Relationship between air pollution &climate change
Toshihiko TAKEMURA Distinguished Professor
Research Institute for Applied Mechanics, Kyushu University, Japan• Lead Author, 5th Assessment Report of the UN Intergovernmental Panel on Climate Change.
• Highly Cited Researcher (2014, 2015, 2016, 2017, 2018, 2019, 2020).
• Awards: Japan Academy Medal / JSPS Prize (2019), Nishida Prize of Japan Geoscience Union (2015),
Society Award of Meteorological Society of Japan (2013), etc.
• Articles to public: https://news.yahoo.co.jp/byline/takemuratoshihiko/ (in Japanese)

Contents• Mechanism of climate change due to atmospheric aerosols.
• Development of a global aerosol climate model, SPRINTARS, for simulating distributions ofatmospheric aerosols and estimating their eﬀects on climate change.
• Ongoing projects on short-lived climate forcers (SLCFs).

UC San Diego – Kyushu University Joint Webinar: SDGs THINK and ACT together (March 9, 2021) Toshihiko Takemura

新エネルギー力学部門

大気海洋環境研究センター

Division of Renewable Energy Dynamics

Center for Oceanic and Atmospheric Research

Research結晶成長学
Institute for Applied Mechanics (RIAM),Kyushu University
海洋力学
Crystal Growth Dynamics

Ocean Dynamics

https://www.riam.kyushu-u.ac.jp
新エネルギー材料工学
Renewable Energy Materials Engineering
海洋環境エネルギー工学
Division
Renewable
Marineof
Environment
and Energy Engineering
Energy風工学Dynamics
Wind Engineering
数値流体力学（寄付研究部門）
Materialdevelopmentfor•
Computational Fluid Dynamics
renewable energy
renewable energy• Marine地球環境力学部門
Division of EarthEnvironment Dynamics etc.
utilization• Wind energy

気候変動科学

CenterforOceanicand海洋モデリング
Ocean Modeling
AtmosphericResearch
海洋変動力学
Climate Change Science

Simulation of atmospheric•大気環境統合解析
Ocean Processes

九州大学

応用 力 学 研究所

大気環境統合解析

Research Institutefor Applied Mechanics

Atmospheric
Environment Integrated Analysis
Division ofEarth
大気海洋相互作用
EnvironmentalDynamics
Ocean-AtmosphereInteraction• Fundamental research andPlasma Science for Steady-state Operation

定常プラズマ加熱
development for nuclear fusion
Plasma Heating for Steady-state Operation

reactorwithaspherical
定常プラズマ制御学
tokamak
instrument
PlasmaControl for Steady-stateOperation QUEST
境界プラズマ実験解析

Renewable Energy Center

Ocean Circulation Dynamics

Boundary Plasma Experiment and Analysis

海洋リモートセンシング

Nonlinear Dynamics

Research Center

定常プラズマ理工学

AtmosphericPhysics sensing
remote• Atmospheric
大気環境モデリング
Atmosphericenvironment model•
Atmospheric Environment Modelingocean research
海洋動態解析
• Experimental
Regional Oceanographyinteractionetc.
• Ocean-atmosphere
海洋循環力学

海洋工学
Experimental
and simulation•Ocean Engineeringresearch on
plasma turbulence
非線形力学

Advanced Fusion
高温プラズマ理工学研究センター
Advanced Fusion Research Center

大気物理

Division
Ocean Remote ofSensingNuclear
大気力学
FusionDynamics
Atmospheric Dynamics

aerosols (PM2.5, dust, …)
大気物理• Oceanic microplastic
大気環境モデリング
etc.
大気力学• ICT smart fisheries

プラズマ波動理工学

Technical Service Division
etc.

••

Plasma Wave Science and Engineering

Wind power
高温プラズマ輸送
High-eﬃciency conversion
高温プラズマ計測
technologies
高温プラズマ壁相互作用
周辺プラズマ・炉材料理工学
New green electronics
etc.

