ENSO modulates wildfire activity in China

Regulation-driven changes in PM2.5 sources in China from 2013 to 2019, a critical review and trend analysis

Identifying changes in source-specific fine particles (PM2.5) over time is essential for evaluating the effectiveness of regulatory measures and informing future policy decisions. After the extreme haze events in China during 2013-14, more comprehensive and stringent policies were implemented to combat PM2.5 pollution. To determine the effectiveness of these policies, it is necessary to assess the changes in the specific source types to which the regulations pertain. Multiple studies have been conducted over the past decade to apportion PM2.5. The purpose of this study was to explore the available literature and conduct a critical review of the reliable results. In total, 5008 articles were screened, but only 48 studies were included for further analysis given our inclusion criteria including covering a monitoring period of ≥1 year and having enough speciation data to provide mass closure. Using these studies, we analyzed temporal and spatial trends across China from 2013 to 2019. We observed the overall decrease in the concentration contributions from all main source categories. The reductions from industry, coal and heavy oil combustion, and the related secondary sulfate were more notable, especially from 2013 to 2016-17. The contributions from biomass burning initially decreased but then increased slightly after 2016 in some locations despite new constraints on agricultural and household burning practices. Although the contributions from vehicle emissions and related secondary nitrate decreased, they gradually became the primary contributors to PM2.5 by ∼2017. Despite the substantial improvements achieved by the air pollution regulation implementations, further improvements in air quality will require additional aggressive actions, especially those targeting vehicular emissions. Ultimately, source apportionment studies based on extended duration, fixed-site sampling are recommended to provide a more thorough understanding of the sources impacting areas and transformations in PM2.5 sources prompted by regulatory actions.

Characteristic changes and environmental indicators of magnetic spherules in the South Yellow Sea mud area for about 7.5 ka

Magnetic spherules originate from anthropogenic and natural sources and can be differentiated based on morphology and composition. Using magnetic measurement, diameter measurement, scanning electron microscopy and energy dispersive spectroscopy (SEM-EDS) analysis of a 10 m sediment core in the mud area of the South Yellow Sea, we found that magnetic spherules occur at all observed depths of the core. The magnetic spherule concentrations vary from 10 spherules/0.5 g to 62 spherules/0.5 g. Here, concentrations generally less than 10 spherules/0.5 g are considered as the background value in the core. The peak value of magnetic spherules appeared at the 0.02, 0.3, 2 and 8 m, and their concentrations are 62, 52, 36, 48 spherules/0.5 g, respectively. According to the deposition age, concentration, diameter, morphology and chemical characteristics of the spherules, it is found that the spherules at 0.02 m are produced by industrial coal burning. A volcanic eruption event was the main responsible for the accumulation of spherules at 0.3 and 8 m, while the spherules located at 2 m are related to a wildfire event. Magnetic spherules are common in continental shelf regions and can well document the human activities and natural environment events.

Vegetation-fire feedbacks increase subtropical wildfire risk in scrubland and reduce it in forests

Climate dictates wildfire activity around the world. But East and Southeast Asia are an apparent exception as fire-activity variation there is unrelated to climatic variables. In subtropical China, fire activity decreased by 80% between 2003 and 2020 amid increased fire risks globally. Here, we assessed the fire regime, vegetation structure, fuel flammability and their interactions across subtropical Hubei, China. We show that tree basal area (TBA) and fuel flammability explained 60% of fire-frequency variance. Fire frequency and fuel flammability, in turn, explained 90% of TBA variance. These results reveal a novel system of scrubland-forest stabilized by vegetation-fire feedbacks. Frequent fires promote the persistence of derelict scrubland through positive vegetation-fire feedbacks; in forest, vegetation-fire feedbacks are negative and suppress fire. Thus, we attribute the decrease in wildfire activity to reforestation programs that concurrently increase forest coverage and foster negative vegetation-fire feedbacks that suppress wildfire.

Wildfire precursors show complementary predictability in different timescales

In most of the world, conditions conducive to wildfires are becoming more prevalent. Net carbon emissions from wildfires contribute to a positive climate feedback that needs to be monitored, quantified, and predicted. Here we use a causal inference approach to evaluate the influence of top-down weather and bottom-up fuel precursors on wildfires. The top-down dominance on wildfires is more widespread than bottom-up dominance, accounting for 73.3% and 26.7% of regions, respectively. The top-down precursors dominate in the tropical rainforests, mid-latitudes, and eastern Siberian boreal forests. The bottom-up precursors dominate in North American and European boreal forests, and African and Australian savannahs. Our study identifies areas where wildfires are governed by fuel conditions and hence where fuel management practices may be more effective. Moreover, our study also highlights that top-down and bottom-up precursors show complementary wildfire predictability across timescales. Seasonal or interannual predictions are feasible in regions where bottom-up precursors dominate.

