• NEANIAS Atmospheric Research Community

Wall flow catalytic filters may represent an efficient solution for PM emission control of biomass-fired boilers and stoves, as they combine physical filtration processes with catalytic oxidative reactions. Moreover, such solution may be applied both in new equipment and in retrofit of existing appliances, and may be easily scaled according to the size of the boiler. The presented results were obtained from experimental tests carried out on filters with a silicon carbide matrix loaded with 20%wt of copper ferrite, and they aimed at evaluating the filter performance on fine PM abatement and the regeneration efficacy. The filters were tested in a customised sampling line at the exhaust of a 30 kW pellets boiler, and regeneration was specifically obtained by a high-temperature electrical heater. PM concentration in the flue gas was monitored by means of a real-time continuous detector and a cascade impactor. Tests showed high efficiency, over 90%, in PM reduction, and allowed to investigate in details the dynamics of regeneration and the effect of successive cycles, providing useful information in order to improve the service life and the performance of the catalytic filters. © 2016 ETA-Florence Renewable Energies.

however, there is no policy for the quantitative management of PM. Therefore, this study aimed to derive and propose an emission evaluation model to be used for the establishment of management policies for construction site PM emissions in South Korea by assuming structures as manufactured products. Therefore, this study derived a method of calculating the PM10, PM2.5, NOx, SOx, and VOCs emission factors for each type of equipment in construction sites and then estimated annual total emissions. In addition, this paper put forth a method for offsetting emission permission standards as the criteria for evaluating the adequacy of the estimated emissions. Finally, a model algorithm was proposed for evaluating emissions in advance during the construction planning phase by comparing the PM10, PM2.5, NOx, SOx, and VOCs emissions in construction sites with established standards Particulate matter (PM) has caused serious environmental issues in Asia, and various policies for systematic management of PM based on evaluation of the characteristics of emissions are being discussed. In Korea, where the damage of PM from construction sites is severe, only regulatory policies according to the concentration are being implemented the supplementary point of the algorithm is discussed for further studies.

Nationally Determined Contribution (NDC) Factsheets Raw JSON data used for the NDC Factsheets available at https://www.climate-resource.com/tools/ndcs. The previous versions of the NDC Factsheets are available at https://www.climatecollege.unimelb.edu.au/ndc-indc-factsheets and https://www.pik-potsdam.de/paris-reality-check/indc-factsheets/. Files included in the dataset For each country/region there are 6 files, each run with different settings to explore the different possible types of commitments. The format of the filename is as follows: {country/region code}_ndc_{date}_{conditionality}_{hotAir}.json Where country/region code is the 3 letter ISO-3166-1 code for the country or a shortcode for a region, conditionality is one of the following: conditional range (the high/low ambitions represent min-max range of commitments) unconditional For some countries, their pledged targets are greater than what a "no additional climate policy" reference scenario would suggest. The "hotAir" component of the filename state whether these hot air pledges are included or excluded (the reference scenario for a country is used instead). In addition to the archive of region/country level data, some additional global timeseries are provided in the "total_*.json" files. These files follow the same file template shown above.

Nationally Determined Contribution (NDC) Factsheets Raw JSON data used for the NDC Factsheets available at https://www.climate-resource.com/tools/ndcs. The previous versions of the NDC Factsheets are available at https://www.climatecollege.unimelb.edu.au/ndc-indc-factsheets and https://www.pik-potsdam.de/paris-reality-check/indc-factsheets/. Files included in the dataset For each country/region there are 6 files, each run with different settings to explore the different possible types of commitments. The format of the filename is as follows: {country/region code}_ndc_{date}_{conditionality}_{hotAir}.json Where country/region code is the 3 letter ISO-3166-1 code for the country or a shortcode for a region, conditionality is one of the following: conditional range (the high/low ambitions represent min-max range of commitments) unconditional For some countries, their pledged targets are greater than what a "no additional climate policy" reference scenario would suggest. The "hotAir" component of the filename state whether these hot air pledges are included or excluded (the reference scenario for a country is used instead). In addition to the archive of region/country level data, some additional global timeseries are provided in the "total_*.json" files. These files follow the same file template shown above.

