Air Pollutant Emission Inventory Research Articles

Civil aviation emissions in China in 2019: Characteristics and abatement potential

Civil aviation is one of the industries facing the greatest challenge in reaching carbon neutrality by the middle of this century, and this sector also contributes to adverse impacts on the regional air quality and human health. China exhibits the second highest air passenger turnover worldwide. Our understanding of civil aviation emissions must be urgently enhanced, and the mitigation potential should be explored. In this study, on the basis of real domestic flight information for 2019, we built a greenhouse gas and air pollution emission inventory for the civil aviation sector in China with the fuel flow method based on the cruise and other phases. We thoroughly analyzed emissions by region, aircraft and engine types, and aircraft age, based on which we designed four measures to evaluate the abatement potential. We found that the hydrocarbon (HC), CO, NOx, SO2, particulate matter (PM) and CO2 emissions in 2019 reached 79.9 kt (95% CI [51.6–114.5]), 176.3 kt (95% CI [114.5–248.2]), 304.2 kt (95% CI [203.4–420.7]), 23.2 kt (95% CI [14.2–33.7]), 1.0 kt (95% CI [0.61–1.44]) and 87.0 Mt (95% CI [57.4–119.6]), respectively. The cruise phase was the major emission phase, accounting for 67%-87% of the total pollutant emissions. If four measures were jointly implemented, the HC, CO, NOx, SO2, PM and CO2 emissions could be reduced by 61%, 54%, 55%, 45%, 32% and 38%, respectively. Utilizing lower-emission aircraft and switching travel modes could substantially reduce civil aviation emissions in China.

Air pollution emission inventory using national high-resolution spatial parameters for the Nordic countries and analysis of PM2.5 spatial distribution for road transport and machinery and off-road sectors

Abstract. Air pollution is an important cause of adverse health effects, even in the Nordic countries, which have relatively good air quality. Modelling-based air quality assessment of the health impacts relies on reliable model estimates of ambient air pollution concentrations, which furthermore rely on good-quality spatially resolved emission data. While quantitative emission estimates are the cornerstone of good emission data, description of the spatial distribution of the emissions is especially important for local air quality modelling at high resolution. In this paper we present a new air pollution emission inventory for the Nordic countries with high-resolution spatial allocation (1 km × 1 km) covering the years 1990, 1995, 2000, 2005, 2010, 2012, and 2014. The inventory is available at https://doi.org/10.5281/zenodo.10571094 (Paunu et al., 2023). To study the impact of applying national data and methods to the spatial distribution of the emissions, we compared road transport and machinery and off-road sectors to CAMS-REGv4.2, which used a consistent spatial distribution method throughout Europe for each sector. Road transport is a sector with well-established proxies for spatial distribution, while for the machinery and off-road sector, the choice of proxies is not as straightforward as it includes a variety of different type of vehicles and machines operating in various environments. We found that CAMS-REGv4.2 was able to produce similar spatial patterns to our Nordic inventory for the selected sectors. However, the resolution of our Nordic inventory allows for more detailed impact assessment than CAMS-REGv4.2, which had a resolution of 0.1° × 0.05° (longitude–latitude, roughly 5.5 km × 3.5–6.5 km in the Nordic countries). The EMEP/EEA Guidebook chapter on spatial mapping of emissions has recommendations for the sectoral proxies. Based on our analysis we argue that the guidebook should have separate recommendations for proxies for several sub-categories of the machinery and off-road sectors, instead of including them within broader sectors. We suggest that land use data are the best starting point for proxies for many of the subsectors, and they can be combined with other suitable data to enhance the spatial distribution. For road transport, measured traffic flow data should be utilized where possible, to support modelled data in the proxies.

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.

