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1
Račić, Nikola, Branko Lalić, Ivan Komar, Frane Vidović, and Ladislav Stazić. "Air Pollutant Emission Measurement." Pedagogika-Pedagogy 93, no. 6s (August 31, 2021): 132–40. http://dx.doi.org/10.53656/ped21-6s.11air.
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One of the main methods for estimating air pollutant emissions from ships is the method developed by Carlo Trozzi, which was later accepted and recommended by the European Environment Agency in its air pollutant emission inventory guidebooks. Consequently, it has become the most commonly used methods for making inventories of air emissions in the shipping industry and for predicting future trends. The method and its equations use emission factors to calculate the emission of air pollutants from ships. Emission factors are calculated depending on fuel consumption or main engine power; results are given for different year of manufacture and engine speed. This paper presents the measurement of air pollutant emissions and some other parameters on marine engines operating in different conditions. The measured values are calculated to obtain values which will enable the next step, the comparison with the emission factors in the latest guide of the European Environment Agency on the inventory of pollutant emissions.
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Chen, Shaobo, Jianhui Li, Qian You, Zhaotong Wang, Wanyue Shan, Xin Bo, and Rongjie Zhu. "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." Atmosphere 14, no. 12 (November 28, 2023): 1747. http://dx.doi.org/10.3390/atmos14121747.
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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.
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Xue, Yifeng, Xizi Cao, Yi Ai, Kangli Xu, and Yichen Zhang. "Primary Air Pollutants Emissions Variation Characteristics and Future Control Strategies for Transportation Sector in Beijing, China." Sustainability 12, no. 10 (May 18, 2020): 4111. http://dx.doi.org/10.3390/su12104111.
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Air pollutant emissions from vehicles, railways, and aircraft for freight and passenger transportation are major sources of air pollution, and strongly impact the air quality of Beijing, China. To better understand the variation characteristics of these emissions, we used the emission factor method to quantitatively determine the air pollutant emissions from the transportation sector. The emission intensity of different modes of transportation was estimated, and measures are proposed to prevent and control air pollutants emitted from the transportation sector. The results showed that air pollutant emissions from the transportation sector have been decreasing year by year as a result of the reduction in emissions from motor vehicles, benefiting from the structural adjustment of motor vehicles. A comparison of the emission intensity of primary air pollutants from different modes of transportation showed that the emission level of railway transportation was much lower than that of road transportation. However, Beijing relies heavily on road transportation, with road freight transportation accounting for 96% of freight transportation, whereas the proportion of railway transportation was low. Primary air pollutants from the transportation sector contributed significantly to the total emissions in Beijing. The proportion of NOX emissions increased from 54% in 2013 to 58% in 2018. To reduce air pollutant emissions from the transportation sector, further adjustments and optimization of the structure of transportation in Beijing are needed. As for the control of motor vehicle pollutant emissions, vehicle composition must be adjusted and the development of clean energy must be promoted, as well as the replacement of diesel vehicles with electric vehicles for passenger and freight transportation.
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Bao, Shuanghui, Osamu Nishiura, Shinichiro Fujimori, Ken Oshiro, and Runsen Zhang. "Identification of Key Factors to Reduce Transport-Related Air Pollutants and CO2 Emissions in Asia." Sustainability 12, no. 18 (September 16, 2020): 7621. http://dx.doi.org/10.3390/su12187621.
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Asian countries are major contributors to global air pollution and greenhouse gas emissions, with transportation demand and emissions expected to increase. However, few studies have been performed to evaluate policies that could reduce transport-related emissions in the region. This study explores transport-related CO2 and air pollutant emissions in major Asian nations along with the impacts of transport, climate, and emission control policies using the Asia-Pacific Integrated Model (AIM)/Transport model. Our results show that by 2050, CO2 emissions in developing countries will be 1.4–4.7-fold greater than the levels in 2005, while most air pollutant emissions will show large reductions (mean annual reduction rates of 0.2% to 6.1%). Notably, implementation of transport, emission control, and carbon pricing policies would reduce CO2 emissions by up to 33% and other air pollutants by 43% to 72%, depending on the emission species. An emission control policy represents the strongest approach for short-term and mid-term reduction of air pollutants. A carbon pricing policy would lead to a direct reduction in CO2 emissions; more importantly, air pollutant emissions would also be effectively reduced. Shifting to public transportation in developing countries can also greatly influence emissions reductions. An increase in traffic speed shows relatively small effects, but can be meaningful in Japan.
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Wang, Bing, Yifan Wang, and Yuqing Zhao. "Collaborative Governance Mechanism of Climate Change and Air Pollution: Evidence from China." Sustainability 13, no. 12 (June 15, 2021): 6785. http://dx.doi.org/10.3390/su13126785.
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Since entering the industrialized era, China’s greenhouse gas emissions and air pollutant emissions have increased rapidly. China is the country with the most greenhouse gas emissions, and it is also facing serious local air pollution problems. China’s industrial sector is the largest contributor to CO2 and air pollutants. The resulting climate change and air pollution issues have caused China to face double pressures. This article uses the CO2 and comprehensive air pollutant emission data of China’s industrial sector as a starting point and uses econometric research methods to explore the synergy between China’s industrial carbon emission reduction and industrial comprehensive air pollutant emission reduction. The synergistic effect between industrial carbon emissions and industrial comprehensive air pollutant emissions has been quantified, and the transmission path of the synergistic effect has been explored. The empirical results show that there are benefits of synergistic governance between climate change and air pollution in China’s industrial sector. Every 1000 tons of carbon reduction in the industrial sector will result in 1 ton of comprehensive air pollutant reduction. The increase in R&D expenditure in the energy and power sector can significantly promote the reduction of air pollutants in the industrial sector. Increasing the intensity of environmental regulations is the main expansion path for synergy. However, in eastern, central, and western China, the synergy is not the same. Therefore, it is necessary to formulate regionally differentiated emission reduction policies. The research conclusions of this article can provide policy references for the coordinated governance of climate change and air pollution in China.
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Cheng, Qianwen, Manchun Li, Feixue Li, and Haoqing Tang. "Response of Global Air Pollutant Emissions to Climate Change and Its Potential Effects on Human Life Expectancy Loss." Sustainability 11, no. 13 (July 4, 2019): 3670. http://dx.doi.org/10.3390/su11133670.
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Geographical environment and climate change are basic factors for spatial fluctuations in the global distribution of air pollutants. Against the background of global climate change, further investigation is needed on how meteorological characteristics and complex geographical environment variations can drive spatial air pollution variations. This study analyzed the response of air pollutant emissions to climate change and the potential effects of air pollutant emissions on human health by integrating the air pollutant emission simulation model (GAINS) with 3 versions and CMIP5. The mechanism by which meteorological characteristics and geographical matrices can drive air pollution based on monitoring data at the site-scale was also examined. We found the total global emission of major air pollutants increased 1.32 times during 1970–2010. Air pollutant emissions will increase 2.89% and 4.11% in China and developed countries when the scenario of only maximum technically feasible reductions is performed (V4a) during 2020–2050. However, it will decrease 19.33% and 6.78% respectively by taking the V5a climate scenario into consideration, and precipitation variation will contribute more to such change, especially in China. Locally, the air circulation mode that is dominated by local geographical matrices and meteorological characteristics jointly affect the dilution and diffusion of air pollutants. Therefore, natural conditions, such as climate changes, meteorological characteristics and topography, play an important role in spatial air pollutant emissions and fluctuations, and must be given more attention in the processes of air pollution control policy making.
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BEBKIEWICZ, Katarzyna, Zdzisław CHŁOPEK, Jakub LASOCKI, Krystian SZCZEPAŃSKI, and Magdalena ZIMAKOWSKA-LASKOWSKA. "Characteristics of pollutant emission from motor vehicles for the purposes of the Central Emission Database in Poland." Combustion Engines 177, no. 2 (May 1, 2019): 165–71. http://dx.doi.org/10.19206/ce-2019-229.
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Within the Institute of Environmental Protection – National Research Institute the Central Emission Database is being established. The Database will cover the most important emission sectors from anthropogenic activities, including usage of motor vehicles. The intensity of emissions of individual pollutants is the input data to air pollution dispersion models. Based on calculations performed by the air pollution dispersion models concentration of pollutants dispersed in atmospheric air (pollution immission) is provided. The annual average immision for a selected place in Poland is a measure of the threat to environment. In order to determine the intensity of pollutant emissions from motor vehicles it is necessary to recognize the intensity of vehicle motion and the volume of emission of pollutants depending on the type of vehicle motion. The task presented in this article is to determine the characteristics of pollutant emissions from motor vehicles depending on the type of their motion. The mean value of vehicle speeds was used to characterize the type of vehicle motion. The emission of pollutants from vehicles is therefore characterized by the dependence of road emissions of pollutants on the average speed of vehicles. The characteristics were determined for cumulated categories of motor vehicles: passenger cars, light commercial vehicles as well as heavy duty trucks and buses. The results of the inventory of pollutant emissions from motor vehicles in Poland in 2016 were used to determine the characteristics of pollutant emissions.
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Chen, Yuyi, Yunong Li, and Jie Yan. "Tracing Air Pollutant Emissions in China: Structural Decomposition and GVC Accounting." Sustainability 11, no. 9 (May 2, 2019): 2551. http://dx.doi.org/10.3390/su11092551.
