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Reay, David S., Keith A. Smith, Anthony C. Edwards, Kevin M. Hiscock, Liang F. Dong, and David B. Nedwell. "Indirect nitrous oxide emissions: Revised emission factors." Environmental Sciences 2, no. 2-3 (June 2005): 153–58. http://dx.doi.org/10.1080/15693430500415525.
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Mugica-Álvarez, Violeta, Francisco Hernández-Rosas, Miguel Magaña-Reyes, Jorge Herrera-Murillo, Naxieli Santiago-De La Rosa, Mirella Gutiérrez-Arzaluz, José de Jesús Figueroa-Lara, and Griselda González-Cardoso. "Sugarcane burning emissions: Characterization and emission factors." Atmospheric Environment 193 (November 2018): 262–72. http://dx.doi.org/10.1016/j.atmosenv.2018.09.013.
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Kong, Haojia, Lifan Shi, Dan Da, Zhijiang Li, Decai Tang, and Wei Xing. "Simulation of China’s Carbon Emission based on Influencing Factors." Energies 15, no. 9 (April 29, 2022): 3272. http://dx.doi.org/10.3390/en15093272.
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China is one of the world’s largest energy consumers and carbon emitters, and the situation of carbon emission reduction is serious. This paper forecasts the future trend of China’s carbon emissions by constructing a system dynamics model of China’s carbon emissions. The results show that China cannot fulfill its commitment to peak its carbon emissions in 2030 as scheduled. Secondly, the Logarithmic Mean Divisia Index model (LMDI) was used to analyze the influencing factors of China’s carbon emissions. The contribution rates of the five factors to China’s carbon emissions are as follows: economic development (226.30%), technological innovation (−105.92%), industrial structure (−26.55%), population scale (11.44%) and energy structure (−5.28%). Finally, this paper formulates five carbon emission reduction paths according to the size and direction of various factors that affect China’s carbon emissions. The paths of carbon emission reduction were simulated by using the system dynamics model of China’s carbon emissions. It is found that technological innovation is the key pathway for China to realize its commitment to carbon emission reduction. Slowing economic growth will delay the arrival time of peak carbon emissions and increase the intensity of carbon emissions. Optimizing the industrial structure, reducing the population scale and adjusting the energy structure can reduce the peak and carbon emissions in China, but the effect is small.
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Castellanos, P., K. F. Boersma, and G. R. van der Werf. "Satellite observations indicate substantial spatiotemporal variability in biomass burning NO<sub>x</sub> emission factors for South America." Atmospheric Chemistry and Physics 14, no. 8 (April 17, 2014): 3929–43. http://dx.doi.org/10.5194/acp-14-3929-2014.
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Abstract. Biomass burning is an important contributor to global total emissions of NOx (NO+NO2). Generally bottom-up fire emissions models calculate NOx emissions by multiplying fuel consumption estimates with static biome-specific emission factors, defined in units of grams of NO per kilogram of dry matter consumed. Emission factors are a significant source of uncertainty in bottom-up fire emissions modeling because relatively few observations are available to characterize the large spatial and temporal variability of burning conditions. In this paper we use NO2 tropospheric column observations from the Ozone Monitoring Instrument (OMI) from the year 2005 over South America to calculate monthly NOx emission factors for four fire types: deforestation, savanna/grassland, woodland, and agricultural waste burning. In general, the spatial patterns in NOx emission factors calculated in this work are consistent with emission factors derived from in situ measurements from the region but are more variable than published biome-specific global average emission factors widely used in bottom-up fire emissions inventories such as the Global Fire Emissions Database (GFED). Satellite-based NOx emission factors also indicate substantial temporal variability in burning conditions. Overall, we found that deforestation fires have the lowest NOx emission factors, on average 30% lower than the emission factors used in GFED v3. Agricultural fire NOx emission factors were the highest, on average a factor of 1.8 higher than GFED v3 values. For savanna, woodland, and deforestation fires, early dry season NOx emission factors were a factor of ~1.5–2 higher than late dry season emission factors. A minimum in the NOx emission factor seasonal cycle for deforestation fires occurred in August, the time period of severe drought in South America in 2005, supporting the hypothesis that prolonged dry spells may lead to an increase in the contribution of smoldering combustion from large-diameter fuels, offsetting the higher combustion efficiency of dryer fine fuels. We evaluated the OMI-derived NOx emission factors with SCIAMACHY NO2 tropospheric column observations and found improved model performance in regions dominated by fire emissions.
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Castellanos, P., K. F. Boersma, and G. R. van der Werf. "Satellite observations indicate substantial spatiotemporal variability in biomass burning NO<sub>x</sub> emission factors for South America." Atmospheric Chemistry and Physics Discussions 13, no. 8 (August 30, 2013): 22757–93. http://dx.doi.org/10.5194/acpd-13-22757-2013.
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Abstract. Biomass burning is an important contributor to global total emissions of NOx (NO + NO2). Generally bottom-up fire emissions models calculate NOx emissions by multiplying fuel consumption estimates with static biome specific emission factors, defined in units of grams of NO per kilogram of dry matter consumed. Emission factors are a significant source of uncertainty in bottom-up fire emissions modeling because relatively few observations are available to characterize the large spatial and temporal variability of burning conditions. In this paper we use NO2 tropospheric column observations from the Ozone Monitoring Instrument (OMI) from the year 2005 over South America to calculate monthly NOx emission factors for four fire types: deforestation, savanna/grassland, woodland, and agricultural waste burning. In general, the spatial trends in NOx emission factors calculated in this work are consistent with emission factors derived from in situ measurements from the region, but are more variable than published biome specific global average emission factors widely used in bottom up fire emissions inventories such as the Global Fire Emissions Database (GFED) v3. Satellite based NOx emission factors also indicate substantial temporal variability in burning conditions. Overall, we found that deforestation fires have the lowest NOx emission factors, on average 30 % lower than the emission factors used in GFED v3. Agricultural fire NOx emission factors were the highest, on average a factor of 2 higher than GFED v3 values. For savanna, woodland, and deforestation fires early dry season NOx emission factors were a factor of ~1.5–2.0 higher than late dry season emission factors. A minimum in the NOx emission factor seasonal cycle for deforestation fires occurred in August, the time period of severe drought in South America in 2005. Our results support the hypothesis that prolonged dry spells may lead to an increase in the contribution of smoldering combustion from large diameter fuels to total fire emissions, which would lower the overall modified combustion efficiency (MCE) and NOx emission factor, and offset the higher combustion efficiency of dryer fine fuels. We evaluated the OMI derived NOx emission factors with SCIAMACHY NO2 tropospheric column observations and found improved model performance in regions dominated by fire emissions.
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Urbanski, Shawn. "Wildland fire emissions, carbon, and climate: Emission factors." Forest Ecology and Management 317 (April 2014): 51–60. http://dx.doi.org/10.1016/j.foreco.2013.05.045.
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Davoli, Enrico, Giancarlo Bianchi, Anna Bonura, Marzio Invernizzi, and Selena Sironi. "Odor Emissions Factors for Bitumen-Related Production Sites." Applied Sciences 11, no. 8 (April 20, 2021): 3700. http://dx.doi.org/10.3390/app11083700.
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Bitumen-related production sites are facing increasing difficulties with nearby residents due to odor emissions. This parameter is still not regulated for these plants and little is known about the emissions that these plants have put into the atmosphere with the technologies available today. In this study, emission data from 47 Italian production plants were collected and analyzed to assess which values could describe the current situation in Italy. The results of the analysis showed that emissions are very variable, with odor concentration values between 200 to 37,000 ouE/m3, but data have a normal distribution. The mean value of the stack odor concentration was found to be 2424 ouE/m3. It was also possible to calculate emission factors of the plants, such as odor emission rate (OER), which represents the quantity of odor emitted per unit of time, and is expressed in odor units per second (ouE∙s−1) and odor emission factor (OEF) per ton of product, expressed in ouE/t. The values obtained were 7.1 × 104 ouE/s and 1.4 × 106 ouE/t. respectively. These data could provide a starting point for the definition of shared values among various stakeholders for the definition of regional guidelines for the emissions of these plants, in order to adjust available technologies towards emission parameters that are protective of the surrounding environment.
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Tang, Tianjia, Michael Claggett, Joon Byun, Mike Roberts, Jessica Granell, and Dale E. Aspy. "MOBILE6.2 Modeling of Exhaust Air Toxic Emission Factors." Transportation Research Record: Journal of the Transportation Research Board 1941, no. 1 (January 2005): 99–106. http://dx.doi.org/10.1177/0361198105194100112.
