Management of secondary byproducts. Focused on managing primary pollutants. * Present. * Past. * Present & Future Focus on risk to human health

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5 * Past Focused on managing primary pollutants (E.g. SOx, CO, NO 2 ) * Present Management of secondary byproducts (E.g. PM 2.5, O 3 ) * Present & Future Focus on risk to human health (E.g. Pb, Benzene)

6 μg / m3 μg / m3 μg / m3 μg / m More than double μg / m3 μg / m3 μg / m3 in London Usually, in spring and winter the average PM 2.5 concentration is high, leading the increasing number of issuance of fine dust warnings. Average PM 2.5 concentration (Jan May) : 28 in in μg / m3 in 2017 Number of issuance of fine dust warnings (Jan May) : 72 in in times in 2017

7 (Metropolitan area) Diesel vehicle (23%) Construction machine & ship(16%) Business(14%) (Whole country) Business (38%) Construction machine & ship(16%) Power plant(15%) Metropolitan area Whole country Transboundary influence differs by season and weather condition. - Usually, from 30% to 50% is influenced by transboundary pollution including the one from China and North Korea; while during the high-concentration episodes from 60% to 80% The joint research in collaboration with NASA revealed that transboundary pollution from overseas countries including China accounts for 48%, and domestic emission for 52% Research period : May Jun in 2016

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9 Vision Clean Air Korea : Towards a dust-free nation Goal 30% reduction of domestic emission by 2022 The number of days in bad level or lower(whole country) : 258 days in days in 2022 PM 2.5 conc.(seoul) : 26 μg / m3 in μg / m3 in 2022 Strate gies Achieve the goal through intensive reduction of large-scale emission sources Improve atmospheric quality in the Northeast Asia region by strengthening environmental cooperation with neighboring countries Protect our citizens health with a special focus on sensitive groups Improve capability to respond to fine dust by strengthening fundamental of scientific research

10 Goal Plan Sector Emission in 2014 (ton, reference year) Emission in 2019 (ton, 12.6%) Emission in 2022 (ton, 31.9%) Reduction (ton) Reduction rate of sectors Reduction rate Portion of reduction based on 31.9% Total 324,109 (100%) 283,400 (100%) 220,836 (100%) 103, % Power generation 49,350 (15%) 42,973 (15%) 36,839 (17%) 12,511 25% 3.9% Industry 123,284 (38%) 104,652 (37%) 70,493 (32%) 52,791 43% 16.3% Transportation 90,361 (28%) 79,982 (28%) 61,377 (28%) 28,984 32% 9.0% Daily surroundings 61,114 (19%) 55,793 (20%) 52,127 (23%) 8,987 15% 2.8%

11 (Emission status) 15% of total national emission (49,350 ton) is from coal power plants in Chungnam area (30 plants/total 61 plants) Coal accounts for 39% in Korea s power generation. This is higher than the average of OECD (30% in 2015) (Goal) Reduce emissions from power generation sector by 5% until 2022 ( 12,511 ton, total 3.9%) (Main plan) Reduce the portion of coal power in generation, for example through reconsidering the plan to construct coal power plants with low process rate, and expanding renewable and eco-friendly energy sources (Emission status) Account for 38% of total emission(123,284 ton), management failure and blind spot The number of business places across the country (total 57,500, in Dec 2016) : 5,496 of type 1 3, 52,004 of type 4 & 5 (Goal) Reduce 43% of emission from the industry sector by 2022 ( 52,791 ton, total 16.3%) (Main plan) Intensive reduction and practical management by expending the areas for total emission regulation and reinforcing monitoring * 33% of smokestacks of mid and large-size workplaces (type 1 3) has smoke stack tele-monitoring system (TMS) attached.

12 (Emission status) 12% of total national emission (39,005 ton). The most cause of fine dust in large cities is diesel car (Case of LA) diesel car occupies about 15% of PM 2.5 concentration in atmosphere, but occupies about 84% of calcinogenic risk. Portion of emission of diesel cars in metropolitan area : 23%(1st), portion of cargo truck emission: 60% of vehicle sector (registration rate is 15%) (Goal) Reduce 43% of road transport sector emission by 2022 ( 16,624 ton, total 5.1%) (Main plan) retrofitting or scrapping of old diesel cars (complete for 2.22 million cars by 2022) with increase the use of eco-friendly vehicles such as electric vehicle & hybrid vehicle (Emission status) 16% of total national emission (51,355 ton), poor management despite is high emissions Detail portion of off road transport sector (PM 2.5 in 2014 ) : Ship (62%) > construction machine (29%) > agricultural machine, etc. (9%) (Goal) Reduce 24% of off-road transport emission by 2022( 12,360 ton, nationally 3.8%) (Main plan) strengthen blind spot management for example through reduction of ship emission and reduction pollution of construction machine * * The supplies for reducing pollution from construction machine in 2016 is about 0.6% of aged construction machine

13 (Emission status) 19% of total national emission (61,114 ton), urgent management needed for fugitive dust & VOCs from daily surroundings Portion of life sector: road re-fugitive dust(39%) > agricultural remainder incineration (16%) > construction site(7%) (Goal) Reduce 15% of daily surrounding emission by 2022 ( 8,987 ton, nationally 2.8%) (Main plan) Strengthen management for pollutant around daily life environment, for example through expanding road cleaning cars and strengthening paint VOCs content standard Seoul ( 15) 18 Paris, Brussel ( 14) Previous Measures 3 rd Jun Special Measures Year

14 Air Quality Monitoring

15 1 Air Pollution Monitoring Network (NAMIS, Air Korea) Monitoring (Station) Data transmission, collection, mgmt. (NAMIS system) - Real-time air pollution data provided in various formats such as indicators, figures and graphs - Prevents damage of air pollution by providing forecast and warning data (PM10, ozone) of air pollution Exterior Government Interior Internet D B Internet Local government Internet Web server DB server Internet Real-time nationwide air quality data and comprehen sive air quality indicator Forecast and warning of air pollution Air pollutionrelated statistics, etc.