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The depth and breadth of China’s participation in global value chains have an important impact on the emissions of air pollutants from the production side, consumption side, and trade implications in China’s industries. Based on the global value chain accounting framework, this paper examines the path of China’s major air pollutant emissions in production and consumption during 1995–2009 and structurally decomposes the factors affecting air pollutant emissions. The results show that, firstly, both the air pollutant emissions on the production side and the air pollution emissions on the consumption side have increased significantly, and the production-side emissions have been higher than the consumption-side emissions. Secondly, the export of intermediate products shows a trend of “high pollution”, and this trend was more obvious after China’s accession to the world trade organization (WTO). Thirdly, the expansion of economic growth was the most important factor in the rapid emission of air pollutants in China and the reduction of pollution efficiency in Chinese industries depends on the increase in service inputs.
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Purwanto, Christine Prita. "INVENTARISASI EMISI SUMBER BERGERAK DI JALAN (ON ROAD) KOTA DENPASAR." ECOTROPHIC : Jurnal Ilmu Lingkungan (Journal of Environmental Science) 9, no. 1 (May 1, 2015): 1. http://dx.doi.org/10.24843/ejes.2015.v09.i01.p01.
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The growth of population in Denpasar City followed by increasing of transportation facilities that potentially cause pollution by vehicle emissions and cause serious environmental problems and which has adverse effect to the human health. The research aimed to estimate the number and distribution of emission gases on air pollutants, such as: PM10, NOx, SO2, CO, CO2 and HC. The calculation of estimated based on road mobile sources (On Road) in Denpasar City, includes all known sources such as the highway, small roads, terminals, and parking lots. The calculation of emissions is calculated by using the approach of emission estimation method. The total load of emissions by moving source on the street in Denpasar for each pollutant gases are: value of NOx is 3765.89 tons/year , value of SO2 is 212.34 tons/year, value of HC is 20049.87 tons/year, value of PM10 is 444.16 tons/year, value of CO2 is 984,280.21 tons/ year, and value of CO is 55432.04 tons/year. Overall, the total load of pollutant emissions gases of Denpasar City is greater than the total load of pollutant emissions gases in Palembang city. Spatially, the distribution of pollutant gas emissions are not spread evenly. The pollutants emissions of NOx, CO2, and HC for each gases have the highest values are about 115 – 239 tons/year, 26.944 – 4.735 tons/year, and 471 – 954 tons/year distributed at West Denpasar District and Niti Mandala Renon area. The highest pollutans emission of SO2 is about 15,5-44 tons/year, distributed at West Denpasar District. The highest pollutans emission of PM10 is about 11,5-21 tons/year, distributed at West Denpasar District, Badung Market area, Puputan Square area, and Niti Mandala Renon area. The highest CO pollutant emission is about 1277-1912 tons/year, distributed at West Denpasar District, Badung Market area, Puputan Square area, Niti Mandala Renon area, and Udayana University area.
10
Zhao, H. Y., Q. Zhang, D. B. Guan, S. J. Davis, Z. Liu, H. Huo, J. T. Lin, W. D. Liu, and K. B. He. "Assessment of China's virtual air pollution transport embodied in trade by using a consumption-based emission inventory." Atmospheric Chemistry and Physics 15, no. 10 (May 19, 2015): 5443–56. http://dx.doi.org/10.5194/acp-15-5443-2015.
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Abstract. Substantial anthropogenic emissions from China have resulted in serious air pollution, and this has generated considerable academic and public concern. The physical transport of air pollutants in the atmosphere has been extensively investigated; however, understanding the mechanisms how the pollutant was transferred through economic and trade activities remains a challenge. For the first time, we quantified and tracked China's air pollutant emission flows embodied in interprovincial trade, using a multiregional input–output model framework. Trade relative emissions for four key air pollutants (primary fine particle matter, sulfur dioxide, nitrogen oxides and non-methane volatile organic compounds) were assessed for 2007 in each Chinese province. We found that emissions were significantly redistributed among provinces owing to interprovincial trade. Large amounts of emissions were embodied in the imports of eastern regions from northern and central regions, and these were determined by differences in regional economic status and environmental policy. It is suggested that measures should be introduced to reduce air pollution by integrating cross-regional consumers and producers within national agreements to encourage efficiency improvement in the supply chain and optimize consumption structure internationally. The consumption-based air pollutant emission inventory developed in this work can be further used to attribute pollution to various economic activities and final demand types with the aid of air quality models.
11
Ai, Yi, Yunshan Ge, Zheng Ran, Xueyao Li, Zhibing Xu, Yangfan Chen, Xifeng Miao, et al. "Quantifying Air Pollutant Emission from Agricultural Machinery Using Surveys—A Case Study in Anhui, China." Atmosphere 12, no. 4 (March 29, 2021): 440. http://dx.doi.org/10.3390/atmos12040440.
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Diesel-powered agricultural machinery (AM) is a significant contributor to air pollutant emissions, including nitrogen oxides (NOx) and particulate matter (PM). However, the fuel consumption and pollutant emissions from AM remain poorly quantified in many countries due to a lack of accurate activity data and emissions factors. In this study, the fuel consumption and air pollutant emission from AM were estimated using a survey and emission factors from the literature. A case study was conducted using data collected in Anhui, one of the agricultural provinces of China. The annual active hours of AM in Anhui ranged 130 to 175 h. The estimated diesel fuel consumption by AM was 1.45 Tg in 2013, approximately 25% of the total diesel consumption in the province. The air pollutants emitted by AM were 57 Gg of carbon monoxide, 14 Gg of hydrocarbon, 74 Gg of NOx and 5.7 Gg of PM in 2013. The NOx and PM emissions from AM were equivalent to 17% and 22% of total on-road traffic emissions in Anhui. Among nine types of AM considered, rural vehicles are the largest contributors to fuel consumption (31%) and air emissions (33–45%).
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Ho, Bang Quoc, Huong Thi Thanh Vo, and Suwat Chuanak. "Evaluation of air pollutant emissions and Modeling of air quality in Saigon Port, Vietnam." Science and Technology Development Journal 16, no. 1 (March 31, 2013): 12–21. http://dx.doi.org/10.32508/stdj.v16i1.1383.
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Saigon Port within the port system of the Vietnam Maritime sector is one the port having highest throughput and productivity in the country. The air quality in the area around the port is polluted. The aim of this study is to calculate air pollutant emissions from ocean-going vessels (OGVs), harbour craft (HC), cargo handling equipment (CHE), road vehicles and power plant within the port. Then the air emissions results are used for modelling air quality in Saigon Port. The results of air quality modelling are used to design emissions abatement strategies. The results of air emission inventories show that total emissions of all pollutants are dominated by OGVs and harbor cranes. Emissions from OGVs are mainly during hotelling due to the long times spent at berth, while harbor cranes emissions are high because of the extended usage and high power rating. The results of air quality modeling using only air emission inventories from the port as input parameter show that concentration of air pollutants is lower than the Vietnamese technical regulation on ambient air quality. Only air emissions from Saigon port don’t pollute the air surrounding area but if combined with other sources of emissions cause air pollution to the surrounding area.
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Tong, Liang, Chunyu Zhang, Zhongbo Peng, and Lumeng Wang. "Spatial–Temporal Distribution Characteristics and Correlation Analysis of Air Pollutants from Ships in Inland Ports." Sustainability 14, no. 21 (October 31, 2022): 14214. http://dx.doi.org/10.3390/su142114214.
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The ship air pollution problem has become a global issue and poses a threat to the environment as well as the health of residents in the port area. This study used Automatic Identification System (AIS) data combined with a list of air pollutant emissions from ships. The total amount of air pollutant emissions was obtained. The spatial and temporal distribution characteristics of air pollutants on ships were analyzed, and the correlation of pollutant concentrations was studied on the three major ports. The three main intensive ports are Cuntan Port, Guoyuan Port, and Luoqi Port, and the Pearson correlation analysis is conducted based on the Statistical Product and Service Solutions (SPSS). The results showed that: (1) The air pollutant emissions from ships in China Chongqing port region during September to December 2021 were mainly dominated by CO2 and NOX. (2) The air pollutant emissions from ships in the Yangtze River Basin were highest in October 2021 and lowest in December. (3) The correlation between PM2.5 and CO2 showed the largest in Cuntan Port and Luoqi Port, and the correlation between CO and CO2 is the largest in Guoyuan Port. It is suggested to establish deceleration zones and emission control zones in Cuntan Port and Guoyuan Port, and to use shore power for berthing in Luoqi Port. We also suggest improving fuel quality and combustion quality, post-treating ship exhaust emissions, increasing port shore power facilities to reduce ship air pollutant emissions, and providing a reference for environmental protection in inland ports.
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Chan, Yatfei, Haoyue Tang, Xiao Li, Weichun Ma, and Weiqi Tang. "Analysis of the Synergies of Cutting Air Pollutants and Greenhouse Gas Emissions in an Integrated Iron and Steel Enterprise in China." Sustainability 15, no. 17 (September 4, 2023): 13231. http://dx.doi.org/10.3390/su151713231.