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The newly released MOBILE6.2 has incorporated both air toxic and particulate matter emission factor modeling functions. A series of test runs were performed to gain a better understanding of the air toxic modeling function and overall model behavior. These test runs and scenarios evaluated the changes in emission factors of all six built-in air toxic compounds as affected by vehicle activities, fuel physical properties, fuel chemical compositions, oxygenated fuel additives, and environmental conditions. Results obtained indicate that exhaust emission factors for acrolein, acetaldehyde, benzene, 1,3-butadiene, formaldehyde, and methyl tertiary butyl ether are inversely proportional to freeway and arterial vehicle speeds. This phenomenon follows the trend of total organic gas emission factors. Effects from roadway facility differences indicated that the higher the percentage of vehicle miles traveled on a freeway, the lower the air toxic emission factors on a per vehicle mile traveled basis. Exhaust air toxic emission factors increase when fuel Reid vapor pressure value and sulfur content increase. Diesel sulfur content has no effect on the six toxic compound emission factors. Effects from fuel chemical compositions on all emission factors varied. However, chemical compositions do have significant effects on all air toxic compound emission factors. On the same note, both minimum and maximum temperatures affect all air toxic emissions significantly. The time series evaluation indicates that all six tested air toxic compound emissions decrease linearly from the year 2002 to 2020.
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Yu, Yao, Ruikai Sun, Yindong Sun, Jinyou Wu, and Wanying Zhu. "China’s Port Carbon Emission Reduction: A Study of Emission-Driven Factors." Atmosphere 13, no. 4 (March 29, 2022): 550. http://dx.doi.org/10.3390/atmos13040550.
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Ports offer an effective way to facilitate the global economy. However, massive carbon emission during port operating aggravates the atmospheric pollution in port cities. Capturing characteristics of port carbon emission is vital to reduce GHG (greenhouse gas) in the maritime realm as well as to achieve China’s carbon neutral objective. In this work, an integrated framework is proposed for exploring the driving factors of China ports’ emissions combined with stochastic effects on population, affluence and technology regression (STIRPAT), Global Malmquist-Luenberger (GML) and multiple linear regression (MLR). The port efficiency is estimated for each port and the potential driving factors of carbon emission are explored. The results indicate that port carbon emissions have a strong connection with port throughput, productivity, containerization and intermodal transshipment. It is worth noting that the containerization ratio and port physical facility with fossil-free energy improvement have positively correlated with carbon emissions. However, the specific value of waterborne transshipment shows a complex impact on carbon dioxide emission as the ratio increases. The findings reveal that China port authorities need to improve containerization ratio and develop intermodal transportation; meanwhile, it is responsible for port authorities to update energy use and improve energy efficiency in ways to minimize the proportion of non-green energy consumption in accordance with optimizing port operation management including peak shaving and intelligent management systems under a new horizon of clean energy and automatic equipment.
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Burns, Paul, Volkmar Timmermann, and Jon M. Yearsley. "Meteorological factors associated with the timing and abundance of Hymenoscyphus fraxineus spore release." International Journal of Biometeorology 66, no. 3 (November 11, 2021): 493–506. http://dx.doi.org/10.1007/s00484-021-02211-z.
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AbstractThe ascomycete Hymenoscyphus fraxineus has spread across most of the host range of European ash with a high level of mortality, causing important economic, cultural and environmental effects. We present a novel method combining a Monte-Carlo approach with a generalised additive model that confirms the importance of meteorology to the magnitude and timing of H. fraxineus spore emissions. The variability in model selection and the relative degree to which our models are over- or under-fitting the data has been quantified. We find that both the daily magnitude and timing of spore emissions are affected by meteorology during and prior to the spore emission diurnal peak. We found the daily emission magnitude has the strongest associations to weekly average net radiation and leaf moisture before the emission, soil temperature during the day before emission and net radiation during the spore emission. The timing of the daily peak in spore emissions has the strongest associations to net radiation both during spore emission and in the day preceding the emission. The seasonal peak in spore emissions has a near-exponential increase/decrease, and the mean daily emission peak is approximately Gaussian.
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Kim, Gun-Yeob, Yeon-Jin Lee, Eun-Ji Cho, Jae-In Lee, Eun-Chae Im, Hancheol Hwang, Sang-Yoon Kim, Sung-Chang Hong, Jin-Ho Kim, and Seong-Jik Park. "Investigation of Factors Influencing on Ammonia Emission from Soils in Agricultural Land." Journal of Korean Society of Environmental Engineers 44, no. 11 (November 30, 2022): 444–52. http://dx.doi.org/10.4491/ksee.2022.44.11.444.
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Objectives : Major factors affecting ammonia emission from the soil and strategies to reduce ammonia emission were investigated through literature surveys.Methods : An academic search was conducted using keywords such as agriculture, ammonia, and fine dust, and the effects of soil characteristics on ammonia emission were summarized for each factor.Results and Discussion : Emissions of ammonia into the atmosphere can reduce economic returns for a farmer and negatively impact the atmospheric environment by acting as a precursor to PM2.5 formations. It is reported that agriculture accounts for 78% of the total ammonia emission sources in Korea. Ammonia emission from the soil is affected by the type of ammonia fertilizer, soil moisture, pH, temperature, cation exchange capacity, organic matter, and soil texture. An increase in soil moisture increases ammonia emissions. As soil pH increases, ammonia emissions increase, noticeably above 7.5. An increase in soil temperature increases the rate of hydrolysis of urea and the rate of conversion to ammonia gas, resulting in increased ammonia emissions. Soils with high cation exchange capacity adsorb ammonium to reduce ammonia emissions. Soils with a high clay content and soil organic matter content are more buffered to changes in soil pH, reducing ammonia emissions.Conclusion : Based on understanding the mechanisms and causes of ammonia emission from the soil, it is possible to establish soil and environmental management to reduce ammonia emissions into the atmosphere.
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Zhou, Fan, Jing Liu, Hang Zhu, Xiaodong Yang, and Yunli Fan. "A Real-Time Measurement-Modeling System for Ship Air Pollution Emission Factors." Journal of Marine Science and Engineering 10, no. 6 (May 31, 2022): 760. http://dx.doi.org/10.3390/jmse10060760.
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The lack of techniques for monitoring ship emissions all day and in all weather conditions to obtain real-time emission factor values is the main problem in understanding the characteristics of ship emissions, and there is still no perfect solution. In this study, a real-time measurement-modeling system was designed and implemented. The system was divided into three parts: (1) a portable exhaust monitoring device, which could be mounted on a drone, aircraft, patrol boat, dock, and bridge crane, as well as on the shore, to conduct all-weather and real-time online monitoring of ship emissions; (2) a monitoring information platform for ship emissions, based on a Spring + Spring MVC + MyBatis (SSM) framework and Vue front-end technology; and (3) a cloud server that received real-time ship emission measurement data and stored it after verification and analysis to calculate the pollutant gas and particulate matter emission factors. Following development, this system was used to monitor the emissions of ocean-going and inland river ships. Analysis of the acquired data showed that the system could effectively measure the emission factors of ship exhausts full-time in a variety of weather scenarios. This system can improve the efficiency of maritime law enforcement and provide technical support for promoting the construction of ship emission control areas. It can also help researchers obtain ship emission data, as well as an improved understanding of the emission characteristics of ships.
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LEE, Kun Mo, and Min Hyeok LEE. "Uncertainty of the Electricity Emission Factor Incorporating the Uncertainty of the Fuel Emission Factors." Energies 14, no. 18 (September 10, 2021): 5697. http://dx.doi.org/10.3390/en14185697.
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Greenhouse gas (GHG) emission from electricity generation has been recognized as one of the most significant contributors to global warming. The GHG emission factor of electricity (hereafter, electricity emission factor) can be expressed as a function of three different (average, minimum, and maximum) fuel emission factors, monthly fuel consumption, and monthly net power generation. Choosing the average fuel emission factor over the minimum and maximum fuel emission factors is the cause of uncertainty in the electricity emission factor, and thus GHG emissions of the power generation. The uncertainties of GHG emissions are higher than those of the electricity emission factor, indicating that the uncertainty of GHG emission propagates in the GHG emission computation model. The bootstrapped data were generated by applying the bootstrap method to the original data set which consists of a 60-monthly average, and minimum and maximum electricity emission factors. The bootstrapped data were used for computing the mean, confidence interval (CI), and percentage uncertainty (U) of the electricity emission factor. The CI, mean, and U were [0.431, 0.443] kg CO2-eq/kWh, 0.437 kg CO2-eq/kwh, and 2.56%, respectively.
