Climate & Health: A Toolkit?

Peter J RobinsonDepartment of Geography

Southeast Regional Climate CenterUniversity of North Carolina – Chapel Hill

Climate & Health: Background

• Multitudinous Links– Few well established– Most probably complex– Climate not always dominant driver

• Emerging Public Awareness– Public Health Awareness Week

– Increasing information needs– Climate predictions required

Objective

• Develop a climate-health impact toolkit– Simple set of broadly applicable techniques

• Match tool (types) to impact (types) – help understand science behind links– help respond to likely impacts– help with predictions– foster rapid (preliminary) response to user needs

• to emerging questions/new threats

Approach: Case study based

• Review known climate-health links– Limited range

• Incorporate other possible methods– Draw on all aspects of applied climatology

• Suggest new approaches– Literature review– Personal interactions– Graduate student input

Ambient Exposure

• Heat wave – Temperature, humidity, radiation– Heat Stress– Rapid health response

• UV exposure – Sunlight intensity, atmospheric transfer– Melanoma– Cumulative dosage response

Heat Wave – Heat Stress• Biophysical model

– Temperature, humidity, radiation, wind….

• Impact vs climate correlation– Measurements, practicality

• Index development– Applicability, understandability

• Regional Analysis– Time series, thresholds

• Forecasting

Heat Index Application

• Heat Stress Index – a simplification– U.S: Tmax, Tmin, humidity, duration

• Thresholds variable across nation

• Not time dependent

– Europe: Tmax, duration• Simple to use

• Seemingly regarded as static

• Applied to the variety of climates

• Cultural adaptation?

Ambient Exposure

• Heat wave – Temperature, humidity, radiation– Heat Stress– Rapid health response

• UV exposure – Sunlight intensity, atmospheric transfer– Melanoma– Cumulative dosage response

UV Exposure

• Culturophysical Model– Intensity/Quality + exposure time– Social “estimation” of times

• Accuracy vs Complexity– Too complex to use

• Ability to test– Time to accumulate too long

• Validity of basic method?

Transport - Diffusion

• Air pollution– Various well-established applications

• Ozone & Particulate Matter– Longer transport time– Synoptic approach

• Indoor- Outdoor: Flu– (Bio)physical transport model– Jet stream or Jet plane?

Air Pollution

• Clear target– Air pollution = generalized health/diseases

• Plume dispersion models– Well established– Refinements for topography….

• Specific Impacts?– Length/Amount of exposure

Ozone & Particulate Matter

• Longer transport time– Potentially broader dispersion

• Analyze like heat stress?– Point data misleading

• Synoptic approach– Upwind trajectory?– Speed of movement?

Charlotte NC Ozone vs Air Mass

Indoor-Outdoor Air: Flu

• More flu in winter– Seasonal = climate connection?– Viral diffusion process

• Means of diffusion– Jet stream or Jet plane?

• (Bio)physical transport model– Viral survival and transport– Scale of flu diffusion problem

Weather and Influenza: What Do We Know?

Cold air Virus is stable (remains active) Breathing cold air increases respiratory clearance More time spent indoors decreases melatonin and Vitamin D

Dry air Virus decays at a slower rate Virus remains suspended in the air Evaporation decreases size of bioaerosol to that favorable for infection

in the lower respiratory tract

Wind Bioaerosols that settle can be “kicked-up” by gusty winds Increased transport and residence time in the air

Regional Shifts

• Long-term Changes– Climate Change– Outside historical record length

• Wide area Variations– Downscale from models– Upscale from observations

Malarial Regional Shifts

• Temperature trends– Warm areas advance poleward– Suitable seasons for malarial mosquitos?– Impacts inferred from Malarial Atlas Project?

• Surface water changes– Known role of standing water in dry areas– Will warm areas get sufficiently wet?– Will seasonality influence mosquitos?

Climate – Malaria Links

• Seasonality of changed climate?– Downscale model results– Link to synoptics– Add temporal variability as random process?

• Response of mosquitos/parasites– Lifecycles under non-tropical conditions?

• Response to Urbanization– Representative of external factors

Summary of Tools

• Statistical climatology models• Synoptic Climatology approaches• Customized biophysical models• General climate models

• Ability to interlink tools• Need to link various climate factors• Awareness of other inputs