Impact of field biomass burning on local pollution and long-range transport of PM2.5 in Northeast Asia

Heterogeneity in the health effects of PM2.5 sources across the major metropolitan cities, South Korea: Significance of region-specific management

Ambient PM2.5, well-known for its adverse impacts on human health, is a very heterogeneous pollutant. Its chemical composition and attributable sources vary by region, influenced by meteorological and geographical conditions as well as emission sources. However, administrative policies are currently focused on mass concentrations. However, not all PM2.5 sources provide equally toxic particles. Thus, those sources that should be the focus of controls has not been the priority. In the present study, we conducted source apportionment utilizing positive matrix factorization (PMF) and investigated the association of PM2.5 source contributions with emergency department visits (EDVs) in major megacities in South Korea. Overall, an interquartile range (IQR) increment in source contribution increased the number of emergency room visits. Industry and coal combustion sources, marked by heavy metals, were principally associated with the adverse health impacts. However, the sources showing significant associations with EDVs differed across the study area. In addition, we found that region-specific relationships between PM2.5 sources and morbidity were plausible, considering the existence of relevant sources such as industrial complexes and coal-fired power plants. The analysis of source contributions according to wind conditions also supported the source-morbidity relationships. These findings suggest that administrative policies for PM2.5 control should be established and implemented considering region-specific characteristics of the links between PM2.5 sources and health impacts to maximize the control's public health effects. Furthermore, the results of the present study indicate that PMF was an effective method for linking acute exposure to PM2.5 source types with health outcomes to prioritize its sources.

Quantification and evaluation of atmospheric emissions from crop residue burning constrained by satellite observations in China during 2016-2020

In rural regions of China, crop residue burning (CRB) is the major biomass burning activity, which can result in massive emissions of atmospheric particulate, greenhouse gas, and trace gas pollutants. Based on Himawari-8 satellite fire radiative power and agricultural statistics data, we implemented a daily inventory of agricultural fire emissions in 2016-2020 with a 2-km spatial resolution, including atmospheric pollutants such as CO₂, CH₄, CO, N₂O, NO_X, NH₃, SO₂, PM₁₀, PM_2.5, Hg, OC, EC, and NMVOCs. Our inventory constrained by geostationary satellite monitoring is more consistent with the actual CRB emissions in China, as many flaring events occur surreptitiously in the early morning and late evening to avoid regulation, which may be overlooked by polar-orbiting satellites. The spatiotemporal characterizations of various CRB emissions are found to be consistent with multiple satellite trace gas retrievals. We also assessed the effectiveness of field burning bans in China. Combined with other relevant datasets, it was found that although China has been advocating for a long time not to burn straw in the open field, CRB emissions was not successfully controlled nationwide until 2016. We estimated that the cumulative reduction of CO₂ CRB emissions alone amounts to 809 ± 651 (2σ) teragram (Tg) during the 13th Five-Year Plan period (2016-2020), with an average value equivalent to 1.2 times the total annual territorial CO₂ emissions by fossil fuels from Germany in 2021 (675 Tg, ranked 1st in EU27 and 7th in the world). Our inventory also suggests that continuous, long-term controls are necessary. Otherwise, CRB emissions may only be delayed on a seasonal scale, rather than reduced.

Striking impacts of biomass burning on PM2.5 concentrations in Northeast China through the emission inventory improvement