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Li, Wenchao, Lingyu Xu, and Yi Jin. "The influence factors of interprovincial power transmission on China's CO2 emissions." Science Progress 105, no. 4 (October 2022): 003685042211374. http://dx.doi.org/10.1177/00368504221137466.
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Electric power system is a major source of CO2 emission in China. Understanding the evolution of power-related CO2 emission is an important step to both emission reduction and a sustainable energy transition. Here, we assess the CO2 emission of power production in China, finding that it increased by 47% from 2008 to 2017 despite a significant decrease in CO2 emission intensity of power production. The CO2 emission intensity of power production differs greatly across provinces, with the highest provincial CO2 emission intensity 11 times the lowest. To understand the evolution of power-related CO2 emission, this study quantified the embodied CO2 emissions of power transmission, and then use decomposition analysis to explore the influencing factors of it. We found that China's embodied CO2 emissions from power transmission increased from 315 to 523 Mt between 2008 and 2017, and the increase in electricity consumption and the dependence on power transmission networks are the important reasons for the increase in embodied CO2 emissions. Nationally, power transmission reduced CO2 emission by 78 Mt. because, compared to the east, the west generally has a larger CO2 emission factor. These dynamics will become important for policymakers and energy planners to achieve carbon neutrality.
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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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Liu, Shiwen, Hongxiong Li, Wen Kun, Zhen Zhang, and Haotian Wu. "How Do Transportation Influencing Factors Affect Air Pollutants from Vehicles in China? Evidence from Threshold Effect." Sustainability 14, no. 15 (August 1, 2022): 9402. http://dx.doi.org/10.3390/su14159402.
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In recent years, China has promoted a series of legal norms to reduce the environmental impact of air pollutants from vehicles. The three main vehicle emission species (carbon monoxide, hydrocarbons, nitrogen oxides) contribute significantly to air pollution. In this study, the emission factor method was used to estimate air pollutants from vehicles in 31 provinces from 2006 to 2016. The results show a trend of total vehicle carbon monoxide (CO) and hydrocarbons (HC) emissions decreasing with time; the vehicle nitrogen oxides (NOx) emission trend is divided into two stages: an upward trend between 2006 and 2012 and a downward trend after 2012. Based on a panel threshold, a regression method was used to divide the vehicle NOx and CO emissions in China into four emission zones: low emissions, medium emissions, high emissions, and extra-high emissions. Vehicle HC emissions were divided into three emission zones, which corresponded to low emissions, medium emissions, and high emissions. Overall, vehicle pollution emission efficiency and per capita GDP have a significant inhibitory effect on the three main air pollutants from vehicles (NOx, HC, CO). Both passenger and freight turnover have significant roles in promoting the three air pollutants from vehicles (NOx, HC, CO). Road density and road carrying capacity have a significant role in promoting vehicle HC and CO emissions. Increasing truck proportion inhibits vehicle CO emissions and promotes vehicle NOx emissions. The urbanization rate has a positive effect on vehicle HC and CO emissions. Moreover, there is obvious heterogeneity in different emission zones of the three air pollutants from vehicles (NOx, HC, CO).
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Zhang, Ye, Yating Song, Tianshi Feng, and Yanyan Chen. "Comparative Analysis of Emission Characteristics of In-Use China II–V Gasoline, Hybrid, Diesel-Fueled Vehicles." Atmosphere 14, no. 2 (January 29, 2023): 272. http://dx.doi.org/10.3390/atmos14020272.
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Increasingly stringent regulations regarding vehicle emissions have contributed to the diversification of vehicle technologies, resulting in the increasing complexity of typical vehicles that make up a fleet. In order to investigate the real gas emissions of different typical vehicles, tests were conducted using a portable emission measurement system (PEMS) in Beijing and emission studies were conducted on eight light-duty passenger vehicles (LDPVs, including light-duty gasoline passenger vehicles and hybrid electric vehicles), eight heavy-duty passenger vehicles (HDPVs), and four light-duty trucks (LDTs). The results show that the emissions of relevant pollutants from LDPV meet the emission standard limits. The emission factors of CO2, CO, NOX, and HC of China IV and China V hybrid electric vehicles (HEVs) are much smaller than the emission standard limits and the emission factors of other vehicles, which have better emission reduction effects. Among LDPV, heavy-duty passenger vehicles (HDPVs), and LDT, the emissions of HDPV and LDT are extremely high. Emission characteristics vary on different types of roads, with the highest emission factors generally occurring on secondary roads. The micro-trip method was used to explore the influence of speed on emission factors. HEV are less sensitive to speed changes and can still maintain a low emission level at low speeds. The average speed and emission factors of HDPV in micro-trip has a strong correlation.
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Mutlu, Esra, Sarah H. Warren, Peggy P. Matthews, Charly King, Leon Walsh, Andrew D. Kligerman, Judith E. Schmid, et al. "Health effects of soy-biodiesel emissions: mutagenicity-emission factors." Inhalation Toxicology 27, no. 11 (September 19, 2015): 585–96. http://dx.doi.org/10.3109/08958378.2015.1080771.
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Niemeier, D. A. "Spatial Applicability of Emission Factors for Modeling Mobile Emissions." Environmental Science & Technology 36, no. 4 (February 2002): 736–41. http://dx.doi.org/10.1021/es0109747.
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Trumbore, David, Angela Jankousky, Edwin L. Hockman, Ronald Sanders, John Calkin, Steve Szczepanik, and Roy Owens. "Emission factors for asphalt-related emissions in roofing manufacturing." Environmental Progress 24, no. 3 (2005): 268–78. http://dx.doi.org/10.1002/ep.10071.
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Wang, Bo, Chunyan Huang, Huaming Wang, and Fangwei Liao. "Impact Factors in Chinese Construction Enterprises’ Carbon Emission-Reduction Intentions." International Journal of Environmental Research and Public Health 19, no. 24 (December 16, 2022): 16929. http://dx.doi.org/10.3390/ijerph192416929.
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The reduction in carbon emissions in the construction industry plays an important role in the realization of the goal of carbon peaking and carbon neutrality, especially in China. Construction enterprises’ personnel’s intentions to reduce their carbon emissions are closely related to low-carbon behavior. However, the research on the impact factors of carbon emission-reduction intention (CERI) is still limited. In order to understand the factors that affect the intentions of construction enterprises’ personnel to reduce carbon emissions, and to put forward valuable suggestions for reducing construction enterprises’ carbon emissions, it is necessary to explore the impact factors in carbon emission-reduction intention through empirical tests. This study adopted the theory of planned behavior (TPB) based on the three impact factors of behavioral attitude (BA), subjective norms (SNs) and perceived behavioral control (PBC), introduced the two potential impact factors of moral obligation (MO) and government supervision (GS), and also uses structural equation modeling (SEM) to test the impact factors in construction enterprises’ personnel’s carbon emission-reduction intention. The results show that BA, MO and GS have a significant positive impact on carbon emission-reduction intention (CERI). Among them, BA plays an intermediary role between MO and CERI, and BA and MO play a chain intermediary role between GS and CERI. The research conclusions will help to provide a theoretical reference for governments and construction enterprises to implement carbon emission-reduction development strategies and policies.
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Park, Yoosung, Sung-Mo Yeon, and Kyu-Hyun Park. "Development of GHG Emission Factors for the Life Cycle of the Animal Manure Treatment Systems." Journal of Korean Society of Environmental Engineers 42, no. 12 (December 31, 2020): 637–44. http://dx.doi.org/10.4491/ksee.2020.42.12.637.
