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Volatile Organic Compounds (VOCs) are not only essential precursors for the formation of ozone and PM2.5, but also hazardous to human health and responsible for unpleasant odors. The pharmaceutical industry has become an important industrial source of VOCs due to China's large emissions and complex emission chains. In total, 245 VOCs samples were collected and analyzed from 11 typical pharmaceutical companies in Zibo City of the North China Plain, in order to investigate the VOCs emission characteristics and odor impacts. The emission factor for the pharmaceutical industry was 7.97 ± 8.21 g/kg pharmaceuticals, while the main emission links were chimney emissions, equipment sealing leakage, and so on. Finally, considering both purifying efficiency and economic benefits, the multistage absorption (AB) method is most effective for VOCs concentrations below 100 mg/m3, while UV photo-oxygenation combined with adsorption (UVA) is more suitable for concentrations below 300 mg/m3. The Regenerative Thermal Oxidizer (RTO), Catalytic Oxidizer (CO), and Condensation + Adsorption (CA) technologies demonstrated greater stability and efficiency, particularly in the treatment of complex organic pollutants, highlighting their advantages in both VOCs and odor removal at higher concentrations. [ABSTRACT FROM AUTHOR]

Accurate measurement of carbon footprint (CFP) is crucial for achieving carbon emission reduction goals. In India's agricultural carbon emission, a consistent and effective conclusion regarding the estimation method, sample selection and calculations of results does not exist. The present study introduces the main accounting method for agricultural carbon emissions in the Indian context, i.e. the customized methodologies based on the Intergovernmental Panel on Climate Change guidelines and International Organization for Standardization (ISO) standards. The present study highlights the critical need to standardize the CFP assessment methodologies following the ISO to obtain credible information for making sound decisions. [ABSTRACT FROM AUTHOR]

Aviation emissions are continuously increasing along with the rapid development of air transportation, and results in the deterioration in regional air quality and the global climate. Accurate emission estimation is of great importance for relevant policies promotion and the sustainable development of the environment. Previous studies focused on the total emissions of a flight and lacked high precision in both spatial and temporal resolutions, especially aviation activities near ground. In this research, we propose an open-sourced emission calculation framework based on actual flight trajectories (TrajEmission), which calculates both the ground and airborne emissions simultaneously according to the configuration parameters, trajectory characteristics, and ambient conditions. We compare the emission results with five emission inventory methods. The results indicate that pollutant (nitrogen oxides, carbon monoxide, and unburned hydrocarbons) emissions in the landing and takeoff (LTO) cycle might usually be underestimated due to a lack of trajectory-based methods. In addition, in the overall results, the method based on the great circle route leads to an overestimation of 56.8% of pollutant emissions compared to the method based on actual routes. We also investigate the extent to which other factors could influence the emission results. To summarize, the TrajEmission framework can build inventories for the whole process of flight movements with high spatial–temporal resolutions and provide solid data support for environmental science and other related fields. [ABSTRACT FROM AUTHOR]

Understanding the pollution levels, potential sources, and chemical reactivity of atmospheric volatile organic compounds (VOCs), the key precursors of ozone (O3) and fine particulate matter (PM2.5), is important for emission control and air pollution abatement. This study presents a systematic VOCs analysis in a less studied heavy industrial urban agglomeration located in Northeast China. Using a cruising platform, we conducted real-time monitoring of VOC concentrations and components at Changchun (CC), Jilin (JL), Siping (SP), and Liaoyuan (LY) in Jilin Province. During the observation period, the average VOC concentrations at CC, JL, SP, and LY were 63.38 ± 127.03, 260.39 ± 855.76, 18.06 ± 17.17, and 10.12 ± 17.48 µg/m3, respectively. Halocarbons were predominant with a high percentage of contribution (22.4–31.1%) to the total observed VOCs for all cities. Combined with 2020-based anthropogenic VOCs emission inventory of Jilin Province, we concluded that industrial processes had the largest contribution to VOCs concentration in CC, whereas petrochemical emission was the major source of VOCs in JL. The assessment of atmospheric photochemical reactivity indicates the dominant role of aromatics and alkenes in O3 formation potential (OFP). As the second-most abundant species in CC and JL, aromatics contributed over 50% of the OFPs. Alkenes played a dominant role in O3 formation in SP and LY, accounting for nearly half of the total OFPs. Considering the VOC emission characteristics and OFP results, we suggest that reducing aromatics emissions, particularly benzene, toluene, ethylbenzene, and xylene, should be given higher priority to mitigate O3 pollution and prevent health risks. Moreover, industrial-related, and petrochemical sources are crucial in the evolution of O3 pollution, which should be incorporated into heavy industrial urban air quality management and targeted control of O3 pollution in Northeast China. [ABSTRACT FROM AUTHOR]

Biomass plays a crucial role in the low‐carbon energy transition, with a projected contribution of 18.7% to the global energy supply by 2050. However, biofuel combustion has been a notable source of toxic mercury emissions, yet the future trends and distribution of the emissions remain inadequately understood. Here, we projected biofuel combustion under various Shared Socioeconomic Pathways (SSPs) using the Global Change Assessment Model and assessed associated mercury emissions in cooking, heating, and power generation over 2020–2050, aligning with the carbon neutrality target. Our analysis reveals that global biofuel mercury emissions are projected to be 9.90–18.40 tons by 2050, compared to the annual emissions of 13.89 tons in 2020. Notably, a substantial increase in emissions from power generation is expected, escalating from 0.57 tons in 2020 to 4.69–8.27 tons by 2050, with China and Southeast Asia emerging as primary contributors. Conversely, mercury emissions from cooking and heating are expected to decrease from 13.32 tons in 2020 to 4.40–11.53 tons by 2050, except in Africa under SSP2, where the emissions may increase from 5.91 to 6.69 tons. Our findings provide a scientific basis for policies aimed at achieving carbon neutrality targets while adhering to the Minamata Convention on Mercury. Plain Language Summary: Biomass plays a crucial role in the low‐carbon energy transition, but its combustion releases toxic mercury. Our study projected mercury emissions from biofuel combustion from 2020‐2050 under different Shared Socioeconomic Pathways scenarios and global net‐zero emissions constraints. We find that while mercury emissions from cooking and heating will decrease, emissions from power generation will significantly increase, especially in China and Southeast Asia. To achieve carbon neutrality and reduce mercury pollution, there is an urgent need for the deployment of air pollution control devices in biomass direct‐fired power plants and the transformation of biomass into cleaner bioenergy should be promoted. Key Points: Spatial and temporal patterns of mercury emissions from biofuel combustion across 32 country/regions under carbon neutrality are delineatedCooking and heating constituted 95.9% of mercury emissions from biofuel combustion in 2020, dropping to one‐third of that level by 2050Mercury emissions of biomass power generation rise by 7.2–13.4 times in 2020–2050, dominated by carbon capture and storage technology in 2050 [ABSTRACT FROM AUTHOR]

With the rapid development of industrialization and urbanization in China, civil aviation plays an increasingly important role in the transportation industry. However, pollutants and greenhouse gas (GHG) emissions from civil aviation are becoming an increasingly concerning environmental problem. In order to mitigate the resulting environmental pollution, such as air quality deterioration, regional and global climate warming, and declining human health, more and more efforts have been devoted to reducing both pollutants and GHG emissions. Among these efforts, emissions inventories from civil aviation provide a basis for quantifying pollutants and GHG emissions, establishing evaluation standards of environmental impact, and formulating management policies for both air quality improvement and climate change mitigation. In this paper, we reviewed both compilation approaches and data collection methods for civil aviation emissions inventories, introduced several typical calculation methods for aviation emissions inventories, and analyzed specific cases of actual application based on typical methods of inventory compilation. We also described in detail the activity level and emission index calculation methods of several pollutants and greenhouse gases. Furthermore, based on the above research methods, four typical application cases were investigated, including a specific airport, the landing and takeoff (LTO) cycle of a nation, the entire period with the LTO cycle and the climb–cruise–descent (CCD) phase of a country, and global emissions inventories from civil aviation. The results suggest that, in addition to quantifying the emissions of both pollutants and GHG produced by civil aviation, the selection of inventory compilation methods is likely to be important for improving aviation emission inventory accuracy and for further reducing the environmental, economic, and health impacts resulting from aviation emissions. Moreover, this paper can also provide a reference and theoretical basis for the development of aviation emission inventory compilation methods in the future. [ABSTRACT FROM AUTHOR]

