Facteur d'émission | EPFL Graph Search

vignette|L'intensité carbone de l'électricité mesure la quantité de gaz à effet de serre émise par unité d'électricité produite. Elle est exprimée en grammes d'équivalent par kilowatt-heure. vignette|Intensité carbone des économies nationales en kilogramme de par unité de PIB (2016). Un facteur d'émission est un ratio entre la quantité de polluants atmosphériques ou de gaz à effet de serre émis par un bien, un service ou une activité et une quantité unitaire de celui ou celle-ci. Ainsi, le facteur d'émission de dioxyde de carbone d'une centrale électrique peut être exprimé en grammes de dioxyde de carbone par kilowatt-heure d'électricité produite. Cet indicateur permet le calcul des émissions de certains polluants ou de gaz à effet de serre pour des systèmes complexes, à partir de la connaissance des facteurs d'émission de leurs composants. L'intensité carbone est un facteur d'émission de , notamment rapporté à la production d'une entreprise ou au PIB d'un pays. Dans le domain

High-resolution hybrid inversion of IASI ammonia columns to constrain US ammonia emissions using the CMAQ adjoint model

Jennifer Kaiser, Athanasios Nenes

Ammonia (NH3) emissions have large impacts on air quality and nitrogen deposition, influencing human health and the well-being of sensitive ecosystems. Large uncertainties exist in the "bottom-up" NH3 emission inventories due to limited source information and a historical lack of measurements, hindering the assessment of NH3-related environmental impacts. The increasing capability of satellites to measure NH3 abundance and the development of modeling tools enable us to better constrain NH3 emission estimates at high spatial resolution. In this study, we constrain the NH3 emission estimates from the widely used 2011 National Emissions Inventory (2011 NEI) in the US using Infrared Atmospheric Sounding Interferometer NH3 column density measurements (IASI-NH3) gridded at a 36 km by 36 km horizontal resolution. With a hybrid inverse modeling approach, we use the Community Multiscale Air Quality Modeling System (CMAQ) and its multiphase adjoint model to optimize NH3 emission estimates in April, July, and October. Our optimized emission estimates suggest that the total NH3 emissions are biased low by 26 % in 2011 NEI in April with overestimation in the Midwest and underestimation in the Southern States. In July and October, the estimates from NEI agree well with the optimized emission estimates, despite a low bias in hotspot regions. Evaluation of the inversion performance using independent observations shows reduced underestimation in simulated ambient NH3 concentra- tion in all 3 months and reduced underestimation in NH4 wet deposition in April. Implementing the optimized NH3 emission estimates improves the model performance in simulating PM2.5 concentration in the Midwest in April. The model results suggest that the estimated contribution of ammonium nitrate would be biased high in a priori NEI-based assessments. The higher emission estimates in this study also imply a higher ecological impact of nitrogen deposition originating from NH3 emissions.

COPERNICUS GESELLSCHAFT MBH2021

Alternative Methods for Assessing Air Quality and Energy Strategies for Developing Countries: A Case Study on Cuba

Jessie Madrazo Bacallao

The worldwide increasing energy consumption is mainly based on fossil fuel which leads to a large number of environmental problems. Indeed, the combustion of fossil fuels releases into the atmosphere different greenhouse gases and harmful pollutants which are responsible for climate change and cause air quality degradation. Moreover, fossil fuel resources are limited and their depletion will happen sooner or later. Governments of the whole world are urged to take relevant measures and policies for energy transition. To support their choices, different decision support approaches have been developed, mainly in industrialized countries. However, these approaches usually lack coherent integration and rely on expensive and often unavailable detailed data, especially in developing countries. This PhD aims at developing alternative methods for the assessment of air quality and energy strategies in the framework of developing countries. The developed methods are implemented in Cuba which seems an excellent test case to design and apply energy strategies for developing countries. The first part of this work deals with methods intended to reliable assess air quality. For this purpose, an air pollution measurement campaign was carried out in Havana. It provided data to implement and improve a pre-existing methodology capable of estimating Cuban vehicle emission factors. Statistical analysis indicated that traffic accounted for around 50% of particular matter concentration levels. Furthermore, vehicles pre-1980s were identified as the most polluting technologies at the street level. This work also demonstrates the usability of an emission inventory designed for air quality simulations. Benchmarking tools developed in the framework of the Forum for Air Quality Modelling in Europe helped to pinpoint differences between global and regional inventories, and identify where efforts should concentrate for improving emission data. This research also sets up simplified algebraic relationships (i.e. so-called Source-Receptor Relationship) capable of predicting the impacts on concentration levels resulting from regional emission abatement strategies, while being more time-efficient than traditional methods. The second part is dedicated to exploring scenarios for a reliable Cuban energy transition. To this end, the energy fluxes between resources, technologies and final demand were computed for the year 2015. A set of scenarios were then designed on the basis of different mixes of energy resources. These scenarios have been compared according to three criteria that seemed the most relevant for the country geopolitical and economic situation: energy security (degree of dependence from energy imports), sustainability of the energy resources and population exposure to harmful pollutants. Overall, the results indicated that energy security and sustainability increase with wind and solar penetration at different rates. A penetration rate of 20% of the demand significantly decreases fossil fuel requirements and imports. Once raised to 50%, Cuba can achieve complete energy independence. The scenario which fulfils 100% of the electricity demands from solar and wind resources shows the maximum of sustainability. Not surprisingly, the penetration of renewables had positive effects on air quality.