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Objectives:A whole process greenhouse gas emission factor was developed considering the direct greenhouse gas emission from the decomposition of livestock manure provided by the IPCC guidelines and the energy consumption of manure management systems.Methods:Greenhouse gas generated by animal manure management is divided into direct greenhouse gas emission by decomposition of manure and greenhouse gas effect in the entire process due to energy use by operating manure management systems. By obtaining and summing them, the whole process greenhouse gas emission factor for the livestock manure treatment system was calculated.Results and Discussion:Among the pig manure management systems, the greenhouse gas emission factors for composting, purification and liquefaction were calculated as 128 kgCO2-eq./ton, 123 kgCO2-eq./ton, 119 kgCO2-eq./ton, respectively. It was analyzed that 20.7% to 24.1% of greenhouse gas emissions generated in the process of managing manure were due to electricity use. As a result of analyzing the change in the emission factor according to the change in GHG emissions of the national electric power according to the 8th Basic Plan for Electricity Supply and Demand, a change in emission of about 6% was confirmed. Based on the results of this study and analysis of direct GHG emissions from manure management in three major Western European countries, France, Germany, and the Netherlands, based on the manure management emission factor in 2017, GHG emissions of 48.9% to 70% compared to this study in all countries.Conclusions:In the greenhouse gas emission factor for the pig manure management system, the greenhouse gas emission from energy used in the manure management system operation represents a contribution of more than 20%, so improvement of energy efficiency of the manure management system in the future can contribute to the reduction of greenhouse gas emission. As the GHG emissions of the pig manure management system are expected to change substantially according to the change in the power grid composition ratio according to the 8th Basic Plan for Electricity Supply and Demand, it is necessary to study the application plan in preparation for the implementation of product environmental footprint certification for livestock products in the future. As a result of comparing direct GHG emissions by manure management with major Western European countries, the difference in emissions was found to be large, suggesting the need to develop a Tier 2 emission factor suitable for the situation in Korea.
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Zhang, Ya, and You Liang Mao. "On Carbon Emissions Measure and its Influencing Factors of Yunnan Province: 1998-2008." Applied Mechanics and Materials 99-100 (September 2011): 539–45. http://dx.doi.org/10.4028/www.scientific.net/amm.99-100.539.
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Coming up with the idea of low-carbon economy, numerous studies both at home and abroad on carbon emissions have emerged, nonetheless of which seldom are studies aiming at specific executive agencies and supervisory authorities of government development plan at provincial administrative area level. This paper, by using calculation formulas in carbon emission calculation guide of IPCC and carbon emission coefficient default value, measured the carbon emissions of Yunnan Province during 1998 and 2008 and analyzed relative influencing factors. The study shows economic growth and industrial restructuring increase the carbon emission intensity which is not remarkably affected by energy restructuring. The key to decrease carbon emission intensity is enhancing energy efficiency.
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Yu, Tai Yi, I. Cheng Chang, Mei Yin Hwa, and Li Teh Lu. "Estimation of Air Pollutant Emissions from Mobile Sources with Three Emission Factors Models." Advanced Materials Research 550-553 (July 2012): 2378–81. http://dx.doi.org/10.4028/www.scientific.net/amr.550-553.2378.
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Vehicle emissions from mobile sources are major contributors to air pollution and varied with vehicle types, vehicle styles, traveled miles, temperature, oil types and the methods of operation and management. This study performs three emission factor models, Mobile-Taiwan 2, Mobile6.2 and EFDB to calculate emission factor of mobile sources from year 1986 to 2011. The emissions of primary air pollutants, MIRs and CO2emitted from mobile sources were calculated. The contribution ratios of varied vehicle types for different air pollutants would be compared and analyzed. Estimated emissions from mobile sources were 32.2, 177, 643, 197 and 401 kilotons/y for PM10, NOx, CO, THC and MIR for 2000; 31.3, 115, 305, 114 and 227 kilotons/y for 2011. Emissions of traditional air pollutants presented a decreasing trend because of fourth-stage emission standards for mobiles sources and CO2 revealed an increasing trend. According to presented control technology for greenhouse gases on mobile sources, ratio of emission for year 2011 to 2000 would be 1.38-1.49.
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Holzinger, R., A. Lee, M. McKay, and A. H. Goldstein. "Seasonal variability of monoterpene emission factors for a ponderosa pine plantation in California." Atmospheric Chemistry and Physics 6, no. 5 (April 24, 2006): 1267–74. http://dx.doi.org/10.5194/acp-6-1267-2006.
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Abstract. Monoterpene fluxes have been measured over an 11 month period from June 2003 to April 2004. During all seasons ambient air temperature was the environmental factor most closely related to the measured emission rates. The monoterpene flux was modeled using a basal emission rate multiplied by an exponential function of a temperature, following the typical practice for modelling temperature dependent biogenic emissions. A basal emission of 1.0 μmol h−1 m−2 (at 30°C, based on leaf area) and a temperature dependence (β) of 0.12°C−1 reproduced measured summer emissions well but underestimated spring and winter measured emissions by 60–130%. The total annual monoterpene emission may be underestimated by ~50% when using a model optimized to reproduce monoterpene emissions in summer. The long term dataset also reveals an indirect connection between non-stomatal ozone and monoterpene flux beyond the dependence on temperature that has been shown for both fluxes.
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Guven, Denizhan, M. Özgür Kayalica, and Gülgün Kayakutlu. "CO2 emissions analysis for East European countries: the role of underlying emission trend." Environmental Economics 11, no. 1 (June 5, 2020): 67–81. http://dx.doi.org/10.21511/ee.11(1).2020.07.
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This paper aims to analyze the impact of energy consumption, economic structure, and manufacturing output on the CO2 emissions of East European countries by applying the Structural Time Series Model (STSM). Several explanatory factors are used to construct the model using annual data of the 1990–2017 period. The factors are: total primary energy supply, GDP per capita and manufacturing value added, and, finally, a stochastic Underlying Emission Trend (UET). The significant effects of all variables on CO2 emissions are detected. Based on the estimated functions, CO2 emissions of Belarus, Ukraine, Romania, Russia, Serbia, and Hungary will decrease, by 2027, to 53.2 Mt, 103.2 Mt, 36.1 Mt, 1528.2 Mt, 36 Mt, and 36.1 Mt, respectively. Distinct from other countries, CO2 emissions of Poland will extend to 312.2 Mt in 2027 due to the very high share of fossil-based supply (i.e., coal and oil) in Poland. The results also indicate that the most forceful factor in CO2 emissions is the total primary energy supply. Furthermore, for Poland, Romania, Hungary, and Belarus, the long-term impact of economic growth on CO2 emissions is negative, while it is positive for Russia, Ukraine, and Serbia. The highest long-term manufacturing value-added elasticity of CO2 emissions is calculated for Serbia and Belarus.
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Kang, Seongmin, Goeun Kim, Joonyoung Roh, and Eui-chan Jeon. "Ammonia Emissions from NPK Fertilizer Production Plants: Emission Characteristics and Emission Factor Estimation." International Journal of Environmental Research and Public Health 19, no. 11 (May 31, 2022): 6703. http://dx.doi.org/10.3390/ijerph19116703.
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Fertilizers are made from manure, but they are also produced through chemical processes. Fertilizer is an ammonia emission source; it releases ammonia when used. Ammonia is also emitted during the production process. Although many studies related to fertilizer application have been conducted, there are few research cases related to the production process and related emissions are not calculated. In this study, the ammonia emissions from NPK (nitrogen phosphorus Potassium oxide) fertilizer production facilities were checked through actual measurement and related characteristics were analyzed. In addition, emission factors were developed, and the necessity of developing emission factors was also confirmed. As a result of the development of the emission factor, it was found to be 0.001 kgNH3/ton, which is like the range of emission factors in related fields. The NPK ammonia emission factor of this study was found to be higher than the minimum emission factor currently applied in South Korea, and it was judged to be a level that can be used as an emission factor.
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Wang, Wang, Zhang, and Dang. "Provincial Carbon Emissions Efficiency and Its Influencing Factors in China." Sustainability 11, no. 8 (April 19, 2019): 2355. http://dx.doi.org/10.3390/su11082355.
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We calculated provincial carbon emissions efficiency and related influencing factors in China with the purpose of providing a reference for other developing countries to develop a green economy. Using panel data covering the period from 2004–2016 from 30 provinces in China, we calculated the carbon emission performance (CEP) and the technology gap ratio of carbon emission (TGR) with the data envelopment analysis (DEA) method and the meta-frontier model separately to analyze provincial carbon emissions efficiency in China. No matter which indicator was employed, we found that distinct differences exist in the eastern, the central, and the western regions of China, and the eastern region has the highest carbon emission performance, followed by the central and the western regions. Then, the panel data Tobit regression model was employed to analyze the influencing factors of carbon emissions efficiency, and we found that scale economy, industrial structure, degree of opening up, foreign direct investment (FDI), energy intensity, government interference, ownership structure, and capital-labor ratio have different impacts on the carbon emission efficiency in different regions of China, which indicates different policies should be implemented in different regions.
