scholarly journals Russia's black carbon emissions: focus on diesel sources

2016 ◽  
Author(s):  
N. Kholod ◽  
M. Evans ◽  
T. Kuklinski
Keyword(s):  
Black Carbon ◽  
Emission Factors ◽  
Diesel Emissions ◽  
Polar Regions ◽  
Emission Model ◽  
Commercial Vehicles ◽  
Road Vehicles ◽  
Activity Data ◽  
Diesel Vehicles

Abstract. Black carbon (BC) is a significant climate forcer with a particularly pronounced forcing effect in polar regions, like the Russian Arctic. Diesel combustion is a major global source of BC emissions, accounting for 25–30 % of all BC emissions. The demand for diesel is growing in Russia, but Russian diesel emissions are poorly understood. This paper presents a detailed inventory of Russian BC emissions from diesel sources. Drawing on a complete Russian vehicle registry with detailed information about vehicle types and emission standards, this paper analyzes BC emissions from diesel on-road vehicles. We use the COPERT emission model with Russia-specific emission factors for all types of on-road vehicles. On-road diesel vehicles emitted 21 Gg of BC in 2014; heavy-duty trucks account for 70 % of the on-road BC emissions, while cars represent only 4 % (light commercial vehicles and buses account for the remainder). Using Russian activity data and fuel-based emission factors, the paper also presents BC emissions from diesel locomotives and ships, off-road engines in industry, construction and agriculture, and from diesel generators. The study also factors in the role of superemitters in BC emissions from diesel on-road vehicles and off-road sources. The total emissions from diesel sources in Russia are estimated to be 48 Gg of BC and 16 Gg of OC in 2014. Off-road diesel sources emitted 57 % of all diesel BC in Russia.

scholarly journals Russia's black carbon emissions: focus on diesel sources

2016 ◽  
Vol 16 (17) ◽  
pp. 11267-11281 ◽  
Author(s):  
Nazar Kholod ◽  
Meredydd Evans ◽  
Teresa Kuklinski
Keyword(s):  
Black Carbon ◽  
Road Transport ◽  
Emission Factors ◽  
Diesel Emissions ◽  
Polar Regions ◽  
Emission Model ◽  
Road Vehicles ◽  
Activity Data ◽  
Diesel Vehicles ◽  
Model Computer

Abstract. Black carbon (BC) is a significant climate forcer with a particularly pronounced forcing effect in polar regions such as the Russian Arctic. Diesel combustion is a major global source of BC emissions, accounting for 25–30 % of all BC emissions. While the demand for diesel is growing in Russia, the country's diesel emissions are poorly understood. This paper presents a detailed inventory of Russian BC emissions from diesel sources. Drawing on a complete Russian vehicle registry with detailed information about vehicle types and emission standards, this paper analyzes BC emissions from diesel on-road vehicles. We use the COPERT emission model (COmputer Programme to calculate Emissions from Road Transport) with Russia-specific emission factors for all types of on-road vehicles. On-road diesel vehicles emitted 21 Gg of BC in 2014: heavy-duty trucks account for 60 % of the on-road BC emissions, while cars represent only 5 % (light commercial vehicles and buses account for the remainder). Using Russian activity data and fuel-based emission factors, the paper also presents BC emissions from diesel locomotives and ships, off-road engines in industry, construction and agriculture, and generators. The study also factors in the role of superemitters in BC emissions from diesel on-road vehicles and off-road sources. The total emissions from diesel sources in Russia are estimated to be 49 Gg of BC and 17 Gg of organic carbon (OC) in 2014. Off-road diesel sources emitted 58 % of all diesel BC in Russia.

scholarly journals Real World Vehicle Emission Factors for Black Carbon Derived from Longterm In-Situ Measurements and Inverse Modelling

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 31
Author(s):  
Anne Wiesner ◽  
Sascha Pfeifer ◽  
Maik Merkel ◽  
Thomas Tuch ◽  
Kay Weinhold ◽  
...  
Keyword(s):  
Black Carbon ◽  
Real World ◽  
Direct Injection ◽  
Urban Pollution ◽  
Pollutant Dispersion ◽  
Road Transport ◽  
Emission Factors ◽  
Climate Modelling ◽  
Emission Model ◽  
Local Conditions

Black carbon (BC) is one of the most harmful substances within traffic emissions, contributing considerably to urban pollution. Nevertheless, it is not explicitly regulated and the official laboratory derived emission factors are barely consistent with real world emissions. However, realistic emission factors (EFs) are crucial for emission, exposure, and climate modelling. A unique dataset of 10 years (2009–2018) of roadside and background measurements of equivalent black carbon (eBC) concentration made it possible to estimate real world traffic EFs and observe their change over time. The pollutant dispersion was modelled using the Operational Street Pollution Model (OSPM). The EFs for eBC are derived for this specific measurement site in a narrow but densely trafficked street canyon in Leipzig, Germany. The local conditions and fleet composition can be considered as typical for an inner-city traffic scenario in a Western European city. The fleet is composed of 22% diesel and 77% petrol cars in the passenger car segment, with an unknown proportion of direct injection engines. For the mixed fleet the eBC EF was found to be 48 mg km−1 in the long-term average. Accelerated by the introduction of a low emission zone, the EFs decreased over the available time period from around 70 mg km−1 to 30–40 mg km−1. Segregation into light (<3.5 t) and heavy (>3.5 t) vehicles resulted in slightly lower estimates for the light vehicles than for the mixed fleet, and one order of magnitude higher values for the heavy vehicles. The found values are considerably higher than comparable emission standards for particulate matter and even the calculations of the Handbook Emission Factors for Road Transport (HBEFA), which is often used as emission model input.

