Frequency and intensity of wildfire occurrences are dramatically increasing worldwide due to global climate change, having a devastating effect on the entire ecosystem including plants. Moreover, distribution of fire-smoke can influence the natural environment over very long distances, i.e. hundreds of kilometres. Dry plant matter contains 0.1–0.9% (w/w) sulphur, which is mainly released during combustion into the atmosphere as sulphur dioxide (SO₂) resulting in local concentrations of up to 3000 nL L⁻¹. SO₂ is a highly hazardous gas, which enters plants mostly via the stomata. Toxic sulphite is formed inside the leaves due to conversion of SO₂. Plants as sessile organisms cannot escape from threats, why they evolved an impressive diversity of molecular defence mechanisms. In the present study, two recent wildfires in Germany were evaluated to analyse the effect of SO₂ released into the atmosphere on deciduous trees: the Meppen peat fire in 2018 and the forest fire close to Luebtheen in 2019. Collected leaf material from beech (Fagus sylvatica) and oak (Quercus robur) was examined with respect to detoxification of sulphur surplus due to the exposure to elevated SO₂. An induced stress reaction in both species was indicated by a 1.5-fold increase in oxidized glutathione. In beech leaves, the enzymatic activities of the sulphite detoxification enzymes sulphite oxidase and apoplastic peroxidases were increased 5-fold and a trend of sulphate accumulation was observed. In contrast, oaks did not regulate these enzymes during smoke exposure, however, the constitutive activity is 10-fold and 3-fold higher than in beech. These results show for the first time sulphite detoxification strategies of trees in situ after natural smoke exposure. Beech and oak trees survived short-term SO₂ fumigation due to exclusion of toxic gases and different oxidative detoxification strategies. Beeches use efficient upregulation of oxidative sulphite detoxification enzymes, while oaks hold a constitutively high enzyme-pool available.

Forest fires significantly affect the wildlife, vegetation, composition and structure of the forests. This study explores the potential of partially burnt wood recovered in the aftermath of a recent Canadian forest fire incident as a feedstock for generating hydrogen-rich syngas through hydrothermal gasification. Partially burnt wood was gasified in hydrothermal conditions to study the influence of process temperature (300–500 °C), residence time (15–45 min), feed concentration (10–20 wt%) and biomass particle size (0.13 mm and 0.8 mm) using the statistical Taguchi method. Maximum hydrogen yield and total gas yield of 5.26 mmol/g and 11.88 mmol/g, respectively were obtained under optimized process conditions at 500 °C in 45 min with 10 wt% feed concentration using biomass particle size of 0.13 mm. The results from the mean of hydrogen yield show that the contribution of each experimental factors was in the order of temperature > feed concentration > residence time > biomass particle size. Other gaseous products obtained at optimum conditions include CO₂ (3.43 mmol/g), CH₄ (3.13 mmol/g) and C₂–C₄ hydrocarbons (0.06 mmol/g).

Continuous measurements of Black Carbon (BC) aerosol mass concentrations were carried at Dehradun (30.33°N, 78.04°E, 700 m amsl), a semi-urban site in the foothills of north-westHimalayas, India during January 2011–December 2017. We reported both the BC seasonal variations as well as mass concentrations from fossil fuel combustion (BCff) and biomass burning (BCbb) sources. Annual mean BC exhibited a strong seasonal variability with maxima during winter (4.86 ± 0.78 μg m⁻³) followed by autumn (4.18 ± 0.54 μg m⁻³), spring (3.93 ± 0.75 μg m⁻³) and minima during summer (2.41 ± 0.66 μg m⁻³). Annual averaged BC mass concentrations were 3.85 ± 1.16 μg m⁻³ varying from 3.29 to 4.37 μg m⁻³ whereas BCff and BCbb ranged from 0.11 to 7.12 μg m⁻³ and 0.13–3.6 μg m⁻³. The percentage contributions from BCff and BCbb to total BC are 66% and 34% respectively, indicating relatively higher contribution from biomass burning as compared to other locations in India. This is explained using potential source contribution function (PSCF) and concentration weighted trajectories (CWT) analysis which reveals the potential sources of BC originating from the north-west and eastern parts of IGP and the western part of the Himalayas that are mostly crop residue burning and forest fire regions in India. The annual mean ARF at top-of-atmosphere (TOA), at surface (SUR), and within the atmosphere (ATM) were found to be −14.84 Wm⁻², −43.41 Wm⁻², and +28.57 Wm⁻² respectively. To understand the impact of columnar aerosol burden on ARF, the radiative forcing efficiency (ARFE) was estimated and averaged values were −31.81, −91.63 and 59.82 Wm⁻² τ⁻¹ for TOA, SUR and ATM respectively. The high ARFE within the atmosphere indicates the dominance of absorbing aerosol (BC and dust) over Northwest Himalayas.