•UC San Diego – Kyushu University Joint Webinar: SDGs THINK and ACT together (March 9, 2021) Toshihiko Takemura

History of air pollution• Traditional local air pollution: heating, cooking, slash-and-burn agriculture, forest fire, etc.
• Consumption of fossil fuel (coal, oil, natural gas, etc.) after the Industrial Revolution.
• Population explosion.

© Daily Mail

➡ Extended and serious air pollution, e.g.:‣ London smog (early-mid 20th century): soot and sulfur oxides.
‣ Transboundary air pollution from western to northern Europe (mid 20th century): acid rain.
‣ Los Angeles smog (mid-late 20th century): nitrogen oxides and photochemical oxides.

While improvement of atmosphericenvironment in developed countries,worsening air pollution in emerging anddeveloping countries results in…
• 9 out of 10 people breathe air containing
high levels of pollutants.
• Around 7 million people die prematurely
every year from exposure to polluted air.

BeijingIndonesia© Washington Post

https://www.who.int/news-room/air-pollution(WHO, 2018)
UC San Diego – Kyushu University Joint Webinar: SDGs THINK and ACT together (March 9, 2021) Toshihiko Takemura© NASA

Present major air pollutants — PM2.5 & photochemical oxidant‣ Photochemical oxidant (Ozone)
Stratospheric O3 (ozone layer)of ultraviolet radiation• Prevention
that is harmful to living things

Ozone layer

UV‣ PM2.5 (fine-mode aerosols)

suspended particle matters (aerosols) less
• Atmosphericthan about 2.5µm in diameterof several-tenth µm in diameter of anthropogenic• Aerosols
sulfate, organics, black carbon, nitrate, etc. principally• Cause of smog
➡ Climate change• Essentials for cloud formation

Tropospheric O3(photochemical oxidant)

Low-level PM2.5eﬀects on plants• Negativeand animals/human’s health• Greenhouse gas

Photochemical oxidant

High-level PM2.5（no clouds）

2011.04.05

NOXVOC@ RIAM, Kyushu University

Infrared radiation

2011.05.02

Most major air pollutants cause
climate change through several processes

UC San Diego – Kyushu University Joint Webinar: SDGs THINK and ACT together (March 9, 2021) Toshihiko Takemura

Energy budget in the atmosphere
incoming
Units (Wm-2) solar TOA

340(340, 341)

79

100

239

(96, 100)(236, 242)

CloudsGreenhouse gases

CloudsAerosols(74, 91)

solarsolarreflecteddown(179, 189) (22,26)
surfacesurface

185

24

161
imbalance

0.6(0.2, 1.0)

atmosphericwindowgreenhousegases

latent heatsolar absorbed
atmosphere

Gases
Aerosols

thermal outgoing
TOA

solar reflected
TOA(154, 166)

solar absorbed
surface

84 20

398

342

(70, 85) (15, 25)(394, 400)

(338, 348)

sensibleheat

thermalup surface

thermaldown surface

evaporation

UC San Diego – Kyushu University Joint Webinar: SDGs THINK and ACT together (March 9, 2021) Toshihiko Takemura

IPCC AR5 (2013)

Aerosol eﬀects on climate system
Irradiance Changes from
Aerosol-Radiation Interactions (ari)Direct EffectSemi-Direct Effects

Radiative Forcing (RFari)

Adjustments

Effective Radiative Forcing (ERFari)

Irradiance Changes from
Aerosol-Cloud Interactions (aci)Cloud Albedo Effect

Lifetime (including glaciation& thermodynamic) Effects

Radiative Forcing (RFaci)

Adjustments

Effective Radiative Forcing (ERFaci)

AR4AR5IPCC AR5 (2013)
UC San Diego – Kyushu University Joint Webinar: SDGs THINK and ACT together (March 9, 2021) Toshihiko TakemuraGlobal aerosol climate model MIROC-SPRINTARS
http://sprintars.net

References: Takemura et al. (JGR, 2000; JCLI, 2002; JGR, 2005; ACP, 2009)
NIES CGER’s Supercomputer Monograph Report Vol. 24

Global climate model（MIROC, MIROC-ESM*）

wind, temperature, clouds, precipitation, etc.