Air pollutant emissions and sources in Lao People’s Democratic Republic: a provincial scale analysis for years 2013-2019

Recent rapid economic development in Lao People’s Democratic Republic (PDR) has increased national fuel consumption, vehicle fleet, industrial output, waste generation, and agricultural production. This has contributed to national average ambient fine particulate matter (PM2.5) air pollutant levels that are four times higher than World Health Organisation guidelines. Emission inventories are a key tool in understanding the major sources to these air pollution levels, and provide a starting point to identify where mitigation action can be targeted. A national air pollutant emission inventory has not been developed in Lao PDR and, combined with a limited air quality monitoring network means there is limited capacity to develop and track the effectiveness of mitigation actions. This study describes the first air pollutant emission inventory at the national and provincial scale for Lao PDR, covering 2013–2019. Emissions of nine air pollutants, and two greenhouse gases, were quantified using national statistics and international default emission factors. In 2019, national total PM2.5, Nitrogen Oxides (NOx), Black Carbon (BC), Sulphur Dioxide (SO2), Non-Methane Volatile Organic Carbons (NMVOCs), and Ammonia (NH3) were 125, 83, 9.7, 26, 219, and 99 thousand tonnes respectively. Key source sectors include forest fires, residential cooking, agriculture, electricity generation, and transport. However, the contribution of different sources varies across provinces. Forest fires are the primary source determining the spatial trend of particulate air pollution while residential and agricultural emissions contribute more significantly to rural provinces such as Savannakhet. Key sectors in major urban provinces (Vientiane Capital and Xayaboury) are industry, transport and electricity generation. These sectors are also significant sources of greenhouse gases (CO2 and CH4), demonstrating the potential for identification, evaluation and prioritisation of actions that simultaneously improve air quality and achieve Lao PDR’s international climate change commitments.

Evaluation of exhaust emissions of agricultural tractors using portable emissions measurement system in Korean paddy field

Recently, diesel engine emissions have been designated as a first-class carcinogen by the World Health Organization (WHO). As such, problems with diesel engine emissions continue to increase around the world. This study aimed to analyze the emissions (CO, NOx, PM) of agricultural tractors during farming operations in order to build a reliable national inventory of air pollutant emissions. Emission data were collected using a portable emission measurement system during actual agricultural operation. The load factor (LF) of the engine was calculated using the collected engine information, the emission factor was analyzed using the LF and the measured emission. The LF was significantly different from the current standard value of 0.48, which is used in Korea to calculate exhaust emissions. The deviation ratio of the emission factor was 0.039 ~ 56.59 compared to Tier-4 emission regulation standards. Under many conditions, the calculated emission factor was higher than the emission limit. Thus, this study provides useful information for emission inventory construction through emission calculation under actual conditions and suggests the need to realize the currently applied emission factor.

Predicting air pollutant emissions of the foundry industry: Based on the electricity big data

Industrial enterprises are one of the largest sources of air pollution. However, the existing means of monitoring air pollutant emissions are narrow in coverage, high in cost, and low in accuracy. To bridge these gaps, this study explored a predicting model for air pollutant emissions from foundry industries based on high-accuracy electricity consumption data and continuous emission monitoring system (CEMS). The model has then been applied to the calculation of air pollutant emissions from foundries without CEMS and the optimization of air pollutant emission temporal allocation factors. The results reveal that electricity consumption and PM emissions during the 2022 Beijing Winter Olympics have the same ascending and descending relationship. Furthermore, a cubic polynomial model between electricity consumption and flue gas flow is established based on the whole year data of 2021 (R2 = 0.85). The relative errors between the PM emissions calculated by the model and the emission factor method are small (−17.09–24.12 %), and the results from the two methods revealed a strong correlation (r = 0.93, p < 0.01). In addition, the monthly PM emissions from foundries are mainly concentrated in spring and winter, and the daily emissions on weekends are significantly lower than those on workdays. These results can be useful for environmental regulation and optimization of air pollutant emission inventories of foundry industry.

