Anthropogenic Emission Inventory Research Articles

ACEIC: a comprehensive anthropogenic chlorine emission inventory for China

Abstract. Chlorine species play a crucial role as precursors to Cl radicals, which can significantly impact the atmospheric oxidation capacity and influence the levels of trace gases related to climate and air quality. Several studies have established a chlorine emission inventory in China in recent years, but the emission remains uncertain and requires further investigation. The Anthropogenic Chlorine Emission Inventory for China (ACEIC) was the first chlorine emission inventory for China based on local data developed in our previous study, which only includes the emissions from coal combustion and waste incineration. In this study, we updated this inventory to include data for a more recent year (2019) and expanded the range of species considered (HCl, fine particulate Cl−, Cl2, and hypochlorous acid (HOCl)) and the number of anthropogenic sources (41 specific sources). Compared with previous studies, this updated inventory considered more anthropogenic sources, used more localized emission factors, and adopted more refined estimation methods. The total emissions of HCl, fine particulate Cl−, Cl2, and HOCl in mainland China for the year 2019 were estimated to be 361 (−18 % to 27 %), 174 (−27 % to 59 %), 18 (−10 % to 15 %), and 79 (−12 % to 18 %) Gg, respectively. To facilitate analysis, we aggregated the chlorine emissions from various sources into five economic sectors: power, industry, residential, agriculture, and biomass burning. HCl emissions were primarily derived from the industry (43 %), biomass burning (38 %), and residential (13 %) sectors. The biomass burning and industry sectors accounted for 74 % and 19 % of the fine particulate Cl− emissions, respectively. Residential and industry sectors contributed 61 % and 29 % of the total Cl2 emissions. HOCl emissions were predominantly from the residential sector, constituting 90 % of the total emissions. Notably, the usage of chlorine-containing disinfectants was identified as the most significant source of Cl2 and HOCl emissions in the residential sector. Geographically, regions with high HCl and fine particulate Cl− emissions were found in the North China Plain, northeastern China, central China, and the Yangtze River Delta, whereas the Pearl River Delta, Yangtze River Delta, and Beijing–Tianjin–Hebei regions exhibited elevated levels of Cl2 and HOCl emissions. Regarding monthly variation, emissions of HCl and fine particulate Cl− were higher during early spring (February to April) and winter (December to January) due to intensified agricultural activities, while Cl2 and HOCl emissions were higher in the summer months due to increased demand for water disinfection. We incorporated this emission inventory into the chemical transport model and found the simulated concentrations of chlorine species agreed reasonably well with the observations, which suggested the relatively faithful estimations of their emissions. This updated inventory contributes to a better understanding of anthropogenic sources of chlorine species and can aid in the formulation of emission control strategies to mitigate secondary pollution in China.

Unexpected anthropogenic emission decreases explain recent atmospheric mercury concentration declines.

Anthropogenic activities emit ~2,000 Mg y-1 of the toxic pollutant mercury (Hg) into the atmosphere, leading to long-range transport and deposition to remote ecosystems. Global anthropogenic emission inventories report increases in Northern Hemispheric (NH) Hg emissions during the last three decades, in contradiction with the observed decline in atmospheric Hg concentrations at NH measurement stations. Many factors can obscure the link between anthropogenic emissions and atmospheric Hg concentrations, including trends in the reemissions of previously released anthropogenic ("legacy") Hg, atmospheric sink variability, and spatial heterogeneity of monitoring data. Here, we assess the observed trends in gaseous elemental mercury (Hg0) in the NH and apply biogeochemical box modeling and chemical transport modeling to understand the trend drivers. Using linear mixed effects modeling of observational data from 51 stations, we find negative Hg0 trends in most NH regions, with an overall trend for 2005 to 2020 of -0.011 ± 0.006 ng m-3 y-1 (±2 SD). In contrast to existing emission inventories, our modeling analysis suggests that annual NH anthropogenic emissions must have declined by at least 140 Mg between the years 2005 and 2020 to be consistent with observed trends. Faster declines in 95th percentile Hg0 values than median values in Europe, North America, and East Asian measurement stations corroborate that the likely cause is a decline in nearby anthropogenic emissions rather than background legacy reemissions. Our results are relevant for evaluating the effectiveness of the Minamata Convention on Mercury, demonstrating that existing emission inventories are incompatible with the observed Hg0 declines.