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Pang, Kaili, Xiangrui Meng, Shuai Ma, and Ziyuan Yin. "Characterization of Pollutant Emissions from Typical Material Handling Equipment Using a Portable Emission Measurement System." Atmosphere 12, no. 5 (May 5, 2021): 598. http://dx.doi.org/10.3390/atmos12050598.
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Non-road equipment has been an important source of pollutants that negatively affect air quality in China. An accurate emission inventory for non-road equipment is therefore required to improve air quality. The objective of this paper was to characterize emissions from typical diesel-fueled material handling equipment (loaders and cranes) using a portable emission measurement system. Instantaneous, modal, and composite emissions were quantified in this study. Three duty modes (idling, moving, and working) were used. Composite emission factors were estimated using modal emissions and time-fractions for typical duty cycles. Results showed that emissions from loaders and cranes were higher and more variable for the moving and working modes than the idling mode. The estimated fuel-based CO, HC, NO, and PM2.5 composite emission factors were 21.7, 2.7, 38.2, and 3.6 g/(kg-fuel), respectively, for loaders, and 8.7, 2.4, 28.3, and 0.3 g/(kg-fuel), respectively, for cranes. NO emissions were highest and should be the main focus for emission controls. CO, HC, NO, and PM2.5 emissions measured were different from emission factors in the US Environmental Protection Agency NONROAD model and the Chinese National Guideline for Emission Inventory Development for Non-Road Equipment. This indicates that improving emission inventory accuracy for non-road equipment requires more real-world emission measurements.
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Vogt, M., E. D. Nilsson, L. Ahlm, E. M. Mårtensson, and C. Johansson. "The relationship between 0.25–2.5 μm aerosol and CO<sub>2</sub> emissions over a city." Atmospheric Chemistry and Physics Discussions 10, no. 9 (September 9, 2010): 21521–45. http://dx.doi.org/10.5194/acpd-10-21521-2010.
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Abstract. Unlike exhaust emissions, non-exhaust traffic emissions are completely unregulated and there are large uncertainties in the non-exhaust emission factors required to estimate the emissions of these aerosols. This study provides the first published results of direct measurements of size resolved emission factors for particles in the size range 0.25–2.5 μm using a new approach deriving aerosol emission factors from the CO2 emission fluxes. Because the aerosol and CO2 emissions have a common source and because the CO2 emission per fuel or traffic amount are much less uncertain than the aerosol emissions, this approach has obvious advantages. Therefore aerosol fluxes were measured during one year using the eddy covariance method at the top of a 118 m high communication tower over Stockholm, Sweden. Maximum CO2 and particle fluxes coincides with the wind direction with densest traffic within the footprint area. Negative fluxes (uptake of CO2 and deposition of particles) coincides with an urban forest area. The fluxes of CO2 were used to obtain emission factors for particles by assuming that the CO2 fluxes could converted to amounts of fuel burnt. The estimated emission factors for the fleet mix in the measurement area are, in number 1.4×1011 [particle veh−1 km−1]. Assuming spherical particles of density 1600 kg/m3 this corresponds to 27.5 mg veh−1 km−1. Wind speed influence the emission factor indicating that wind induced turbulence may be important.
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Sun, Lili, Huijuan Cui, and Quansheng Ge. "Driving Factors and Future Prediction of Carbon Emissions in the ‘Belt and Road Initiative’ Countries." Energies 14, no. 17 (September 1, 2021): 5455. http://dx.doi.org/10.3390/en14175455.
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‘Belt and Road Initiative’ (B&R) countries play critical roles in mitigating global carbon emission under the Paris agreement, but their driving factors and feasibility to reduce carbon emissions remain unclear. This paper aims to identify the main driving factors (MDFs) behind carbon emissions and predict the future emissions trajectories of the B&R countries under different social-economic pathways based on the extended STIRPAT (stochastic impacts by regression on population, affluence, and technology) model. The empirical results indicate that GDP per capita and energy consumption structure are the MDFs that promote carbon emission, while energy intensity improvement is the MDF that inhibits carbon emission. Population, as another MDF, has a dual impact across countries. The carbon emissions in all B&R countries are predicted to increase from SSP1 to SSP3, but emissions trajectories vary across countries. Under the SSP1 scenario, carbon emissions in over 60% of B&R countries can peak or decline, and the aggregated peak emissions will amount to 21.97 Gt in 2030. Under the SSP2 scenario, about half of the countries can peak or decline, while their peak emissions and peak time are both higher and later than SSP1, the highest emission of 25.35 Gt is observed in 2050. Conversely, over 65% of B&R countries are incapable of either peaking or declining under the SSP3 scenario, with the highest aggregated emission of 33.10 Gt in 2050. It is further suggested that decline of carbon emission occurs when the inhibiting effects of energy intensity exceed the positive impacts of other MDFs in most B&R countries.
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Sirithian, Duanpen, Pantitcha Thanatrakolsri, and Surangrat Pongpan. "CO2 and CH4 Emission Factors from Light-Duty Vehicles by Fuel Types in Thailand." Atmosphere 13, no. 10 (September 28, 2022): 1588. http://dx.doi.org/10.3390/atmos13101588.
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Correct emission factors are necessary for evaluating vehicle emissions and making proper decisions to manage air pollution in the transportation sector. In this study, using a chassis dynamometer at the Automotive Emission Laboratory, CO2 and CH4 emission factors of light-duty vehicles (LDVs) were developed by fuel types and driving speeds. The Bangkok driving cycle was used for the vehicle’s running and controlling under the standard procedure. Results present that the highest average CO2 and CH4 emission factors were emitted from LDG vehicles, at 232.25 g/km and 9.50 mg/km, respectively. The average CO2 emission factor of the LDD vehicles was higher than that of the LDG vehicles, at 182.53 g/km and 171.01 g/km, respectively. Nevertheless, the average CH4 emission factors of the LDD vehicles were lower than those of the LDG vehicles, at 2.21 mg/km and 3.02 mg/km, respectively. The result reveals that the lower driving speed emitted higher CO2 emission factors for LDVs. It reflects the higher fuel consumption rate (L/100 km) and the lower fuel economy rate (km/L). Moreover, the portion of CO2 emissions emitted from LDVs was 99.96% of total GHG emissions. The CO2 and CH4 emission factors developed through this study will be used to support the greenhouse gas reduction policies, especially concerning the CO2 and CH4 emitted from vehicles. Furthermore, it can be used as a database that encourages Thailand’s green transportation management system.
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Misztal, Pawel K., Jeremy C. Avise, Thomas Karl, Klaus Scott, Haflidi H. Jonsson, Alex B. Guenther, and Allen H. Goldstein. "Evaluation of regional isoprene emission factors and modeled fluxes in California." Atmospheric Chemistry and Physics 16, no. 15 (August 2, 2016): 9611–28. http://dx.doi.org/10.5194/acp-16-9611-2016.
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Abstract. Accurately modeled biogenic volatile organic compound (BVOC) emissions are an essential input to atmospheric chemistry simulations of ozone and particle formation. BVOC emission models rely on basal emission factor (BEF) distribution maps based on emission measurements and vegetation land-cover data but these critical input components of the models as well as model simulations lack validation by regional scale measurements. We directly assess isoprene emission-factor distribution databases for BVOC emission models by deriving BEFs from direct airborne eddy covariance (AEC) fluxes (Misztal et al., 2014) scaled to the surface and normalized by the activity factor of the Guenther et al. (2006) algorithm. The available airborne BEF data from approx. 10 000 km of flight tracks over California were averaged spatially over 48 defined ecological zones called ecoregions. Consistently, BEFs used by three different emission models were averaged over the same ecoregions for quantitative evaluation. Ecoregion-averaged BEFs from the most current land cover used by the Model of Emissions of Gases and Aerosols from Nature (MEGAN) v.2.1 resulted in the best agreement among the tested land covers and agreed within 10 % with BEFs inferred from measurement. However, the correlation was sensitive to a few discrepancies (either overestimation or underestimation) in those ecoregions where land-cover BEFs are less accurate or less representative for the flight track. The two other land covers demonstrated similar agreement (within 30 % of measurements) for total average BEF across all tested ecoregions but there were a larger number of specific ecoregions that had poor agreement with the observations. Independently, we performed evaluation of the new California Air Resources Board (CARB) hybrid model by directly comparing its simulated isoprene area emissions averaged for the same flight times and flux footprints as actual measured area emissions. The model simulation and the observed surface area emissions agreed on average within 20 %. We show that the choice of model land-cover input data has the most critical influence on model-measurement agreement and the uncertainty in meteorology inputs has a lesser impact at scales relevant to regional air quality modeling.