• Iron & steel industry contributed the most for unintentional PCNs emissions • Overall upward trend of unintentional PCNs emissions from 1960 to 2019 was revealed. • Per-capita emissions follows the typical inverted U-shaped environmental Kuznets curves. • Low-chlorinated PCNs dominate emissions by mass, while it's high-chlorinated PCNs by toxicity. Polychlorinated naphthalenes (PCNs) are detrimental to human health and the environment. With the commercial production of PCNs banned, unintentional releases have emerged as a significant environmental source. However, relevant information is still scarce. In this study, provincial emissions for eight PCNs homologues from 37 sources in the Chinese mainland during the period of 1960-2019 were estimated based on a source-specific and time-varying emission factor database. The results showed that the total PCNs emissions in 2019 reached 757.0 kg with Hebei ranked at the top among all the provinces and iron & steel industry as the biggest source. Low-chlorinated PCNs comprised 90% of emissions by mass, while highly chlorinated PCNs dominated in terms of toxicity, highlighting divergent priorities for mitigating emissions and safeguarding human health. The emissions showed an overall upward trend from 1960 to 2019 driven by emission increase from iron & steel industry in terms of source, and from North China and East China in terms of geographic area. Per-capita emissions followed an inverted U-shaped environmental Kuznets curve while emission intensities decreased with increasing per-capita Gross Domestic Product (GDP) following a nearly linear pattern when log-transformed. [Display omitted] [ABSTRACT FROM AUTHOR]

Biogenic volatile organic compounds (BVOCs) are regarded as important precursors for ozone and secondary organic aerosol, mainly from vegetation emissions. In the context of the expanding trend of vegetation greening, the development of high‐precision vegetation data and accurate BVOC emission estimates are essential to develop effective air pollution control measures. In this study, by integrating the multi‐source vegetation cover data, we established a high‐resolution vegetation distribution (HRVD) data set to develop a high spatio‐temporal resolution emission inventory and investigated the impact of different land cover data sets on emission simulation and impact of land cover change on BVOC emissions during 2001–2020. The annual total BVOC emissions in China for 2020 was 15.66 Tg, which were mainly from trees. The emissions simulated by CNLUCC and MODIS data sets were 1.53% and 1.72% higher than those simulated by HRVD data sets, respectively. The spatial distribution of emission differences was consistent with that of land cover differences. The simulated BVOC emissions by the HRVD data set had the best accuracy as they improved the bias between modeling and observation from 69.06% to 65.35% and decreased the underprediction of observations by a factor of 2.13 compared with simulation by MEGAN default vegetation data. The annual BVOC emissions caused by changing vegetation distribution and LAIv (LAI of vegetation covered surfaces) enhanced at a rate of 72.06 Gg yr−1 during 2001–2020. LAIv was the main driver of emission variations. The total OH reactivity of the resulted BVOC emissions increased at a rate of 1.59 s−1 yr−1, with isoprene contributed the most. Plain Language Summary: Biogenic Volatile organic compounds (BVOCs) are the key precursors of fine particulate matter and ozone, that mainly from vegetation emissions. To help to develop effective air pollution control measures in the context of expanding vegetation coverage for realizing carbon neutralization in China, it is urgent to develop highly precise vegetation data and accurately estimate BVOC emission. A high‐resolution vegetation distribution data set was established through integrating multi‐source vegetation cover data. Using it, the simulated annual BVOC emission in China was 15.66 Tg and mainly emitted from trees. Emissions from varied growth forms had different compound compositions. The BVOC emission simulated using the high‐resolution vegetation distribution data set we developed had better accuracy than that using the single vegetation databases. The annual BVOC emissions caused by changing vegetation cover and leaf area index (LAI) enhanced at a rate of 72.06 Gg yr−1 during 2001–2020. LAI was the main driver of BVOC emission variations. The interannual variation and its spatial pattern of the OH loss rates of BVOCs during 2001–2020 were consistent with that of BVOC emissions, especially isoprene. Key Points: Annual total BVOC emissions in China for 2020 was 15.66 Tg and emissions from varied growth forms had different compositionsBVOC emission inventory simulated by the developed high‐resolution vegetation distribution (HRVD) data set had better accuracyBVOC emission enhanced at a rate of 72.06 Gg yr−1 during 2001–2020 caused by land cover change, mainly driven by changing leaf area index [ABSTRACT FROM AUTHOR]

Ammonia is one of the precursor gases in the formation of particulate matter (PM) that reacts with nitrogen oxides and sulfur oxides in the atmosphere. Based on the Clean Air Policy Support System (CAPSS) of Korea, the annual ammonia emissions amounted to 261,207 tons in 2020 and the agricultural source (manure management sector) contributes the highest proportion of the ammonia inventory. However, the methodology for the study of ammonia emissions in Korea has some limitations regarding the representativeness of the sites selected and the reliability of the measurement method. In this study, we aimed to recalculate the ammonia emissions from the livestock industry in Korea using the UK's estimation method, which uses the life cycle assessment of livestock manure. Three major animal types, i.e., cattle (beef cattle and dairy cows), pigs and chickens, and three major processes based on the manure flow, i.e., housing, manure storage and treatment and land application processes, were considered. The total ammonia emissions were estimated to be approximately 33% higher than the official ammonia emissions stated by the CAPSS. For the manure flow, the ammonia emissions were the highest from land application processes. The ammonia emissions from dairy cow and poultry manure were much higher than those stated by the CAPSS, while the emissions from beef cattle and pig manure showed similar levels. The methodology used in this study can offer an alternative approach to the ammonia emission estimation of the manure management sector in the agriculture industry of Korea. Korean emission factors based on the manure flow should be developed and applied in the future. [ABSTRACT FROM AUTHOR]

Atmospheric volatile organic compounds (VOCs), such as olefins and aromatics, released from synthetic chemical pesticide sprays can increase regional air pollution, public health risks, and food security risks. However, significant uncertainties remain regarding the measurement methods and chemical profiles of VOC emissions. Using an agricultural city, Changchun City in Northeast China, as a case study, we quantified real-time concentration and composition data based on online monitoring instruments for the year 2023. This study optimized data collection methods for emission factors and activity levels and developed a high-precision emission inventory of VOCs in pesticides at the city scale. The emission factors for VOCs from the seven categories of pesticides were estimated as follows: 78 g/kg (nicosulfuron and atrazine, oil-dispersible [OD] and suspension emulsion [SE], respectively), 4 g/kg (chlorpyrifos and indoxair conditioningarb, suspension concentrate [SC]), 5 g/kg (fluopicolide and propamocarb hydrochloride, SC), 217 g/kg (MCPA-dimethylammonium, aqueous solution [AS]), 34 g/kg (glyphosate, AS), 575 g/kg (beta-cypermethrin and malathion, emulsifiable concentrate [EC]), and 122 g/kg (copper abietate, emulsion in water [EW]), depending on the pesticide formulation components and formulation types. The orchard insecticide exhibited the highest emission factors among all pesticides owing to its emulsifiable concentrate formulation and 80% content of inactive ingredients (both factors contribute to the high content of organic solvents in the pesticide). The major components of VOC emissions from pesticide spraying were halocarbons (27–44%), oxygenated VOCs (OVOCs) (25–38%), and aromatic hydrocarbons (15–28%). The total VOC emissions from pesticide spraying in the Changchun region accounted for 10.6 t, with Yushu City contributing 28% of the VOC emissions and Gongzhuling City and Dehui City contributing 18.7% and 16.0%, respectively. Herbicides were the main contributors to VOC emissions because of their high emission factors and extensive use in fields (used for spraying maize and rice, the main crops in Changchun City). May and June exhibited the highest VOC emissions from pesticide application, with May accounting for 57.0% of annual pesticide emissions, predominantly from herbicides (95.1%), followed by insecticides (4.9%). June accounted for 30.1% of the annual pesticide emissions, with herbicides being the largest contributor of VOC emissions. An emission inventory of VOC with a monthly scale and spatial grid resolutions of 0.083° and 0.5° in 2023 was developed. These emission factors and inventories of pesticide applications provide valuable information for air quality modeling. This study also provides an important scientific basis for enhancing regional air quality and mitigating the environmental impact of pesticide use in major grain-producing areas. [ABSTRACT FROM AUTHOR]

Accurately estimating vehicle emissions is crucial for effective air quality management. As key data for emission inventory construction, emission factors (EFs) are influenced by vehicle usage characteristics and experience deterioration. Current deterioration models often employ single-factor approaches based on vehicle age or accumulated mileage, which fail to capture the effects of varying usage intensities within the same mileage or age intervals. This study addressed this limitation by developing a novel emission deterioration model that incorporates multi-dimensional usage characteristics and that utilizes a large-scale inspection and maintenance (I/M) dataset for light-duty gasoline vehicles (LDGVs). The modeling results reveal distinct deterioration patterns for different pollutants and highlight the synergistic effects of the usage duration and intensity: natural aging significantly impacts HC and NOx emissions, while CO emissions are more strongly affected by intensive use. Specifically, China V LDGVs that were driven 4 × 104 km/yr exhibited HC, CO, and NOx deterioration rates per mile that were approximately 4.1 % lower, 10.3 % higher, and 1.1 % higher, respectively, than those of vehicles driven 2 × 104 km/yr as the mileage increased from 5 × 104 km to 10 × 104 km. By leveraging timely emission data and explicitly accounting for usage intensity, this study corrected biases in local emission estimates by 5–85 % with respect to estimates from commonly used models. This framework enables the development of more effective control strategies and refinements to policy evaluations in megacities with I/M programs.