Local and regional enhancements of CH4, CO, and CO2 inferred from TCCON column measurements

Abstract. In this study, we demonstrate the utility of available correlative measurements of carbon species to identify regional and local air mass characteristics as well as their associated source types. In particular, we combine different regression techniques and enhancement ratio algorithms with carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) total column abundance from 11 sites of the Total Carbon Column Observing Network (TCCON) to infer relative contributions of regional and local sources to each of these sites. The enhancement ratios provide a viable alternative to univariate measures of relationships between the trace gases that are insufficient in capturing source-type and transport signatures. Regional enhancements are estimated from the difference between bivariate regressions across a specific time window of observed total abundance of these species (BERr for bulk enhancement regression ratio) and inferred anomalies (AERr for anomaly enhancement regression ratio) associated with a site-specific background. Since BERr and AERr represent the bulk and local species enhancement ratio, respectively, its difference simply represents the site-specific regional component of these ratios. We can then compare these enhancements for CO2 and CH4 with CO to differentiate between combustion and non-combustion air masses. Our results show that while the regional and local influences in enhancements vary across sites, dominant characteristics are found to be consistent with previous studies over these sites and with bottom-up anthropogenic and fire emission inventories. The site in Pasadena shows a dominant local influence (> 60 %) across all species enhancement ratios, which appear to come from a mixture of biospheric and combustion activities. In contrast, Anmyeondo shows more regionally influenced (> 60 %) air masses associated with high-temperature and/or biofuel combustion activities. Ascension Island appears to only show a large regional influence (> 80 %) on CO / CO2 and CO / CH4, which is indicative of transported and combustion-related CO from the nearby African region, consistent with a sharp rise in column CO (3.51 ± 0.43 % ppb yr−1) at this site. These methods have important applications to source analysis using spaceborne column retrievals of these species.

On the Biases of MERRA-2 Reanalysis and Ground-Based Measurements of Black Carbon Aerosols Over India

The precise measurement of black carbon (BC) and assessment of involved biases are very important considering its serious health and climatic effects. MERRA-2 reanalysis data (modern-era retrospective analysis for research and applications, version 2) of surface black carbon (SBC) and ground measurements by optical photometers (mostly Aethalometer) have been used widely to study the temporal and spatial variation of BC aerosols over India. However, a significant bias (more than 70%) between MERRA-2 SBC concentration and ground measurements of BC (by Aethalometer, referred as MBC (AE)) was observed by Malik and Aggarwal, (2021). In the current study, the possible reasons for this bias are further evaluated by comparing the MERRA-2 SBC and Aethalometer measurements against a reference photometer, i.e., continuous soot monitoring system (COSMOS). Three-year (2020-2022) SBC concentrations of MERRA-2 reanalysis data are compared against simultaneous measurements of BC by COSMOS (MBC (COSMOS)). Additionally, the biases in ground measurements are further investigated by comparing one-month (March 2023) observations of Aethalometer (MBC (AE)). These comparison results revealed a 40% underestimation in MERRA-2 reanalysis during 2020-2022. The higher underestimation (50%) of SBC during increased biomass emissions months (October to May), in contrast to the 25% underestimation during conventional emissions months (June to September), emphasizes the underestimation of biomass emissions inputs in MERRA-2 SBC reanalysis. The initial large bias between raw data of Aethalometer (MBC (AE-raw) = 1.92-1.98 times MBC (COSMOS)) get reduced significantly when correction due to multiple scattering in the filter media and mass absorption cross-section (MAC) are incorporated to correct the Aethalometer data (MBC (AE-corr) = 1.15-1.18 times MBC (COSMOS)). The findings of this study underscore the need to harmonize the correction methods for multiple scattering and redefine the MAC values for Aethalometer measurements as well as updating the anthropogenic emission inventories in MERRA-2 SBC reanalysis.

