Glenn McGregor

Climate Change, Tropospheric Ozone and Particulate Matter, and Health Impacts

Objective Because the state of the atmosphere determines the development, transport, dispersion, and deposition of air pollutants, there is concern that climate change could affect morbidity and mortality associated with elevated concentrations of these gases and fine particles. We review how climate change could affect future concentrations of tropospheric ozone and particulate matter (PM), and what changing concentrations could mean for population health. Data sources We review studies projecting the impacts of climate change on air quality and studies projecting the impacts of these changes on morbidity and mortality. Data synthesis Climate change could affect local to regional air quality through changes in chemical reaction rates, boundary layer heights that affect vertical mixing of pollutants, and changes in synoptic airflow patterns that govern pollutant transport. Sources of uncertainty include the degree of future climate change, future emissions of air pollutants and their precursors, and how population vulnerability may change in the future. Given these uncertainties, projections suggest that climate change will increase concentrations of tropospheric ozone, at least in high-income countries when precursor emissions are held constant, which would increase morbidity and mortality. Few projections are available for low- and middle-income countries. The evidence is less robust for PM, primarily because few studies have been conducted. Conclusions Additional research is needed to better understand the possible impacts of climate change on air pollution–related health impacts. If improved models continue to project higher ozone concentrations with climate change, then reducing greenhouse gas emissions would enhance the health of current and future generations.

Climate change and heat-related mortality in six cities Part 2: Climate model evaluation and projected impacts from changes in the mean and variability of temperature with climate change.

Previous assessments of the impacts of climate change on heat-related mortality use the “delta method” to create temperature projection time series that are applied to temperature–mortality models to estimate future mortality impacts. The delta method means that climate model bias in the modelled present does not influence the temperature projection time series and impacts. However, the delta method assumes that climate change will result only in a change in the mean temperature but there is evidence that there will also be changes in the variability of temperature with climate change. The aim of this paper is to demonstrate the importance of considering changes in temperature variability with climate change in impacts assessments of future heat-related mortality. We investigate future heat-related mortality impacts in six cities (Boston, Budapest, Dallas, Lisbon, London and Sydney) by applying temperature projections from the UK Meteorological Office HadCM3 climate model to the temperature–mortality models constructed and validated in Part 1. We investigate the impacts for four cases based on various combinations of mean and variability changes in temperature with climate change. The results demonstrate that higher mortality is attributed to increases in the mean and variability of temperature with climate change rather than with the change in mean temperature alone. This has implications for interpreting existing impacts estimates that have used the delta method. We present a novel method for the creation of temperature projection time series that includes changes in the mean and variability of temperature with climate change and is not influenced by climate model bias in the modelled present. The method should be useful for future impacts assessments. Few studies consider the implications that the limitations of the climate model may have on the heat-related mortality impacts. Here, we demonstrate the importance of considering this by conducting an evaluation of the daily and extreme temperatures from HadCM3, which demonstrates that the estimates of future heat-related mortality for Dallas and Lisbon may be overestimated due to positive climate model bias. Likewise, estimates for Boston and London may be underestimated due to negative climate model bias. Finally, we briefly consider uncertainties in the impacts associated with greenhouse gas emissions and acclimatisation. The uncertainties in the mortality impacts due to different emissions scenarios of greenhouse gases in the future varied considerably by location. Allowing for acclimatisation to an extra 2°C in mean temperatures reduced future heat-related mortality by approximately half that of no acclimatisation in each city.

Biometeorology for Adaptation to Climate Variability and Change

Introduction 1 Biometeorology for Adaptation to Climate Variability and Change.- Section 1: Research Frontiers.- 2 The thermal environment.- 3 Heatwave and health warning systems.- 4 Early warning systems for vectorborne diseases.-5 Pollen, allergies, and adaptation.- 6 Plant biometeorology and adaptation.- 7 Adaptive responses of domestic (farm animals) to climate challenges.- 8 Tourism and recreation.- 9Adaptation and water resources.- 10 Psychology of weather and climate.- Section 2: Perspectives.- 11 Adaptation within the paradigm of climate determinism and change.- 12 Adaptation and adaptive capacity: synthesis, research directions, and policy questions.

Humidity: A review and primer on atmospheric moisture and human health

Research examining associations between weather and human health frequently includes the effects of atmospheric humidity. A large number of humidity variables have been developed for numerous purposes, but little guidance is available to health researchers regarding appropriate variable selection. We examine a suite of commonly used humidity variables and summarize both the medical and biometeorological literature on associations between humidity and human health. As an example of the importance of humidity variable selection, we correlate numerous hourly humidity variables to daily respiratory syncytial virus isolates in Singapore from 1992 to 1994. Most water-vapor mass based variables (specific humidity, absolute humidity, mixing ratio, dewpoint temperature, vapor pressure) exhibit comparable correlations. Variables that include a thermal component (relative humidity, dewpoint depression, saturation vapor pressure) exhibit strong diurnality and seasonality. Humidity variable selection must be dictated by the underlying research question. Despite being the most commonly used humidity variable, relative humidity should be used sparingly and avoided in cases when the proximity to saturation is not medically relevant. Care must be taken in averaging certain humidity variables daily or seasonally to avoid statistical biasing associated with variables that are inherently diurnal through their relationship to temperature.