EPFL2018

Optimal Methodology to Generate Road Traffic Emissions for Air Quality Modeling

Quoc Bang Ho

Growing population, consuming a large amount of energy such as combustion of fossil fuel, increasing pollutant emissions in the atmosphere are the threats to the sustainable development of our planet in general, and of the air quality in particular. According to the World Health Organization, air pollution causes the death of more than 2 million people per year in developing countries, and millions of people also suffer from various respiratory illnesses. Road traffic is the main source of air pollution in cities and there are large uncertainties associated to this source of pollution. Different models are available to quantify the amount of pollutants released by road traffic. However, these models always require a large amount of information and work, and thus their use results expensive. These limitations are difficult for the study and the management of air quality in cities from the developing world. Thus, it is extremely difficult to design efficient abatement strategies to reduce air pollution. For this reason, it is necessary to develop a new methodology for generating road traffic emissions to contribute to a better management of the urban air quality. The first aim of this PhD thesis is to develop and to validate a new model for generating road traffic emissions in several steps with different levels of complexity. The developed model is called EMISENS. Its main specifications are: (i) EMISENS is able to compute a total amount of emissions and to distribute it in time and in space using a methodology which combines the top-down and the bottom-up approaches; (ii) the model is able to compute the emissions and the uncertainties within a reasonable computing time and (iii) the model formulation is based on well referenced methodology (COPERT IV). The validation of EMISENS model was carried out by its application over Strasbourg, France. The results of EMISENS have been compared with the results of the more complete and complex model Circul'air which is currently used to manage the Strasbourg air quality. After comparing the results of the two models, it appeared that they are very close. This example of application illustrates the capacity of EMISENS to calculate road traffic emission inventory (EI) for cities in developed countries as well as in developing countries. Further on, a complete EI is carried out over Ho Chi Minh City (HCMC) by applying an innovative methodology based on the application of the EMISENS model. HCMC is the largest city in Vietnam, it had more than 6 million inhabitants in 2006. It has more than three million vehicles and 28,500 factories in the city. High levels of air pollution are thus very often detected. The purpose of this part of the research consists in applying the EMISENS model to generate road traffic emissions. For the other emission sources, the top-down approach is used for generating the EI. The results show that the road traffic is the main emission source in the city. The motorcycles are responsible of the traffic emissions (94 % of CO, 68% of Non-Methane Volatile Organic Compound (NMVOC), 61 % of SO2 and 99 % of CH4). Two scenarios for reducing traffic emissions are evaluated to reduce the HCMC emissions for the year 2015 and 2020. In addition, two other scenarios are the Business as Usual scenarios for the year 2015 and 2020 are also studied to evaluate the traffic emissions in HCMC. The third part of this work consists in applying air quality models to the region of HCMC, the aim here is to study abatement strategies for emission reduction in the city. The results of the simulation show that the plume of O3 is developed in the north-western part of the city. These results are in good agreement with the measurements. Among the four previous emission scenarios, we chose only two reduction emission scenarios to study the effective abatement strategies for the year 2015 and 2020 in using air quality model. These two affective abatement strategies are adopted to help the local government to take decision for managing air quality in HCMC. The 100 Monte Carlo (MC) simulations are run for estimating the uncertainty in the results of air quality simulations. The results of these two abatement strategies showed that if the local government follows the emission control plan: For 2015, the O3 concentration in 2015 will be similar to the present O3 concentration. For 2020, the O3 concentration in 2020 will decrease of around 10% to 30% of O3 in comparison to the actual level. However, the O3 concentration in 2020 is still higher than standard limit. The developed methodology for generating road traffic emissions offers several advantages. It is able to calculate a road traffic emission for both developing and developed countries. The calculation is divided in several steps with different level of complexity. Therefore, this methodology provides the new approach to manage air quality in cities.

EPFL2010