Source attribution of carbon monoxide over Northern India during crop residue burning period over Punjab

National Capital Territory of Delhi and its satellite cities suffer from poor air quality during the post-monsoon months of October–November. In this study, a novel attempt is made to estimate the contribution of different emission sources (industrial, residential, power generation, transportation, biomass burning, photochemical production, lateral transport, etc.) towards the criteria air pollutant carbon monoxide (CO) concentration over North India. Multiple simulations of the WRF-Chem model with a tagged tracer approach with different inputs (6 anthropogenic emission inventories and 3 biomass burning emission inventories) were used. The model performance was evaluated against the MOPITT retrieved CO surface concentration. Analysis of model simulated CO over North India suggests that anthropogenic emissions contribute around 32–49% to surface CO concentration while crop residue burning contributes 27–44% of which 80% originates from Punjab. For Delhi, the contribution from anthropogenic sources is dominant (53–77%) of which 10–28% is from the domestic sector and 14–55% is from the transport sector. Agricultural waste burning contributes about 15–30% to Delhi's surface CO concentration (of which 75% originates from Punjab). Crop residue burning emission is a chief source of CO over Punjab with a contribution of about 56–76%. The results suggest that industrial, transport, and domestic sector activities are more responsible for increased CO levels over New Delhi and surrounding regions than crop residue burning over Punjab. Furthermore, critical meteorological parameters like 10 m wind speed, boundary layer height, 2 m temperature, total precipitation, and relative humidity were evaluated against CO concentration to understand their impact on CO distribution. Results conclude that deteriorating air quality over the North Indian region is caused by a combination of prevailing meteorological factors (such as slow winds, shallow mixing layer, and cold temperatures) and man-made emissions.

Evaluation of WRF-Chem PM2.5 simulations in Thailand with different anthropogenic and biomass-burning emissions

Thailand experiences severe air quality issues, predominantly due to PM2.5 pollution that surpasses WHO guidelines. The main sources are attributed to energy production, industrial activities, vehicular emissions, agricultural burning, and transboundary transport of pollutants. Understanding the transport and transformation of these pollutants is necessary for addressing air quality issues. The Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) provides information about meteorology, chemical reactions, and transport of trace gases and aerosols. The accuracy of WRF-Chem simulations greatly depends on the choice of anthropogenic and biomass burning emissions inventories. This study provides a detailed evaluation of these inventories to model PM2.5 concentrations in Thailand during both haze and off-haze seasons in 2019. We evaluated WRF-Chem using four anthropogenic emission inventories—CAMS-GLOB-ANT, ECLIPSE, HTAP, and REAS—and four biomass burning emissions inventories—FINN1.5, FINN2.5 MOD, FINN2.5 MODVAR, and QFED—using data from ground-based air quality stations, MODIS AOD, and MOPITT CO satellite data. Our findings suggest CAMS-GLOB-ANT performs optimally for North Thailand, while HTAP and REAS are more effective in Eastern Thailand. For biomass burning, FINN1.5 shows superior performance. The study also highlights the challenge in capturing PM2.5 diurnal variability, particularly due to inaccuracies in simulating the planetary boundary layer height during nighttime in complex terrains. Moreover, our analysis exhibits moderate model performances during the off-haze season while using global and regional anthropogenic emissions in Thailand, emphasizing the need for improving anthropogenic inventories for reliable air quality prediction. For biomass burning emissions, updating emission factors to reflect Thailand's specific vegetation types is recommended to improve WRF-Chem's representation of PM2.5 levels.

Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote-sensing observations

Abstract. Formaldehyde (HCHO), a precursor to tropospheric ozone, is an important tracer of volatile organic compounds (VOCs) in the atmosphere. Two years (2019–2020) of HCHO simulations obtained from the global chemistry transport model CHASER at a horizontal resolution of 2.8° × 2.8° have been evaluated using the Tropospheric Monitoring Instrument (TROPOMI) and multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations. In situ measurements from the Atmospheric Tomography Mission (ATom) in 2018 were used to evaluate the HCHO simulations for 2018. CHASER reproduced the TROPOMI-observed global HCHO spatial distribution with a spatial correlation (r) of 0.93 and a negative bias of 7 %. The model showed a good capability to reproduce the observed magnitude of the HCHO seasonality in different regions, including the background conditions. The discrepancies between the model and satellite in the Asian regions were related mainly to the underestimated and missing anthropogenic emission inventories. The maximum difference between two HCHO simulations based on two different nitrogen oxide (NOx) emission inventories was 20 %. TROPOMI's finer spatial resolution than that of the Ozone Monitoring Instrument (OMI) sensor reduced the global model–satellite root-mean-square error (RMSE) by 20 %. The OMI- and TROPOMI-observed seasonal variations in HCHO abundances were consistent. The simulated seasonality showed better agreement with TROPOMI in most regions. The simulated HCHO and isoprene profiles correlated strongly (R=0.81) with the ATom observations. However, CHASER overestimated HCHO mixing ratios over dense vegetation areas in South America and the remote Pacific region (background condition), mainly within the planetary boundary layer (< 2 km). The simulated seasonal variations in the HCHO columns showed good agreement (R>0.70) with the MAX-DOAS observations and agreed within the 1σ standard deviation of the observed values. However, the temporal correlation (R∼0.40) was moderate on a daily scale. CHASER underestimated the HCHO levels at all sites, and the peak occurrences in the observed and simulated HCHO seasonality differed. The coarseness of the model's resolution could potentially lead to such discrepancies. Sensitivity studies showed that anthropogenic emissions were the highest contributor (up to ∼ 35 %) to the wintertime regional HCHO levels.

Evaluation and prediction of anthropogenic impacts on long-term multimedia fate and health risks of PFOS and PFOA in the Elbe River Basin

Perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) have aroused great concern owing to their widespread occurrence and toxic effects. However, their long-term trends and multimedia fate remain largely unknown. Here, we investigate the spatiotemporal characteristics and periodic oscillations of PFOS and PFOA in the Elbe River between 2010 and 2021. Anthropogenic emission inventories and multimedia fugacity model were developed to analyse their historical and future transport fates and quantify related human risks in each medium for the three age groups. The results show that average PFOS and PFOA concentrations in the Elbe River were 4.08 and 3.41 ng/L, declining at the annual rate of 7.36% and 4.98% during the study period, respectively. Periodic oscillations of their concentrations and mass fluxes were most pronounced at 40–60 and 20–40 months. The multimedia fugacity model revealed that higher concentrations occurred in fish (PFOS: 14.29, PFOA: 0.40 ng/g), while the soil was their dominant sink (PFOS: 179, PFOA: 95 tons). The exchange flux between water and sediment was the dominant pathway in multimedia transportation (397 kg/year). Although PFOS and PFOA concentrations are projected to decrease by 22.41% and 50.08%, respectively, from 2021 to 2050, the hazard quotient of PFOS in fish is a low hazard. This study provides information for the assessment of PFOS and PFOA pollution in global watersheds and the development of related mitigation policies, such as banning fish predation in polluted rivers, to mitigate their risks.

Light oxygenated volatile organic compound concentrations in an Eastern Mediterranean urban atmosphere rivalling those in megacities

Highly resolved measurements of primary and secondary oxygenated volatile organic compounds (OVOCs) by proton-transfer-reaction mass spectrometry (PTR-MS) and the AMOVOC sampler (Airborne Measurements Of VOC) were performed in Beirut, Lebanon, during the ECOCEM (Emissions and Chemistry of Organic Carbon in the East Mediterranean) experiments. The OVOC concentrations (0.15–7.0 ppb) rival those reported for international megacities like Paris, Tokyo, or São Paulo (0.3–6.5 ppb). This study highlights the seasonal variability of OVOCs, the potential role of background pollution on OVOC concentrations, traffic emissions of OVOCs, and the secondary production of OVOCs during both summer and winter.The primary and secondary OVOC fractions were estimated using two methods based on the night-time emission ratio and photochemical age. Our calculations coupled with a correlation analysis revealed the following: firstly, background concentrations contributed significantly, especially for longer-lived OVOCs, such as methanol and acetone (30%–80%). Secondly, secondary production in summer increased up to 60%, except for methanol and isoprene oxidation products, i.e., for methacrolein and methyl vinyl ketone. Thirdly, the secondary production in the Eastern Mediterranean persisted in winter, and finally, strong primary traffic emissions dominated the primary biogenic emissions.Finally, the emission ratios were used to evaluate the global anthropogenic emission inventories downscaled to Lebanon. Although limited to two individual non-lumped species (formaldehyde and acetone), the emission ratios compared well, within a factor of 2. However, the emissions of aldehydes and ketones from the CAMS, Edgar, and MACCITY inventories showed discrepancies of up to three orders of magnitude. This demonstrates a need for improved OVOC representation in emission inventories, considering the atmospheric relevance and abundance of OVOCs and their use in volatile chemical products.

