of the wildfires on distant populations. In Portugal, the population was exposed in average to additional PM₁₀ levels that varied from 16.2 to 120.6 µg/m³ in smoky days with dust and from 6.1 to 20.9 µg/m³ in dust-free smoky days. Results suggest that PM₁₀ had a significant effect on the same day natural and cardiorespiratory mortalities during the month of October 2017. For every additional 10 µg/m³ of PM₁₀, there was a 0.89% (95% confidence interval, CI, 0-1.77%) increase in the number of natural deaths and a 2.34% (95% CI, 0.99-3.66%) increase in the number of cardiorespiratory-related deaths. With rising temperatures and a higher frequency of storms due to climate change, PM from Iberian wildfires together with NW African dust will tend to be more often transported into Northern European countries, which may carry health threats to areas far from the ignition sites.

Environmental Particulate Matter Levels during 2017 Large Forest Fires and Megafires in the Center Region of Portugal: A Public Health Concern?

This work characterizes the dimension and the exceptionality of 2017 large- and mega-fires that occurred in the center region of Portugal through the assessment of their impact on the ambient levels of particulate matter (PM10 and PM2.5), retrieved from local monitoring stations, and the associated public health risks. PM10 and PM2.5 concentrations were increased during the occurrence of large fires and megafires, with daily concentrations exceeding the European/national guidelines in 7-14 and 1-12 days of 2017 (up to 704 µg/m3 for PM10 and 46 µg/m3 for PM2.5), respectively. PM10 concentrations were correlated with total burned area (0.500 < r < 0.949; p > 0.05) and with monthly total burned area/distance2 (0.500 < r < 0.667; p > 0.05). The forest fires of 2017 took the life of 112 citizens. A total of 474 cases of hospital admissions due to cardiovascular diseases and 3524 cases of asthma incidence symptoms per 100,000 individuals at risk were assessed due to exposure to 2017 forest fires. Real-time and in situ PM methodologies should be combined with protection action plans to reduce public health risks. Portuguese rural stations should monitor other health-relevant pollutants (e.g., carbon monoxide and volatile organic compounds) released from wildfires to allow performing more robust and comprehensive measurements that will allow a better assessment of the potential health risks for the exposed populations.

Influence of Meteorological Variables and Forest Fires Events on Air Quality in an Urban Area (Córdoba, Argentina)

Extreme environmental events, such as forest fires, are a major emission source of aerosols into the atmosphere. Thus, to investigate the contribution of local forest fires to urban particulate matter, we selected several forest fire indicators, such as number of heat sources, fire events, and burnt area, and collected particles smaller than 2.5 µm (PM_2.5) during a 2.5-year period in Cordoba City (Argentina). Temporal variation of PM_2.5 concentration and composition was described considering fire and nonfire periods, and the influence of meteorological variables was estimated as well. On average, PM_2.5 levels registered in Córdoba city during the study period were lower than values reported for other similar cities in Latin America, despite the fact that during wintertime an increase in PM_2.5 levels was observed due to the occurrence of thermal inversions. Several fire events taking place in the nearby hills around the city during winter and spring 2013 suggest that biomass burning was a strong contribution to urban particles levels, which is consistent with the significant correlation between PM_2.5 concentration and heat sources number. During fire periods, levels of Fe, Ca, and K, were significantly higher than in the nonfire periods, suggesting that these elements can be reliable forest fire markers.

Anthropogenic and naturally occurring radionuclide content in near surface air in Cáceres (Spain)

The anthropogenic (¹³⁷Cs, ⁹⁰Sr, ^239+240Pu and ²⁴¹Am) and naturally occurring radionuclide (⁴⁰K, ^234,238U, ^228,230,232Th, ²²⁶Ra and ²¹⁰Pb) content in near surface air present seasonal variations related to natural processes, such as soil erosion, resuspension of fine particles of soil and radon exhalation from soil (²¹⁰Pb). The objective is to analyze seasonal variations of their concentrations and compare with radiological events (Fukushima fallout and wild fire) in a location without any known source of anthropogenic radionuclides. The ²¹⁰Pb, ⁴⁰K, and ¹³⁷Cs presented annual variations, with maximum activity levels in summer. Solar radiation and rainfall were correlated with ²¹⁰Pb and ⁴⁰K. The ^234,238U, ^228,230,232Th, ²²⁶Ra, ¹³⁷Cs and ⁹⁰Sr presented positive correlation with monthly mean values of temperature. The ratio ⁹⁰Sr/¹³⁷Cs was within the range of those reported for soils in Spain. Finally, the maximal effective dose rate was estimated to be 37 and 88 μSv/y for infants and adults, respectively, well below 1 mSv/y reference level. The main contributor to effective dose was ²¹⁰Pb, about 92%, followed by: ²¹⁰Pb ≫ ^228,230,232Th > ²²⁶Ra, ^234,238U > ⁷Be, ^239+240Pu > ⁴⁰K, ⁹⁰Sr > ¹³⁷Cs > ²²Na.