Abstract Biomass plays a crucial role in the low‐carbon energy transition, with a projected contribution of 18.7% to the global energy supply by 2050. However, biofuel combustion has been a notable source of toxic mercury emissions, yet the future trends and distribution of the emissions remain inadequately understood. Here, we projected biofuel combustion under various Shared Socioeconomic Pathways (SSPs) using the Global Change Assessment Model and assessed associated mercury emissions in cooking, heating, and power generation over 2020–2050, aligning with the carbon neutrality target. Our analysis reveals that global biofuel mercury emissions are projected to be 9.90–18.40 tons by 2050, compared to the annual emissions of 13.89 tons in 2020. Notably, a substantial increase in emissions from power generation is expected, escalating from 0.57 tons in 2020 to 4.69–8.27 tons by 2050, with China and Southeast Asia emerging as primary contributors. Conversely, mercury emissions from cooking and heating are expected to decrease from 13.32 tons in 2020 to 4.40–11.53 tons by 2050, except in Africa under SSP2, where the emissions may increase from 5.91 to 6.69 tons. Our findings provide a scientific basis for policies aimed at achieving carbon neutrality targets while adhering to the Minamata Convention on Mercury.

Abstract Road-based transport is a significant contributor to global transport emissions of greenhouse gases and local pollutants, thus contributing to the environmental impact of the mobility of people and goods. In order to develop strategies to mitigate this impact, it is necessary to build reliable emission inventories that include sector-specific emissions. Furthermore, the methods for creating these inventories should be applicable for forecasts and scenario calculations to facilitate the evaluation of pathways towards a more sustainable transport system. The study at hand proposes a model-based framework to predict travel demand and its spatial distribution for a bottom-up calculation of road transport emissions in Europe. With this framework, it is possible to calculate emissions based on the road network structure, traffic flows and vehicle types. In order to demonstrate the applicability of the framework for scenario calculations, it is applied to three exemplary scenarios where population data is modified. With the developed methodology, a tool for the large-scale assessment of emissions from road transport is provided, which is able to simulate the impact of socio-economic and economic changes on these emissions.

Abstract With its high energy consumption and pollutant emissions, the iron and steel industry is a significant source of air pollution and carbon emissions in the Beijing–Tianjin–Hebei (BTH) region. To improve air quality and reduce greenhouse gas emissions, a series of policies involving ultra-low emission, synergistic reduction of pollution, and carbon application have been implemented in the region. This study has assessed air pollutant and CO2 emission patterns in the iron and steel industry of the region by employing co-control effects coordinate system, marginal abatement cost curve, and numerical modeling, along with the synergistic benefits of typical technologies. The results have demonstrated that: (1) the intensive production activities pertinent to iron and steel enterprises has contributed greatly to the emission in Tangshan and Handan, where the sintering process is the main source of SO2, NOx, PM2.5, and CO, accounting for 64.86%, 55.15%, 29.98%, and 46.43% of the total emissions, respectively. (2) Among the typical pollution control and reduction measures, industrial restructuring and adjustment of the energy-resource structure have led to the greatest effects on emission reduction. Technologies exhibiting great potential in emission reduction and high-cost efficiency such as Blast Furnace Top Gas Recovery Turbine Unit (TRT) need to be promoted. (3) In Tangshan city with the highest level of steel production, the iron and steel production activities contributed to the concentration of 30.51% of PM2.5, 50.67% of SO2, and 42.54% of NO2 during the non-heating period. During the heating period, pollutants pertinent to the combustion of fossil energy for heating have increased, while iron and steel induced emissions have decreased to 23.7%, 34.32%, and 29.13%, respectively. By 2030, it is speculated that the contribution of the iron and steel industry to air quality will be significantly decreased as result of successful implementation of ultra-low emission policies and typical synergistic reduction technologies.

Road-based transport is a significant contributor to global transport emissions of greenhouse gases and local pollutants, thus contributing to the environmental impact of the mobility of people and goods. In order to develop strategies to mitigate this impact, it is necessary to build reliable emission inventories that include sector-specific emissions. Furthermore, the methods for creating these inventories should be applicable for forecasts and scenario calculations to facilitate the evaluation of pathways towards a more sustainable transport system. The study at hand proposes a model-based framework to predict travel demand and its spatial distribution for a bottom-up calculation of road transport emissions in Europe. With this framework, it is possible to calculate emissions based on the road network structure, traffic flows and vehicle types. In order to demonstrate the applicability of the framework for scenario calculations, it is applied to three exemplary scenarios where population data is modified. With the developed methodology, a tool for the large-scale assessment of emissions from road transport is provided, which is able to simulate the impact of socio-economic and economic changes on these emissions. [ABSTRACT FROM AUTHOR]

Road silt loading (sL) directly affects the fugitive road dust (FRD) emission factor, which is an important parameter in the study of FRD emissions. In this study, an improved collection method combined with the AP−42 method was newly developed to estimate the sL of asphalt roads in Jinan, China. The characteristics of sL in Jinan followed the order National highway (NH) > Branch road (BR) > Provincial highway (PH) > Country highway (CH) > Minor arterial (MiA) > Major arterial (MaA) > Urban expressway (UE) with 3.9 ± 2.5, 3.9 ± 1.9, 3.8 ± 2.8, 3.8 ± 0.9, 2.1 ± 1.4, 1.7 ± 1.2, and 1.4 ± 1.2 g/m2, respectively. The size orders of PM2.5 and PM10 emission factors are consistent with total suspended particulate (TSP). The characteristics of the TSP emission factor of FRD followed the order NH > PH > CH > Expressway (EW) > MiA > BR > MaA > UE with 27.3, 23.4, 19.4, 13.7, 7.7, 7.4, 6.2, and 3.0 g/VKT (vehicle kilometers traveled), respectively. The annual emissions of TSP, PM10, and PM2.5 from FRD in Jinan in 2020 were about 985.2, 209.8, and 57.8 kt, respectively. Laiwu, Jiyang, and Licheng districts show the top three TSP emissions of FRD; the sum of their emissions accounts for 44.7% of the TSP emissions from FRD in Jinan. TSP emissions from municipal roads and administrative roads accounted for about 29.2% and 70.8% of the total emissions in Jinan, respectively, of which emissions from MiA accounted for the largest proportion of TSP emissions from municipal roads, contributing about 37.9%, while TSP emissions from NH made the largest contribution to TSP emissions from administrative roads, with a contribution of about 35.8%. Based on Monte Carlo simulation results using Crystal Ball, the uncertainty range of the emission inventory of FRD in Jinan ranged from −79.9 to 151.8%. In 2020, about 985,200 tons of road particulate matter in Jinan City entered the atmosphere, having an adverse effect on air quality and human health. [ABSTRACT FROM AUTHOR]

With its high energy consumption and pollutant emissions, the iron and steel industry is a significant source of air pollution and carbon emissions in the Beijing–Tianjin–Hebei (BTH) region. To improve air quality and reduce greenhouse gas emissions, a series of policies involving ultra-low emission, synergistic reduction of pollution, and carbon application have been implemented in the region. This study has assessed air pollutant and CO2 emission patterns in the iron and steel industry of the region by employing co-control effects coordinate system, marginal abatement cost curve, and numerical modeling, along with the synergistic benefits of typical technologies. The results have demonstrated that: (1) the intensive production activities pertinent to iron and steel enterprises has contributed greatly to the emission in Tangshan and Handan, where the sintering process is the main source of SO2, NOx, PM2.5, and CO, accounting for 64.86%, 55.15%, 29.98%, and 46.43% of the total emissions, respectively. (2) Among the typical pollution control and reduction measures, industrial restructuring and adjustment of the energy-resource structure have led to the greatest effects on emission reduction. Technologies exhibiting great potential in emission reduction and high-cost efficiency such as Blast Furnace Top Gas Recovery Turbine Unit (TRT) need to be promoted. (3) In Tangshan city with the highest level of steel production, the iron and steel production activities contributed to the concentration of 30.51% of PM2.5, 50.67% of SO2, and 42.54% of NO2 during the non-heating period. During the heating period, pollutants pertinent to the combustion of fossil energy for heating have increased, while iron and steel induced emissions have decreased to 23.7%, 34.32%, and 29.13%, respectively. By 2030, it is speculated that the contribution of the iron and steel industry to air quality will be significantly decreased as result of successful implementation of ultra-low emission policies and typical synergistic reduction technologies. [ABSTRACT FROM AUTHOR]