Improvement of the anthropogenic emission rate estimate in Ulaanbaatar, Mongolia, for 2020–21 winter

Ulaanbaatar (UB), the fast-growing capital of Mongolia, is known for its world's worst level of particulate matter (PM) concentrations in winter. However, current anthropogenic emission inventories over the UB are based on data from more than fifteen years ago, and satellite observations are scarce because UB is in high latitudes. During the winter of 2020–21, the first period of the Fine Particle Research Initiative in East Asia considering the National Differences (FRIEND), several times higher concentrations of PM in UB compared to other urban sites in East Asia were observed but not reproduced with a chemical transport model mainly due to the underestimated anthropogenic emissions. Therefore, we devised a method for sequentially adjusting emissions based on the reactivity of PM precursors using ground observations. We scaled emission rates for the inert species (CO, elemental carbon (EC), and organic carbon (OC)) to reproduce their observed ambient concentrations, followed by SO2 to reproduce the concentration of SO42−, which was examined to have the least uncertainty based on the abundance of observed NH3, and finally NO and NH3 for NO3−, and NH4+. This improved estimation is compared to regional inventories for Asia and suggests more than an order of magnitude increase in anthropogenic emissions in UB. Using the improved emission inventory, we were able to successfully reproduce independent observation data on PM2.5 concentrations in UB in December 2021 from the U.S. Embassy. During the campaign period, we found more than 50% of the SO42−, NO3−, and NH4+ increased in UB due to the improvement could travel to Beijing, China (BJ), and about 20% of the SO42− could travel to Noto, Japan (NT), more than 3000 km away. Also, the anthropogenic emissions in UB can effectively increase OC, NO3−, and NH4+ concentrations in BJ when Gobi dust storms occur.

Detection of Chinese Spring Festival in Beijing using in-situ CO2 observations and atmospheric inversion

Anthropogenic CO2 emissions inventories in urban areas are highly uncertain and lack fine-scale temporal information. Here, we use atmospheric CO2 observations from 6 sites and an ensemble-based "top-down" inversion system to estimate the spatiotemporal dynamics of CO2 emissions in the world's largest urban agglomeration of Beijing-Tianjin-Hebei (JJJ). Relative to the period before the Chinese Spring Festival (CSF) in 2019, we showed, for the first time, a 13.9% reduction and a 14.3% increase in emissions during and after the CSF, respectively, which is missed by a monthly emissions inventory. Moreover, the emissions reduction occurred in most of the JJJ areas. The exact timing of emissions dynamics inferred from the CO2 observations is consistent with a NO2 observation and a near-real-time daily “bottom-up” estimate. Here, we showed the advantages of "top-down" inversion on a fine temporal scale (e.g., daily to weekly) emissions assessment and its potential applications in refined emissions management and reductions.

Coordinated Control of Carbon Emission Reduction and Air Quality Improvement in the Industrial Sector in Hunan Province

Climate warming and air pollution are the main environmental problems in China. This study used China's Carbon Accounting Database, energy economic model, and air quality model to analyze the potential carbon emission peaking path and synergistic air quality improvement gain in the industrial sector in Hunan Province. Based on China's Carbon Accounting Database and the local industry/energy statistical yearbooks in Hunan, the total CO2 emissions in Hunan Province in 2019 were 310.6 Mt, of which the industrial sector accounted for over 70% of the emissions, mainly from the production and supply of electricity, steam, and heat; the production of non-metallic minerals; and the smelting and pressing of ferrous metals. Three potential industrial carbon emission peaking scenarios were analyzed using the LEAP energy economic model, including the business-as-usual scenario (peaking by 2030), moderate emission reduction scenario (peaking by 2028), and aggressive emission reduction scenario (peaking by 2025), by employing different economic growth rates, energy technology progress, and energy structures of the industrial sector. Furthermore, by combining the anthropogenic air pollutant emission inventory and the regional air quality model WRF-Chem, we analyzed the air quality improvement associated with various carbon emission peak paths. The results showed that the annual mean concentrations of major air pollutants had decreased in the three scenarios, especially in the Chang-Zhu-Tan Region. The aggressive emission reduction scenario was the most effective scenario, followed by the moderate emission reduction scenario and the business-as-usual scenario. Manufacturing was the sector with the most significant synergistic effect of pollution and carbon reduction. When carbon emission peaks were achieved, the annual average concentrations of PM2.5 and PM10 in Hunan Province could be synergistically reduced by 0.6-1.8 μg·m-3 and 1.8-8.9 μg·m-3, respectively. Our findings offer important insights into carbon emission peaking and can provide useful information for potential mitigation actions.

Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL

Abstract. To design a monitoring network for estimating CO2 fluxes in an urban area, a high-resolution observing system simulation experiment (OSSE) is performed using the transport model Graz Mesoscale Model (GRAMMv19.1) coupled to the Graz Lagrangian Model (GRALv19.1). First, a high-resolution anthropogenic emission inventory which is considered as the truth serves as input to the model to simulate CO2 concentration in the urban atmosphere on 10 m horizontal resolution in a 12.3 km × 12.3 km domain centred in Heidelberg, Germany. By sampling the CO2 concentration at selected stations and feeding the measurements into a Bayesian inverse framework, CO2 fluxes on a neighbourhood scale are estimated. Different configurations of possible measurement networks are tested to assess the precision of posterior CO2 fluxes. We determine the trade-off between the quality and quantity of sensors by comparing the information content for different set-ups. Decisions on investing in a larger number or in more precise sensors can be based on this result. We further analyse optimal sensor locations for flux estimation using a Monte Carlo approach. We examine the benefit of additionally measuring carbon monoxide (CO). We find that including CO as tracer in the inversion enables the disaggregation of different emission sectors. Finally, we quantify the benefit of introducing a temporal correlation into the prior emissions. The results of this study have implications for an optimal measurement network design for a city like Heidelberg. The study showcases the general usefulness of the inverse framework developed using GRAMM/GRAL for planning and evaluating measurement networks in an urban area.

OMI-based emission source classification in East China and its spatial redistribution in view of pollution control measures

This study aims to generate a satellite-based qualitative emission source characterization for the heavily polluted eastern part of China in the 2010–2016 time period. The applied source identification technique relies on satellite-based NOx and SO2 emission estimates by OMI, their SO2:NOx ratio, and the MIX anthropogenic emission inventory to distinguish emissions from different emission categories (urban, industrial, natural) and characterize the dominant source per 0.25° × 0.25° grid cell in East China. Overall, we find good agreement between the satellite- and emission inventory–based spatiotemporal distribution and characterization of the dominant emission sources in East China in 2010–2016. In 2010, the satellite measurements suggest an emission distribution less dominated by industrial areas, a somewhat larger role for urban/transportation areas and agricultural activities, and more natural emissions in the southern part compared to the bottom-up emission categorization. In 2016, more than half of the classified emission categories over East China have remained the same. At the same time, there is a notable increase of agricultural lands and decrease of areas dominated by industry/transportation in 2016, suggestive of an overall decrease in heavy air pollution in East China over the course of 7 years. This is likely attributed to the sustained efforts of the Chinese government to drastically improve the air quality, especially since 2013 when the National Air Pollution Prevention and Control Action Plan was enacted. However, signs of urban expansion (urbanization) and rural–urban migration (“Go West” motion) stemmed from China’s rapid economic growth and labour demand are evident; escalating industrialization (even with cleaner means) and the urban population growth in East China resulted in stronger emissions from sources representing consumption and transportation which are strongly related to NO2 and PM10 pollution (rather than SO2) and are directly influenced by the population size. This resulted to a shift of the emissions from the east mainly to the north and northwest of East China. Overall, although the effectiveness of the Chinese environmental control policies has been successful, the air pollution problem remains an important concern.