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The iron and steel industry in China is characterized by high energy consumption, high air pollutant emissions and high greenhouse gas (GHG) emissions, and it is imperative to reduce air pollutants and control GHG emissions in the present and future. Quantifying the synergistic effects of air pollutants and GHG emissions reduction in the ISI is helpful for controlling the emissions of both jointly. Taking a typical integrated iron and steel works as a case study, the synergistic effect between the environmental impacts (EIs) of air pollutants and GHGs under different scenarios was quantified through a life cycle assessment (LCA). The total environmental impact of the business-as-usual scenario, ultra-low emissions scenario, carbon peak scenario and comprehensive emission reduction scenario were 1.629 × 10−10, 1.670 × 10−10, 1.322 × 10−10 and 1.341 × 10−10, respectively. Based on the analysis of synergistic effects, the comprehensive emission reduction scenario combined the other two to better coordinate the emissions of air pollutants and greenhouse gases.
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Voznyak, Orest, Yuriy Yurkevych, Oleksandr Dovbush, Olena Savchenko, and Mariana Kasynets. "MONITORING THE STATE OF THE AIR ENVIRONMENT IN THE LVIV REGION." Theory and Building Practice 2022, no. 1 (June 20, 2022): 49–56. http://dx.doi.org/10.23939/jtbp2022.01.049.
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The article presents the results of monitoring the state of the air environment of Lviv region in 2020. The main sources of pollution are identified and statistical data on emissions of pollutants into the atmosphere are given. The aim of the work is to analyze the state of the environment, natural resources of Lviv region, trends in their changes and environmental measures. Volumes of pollutant emissions from stationary sources of air pollution from enterprises, institutions and organizations of Lviv region were determined by conducting an inventory of stationary sources of pollutant emissions into the air, types and volumes of pollutant emissions into the atmosphere by stationary sources, equipment facilities of the region.
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Han, Gyu-Gang, Jun-Hyuk Jeon, Yong-Jin Cho, Myoung-Ho Kim, and Seong-Min Kim. "Analysis of Air Pollutant Emissions for Mechanized Rice Cultivation in Korea." Agriculture 11, no. 12 (December 1, 2021): 1208. http://dx.doi.org/10.3390/agriculture11121208.
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In Korea, rice is a major staple grain and it is mainly cultivated using various types of agricultural machinery. Air pollutants emitted from agricultural machinery have their origins mainly from the exhaustion of internal combustion engines. In this study, the emission characteristics of five main air pollutants by the European Environment Agency’s Tier 1 method for rice cultivation were analyzed. Diesel is a main fuel for agricultural machinery and gasoline is generally used only for rice transplanters as a fuel in Korea. Tractors consume 46% of total fuel consumption and 56% of diesel fuel consumption. Gasoline used for rice transplanters accounts for about 17% of the total fuel consumption each year. Tractors and rice transplanters emit 82% of all total pollutants. From 2011 to 2019, the total amount of air pollutant emissions decreased by 15%. That accounted for the reduction of rice cultivation fields in those periods. Rice transplanting operation accounts for 42% of total emissions. Then, harrowing, harvesting, tilling, leveling, and pest control operations generated 10%, 10%, 8%, 8%, and 7% of total emissions, respectively. The contribution of each air pollutant held 54% of CO, 39% of NOx, 5% of NMVOC, and 2% of TSP from the total emission inventory. The three major regions emitting air pollutants from mechanized agricultural practices were Jeollanam-do, Chungcheongnam-do, and Jeollabuk-do, which consume 55% of the total fuel usage in rice farming. The total amount of air pollutant emissions from rice cultivation practices in 2019 was calculated as 8448 tons in Korea.
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Zhukorskyi, O., O. Nykyforuk, and N. Boltik. "Emission assessment of endogenous pollutants of the air from milk production farms." Agroecological journal, no. 2 (May 21, 2015): 21–25. http://dx.doi.org/10.33730/2077-4893.2.2015.271430.
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The hazardous influence of the dairy farm activities on the air has been analyzed. There have been calculated the odor pollutant emissions into the atmosphere from the dairy farms based on various technologies of the cows maintenance, their number and productivity. The approximate mass of these pollutant emissions and maintenance wastes have been defined by the calculating method. For these calculations there has been used the index of the quantity of the specific pollutant emissions into the atmosphere from 1 CWT of live weight with balanced feeding. The quantities of the specific emissions include the absorbtion of carbonyl compounds, carboxylic acids and amines, mercaptans and hydrogen sulfide and mercaptans transformation in dimethyl sulfide by the intestine microflora. The causes of odor pollutant creation have been analyzed. The largest contribution to the emission of pollutants from both animals and from their metabolic products is given by ammonia – 83%, the lowest by metantyol – 0.01%. It has been determined in the experiment that the pollutant emissions increase with the growth of the cows’ live weight, and they decrease with the growth of milk productivity per 1 kg of the produced milk.
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Zhang, Zhenhua, Guoxing Zhang, Shunfeng Song, and Bin Su. "Spatial Heterogeneity Influences of Environmental Control and Informal Regulation on Air Pollutant Emissions in China." International Journal of Environmental Research and Public Health 17, no. 13 (July 6, 2020): 4857. http://dx.doi.org/10.3390/ijerph17134857.
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High air pollutant emissions in China have become serious environmental issues threatening public health. While spatial heterogeneity plays an important role in environmental regulation in China, it is necessary to analyze the spatial heterogeneity influences of air pollution control policies and informal environmental regulation on air pollutant emissions in China. Based on the quantification of air pollution control policies, this paper incorporates the central government’s policy formulation and local government’s policy implementation into the intensity of air pollution control policy. This paper uses the panel data of China’s 30 provinces to examine the spatial impact of air pollution control policy and informal environmental regulation on air pollutant emissions. The results show that (a) air pollutant emissions represented by soot and dust emission intensity has a significant positive spatial spillover effect; (b) air pollution control policy and informal environmental regulation play significant inhibitory roles in air pollutant emissions; (c) informal environmental regulation has a negative moderating effect on the negative relationship between air pollution control policy and air pollutant emissions. Other implications for environmental management have also been discussed.
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Li, Shengyue, Shuxiao Wang, Qingru Wu, Yanning Zhang, Daiwei Ouyang, Haotian Zheng, Licong Han, et al. "Emission trends of air pollutants and CO2 in China from 2005 to 2021." Earth System Science Data 15, no. 6 (June 6, 2023): 2279–94. http://dx.doi.org/10.5194/essd-15-2279-2023.
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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.
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Liu, Siyang, Yongjie Nie, Bo Li, Mengyao Zhu, Zhengxing Li, Ting Li, Min Cao, et al. "Research on Power IoT System Based City Block Air Pollutant Emission Prediction." E3S Web of Conferences 406 (2023): 03020. http://dx.doi.org/10.1051/e3sconf/202340603020.
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In order to constantly improve city environmental air quality, it is necessary to accurately control the major pollutants emissions such as air fine particulate matter. By adopting the proposed iterative update framework of air pollutant emission inventory, combined with block-level real-time electricity consumption data acquired by the smart city power IoT, and utilizing station-level and hourly environmental air quality monitoring data in specific areas of Yuxi and Dali in Yunnan Province from 2020 to 2021, the iterative update of emission inventory and prediction of air pollutant emission are studied. The experimental results shows that the prediction of the monthly average major air pollutants emissions such as NO2/PM10/PM2.5 in specific neighbourhoods of the two cities mentioned above reaches the same accuracy level as using numerical simulation prediction methods, but the prediction computational power requirements are greatly reduced, making it more suitable for the application requirements of the power IoT. This study provides a new idea for improving the regulatory capacity of intelligent environment and achieving higher urban air quality based on the smart city power IoT.
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Tsai, Jiun-Horng, Shih-Hsien Chen, Shen-Fong Chen, and Hung-Lung Chiang. "Air Pollutant Emission Abatement of the Fossil-Fuel Power Plants by Multiple Control Strategies in Taiwan." Energies 14, no. 18 (September 10, 2021): 5716. http://dx.doi.org/10.3390/en14185716.
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This study is an investigation of air pollutant emission abatement in the electricity generation sector from fossil-fuel power plants in Taiwan in 2014 and 2018. PM concentrations are determined by the results of regular tests, while SOx and NOx are determined by continuous emission monitoring systems (CEMS) of flue gas from power plants. The results indicate that electricity generation from fossil-fuel power plants increased by 13.8% from 2014 to 2018. However, emissions of air pollutants from fossil-fuel power plants declined during this period. The results indicate that the annual emissions of SOx, NOx, and PM were 40,826, 59,196, and 5363 tons per year (TPY), respectively, in 2014. The emissions decreased to 30,097 TPY (28% reduction) for SOx, 48,530 TPY (18% reduction) for NOx, and 4496 TPY (16% reduction) for PM in 2018. The ensemble mean values of each air pollutant emission factor also decreased significantly. SOx emissions decreased from 0.2443 to 0.1583 mg/kWh (35% reduction). NOx emissions decreased from 0.3542 to 0.2552 g/kWh (28% reduction). PM emissions decreased from 0.0321 to 0.0236 mg/kWh (26.5% reduction). The results indicated that phasing out of high-pollutant generating units and switching the fuel from coal to natural gas could abate the emissions of SOx and PM, and NOx emissions could be abated by introducing control devices. In addition, new power generation sectors will be constructed and equipped with ultra-low emission control systems to reduce air pollution and create a cleaner and healthier electricity generation system in Taiwan.
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Ramani, Tara, Rohit Jaikumar, Haneen Khreis, Mathieu Rouleau, and Nick Charman. "Air Quality and Health Impacts of Freight Modal Shifts: Review and Assessment." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 3 (March 2019): 153–64. http://dx.doi.org/10.1177/0361198119834008.