Biomass burning exerts substantial influences on air quality and climate, which in turn to further aggravate air quality. The biomass burning emissions in particular of the agricultural burning may suffer large uncertainties which limits the understanding of their impact on air quality. Based on an improved emission inventory of the Visible Infrared Imaging Radiometer Suite (VIIRS) relative to commonly used Global Fire Emissions Database (GFED), we thoroughly evaluate the impact of biomass burning on air quality and climate during the episodes of November 2017 in Northeast China which is rich in agriculture burning. The results first indicate substantial underestimates in simulated PM_2.5 concentrations without the inclusion of biomass burning emission inventory, based on a regional air quality model Weather Research and Forecasting model and Community Multiscale Air Quality model (WRF-CMAQ). The addition of biomass burning emissions from GFED then reduces the bias to a certain extent, which is further reduced by replacing the agricultural fires data in GFED with VIIRS. Numerical sensitivity experiments show that based on the improved emission inventory, the contribution of biomass burning emissions to PM_2.5 concentrations in Northeast China reaches 32%, contrasting to 15% based on GFED, during the episode from November 1 to 7, 2017. Aerosol direct radiative effects from biomass burning are finally elucidated, which not only reduce downward surface shortwave radiation and planetary boundary layer height, but also affect the vertical distribution of air temperature, wind speed and relative humidity, favorable to the accumulation of PM_2.5. During November 1-7, 2017, the mean daily PM_2.5 enhancement due to aerosol radiative effects from VIIRS_G is 16 μg m^-3, a few times higher than that of 2.8 μg m^-3 from GFED. The study stresses the critical role of biomass burning, particularly of small fires easily missed in the traditional low-resolution satellite products, on air quality.

Thermochemical conversion of large-size woody biomass for carbon neutrality: Principles, applications, and issues

Large-size woody biomass is a valuable renewable resource to replace fossil fuels in biorefinery processes. The preprocessing of wood chips and briquettes is challenging to manage, especially in an industrial setting, as it generates a significant amount of dust and noise and occasionally causes unexpected accidents. As a result, a substantial amount of resources, energy, labor, and space are needed. The thermochemical conversion behavior of large-size woody biomass was studied to reduce energy consumption for chipping. Large-size wood was 1.5 m in length, 0.1 m in breadth, and stacked 90 cm in height. This strategy has many benefits, including increased effectiveness and reduced CO₂ emissions. The target of this paper presents the thermochemical process, and large-size wood was chosen because it provides high-quality product gas while reducing the preprocessing fuel cost. This review examines the benefits of thermochemical conversion technologies for assessing the likelihood of carbon neutrality.

Impacts of springtime biomass burning in Southeast Asia on atmospheric carbonaceous components over the Beibu Gulf in China: Insights from aircraft observations

Limited by the scarcity of in situ vertical observation data, the influences of biomass burning in Southeast Asia on major atmospheric carbonaceous compositions in downwind regions have not been thoroughly studied. In this study, aircraft observations were performed to obtain high time-resolved in situ vertical distributions of black carbon (BC) as well as carbon monoxide (CO) and carbon dioxide (CO₂). Four types of profiles were revealed: Mode I (from 2000 to 3000 m, the BC, CO and CO₂ concentrations were enhanced), Mode II (with increasing altitude, the BC, CO and CO₂ concentrations almost decreased), Mode III (inhomogeneous vertical BC, CO and CO₂ profiles with BC peaks were observed from 2500 to 3000 m) and Mode IV (the BC, CO and CO₂ concentrations increased above 1500 m). Furthermore, simulations were conducted to calculate radiative forcing (RF) caused by BC and study the heating rate (HR) of BC in combination with the vertical BC profiles. A larger BC distribution in the atmosphere resulted in a sharp RF change from negative to positive values, imposing a nonnegligible influence on the atmospheric temperature profile, with maximum HR values ranging from 0.4 to 5.8 K/day. The values of the absorption Ångström exponent (AAE) were 1.46 ± 0.11 and 1.48 ± 0.17 at altitudes from 1000 to 2000 and 2000-3000 m, respectively. The average BC light absorption coefficient at the 370 nm wavelength (α _{BC (370)}) accounted for 50.3 %-76.8 % of the α ₍₃₇₀₎, while the brown carbon (BrC) light absorption coefficient at the 370 nm wavelength (α _{BrC (370)}) contributed 23.2 %-49.7 % to the α ₍₃₇₀₎ at altitudes of 1000-2000 m. At altitudes of 2000-3000 m, α _{BC (370)} and α _{BrC (370)} contributed 43.8 %-88.2 % and 11.8 %-56.2 % to the α ₍₃₇₀₎, respectively. These findings show that calculations that consider the surface BC concentration but ignore the vertical BC distribution could result in massive uncertainties in estimating the RF and HR caused by BC. This study helped achieve a deeper understanding of the influences of biomass burning over the region of Southeast Asia on the profiles of atmospheric carbonaceous compositions and atmospheric BC absorption and its warming effect.