Establishment and verification of anthropogenic speciated VOCs emission inventory of Central China

Improving the accuracy of anthropogenic volatile organic compounds (VOCs) emission inventory is crucial for reducing atmospheric pollution and formulating control policy of air pollution. In this study, an anthropogenic speciated VOCs emission inventory was established for Central China represented by Henan Province at a 3 km × 3 km spatial resolution based on the emission factor method. The 2019 VOCs emission in Henan Province was 1003.5 Gg, while industrial process source (33.7%) was the highest emission source, Zhengzhou (17.9%) was the city with highest emission and April and August were the months with the more emissions. High VOCs emission regions were concentrated in downtown areas and industrial parks. Alkanes and aromatic hydrocarbons were the main VOCs contribution groups. The species composition, source contribution and spatial distribution were verified and evaluated through tracer ratio method (TR), Positive Matrix Factorization Model (PMF) and remote sensing inversion (RSI). Results show that both the emission results by emission inventory (EI) (15.7 Gg) and by TR method (13.6 Gg) and source contribution by EI and PMF are familiar. The spatial distribution of HCHO primary emission based on RSI is basically consistent with that of HCHO emission based on EI with a R-value of 0.73. The verification results show that the VOCs emission inventory and speciated emission inventory established in this study are relatively reliable.

Deforestation as an Anthropogenic Driver of Mercury Pollution.

Deforestation reduces the capacity of the terrestrial biosphere to take up toxic pollutant mercury (Hg) and enhances the release of secondary Hg from soils. The consequences of deforestation for Hg cycling are not currently considered by anthropogenic emission inventories or specifically addressed under the global Minamata Convention on Mercury. Using global Hg modeling constrained by field observations, we estimate that net Hg fluxes to the atmosphere due to deforestation are 217 Mg year-1 (95% confidence interval (CI): 134-1650 Mg year-1) for 2015, approximately 10% of global primary anthropogenic emissions. If deforestation of the Amazon rainforest continues at business-as-usual rates, net Hg emissions from the region will increase by 153 Mg year-1 by 2050 (CI: 97-418 Mg year-1), enhancing the transport and subsequent deposition of Hg to aquatic ecosystems. Substantial Hg emissions reductions are found for two potential cases of land use policies: conservation of the Amazon rainforest (92 Mg year-1, 95% CI: 59-234 Mg year-1) and global reforestation (98 Mg year-1, 95% CI: 64-449 Mg year-1). We conclude that deforestation-related emissions should be incorporated as an anthropogenic source in Hg inventories and that land use policy could be leveraged to address global Hg pollution.

Significant Increase in Ammonia Emissions in China: Considering Nonagricultural Sectors Based on Isotopic Source Apportionment.

Isotopic source apportionment results revealed that nonagricultural sectors are significant sources of ammonia (NH3) emissions, particularly in urban areas. Unfortunately, nonagricultural sources have been substantially underrepresented in the current anthropogenic NH3 emission inventories (EIs). Here, we propose a novel approach to develop a gridded EI of nonagricultural NH3 in China for 2016 using a combination of isotopic source apportionment results and the emission ratios of carbon monoxide (CO) and NH3. We estimated that isotope-corrected nonagricultural NH3 emissions were 4370 Gg in China in 2016, accounting for an increase in the total NH3 emissions from 7 to 31%. As a result, compared to the original NH3 EI, the annual emissions of total NH3 increased by 35%. Thus, in comparison to the simulation driven by the original NH3 EI, the WRF-Chem model driven by the isotope-corrected NH3 EI has reduced the model biases in the surface concentrations and dry deposition flux of reduced nitrogen (NHx = gaseous NH3 + particulate NH4+) by 23 and 31%, respectively. This study may have wide-ranging implications for formulating targeted strategies for nonagricultural NH3 emissions controls, making it facilitate the achievement of simultaneously alleviating nitrogen deposition and atmospheric pollution in the future.