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Kang, Seongmin, Yoon-Jung Hong, Seong-Dong Kim, and Eui-Chan Jeon. "Ammonia Emission Factors and Uncertainties of Coke Oven Gases in Iron and Steel Industries." Sustainability 12, no. 9 (April 25, 2020): 3518. http://dx.doi.org/10.3390/su12093518.
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In this study, uncertainties related to NH3 concentration, emission factor, and emission factor estimation in the exhaust gas of the steel sintering furnace using COG (coke oven gas) among the by-product gas generated in steel production was estimated to identify the missing source. By measuring the NH3 concentration in the exhaust gas of steel sintering furnace using COG, a concentration between 0.02 and 0.12 ppm was found, with an average concentration of 0.06 ppm, confirming the emissions of NH3. Using this measurement of the NH3 concentration, an NH3 emission factor of 0.0061 kg NH3/ton was derived. The uncertainty of the developed NH3 emission factor of the sintering furnace using COG was analyzed using a Monte Carlo simulation. Consequently, the uncertainty range of NH3 emission factor of the sintering furnace using COG was derived to be −11.4% to +12.89% at the 95% confidence level. According to the results of this study, NH3 emissions occur from the use of COG, yielding values higher than the NH3 emission factor resulting from the use of LNG(liquefied natural gas) in combustion facilities. It should be recognized that it is a missing emission source and the corresponding emission should be calculated.
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Mastepanov, M., C. Sigsgaard, T. Tagesson, L. Ström, M. P. Tamstorf, M. Lund, and T. R. Christensen. "Revisiting factors controlling methane emissions from high-arctic tundra." Biogeosciences Discussions 9, no. 11 (November 13, 2012): 15853–900. http://dx.doi.org/10.5194/bgd-9-15853-2012.
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Abstract. Among the numerous studies of methane emission from northern wetlands the number of measurements carried on at high latitudes (north of the Arctic Circle) is very limited, and within these there is a bias towards studies of the growing season. Here we present results of five years of automatic chamber measurements at a high-arctic location in Zackenberg, NE Greenland covering both the growing seasons and two months of the following freeze-in period. The measurements show clear seasonal dynamics in methane emission. The start of the growing season increase in CH4 fluxes were strongly related to the date of snow melt. The greatest variation in fluxes between the study years were observed during the first part of the growing season. Somewhat surprisingly this variability could not be explained by commonly known factors controlling methane emission, i.e. temperature and water table position. Late in the growing season CH4 emissions were found to be very similar between the study years (except the extremely dry 2010) despite large differences in climatic factors (temperature and water table). Late-season bursts of CH4 coinciding with soil freezing in the autumn were observed at least during three years between 2006 and 2010. The accumulated emission during the freeze-in CH4 bursts was comparable in size with the growing season emission for the year 2007, and about one third of the growing season emissions for the years 2009 and 2010. In all three cases the CH4 burst was accompanied by a~corresponding episodic increase in CO2 emission, which can compose a significant contribution to the annual CO2 flux budget. The most probable mechanism of the late season CH4 and CO2 bursts is physical release of gases, accumulated in the soil during the growing season. In this study we investigate the drivers and links between growing season and late season fluxes. The reported surprising seasonal dynamics of CH4 emissions at this site show that there are important occasions where conventional knowledge on factors controlling methane emissions is overruled by other processes, acting in longer than seasonal time scales. Our findings suggest the importance of multiyear studies with continued focus on shoulder seasons.
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Bai, Caiquan, Yuehua Mao, Yuan Gong, and Chen Feng. "Club Convergence and Factors of Per Capita Transportation Carbon Emissions in China." Sustainability 11, no. 2 (January 21, 2019): 539. http://dx.doi.org/10.3390/su11020539.
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China is the largest carbon dioxide emitter in the world, and reducing China’s transportation carbon emissions is of great significance for the world. Using the Chinese provincial data from 2005–2015, this article analyzes the convergence characteristics of per capita transportation carbon emissions in China. It employs the log t regression test method and the club clustering algorithm developed by Phillips and Sul (2007) to separate the provinces and municipalities in China into three convergence clubs with different transportation carbon emission levels and one divergent group. Among them, the divergent group consisted of Beijing and Liaoning; the high carbon emission club consisted of Shanghai and Inner Mongolia; the low carbon emission club consisted of Jiangxi, Henan, Shandong, Hebei, and Sichuan; the medium carbon emission club consisted of the remaining 21 provinces and municipalities. On this basis, this article adopts the Ordered Logit model to explore factors influencing the formation of the convergence clubs. The regression results showed that the per capita transportation carbon emissions in the provinces with a high energy intensity of the transportation sector, a high urbanization level, or a high fixed assets investment intensity of the transportation sector tended to converge into the high carbon emission club.
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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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Ma, Zhongmin, Yuanyuan Yang, Peiting Sun, Hui Xing, Shulin Duan, Hongfei Qu, and Yongjiu Zou. "Analysis of Marine Diesel Engine Emission Characteristics of Different Power Ranges in China." Atmosphere 12, no. 9 (August 27, 2021): 1108. http://dx.doi.org/10.3390/atmos12091108.
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In order to accurately assess China’s port air pollution caused by the shipping industry, two main methods can be used to calculate the emissions of ships, including the method based on ship fuel consumption and the method based on ship activities. Both methods require accurate diesel engine emission factors, or specific emissions. In this paper, the emission characteristics of NOX, CO, CO2 and THC from 197 domestic marine diesel engines were tested under bench test conditions by a standard emission measurement system. The diesel engines were divided into six Classes, A~F, according to their power distribution, and the fuel-based emission factors and energy-based emission factors of marine main engine and auxiliary engine meeting IMO NOX Tier II standards were given. The results showed that the main engine fuel-based emission factors of NOX, CO, CO2 and THC from Class A to Class F were 33.25~76.58, 2.70~4.33, 3123.92~3166.47 and 1.10~2.64 kg/t-fuel, respectively; and the energy-based emission factors were 6.57~11.75, 0.56~0.81, 530.28~659.71 and 0.18~0.61 g/kW h, respectively. The auxiliary engine fuel-based emission factors of NOX, CO, CO2 and THC from Class A to Class D were 27.17~39.81, 2.66~5.12, 3113.01~3141.34 and 1.16~2.87 kg/t-fuel respectively; and their energy-based emission factors were 6.06~8.33, 0.47~0.77, 656.86~684.91 and 0.21~0.61 g/kW h, respectively. The emission factors for different types of diesel engines were closely related to the diesel engine load, and the relation between them could be expressed by quadratic polynomial or power function. The results of this paper provide valuable data for the estimation of waterway transportation exhaust emissions and comprehensive understanding of the emission characteristics of marine diesel engines.
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de Carvalho, João Andrade, André de Castro, Gutemberg Hespanha Brasil, Paulo Antonio de Souza, and Andrés Z. Mendiburu. "CO2 Emission Factors and Carbon Losses for Off-Road Mining Trucks." Energies 15, no. 7 (April 5, 2022): 2659. http://dx.doi.org/10.3390/en15072659.
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There are myriad questions that remain to be answered in greenhouse gas (GHG) emissions trading. This article addresses carbon dioxide (CO2) emission factors and carbon losses from heavy equipment that is used to transport ores. Differences occurred between the Intergovernmental Panel for Climate Change (IPCC) emission factor and those that were obtained by considering incomplete combustion and on-site exhaust concentration measurements. Emissions from four off-road vehicles were analyzed. They operated at idle (loading, unloading, and queuing) and in motion (front and rear, loaded and unloaded). The results show that the average CO2 emission factors can be as low as 64.8% of the IPCC standard value for diesel fuel. On the other hand, carbon losses can be up to 33.5% and energy losses up to 25.5%. To the best of the authors’ knowledge, the method that was developed here is innovative, simple, useful, and easily applicable in determining CO2 emission factors and fuel losses for heavy machinery.
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Mihajlovic, Marina, Dimitrije Stevanovic, Jovan Jovanovic, and Mica Jovanovic. "VOC emission from oil refinery and petrochemical wastewater treatment plant estimation." Chemical Industry 67, no. 2 (2013): 365–73. http://dx.doi.org/10.2298/hemind120427077s.