A bilinear interpolation model for estimating commercial vehicles' fuel consumption and exhaust emissions

In this paper, an estimation model based on bilinear interpolation of data from the EMEP/EEA air pollutant emission inventory guidebook database regarding fuel consumption and exhaust emissions of commercial vehicles in different operating conditions is developed. Depending on vehicle's average speed, road slope and load factor, the model determines the fuel consumption and emissions for the observed vehicle type, category and emission standard. In order to validate the model, recordings on actual commercial vehicles were made in real operating conditions on two urban public transport bus lines in Belgrade. Comparison of the estimated and actual results from vehicle operation substantiate satisfactory validation of the model, making it suitable for logistics managers in operational and tactical planning as easy to use decision making tool allowing better sustainability and lower environmental footprint.

Improving the Air Quality Management: The Air Pollutant and Carbon Emission and Air Quality Model for Air Pollutant and Carbon Emission Reduction in the Iron and Steel Industries of Tangshan, Hebei Province, China

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.

Increased Impact of Aviation on Air Quality and Human Health in China.

China's civil aviation market has rapidly expanded, becoming the world's second-largest. However, the air quality and health impacts caused by its aircraft emissions have been inadequately assessed. Here, we leverage an updated emission inventory of air pollutants with improved temporal and spatial resolution based on hundreds of thousands of flight trajectories and simulate aviation-attributable contributions to ground-level air pollution in China. We find that in 2017, the annual-average aviation-attributed PM2.5 and O3 concentrations were 0.4-1.5 and 10.6-14.5 μg·m-3, respectively, suggesting that aviation emissions have become an increasingly important source of ambient air pollution. The contributions attributable to high-altitude emissions (climb/cruise/descent) were comparable to those at low altitudes (landing and takeoff). Aviation-attributed ambient PM2.5 and O3 exposures are estimated to have caused about 67,000 deaths in China in 2017, with populous coastal regions in Eastern China suffering the most due to the dense aviation activity. We recommend that industrial and policy stakeholders expedite an agenda of regulating air pollutants harmonized with decarbonization efforts for a more sustainable aviation future.

Analysis of emission characteristics and driving forces of air pollutants and GHG from coal-fired industrial boilers in China

Coal burning is considered to be the main anthropogenic source of air pollutants, which can cause serious environmental pollution. As one of the important coal burning sources, coal-fired boilers have become the important challenges of the policy of “carbon peaking” and “carbon neutrality” of Chinese government. In this paper, the emission inventory of air pollutants (TSP, SO2, NOX, VOCs), and greenhouse gases (GHG, including CO2, CH4, N2O) from coal-fired industrial boilers (CFIB) from 2006 to 2020 are established by using the “bottom-up” emission factor method. Besides, Kaya identical equation and Logarithmic mean Divisia index (LMDI) model are used to quantify the driving forces of the changing tendency in pollutants emission based on five driving factors, which include pollution production coefficient (f), control technology level (β), economy (GOV), industrial energy intensity (e) and coal consumption structure of industrial boilers (s). Combined with existing relevant policies, the future emission tendency of air pollutants and GHG in 2025 and 2030 is projected. The result shows that policy adjustment has a significant impact on pollutant emission trends. In 2020, emissions of TSP, SO2, NOX, VOCs and GHG from CFIB in China are 679.5 kt, 644.7 kt, 603.9 kt, 40.7 kt and 4.4 × 105 kt CO2e, respectively. Control technology level is the main factor to the emission reduction of SO2 and TSP, which has caused a decrease of 4278.6 kt and 3337.3 kt in emissions of SO2 and TSP compared to those of 2006 respectively, while the influencing effect on NOX, GHG and VOCs was relatively weak. In addition, in the scenario of improved control technology, pollutant emissions could be reduced by 62.6%–94.9% until 2030.