Bogota registers frequent episodes of poor air quality from high PM₁₀ concentrations. It is one of the main Latin American megacities, located at 2600 m in the tropical Andes, but there is insufficient data on PM₁₀ source contribution. A characterization of the chemical composition and the source apportionment of PM₁₀ at an urban background site in Bogota was carried out in this study. Daily samples were collected from June 2015 to May 2016 (a total of 311 samples). Organic carbon (OC), elemental carbon (EC), water soluble compounds (SO₄²⁻, Cl⁻, NO₃⁻, NH₄⁺), major elements (Al, Fe, Mg, Ca, Na, K, P) and trace metals (V, Cd, Pb, Sr, Ba, among others) were analyzed. The results were interpreted in terms of their variability during the rainy season (RS) and the dry season (DS). The data obtained revealed that the carbonaceous fraction (∼51%) and mineral dust (23%) were the main PM₁₀ components, followed by others (15%), Secondary Inorganic Compounds (SIC) (11%) and sea salt (0.4%). The average concentrations of soil, SIC and OC were higher during RS than DS. However, peak values were observed during the DS due to photochemical activity and forest fires. Although trace metals represented <1% of PM₁₀, high concentrations of toxic elements such as Pb and Sb on RS, and Cu on DS, were obtained. By using a PMF model, six factors were identified (∼96% PM₁₀) including fugitive dust, road dust, metal processing, secondary PM, vehicles exhaust and industrial emissions. Traffic (exhaust emissions + road dust) was the major PM₁₀ source, accounting for ∼50% of the PM₁₀. The results provided novel data about PM₁₀ chemical composition, its sources and its seasonal variability during the year, which can help the local government to define control strategies for the main emission sources during the most critical periods.

Char as a carbon-rich material, can be produced under pyrolytic conditions, wildfires or prescribed burn offs for fire management. The objective of this study was to elucidate mechanistic interactions of copper (Cu2+) and nickel (Ni2+) with different chars produced by pyrolysis (green waste, GW; blue-Mallee, BM) and forest fires (fresh-burnt by prescribed fire, FC; aged char produced by wild fire, AC). The pyrolytic chars were more effective sorbents of Cu2+ (∼11 times) and Ni2+ (∼5 times) compared with the forest fire chars. Both cross-polarization (CPMAS-NMR) and Bloch decay (BDMAS-NMR) 13C NMR spectroscopies showed that forest fire chars have higher woody components (aromatic functional groups) and lower polar groups (e.g. O-alkyl C) compared with the pyrolytic chars. The polarity index was greater in the pyrolytic chars (0.99–1.34) than in the fire-generated chars (0.98–1.15), while aromaticity was lower in the former than in the latter. Fourier transform infrared (FTIR) and Raman spectroscopies indicated the binding of carbonate and phosphate with both Cu2+ and Ni2+ in all chars, but with a greater extent in pyrolytic than forest fire-generated chars. These findings have demonstrated the key role of char's oxygen-containing functional groups in determining their sorption capacity for the Cu2+ and Ni2+ in contaminated lands.