Developing air pollution concentration fields for health studies using multiple methods: Cross-comparison and evaluation

Past air pollution epidemiological studies have used a wide range of methods to develop concentration fields for health analyses. The fields developed differ considerably among these methods. The reasons for these differences and comparisons of their strengths, as well as the limitations for estimating exposures, remains under-investigated. Here, we applied nine methods to develop fields of eight pollutants (carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), fine particulate matter (PM_2.5), and three speciated PM_2.5 constituents including elemental carbon (EC), organic carbon (OC), and sulfate (SO₄)) for the metropolitan Atlanta region for five years. The nine methods are Central Monitor (CM), Site Average (SA), Inverse Distance Weighting (IDW), Kriging (KRIG), Land Use Regression (LUR), satellite Aerosol Optical Depth (AOD), CMAQ model, CMAQ with kriging adjustment (CMAQ-KRIG), and CMAQ based data fusion (CMAQ-DF). Additionally, we applied an increasingly popular method, Random Forest (RF), and compared its results for NO₂ and PM_2.5 with other methods. For statistical evaluation, we focused our discussion on the temporal coefficient of determination, although other metrics are also calculated. Raw output from the CMAQ model contains modeling biases and errors, which are partially mitigated by fusing observational data in the CMAQ-KRIG and CMAQ-DF methods. Based on analyses that simulated model responses to more limited input data, the RF model is more robust and outperforms LUR for PM_2.5. These results suggest RF may have potential in air pollution health studies, especially when limited measurement data are available. The RF method has several important weaknesses, including a relatively poor performance for NO₂, diagnostic challenges, and computational intensiveness. The results of this study will help to improve our understanding of the strengths and weaknesses of different methods for estimating air pollutant exposures in epidemiological studies.

A Pre-Operational System Based on the Assimilation of MODIS Aerosol Optical Depth in the MOCAGE Chemical Transport Model

In this study we present a pre-operational forecasting assimilation system of different types of aerosols. This system has been developed within the chemistry-transport model of Météo-France, MOCAGE, and uses the assimilation of the Aerosol Optical Depth (AOD) from MODIS (Moderate Resolution Imaging Spectroradiometer) onboard both Terra and Aqua. It is based on the AOD assimilation system within the MOCAGE model. It operates on a daily basis with a global configuration of 1∘×1∘ (longitude × latitude). The motivation of such a development is the capability to predict and anticipate extreme events and their impacts on the air quality and the aviation safety in the case of a huge volcanic eruption. The validation of the pre-operational system outputs has been done in terms of AOD compared against the global AERONET observations within two complete years (January 2018–December 2019). The comparison between both datasets shows that the correlation between the MODIS assimilated outputs and AERONET over the whole period of study is 0.77, whereas the biases and the RMSE (Root Mean Square Error) are 0.006 and 0.135, respectively. The ability of the pre-operational system to predict extreme events in near real time such as the desert dust transport and the propagation of the biomass burning was tested and evaluated. We particularly presented and documented the desert dust outbreak which occurred over Greece in late March 2018 as well as the wildfire event which happened on Australia between July 2019 and February 2020. We only presented these two events, but globally the assimilation chain has shown that it is capable of predicting desert dust events and biomass burning aerosols which happen all over the globe.