Nationally Determined Contribution (NDC) Factsheets Raw JSON data used for the NDC Factsheets available at https://www.climate-resource.com/tools/ndcs. The previous versions of the NDC Factsheets are available at https://www.climatecollege.unimelb.edu.au/ndc-indc-factsheets and https://www.pik-potsdam.de/paris-reality-check/indc-factsheets/. Files included in the dataset For each country/region there are 6 files, each run with different settings to explore the different possible types of commitments. The format of the filename is as follows: {country/region code}_ndc_{date}_{conditionality}_{hotAir}.json Where country/region code is the 3 letter ISO-3166-1 code for the country or a shortcode for a region, conditionality is one of the following: conditional range (the high/low ambitions represent min-max range of commitments) unconditional For some countries, their pledged targets are greater than what a "no additional climate policy" reference scenario would suggest. The "hotAir" component of the filename state whether these hot air pledges are included or excluded (the reference scenario for a country is used instead). In addition to the archive of region/country level data, some additional global timeseries are provided in the "total_*.json" files. These files follow the same file template shown above.

Nationally Determined Contribution (NDC) Factsheets Raw JSON data used for the NDC Factsheets available at https://www.climate-resource.com/tools/ndcs. The previous versions of the NDC Factsheets are available at https://www.climatecollege.unimelb.edu.au/ndc-indc-factsheets and https://www.pik-potsdam.de/paris-reality-check/indc-factsheets/. Files included in the dataset For each country/region there are 6 files, each run with different settings to explore the different possible types of commitments. The format of the filename is as follows: {country/region code}_ndc_{date}_{conditionality}_{hotAir}.json Where country/region code is the 3 letter ISO-3166-1 code for the country or a shortcode for a region, conditionality is one of the following: conditional range (the high/low ambitions represent min-max range of commitments) unconditional For some countries, their pledged targets are greater than what a "no additional climate policy" reference scenario would suggest. The "hotAir" component of the filename state whether these hot air pledges are included or excluded (the reference scenario for a country is used instead). In addition to the archive of region/country level data, some additional global timeseries are provided in the "total_*.json" files. These files follow the same file template shown above.

The following report shows the evolution of the greenhouse gas emissions from flights from business trips undertaken by ETH Zurich staff and guests, provided that the expenses are covered by ETH Zurich, and by students as part of their curriculum for the period 2016 to 2019. Overall, the flight emissions have decreased in 2019 compared to the base period 2016-2018, and more than half of the departments have already met their pledged 2025 reduction targets. This conclusion should be interpreted with care since year-to-year variations in the flight activity and therefore emissions are large. The data however show that in 2019 almost all employment categories contributed to this decrease, but overall less burden for emissions reductions are put on early career researchers (doctoral students) compared to more established researchers and professors, and emissions from guests have been cut the most (in %). For the base period, long-haul flights caused most of the emissions (86 %) although these only come from 38 % of the flights. For 2019, these numbers are 86 % and 41 %, respectively. Policies addressing or discouraging short distance flights are often aimed at flights that can be replaced by other means of transport. For the period 2016-2018, 38 % of the long-haul flights were also related to non long-haul flights, and 34 % of all short flights are related to a long-haul flight. Even thought most (94 %) flights recorded during the base period are economy class, 19 % of the emissions come from business and first class flights. This number decreased to 16 % in 2019. These numbers show that there is still potential for halving the emissions from business (and first) class flights just by changing flight class, and by cutting short flights that are not connected to other flights.

Spatial distribution of emissions is a key element in assessing human exposure to air pollution through use of dispersion modelling. The quality of the spatial emission mapping is crucial for the quality, applicability and reliability of modelled air pollution levels, estimated human exposure, incurred health effects and related costs; all very important information for policy makers in decisions of implementation of environmental policies and measures. The purpose of the MapEIre project, funded by Ireland’s Environmental Protection Agency, is to develop a high-resolution spatial mapping of the Irish emission inventory. The work is state-of-the-art and combines a large amount of statistical data with detailed spatial information to allow for a complete spatial emission mapping on a 1 kilometre by 1-kilometre resolution. The spatial model is developed as an integrated database system focusing on user-friendliness and performance optimisation. The spatial model for Ireland integrates official statistics, such as the Irish emission inventory, and censuses of population, housing and agriculture, with a large number of spatial datasets as diverse as heat demand, building use, road network and land cover maps, selected through a comprehensive assessment of available spatial data. The model covers 32 pollutants and 177 sectors and includes the entire Irish exclusive economic zone. The methodology developed and the lessons learned will be of great benefit to other countries, which are embarking to develop high-resolution spatial emission distributions. The detailed spatial distribution of emissions can be used by policy makers on both national and local level in decision making and prioritising of environmental measures. Further, it allows for a more detailed regulation, implementing measures targeting areas where emissions are highest, allowing for more cost-effective initiatives on local, regional and national scale.