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The introduction of environmental legislation improvement for industrial producers in Serbia, notably the Integrated Pollution Prevention Control (IPPC) license, will oblige the industrial producers to provide annual report on the pollutant emissions into the environment, as well as to pay certain environment fee. Wastewater treatment plant can be a significant source of volatile organic compounds (VOCs) diffuse emissions, which are difficult to measure directly. In the near future reporting obligations might expend to benzene and other VOCs. This paper deals with gaseous emissions calculations from API separator based on the emission factors and the adequate software applications. The analyzed results show that the estimated emission values differ depending on the applied method. The VOC emissions have been estimated using US EPA and CONCAWE emissions factors. The calculated emissions range from 40 to 4500 tons/year for oil refinery WWTP of 2,000,000 m3/year. The calculations of benzene and toluene emissions have been performed using three methods: US EPA emission factors, WATER9, and Toxchem+ software. The calculated benzene and toluene emissions range from 5.5-60 and 0.7-20 tons/year, respectively. The highest emission values were obtained by the US EPA emission factors, while the lowest values were the result of Toxchem+ analysis. The sensitivity analysis of obtained results included the following parameters: flow, temperature, oil content, and the concentration of benzene and toluene in the effluent. Wide range of results indicates the need for their official interpretation for the conditions typical for Serbia, thus establishing adequate national emission factors for future utilization of the ?polluter pays principle? on the VOC and benzene emissions.
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Lou, Di Ming, Si Li Qian, Zhi Yuan Hu, and Pi Qiang Tan. "On-Road Gaseous Emission Characteristics of the Bus Based on DOC + CDPF Technology." Advanced Materials Research 726-731 (August 2013): 2234–40. http://dx.doi.org/10.4028/www.scientific.net/amr.726-731.2234.
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In this paper, an experimental investigation was conducted using Vehicle Emission Testing System to study on-road gaseous emissions (CO, THC, NOX, CO2) characteristics based on diesel oxidation catalyst (DOC) and catalyzed diesel particulate filter (CDPF) technology. The results show that after the implementation of DOC + CDPF device, CO, THC emissions are significantly reduced, while the NOX, CO2 emissions remain almost the same. Under steady conditions, the reduction percentages of CO, THC, NOX, CO2 emission factors are 56.0%, 66.0%, 18.3%, 17.5%, respectively. Under transient operation conditions, the reduction percentages of CO, THC, NOX, CO2 emission factors are found to be 43.2%, 65.9%, 13.7%, 10.9%, respectively. Addition to the THC emission factor, the emission factors of CO, NOX and CO2 in transient operation conditions are higher than steady conditions.
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Lei, Y., Q. Zhang, K. B. He, and D. G. Streets. "Primary aerosol emission trends for China, 1990–2005." Atmospheric Chemistry and Physics Discussions 10, no. 7 (July 12, 2010): 17153–212. http://dx.doi.org/10.5194/acpd-10-17153-2010.
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Abstract. An inventory of anthropogenic primary aerosol emissions in China was developed for 1990–2005 using a technology-based approach. Taking into account changes in the technology penetration within industry sectors and improvements in emission controls driven by stricter emission standards, a dynamic methodology was derived and implemented to estimate inter-annual emission factors. Emission factors of PM2.5 decreased by 7%–69% from 1990 to 2005 in different industry sectors of China, and emission factors of TSP decreased by 18%–80% as well. Emissions of PM2.5, PM10 and TSP presented similar trends: increased in the first six years of 1990s and decreased until 2000, then increased again in the following years. Emissions of TSP reached a historical high (35.5 Tg) in 1996, while the peak of PM10 (18.8 Tg) and PM2.5 (12.7 Tg) emissions occurred in 2005. Although various emission trends were identified across sectors, the cement industry and biofuel combustion in the residential sector were consistently the largest sources of PM2.5 emissions, accounting for 53%–62% of emission over the study period. The non-metallic mineral product industry, including the cement, lime and brick industries, accounted for 54%–63% of national TSP emissions. There were no significant trends of BC and OC emissions until 2000, but the increase after 2000 brought the historical high of BC (1.51 Tg) and OC (3.19 Tg) emissions in 2005. Although significant improvements in the estimation of primary aerosols are presented, there still exist large uncertainties. More accurate and detailed activity information and emission factors based on local tests are essential to further improve emission estimates, this especially being so for the brick and coke industries, as well as for coal-burning stoves and biofuel usage in the residential sector.
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Hu, Xiaodong, Ximing Zhang, Lei Dong, Hujun Li, Zheng He, and Huihua Chen. "Carbon Emission Factors Identification and Measurement Model Construction for Railway Construction Projects." International Journal of Environmental Research and Public Health 19, no. 18 (September 9, 2022): 11379. http://dx.doi.org/10.3390/ijerph191811379.
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Carbon emissions have become a focus of political and academic concern in the global community since the launch of the Kyoto Protocol. As the largest carbon emitter, China has committed to reaching the carbon peak by 2030 and carbon neutrality by 2060 in the 75th United Nations High-level Meeting. The transport sector needs to be deeply decarbonized in China to achieve this goal. Previous studies have shown that the carbon emissions of the railway sector are small compared to highways, waterways, and civil aviation. However, these studies only consider the operation stage and do not consider the carbon emissions caused by large-scale railway infrastructure construction during the construction stage. As an essential source of carbon emissions and the focus of emissions reduction, the carbon emission of railway construction projects (RCPs) is in urgent need of relevant research. Based on a systematic literature review (SLR), this paper sorts out the carbon emission factors (CEFs) related to RCPs; combines semi-structured expert interviews to clarify the carbon emissions measurement boundary of RCPs; modifies and calibrates CEFs; constructs the carbon emission measurement model of RCPs including building material production stage, building material transportation stage, and construction stage; and conducts empirical analysis to validate carbon emission factors and measurement models. This study effectively complements the theoretical research on CEFs and measurement models in the construction stage of railway engineering and contributes to guiding the construction of low-carbon railways practically.
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Li, Xiang, Timothy R. Dallmann, Andrew A. May, and Albert A. Presto. "Seasonal and Long-Term Trend of on-Road Gasoline and Diesel Vehicle Emission Factors Measured in Traffic Tunnels." Applied Sciences 10, no. 7 (April 3, 2020): 2458. http://dx.doi.org/10.3390/app10072458.
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Emissions of gaseous and particulate pollutants from on-road gasoline and diesel vehicles were measured in a traffic tunnel under real-world driving conditions. Emission factors were attributed to gasoline and diesel vehicles using linear regression against the fraction of fuel consumed by diesel vehicles (% fuelD). We measured 67% higher NOx emissions from gasoline vehicles in winter than in spring (2 versus 1.2 g NO2 kg fuel−1). Emissions of CO, NOx, and particulate matter from diesel vehicles all showed impacts of recent policy changes to reduce emissions from this source. Comparison of our measurements to those of a previous study ~10 years prior in a nearby traffic tunnel on the same highway showed that emission factors for both gasoline and diesel vehicles have fallen by 50–70%. To further confirm this long-term trend, we summarized emission factors measured in previous tunnel studies in the U.S. since the 1990s. More restrictive emission standards are effective at reducing emissions from both diesel and gasoline vehicles, and decreases in observed emissions can be mapped to specific vehicle control policies. The trend of diesel-to-gasoline emission factor ratios revealed changes in the relative importance of vehicle types, though fuel-specific emission factors of NOx and elemental carbon (EC) are still substantially larger (~5–10 times) for diesel vehicles than gasoline vehicles.
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Ho, Dzung Minh, and Thang Xuan Dinh. "ESTIMATION OF AIR POLLUTANTS EMISSION FACTORS FOR VEHICLES ON ROAD TRAFFIC SUITABLE WITH HOCHIMINH CITY CONDITION." Science and Technology Development Journal 13, no. 3 (September 30, 2010): 5–18. http://dx.doi.org/10.32508/stdj.v13i3.2138.
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The estimation of emissions depends strongly on the quality of the emission factors used for the calculations. It is necessary to find method for estimation of emission factors from road traffic to calculate the emissions of air pollutants from transportation activity in Hochiminh City (HCMC). From the research results, suitable method and tracer were selected. Emission factors of 15 VOCs from C2-C6, NOx, and CO from road traffic in HCMC were estimated. The measurement campaign was carried out in 3/2 street., distrist 10, HCMC from 10h00 to 22h00 per day. Three VOCs compounds with high average emission factors were hexane (59,7 9,2 mg/km.veh.), i-pentane (52,7 7,4 mg/km.veh.) and 3-methylpentane (36,1 3,6 mg/km.veh.). The average emission factor of NOx and CO were 0,20 0,03 g/km.veh and 23,37 6,61 g/km.veh, respectively. Besides, the emission factors of air pollutants for motorcycles, light duty vehicles and heavy duty vehicles were caculated by regression linear method.