Thermochemical Conversion of Lignocellulosic Biomass into Mass-Producible Fuels: Emerging Technology Progress and Environmental Sustainability Evaluation

Lignocellulosic biomass is increasingly recognized as a carbon-neutral resource rather than an organic solid waste nowadays. It can be used for the production of various value-added chemicals and biofuels like bio-oil. However, the undesirable properties of bio-oil such as chemical instability, low heating value, high corrosivity, and high viscosity are greatly restricting the utilization of bio-oil as a drop-in fuel. As a consequence, bio-oil should be upgraded. Recently, several emerging methods, such as electrocatalytic hydrogenation, atmospheric distillation, and plasma-assisted catalysis, have been developed for improving the bio-oil quality under mild conditions. Here, we overview the new knowledge on the molecular structure of lignocellulosic biomass gained over the past years and discuss the future challenges and opportunities for further advances of the bio-oil production and upgrading from lignocellulosic biomass. The development of sustainable biomass resource recycle systems with improved efficiency and minimized environmental impacts is analyzed in details. Also, their environmental impacts and sustainability are evaluated. Lastly, the remaining knowledge gaps are identified, and the future research needs that may lead to massive production of biofuels from lignocellulosic biomass are highlighted.

Assessment of the effects of straw burning bans in China: Emissions, air quality, and health impacts

Open biomass burning (OBB) plays an important role in air pollution and climate change by releasing short-term but intensive amounts of particulate matter and gaseous air pollutants. During past years, policies with respect to prohibition on open straw burning have been issued in China in order to mitigate the air pollution problems and the effectiveness of these straw burning bans in different regions remains to be evaluated. In this study, open crop straw burning (OCSB) emissions during 2010-2018 were analyzed based on a commonly used emission inventory with high spatial and temporal resolution. High emissions concentrated over Northeast China (31.8% of national total PM_2.5 emissions in 2018), East China (24.0%), and North China (16.6%). Simulations based on an integrated meteorology-air quality modeling system and an exposure-response function show that OCSB emissions could increase monthly PM_2.5 concentration by as much as 10 μg/m³ during burning seasons in Northeast China and were associated with 4741 premature deaths in 2018. Spatial heterogeneities were observed with respect to the trends of OCSB emissions during 2010-2018. In East China, North China, and Central China, OCSB emissions showed a general declining trend since 2013 while an opposing increasing trend was observed in Northeast China with peak emissions in 2017. Comparing 2013 (before intensive implementation of straw burning bans) and 2018 (after), national total PM_2.5 emissions from OCSB activities decreased by 46.9%, ranging from -14.1% to +70% depending on the specific regions. Northeast China is the only region that showed higher OCSB emissions in 2018 compared to 2013, probably associated with the relatively delayed implementation of the straw burning bans. Avoided number of premature deaths due to reduced OCSB emissions was estimated to be 4256 on a national scale, with most health benefits gained in East and Central China. Results from this study demonstrate the importance of OCSB contribution to PM_2.5 concentrations and spatial heterogeneities exist in terms of the effectiveness of the straw burning bans in reducing OCSB emissions and gained health benefits.

Cause analysis of PM2.5 pollution during the COVID-19 lockdown in Nanning, China

To analyse the cause of the atmospheric PM_2.5 pollution that occurred during the COVID-19 lockdown in Nanning, Guangxi, China, a single particulate aerosol mass spectrometer, aethalometer, and particulate Lidar coupled with monitoring near-surface gaseous pollutants, meteorological conditions, remote fire spot sensing by satellite and backward trajectory models were utilized during 18–24 February 2020. Three haze stages were identified: the pre-pollution period (PPP), pollution accumulation period (PAP) and pollution dissipation period (PDP). The dominant source of PM_2.5 in the PPP was biomass burning (BB) (40.4%), followed by secondary inorganic sources (28.1%) and motor vehicle exhaust (11.7%). The PAP was characterized by a large abundance of secondary inorganic sources, which contributed 56.1% of the total PM_2.5 concentration, followed by BB (17.4%). The absorption Ångström exponent (2.2) in the PPP was higher than that in the other two periods. Analysis of fire spots monitored by remote satellite sensing indicated that open BB in regions around Nanning City could be one of the main factors. A planetary boundary layer-relative humidity-secondary particle matter-particulate matter positive feedback mechanism was employed to elucidate the atmospheric processes in this study. This study highlights the importance of understanding the role of BB, secondary inorganic sources and meteorology in air pollution formation and calls for policies for emission control strategies.