High-resolution atmospheric mercury emission from open biomass burning in China: Integration of localized emission factors and multi-source finer resolution remote sensing data

Mercury (Hg) emissions from open biomass burning represent one of the largest Hg inputs to the atmosphere, with considerable effects on the atmospheric Hg budget. However, there is currently large uncertainty in the inventory of Hg emissions from open biomass burning in China due to limitations on the coarse resolution of burned area products, rough biomass data, and the unavailability of suitable emission factors (EFs). In this study, we developed high tempo-spatial resolution (30 m) and long time-series (2000-2019) atmospheric Hg emission inventories from open biomass burning using the Global Annual Burned Area Map (GABAM) product, high-resolution biomass map, Landsat-based tree cover datasets as well as local EFs in China. The results showed that the average annual Hg emission from open biomass burning in China amounted to 172.6 kg during 2000-2019, with a range of 63-398.5 kg. The largest Hg emissions were found in cropland (72%), followed by forest (25.9%), and grassland (2.1%). On a regional level, Northeast China (NE) and Southwest China (SW) were the two main contributors, together accounting for more than 60% of total Hg emissions. The temporal distribution of Hg emissions showed that the peaks occurred in 2003 and 2014. This is a comprehensive estimation of Hg emissions from open biomass burning in China by integrating various high-resolution remotely sensed data and nationwide localized EFs, which has important implications for understanding the role of open biomass burning in China in regional and global atmospheric Hg budget.

North-south antiphase of wildfire activity across the pyroregions of continental China driven by NAO and the Antarctic oscillation

Wildfires are a natural disturbance in many parts of the world, but fire regimes are changing as a result of anthropogenic pressures. A key uncertainty towards anticipating future changes in burned area lies in understanding the effects of climate teleconnections (CTs). Here we test how different CTs impact burned area in China, a large country comprising different biomes and where similar fire-suppression and post-fire afforestation policies are implemented. We observed diverging temporal trends in burned area across the different pyroregions of China, from increases in the Northeastern grasslands and mixed forests pyroregion to decreases in the Southern tropical forests pyroregion. This North-South antiphase in fire activity was being partly driven by joint effects of the North Atlantic Oscillation and the Antarctic Oscillation, which exerted contrasting effects on fire weather across latitude. El Niño Southern Oscillation and the other examined teleconnections had minor effects over burned area. The increasing burned area in the NE-mixed forests pyroregion indicates that mega-fires may increase under global warming but their occurrence may be modulated by potential strengthening or weakening of NAO and AAO.

Increased diurnal difference of NO2 concentrations and its impact on recent ozone pollution in eastern China in summer

Nitrogen dioxide (NO₂) is a key tropospheric O₃ precursor. Since 2013, efforts to decrease air pollution in China have driven substantial declines in annual NO₂ concentrations, whereas ozone (O₃) concentrations have increased. Based on nationwide NO₂ observations and a regional air quality model (WRF-CMAQ), we analyzed trends in the diurnal difference (DD, the difference between nighttime and daytime concentrations) of NO₂ concentrations across eastern China and in five national urban agglomerations (UAs) from 2014 to 2021, and explored the factors underlying such changes and the potential impacts on O₃ pollution. We found that the observed DD of NO₂ has increased in most cities and UAs, and that this trend can be primarily attributed to changes in anthropogenic emissions, based on comparison with DDs simulated with fixed anthropogenic emissions, which generally showed much weaker trends and little interannual variation. A sensitivity analysis using the WRF-CMAQ model was conducted to investigate the impact of a modified diurnal cycle of nitrogen oxides (NO_x) emissions on O₃ concentrations. The result revealed that enhancing the DD of NO₂ would increase O₃ concentrations in the morning and the daily maximum 8-h O₃ concentrations in the cities with high NO_x concentrations, as well as downwind areas of cities, indicating that greater DDs in NO₂ is one of the reasons that have led to the enhanced China's O₃ pollution in recent years.