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Huang, Junfeng, Jianbing Gao, Yufeng Wang, Ce Yang, and Chaochen Ma. "Real-World Pipe-Out Emissions from Gasoline Direct Injection Passenger Cars." Processes 11, no. 1 (December 27, 2022): 66. http://dx.doi.org/10.3390/pr11010066.
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The analysis of real-world emissions is necessary to reduce the emissions of vehicles during on-road driving. In this paper, the matrix of gasoline direct injection passenger cars is applied to analyze the real-world emissions. The results show that high acceleration and high speed conditions are major conditions for the particulate number emissions, and the particulate number emissions are positively correlated with torque and throttle opening. The catalyst temperature and saturation are important factors that affect nitrogen oxide emission. The nitrogen oxide emissions of low speed and low torque conditions cannot be ignored in real-world driving. The carbon dioxide emissions are positively correlated with acceleration, torque and throttle opening. Once the vehicles are in the acceleration condition, the carbon dioxide emissions increase rapidly. The vehicles with higher average emission factors are more susceptible to driving behaviors, and the differences in the emission factors are more obvious, leading to an increase in the difficulty of emission control.
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Zhao, Xiaochun, Mei Jiang, and Wei Zhang. "Decoupling between Economic Development and Carbon Emissions and Its Driving Factors: Evidence from China." International Journal of Environmental Research and Public Health 19, no. 5 (March 2, 2022): 2893. http://dx.doi.org/10.3390/ijerph19052893.
Full textAbstract:
Analyzing the relationship between economic development and carbon emissions is conducive to better energy saving and emission reduction. This study is based on the panel data of China’s carbon emissions, from 2009 to 2019, and quantitative analysis of the relationship between carbon emissions and economic development through the Tapio decoupling model and the Logarithmic Mean Divisia Index (LMDI) decomposition model. The results show that: First, carbon emission and economic development are increasing year by year, and the development trend of economic growth rate and carbon emission growth rate presents the characteristics of consistency and stage. Second, China’s carbon emissions and economic development are basically in a weak decoupling state, and carbon emissions and economic development are positively correlated. Third, there are significant differences in decoupling indices among the four regions, mainly in that the central region is better than the eastern region, the eastern region is better than the northeast region, the northeast region is better than the western region, and the development of provinces in the region is unbalanced. Fourth, from the perspective of driving factors, the elasticity of population size and economic intensity can restrain the decoupling of carbon emissions, while the elasticity of energy intensity and carbon intensity have a positive effect. Finally, according to the results of empirical analysis, this paper focuses on promoting China’s emission reduction and energy sustainable development from the aspects of developing low-carbon and zero carbon technology, supporting new energy industries and promoting the construction of a carbon emission trading market.
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Zhong, Mingchun, Linzhi Que, and Guofu Lian. "Empirical analysis of influencing factors of carbon emissions in transportation industry in Fujian Province, China." JUSTC 53, no. 1 (2023): 5. http://dx.doi.org/10.52396/justc-2022-0079.
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The transportation industry has become an important source of carbon emissions with rapid economic development and the acceleration of urbanization. Identifying the key factors of carbon emissions is crucial for energy conservation, emission reduction and green development in the transportation industry. Here, variance analysis was used to study the influencing factors of carbon emissions in the transportation industry in Fujian Province, China. The results showed that transportation efficiency have the most significant impact on carbon emissions, followed by carbon emission intensity in transportation, and then the transportation structure. Meanwhile, there was a significant interaction between transportation efficiency and structure. Therefore, innovative energy-saving and emission-reduction technologies for transportation efficiency should be studied as the focus for the green and low-carbon development of the transportation industry.
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Dai, S., X. Bi, L. Y. Chan, J. He, B. Wang, X. Wang, P. Peng, G. Sheng, and J. Fu. "Chemical and stable carbon isotopic composition of PM<sub>2.5</sub> from on-road vehicle emissions in the PRD region and implications for vehicle emission control policy." Atmospheric Chemistry and Physics 15, no. 6 (March 18, 2015): 3097–108. http://dx.doi.org/10.5194/acp-15-3097-2015.
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Abstract. Vehicle emissions are a major source of urban air pollution. In recent decade, the Chinese government has introduced a range of policies to reduce vehicle emissions. In order to understand the chemical characteristics of PM2.5 from on-road vehicle emissions in the Pearl River Delta (PRD) region and to evaluate the effectiveness of control policies on vehicle emissions, the emission factors of PM2.5 mass, elemental carbon (EC), organic carbon (OC), water-soluble organic carbon (WSOC), water-soluble inorganic ions (WSII), metal elements, organic compounds and stable carbon isotopic composition were measured in the Zhujiang tunnel of Guangzhou, in the PRD region of China in 2013. Emission factors of PM2.5 mass, OC, EC and WSOC were 92.4, 16.7, 16.4 and 1.31 mg vehicle−1 km−1 respectively. Emission factors of WSII were 0.016 (F-) ~ 4.17 (Cl−) mg vehicle−1 km−1, contributing about 9.8% to the PM2.5 emissions. The sum of 27 measured metal elements accounted for 15.2% of PM2.5 emissions. Fe was the most abundant metal element, with an emission factor of 3.91 mg vehicle−1 km−1. Emission factors of organic compounds including n-alkanes, polycyclic aromatic hydrocarbons, hopanes and steranes were 91.9, 5.02, 32.0 and 7.59 μg vehicle−1 km−1, respectively. Stable carbon isotopic composition δ13C value was −25.0‰ on average. An isotopic fractionation of 3.2‰ was found during fuel combustion. Compared to a previous study in Zhujiang tunnel in 2004, emission factors of PM2.5mass, EC, OC, WSII except Cl- and organic compounds decreased by 16.0 ~ 93.4%, which could be attributed to emission control policy from 2004 to 2013. However, emission factors of most of the metal elements increased significantly, which could be partially attributed to the changes in motor oil additives and vehicle conditions. There are no mandatory national standards to limit metal content from vehicle emissions, which should be a concern of the government. A snapshot of the 2013 characteristic emissions of PM2.5 and its constituents from the on-road vehicular fleet in the PRD region retrieved from our study would be helpful for the assessment of past and future implementations of vehicle emission control policy.
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Seckinger, Nils, and Peter Radgen. "Dynamic Prospective Average and Marginal GHG Emission Factors—Scenario-Based Method for the German Power System until 2050." Energies 14, no. 9 (April 28, 2021): 2527. http://dx.doi.org/10.3390/en14092527.
Full textAbstract:
Due to the continuous diurnal, seasonal, and annual changes in the German power supply, prospective dynamic emission factors are needed to determine greenhouse gas (GHG) emissions from hybrid and flexible electrification measures. For the calculation of average emission factors (AEF) and marginal emission factors (MEF), detailed electricity market data are required to represent electricity trading, energy storage, and the partial load behavior of the power plant park on a unit-by-unit, hourly basis. Using two normative scenarios up to 2050, different emission factors of electricity supply with regard to the degree of decarbonization of power production were developed in a linear optimization model through different GHG emission caps (Business-As-Usual, BAU: −74%; Climate-Action-Plan, CAP: −95%). The mean hourly German AEF drops to 182 gCO2eq/kWhel (2018: 468 gCO2eq/kWhel) in the BAU scenario by the year 2050 and even to 29 gCO2eq/kWhel in the CAP scenario with 3700 almost emission-free hours from power supply per year. The overall higher MEF decreases to 475 and 368 gCO2eq/kWhel, with a stricter emissions cap initially leading to a higher MEF through more gas-fired power plants providing base load. If the emission intensity of the imported electricity differs substantially and a storage factor is implemented, the AEF is significantly affected. Hence, it is not sufficient to use the share of RES in net electricity generation as an indicator of emission intensity. With these emission factors it is possible to calculate lifetime GHG emissions and determine operating times of sector coupling technologies to mitigate GHG emissions in a future flexible energy system. This is because it is decisive when lower-emission electricity can be used to replace fossil energy sources.