advection, convection, diffusion

Resolution horizontal: T319/T213/T106/T85/T42, vertical: L56/L40/L20

Aerosols

chemicalGases
SecondaryPrimary
reaction
SO2, DMS, nucleation sulfate, organics,
soil dust, sea salt,NOx, VOC, etc.
nitrateblack carbon, organics

emission

wet deposition(dissolution)
dry deposition(turbulence)

wet deposition(collision)
dry deposition(turbulence,gravitation)

emission

CCNIN
cloud
dropleticecrystalrainsnow

Climate eﬀects
of aerosols
Aerosol-radiationinteraction
scattering andabsorption of solar andthermal radiation
change in clouds due
to absorbing radiation
by aerosols

Aerosol-cloudinteractionchanges in cloudparticle size andlifetime through acting
as cloud condensation
nuclei (CCN) and ice
nuclei (IN)

* MIROC, MIROC-ESM: Global climate model and earth system model developed by Atmosphere Ocean Research Institute (AORI)/Univ. Tokyo,
National Institute for Environmental Studies, Japan, and Japan Agency for Marine-Earth Science and Technology (JAMSTEC)UC San Diego – Kyushu University Joint Webinar: SDGs THINK and ACT together (March 9, 2021) Toshihiko Takemura

Simulation of global aerosol transport by MIROC-SPRINTARS
https://youtu.be/j77PG1IyRIc

UC San Diego – Kyushu University Joint Webinar: SDGs THINK and ACT together (March 9, 2021) Toshihiko TakemuraGlobal warming due to clean air

NaturalRadiative forcing by emissions and drivers

Level ofconfidence

CO2CO21.68 [1.33 to 2.03]

VHCH4CO2 H2Ostr O3 CH40.97 [0.74 to 1.20]

H

Halocarbons

O3 CFCs HCFCs

0.18 [0.01 to 0.35]

HN 2O

N 2O

0.17 [0.13 to 0.21]

VH

COCO2CH4 O3

0.23 [0.16 to 0.30]

M

NMVOC

CO2CH4 O3

0.10 [0.05 to 0.15]

M

NOxNitrate CH4 O3-0.15 [-0.34 to 0.03]

M

Aerosols andprecursors

Mineral dust Sulphate Nitrate-0.27 [-0.77 to 0.23]

H

Cloud adjustments
due to aerosols-0.55 [-1.33 to -0.06]

L

Albedo change
due to land use-0.15 [-0.25 to -0.05]

M

Changes insolar irradiance0.05 [0.00 to 0.10]

M(Mineral dust,SO2, NH3,Organic carbon
and Black carbon)

Organic carbon Black carbon

2.29 [1.13 to 3.33]

Total anthropogenic
RF relative to 1750

IPCC AR5 (2013)

H

2011

119801.25 [0.64 to 1.86]

H

1950

0.57 [0.29 to 0.85]

M

0123
Radiative forcing relative to 1750 (W m2)

Long-livedgases

Resulting atmospheric
drivers

Short-lived
climate forces(SLCFs)Short lived gases and aerosols

Anthropogenic

Well-mixed greenhouse gases

Emittedcompounddoi:10.1038/s41598-020-78805-1Annual mean change in surface air temperature due
to complete removal of fuel SO2 emission simulatedby MIROC-SPRINTARS (Takemura, Sci. Rep., 2020).

• Reductions of aerosol concentrations brings

global warming.
• A reduction in NOx emissions leads to reducing
O3 while an increase in CH4, both of which aregreenhouse gases.

Simple emission reductions of short-lived components result in clean air
while contributing to global warming.
➡ It is essential to mitigate both air pollution and global warming simultaneously.
UC San Diego – Kyushu University Joint Webinar: SDGs THINK and ACT together (March 9, 2021) Toshihiko Takemura

Ongoing project: Hierarchical simulations of SLCFs
Atmosphere-ocean GCM MIROC

Aerosol model

Chemistry model

https://www.riam.kyushu-u.ac.jp/climate/KAKENHI_S/
Use as knowledge to improve
quantitative representation of clouds.

Horizontal res.: tens of km Integration time: 10〜100yr
Simulation of both atmosphere-only and coupled atmosphere-ocean models
with varying SLCFs-related emission by regions, compositions, and origins.
➡ Evaluating the impact of SLCFs dividing the contributions of fastadjustment (days to years) and slow response (decades).