Ozone levels in the Spanish Sierra de Guadarrama mountain range are above the thresholds for plant protection: analysis at 2262, 1850, and 995 m a.s.l

The Sierra de Guadarrama mountain range, located at 60 km from Madrid City (Spain), includes high valuable ecosystems following an altitude gradient, some of them protected under the Sierra de Guadarrama National Park. The characteristic Mediterranean climatic conditions and the precursors emitted from Madrid favor a high photochemical production of ozone (O₃) in the region. However, very little information is available about the patterns and levels of O₃ and other air pollutants in the high elevation areas and their potential effects on vegetation. Ozone levels were monitored at three altitudes (2262, 1850, and 995 m a.s.l.) for at least 3 years within the 2005-2011 period. NO _x and SO₂ were also recorded at the highest and lowest altitude sites. Despite the inter-annual and seasonal variations detected in the O₃ concentrations, the study revealed that SG is exposed to a chronic O₃ pollution. The two high elevation sites showed high O₃ levels even in winter and at nighttime, having low correlation with local meteorological variables. At the lower elevation site, O₃ levels were more related with local meteorological and pollution conditions. Ozone concentrations at the three sites exceeded the thresholds for the protection of human health and vegetation according to the European Air Quality Directive (EU/50/2008) and the thresholds for vegetation protection of the CLRTAP. Ozone should be considered as a stress factor for the health of the Sierra de Guadarrama mountain ecosystems. Furthermore, since O₃ levels at foothills differ from concentration in high elevation, monitoring stations in mountain ranges should be incorporated in regional air quality monitoring networks.

GIS applied to location of fires detection towers in domain area of tropical forest

In most countries, the loss of biodiversity caused by the fires is worrying. In this sense, the fires detection towers are crucial for rapid identification of fire outbreaks and can also be used in environmental inspection, biodiversity monitoring, telecommunications mechanisms, telemetry and others. Currently the methodologies for allocating fire detection towers over large areas are numerous, complex and non-standardized by government supervisory agencies. Therefore, this study proposes and evaluates different methodologies to best location of points to install fire detection towers considering the topography, risk areas, conservation units and heat spots. Were used Geographic Information Systems (GIS) techniques and unaligned stratified systematic sampling for implementing and evaluating 9 methods for allocating fire detection towers. Among the methods evaluated, the C3 method was chosen, represented by 140 fire detection towers, with coverage of: a) 67% of the study area, b) 73.97% of the areas with high risk, c) 70.41% of the areas with very high risk, d) 70.42% of the conservation units and e) 84.95% of the heat spots in 2014. The proposed methodology can be adapted to areas of other countries.

Assessment of the ozone tolerance of two soybean cultivars (Glycine max cv. Sambaíba and Tracajá) cultivated in Amazonian areas

Brazilian soybean cultivars (Glycine max Sambaíba and Tracajá) routinely grown in Amazonian areas were exposed to filtered air (FA) and filtered air enriched with ozone (40 and 80 ppb, 6 h/day for 5 days) to assess their level of tolerance to this pollutant by measuring changes in key biochemical, physiological, and morphological indicators of injury and in enzymatic and non-enzymatic antioxidants. Sambaíba plants were more sensitive to ozone than Tracajá plants, as revealed by comparing indicator injury responses and antioxidant stimulations. Sambaíba exhibited higher visible leaf injury, higher stomatal conductance, and a severe decrease in the carbon assimilation rate. Higher ozone level (80 ppb) caused an increase in cell death in both cultivars. Levels of malondialdehyde and hydrogen peroxide also increased in Tracajá exposed under 80 ppb. Sambaíba plants exhibited decreases in ascorbate and glutathione levels and in enzymatic activities associated with these antioxidants. The higher tolerance of the Tracajá soybean appeared to be indicated by reduced physiological injuries and lower stomatal conductance, which might decrease the influx of ozone and enhance oxidation-reduction reactions involving catalase, ascorbate peroxidase, ascorbate, and glutathione, most likely stimulated by higher hydrogen peroxide.