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Freight movement is a significant and growing contributor to transportation emissions globally. Modal shifts in freight, that is, moving freight from a higher emission mode to one associated with lower emissions, are discussed as a strategy to reduce emissions of criteria pollutants and greenhouse gases (GHGs). However, there is limited knowledge of the magnitude of potential benefits and their impacts on human health. The overall goal of this study is to identify and characterize the potential of modal shifts in freight transport for mitigating air pollutant emissions, air pollutant concentrations, population exposure to air pollutants, and health impacts. The analysis was conducted in the Canadian context, with a focus on land-based freight such as trucks, trains, and pipelines, as well as marine shipping for inland and coastal waters. A structured review of the existing literature database, and a critical assessment of the findings was conducted, using a weight-of-evidence approach. The assessment took into consideration potential local and regional variables for Canada. The results indicated that there is limited evidence that road-to-rail, road-to-marine, and rail-to-marine modal shifts could reduce pollutant and GHG emissions. There was insufficient evidence on modal shifts involving the pipeline mode, and on the air quality, population exposure, and health impacts related to any modal shift. Several research gaps remain, which must be addressed establish the emissions, air quality, and health impacts of freight modal shifts.
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Liu, Jun, Dan Tong, Yixuan Zheng, Jing Cheng, Xinying Qin, Qinren Shi, Liu Yan, Yu Lei, and Qiang Zhang. "Carbon and air pollutant emissions from China's cement industry 1990–2015: trends, evolution of technologies, and drivers." Atmospheric Chemistry and Physics 21, no. 3 (February 8, 2021): 1627–47. http://dx.doi.org/10.5194/acp-21-1627-2021.
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Abstract. China is the largest cement producer and consumer in the world. Cement manufacturing is highly energy-intensive and is one of the major contributors to carbon dioxide (CO2) and air pollutant emissions, which threatens climate mitigation and air quality improvement. In this study, we investigated the decadal changes in carbon dioxide and air pollutant emissions for the period of 1990–2015 based on intensive unit-based information on activity rates, production capacity, operation status, and control technologies which improved the accuracy of the cement emissions in China. We found that, from 1990 to 2015, accompanied by a 10.3-fold increase in cement production, CO2, SO2, and NOx emissions from China's cement industry increased by 627 %, 56 %, and 659 %, whereas CO, PM2.5, and PM10 emissions decreased by 9 %, 63 %, and 59 %, respectively. In the 1990s, driven by the rapid growth of cement production, CO2 and air pollutant emissions increased constantly. Then, the technological innovation in production of replacing traditional shaft kilns with the new precalciner kilns equipped with high-efficiency control facilities in the 2000s markedly reduced SO2, CO, and PM emissions in the cement industry. In 2010, nationwide, 39 % and 31 % of the nationwide PM2.5 and NOx emission were produced by 3 % and 15 % of the total capacity of the production lines, indicating the disproportionately high emissions from a small number of the super-polluting units. Since 2010, the growing trend of emissions has been further curbed by a combination of measures, including promoting large-scale precalciner production lines and phasing out small ones, upgrading emission standards, installing low NOx burners (LNB), and selective non-catalytic reduction (SNCR) to reduce NOx emissions, as well as adopting more advanced particulate matter control technologies. Our study highlights the effectiveness of advanced technologies on air pollutant emission control; however, CO2 emissions from China's cement industry kept growing throughout the period, posing challenges to future carbon emission mitigation in China.
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Wang, Minghao. "A Review of Engine Emissions Testing Methods for Environmental Sustainability." Trends in Renewable Energy 8, no. 2 (2022): 96–106. http://dx.doi.org/10.17737/tre.2022.8.2.00141.
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With the increase of vehicle ownership, vehicle emission pollution has become a major source of air pollution. The control of automobile pollutant emissions is one of the effective methods to reduce air pollution. Domestic and foreign exhaust pollutant testing methods for in-use vehicles have been gradually developed from the original idling method to the double-idling method and the simple working condition method. There are many methods to test the exhaust pollutants of in-use vehicles, but the test operation cycle, gas analysis principle, cost, application occasions and the accuracy level of various testing methods are different. This paper introduces the idling method, the working condition method and the on-board emission testing method for detecting vehicle emission pollutants. Two optimized methods for detecting automotive emission pollutants (namely the double-idle method and the simple transient working condition method) are also introduced.
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Zhang, Ziyue, Wenyu Yang, Shucai Zhang, and Long Chen. "Impacts of Pollutant Emissions from Typical Petrochemical Enterprises on Air Quality in the North China Plain." Atmosphere 14, no. 3 (March 13, 2023): 545. http://dx.doi.org/10.3390/atmos14030545.
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Under the state’s key surveillance, petrochemical industries are considered polluting enterprises. Even though large-scale petrochemical enterprises follow the complete treatment of combustion waste gas, process waste gas, and volatile organic waste gas pollutants, the impact of pollutant emissions on the regional air quality is unclear. This study used the atmospheric chemical transport model and adopted the subtraction method to simulate the impacts of air pollutant emissions from four typical petrochemical enterprises on regional air quality of the North China Plain. Results indicated that emissions from petrochemical enterprises on surface PM2.5, SO2, and NO2 concentrations mainly contributed to the nearby area, particularly SO2 and NO2. The pollution can be controlled within the boundaries of the petrochemical plants. Petrochemical enterprises had a small SO2 and NO2 contribution with a maximum of up to 4.65% within a 9 km distance. Emissions from petrochemical enterprises contributed less to surface PM2.5 concentrations (less than 0.5%) within a 9 km distance. Surface O3 concentrations driven by petrochemical enterprises did not show near-source distribution characteristics, which were closely related to its complex precursors and secondary reactions. Contributions of petrochemical enterprises to local pollution decreased significantly with the increase in distance. The SO2 and NO2 pollution contributions to the North China Plain remained around 0.1–0.2%, with the maximum contribution occurring in January and July. The maximum contribution of PM2.5 in this region was in April (0.42%) while it was below 0.1% for other months. The pollutant emission from the four typical petrochemical enterprises in the North China Plain had little impact on the concentration of air pollutants in the North China Plain. However, it had a significant impact on the ambient air quality in the region near the enterprise. This study can be useful in analyzing and refining the influence of enterprises on the region.
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Zheng, Chunyan, Ruiyuan Liu, Shuai Zhang, Jiaojiao Li, Pengcheng Ma, Dong Guo, Ronghan Yao, Cong Guo, Jianlong Li, and Yongjia Sui. "Study of Mobile Source Pollutants Based on Multi-Source Data Fusion: A Case Study of Zibo City, China." Sustainability 15, no. 11 (May 23, 2023): 8481. http://dx.doi.org/10.3390/su15118481.
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The primary pollutants emitted from mobile sources have become one of the main sources of urban air pollution. In this study, the primary pollutants CO, HC, NOx and PM from mobile sources in Zibo city, China are studied. Firstly, the localized mobile-source pollutant emission factors are corrected using vehicle emission experiments; secondly, multi-source data fusion is performed using road network data, road traffic data, air quality and meteorological data; then, the corrected pollutant emission factors and multi-source data are used to construct a localized emission measurement model and dispersion simulation model, visualize the emission distribution and propose residual concentration correction to accurately obtain the pollutant sharing rate. The results show that the pollutant emission trends are highly coupled with the distribution of urban residents’ working hours. Based on the localized dispersion model used to analyze the pollutant traceability at air monitoring stations, the emission sharing rate of NOx is the largest, and according to the analysis of the changing trend of mobile-source emission sharing rate, the mobile source pollutants in Zibo are mainly influenced by pollutant emissions from road motor vehicles. This study provides data support and a theoretical basis for the management of the transportation industry to carry out exhaust gas control of motor vehicles and non-road mobile machinery and to make decisions related to improving the air environment (delineating the scope of low emission zones).
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Zhao, H. Y., Q. Zhang, S. J. Davis, D. Guan, Z. Liu, H. Huo, J. T. Lin, W. D. Liu, and K. B. He. "Assessment of China's virtual air pollution transport embodied in trade by a consumption-based emission inventory." Atmospheric Chemistry and Physics Discussions 14, no. 18 (October 9, 2014): 25617–50. http://dx.doi.org/10.5194/acpd-14-25617-2014.
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Abstract. High anthropogenic emissions from China have resulted in serious air pollution, and it has attracted considerable academic and public concern. The physical transport of air pollutants in the atmosphere has been extensively investigated, however, understanding the mechanisms how the pollutants were transferred through economic and trade activities remains challenge. In this work, we assessed China's virtual air pollutant transport embodied in trade, by using consumption-based accounting approach. We first constructed a consumption-based emission inventory for China's four key air pollutants (primary PM2.5, sulfur dioxide (SO2), nitrogen oxides (NOx) and non-methane volatile organic compounds (NMVOC)) in 2007, based on the bottom-up sectoral emission inventory concerning their production activities – a production-based inventory. We used a multiregional input-output (MRIO) model to integrate the sectoral production-based emissions and the associated economic and trade activities, and finally obtained consumption-based inventory. Unlike the production-based inventory, the consumption-based inventory tracked emissions throughout the supply chain related to the consumption of goods and services and hereby identified the emission flows followed the supply chains. From consumption-based perspective, emissions were significantly redistributed among provinces due to interprovincial trade. Large amount of emissions were embodied in the net imports of east regions from northern and central regions; these were determined by differences in the regional economic status and environmental policies. We also calculated the emissions embodied in exported and imported goods and services. It is found that 15–23% of China's pollutant emissions were related to exports for foreign consumption; that proportion was much higher for central and export-oriented coastal regions. It is suggested that measures should be introduced to reduce air pollution by integrating cross-regional consumers and producers in national agreements to encourage efficiency improvement in the supply chain and optimizing consumption structure internationally. The consumption-based air pollutants emission inventory developed in this work can be further used to attribute pollution to different economic activities and final demand types with the aid of air quality models.
