Future Air Quality in Representative Concentration Pathway Scenarios:Relationships Between Economic

Wellbeing and Air Quality

J. Jason WestSteven J. Smith, Joint Global Change Research

InstituteLouisa Emmons, NCAR

Larry W. Horowitz, GFDL

The UNC

Climate, Health and Air Quality Lab

What Will Future Air Quality Be?

• The IPCC Special Report on Emissions Scenarios (SRES, 2000) projected high growth of air pollutant emissions, in future scenarios.

Modeled monthly mean ozone increase in 2100 (SRES A2 scenario), relative to 2000 – average of 10 global models (Prather et al., 2003).

Will A Richer World Put Up With Air Pollution?

Environmental Kuznets Curves: Richer countries are expected to be more willing to devote resources for environmental protection

Ausubel and Waggoner, 2009

Income per Capita

Env

ironm

enta

l Im

pact

• Integrated Assessment Models assume that emission controls increase with income.

• However, pollutant concentrations, should be more closely related to incomes.

Smith et al., 2009

ObjectiveEvaluate one RCP scenario for its consistency across regions in terms of air quality, by using

a global chemical transport model in the scenario development process.- Analyze the relationships between income and air quality, rather than emissions controls.- Use an iterative process of creating scenario and simulating global air quality.

New scenarios for use in IPCC AR5 = Representative Concentration Pathway (RCP) Scenarios

Use MOZART (versions 2 and 4) for global simulations of future air quality.

RCP Scenarios

We will use MOZART to model the RCP4.5 scenario.

RCP8.5>8.5 W/m2 in 2100, Rising

MESSAGE model, IIASA, Austria

RCP6~6 W/m2 at stabilization after 2100Stabilization without exceeding target

AIM model, NIES, Japan

RCP4.5~4.5 W/m2 at stabilization after 2100Stabilization without exceeding target

MiniCAM model, PNNL, USA

RCP3-PD<3 W/m2 in 2100peak & decline stabilization

IMAGE model, PBL, Netherlands

RCP scenarios named for their radiative forcings in 2100.

• MOZART-2 is used to model RCP4.5 scenario in 2005, 2050 and 2095, based on gridded emissions outputs of MiniCAM.

• Resolution: T42, 2.8°x2.8° with 34 vertical levels.• Meteorology: MACCM3 simulated global meteorology for the

present.• VOC speciation: from POET global emissions.• Seasonal distributions of emissions: from RETRO global

emissions.• Natural emissions: from base MOZART-2 simulation

(Horowitz et al., 2003).• PM2.5 = SO4 + NO3 + NH4 + EC + OCx1.5• Methane is fixed globally at estimated future concentrations.• This version of MOZART-2 has been evaluated extensively

against measurements, but not for these base emissions.

MOZART-2 setup

Results: Second IterationAnnual average PM2.5

2050 2095

2005

World Regions

Results – PM2.5 by region

Mean PM2.5 for the consecutive 3 month period with highest PM2.5 in each region.

0

5

10

15

20

25

30

35

2000 2020 2040 2060 2080 2100

Max

Sea

sona

l PM

(ug/

m3)

Year

Max Seasonal PM Levels

NothingEuropeMiddleEastSouthAmericaAustraliaFormerSovietEast ChinaIndia, etc.SoutheastAsiaNorthAfricaJapanMexicoSouthernEuropeSouthern-Cent AfricaEasternUSGlobal

0

5

10

15

20

25

30

35

0 20 40 60

Max

Sea

sona

l PM

(ug/

m3)

Income (1000s MER$/cap)

Max Seasonal PM Levels

EuropeMiddleEastSouthAmericaAustraliaFormerSovietEast ChinaIndia, etc.SoutheastAsiaNorthAfricaJapanMexicoSouthernEuropeSouthern-Cent AfricaEasternUSGlobal

Results: Second Iteration Annual average ozone

2050 2095

2005

Results – Ozone by region

Mean ozone for the consecutive 3 month period with highest ozone in each region.

20

30

40

50

60

2000 2020 2040 2060 2080 2100

Max

Sea

sona

l O3

(ppm

)

Year

Max Seasonal O3 Levels

NothingEuropeMiddleEastSouthAmericaAustraliaFormerSovietEast ChinaIndia, etc.SoutheastAsiaNorthAfricaJapanMexicoSouthernEuropeSouthern-Cent AfricaEasternUSGlobal20

30

40

50

60

0 20 40 60

Max

Sea

sona

l O3

(ppm

)

Income (1000s MER $/cap)

Max Seasonal O3 Levels

EuropeMiddleEastSouthAmericaAustraliaFormerSovietEast ChinaIndia, etc.SoutheastAsiaNorthAfricaJapanMexicoSouthernEuropeSouthern-Cent AfricaEasternUSGlobal

• We’ve shown how atmospheric modeling can be used in the scenario development process.

• By adjusting emission controls, future PM2.5 concentrations were made to yield reasonably consistent relationships with projected future incomes, among world regions.

• Ozone was found to be harder to adjust using a region’s own emission controls, because of the influence of background and foreign sources.

Preliminary Conclusions

Next Steps• Convert to MOZART-4 and evaluate model against

measurements for base emissions.• Simulate final RCP4.5 scenario, and other RCP

scenarios.• Evaluate simulating under future climate conditions.