Identification and evaluation of soil moisture flash drought by a nonstationary framework considering climate and land cover changes

Soil moisture flash drought can cause extensive damage to agriculture, ecosystems, and economies due to its sudden onset. Previous research identified soil moisture flash drought using stationary methods, in which, stationary probability distributions were employed to derive cumulative percentages (CPs) of given soil moisture values, and then based on the CPs sequence, the run theory was used to identify soil moisture flash drought events. However, because changes in climate or land cover can induce significant variations in the underlying probability distributions of soil moisture, the method's usual assumption of stationarity should be questioned. In this study, a nonstationary framework based on the nonstationary frequency analysis method and the run theory was developed for identifying soil moisture flash drought events. This framework was applied to the study of the pentad average root-zone soil moisture (PRZSM) of the Pearl River basin (PRB) in South China based on the ERA5-Land and the GLEAM datasets from 1981 to 2020. The results of the ERA5-Land were general consistent with those of the GLEAM, and the major findings include: (1) without considering the nonstationarity of soil moisture, the onset rate of flash droughts may be underestimated. The average onset rate of flash droughts in nonstationary conditions is slightly greater by 1 %/pentad -2 %/pentad than that in stationary conditions; (2) without considering the nonstationarity of soil moisture, the severity of flash droughts may be overestimated. The average severity of flash droughts in nonstationary conditions is smaller by 10% ⋅ pentads-20% ⋅ pentads than that in stationary conditions; and (3) the trends of the characteristics of soil moisture flash drought are consistent between the stationary and the nonstationary conditions. In conclusion, the above findings contribute to a better understanding of the implications of soil moisture nonstationarity on flash drought identification.

Decreasing causal impacts of El Niño-Southern Oscillation on future fire activities

Wildfires alter the composition and structure of ecosystems and result in huge economic costs. While future fires and ecosystems recovery might become increasingly challenging to manage under warming environment, further understanding of the main drivers of wildfires is necessary. The El Niño-Southern Oscillation (ENSO) is a major climate mode and is expected to affect global wildfires. Nevertheless, there is uncertainty regarding the causal impacts of ENSO on future fire activities at the global scale. Here we use model outputs from the Coupled Modeling Intercomparison Project Phase 6 to systematically evaluate the response of future fire activities (i.e., fire carbon emissions) to ENSO during the period 2015-2100 over different continents. Our results demonstrate that the impacts of ENSO on fires are found in the tropical and subtropical regions of Africa, Asia, Oceania, and America, while ENSO impacts over high latitude regions are very limited over Alaska and far eastern Europe. We showed that the role of ENSO on fire activities over subtropical regions might be more important than previously understood. High consistency between models is observed for the impacted regions. In historical experiment, the areas with significant ENSO effects on wildfires account for approximately 5.85% of land-area and this ratio decreases to approximately 5.39% and 2.92% of land-area in the future scenarios SSP2-4.5 and SSP5-8.5, respectively. These results imply a decrease in ENSO impacts on global fire activities in future projections compared to the historical period 1915-2000. This work might contribute to the ENSO-based forecasts of global fire activities.

Mapping China’s Forest Fire Risks with Machine Learning

Forest fires are disasters that are common around the world. They pose an ongoing challenge in scientific and forest management. Predicting forest fires improves the levels of forest-fire prevention and risk avoidance. This study aimed to construct a forest risk map for China. We base our map on Visible Infrared Imaging Radiometer Suite data from 17,330 active fires for the period 2012–2019, and combined terrain, meteorology, social economy, vegetation, and other factors closely related to the generation of forest-fire disasters for modeling and predicting forest fires. Four machine learning models for predicting forest fires were compared (i.e., random forest (RF), support vector machine (SVM), multi-layer perceptron (MLP), and gradient-boosting decision tree (GBDT) algorithm), and the RF model was chosen (its accuracy, precision, recall, F1, AUC values were 87.99%, 85.94%, 91.51%, 88.64% and 95.11% respectively). The Chinese seasonal fire zoning map was drawn with the municipal administrative unit as the spatial scale for the first time. The results show evident seasonal and regional differences in the Chinese forest-fire risks; forest-fire risks are relativity high in the spring and winter, but low in fall and summer, and the areas with high regional fire risk are mainly in the provinces of Yunnan (including the cities of Qujing, Lijiang, and Yuxi), Guangdong (including the cities of Shaoguan, Huizhou, and Qingyuan), and Fujian (including the cities of Nanping and Sanming). The major contributions of this study are to (i) provide a framework for large-scale forest-fire risk prediction having a low cost, high precision, and ease of operation, and (ii) improve the understanding of forest-fire risks in China.