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Wang, J. M., C. H. Jeong, N. Zimmerman, R. M. Healy, D. K. Wang, F. Ke, and G. J. Evans. "Plume-based analysis of vehicle fleet air pollutant emissions and the contribution from high emitters." Atmospheric Measurement Techniques 8, no. 8 (August 13, 2015): 3263–75. http://dx.doi.org/10.5194/amt-8-3263-2015.
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Abstract. An automated identification and integration method has been developed for in-use vehicle emissions under real-world conditions. This technique was applied to high-time-resolution air pollutant measurements of in-use vehicle emissions performed under real-world conditions at a near-road monitoring station in Toronto, Canada, during four seasons, through month-long campaigns in 2013–2014. Based on carbon dioxide measurements, over 100 000 vehicle-related plumes were automatically identified and fuel-based emission factors for nitrogen oxides; carbon monoxide; particle number; black carbon; benzene, toluene, ethylbenzene, and xylenes (BTEX); and methanol were determined for each plume. Thus the automated identification enabled the measurement of an unprecedented number of plumes and pollutants over an extended duration. Emission factors for volatile organic compounds were also measured roadside for the first time using a proton transfer reaction time-of-flight mass spectrometer; this instrument provided the time resolution required for the plume capture technique. Mean emission factors were characteristic of the light-duty gasoline-dominated vehicle fleet present at the measurement site, with mean black carbon and particle number emission factors of 35 mg kg fuel−1 and 7.5 × 1014 # kg fuel−1, respectively. The use of the plume-by-plume analysis enabled isolation of vehicle emissions, and the elucidation of co-emitted pollutants from similar vehicle types, variability of emissions across the fleet, and the relative contribution from heavy emitters. It was found that a small proportion of the fleet (< 25 %) contributed significantly to total fleet emissions: 100, 100, 81, and 77 % for black carbon, carbon monoxide, BTEX, and particle number, respectively. Emission factors of a single pollutant may help classify a vehicle as a high emitter; however, regulatory strategies to more efficiently target multi-pollutant mixtures may be better developed by considering the co-emitted pollutants as well.
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Yatsenko, Y. "THE INFLUENCE OF MILITARY ACTIONS ON ATMOSPHERIC AIR QUALITY IN UKRAINE." Bulletin of Taras Shevchenko National University of Kyiv. Geography, no. 82-83 (2022): 84–88. http://dx.doi.org/10.17721/1728-2721.2022.82.12.
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During the research of the assessment of the consequences of military actions on atmospheric air quality, general scientific research methods were used: methods of analysis and synthesis, which involve the collection, analysis and generalization of information. Information on the assessment of the consequences of military actions on atmospheric air quality in Ukraine and the world was collected, analyzed, structured and summarized. The main sources of emissions of pollutants during military operations were analyzed and identified. It was established that they can be divided into three groups: 1) emissions of pollutants as a result of explosions and shelling of industrial facilities; 2) emissions of pollutants due to fires in ecosystems; 3) emissions due to the burning of fuel by military transport. A number of pollutants entering the atmospheric air from the specified sources have been identified. All pollutants are divided into three groups. The first group is the main pollutants (PM2.5, PM10, O3, SO2, CO, NOx, heavy metals, etc.). The second group is specific pollutants (a huge variety of them is introduced). The third group is greenhouse gases (CO2, CH4, N2O). It has been determined that pollutant emissions based on the required input information on fuel mass or burning area can be estimated using emission factors used in EPA, EMEP, etc. reports. In the absence of emission factors, pollutant emissions can be specified taking into account the technical requirements of atmospheric transfer models. As a result of constant bombings, artillery fire, fires and accidents that occur, the movement of heavy military transport, there is a significant emission of pollutants into the atmosphere. It has a very negative effect on its quality. Knowing the causes and sources of pollution, as well as pollutants entering the air as a result of military actions, is extremely important and relevant. After all, this will directly help to assess the consequences of such an impact on the life and health of the population and can become indisputable evidence for the state when deciding the issue of reparations.
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Dragomir Balanica, Carmelia Mariana, Ciprian Cuzmin, Cecilia Serban, and Cristian Muntenita. "The impact of road transport emissions on air quality in Brăila, Romania." Present Environment and Sustainable Development 15, no. 2 (October 3, 2021): 5–14. http://dx.doi.org/10.15551/pesd2021152001.
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Road transport, including accessibility and individual mobility is considered unanimously as a fundamental element of contemporary living. The study area is considering Braila County with a total population of around over 305,000. The area it is well served by 6 national roads, 27 county roads and 42 communal roads and contains some of the most heavily trafficked stretches of road in the Romania. The emissions analysed in this study CH4, CO, CO2, N2O, NH3, NOx, PM2.5 and PM10, were collected by the Agency for Environmental Protection Braila during 2015-2019 based on questionnaires according to EMEP/EEA air pollutant emission inventory guidebook. The highest level of pollutant emissions was recorded in 2017, more exactly 191714,5 Megatons. In this article we analysed five categories of pollution sources: Passenger car, Light commercial trucks, Heavy-duty vehicles, Motorcycles and Non - Road vehicles and other mobile equipment. With the exception of CO2, N2O and NH3, pollutant emissions decreased for the eight pollutants analysed.
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Al-Mutairi, Motirh, Nahaa Al-Otaibi, Amgad Saber, Heshmat Abdel Basset, and Mostafa Morsy. "Climatological Study of Air Pollutant Emissions in Saudi Arabia." Atmosphere 14, no. 4 (April 18, 2023): 729. http://dx.doi.org/10.3390/atmos14040729.
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This study aims to investigate the spatio-temporal distribution, variation, abrupt change, and long-term trends of major pollutant emissions in the Kingdom of Saudi Arabia (KSA) over the period 1960–2020 using the Monitoring Atmospheric Composition and Climate (MACC)/CityZEN EU projects (MACCity) emissions dataset inventory. These pollutants are carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), volatile organic compounds (VOCs), black carbon (BC), and organic carbon (OC). Seven stations were selected (Al-Bahah, Abha, Dahra, Jeddah, Riyadh, Qassim, and Ahsa), which correspond to the highest (hotspot) annual pollutant emissions. The annual cycle analysis of the six pollutant emissions revealed that there are four distinct patterns; the first one has one interannual wave while the other three patterns have two interannual waves. The analysis of the different sectors’ contributions to pollutant emissions revealed that the energy, transportation, and industries sectors have the highest percentage contributions. Significant abrupt change points were detected in 1970, 1980, 1990, 2000, 2005, and 2010. The development and growth rates in the KSA starting from the early 1970s are attributed to the oil boom. The great increase in pollutant emissions in the early 1980s followed by that in the 1990s up to 2000 is due to an increase in fossil fuel demand, industries, transportation, and energy consumption.
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LU, Guangliang, Ziyan LIU, Zheyu YIN, and Jiancheng WANG. "Review of the Eco-Environmental Protection Progress in China by the National Pollution Source Census Data Analysis." Progress in Chinese Eco-Environmental Protection 1, no. 4 (December 28, 2023): 36–48. http://dx.doi.org/10.48014/pcep.20230918003.
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Based on the results of the first national pollutant source census in 2007 (hereinafter referred to as the first pollutant census) and the second national pollutant source census in 2017 (hereinafter referred to as the second pollutant census) , this paper analyzes the current situation of various pollutants in the past ten years. The differences in the contents of the two censuses, and the comparison of the data from the two censuses, show that China’s ecological and environmental protection work has made positive progress, in which China's ability to comprehensively manage water pollution has been greatly improved, the discharge of water pollutants from industrial sources has been significantly improved, the control effect of atmospheric pollutants has been remarkable, and various environmental indicators have been optimized in a comprehensive manner. However, there are still challenges in environmental protection: the national water pollutant emissions are still huge, of which the contribution of agricultural sources and living sources of water pollutant emissions increased, living sources have become the focus of water pollutant emissions control; the national air pollutant prevention and control potential is huge, industrial sources are still an important source of air pollutant emissions in the country, and mobile sources have become a key focus of air pollution control. At the same time, the changes in the direction of air pollutant control under the background of “carbon peak carbon neutral” are summarized; The disposal and utilization efficiency of solid waste still needs to be strengthened, and the cumulative storage of industrial hazardous waste has increased dramatically. In conclusion, China’s overall pollution prevention and control has made great achievements, and the future ecological environment work has a long way to go. The overall pollution management needs to be based on the "two pollution census", and the precise application of policy.
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Kurokawa, Junichi, and Toshimasa Ohara. "Long-term historical trends in air pollutant emissions in Asia: Regional Emission inventory in ASia (REAS) version 3." Atmospheric Chemistry and Physics 20, no. 21 (November 4, 2020): 12761–93. http://dx.doi.org/10.5194/acp-20-12761-2020.