High-precision spatio-temporal variations and future perspectives of multiple air pollutant emissions from Chinese biomass-fired industrial boilers

Biomass-fired industrial boilers (BFIBs) are one of the neglected and important anthropogenic sources of air pollutants. A comprehensive boiler-based emission inventory of multiple air pollutants from BFIBs in China in 2020 was first developed based on the activity level database and updated emission factors. Results showed that national emissions of air pollutants from BFIBs in 2020 were estimated to be 11.5 kt of PM, 10.8 kt of PM10, 7.4 kt of PM2.5, 40.5 kt of SO2, 79.8 kt of NOx, 4.2 kt of organic carbon (OC), 1.0 kt of elemental carbon (EC), 31.7 kt of nonmethane volatile organic compounds (NMVOCs), 15.9 kt of NH3, and 116.5 t of five trace metals (Hg, Cr, Cd, Pb, and As), respectively. Air pollutant emissions exhibited significant spatio-temporal heterogeneity. Monthly air pollutant emissions varied by geographical division due to the combined effects of industrial production and winter heating demand. These emissions were mainly concentrated in the eastern coastal region, with Guangdong, Guangxi, Fujian, Jiangsu, and Zhejiang being the five provinces having the highest emissions. In addition, scenario predictions indicate that as the pollution and carbon reduction strategy is implemented, air pollutant emissions from BFIBs in China could become well controlled, with PM, NOx, SO2, and Hg emissions in 2050 projected to be 3.0–8.3 kt, 36.5–75.7 kt, 16.2–32.8 kt, and 0.52–0.87 t, respectively. Our results can provide a highly spatio-temporal resolution inventory of multiple air pollutant emissions from BFIBs for air quality modelling and support the formulation of air pollution control policies for biomass fuel utilization in the context of the pollution and carbon reduction strategy.

Collaborative governance of trade-driven transboundary air pollution in China: A responsibility-based fair compensation mechanism

Transboundary air pollution poses a significant challenge in China, and collaborative governance presents a promising approach to tackle this problem. However, such approach is rarely implemented due to the influence of inter-regional trade dynamics. To address this issue, a comprehensive, responsibility-based fair compensation mechanism was established in the present study. The aim of the mechanism is to bridge the existing gap through the integrated utilization of air pollutant emission inventories, multi-regional input-output analysis, emission responsibility allocation, and an ecological compensation model. In 2017, approximately 50% of China's air pollutant emissions were embedded in inter-provincial trade, primarily originating from wealthier provinces and directed towards less-developed regions with higher pollution intensity. There exists a significant imbalance between the inter-provincial transfers of air pollution and economic benefits, owing to which Inner Mongolia and Liaoning have suffered from serious environmental inequity brought about by trade. The allocation of responsibility for trade-related emissions between producers and consumers is determined by the economic surplus they gain from trade. Such approach results in an intermediate outcome that falls between production-based and consumption-based emissions for the majority of provinces. The scheme highlights the import-related share of responsibility for economically developed provinces and the export-related share for less-developed, pollution-intensive provinces, which can primarily be attributed due to their differences in value chain specialization. The inter-provincial compensation volumes for trade-related emissions are determined based on the economically equitable emission responsibility sharing scheme. More developed provinces, characterized by industrial structures focused on low-pollution, high-value-added products, primarily function as compensation providers. In contrast, less-developed provinces with higher pollution intensity seek compensation from these more affluent regions. The present findings can offer a quantitative basis for the ecological compensation and collaborative control mechanism of trade-driven transboundary air pollution in China.

Synergistic Benefits of Pollution and Carbon Reduction from Air Pollution Control in Hebei Province from 2013 to 2020

Recently, China has been facing the dual challenges of air pollution control and carbon emission reduction. Pollution and carbon reduction have become a breakthrough point for green socio-economic transformation. Air pollutant and CO2 emission inventories provide a tool for monitoring pollution and carbon reduction; however, there have been some problems in previous studies, including incomplete species coverage, different source classifications, and narrow time scales. Based on the unified emission source classification system and estimation method, an emission inventory was developed for Hebei Province from 2013 to 2020, and the emission trends, structure change, driving force, synergistic benefits, and spatial distribution were analyzed. Hebei Province achieved a balance during the study period in socio-economic development and anthropogenic emission control. SO2 emissions decreased rapidly during the "Ten Atmospheric Measures" period. VOCs and NH3 emissions reduction were more significant during the "Blue Sky Defense War" period. The decrease rates of NOx and PM2.5 emissions were relatively stable, and CO2 emissions increased slightly. The coal-fired treatment effectively reduced the air pollutant and CO2 emissions and strengthening the emission standards for key industries reduced SO2, NOx, and PM2.5 emissions; however, the VOCs emission control requires improvement. Power and residential sources achieved co-reduction of air pollutants and CO2 and reducing residential coal optimized the energy structure, thereby leading to greater synergistic benefits in the residential source. The key pollution and carbon reduction areas in Hebei Province were Shijiazhuang, Tangshan, Handan, Baoding, and Langfang. The methods and conclusions in this study can provide technical and decision-making references for regional pollution and carbon reduction efforts.