scholarly journals Supplementary material to "Emission Factors of Black Carbon and Co-pollutants from Diesel Vehicles in Mexico City"

2017 ◽  
Author(s):  
Miguel Zavala ◽  
Luisa T. Molina ◽  
Tara I. Yacovitch ◽  
Edward C. Fortner ◽  
Joseph R. Roscioli ◽  
...  
Keyword(s):  
Black Carbon ◽  
Mexico City ◽  
Emission Factors ◽  
Diesel Vehicles ◽  
Supplementary Material

Mitigation potential of black carbon emissions from on-road vehicles in China

2021 ◽  
Vol 278 ◽  
pp. 116746
Author(s):  
Shaojun Zhang ◽  
Xiaomeng Wu ◽  
Xuan Zheng ◽  
Yifan Wen ◽  
Ye Wu
Keyword(s):  
Black Carbon ◽  
Carbon Emissions ◽  
Road Vehicles ◽  
Mitigation Potential

scholarly journals The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic

2021 ◽  
Author(s):  
Francesco Piccialli ◽  
Vincenzo Schiano di Cola ◽  
Fabio Giampaolo ◽  
Salvatore Cuomo
Keyword(s):  
Artificial Intelligence ◽  
Clinical Trials ◽  
Digital Transformation ◽  
Daily Activities ◽  
Commercial Vehicles ◽  
Human Skills ◽  
To Come ◽  
Complex Scenario ◽  
The Impact

AbstractThe first few months of 2020 have profoundly changed the way we live our lives and carry out our daily activities. Although the widespread use of futuristic robotaxis and self-driving commercial vehicles has not yet become a reality, the COVID-19 pandemic has dramatically accelerated the adoption of Artificial Intelligence (AI) in different fields. We have witnessed the equivalent of two years of digital transformation compressed into just a few months. Whether it is in tracing epidemiological peaks or in transacting contactless payments, the impact of these developments has been almost immediate, and a window has opened up on what is to come. Here we analyze and discuss how AI can support us in facing the ongoing pandemic. Despite the numerous and undeniable contributions of AI, clinical trials and human skills are still required. Even if different strategies have been developed in different states worldwide, the fight against the pandemic seems to have found everywhere a valuable ally in AI, a global and open-source tool capable of providing assistance in this health emergency. A careful AI application would enable us to operate within this complex scenario involving healthcare, society and research.

Particulate mass and number emission factors for road vehicles based on literature data and relevant gap filling methods

2017 ◽  
Vol 168 ◽  
pp. 75-89 ◽  
Author(s):  
Ilias Vouitsis ◽  
Leonidas Ntziachristos ◽  
Christos Samaras ◽  
Zissis Samaras
Keyword(s):  
Emission Factors ◽  
Gap Filling ◽  
Road Vehicles ◽  
Particulate Mass

scholarly journals Determination of car on-road black carbon and particle number emission factors and comparison between mobile and stationary measurements

2015 ◽  
Vol 8 (1) ◽  
pp. 43-55 ◽  
Author(s):  
I. Ježek ◽  
L. Drinovec ◽  
L. Ferrero ◽  
M. Carriero ◽  
G. Močnik
Keyword(s):  
Black Carbon ◽  
Particle Number ◽  
Emission Factors ◽  
Emission Measurement ◽  
Stationary Method ◽  
Characteristic Value ◽  
Portable Emission Measurement System ◽  
Specific Distribution ◽  
Mobile Measurement

Abstract. We have used two methods for measuring emission factors (EFs) in real driving conditions on five cars in a controlled environment: the stationary method, where the investigated vehicle drives by the stationary measurement platform and the composition of the plume is measured, and the chasing method, where a mobile measurement platform drives behind the investigated vehicle. We measured EFs of black carbon and particle number concentration. The stationary method was tested for repeatability at different speeds and on a slope. The chasing method was tested on a test track and compared to the portable emission measurement system. We further developed the data processing algorithm for both methods, trying to improve consistency, determine the plume duration, limit the background influence and facilitate automatic processing of measurements. The comparison of emission factors determined by the two methods showed good agreement. EFs of a single car measured with either method have a specific distribution with a characteristic value and a long tail of super emissions. Measuring EFs at different speeds or slopes did not significantly influence the EFs of different cars; hence, we propose a new description of vehicle emissions that is not related to kinematic or engine parameters, and we rather describe the vehicle EF with a characteristic value and a super emission tail.

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