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Abstract. A long-term historical emission inventory of air and climate pollutants in East, Southeast, and South Asia during 1950–2015 was developed as the Regional Emission inventory in ASia version 3 (REASv3). REASv3 provides details of emissions from major anthropogenic sources for each country and its sub-regions and also provides monthly gridded data with 0.25∘ × 0.25∘ resolution. The average total emissions in Asia during 1950–1955 and during 2010–2015 (growth rates in these 60 years estimated from the two averages) are as follows: SO2: 3.2 Tg, 42.4 Tg (13.1); NOx: 1.6 Tg, 47.3 Tg (29.1); CO: 56.1 Tg, 303 Tg (5.4); non-methane volatile organic compounds: 7.0 Tg, 57.8 Tg (8.3); NH3: 8.0 Tg, 31.3 Tg (3.9); CO2: 1.1 Pg, 18.6 Pg (16.5) (CO2 excluding biofuel combustion 0.3 Pg, 16.8 Pg (48.6)); PM10: 5.9 Tg, 30.2 Tg (5.1); PM2.5: 4.6 Tg, 21.3 Tg (4.6); black carbon: 0.69 Tg, 3.2 Tg (4.7); and organic carbon: 2.5 Tg, 6.6 Tg (2.7). Clearly, all the air pollutant emissions in Asia increased significantly during these 6 decades, but situations were different among countries and regions. Due to China's rapid economic growth in recent years, its relative contribution to emissions in Asia has been the largest. However, most pollutant species reached their peaks by 2015, and the growth rates of other species were found to be reduced or almost zero. On the other hand, air pollutant emissions from India showed an almost continuous increasing trend. As a result, the relative ratio of emissions of India to that of Asia has increased recently. The trend observed in Japan was different from the rest of Asia. In Japan, emissions increased rapidly during the 1950s–1970s, which reflected the economic situation of the period; however, most emissions decreased from their peak values, which were approximately 40 years ago, due to the introduction of control measures for air pollution. Similar features were found in the Republic of Korea and Taiwan. In the case of other Asian countries, air pollutant emissions generally showed an increase along with economic growth and motorization. Trends and spatial distribution of air pollutants in Asia are becoming complicated. Data sets of REASv3, including table of emissions by countries and sub-regions for major sectors and fuel types, and monthly gridded data with 0.25∘ × 0.25∘ resolution for major source categories are available through the following URL: https://www.nies.go.jp/REAS/index.html (last access: 31 October 2020).
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Büke, T., and A. Ç. Köne. "External cost of pollutant emissions in Turkey." IOP Conference Series: Earth and Environmental Science 1123, no. 1 (December 1, 2022): 012066. http://dx.doi.org/10.1088/1755-1315/1123/1/012066.
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Abstract External costs that occur in the use of energy resources are one of the most important criteria in determining energy and environmental policies. For this purpose, it is important to know the external costs of any energy sources. The purpose of this study is to calculate external costs due to air pollutants in Turkey for the years 2000 and 2019. The air pollutants namely ammonia, nonmethane volatile organic compounds, nitrogen oxides, particulate matter, and sulphur dioxide have been taken into consideration in the evaluation for the impact categories-human health damage, loss of biodiversity, crop losses, and buildings damaged. These pollutant emissions data were obtained from the European Environmental Agency database. Then, these pollutant emissions data were used in the monetization calculations for the years 2000 and 2019. According to the evaluation, air pollutant emissions’ total external costs in Turkey were 25135,72 Million Euros and 24654,42 Million Euros for the years 2000 and 2019 respectively.
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Wayson, Roger L., and William Bowlby. "Inventorying Airport Air Pollutant Emissions." Journal of Transportation Engineering 114, no. 1 (January 1988): 1–20. http://dx.doi.org/10.1061/(asce)0733-947x(1988)114:1(1).
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Yu, Yue, Zhi-xin Jin, Ji-zu Li, Yu-cheng Wu, and Li Jia. "An Air Pollutant Emission Reduction Path of China’s Power Industry." Atmosphere 11, no. 8 (August 12, 2020): 852. http://dx.doi.org/10.3390/atmos11080852.
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In China, as the major source of energy consumption and air pollutant emissions, the power industry is not only the principal force that bears the responsibility of national emission reduction targets but also a breakthrough that reflects the effectiveness of emission reduction. In this study, based on the integrated MARKAL-EFOM system (TIMES) model and scenario analysis method, a bottom-up energy system optimization model for the power industry was established, and four scenarios with different constraints were set up to predict and analyze the power demand and the energy consumption structure. Emission characteristics, emission reduction characteristics, and emission reduction cost of sulfur dioxide (SO2), nitrogen oxide (NOX), particulate matter 2.5 (PM2.5), and mercury (Hg) were quantitatively studied. Finally, for the environmentally friendly development and optimal adjustment of power production systems in China, the control path in the power industry that is conducive to the emission reduction of air pollutants was obtained, which is of great significance for the ultimate realization of climate friendliness. The results demonstrate that from 2020 to 2050, the power demand of the terminal departments will increase, with the composition significantly changed. The focus of power demand will change from industry to the service industry gradually. If no additional targeted emission reduction or adjustment policies are added in the power industry, the primary energy and air pollutant emissions will increase significantly, putting great pressure on resources and the environment. For the emission reduction of air pollutants, the promotion effect of emission reduction measures, such as the implementation and promotion of non-fossil fuels, is restricted. The power industry can introduce and maximize the best available technologies while optimizing the structure of energy consumption to realize efficient emission reduction of air pollutants and energy conservation. In 2030, emissions will reach peak values with reasonable emission reduction cost. This has the additional effect of abating energy consumption and preventing deterioration of the ecological environment, which is of profound significance for the ultimate realization of climate friendliness.
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Hodijah, Nurhadi, Bintal Amin, and Mubarak Mubarak. "Estimasi Beban Pencemar Dari Emisi Kendaraan Bermotor di Ruas Jalan Kota Pekanbaru." Dinamika Lingkungan Indonesia 1, no. 2 (July 14, 2014): 71. http://dx.doi.org/10.31258/dli.1.2.p.71-79.
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Increasing population and economy in Pekanbaru City was clearly followed by anincrease in the number of motor vehicles has the potential to cause air pollution andendanger human health. This research was aimed to analyze the pollutant load gases of CO,HC, NO 2 , SO 2 and PM 10 emissions from motor vehicles at at Pekanbaru City. Survey on thevolume of motor vehicles, roadside air quality and vehicle emission test was conducted onthree different road in Pekanbaru city. The volume of motor vehicles and pollutants loadsfrom motor vehicle emissions was highest at Sudirman road and the lowest at Diponegororoad. There are very significant differences between Sudirman road with Diponegoro roadand Tuanku Tambusai road with Diponegoro road. Higher pollutant load was found for gasCO (76,4 %), than gas HC (19,4 %), gas NO 2 (3,6 %), gas SO 2 (0,1 % ) and PM 10 ( 0,7 % ).The largest contribution of pollutant load gas CO, HC and PM 10 comes from motorcycles, gasNO 2 from the city cars and gas SO 2 coming from the truck. The quality of roadside air in thethird road to the gases CO, NO 2 , SO 2 and PM 10 are still below the ambient air qualitystandards, whilest gas HC had passed the ambient air quality standard. A positive correlationbetween concentrations of roadside air pollutants with a load of motor vehicle emissions wasfound. The percentage of motor vehicle emission test results explain that the rates of vehiclesfueled with gasoline were higher than diesel vehicles and that do not pass of the emission testwere generally produced before 2007, while for diesel vehicles that do not pass the emissionstest opacity value that were produced in the 2010 onward.
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Zasina, Damian, and Jarosław Zawadzki. "On the Temporal Variability of Air Pollutants’ Emissions – Case Study of Residential PM10 Emission in Silesian Metropolis." New Trends in Production Engineering 3, no. 1 (August 1, 2020): 21–29. http://dx.doi.org/10.2478/ntpe-2020-0003.
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AbstractThe paper summarizes previous studies associated with carrying out of the air pollutant emission inventories. There are presented three approaches for obtaining monthly distribution of PM10 air emission: using expert’s judgement, modelling of the heating demand, and temporal disaggregation using the heating degree days (HDD). However some differences due to not considering hot water demand, it can be effectively used for obtaining temporal, and spatiotemporal distributions of air pollutants’ air emissions necessary for air quality modelling.
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Tian, Ya, Chao He, Lu Yang, Jiahui Yi, Biqin Ke, Hang Mu, Peiyue Tu, Zhixiang Ye, and Song Hong. "Spatiotemporal Dynamic Correlation Characteristics and Driving Factors of Major Air Pollutant Emissions in China." Atmosphere 14, no. 1 (January 6, 2023): 130. http://dx.doi.org/10.3390/atmos14010130.