Forests are considered a pool of mercury in the global mercury cycle. However, few studies have investigated the distribution of mercury in the forested systems in China. Tieshanping forest catchment in southwest China was impacted by mercury emissions from industrial activities and coal combustions. Our work studied mercury content in atmosphere, soil, vegetation and insect with a view to estimating the potential for mercury release during forest fires. Results of the present study showed that total gaseous mercury (TGM) was highly elevated and the annual mean concentration was 3.51 ± 1.39 ng m−2. Of the vegetation tissues, the mercury concentration follows the order of leaf/needle > root > bark > branch > bole wood for each species. Total ecosystem mercury pool was 103.5 mg m−2 and about 99.4% of the mercury resides in soil layers (0–40 cm). The remaining 0.6% (0.50 mg m−2) of mercury was stored in biomass. The large mercury stocks in the forest ecosystem pose a serious threat for large pluses to the atmospheric mercury during potential wildfires and additional ecological stress to forest insect: dung beetles, cicada and longicorn, with mercury concentration of 1983 ± 446, 49 ± 38 and 7 ± 5 ng g−1, respectively. Hence, the results obtained in the present study has implications for global estimates of mercury storage in forests, risks to forest insect and potential release to the atmosphere during wildfires.

Atmospheric deposition in the Athabasca Oil Sands Region decreased exponentially with distance from the industrial center. Throughfall deposition (kg ha−1 yr−1) of NH4–N (.8–14.7) was double that of NO3–N (.3–6.7), while SO4–S ranged from 2.5 to 23.7. Gaseous pollutants (NO2, HNO3, NH3, SO2) are important drivers of atmospheric deposition but weak correlations between gaseous pollutants and deposition suggest that particulate deposition is also important. The deposition (eq ha−1) of base cations (Ca + Mg + Na) across the sampling network was highly similar to N + S deposition, suggesting that acidic deposition is neutralized by base cation deposition and that eutrophication impacts from excess N may be of greater concern than acidification. Emissions from a large forest fire in summer 2011 were most prominently reflected in increased concentrations of HNO3 and throughfall deposition of SO4–S at some sites. Deposition of NO3–N also increased as did NH4–N deposition to a lesser degree.

monitoring sites operated by the National Park Service in Sierra Nevada, California, are used to develop an ozone forecasting model and to estimate the contribution of wildland fires on ambient ozone levels. The analyses of weather and ozone data pointed to the transport of ozone precursors from the Central Valley as an important source of pollution in these National Parks. Comparisons of forecasted and observed values demonstrated that accurate forecasts of next-day hourly ozone levels may be achieved by using a time series model with historic averages, expected local weather and modeled PM values as explanatory variables. Results on fire smoke influence indicated occurrence of significant increases in average ozone levels with increasing fire activity. The overall effect on diurnal ozone values, however, was small when compared with the amount of variability attributed to sources other than fire. We have demonstrated that it is possible to produce accurate forecasts of next-day hourly ozone levels in the Sierra Nevada, CA, during fire season.

High concentration particulate matter 2.5 released from forest fires, in addition to direct burns and asphyxia, PM₂.₅ is one of the main pollutants which threaten the safety of forest fire fighter. Therefore, to assess spatial distribution of PM₂.₅, a simulation study was conducted. Fuel beds with different moisture contents and loads were constructed. 144 times burning experiments were carried out under different wind speeds by using wind tunnel device. PM₂.₅ particles at different spatial points were collected and calculated. The results show that, in the two of three variables interaction between wind speed, fuel load, and, except fuel moisture content, wind speed and fuel load are positively correlated with the PM₂.₅ concentrations. From PM₂.₅ concentration which collected at each point in the horizontal and vertical directions, the overall trend is that PM₂.₅ concentration increases along the horizontal downwind direction (C and D higer than A and B) and the vertical upward direction (A and C higer than B and D) Based on BP neural network, the spatial distribution model of PM₂.₅ concentration with single hidden layer was established. The prediction accuracy of modeling samples and validation samples is balanced when hidden layer node is 5. This study will help to make reference for PM₂.₅ occupational exposure standards, forest fire smoke management and forest fire management in China.