Emission inventory of air pollutants from residential coal combustion over the Beijing-Tianjin-Hebei Region in 2020

Emission inventory of air pollutants from residential coal combustion over the Beijing-Tianjin-Hebei Region in 2020

Impact of Solvent Emissions on Reactive Aromatics and Ozone in the Great Lakes Region

While transportation emissions have declined over the past several decades, volatile organic compound (VOC) emissions from solvent use applications have increased as urban areas expand. In this work, the Canadian air quality model (GEM-MACH-TEB) is used to assess the importance of solvent emissions during the Michigan Ontario Ozone Source Experiment (MOOSE). Model predictions are compared to ozone and total mono-substituted aromatics (TOLU) observations collected in Windsor, Ontario. For summer 2018, model estimates of TOLU from solvent emissions are smaller (30% for an 8 h daytime average) in Windsor than estimates from positive matrix factorization (44% for a 24 h average). The use of updated U.S. solvent emissions from the EPA’s VCPy (Volatile Chemical Product framework) for summer 2021 simulations increases the solvent use source contribution over Detroit/Windsor (30–50% for an 8 h daytime average). This also provides a more uniform spatial distribution across the U.S./Canada border (30–50% for an 8 h daytime average). Long-chain alkanes are the dominant speciation in the model’s air pollutant emission inventory and in the observation-derived solvent use factor. Summertime 8 h daytime ozone decreased by 0.4% over Windsor for a 10% solvent use VOC emission reduction scenario. A 10% mobile NOx emission reduction scenario resulted in a 0.6% O3 decrease over Windsor and more widespread changes over the study region.

The HTAP_v3 emission mosaic: merging regional and global monthly emissions (2000–2018) to support air quality modelling and policies

Abstract. This study, performed under the umbrella of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP), responds to the global and regional atmospheric modelling community's need of a mosaic emission inventory of air pollutants that conforms to specific requirements: global coverage, long time series, spatially distributed emissions with high time resolution, and a high sectoral resolution. The mosaic approach of integrating official regional emission inventories based on locally reported data, with a global inventory based on a globally consistent methodology, allows modellers to perform simulations of high scientific quality while also ensuring that the results remain relevant to policymakers. HTAP_v3, an ad hoc global mosaic of anthropogenic inventories, has been developed by integrating official inventories over specific areas (North America, Europe, Asia including Japan and South Korea) with the independent Emissions Database for Global Atmospheric Research (EDGAR) inventory for the remaining world regions. The results are spatially and temporally distributed emissions of SO2, NOx, CO, non-methane volatile organic compounds (NMVOCs), NH3, PM10, PM2.5, black carbon (BC), and organic carbon (OC), with a spatial resolution of 0.1∘ × 0.1∘ and time intervals of months and years, covering the period 2000–2018 (https://doi.org/10.5281/zenodo.7516361, Crippa, 2023, https://edgar.jrc.ec.europa.eu/dataset_htap_v3, last access: June 2023). The emissions are further disaggregated into 16 anthropogenic emitting sectors. This paper describes the methodology applied to develop such an emission mosaic, reports on source allocation, differences among existing inventories, and best practices for the mosaic compilation. One of the key strengths of the HTAP_v3 emission mosaic is its temporal coverage, enabling the analysis of emission trends over the past 2 decades. The development of a global emission mosaic over such long time series represents a unique product for global air quality modelling and for better-informed policymaking, reflecting the community effort expended by the TF-HTAP to disentangle the complexity of transboundary transport of air pollution.