Model vs. observation discrepancy in aerosol characteristics during a half-year long campaign in Northeast China: The role of biomass burning

Complex air pollutant sources and distinct meteorological conditions resulted in unique wintertime haze pollution in the Harbin-Changchun (HC) metropolitan area, China's only national-level city cluster located in the severe cold climate region. In this study, field observation and air quality modeling were combined to investigate fine particulate matter (PM_2.5) pollution during a six-month long heating season in HC's central city (Harbin). The model significantly underpredicted PM_2.5 and organic carbon (by up to ∼230 μg/m³ and 110 μgC/m³, respectively, in terms of daily average) when levoglucosan concentrations were above 0.5 μg/m³. Based on a synthesis of levoglucosan concentrations and fire counts, the large gaps were attributed to underestimation of open burning emissions by the model. However, the model tended to overpredict elemental carbon (more significantly at higher NO₂), likely pointing to an overestimation of vehicle emissions. With increasing levoglucosan, the difference between observed and simulated nitrate (nitrate_obs ‒ nitrate_mod, i.e., Δnitrate) showed a transition from negative to positive values. The positive Δnitrate were attributed to underprediction of the open-burning related nitrate, whereas the negative Δnitrate were likely caused by overprediction of nitrate from other sources (presumably vehicle emissions). The dependence of Δnitrate on levoglucosan indicated that with stronger impact of open burning, the overprediction effect was gradually offset and finally overwhelmed. Influence of open burning on sulfate formation was evident as well, but less apparent compared to nitrate. This study illustrates how the uncertainties in open burning emissions will influence PM_2.5 simulation, on not only primary components but also secondary species.

Time-resolved characterization of organic compounds in PM2.5 collected at Oki Island, Japan, affected by transboundary pollution of biomass and non-biomass burning from Northeast China

To evaluate the transboundary pollution of organic aerosols from Northeast Asia, a highly time-resolved measurement of organic compounds was performed in March 2019 at Oki Island located in Japan, which is a remote site and less affected by local anthropogenic sources. PM_2.5, water-soluble organic carbon (WSOC) concentrations, and WSOC fraction in PM_2.5 showed high values on March 22-23 (high-WSOC period (HWSOC)) when the air mass passed through the area where many fire spots were detected in Northeast China. Biomass burning tracers showed higher concentration, especially levoglucosan exceeded 1 μg/m³ during the HWSOC than the low-WSOC period (LWSOC). Notably, high time-resolved measurements of biomass burning tracers and back trajectory analysis during HWSOC revealed a difference in the variation of lignin pyrolyzed compounds and anhydrous sugars on 22 and 23 March. The air mass passed to different areas in Northeast China in which fire spots were detected, such as the eastern area on the 22nd and the western area on the 23rd. Almost-organic compounds also showed high concentration and strong correlations with levoglucosan and sulfate during HWSOC. Moreover, low-carbon dicarboxylic acids (e.g., adipic acid) and secondary products from anthropogenic volatile organic compounds (e.g., 2,3-dihydroxy-4-oxopentanoic, phthalic, 5-nitrosalicylic acids), also showed a strong correlation with sulfate ions during the HWSOC and LWSOC, respectively. These higher concentrations and strong correlations with levoglucosan and sulfate during the HWSOC propose that their generation could be enhanced by biomass burning. The ratios of organics (e.g., levoglucosan/mannnosan, pinic/3-methylbutane-1,2,3-tricarboxylic acids) suggest that the high concentrations of PM_2.5 and WSOC observed during the HWSOC were caused by aged organic aerosols that originated from the combustion of herbaceous plants transported from Northeast China. Our findings indicate that biomass combustion in Northeast China could significantly affect the chemical compositions and the characterization of organic aerosols in downwind regions of Northeast China.