Open straw burning has been widely recognized as a significant source of greenhouse gases (GHGs), posing critical risks to atmospheric integrity and potentially exacerbating global warming. In this study, we proposed a novel method that integrates crop cycle information into extraction and classification of fire spots from open straw burning in Northeast China from 2001 to 2020. By synergizing the extracted fire spots with the modified Fire Radiative Power (FRP) algorithm, we developed high spatial resolution emission inventories of GHGs, including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Results showed that the northern Sanjiang Plain, eastern Songnen Plain, and eastern Liao River Plain were areas with high intensity of open straw burning. The number of fire spots was elevated during 2013-2017, accounting for 58.0% of the total fire spots observed during 2001-2020. The prevalent season for open straw burning shifted from autumn (pre-2016) to spring (post-2016), accompanied by a more dispersed pattern in burning dates. The two-decade cumulative emissions of CO2, CH4, and N2O were quantified at 202 Tg, 568 Gg, and 16.0 Gg, respectively, amounting to 221 Tg of CO²-eq. Significant correlations were identified between GHGs emissions and both straw yields and straw utilization (p < 0.01). The enforcement of straw burning bans since 2018 has played a pivotal role in curbing open straw burning, and reduced fire spots by 50.7% on annual basis compared to 2013-2017. The novel method proposed in this study considerably enhanced the accuracy in characterizing spatiotemporal distributions of fire spots from open straw burning and quantifying associated pollutants emissions. [ABSTRACT FROM AUTHOR]

Jakarta had a congestion level of 53% in 2019, ranking 10th among the most traffic jams globally. Therefore, the transportation sector is the largest contributor to air pollution in the special area of the capital city Jakarta (DKI Jakarta). In this study, a vehicle age cohort was analyzed using dynamic models. Several factors, such as emission standards, vehicle speed, as well as fuel quality and type, were included to drive the models. The emission inventory for air pollutants, such as carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx), and particulate matter (PM10) can be calculated using this model. The results showed that motorbikes were the major contributor to the increase in the four pollutants in DKI Jakarta from 2007 to 2018 and will still be a significant contributor until 2040. In 2018, the major contributors to CO, HC, NO, and PM10 were motorbikes (52.7%), motorbikes (79.6%), buses (63.9%), and motorbikes (74.7%), respectively. It is predicted that in 2040, using the business-as-usual (BAU) scenario, motorbikes will also be the primary contributors of air pollutants (CO, HC, and PM) 70.2%, 91.4%, and 82.9%, respectively. Diesel passenger cars will become a lesser contributor to air pollutants than all vehicles from 2018 to 2040 in DKI Jakarta. [ABSTRACT FROM AUTHOR]

The emissions from ships are the key factor influencing the air quality near large ports. Although ship emissions are difficult to quantify, doing so can help port management find logistical solutions that can reduce the impact of having a large number of giant ships in a limited space. The joint study between the University of Naples and Istanbul Technical University, which focuses on the investigation of ship emissions in ports, is presented in this paper. It is expected that this study will lead to create new techniques for calculating, measuring, and validating emissions from ships at ports. [ABSTRACT FROM AUTHOR]

The reduction in agricultural carbon emissions (ACEs) in Shandong Province is essential to China's carbon peak and carbon neutrality objectives. In this regard, we constructed an ACE inventory for Shandong Province at a resolution of 1 km × 1 km, integrating the emission factor method with geographic information system (GIS) technology. Building upon this, we explored the dynamic evolution patterns of ACEs using kernel density estimation and conditional probability density estimation. Additionally, long short-term memory networks were trained to predict ACEs under various scenarios. The results showed that: (1) ACEs in Shandong Province exhibited two stages of change, i.e., "rise and decline". Notably, 64.39% of emissions originated from the planting industry. The distribution of emissions was closely correlated with regional agricultural production modes. Specifically, CO2 emissions were predominantly distributed in crop cultivation areas, while CH4 and N2O emissions were primarily distributed in livestock breeding areas. The uncertainty of the emission inventory ranged from −12.04% to 10.74%, mainly caused by emission factors. (2) The ACE intensity of various cities in Shandong Province is decreasing, indicating a decoupling between ACEs and agricultural economic growth. Furthermore, the emission disparities among different cities are diminishing, although significant spatial non-equilibrium still persists. (3) From 2022 to 2030, the ACEs in Shandong Province will show a continuous downward trend. By 2030, the projected values under the baseline scenario, low-carbon scenario I, and low-carbon scenario II will be 6301.74 × 104 tons, 5980.67 × 104 tons, and 5850.56 × 104 tons. The low-carbon scenario reveals greater potential for ACE reduction while achieving efficient rural economic development and urbanization simultaneously. This study not only advances the methodology of the ACE inventory but also provides quantitative references and scientific bases for promoting low-carbon, efficient, and sustainable regional agriculture. [ABSTRACT FROM AUTHOR]

Excessive fluoride emissions threaten ecological stability and human health. Previous studies have noted that industrial sources could be significant. However, quantifying industrial fluoride emissions has not been yet reported. In this study, both bottom-up and top-down approaches were used to estimate the fluoride emissions in the Nansi Lake Basin. Global and local spatial autocorrelation were adopted to reveal the spatial agglomeration effects. The fluoride emissions calculated by the bottom-up approach were larger than those calculated by the top-down method. The highest fluoride input mainly occurred in Zoucheng and Mudan. The highest fluoride emissions mainly occurred in Zoucheng and Rencheng using the bottom-up approach. The highest fluoride emissions mainly occurred in Zoucheng and Yanzhou using the top-down approach. Mining and washing of bituminous coal and anthracite (BAW) was the most significant source of fluoride input and emissions. A significant spatial agglomeration effect of fluoride emissions was found. These findings could provide a method for accurate industrial fluoride emission estimation, complement the critical data on the fluoride emissions of main industrial sectors, and provide a scientific basis for tracing fluoride sources. [ABSTRACT FROM AUTHOR]

• The cold drum process, coking and quenching were the main processes responsible for VOCs pollutant emissions. • BTX and naphthalene were indicators of coking industry VOC emissions. • The impact of the coking industry on the surrounding environment was negatively related to the distance from the facility. • Coking emission sources were identified across the entire monitoring area. Industrial coking facilities are an important emission source for volatile organic compounds (VOCs). This study analyzed the atmospheric VOC characteristics within an industrial coking facility and its surrounding environment. Average concentrations of total VOCs (TVOCs) in the surrounding residential activity areas (R1 and R2), the coking facility (CF) and the control area (CA) were determined to be 138.5, 47.8, 550.0, and 15.0 µg/m3, respectively. The cold drum process and coking and quenching areas within the coking facility were identified as the main polluting processes. The spatial variation in VOCs composition was analyzed, showing that VOCs in the coking facility and surrounding areas were mainly dominated by aromatic compounds such as BTX (benzene, toluene, and xylenes) and naphthalene, with concentrations being negatively correlated with the distance from the coking facility (p < 0.01). The sources of VOCs in different functional areas across the monitoring area were analyzed, finding that coking emissions accounted for 73.5%, 33.3% and 27.7% of TVOCs in CF, R1 and R2, respectively. These results demonstrated that coking emissions had a significant impact on VOC concentrations in the areas surrounding coking facility. This study evaluates the spatial variation in exposure to VOCs, providing important information for the influence of VOCs concentration posed by coking facility to surrounding residents and the development of strategies for VOC abatement. Coking facility emitted a large amount of VOCs, had significant impacts on VOCs concentration of surrounding areas. [Display omitted] [ABSTRACT FROM AUTHOR]

Air pollutants from biomass burning, including forest fires and agricultural trash burning, have contributed significantly to the pollution of the Asian atmosphere. Burned area estimates are variable, making it difficult to measure these emissions. Improving emission quantification of these critical air pollution sources requires refining methods and collecting thorough data. This study estimates air pollutants from biomass burning, including PMs, NOX, SO2, BC, and OC. Machine learning (ML) with the Random Forest (RF) method was used to assess burned areas in Google Earth Engine. Forest emissions were highest in the upper north and peaked in March and April 2019. Air pollutants from agricultural waste residue were found in the lower north, but harvesting seasons made timing less reliable. Biomass burning was compared to the MODIS aerosol optical depth (AOD) and Sentinel-5P air pollutants, with all comparisons made by the Pollution Control Department (PCD) Thailand air monitoring stations. Agro-industries, mainly sugar factories, produce air pollutants by burning bagasse as biomass fuel. Meanwhile, the emission inventory of agricultural operations in northern Thailand, including that of agro-industry and forest fires, was found to have a good relationship with the monthly average levels of ambient air pollutants. Overall, the information uncovered in this study is vital for air quality control and mitigation in northern Thailand and elsewhere. [ABSTRACT FROM AUTHOR]