Emission Inventory of Airborne Pollutants from Biomass Combustion in Guizhou Province

With the objective to ascertain the emissions of biomass combustion in Guizhou, the activity levels were measured through data collection and field surveys, and the emission factors were acquired using actual monitoring data and data cited from previous literature. A 3 km×3 km-gridded emission inventory of nine air pollutants from biomass combustion sources in Guizhou Province in 2019 was developed in combination with GIS technology. The results showed that the total emissions of CO, NOx, SO2, NH3, VOCs, PM2.5, PM10, BC, and OC in Guizhou were estimated to be 293505.53, 14781.19, 4146.11, 8501.07, 45025.70, 39463.58, 41879.31, 6832.33, and 15134.74 t, respectively. The distribution of atmospheric pollutants emitted by biomass combustion sources in different cities was noticeably uneven, being mainly concentrated in Qiandongnan Miao and Dong Autonomous Prefecture. The analysis of variation characteristics of emissions indicated that the monthly emissions were concentrated in February, March, April, and December, and the hourly emissions peaked daily from 14:00 to 15:00. Some uncertainty remained in the emission inventory. It is necessary to perform in-depth analyses of the accuracy of obtaining activity-level data, localize the emission factors through more combustion experiments in subsequent research for improving the emission inventory of air pollutants from biomass combustion in Guizhou Province, and provide a basis for the cooperative governance of the atmospheric environment.

Emission trends of air pollutants and CO2 in China from 2005 to 2021

Abstract. China is facing the challenge of synergistic reduction of air pollutants and CO2 emissions. However, the studies on its historical progress and future priorities are insufficient. This study compiled China's emission inventory of air pollutants and CO2 from 2005 to 2021 (ABaCAS-EI v2.0 dataset) based on a unified emission-source framework by considering the influences of activity level, technology evolution, and emission control policies. The characteristics of air pollutants and CO2 emissions were comprehensively analyzed from multiple dimensions such as time, space, sector, and synergies between air pollutants and CO2 emissions. Mitigation policies have decoupled the emissions of air pollutants and CO2 with economic development in China since 2013. In the context of growing activity levels, energy structure adjustment and energy and material saving reduced the average annual increase rate of CO2 emissions by 7 % after 2011. Based on this, end-of-pipe control contributed 51 %–98 % of air pollutant emission reductions after 2013. Industrial boilers and residential fossil fuel combustion sectors in seven provinces (Beijing, Tianjin, Shanghai, Jilin, Henan, Sichuan, and Qinghai) achieved emission reductions in both air pollutants and CO2 during 2013–2021. The declining trends in both the sectoral and regional emission ratios of air pollutants to CO2 indicated that the potential for synergistic emission reduction in China declined from 2013 to 2021. The emission ratios in 2021 showed that residential fossil fuel combustion, iron and steel industry, and transportation exhibited relatively higher co-benefits of SO2, PM2.5, NOx, and VOC emission reductions when CO2 emissions were reduced. Most cities with a higher potential to synergistically reduce NOx, VOC, and CO2 emissions were within the Yangtze River Economic Belt, while those with a higher potential to co-control SO2 and CO2, and PM2.5 and CO2 were in southern and northeast China, respectively. Further deconstruction of the sectoral emissions in 2021 suggested future reduction measures: for example, controlling coal consumption in the energy field; promoting innovative technologies with low air pollutant emission intensities and coal-saving measures in the iron and steel industry; combining coal and carbonate replacement technologies with separated particle control measures in the cement industry; and controlling light-duty passenger vehicles, heavy-duty trucks, agricultural machinery, and inland water transport in the transportation sector. Our dataset and findings provide insights into the co-control of air pollutants and CO2 emissions in the future in China and other countries with the same demand. Our ABaCAS-EI v2.0 dataset can be accessed from https://doi.org/10.6084/m9.figshare.21777005.v1 (S. Li et al., 2022) by species, sector, and province.