Impacts of the Tree Canopy and Chemical Reactions on the Dispersion of Reactive Pollutants in Street Canyons

Traffic-related air pollution in street canyons can cause health problems for pedestrians. In order to clarify the behavior of reactive pollutants, such as NOx and O3, in street canyons, a computational fluid dynamics (CFD) model coupled with a chemistry model and tree canopy model was developed, and then, a set of numerical experiments were performed to investigate the impacts of chemical reactions and aerodynamic effects of trees planted in a canyon. The results were compared with the observation data. Through the results of the numerical experiments designed to simulate a realistic urban street canyon, it was found that chemical reactions have a dominant impact on the NO/NO2 ratio and O3 concentration. While the tree canopy had little impact on the NO/NO2 ratio, it had a moderate impact on the flow field in the canyon and the amount of NOx and O3 in the canyon. In accordance with the aerodynamic effects of tree canopies, the local NOx concentration in the experiments increased and decreased by up to 51% and 11%, respectively. The current findings of this study demonstrate the utility of the proposed model for conducting air quality investigations in urban areas.

Assessing the PM2.5 impact of biomass combustion in megacity Dhaka, Bangladesh

In Dhaka, Bangladesh, fine particulate matter (PM_2.5) air pollution shows strong seasonal trends, with significantly higher mean concentrations during winter than during the monsoon (winter = 178.1 μg/m³ vs. monsoon = 30.2 μg/m³). Large-scale open burning of post-harvest agricultural waste across the Indo-Gangetic Plain is a major source of PM_2.5 air pollution in northern India during the non-monsoon period. This study evaluates the extent to which the seasonal differences in PM_2.5 pollution concentrations in Dhaka are accounted for by biomass-burning vs. fossil-fuel combustion sources. To assess this, an index was developed based on elemental potassium (K) as a marker for biomass particulate matter, after adjusting for soil-associated K contributions. Alternatively, particulate sulfur was employed as a tracer index for fossil-fuel combustion PM_2.5. By simultaneously regressing total PM_2.5 on S and adjusted K, the PM_2.5 mass for each day was apportioned into: 1) fossil-fuels combustion associated PM_2.5; 2) biomass-burning associated PM_2.5; and, 3) all other PM_2.5. The results indicated that fossil-fuel combustion contributed 21.6% (19.5 μg/m³), while biomass contributed 40.2% (36.3 μg/m³) of overall average PM_2.5 from September 2013 to December 2017. However, the mean source contributions varied by season: PM_2.5 in Dhaka during the monsoon season was dominated by fossil-fuels sources (44.3%), whereas PM_2.5 mass was dominated by biomass-burning (41.4%) during the remainder of the year. The contribution to PM_2.5 and each of its source components by transport of pollution into Dhaka during non-monsoon time was also evaluated by: 1) Conditional bivariate (CBPF) and pollution rose plots; 2) Concentration weighted trajectories (CWT), and; 3) NASA satellite photos to identify aerosol loading and fire locations on high pollution days. The collective evidence indicates that, while the air pollution in Dhaka is contributed to by both local and transboundary sources, the highest pollution days were dominated by biomass-related PM_2.5, during periods of crop-burning in the Indo-Gangetic Plain.