Trace metals from natural and anthropogenic sources impact the atmospheric environment and enter the soil through dry and wet atmospheric deposition, ultimately affecting human health. In this study, we established an emission inventory of Pb, As, Cr, and Cd in East Asia (80° E–140° E, 15° N–50° N) for the year 2017, including dust and anthropogenic sources from both land and marine. We modified the Community Multiscale Air Quality (CMAQ) model to provide gridded data on concentrations, as well as dry and wet atmospheric deposition fluxes of metals, with a focus on mainland China. The emissions of Pb, As, Cr, and Cd in East Asia were 19,253, 3415, 3332, and 9379 tons, respectively, in 2017, with 55%, 69%, 25%, and 58% distributed in the fine mode. The spatial distribution of atmospheric concentrations and dry deposition of trace metals was similar to that of emissions, while the spatial distribution of precipitation-related wet deposition was further east and greater in the south than in the north. In mainland China, the average bulk-deposition fluxes of Pb, As, Cr, and Cd were 1036.5, 170.3, 465.9, and 185.0 μg·m−2·year−1, respectively. Our study provides gridded data on trace metals in mainland China, which can be used for assessing air quality, human exposure risks, and metal inputs to soils. [ABSTRACT FROM AUTHOR]

Abstract Background The European Water Framework Directive foresees the establishment of emission inventories for micropollutants (MP) to facilitate an evidence-based development of mitigation measures. Regionalized pathway analysis constitutes a moderately data-intensive approach to quantify the contribution of different pathways to the total pollution of surface waters. So far, only few European member states have created an inventory that includes diffuse pathways. The fundamental basis to enable it is an accessible, well-structured and harmonized database with data on the concentration of MPs in multiple compartments, such as soils, groundwater, atmospheric deposition and urban systems. Combined with the water and suspended substance balance in river basins, such data enables the estimation of emission loads via specific pathways. In the Danube River Basin, but in general in Europe, a public data management platform with such scope and criteria is still lacking. Results We collected and harmonized MP measurements across multiple compartments and countries together with key metadata, harmonized and combined them into a new database. The resulting tool, available for download, facilitates the assessment of current data availability, in terms of quantity and quality. For example, while the majority of available data stems from groundwater and surface water, other highly relevant compartments are scarcely represented. By examining differences in MP concentration level across compartments, the database can lead to understand the relevance of specific emission pathways and thus to prioritize data-retrieval and calculation efforts in modelling applications. Selected examples show how to exploit the metadata associated to the measurements to extrapolate the results to regions not covered by specific monitoring programmes. For example, PFAS concentrations in treated wastewater show significant dependence on the design capacity of the treatment plant. Conclusions This study showcases how such database can support the setup of emission inventories, guide data providers and national authorities in prioritizing the allocation of resources for new surveys and in optimizing their national data collection and management systems. The process tested showed a great need for enhanced data literacy across countries and institutions to increase data availability and quality to secure the exploitation of the full information potential generated via monitoring programmes.

Volatile Organic Compounds (VOCs) are not only essential precursors for the formation of ozone and PM2.5, but also hazardous to human health and responsible for unpleasant odors. The pharmaceutical industry has become an important industrial source of VOCs due to China’s large emissions and complex emission chains. In total, 245 VOCs samples were collected and analyzed from 11 typical pharmaceutical companies in Zibo City of the North China Plain, in order to investigate the VOCs emission characteristics and odor impacts. The emission factor for the pharmaceutical industry was 7.97 ± 8.21 g/kg pharmaceuticals, while the main emission links were chimney emissions, equipment sealing leakage, and so on. Finally, considering both purifying efficiency and economic benefits, the multistage absorption (AB) method is most effective for VOCs concentrations below 100 mg/m3, while UV photo-oxygenation combined with adsorption (UVA) is more suitable for concentrations below 300 mg/m3. The Regenerative Thermal Oxidizer (RTO), Catalytic Oxidizer (CO), and Condensation + Adsorption (CA) technologies demonstrated greater stability and efficiency, particularly in the treatment of complex organic pollutants, highlighting their advantages in both VOCs and odor removal at higher concentrations.

Aviation emissions are continuously increasing along with the rapid development of air transportation, and results in the deterioration in regional air quality and the global climate. Accurate emission estimation is of great importance for relevant policies promotion and the sustainable development of the environment. Previous studies focused on the total emissions of a flight and lacked high precision in both spatial and temporal resolutions, especially aviation activities near ground. In this research, we propose an open-sourced emission calculation framework based on actual flight trajectories (TrajEmission), which calculates both the ground and airborne emissions simultaneously according to the configuration parameters, trajectory characteristics, and ambient conditions. We compare the emission results with five emission inventory methods. The results indicate that pollutant (nitrogen oxides, carbon monoxide, and unburned hydrocarbons) emissions in the landing and takeoff (LTO) cycle might usually be underestimated due to a lack of trajectory-based methods. In addition, in the overall results, the method based on the great circle route leads to an overestimation of 56.8% of pollutant emissions compared to the method based on actual routes. We also investigate the extent to which other factors could influence the emission results. To summarize, the TrajEmission framework can build inventories for the whole process of flight movements with high spatial–temporal resolutions and provide solid data support for environmental science and other related fields.

In tandem with the advancement of urban intelligent technology, the construction of remote monitoring platforms and databases for non-road mobile machinery is gradually improving in various provinces and cities. Employing the remote monitoring platform for non-road mobile machinery enables a detailed big data analysis of the actual operational state of the machinery. This method yields precise data on the activity levels of various machinery types. Importantly, it addresses the issue of reduced accuracy in emission inventories, which often arises from the conventional practice of using standard recommended values from the Guide to determine machinery activity levels during the compilation of non-road mobile machinery emission inventories. Based on the remote monitoring and management system of non-road mobile machinery, the actual value of the activity level of non-road mobile machinery was obtained, and the emission inventory of non-road mobile machinery in Shandong Province was established. The emission levels of PM, HC, NOx, and CO from main non-road mobile machinery, including forklifts, excavators, loaders, off-road trucks, and road rollers, were measured. The findings indicate that the operational activity levels of non-road mobile machinery in Shandong Province typically exceeded the guideline's recommended values. Among them, the annual use time of port terminal ground handling equipment was the longest, with an average annual working time of 4321.5 h per equipment, more than six times the recommended value. Among all types of non-road mobile machinery, loader emissions accounted for the highest proportion, reaching 43.13% of the total emissions of various pollutants. With the tightening of the national standard for non-road mobile machinery from Stage II to Stage III, a significant reduction in actual mechanical emissions was observed, primarily manifested as a 91% decrease in NOx emissions. Based on the data from the remote monitoring platform, a new method for compiling the emission inventory of non-road mobile machinery is proposed in this paper. The calculated emission inventory can reflect more real emission situations and provide a reference and basis for emission control and sustainable emission reduction policy measures for non-road mobile machinery. [ABSTRACT FROM AUTHOR]

We explored the microplastic (MPs) emissions of Japanese municipal solid waste incinerators (MSWIs); specifically, the numbers and types of MPs in wastewaters discharged by three MSWIs. We calculated the MSWI MPs emission factors and inventories, and we discuss the results. More than fifteen types of MPs, principally fragments shape were detected. It was important to obtain composite samples because the nature of raw wastewater fluctuated significantly during both day and night in response to the MSWI treatments. MSWI wastewater treatments tended to remove larger particles; over 99% of MPs (in terms of both number and weight) were ultimately removed. The MP emission inventory from MSWIs to public water bodies was 7.22 × 105–1.64 × 106 MPs/year for MPs sized 100–5000 µm. This is very low, at only 0.0053–0.026% of the total MP emission inventory Japanese WWTPs. It is, therefore, possible to remove almost 100% plastics in input waste via incineration and wastewater treatment. [ABSTRACT FROM AUTHOR]