Biological wastewater treatment plants as sources of environmental pollution by persistent organic pollutants (on the example of Odesa industrial-and-urban agglomeration)

Formulation of the problem. Effective mechanism of wastewater treatment (WT) are important components of reducing anthropogenic load on the environment. One of the most widespread mechanisms of urban wastewater treatment is the biological treatment on a Biological Wastewater Treatment Plant (BWTP). However, increasing the nomenclature of pollutants concentrated in urban wastewater seriously affects the effectiveness of WT on BWTPs, which are not intended for such a wide spectrum of specific pollutants such as, in particular, Persistent Organic Pollutants (POPs). The control of their intake into the environment must be regulated according to the Stockholm convention. The goal of the research is the evaluation of the intake of polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) into the environment from the wastewater of Odesa Industrial-and-Urban Agglomeration (IUA) and determining the volumes of their accumulation in the sea environment. Purpose. The assessment of the amount of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/F) entering the environment with the wastewater from Odesa IUA and determining the amount of their accumulation in the sea environment. Methods. In our research, all available official methods of calculation of the unintentional formation of POPs were reviewed, as a result – the main and most complete methods were selected: «UNEP (2013). Toolkit for Identification and Quantification of Releases of Dioxins, Furans and Other Unintentional POPs» and «EMEP/EEA air pollutant emission inventory guidebook. Technical guidance to prepare national emission inventories, 2019». For evaluation of PCDD/F accumulation in the sea environment an improved by authors methodology for calculation of PCDD/F accumulation with their cumulative effect and half life taken into account was used. Results. The work provides justification for the necessity of use of calculation methodologies for determing the intake of PCDD/F to the sea environment adjacent to Odesa IUA; annual massed of PCDD/F entering the sea environment as part of treated, insufficiently treated and untreated wastewater are calculated; massed of PCDD/F that accumulate in waste activated sludge (WAS) on BWTP are calculated; volumes and specifics of PCDD/F accumulation in the sea basin, where the wastewater of Odesa IUA is being discharged to are determined using the improved methodology that enables taking into account the cumulative effect and half life period of these substances; mass and concentration of PCDD/F, immobilized in WAS, are determined, the excess level of concentration of PCDD/F in WAS compared to the maximum permissible concentration is determined. The total accumulation of PCDD/F in the sea environment over 2007-2017 period is determined. Conclusions. It was established that the use of calculation methodologies for evaluating PCDD/F volumes in the water environment is the only and necessary condition for satisfying the requirements of the Stockholm convention due to the impossibility of performing a regular instrumental monitoring of PCDD/F intake into the water environment. The use of suggested by us improved methodology for calculation of PCDD/F accumulation with their cumulative effect and half-life period taken into account allows for calculation of PCDD/F masses that were formed throughout the year under consideration, taking into account the PCDD/F masses that were formed during previous years as well.

Impact of introducing net-zero carbon strategies on tropospheric ozone (O3) and fine particulate matter (PM2.5) concentrations in Japanese region in 2050

In this study, we estimated the future emission inventory of primary air pollutants in Japan in 2050 after introducing low-carbon technology based on the results of the socio-economic model provided by the Japanese government. The results suggested that introducing net-zero carbon technology would contribute to a 50–60 % decrease in primary NOx, SO2, and CO emissions and a ~30 % decrease in primary emissions of volatile organic compounds (VOCs) and PM2.5. The estimated emission inventory and future meteorological conditions in 2050 were applied as inputs to a chemical transport model. A scenario involving the application of future reduction strategies with relatively moderate global warming (RCP4.5) was evaluated. The results showed that the concentration of tropospheric ozone (O3) was highly reduced compared with that in 2015 after applying net-zero carbon reduction strategies. On the other hand, the fine particulate matter (PM2.5) concentration under the 2050 scenario was expected to be equal or higher because of the growth in secondary aerosol formation caused by the increase in short-wave radiation. Finally, the premature mortality change from 2015 to 2050 was analyzed, and the change in air quality contributed by net-zero carbon technology will contribute to a ~4000 decrease in premature deaths in Japan.