Impacts of post-harvest open biomass burning and burning ban policy on severe haze in the Northeastern China

Open filed biomass burning is a major contributor to airborne particulate matter and reactive trace gases during the post-harvest season in the Northeastern China. Due to prevailing weather conditions and high emission density, this region is prone to the accumulation of air pollutants that often leads to severe haze events. In this study, we combined satellite and ground observations, and a regional air quality modeling system to quantify the contribution of open biomass burning to surface PM_2.5 (particulate matter with diameter less than 2.5 µm) concentrations during a severe haze episode. During this period (November 1^st - 4^th, 2015), the average PM_2.5 concentrations in Heilongjiang, Jilin, and Liaoning provinces reached 116.98 μg/m³, 98.60 μg/m³, and 70.17 μg/m³ respectively. Model simulations showed that open biomass burning contributed to 52.7% of PM_2.5 concentrations over Northeast China. Using the differences in active fire spots as detected by the Visible Infrared Imaging Radiometer Suites (VIIRS) aboard the Suomi-NPP, we estimated that the burning ban enforced in 2018 have caused the PM_2.5 concentrations to decrease from the 2015 level by 67.10%, 53.23%, and 10.06% in the Heilongjiang, Jilin, and Liaoning provinces respectively. Over the region, the burning ban proved to be effective in reducing fire emissions and lowering region-wide PM_2.5 concentration by 48.1% during the post-harvest season.

Numerical study of air pollution over a typical basin topography: Source appointment of fine particulate matter during one severe haze in the megacity Xi'an

Many cities are located in lands with typical basin topographies, which are not conducive to the spread of air pollutants. In the winter of 2016/2017, a severe haze happened in Xi'an, the main city in the Guanzhong Basin in central China. When the peak daily concentration of fine particulate matter (PM_2.5) reaches 499 μg/m³, the source of the atmospheric pollution needs to be found urgently in order to take countermeasures. The comprehensive air quality model with extensions, coupled with the tracer tagging particulate source apportionment technology (PSAT) module, and an improved emission inventory, higher grid resolution, and bigger inner domain area, have been applied to quantify the contributions of local and regional emissions to the PM_2.5 pollutions. The model performed well in time period considered in this study. The correlation of the simulated daily PM_2.5 concentration data reaches 0.82, and the fraction of predictions within a factor of two of observations approaches 84%. With the PSAT module, the PM_2.5 contributions from local and regional sources to the urban centre and rural areas during the severe winter haze event are analysed in detail. The PM_2.5 concentrations in the urban centre in Xi'an is mainly originating from local emissions (60%), and Xianyang City is the largest contributor among the surrounding source regions (11.6%), while the transportation sector outside the Shaanxi Province (5.1%) also contributes significantly. Comparatively, the rural areas have lower local contributions and higher transport contributions. In particular, in the northern rural area Yanliang, the contribution from surrounding source regions approaches 82%. The results of this study suggest that to improve the air quality in a typical basin city, a regional-scale coordinated emissions control should be used, focusing on the emissions from both local and surrounding areas.

Detection of PM2.5 plume movement from IoT ground level monitoring data

In this study, we analysed a data set from 10 low-cost PM_2.5 sensors using the Internet of Things (IoT) for air quality monitoring in Mae Sot, which is one of the most vulnerable areas for high PM_2.5 concentration in Thailand, during the 2018 burning season. Our objectives were to understand the nature of the plume movement and to investigate possibilities of adopting IoT sensors for near real-time forecasting of PM_2.5 concentrations. Sensor data including PM_2.5 and meteorological parameters (wind speed and direction) were collected online every 2 min where data were grouped into four zones and averaged every 15 min interval. Results of diurnal profile plot revealed that PM_2.5 concentrations were high around early to late morning (3:00-9:00) and gradually reduced till the rest of the day. During the biomass burning period, maximum daily average concentration recorded by the sensors was 280 μg/m³ at Thai Samakkhi while the minimum was 13 μg/m³ at Mae Sot. Lag time concentrations, attributed by biomass burning (hotspots), significantly influenced the formation of PM_2.5 while the disappearance of PM_2.5 was found to be influenced by moderate wind speed. The PM_2.5 concentrations of the next 15 min at the downwind zone (MG) were predicted using lag time concentrations with different wind categories. The next 15 min predictions of PM_2.5 at MG were found to be mainly influenced by its lag time concentrations (MG_Lag); with higher wind speed, however, the lag time concentrations from the upwind zones (MS_Lag and TS_Lag) started to show more influence. From this study, we have found that low-cost IoT sensors provide not only real-time monitoring information but also demonstrate great potential as an effective tool to understand the PM_2.5 plume movement with temporal variation and geo-specific location.