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Air pollution is closely associated with human health and the economy. Therefore, it is important to understand variations in the spatiotemporal and sectoral emission distributions of major air pollutants and their drivers. The policies (APAPPC) promulgated by China in 2013 have also achieved remarkable results. Rate of change, trend analysis, and a geographically and temporally weighted regression model were used to study the effects of socioeconomic factors on NOx, SO2, and dust emissions in China during 2011—2017. During the study period, annual average emissions of NOx, SO2, and dust decreased by 11.45, 13.42, and 4.82 Mt (−47.64, −60.53, and −39.05%), respectively. Pollutant emissions were concentrated in North China, with Shandong and Hebei provinces exhibiting the highest NOx and SO2 and dust emissions, respectively. Pollutant emissions from the power and industrial sectors were mainly distributed in East (27.08 and 28.00%, respectively) and North China (23.57 and 20.04%, respectively), whereas emissions from the residential sector were mainly concentrated in North (22.48%) and Southwest China (20.07%). Pollutant emissions were positively correlated with electricity generation, urban population density, urban green spaces, private car ownership, the secondary industry as a share of regional GDP, and steel production and negatively correlated with disposable income and gross construction output. Per capita disposable income was the dominant driving factor.
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De Jesus Carretilha, Maurício, Fabiana Rocha Pinto, David Barbosa de Alencar, and Gisele De Freitas Lopes. "Quantification of CO2 Emissions by Top-down Method of Manaus Public and Private Transport Fleet." International Journal for Innovation Education and Research 7, no. 11 (November 30, 2019): 274–82. http://dx.doi.org/10.31686/ijier.vol7.iss11.1879.
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Air pollutants emitted by motor vehicles make a major contribution to air pollution in large urban centers, accounting for about 75% of emissions. The estimation of GHG emissions by the “Top-down” method used in the National Energy Balance - BEN, provides for the conversion of all fuel consumption measures to a common unit. Thus, the study aimed to guide the monitoring and monitoring of the concentrations of pollutant gases emitted by diesel combustion vehicles, comparing CO2 emissions in 2018, in two public and private transport fleets in the city of Manaus. - AM Based on the application of the Top-Down methodology generating the data in the comparative table of public and private transport companies, it is evident that CO2 emissions for both fleets present a high air pollution index suggesting the adaptation of the vehicle fleet. by adopting similar fuel with lower pollutant content. The data obtained in the study show that fuels with low emission factors should be used in urban public transport vehicles.
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Guo, Xiurui, Chunxiao Ning, Yaqian Shen, Chang Yao, Dongsheng Chen, and Shuiyuan Cheng. "Projection of the Co-Reduced Emissions of CO2 and Air Pollutants from Civil Aviation in China." Sustainability 15, no. 9 (April 23, 2023): 7082. http://dx.doi.org/10.3390/su15097082.
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Civil aviation transport is a key area of fossil energy consumption and greenhouse gas emission, and it is also an important source of air pollutants; the emissions of these have caused severe environmental problems. In this paper, we estimated the emissions in 235 domestic civil airports, and predicted the future trends of CO2 and air pollutant emissions from civil aviation in China until 2050 under three scenarios. The co-reduced emissions of each measure were evaluated by using the co-control effects coordinate system. The results show that in 2018, the emissions of CO2, NOx, SO2, CO, PM and HC were 117.23 × 106 tons, 90.47 × 104 tons, 14.37 × 104 tons, 9 × 104 tons, 1.29 × 104 tons and 0.66 × 104 tons, respectively. CO2, NOx, SO2 and PM emissions were mainly concentrated in cruise mode, accounting for 87–93% of the total emissions; HC and CO emissions were more frequently from the LTO. Under the baseline scenario, the growth rate of air pollutant emissions will account for a greater share, from 84% in 2030 to 464% in 2050, whereas the general scenario reduces emissions by 15% and 71%, respectively, and a higher reduction of 26% and 93% is seen in the stringent scenario. Improving aviation fuels is the most significant co-reduction measure, which can reduce CO2 by 89% and 68% in 2030 and 2050, and reduce air pollutants by 86–89% and 62–65%, respectively.
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Zhang, Haixia, Bo Liu, Angzu Cai, Zefei Zhao, Xia Wang, and Rui Li. "Study on Synergistic Emission Reduction in Greenhouse Gases and Air Pollutants in Hebei Province." Sustainability 15, no. 24 (December 13, 2023): 16790. http://dx.doi.org/10.3390/su152416790.
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Addressing climate change and improving air quality are prominent tasks facing China’s ecological environment. The synergistic emission reduction in greenhouse gases (GHGs) and air pollutants has become an important task of environmental governance in different provinces. In this study, Hebei Province was taken as the research object. Firstly, the emission factors of GHGs (CO2, CH4, and NO2) and air pollutants (SO2, NOX, and smoke & dust) in Hebei Province from 2011 to 2020 were calculated and analyzed. Seven socio-economic indicators were selected to analyze the trend during the study period. The Spearman rank correlation coefficient method was used to analyze the correlation between GHG and air pollutant emissions. Finally, the synergistic control effect coordinate system and the cross-elasticity coefficient of emission reduction were used to study the synergistic emission reduction effect of GHGs and air pollutants. The results showed that the total amount of GHG emissions fluctuated slightly from 2011 to 2020, and energy activities were the main source of total GHG emissions. The total emissions of air pollutants decreased year by year, and decreased by 71.13% in 2020 compared with 2011. During the study period, the emission synergy between smoke & dust and GHG was better than that between SO2, NOX, and GHG. GHG and SO2, NOX, and smoke & dust achieved synergistic emission reduction in most years, but the overall emission reduction synergy was poor.
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Loughlin, D. H., W. G. Benjey, and C. G. Nolte. "ESP v1.0: methodology for exploring emission impacts of future scenarios in the United States." Geoscientific Model Development 4, no. 2 (April 8, 2011): 287–97. http://dx.doi.org/10.5194/gmd-4-287-2011.
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Abstract. This article presents a methodology for creating anthropogenic emission inventories that can be used to simulate future regional air quality. The Emission Scenario Projection (ESP) methodology focuses on energy production and use, the principal sources of many air pollutants. Emission growth factors for energy system categories are calculated using the MARKAL energy system model. Growth factors for non-energy sectors are based on economic and population projections. These factors are used to grow a 2005 emissions inventory through 2050. The approach is demonstrated for two emission scenarios for the United States. Scenario 1 extends current air regulations through 2050, while Scenario 2 adds a hypothetical CO2 mitigation policy. Although both scenarios show significant reductions in air pollutant emissions through time, these reductions are more pronounced in Scenario 2, where the CO2 policy results in the adoption of technologies with lower emissions of both CO2 and traditional air pollutants. The methodology is expected to play an important role within an integrated modeling framework that supports the US EPA's investigations of linkages among emission drivers, climate and air quality.
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Kim, Myoung Ho, and Seong Min Kim. "Estimation of Air Pollutant Emissions by Tractor Utilization in Korea." Agriculture 13, no. 9 (September 14, 2023): 1811. http://dx.doi.org/10.3390/agriculture13091811.
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The utilization of tractors is essential because of both the shortage of agricultural labor forces and the rapid aging of farmers in Korean agriculture. Tractors can be classified into two types: a walking tractor called as a power tiller, and a riding tractor. In this study, diesel emission inventories of tractors were established and variations of air pollutants were analyzed with each other using 2011 and 2019 survey data in Korea. Agricultural tractors including walking and riding types, which were categorized into three levels via the rated output power, were the main sources of diesel emissions. The emission inventory including CO, NOx, SOx, TSP(PM10), PM2.5, VOCs, and NH3 were established using a Tier 3 methodology. The total amount of emissions using agricultural tractors was decreased by about 13% from 2011 to 2019. The number of walking tractors were decreased by about 19% in 8 years; on the other hand, that of riding tractors were increased by about 12%. However, the emission reduction is about 48% for walking tractors, and the emission increment is about 5% for riding tractors. Thus, the total emission from agricultural tractors was decreased by about 16% in those periods. It is due to the decrease of 21% and 15% in the hours of use of walking and riding tractors, respectively, in 2019. Walking tractors mainly emit air pollutants from spraying and transporting. Riding tractors emit about 61% of the total air pollutants mainly from soil preparation and transporting operations. The geographic information system (GIS) was used to visualize the distribution of air pollutants in Korea. High-emission generating regions and the changes of emissions over 8 years were clearly seen in the GIS analysis. High air-pollutant emitting regions are mainly located in the western and southern regions of Korea, which have plenty of arable areas compared to other regions in Korea.
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Roeva, N. N., S. S. Voronich, D. A. Zaitsev, N. S. Voronich, and A. G. Chernobrovina. "On a New Method for the Rapid Determination of the Strength of Industrial Emissions of a Pollutant." Ecology and Industry of Russia 23, no. 12 (December 13, 2019): 34–37. http://dx.doi.org/10.18412/1816-0395-2019-12-34-37.
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A method has been developed for the operational determination of the strength of industrial emissions of a pollutant by an APS without direct measurements of concentrations and parameters in it, which relates to industrial ecology and can be used in the state environmental control or monitoring system to increase its effectiveness and responsiveness. The essence of the method is to use the information provided by public authorities. An information base is being created for all organized APS located in the observed urbanized area, which contains information about the sources of pollutant emissions and their characteristics; establishes the fact of unauthorized pollutant release by detecting elevated concentrations of various pollutants in the observed area according to the results of quantitative chemical analysis of atmospheric air samples and determines their ratio; the inverse dispersion problem is solved and the area of the location of sources of unauthorized pollutant emissions is identified, the source of unauthorized pollutant emissions is determined, and then the strength of this pollutant emission is estimated (Mi, g/s).