Large-Scale Climatic Controls on New England River Flow

Abstract Understanding atmospheric drivers of river flow variability necessitates clear knowledge of the process chain linking climate and hydrology, yet the nature of such linkages remains poorly understood for the New England region of the northeastern United States. This research gap is addressed through a composite analysis of large-scale climatic controls on monthly high and low river flow in New England for 1958–2001, based on 40-yr ECMWF Re-Analysis (ERA-40) data. Analysis is focused on climate fields at the North Atlantic spatial scale, with particular attention given to the influence of the North Atlantic Oscillation (NAO). High (low) river flow is shown to be characterized by greater (lower) geopotential height throughout the year, and from December to April, higher (lower) temperature. Wind speed is inversely associated with river flow in all months, with wind direction more southerly (northerly) under high (low) flow situations. Relative vorticity differences reveal more cyclonic circulation c...

The benefits of quantifying climate model uncertainty in climate change impacts assessment: an example with heat-related mortality change estimates

The majority of climate change impacts assessments account for climate change uncertainty by adopting the scenario-based approach. This typically involves assessing the impacts for a small number of emissions scenarios but neglecting the role of climate model physics uncertainty. Perturbed physics ensemble (PPE) climate simulations offer a unique opportunity to explore this uncertainty. Furthermore, PPEs mean it is now possible to make risk-based impacts estimates because they allow for a range of estimates to be presented to decision-makers, which spans the range of climate model physics uncertainty inherent from a given climate model and emissions scenario, due to uncertainty associated with the understanding of physical processes in the climate model. This is generally not possible with the scenario-based approach. Here, we present the first application of a PPE to estimate the impact of climate change on heat-related mortality. By using the estimated impacts of climate change on heat-related mortality in six cities, we demonstrate the benefits of quantifying climate model physics uncertainty in climate change impacts assessment over the more common scenario-based approach. We also show that the impacts are more sensitive to climate model physics uncertainty than they are to emissions scenario uncertainty, and least sensitive to whether the climate change projections are from a global climate model or a regional climate model. The results demonstrate the importance of presenting model uncertainties in climate change impacts assessments if the impacts are to be placed within a climate risk management framework.

Evaluating the impact of climate on snow- and ice-melt dynamics in the Taillon basin, French Pyrénées

This pilot study adopts a computer-assisted synoptic typing methodology to evaluate the totality of climatic influences on snow- and ice-melt dynamics within a small cirque basin in the French Pyrenees. The synoptic categories identified possess contrasting large-scale atmospheric circulation patterns and surface energy budgets which generate differential ablation responses. Continental air masses yield consistently high melt. Advection of moist maritime air also produces elevated but more variable ablation due to air-mass transitions. The two observed local valley circulation types show melt to be higher under nocturnal katabatic drainage than for anabatic wind flows associated with development of daytime ridge-top cumulus.

THE IMPACT OF THE 2003 HEAT WAVE ON MORTALITY AND HOSPITAL ADMISSIONS IN ENGLAND

This article quantifies the impact of the heat wave, 4 to 13 August 2003, on mortality and emergency hospital admissions in England by region and age group. The August 2003 heat wave was associated with a large short-term increase in mortality, particularly in London. Overall in England there were 2,091 (17 per cent) excess deaths. Worst affected were those over the age of 75. The greatest increase of any region in England was in London in the over 75 age group with 522 excess deaths (59 per cent). Excess hospital admissions of 16 per cent were recorded in London for the over 75s. Temperatures in England were unusually hot. Ozone and particulate matter concentrations were also elevated during the heat wave. Estimated excess mortality was greater than for other recent heat waves in the UK.

A Comparison of TRMM Microwave Techniques for Detecting the Diurnal Rainfall Cycle

This paper uses rainfall estimates retrieved from active and passive microwave data to investigate how spatially and temporally dependent algorithm biases affect the monitoring of the diurnal rainfall cycle. Microwave estimates used in this study are from the Tropical Rainfall Measuring Mission (TRMM) and include the precipitation radar (PR) near-surface (2A25), Goddard Profiling (GPROF) (2A12), and PR– TRMM Microwave Imager (TMI) (2B31) rain rates from the version 5 (v5) 3G68 product. A rainfall maximum is observed early evening over land, while oceans generally show a minimum in rainfall during the morning. Comparisons of annual and seasonal mean hourly rain rates and harmonics at both global and regional scales show significant differences between the algorithms. Relative and absolute biases over land vary according to the time of day. Clearly, these retrieval biases need accounting for, either in the physics of the algorithm or through the provision of accurate error estimates, to avoid erroneous climatic signals and the discrediting of satellite rainfall estimations.

Performance Assessment of a Heat Wave Vulnerability Index for Greater London, United Kingdom

This study reports on the assessment of a multivariate heat wave vulnerability index (HVI) developed for London, United Kingdom. The HVI is assessed in terms of its ability to predict whether mortality and ambulance callout attain above average levels during heat wave events. Three approaches to assessment were adopted: 1) calculation of categorical statistics and associated skill scores for the dichotomous situation that above average mortality or ambulance callout occurred or not, 2) the degree to which relative risk of the aforementioned health outcomes changed with an increase in heat vulnerability as established using Poisson regression analysis, and 3) an independent samples test of the difference of mean mortality and ambulance callout between census units with and without high heat exposure and high vulnerability. The assessment results reveal that the HVI and a simple single variable index that represents age as a heat risk factor (the elderly index) offer potential as a priori indicators of the level of ambulance callout and mortality for all summer days and heat wave events, respectively. Based on the assessment results the utility of the HVI for heat risk management is discussed.