This document on Abattoirs and manufacture of meat products has been published within the SPIN project. In this project information has been collected on industrial plants or industrial processes to afford support to governmental policy on emission reduction. This document contains information on the processes, emission sources, emissions to air and water, waste, emission factors, use of energy and energy factors, emission reduction, energy conservation, research on clean technology and standards and licences.

Air pollutants in the exhaust emissions from internal combustion engine (ICE) vehicles result from unburnt fuel, high temperature combustion of fuel in the presence of air, and from exhaust after-treatment processes. As many of these pollutants are harmful to human health, impact climate as greenhouse gases, or both, emissions from vehicles have been subject to regulation for many years. Europe-wide standards on vehicle exhaust were introduced in the early 1990s and have been progressively made more stringent, extending the range of regulated pollutants included and reducing the permissible levels of emissions in new vehicles introduced to the fleet. A review of the development and evolution of exhaust emissions standards of relevance to UK vehicles is provided in Chapter 2 of this report.To comply with these standards, technologies for reducing emissions of regulated pollutants have been developed and fitted to vehicle exhaust systems. In combination with advances in engines, these have substantially reduced emissions of many of the regulated pollutants, and a review of the key technologies has been undertaken. Whilst there has been considerable success in substantially reducing exhaust emissions of pollutants such as carbon monoxide (CO), hydrocarbons (HCs) and particulate matter (PM), exhaust emissions from ICE vehicles remain a major source of nitrogen oxides (NOx) and an important contributor to poor urban air quality.Ambient atmospheric measurements have previously revealed important disparities between urban and roadside concentrations of nitrogen dioxide (NO2) and those that would be projected based on the prevailing vehicle emissions standards of NOx. It is now understood that exhaust gas after-treatment technologies introduced on diesel vehicles have not always been effectively implemented and not delivered the anticipated reductions in emissions when in real-world use. The on-road effectiveness of exhaust emissions controls has been found to be highly variable even between vehicles that are technically compliant with the same regulatory standards. There is now greater appreciation of the need to evaluate and demonstrate vehicle emissions performance under real-world driving conditions. On-road emissions have been higher than those measured during laboratory based tests, although in the past five years that gap has closed for some vehicles, and improvements continue. Future European standards will move close to demanding equivalence between on-road and laboratory performance. Real-world driving emissions are reviewed for various vehicle types in Chapter 3.The dynamic nature of the vehicle fleet means that vehicles with a range of different exhaust control technologies and historic standards are in use on UK roads. Between 1990 and 2015, the UK vehicle fleet transitioned to a greater proportion of diesel cars, compared with gasoline, a change that was motivated by predicted fuel economy savings and lower CO2 emissions per mile driven. The relative contributions of exhaust emissions from diesel, gasoline, and more recently hybrid electric vehicles continue to evolve as new technologies develop, and the regulatory framework and consumer preferences (in part driven by economic policy such as fuel tax) change. The vehicle fleet will continue to change over the next decade with older more polluting vehicles leaving the fleet and newer cleaner vehicles joining. This report provides, in Chapter 4, modelled estimates of the vehicle fleet composition over time and the resulting exhaust emissions using best available estimates from inventories used for international reporting. Understanding how the future ensemble of vehicles on the roads will contribute to air pollution emissions is significant for policy development since this information can support the evaluation of interventions such as low emissions zones, and the likely compliance with air quality directives. This report was drafted prior to the COVID-19 crisis and projections of future vehicle use are based on knowledge and understanding at that time. Since March 2020 traffic volumes have varied significantly depending on national restrictions and this has influenced roadside concentrations of many vehicle-derived pollutants. AQEG provided an initial analysis of these effects to Defra in June 2020. The post-COVID fall in new vehicle sales and economic conditions which may affect transport in the future are not assessed here.Ambient observations of air pollution, particularly at the roadside, provide an independent assessment of vehicle exhaust emissions, trends in these emissions over time, and by extension whether emissions controls are working as intended. Methods to assess vehicle exhaust emissions using UK ambient air quality data for a range of different pollutants are presented in Chapter 5, which also includes examples of where ambient observations have detected unanticipated trends in emissions not predicted based on laboratory tests.Chapter 6 identifies possible future interventions and technologies to reduce exhaust emissions and their impacts, including after-treatment approaches. The longer-term impacts on vehicle exhaust emissions from increased use of ICE-electric hybridisation propulsion and driver automation technologies are considered, as are potential approaches to retrofitting as a means to improve emissions performance for existing vehicles. Potential regulatory approaches to managing exhaust emissions are also reviewed, including the possible impacts of changed vehicle inspection regimes, new fuels standards and external traffic management controls on vehicle movements and on idling.Chapter 7 provides the AQEG recommendations.