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Mentes, Dóra, Zoltán Sajti, Tamás László Koós, and Csaba Póliska. "Optimizing the combustion processes of a small scale solid fuel-fired boiler." International Journal of Engineering and Management Sciences 4, no. 4 (December 12, 2019): 358–69. http://dx.doi.org/10.21791/ijems.2019.4.41.
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Over the last decade, the public has been paying increasing attention to reducing greenhouse gas and acid rain emissions and reducing particulate matter, which is extremely harmful to health and the environment. To improve air quality, the European Commission has achieved a range of measures to reduce air pollutant emissions in the transport, heat and electricity, industrial and agricultural sectors. In Hungary, the amount of gas and solid air pollutants from solid fuel combustion used by the public during the heating season represents a significant percentage of the total amount present in the atmosphere. In 2016, taking into the total emission, the 29% of CO2 emissions; 85% of CO emissions; 75% of the particulate matter emissions and 21% of the NOx emissions were derived from households. It follows that the improvement of air quality can also be achieved by controlling the emissions of solid fuel combustion plants. During our research we aimed to optimize the operation of a newly purchased TOTYA S18 boiler and a pilot pellet boiler. Operating the boilers in the correct mode minimizes air pollutant emissions, and the greater part of the heat generated is actually turns to heating the home, as with poor settings, a lot of heat leaves through the chimney. The data obtained during the tests can also be used to determine whether the boilers comply with the emission values set out in Commission Regulation (EU) 2015/1185.
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Wang, J. M., C. H. Jeong, N. Zimmerman, R. M. Healy, D. K. Wang, F. Ke, and G. J. Evans. "Plume-based analysis of vehicle fleet air pollutant emissions and the contribution from high emitters." Atmospheric Measurement Techniques Discussions 8, no. 3 (March 18, 2015): 2881–912. http://dx.doi.org/10.5194/amtd-8-2881-2015.
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Abstract. An automated identification and integration method has been developed to investigate in-use vehicle emissions under real-world conditions. This technique was applied to high time resolution air pollutant measurements of in-use vehicle emissions performed under real-world conditions at a near-road monitoring station in Toronto, Canada during four seasons, through month-long campaigns in 2013–2014. Based on carbon dioxide measurements, over 100 000 vehicle-related plumes were automatically identified and fuel-based emission factors for nitrogen oxides; carbon monoxide; particle number, black carbon; benzene, toluene, ethylbenzene, and xylenes (BTEX); and methanol were determined for each plume. Thus the automated identification enabled the measurement of an unprecedented number of plumes and pollutants over an extended duration. Emission factors for volatile organic compounds were also measured roadside for the first time using a proton transfer reaction time-of-flight mass spectrometer; this instrument provided the time resolution required for the plume capture technique. Mean emission factors were characteristic of the light-duty gasoline dominated vehicle fleet present at the measurement site, with mean black carbon and particle number emission factors of 35 mg kg−1 and 7.7 × 1014 kg−1, respectively. The use of the plume-by-plume analysis enabled isolation of vehicle emissions, and the elucidation of co-emitted pollutants from similar vehicle types, variability of emissions across the fleet, and the relative contribution from heavy emitters. It was found that a small proportion of the fleet (< 25%) contributed significantly to total fleet emissions; 95, 93, 76, and 75% for black carbon, carbon monoxide, BTEX, and particle number, respectively. Emission factors of a single pollutant may help classify a vehicle as a high emitter. However, regulatory strategies to more efficiently target multi-pollutants mixtures may be better developed by considering the co-emitted pollutants as well.
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Wu, Jian, Shaofei Kong, Fangqi Wu, Yi Cheng, Shurui Zheng, Qin Yan, Huang Zheng, et al. "Estimating the open biomass burning emissions in central and eastern China from 2003 to 2015 based on satellite observation." Atmospheric Chemistry and Physics 18, no. 16 (August 16, 2018): 11623–46. http://dx.doi.org/10.5194/acp-18-11623-2018.
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Abstract. Open biomass burning (OBB) has significant impacts on air pollution, climate change and potential human health. OBB has gathered wide attention but with little focus on the annual variation of pollutant emission. Central and eastern China (CEC) is one of the most polluted regions in China. This study aims to provide a state-of-the-art estimation of the pollutant emissions from OBB in CEC from 2003 to 2015, by adopting the satellite observation dataset – the burned area product (MCD64Al) and the active fire product (MCD14 ML) – along with local biomass data (updated biomass loading data and high-resolution vegetation data) and local emission factors. The successful adoption of the double satellite dataset for long-term estimation of pollutants from OBB with a high spatial resolution can support the assessing of OBB on regional air quality, especially for harvest periods or dry seasons. It is also useful to evaluate the effects of annual OBB management policies in different regions. Here, monthly emissions of pollutants were estimated and allocated into a 1×1 km spatial grid for four types of OBB including grassland, shrubland, forest and cropland. From 2003 to 2015, the emissions from forest, shrubland and grassland fire burning had an annual fluctuation, whereas the emissions from crop straw burning steadily increased. The cumulative emissions of organic carbon (OC), elemental carbon (EC), methane (CH4), nitric oxide (NOx), non-methane volatile organic compounds (NMVOCs), sulfur dioxide (SO2), ammonia (NH3), carbon monoxide (CO), carbon dioxide (CO2) and fine particles (PM2.5) were 3.64×103, 2.87×102, 3.05×103, 1.82×103, 6.4×103, 2.12×102, 4.67×102, 4.59×104, 9.39×105 and 4.13×103 Gg in these years, respectively. Crop straw burning was the largest contributor for all pollutant emissions, by 84 %–96 %. For the forest, shrubland and grassland fire burning, forest fire burning emissions contributed the most, and emissions from grassland fire were negligible due to little grass coverage in this region. High pollutant emissions concentrated in the connection area of Shandong, Henan, Jiangsu and Anhui, with emission intensity higher than 100 tons per square kilometer, which was related to the frequent agricultural activities in these regions. Peak emission of pollutants occurred during summer and autumn harvest periods including May, June, September and October, during which ∼50 % of the total pollutant emissions were emitted in these months. This study highlights the importance of controlling the crop straw burning emissions. From December to March, the crop residue burning emissions decreased, while the emissions from forest, shrubland and grassland exhibited their highest values, leading to another small peak in emissions of pollutants. Obvious regional differences in seasonal variations of OBB were observed due to different local biomass types and environmental conditions. Rural population, agricultural output, economic levels, local burning habits, social customs and management policies were all influencing factors for OBB emissions.
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Salcido, Alejandro, Susana Carreón-Sierra, and Ana-Teresa Celada-Murillo. "Air Pollution Flow Patterns in the Mexico City Region." Climate 7, no. 11 (November 5, 2019): 128. http://dx.doi.org/10.3390/cli7110128.
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According to the Mexico City Emissions Inventory, mobile sources are responsible for approximately 86% of nitrogen oxide emissions in this region, and correspond to a NOx emission of 51 and 58 kilotons per year in Mexico City and the State of Mexico, respectively. Ozone levels in this region are often high and persist as one of the main problems of air pollution. Identifying the main scenarios for the transport and dispersion of air pollutants requires the knowledge of their flow patterns. This work examines the surface flow patterns of air pollutants (NO2, O3, SO2, and PM10) in the area of Mexico City (a region with strong orographic influences) over the period 2001–2010. The flow condition of a pollutant depends on the spatial distribution of its concentration and the mode of wind circulation in the region. We achieved the identification and characterization of the pollutant flow patterns through the exploitation of the 1-hour average values of the pollutant concentrations and wind data provided by the atmospheric monitoring network of Mexico City and the application of the k-means method of cluster analysis. The data objects for the cluster analysis were obtained by modeling Mexico City as a 4-cell spatial domain and describing, for each pollutant, the flow state in a cell by the spatial averages of the horizontal pollutant flow vector and its gradients (the divergence and curl of the flow vector). We identified seven patterns for wind circulation and nine patterns for each of NO2, O3, PM10, and SO2 pollutant flows. Their seasonal and annual average intensities and probabilities of occurrence were estimated.
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Singh, Ashish Shankar. "Preparing Municipal Solid Waste Emission Inventory and Spatial Distribution of Prayagraj City Using GIS." International Journal for Research in Applied Science and Engineering Technology 9, no. 9 (September 30, 2021): 317–25. http://dx.doi.org/10.22214/ijraset.2021.37935.
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Abstract: Pollutants in the air are emitted from a variety of sources in metropolitan areas, causing poor air quality. Using a Geographic Information System (GIS), this project attempts to assess municipal solid waste (MSW) burning emissions and prepare a spatial distribution grid for Prayagraj city. PM10, PM2.5, NOx, SO2, and CO emissions were computed using activity data and emission factors using a bottom-up approach. The result from this study shows that emissions for all 5 pollutants PM10, PM2.5, NOx, SO2, CO are 718, 488, 269, and 3771kg/day respectively, where CO is the highest emitted pollutant. The Prayagraj municipal area was divided into grids of 3 km2 area. The spatial distribution plotted for Prayagraj city shows the hotspot grid areas for all 5 air pollutants emission. The hotspot grids for PM10 are P9, P10, P17, P29 and for PM2.5, NOx, SO2, are P9, P10, P17 and for CO are P9, P10, P14, P17, P29. Keywords: PM10, PM2.5, NOX, SO2, CO, Emission Inventory, Spatial distribution, Hotspot grids