CO2, CO, hydrocarbon gases and PM2.5 emissions on dry season by deforestation fires in the Brazilian Amazonia

The rate of deforestation in Brazil increased by 29% between 2015 and 2016, resulting in an increase of greenhouse gas emissions (GHG) of 9%. Deforestation fires in the Amazonia are the main source of GHG in Brazil. In this work, amounts of CO₂, CO, main hydrocarbon gases and PM_2.5 emitted during deforestation fires, under real conditions directly in Brazilian Amazonia, were determined. A brief discussion of the relationship between the annual emission of CO₂ equivalent (CO_2,eq) and Paris Agreement was conducted. Experimental fires were carried out in Western Amazonia (Candeias do Jamari, Rio Branco and Cruzeiro do Sul) and results were compared with a previous fire carried out in Eastern Amazonia (Alta Floresta). The average total fresh biomass on the ground before burning and the total biomass consumption were estimated to be 591 ton ha^-1 and 33%, respectively. CO₂, CO, CH₄, and non-methane hydrocarbon (NMHC) average emission factors, for the four sites, were 1568, 140, 8, and 3 g kg^-1 of burned dry biomass, respectively. PM_2.5 showed large variation among the sites (0.9-16 g kg^-1). Emissions per hectare of forest were estimated as 216,696 kg of CO₂, 18,979 kg of CO, 1,058 kg of CH₄, and 496 kg of NMHC. The average annual emission of equivalent CO₂ was estimated as 301 ± 53 Mt year^-1 for the Brazilian Amazonia forest. From 2013, the estimated CO_2,eq showed a trend to increase in Amazon region. The present study is an alert and provides important information that can be used in the development of the public policies to control emissions and deforestation in the Brazilian Amazonia.

The impact of the direct effect of aerosols on meteorology and air quality using aerosol optical depth assimilation during the KORUS-AQ campaign

To quantify the impact of the direct aerosol effect accurately, this study incorporated the Geostationary Ocean Color Imager (GOCI) aerosol optical depth (AOD) into a coupled meteorology-chemistry model. We designed three model simulations to observe the impact of AOD assimilation and aerosol feedback during the KORUS-AQ campaign (May - June 2016). By assimilating the GOCI AOD with high temporal and spatial resolutions, we improve the statistics from the comparison AOD and AERONET data (RMSE: 0.12, R: 0.77, IOA: 0.69, MAE: 0.08). The inclusion of the direct effect of aerosols produces the best model performance (RMSE: 0.10, R: 0.86, IOA: 0.72, MAE: 0.07). AOD values were increased as much as 0.15, which is associated with an average reduction in solar radiation of -31.39 W/m², a planetary boundary layer height (-104.70 m), an air temperature (-0.58 °C), and a surface wind speed (-0.07 m/s) over land. In addition, concentrations of major gaseous and particulate pollutants at the surface (SO₂, NO₂, NH₃, SO 4 2 - , NO 3 - , NH 4 + , PM_2.5) increase by 7.87 - 34% while OH concentration decreases by -4.58 %. Changes in meteorology and air quality appear to be more significant in high-aerosol loading areas. The integrated process rate analysis shows decelerated vertical transport, resulting in an accumulation of air pollutants near the surface and the amount of nitrate, which is higher than that of sulfate because of its response to reduced temperature. We conclude that constraining aerosol concentrations using geostationary satellite data is a prerequisite for quantifying the impact of aerosols on meteorology and air quality.