NICAM-Chem
Global cloud resolving model NICAM

Comparison andimprovement ofhydrological cycle
by fast response
due to SLCFs.
sulfatesea salt
dustcarbon
cloudLarge

Spatio-temporal scale

MIROC-SPRINTARS / MIROC-CHASER

Horizontal res.: 3.5, 7, 14km Integration time: a few yr
Detailed spatio-temporal SLCFs distributions and aerosol-cloud interaction
based on explicit expression of cloud dynamics and physical processes.
Horizontal res.: tens to hundreds meters
SCALE-LES Incorporating SPRINTARS/CHASER into a model with direct treatment of cloud dynamics.
UC San Diego – Kyushu University Joint Webinar: SDGs THINK and ACT together (March 9, 2021) Toshihiko Takemura

SmallOngoing project: Research on mitigation measures for SLCFs
Theme 1
Assessment of regional-scale
climate change by SLCFs
Atmosphere-ocean model
High-resolution climate model
Temperature
Precipitation
Extreme events
Mitigation scenario
Integrated assessment model
Inventory

Theme 3
Quantification of mitigation
scenario for environmental
impacts by SLCFs

https://www.riam.kyushu-u.ac.jp/climate/S-20/
Downscaling

Theme 2
Assessment of regional-scaleenvironmental impacts by SLCFs

Aerosols 1)
2)
Trace gases

SLCFs
Creating scientificknowledge for mitigation
policies on climate change
and environmental impacts
by SLCFs in different regions

Impact assessment model
HealthCrops
Flood / Drought
Paris Agreement
Domestic policies
IPCC

CCAC

APCAP

1) sulfate, BC, organics,nitrate, their precursors2) CH4, O3, HFCs,
their precursors

UC San Diego – Kyushu University Joint Webinar: SDGs THINK and ACT together (March 9, 2021) Toshihiko Takemura

Need for rapid reductions of greenhouse gas emissions

Figure ES.5. ,QTGFQ ,-, JRNXXNTSX ZSIJW INKKJWJSY XHJSFWNTX FSI YMJ JRNXXNTSX LFU NS  RJINFS FSI  th YT thUJWHJSYNQJWFSLJ GFXJITSYMJUWJ(4;.)HZWWJSYUTQNHNJXXHJSFWNT
70

Mauna Loa Observatory, Hawaii and South Pole, Antarctica
Monthly Average Carbon Dioxide Concentration
2010-Policies scenario

420
60

Current policies scenario

Data from Scripps CO2 Program

Last updated January 2021

410

Unconditional NDC scenario
Conditional
NDC scenario30Remaining gap
to stay within
2°C limit

GtCO2e

GtCO2eMedianestimateof levelconsistent
with 2°C:
41 GtCO݅e(range 39-46)

1.8°C
range
Green area shows pathways
limiting global temperature
increase to below 1.5°C by
2100 and peak below 1.7°C(both with 66% chance)

29
Uncond. NDC case

Turquoise area shows
pathways limiting global
temperature increase tobelow 2°C with about
66% chance

32

GtCO2eCond. NDC case

GtCO݅e
40

2°C
range

Uncond. NDC case

12

GtCO2e15Cond. NDC case

50

1.5°C
range
Median estimateof level consistent
with 1.5°C:25 GtCO݅e(range 22-31)

2015

2020

2025

2030

60

Current policy scenario
Unconditional NDC scenario
Conditional NDC scenario

30

Emissions Gap Report 2020

370
360
350
340

https://scrippsco2.ucsd.edu

330

310

1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

2010

2015

2020

Year

40

2°C range

20

1.8°C range

10

1.5°C range

0
2010

380

2010-Policies scenario

50

Emissions Gap Report(2020)

390

320

70

20

CO2 Concentration (ppm)

400

2020

2030

2040

Climate science clearly shows the need for urgent
and drastic reductions in greenhouse gases.