This paper describes an innovative method that recursively applies the machine learning Random Forest to an assumed homogeneous aerographic domain around measurement sites to predict concentrations and emissions of ammonia, an atmospheric pollutant that causes acidification and eutrophication of soil and water and contributes to secondary PM2.5. The methodology was implemented to understand the effects of weather and emission changes on atmospheric ammonia concentrations. The model was trained and tested by hourly measurements of ammonia concentrations and atmospheric turbulence parameters, starting from a constant emission scenario. The initial values of emissions were calculated based on a bottom-up emission inventory detailed at the municipal level and considering a circular area of about 4 km radius centered on measurement sites. By comparing predicted and measured concentrations for each iteration, the emissions were modified, the model's training and testing were repeated, and the model converged to a very high performance in predicting ammonia concentrations and establishing hourly time-varying emission profiles. The ammonia concentration predictions were extremely accurate and reliable compared to the measured values. The relationship between NH3 concentrations and the calculated emissions rates is compatible with physical atmospheric turbulence parameters. The site-specific emissions profiles, estimated by the proposed methodology, clearly show a nonlinear relation with measured concentrations and allow the identification of the effect of atmospheric turbulence on pollutant accumulation. The proposed methodology is suitable for validating and confirming emission time series and defining highly accurate emission profiles for the improvement of the performances of chemical and transport models (CTMs) in combination with in situ measurements and/or optical depth from satellite observation. [ABSTRACT FROM AUTHOR]

Vehicle emissions have become a significant contributor to urban air pollution. However, studies specific to city-level vehicle emission inventories are still scarce and tend to be outdated. This study introduces a methodology for developing high-resolution monthly vehicle emission inventories. We applied this methodology to Changzhou in 2022 to analyze emission characteristics and generate gridded emission data with a resolution of 0.01° × 0.01°. The results show that the total vehicle emissions of carbon monoxide (CO), volatile organic compounds (VOCs), nitrogen oxides (NOx), and fine particulate matters (PM2.5) in Changzhou are 39.69, 8.68, 18.6, and 0.56 Gg, respectively. Light-duty passenger vehicles are the main contributors to CO (74.3%) and VOCs (86.1%) emissions, while heavy-duty trucks play a significant role in NOx (50.7%) and PM2.5 (34.7%) emissions. Gasoline vehicles are mainly responsible for CO (78.6%) and VOCs (91.4%) emissions, while diesel vehicles are the primary source of NOx (81.1%) and PM2.5 (70.6%) emissions. Notably, China IV vehicles have the highest emission contribution rates (ranging from 32.5% to 44.9%). Seasonally, emissions peak in winter and are lowest in April. Spatially, emission intensity is higher in the northeast of Changzhou compared to the west and south. The methodology presented in this study offers a valuable tool for developing comprehensive city-level emission inventories, and the results provide critical insights that can inform the formulation of effective environmental policies. [ABSTRACT FROM AUTHOR]

This study employs an ensemble Kalman filter assimilation method to validate and update the pollutant emission inventory to mitigate the impact of uncertainties on the forecasting performance of air quality numerical models. Based on nationwide ground-level pollutant monitoring data in China, the emission inventory for the entire country was inverted hourly in 2022. The emission rates for PM2.5, CO, NOx, SO2, NMVOCs, BC, and OC updated by the inversion were determined to be 6.6, 702.4, 37.2, 13.4, 40.3, 3, and 18.2 ng/s/m2, respectively. When utilizing the inverted inventory instead of the priori inventory, the average accuracy of all cities' PM2.5 forecasts was improved by 1.5–4.2%, especially for a 7% increase on polluted days. The improvement was particularly remarkable in the periods of January–March and November–December, with notable increases in the forecast accuracy of 12.5%, 12%, and 6.8% for the Northwest, Northeast, and North China regions, respectively. The concentration values and spatial distribution of PM2.5 both became more reasonable after the update. Significant improvements were particularly observed in the Northwest region, where the forecast accuracy for all preceding days was improved by approximately 15%. Additionally, the underestimated concentration of PM2.5 in the priori inventory compared to the observation value was notably alleviated by the application of the inversion. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic negatively affected many sectors including aviation and travel. Travel bans and forced lockdowns prevented transportation activity, especially air travel. Accordingly, huge amounts of emission reductions occurred. On the other hand, travel restrictions are not the only cause of emissions reductions. Changing travel intention in the era of Covid-19 is another important factor that affects aviation emissions. This paper aims to investigate the Landing/Take-Off (LTO) emission changes at Turkish airports. An emission inventory has been implemented for the years 2019 and 2020 to reveal the impacts of Covid-19 on aviation emissions. Domestic, international, and cargo flights have been included in the inventory. According to the results, total emissions of SO2, CO2, CO, NOx, NMVOC, CH4, N2O, and PM2.5 have decreased in 2020 compared to 2019 by 49.8%, 49.7%, 41.0%, 52.6%, 40.0%, 33.8%, 49.8%, and 50.3%, respectively. Total CO2 reductions in the Q2, Q3, and Q4 periods of 2020 compared to that of 2019 are 87%, 50% and 43%, respectively. Another aim of this paper is to find the underlying reasons for emission reductions. For Turkish airports, emission reductions have resulted from travel bans in Q2. After the relaxation of restrictions with the declaration of the "New Normal" in Turkey, flight traffic rebounded to a certain level but was lower than 2019 levels. Therefore, changing travel intention is the main cause of emission reductions in Q3 and Q4 of 2020. The results of this study contribute to both the areas of air pollution and tourism management. [ABSTRACT FROM AUTHOR]

• Young wildfire plumes were observed and documented for the first time in suburban Orléans city, France. • Regional air quality was reduced by the wildfire emissions. • Emission factors of various pollutants were derived and compared with the literature. • Current biomass burning emission inventories have uncertainties in estimating small fire emissions. Wildfire events are increasing globally which may be partly associated with climate change, resulting in significant adverse impacts on local, regional air quality and global climate. In September 2020, a small wildfire (burned area: 36.3 ha) event occurred in Souesmes (Loir-et-Cher, Sologne, France), and its plume spread out over 200 km on the following day as observed by the MODIS satellite. Based on measurements at a suburban site (∼ 50 km northwest of the fire location) in Orléans and backward trajectory analysis, young wildfire plumes were characterized. Significant increases in gaseous pollutants (CO, CH 4 , N 2 O, VOCs, etc.) and particles (including black carbon) were found within the wildfire plumes, leading to a reduced air quality. Emission factors, defined as EF (X) = ∆ X /∆CO (where, X represents the target species), of various trace gases and black carbon within the young wildfire plumes were determined accordingly and compared with previous studies. Changes in the ambient ions (such as ammonium, sulfate, nitrate, chloride, and nitrite in the particle- and gas- phase) and aerosol properties (e.g., aerosol water content, aerosol pH) were also quantified and discussed. Moreover, we estimated the total carbon and climate-related species (e.g., CO 2 , CH 4 , N 2 O, and BC) emissions and compared them with fire emission inventories. Current biomass burning emission inventories have uncertainties in estimating small fire burned areas and emissions. For instance, we found that the Global Fire Assimilation System (GFAS) may underestimate emissions (e.g., CO) of this small wildfire while other inventories (GFED and FINN) showed significant overestimation. Considering that it is the first time to record wildfire plumes in this region, related atmospheric implications are presented and discussed. [Display omitted] [ABSTRACT FROM AUTHOR]

In this study, the relative contributions of main emission sources to the typical ambient concentrations of key pollutants, such as sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and particulate matter (PM10 and PM2.5) in Guayaquil, Ecuador, were investigated. A previous urban emissions inventory for mobile sources was expanded to include other transportation means and main industrial activities using the EMEP/EEA methodology to achieve this objective. The WRF/CALMET/CALPUFF modeling system was used to simulate the annual spatiotemporal distribution of air pollution in the city. According to the model, NO2 concentrations exceed the yearly value and 1-h Ecuadorian standards (40 and 200 μg/m3) in 1 % and 6 % of the cells of the modeling domain, respectively. These hotspots related to local sources were located in the northwest center of the city. The contributions of the manufacturing sector, thermal power plants, ports, airports, and road traffic were assessed individually, and the results indicated that air quality in the study area was strongly dominated by road traffic. The contributions of NO2, CO, PM10, and PM2.5 at the city level reached 76 %, 96 %, 90 %, and 92 % of the annual mean, respectively. In the case of SO2, the manufacturing sector made the most significant contribution (75 %), followed by thermal power plants (16 %). Furthermore, an analysis at 14 specific locations across Guayaquil identified spatial variations that may support the design and development of an air quality monitoring network for the city.