Polycyclic aromatic hydrocarbon occurrence in forest soils in response to fires: a summary across sites

Forest fires are important sources of polycyclic aromatic hydrocarbons (PAHs) in soils. However, factors controlling PAH production in soils subjected to fires in different sites are poorly understood. Here, we analyzed 143 sets of previously published data to evaluate the concentrations and composition profiles of PAHs in ash and soils associated with forest fires and to assess the impacts of soil depth, fire intensity, post-fire duration, and vegetation type on their occurrence. Compared to unburned soils, the total PAH concentrations increased by 205% (95% confidential interval of 152-269%; n = 136) in soils associated with fires. This increase surpassed that of PAH toxic equivalents (73%) because fires produce dominantly low-ring PAHs with relatively low toxicity. PAH concentrations in fire-impacted sites increased by 684%, 258%, and 155% in the ash, 0-5 cm soil depth interval, and >5 cm soil depth interval, respectively. The increases in PAH concentrations associated with mild-intensity fires (412%) exceeded those associated with moderate-intensity (163%) and high-intensity (168%) fires, which is possibly due to pyromineralization or volatilization of organic matters at high burning temperatures. These increases were highest within a month after the fire (280%), gradually decreasing over time, and showed no significant difference compared to the reference sites after 24 months. The concentration increases exhibit no major difference between various vegetation types (broad-leaved forest vs. coniferous forest vs. shrub). Assessments reveal that exposure to post-fire soil PAHs involves no serious human health risk. However, potential adverse effects of soil PAHs on other organisms (e.g., microbes and plants) and ecosystems should be further examined. The present study highlights the strong impacts of soil depth, fire intensity, and post-fire duration, and the relatively weak impact of the vegetation type on PAH concentrations in soils associated with fires in different areas.

Fires Drive Long-Term Environmental Degradation in the Amazon Basin

The Amazon Basin is undergoing extensive environmental degradation as a result of deforestation and the rising occurrence of fires. The degradation caused by fires is exacerbated by the occurrence of anomalously dry periods in the Amazon Basin. The objectives of this study were: (i) to quantify the extent of areas that burned between 2001 and 2019 and relate them to extreme drought events in a 20-year time series; (ii) to identify the proportion of countries comprising the Amazon Basin in which environmental degradation was strongly observed, relating the spatial patterns of fires; and (iii) examine the Amazon Basin carbon balance following the occurrence of fires. To this end, the following variables were evaluated by remote sensing between 2001 and 2019: gross primary production, standardized precipitation index, burned areas, fire foci, and carbon emissions. During the examined period, fires affected 23.78% of the total Amazon Basin. Brazil had the largest affected area (220,087 fire foci, 773,360 km2 burned area, 54.7% of the total burned in the Amazon Basin), followed by Bolivia (102,499 fire foci, 571,250 km2 burned area, 40.4%). Overall, these fires have not only affected forests in agricultural frontier areas (76.91%), but also those in indigenous lands (17.16%) and conservation units (5.93%), which are recognized as biodiversity conservation areas. During the study period, the forest absorbed 1,092,037 Mg of C, but emitted 2908 Tg of C, which is 2.66-fold greater than the C absorbed, thereby compromising the role of the forest in acting as a C sink. Our findings show that environmental degradation caused by fires is related to the occurrence of dry periods in the Amazon Basin.

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015-2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM_2.5, PM₁₀, PMC (coarse fraction of PM), NO₂, SO₂, NOx, CO, O₃ and the total gaseous oxidant (OX = NO₂ + O₃) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015-2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO₂ and NOx concentrations and peoples' mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO₂ and between 30% and 40% in mean PM_2.5 concentrations over 2020 full lockdown compared to the same period in 2015-2019. However, PM_2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO₂/CO ratio). Some Chinese cities showed similar increases in PM_2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O₃ concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO₂ anomalies were negative for 2020 compared to 2015-2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO₂/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO₂ decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO₂ + O₃) showed that primary NO₂ emissions at urban locations were greater than the O₃ production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO₂ and O₃ concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM_2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.