2050UC San Diego – Kyushu University Joint Webinar: SDGs THINK and ACT together (March 9, 2021) Toshihiko Takemura

SPRINTARS aerosol forecasting system to public
http://sprintars.net/forecastj.html (Japanese)
http://sprintars.net/forecast.html (English)

SPRINTARS
Spectral Radiation-Transport Model for Aerosol Species

ホーム

週間予測（一般）

週間予測（専門）

アーカイブ

研究室ホームEnglish毎日午前5時頃更新予定

各地の予測

PM2.5予測・黄砂予測

今日・明日

2016年2月27日

週間予測はこちら

週間予測動画PM2.5
東アジア

今日（2月27日）

アジア広域
アジア予測
(在留邦人向け)

6-12

12-18

18-24

0-6

6-12

12-18

18-24

PM2.5

少ない

少ない

少ない

少ない

少ない

少ない

少ない

黄砂少ない

少ない少ない

少ない

少ない

少ない

少ない

PM2.5少ない

少ない

少ない

少ない

少ない

少ない

少ない

黄砂少ない

少ない

少ない

少ない

少ない

少ない

少ない

PM2.5少ない

やや多い

やや多い

やや多い

少ない

少ない

やや多い

黄砂

少ない

少ない

少ない

少ない

少ない

少ない

少ない

PM2.5

やや多い

多い

多い

多い

やや多い

やや多い

多い

黄砂少ない

少ない

少ない

少ない

少ない

少ない

少ない

PM2.5多い

多い

多い

多い

やや多い

やや多い

多い

黄砂少ない

少ない

少ない

少ない

少ない

少ない

少ない

PM2.5多い

多い

多い

多い

多い

多い

やや多い

黄砂少ない

少ない

少ない

少ない

少ない

少ない

少ない

PM2.5多い

多い

多い

多い

多い

多い

やや多い

黄砂少ない

少ない

少ない

少ない

少ない

少ない

少ない

PM2.5多い

多い

多い

非常に多い

非常に多い

多い

やや多い

黄砂少ない

少ない

少ない

少ない

少ない

少ない

少ない

PM2.5多い

多い

多い

多い

多い

多い

やや多い

黄砂少ない

少ない

少ない

少ない

少ない

少ない

少ない

PM2.5多い

多い

多い

やや多い

多い

やや多い

多い

黄砂少ない

少ない

少ない

少ない

少ない

少ない

少ない

PM2.5

やや多い

やや多い

やや多い

多い

多い

やや多い

やや多い

黄砂少ない

少ない

少ない

少ない

少ない

少ない

少ない

PM2.5少ない

少ない

少ない

少ない

少ない

少ない

少ない

黄砂少ない

少ない

少ない

少ない

少ない

少ない

少ない

6-1212-18

18-24

0-6

6-1212-1818-24

北海道

東北北部

東北南部

首都圏

今日・明日
週間
このページのPM2.5予

測・黄砂予測は数値モデ
ル SPRINTARS を使用し北陸信越

東海

たシミュレーションによ近畿

PM2.5は地表付近の濃中国り行われています。

度​，黄砂は地表付近から高度約200mまでの平均質量濃度を表示しています。シミュレーションは水平方向約35km格子で行われているため，それ

四国

九州北部以下のエアロゾル濃度の変動は予測されていません。各地方全般の高濃度

九州南部

や他の地方・国からの越境汚染が予測されています。

携帯電話用URLをメール送信する

明日（2月28日）

時間帯（時）

アジア広域黄砂
東アジア

発表

沖縄時間帯（時）今日（2月27日）

明日（2月28日）

PM2.5予測・黄砂予測トップページへ
非常に多い

注意喚起レベル多い

日本の環境基準値程度

やや多い

大気が少し霞む程度

少ない

清浄

7-days forecast for aerosols
including PM2.5 and dust
shown as:• 4-step level display forJapanese each prefecture.
• Movies for East Asia, Asia,and global.
SPRINTARS PM2.5 forecast
is cited by TVs, radios,newspapers, otherwebsites, apps, and local
governments➡ Voluntary contribution topublic.

UC San Diego – Kyushu University Joint Webinar: SDGs THINK and ACT together (March 9, 2021) Toshihiko Takemura