To address global phosphorus reduction challenges, we establish a quantitative framework for anthropogenic phosphorus emissions using a lifecycle model and decomposition analysis. Focusing on China's Pearl River Delta urban agglomeration, we highlight persistent difficulties in controlling phosphorus emissions from agricultural fertilizers and the emerging issue from industrial products. Emission intensity is a crucial factor for phosphorus reduction, yet gradually offset by affluence and population growth. Prioritizing agricultural control with supplementary industrial reduction, we delve into the decoupling challenge between phosphorus emissions, population expansion, and economic development. Proposing green economic development, our approach contributes to achieving sustainable phosphorus management goals.

Abstract Using updated emission inventories can enhance the accuracy of air quality forecast models. Given China’s rapid economic growth and Korea’s geographical and meteorological position on the windward side of China, updating China’s emission inventory has become particularly crucial for Korea’s air quality modeling. This study aimed to develop an updated version of China’s Emission Inventory in Comprehensive Regional Emissions for Atmospheric Transport Experiments version 3 for the base year of 2019 (CREATEv3 (YR 2019)). To achieve this goal, we utilized the Chinese emission inventory of CREATEv3 for the base year of 2015 (CREATEv3 (YR 2015)) as a framework to incorporate the latest Chinese emission data from the Multi-resolution Emission Inventory Model for Climate and Air Pollution Research for the base year of 2019 (MEIC COVID-19 (YR 2019)) and update the inventory. The updated China’s annual emissions are now reflected in CREATEv3 (YR 2019), and the amounts are as follows: 132 Tg for CO, 21 Tg for NO x , 8 Tg for SO2, 7 Tg for PM2.5, 9 Tg for NH3, and 28 Tg for volatile organic compound (VOC). By comparing previous Chinese emission inventories with the updated inventory developed in this study, it was found that SO2, NO x , VOC, and NH3 emissions were decreased. Therefore, using the updated inventory seemingly reduces the impact of China’s fine dust on Korea. By comparing emissions by pollutant and region in China using CREATEv3 (YR 2019), it was found that regions with high emissions of targeted pollutants strongly correlated with major industries operating in those areas. This study is expected to provide insights into China’s emission changes in 2019 and support air quality forecasting.

Atmospheric volatile organic compounds (VOCs), such as olefins and aromatics, released from synthetic chemical pesticide sprays can increase regional air pollution, public health risks, and food security risks. However, significant uncertainties remain regarding the measurement methods and chemical profiles of VOC emissions. Using an agricultural city, Changchun City in Northeast China, as a case study, we quantified real-time concentration and composition data based on online monitoring instruments for the year 2023. This study optimized data collection methods for emission factors and activity levels and developed a high-precision emission inventory of VOCs in pesticides at the city scale. The emission factors for VOCs from the seven categories of pesticides were estimated as follows: 78 g/kg (nicosulfuron and atrazine, oil-dispersible [OD] and suspension emulsion [SE], respectively), 4 g/kg (chlorpyrifos and indoxair conditioningarb, suspension concentrate [SC]), 5 g/kg (fluopicolide and propamocarb hydrochloride, SC), 217 g/kg (MCPA-dimethylammonium, aqueous solution [AS]), 34 g/kg (glyphosate, AS), 575 g/kg (beta-cypermethrin and malathion, emulsifiable concentrate [EC]), and 122 g/kg (copper abietate, emulsion in water [EW]), depending on the pesticide formulation components and formulation types. The orchard insecticide exhibited the highest emission factors among all pesticides owing to its emulsifiable concentrate formulation and 80% content of inactive ingredients (both factors contribute to the high content of organic solvents in the pesticide). The major components of VOC emissions from pesticide spraying were halocarbons (27–44%), oxygenated VOCs (OVOCs) (25–38%), and aromatic hydrocarbons (15–28%). The total VOC emissions from pesticide spraying in the Changchun region accounted for 10.6 t, with Yushu City contributing 28% of the VOC emissions and Gongzhuling City and Dehui City contributing 18.7% and 16.0%, respectively. Herbicides were the main contributors to VOC emissions because of their high emission factors and extensive use in fields (used for spraying maize and rice, the main crops in Changchun City). May and June exhibited the highest VOC emissions from pesticide application, with May accounting for 57.0% of annual pesticide emissions, predominantly from herbicides (95.1%), followed by insecticides (4.9%). June accounted for 30.1% of the annual pesticide emissions, with herbicides being the largest contributor of VOC emissions. An emission inventory of VOC with a monthly scale and spatial grid resolutions of 0.083° and 0.5° in 2023 was developed. These emission factors and inventories of pesticide applications provide valuable information for air quality modeling. This study also provides an important scientific basis for enhancing regional air quality and mitigating the environmental impact of pesticide use in major grain-producing areas.

Ammonia is one of the precursor gases in the formation of particulate matter (PM) that reacts with nitrogen oxides and sulfur oxides in the atmosphere. Based on the Clean Air Policy Support System (CAPSS) of Korea, the annual ammonia emissions amounted to 261,207 tons in 2020 and the agricultural source (manure management sector) contributes the highest proportion of the ammonia inventory. However, the methodology for the study of ammonia emissions in Korea has some limitations regarding the representativeness of the sites selected and the reliability of the measurement method. In this study, we aimed to recalculate the ammonia emissions from the livestock industry in Korea using the UK’s estimation method, which uses the life cycle assessment of livestock manure. Three major animal types, i.e., cattle (beef cattle and dairy cows), pigs and chickens, and three major processes based on the manure flow, i.e., housing, manure storage and treatment and land application processes, were considered. The total ammonia emissions were estimated to be approximately 33% higher than the official ammonia emissions stated by the CAPSS. For the manure flow, the ammonia emissions were the highest from land application processes. The ammonia emissions from dairy cow and poultry manure were much higher than those stated by the CAPSS, while the emissions from beef cattle and pig manure showed similar levels. The methodology used in this study can offer an alternative approach to the ammonia emission estimation of the manure management sector in the agriculture industry of Korea. Korean emission factors based on the manure flow should be developed and applied in the future.

Abstract Background Urban agglomerates play a crucial role in reaching global climate objectives. Many cities have committed to reducing their greenhouse gas emissions, but current emission trends remain unverifiable. Atmospheric monitoring of greenhouse gases offers an independent and transparent strategy to measure urban emissions. However, careful design of the monitoring network is crucial to be able to monitor the most important sectors as well as adjust to rapidly changing urban landscapes. Results Our study of Paris and Munich demonstrates how climate action plans, carbon emission inventories, and urban development plans can help design optimal atmospheric monitoring networks. We show that these two European cities display widely different trajectories in space and time, reflecting different emission reduction strategies and constraints due to administrative boundaries. The projected carbon emissions rely on future actions, hence uncertain, and we demonstrate how emission reductions vary significantly at the sub-city level. Conclusions We conclude that quantified individual cities’ climate actions are essential to construct more robust emissions trajectories at the city scale. Also, harmonization and compatibility of plans from various cities are necessary to make inter-comparisons of city climate targets possible. Furthermore, dense atmospheric networks extending beyond the city limits are needed to track emission trends over the coming decades.

The escalating greenhouse gas (GHG) emissions from maritime trade present a serious environmental and biological threat. With increasing emission reduction initiatives, such as the European Union's incorporation of the maritime sector into the emissions trading system, both challenges and opportunities emerge for maritime transport and associated industries. To address these concerns, this study presents a model specifically designed for estimating and projecting the spatiotemporal GHG emission inventory of ships, particularly when dealing with incomplete automatic identification system datasets. In the computational aspect of the model, various data processing techniques are employed to rectify inaccuracies arising from incomplete or erroneous AIS data, including big data cleaning, ship trajectory aggregation, multi-source spatiotemporal data fusion and missing data complementation. Utilizing a bottom-up ship dynamic approach, the model generates a high-resolution GHG emission inventory. This inventory contains key attributes such as the types of ships emitting GHGs, the locations of these emissions, the time periods during which emissions occur, and emissions. For predictive analytics, the model utilizes temporal fusion transformers equipped with the attention mechanism to accurately forecast the critical emission parameters, including emission locations, time frames, and quantities. Focusing on the sea area around Tianjin port--a region characterized by high shipping activity--this study achieves fine-grained emission source tracking via detailed emission inventory calculations. Moreover, the prediction model achieves a promising loss function of approximately 0.15 under the optimal parameter configuration, obtaining a better result than recurrent neural network (RNN) and long short-term memory network (LSTM) in the comparative experiments. The proposed method allows for a comprehensive understanding of emission patterns across diverse vessel types under various operational conditions. Coupled with the prediction results, the study offers valuable theoretical and data-driven support for formulating emission reduction strategies and optimizing resource allocation, thereby contributing to sustainable maritime transformation. [ABSTRACT FROM AUTHOR]