16 1 Air Pollution Monitoring Network (NAMIS, Air Korea) General air pollution monitoring network Specialized air pollution monitoring network Intensive monitoring network Central gov. (154 stations) Suburban (19 stations) National (3) HAPs (32) Photochemical air pollutants (18) Acidic deposits (40) Global atmosphere (1) PM-2.5 (35) Intensive monitoring network (6) Baseline concentration in vast area SO 2, CO, NO X, O 3, PM 10, wind direction & speed, temperature, humidity Nationwide baseline concentration and current status of long-range transboundary pollution coming from overseas Current status of pollution caused by specific HAPs VOCs (14 kinds), PAHs (7 kinds) Concentration of ozone precursor (VOCs), ozone pollution investigation and use of basic data for forecast NOx, NOy, O 3, PM 10, PM 2.5, low concentration CO, VOCs (56 kinds) Wet deposition of pollutants caused by precipitation PM 2.5, cation, anion, PH, mercury (HgT, HgP,..), rainfall Concentration of global warming and ozone depleting substances CO 2, CFC(-11,-12,-113), N 2 O, CH 4 Concentration and content of PM 2.5 with high risk to human health, investigation of emission source Status of air quality by major zones and analysis of yellow dust and other long-range transboundary pollutants SO 2, CO, NO X, O 3, PM 10, PM 2.5, carbon, ion, heavy metals Local gov. (351 stations) Urban (259) Roadside (38) Heavy metals (54) Average concentration in urban area, determinining if environmental criteria are met SO 2, CO, NOX, PM 10, PM 2.5, O 3, wind direction & speed, temperature, humidity Roadside air quality with high traffic volume and floating population SO 2, CO, NO X, PM 10, O 3, (If necessary, Pb, PM 2.5, HC, and traffic volume added) Pollution status caused by heavy metals in urban areas or areas near industrial complex Pb, Cd, Cr, Cu, Mn, Fe, Ni, As, Be (During yellow dust season, Al, Ca, and Mg added)

17 2 Environmental Satellite(GEMS, Geostationary Environment Monitoring Spectrometer) TEMPO (America) Constellation of GEO Mission for synergistic products UV-Vis nm GMES S4 UVN (Europe) UV-Vis-NIR , nm GEMS + AMI + GOCI2 GEO KOMPSAT(Asia) UV-Vis nm Constellation synergy - Improving spatial and temporal coverage to monitor globalized pollutants & SLCF - Sharing basic requirements on data products and instrument to maintain data quality - Consolidating socio-economic benefit analysis - Supporting QA and CAL/VAL

18 2 Environmental Satellite(GEMS, Geostationary Environment Monitoring Spectrometer)

19 2 Environmental Satellite(GEMS, Geostationary Environment Monitoring Spectrometer)

20 3 Emission Inventory of Air Pollutants (CAPSS) Major Emission Sources Emission volume in 2013 [Unit : ton/yr] Total VKT 260 bn. km No. of vehicles 580k takeoffs & landings 18 mn. cars High-level source category Energy ind. combustion Non-ind. combustion Manufacturing ind. comb. Production process Energy transp. & storage Use of organic solvent On-road mobile source Non-road mobile source Waste treatment Agriculture Other area sources Total Ratio of open air incineration in rural area 74.9% Forest fire 1,090 ha 100k installation stacks 390k construction machinery Fugitive dust Biomass burning Total (including fugitive/ biomass burning)

21 4 Emission Source Survey(SEMS, CleanSYS) Workflow of SEMS CAPSS and relevant authorities Request for information Data of installations and their activities Local government Target installation info. (Stack Emission Management System) CleanSYS data K-eco Info. disclosure Basic data, statistics, user mgmt. regarding installation and emission info. Operational record and self monitoring data input Report & verification result Data mgmt. Verification Operational statistics report Approx. 4,100 installations Support for registration NIER (MoE)

22 5 Air Quality Modelling System(K-MEMs) for Policy makers FNL/ECMWF K-MEMs WRF MCIP CMAQ CMAQ w/ probing tool Visualization MEGAN SMOKE EMISSION EMISSION perturbation

23 6 Air Quality Forecasting System (NAQMS) 1. Observation 2. Modeling 3. Decision Making 4. Announcement - Analysis of current AQ based on various measurements - Predicting air quality levels using the simulated results - Decision making by forecasters based on observation and modeling results - Public services using Broadcasting media, PC and mobile Phone General information about AQF ( 4 index bands ) [ Forecast maps ] Materials Low Moderate High Very high PM 10 0~30 31~80 81~ ~ PM 2.5 0~15 16~35 36~75 76~ O 3 0~30 31~90 91~ ~

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25 1 Implications In order to protect the health of air pollution, Need management of secondary pollutants unlike the past Scientific policy is needed to improve secondary pollutants that are difficult to manage Scientific policy is important to measure, emissions, modeling, etc. 2 Suggestions Simple Quiz? 1. What pollutants should we target first? 2. What pollution sources should be reduced for air quality management? 3. What is the measurement, emissions, and modeling priority?

26 Science-Policy conceptual Model Courtesy: Harvey Jeffries

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