Multimedia fate simulation of mercury in a coastal urban area based on the fugacity/aquivalence method

Due to intensive industrial production and living activities, urban areas are the main anthropogenic mercury (Hg) emission sources. After entering the environment through exhaust gases, wastewater or waste residues, Hg can migrate and transform among different environmental compartments in various species, such as elemental mercury (Hg0), divalent mercury (Hg2+) and methylmercury (MeHg). Studies have yet to report on the multimedia behaviors of Hg in urban areas due to the complexity of the processes involved. In this study, the atmospheric Hg emission in Dalian, a coastal city in Northeast China, was estimated by an anthropogenic emission inventory, and a Level III multimedia model was constructed based on the fugacity/aquivalence method to simulate the fate of Hg in air, water, soil, sediment, vegetation and film. The total annual atmospheric emission was 9.91 t, of which coal combustion and non-coal sources accounted for 70.1 % and 29.9 %, respectively. Atmospheric emission and advection were dominated by Hg0, and aquatic emission and advection were dominated by Hg2+. The migration of air–vegetation, vegetation–soil and soil–air were three important pathways of Hg in urban areas. The model was validated by collecting local soil and vegetation samples and regional air, seawater and sediment monitoring data. The scenario simulation indicated that the local load would decrease to different extents with a 21.0 % reduction in atmospheric Hg emission by implementing the “coal-to-gas” measures. Our developed model can characterize the fate of Hg in coastal urban areas and provide a reference for control strategies.

К РАСЧЕТАМ АНТРОПОГЕННЫХ ВЫБРОСОВ ИЗ ИСТОЧНИКОВ И АБСОРБЦИЙ ПОГЛОТИТЕТЯМИ ПАРНИКОВЫХ ГАЗОВ В ЛЕСНОМ И СЕЛЬСКОМ ХОЗЯЙСТВЕ ДЛЯ ЕЖЕГОДНОГО НАЦИОНАЛЬНОГО ДОКЛАДА РЕСПУБЛИКИ КАЗАХСТА

The results presented in the article were obtained in the process of preparing the National Report on the inventory of anthropogenic emissions from sources and absorption of greenhouse gases not regulated by the Montreal Protocol, in terms of land use. The report is submitted annually by the Republic of Kazakhstan, as a party to the United Nations Framework Convention on Climate Change (UNFCCC). Preliminary calculations of the dynamics of carbon dioxide (CO2) associated with land use in the Republic of Kazakhstan for 1991...2020 showed that its absorption from the atmosphere by natural ecosystems could range from 3 to 50...60 million tons per year, and emissions into the atmosphere – from 10 to 45 million tons/year. In the process of research, a detailed analysis of the country's existing system of ground-based monitoring of land use and land resources was carried out with calculations of anthropogenic CO2 flows at various territorial levels. The results obtained confirm the possibility of calculating greenhouse gases at the zonal and regional levels. This confirms the possibility of additional control of calculations of greenhouse gas fluxes associated with land use and assessment of the potential for a possible increase in absorption volumes for natural ecosystems (Forests and Pastures) and reductions in emissions for the Croplands agroecosystem.

The Impact of Anthropogenic VOC Emissions on Atmospheric Pollution: A Case Study of a Typical Industrialized Area in China

Volatile organic compounds (VOCs) are the main precursors of pollution from ground ozone (O3) and PM2.5, which cause the deterioration of urban air quality. The emissions of VOCs from industrialized areas are significant and their characteristics are complex, which nowadays contribute significantly to the challenges of investigating the emission inventory. Taking a typical industrialized area in Tianjin as a case study, the anthropogenic VOCs emission inventory for 2020 was established in this study by using the activity data from a large-scale survey and the latest emission factors. The impact of VOCs on the environment was analyzed from the perspective of the combined control of PM2.5 and O3. The results showed that the total emission of VOCs in 2020 was about 1.68 Gg, mainly from industrial processes and mobile sources, which accounted for 38.4% and 36.5% of the total emissions, respectively. The top 10 emitted VOCs were toluene, acetone, ethylbenzene, m/p-xylene, i-pentane, n-hexane, formaldehyde, benzene, ethyl acetate and ethylene. The dominant species of O3 formation potential (OFP) were almost all aromatic hydrocarbons and alkenes, with m/p-xylene contributing the most to the OFP emissions (8.90%). The top 10 secondary organic aerosols formation potential (SOAP) emission species were aromatic hydrocarbons and long-chain alkanes, and the largest emission came from toluene (39.9%). An analysis of an ADMS diffusion model showed that VOCs emitted from traffic-heavy main roads and industrialized central areas had the greatest impact on the air quality in the surrounding areas. The VOCs concentration was higher in winter due to unfavorable meteorological conditions. Our research updated the VOC inventory of industrialized areas and evaluated VOCs species reactivity and their impact on ambient air quality.