Rice cultivation stands as the primary agricultural activity in Asia, generating a substantial amount of agricultural waste. Unfortunately, this waste is often disposed of through burning, contributing to severe environmental, health and climate issues. This study presents the characterization of PCDD/Fs, PCBs and PAHs. The emissions were quantified using a fixed-grid-system biomass plant and measuring the macro-pollutants online and sampling the organic micro-pollutants and metals in isokinetic mode, followed by ISO and CEN standards methods. Additionally, the role of agrochemicals was monitored in terms of metal catalysis resulting in POP emissions. This study provides the comprehensive characterization of the most relevant groups of pollutants (metals, PCDD/Fs, PCBs and PAHs) resulting from agricultural waste combustion. Prominent catalytic metals quantified were Cu (22–48 µg/Nm3) and Fe (78–113 µg/Nm3). Rice straw samples from AJK exhibited higher values of organochlorine micro-pollutants compared to those from Punjab and Sindh, i.e., ∑PCDD/F (2594 > 1493 > 856 pg/Nm3) and ∑PCB (41 > 38 > 30 pg/Nm3), respectively, whereas the organic micro-pollutants ∑c-PAH, indicators of incomplete combustion (PICs), were recorded high in the samples from Sindh followed by Punjab and AJK. The average EF is 100 pg/kg, 2.2 pg/kg and 1053.6 µg/kg for ∑PCDD/F, ∑PCB and ∑c-PAH. This study supports the idea that the phenomena leading to the formation of dioxin and dioxin-like compounds are influenced not only by poor combustion but also by the presence of metal catalysts in the burned fuel. [ABSTRACT FROM AUTHOR]

Currently, Tangshan confronts the dual challenge of elevated carbon emissions and substantial pollution discharge from the iron and steel industries (ISIs). While significant efforts have been made to mitigate air pollutants and carbon emissions within the ISIs, there remains a gap in comprehending the control of carbon emissions, air pollutant emissions, and their contributions to air pollutant concentrations at the enterprise level. In this study, we devised the Air Pollutant and Carbon Emission and Air Quality (ACEA) model to identify enterprises with noteworthy air pollution and carbon emissions, as well as substantial contributions to air pollutant concentrations. We constructed a detailed inventory of air pollutants and CO2 emissions from the iron and steel industry in Tangshan for the year 2019. The findings reveal that in 2019, Tangshan emitted 5.75 × 104 t of SO2, 13.47 × 104 t of NOx, 3.55 × 104 t of PM10, 1.80 × 104 t of PM2.5, 5.79 × 106 t of CO and 219.62 Mt of CO2. The ACEA model effectively pinpointed key links between ISI enterprises emitting air pollutants and carbon dioxide, notably in pre-iron-making processes (coking, sintering, pelletizing) and the Blast furnace. By utilizing the developed air pollutant emission inventory, the CALPUFF model assessed the impact of ISI enterprises on air quality in the Tangshan region. Subsequently, we graded the performance of air pollutant and CO2 emissions following established criteria. The ACEA model successfully identified eight enterprises with significant air pollution and carbon emissions, exerting notable influence on air pollutant concentrations. Furthermore, the ACEA outcomes offer the potential for enhancing regional air quality in Tangshan and provide a scientific instrument for mitigating air pollutants and carbon emissions. The effective application of the ACEA model in Tangshan's steel industry holds promise for supporting carbon reduction initiatives and elevating environmental standards in other industrial cities across China. [ABSTRACT FROM AUTHOR]

Background: Urban agglomerates play a crucial role in reaching global climate objectives. Many cities have committed to reducing their greenhouse gas emissions, but current emission trends remain unverifiable. Atmospheric monitoring of greenhouse gases offers an independent and transparent strategy to measure urban emissions. However, careful design of the monitoring network is crucial to be able to monitor the most important sectors as well as adjust to rapidly changing urban landscapes. Results: Our study of Paris and Munich demonstrates how climate action plans, carbon emission inventories, and urban development plans can help design optimal atmospheric monitoring networks. We show that these two European cities display widely different trajectories in space and time, reflecting different emission reduction strategies and constraints due to administrative boundaries. The projected carbon emissions rely on future actions, hence uncertain, and we demonstrate how emission reductions vary significantly at the sub-city level. Conclusions: We conclude that quantified individual cities' climate actions are essential to construct more robust emissions trajectories at the city scale. Also, harmonization and compatibility of plans from various cities are necessary to make inter-comparisons of city climate targets possible. Furthermore, dense atmospheric networks extending beyond the city limits are needed to track emission trends over the coming decades. [ABSTRACT FROM AUTHOR]

Prevailing dry conditions and rainfall deficit during the spring season in North India led to heat wave conditions which resulted in widespread and intense forest fire events in the Himalayan state of Uttarakhand during April 16–30, 2022. A total of 7589 active fires were detected by VIIRS during the second half of April 2022 compared to 1558 during the first half. The TROPOMI observed total column values of CO and NO2 increased by 4.4% and 11.7%, respectively during April 16–30, 2022 with respect to April 1–15, 2022. A noticeable increase in surface level concentration of trace gases was also observed at Dehradun. In situ measurements of CO, NOx, and O3 during April 16–30, 2022 show an increase of 133, 35, and 6% compared to previous year observations during the same period. Weather Research and Forecasting model with chemistry (WRF-Chem) is utilized to quantitatively estimate the contribution of this event on the distribution of air pollutants over this state. The model results were evaluated against ERA5 reanalysis, upper air soundings, and TROPOMI-retrieved total column density (TCD) of CO, NO2, and O3. Two simulations with (Fire) and without (NoFire) biomass burning emissions input were performed to quantify the contribution of forest fires to the concentration of trace gases and particulates. The CO, NO2, and O3 emitted/produced from forest fire over Uttarakhand during April 2022 contributed approximately 39.95, 35.73, and 9.97% to the surface concentration of respective gas. In the case of aerosols, it was around 71.20, 71.44, and 33.62% for PM2.5, PM10, and BC respectively. The vertical profile analysis of pollutants revealed that extreme forest fire events can perturb the distribution of air pollutants from the surface up to 450 hPa. [ABSTRACT FROM AUTHOR]

Elevated emission of particulate matter (both PM2.5 and PM10) is not limited to urban areas. It's the major pollutant that drives the air quality across the Indian sub-continent as well as across the globe with adverse health impacts. Moreover, India is home to many polluted cities in recent years that are among the list of most polluting cities in the globe. Therefore, the identification of sources of particulate matter and their quantification along with spatial variability has become of paramount importance from the modelling point of view. The present work is an attempt to develop a high-resolution (~10kmx~10km) national inventory of particulate (both PM2.5 and PM10) pollutants for India for the base year 2020 using IPCC methodology. The study quantifies the emission load from all possible sources in the county using the best possible resolution activity data and bottom-up approach. The estimated annual emission for PM2.5 and PM10, are calculated to be 15.8 Tg/yr, and 8.3 Tg/yr respectively. The developed emission dataset is publicly available on Zenodo at https://doi.org/10.5281/zenodo.7885103 (Sahu et al., 2023). Transport-driven windblown road dust remains the dominating source of PM10 emission, while transport and industry are the most important sources of PM2.5. The unattended anthropogenic source - municipal solid waste burning is found to be emerging as a new threat followed by crop residue burning. The developed new surface dataset has formulated a few recommendations of possible mitigation strategies for India and would be a critical tool for modelling studies. [ABSTRACT FROM AUTHOR]

Road silt loading (sL) is an important parameter in the fugitive road dust (FRD) emissions. In this study, the improved Testing Re-entrained Aerosol Kinetic Emissions from Roads (TRAKER) combined with the AP-42 method was firstly developed to quickly measure and estimate the sLs of paved roads in Beijing, China. The annual average sLs in Beijing was 0.59±0.31 g/m2 in 2020, and decreased by 22.4% compared with that in 2019. The seasonal variations of sLs followed the order of spring > winter > summer > autumn in the two years. The seasonal mean road sLs on the same type road in the four seasons presented a decline trend from 2019 to 2020, especially on the Express way, decreasing 47.4%-72.7%. The road sLs on the different type roads in the same season followed the order of Major arterial ∼ Minor arterial ∼ Branch road > Express road, and Township road ∼ Country highway > Provincial highway ∼ National highway. The emission intensities of PM 10 and PM 2.5 from FRD in Beijing in 2020 were lower than those in 2019. The PM 10 and PM 2.5 emission intensities at the four planning areas in the two years all presented the order of the capital functional core area > the urban functional expansion area > the urban development new area > the ecological conservation and development area. The annual emissions of PM 10 and PM 2.5 from FRD in Beijing in 2020 were 74,886 ton and 18,118 ton, respectively, decreasing by ∼33.3% compared with those in 2019. [Display omitted] [ABSTRACT FROM AUTHOR]