Meteorology-driven PM2.5 interannual variability over East Asia

Atmospheric fine particulate matter (PM2.5) is a human health risk factor, but its ambient concentration depends on both precursor emissions and meteorology. While emission reductions are used to set PM2.5-related health policies, the effect of meteorology is often overlooked. To explore this aspect, we examined PM2.5 interannual variability (IAV) associated with meteorological parameters using the long-term simulation from the Community Earth System Model (CESM1), a global climate-chemistry model, with fixed emissions. The results are subsequently contrasted with the MERRA-2 reanalysis dataset, which inherently considers emission and meteorology effects. Over continental East Asia, the CESM1 domain-average PM2.5 IAV is 6.7 %, mainly attributed to humidity, precipitation, and ventilation variation. The grid-cell PM2.5 IAVs over southern East China are larger, up to 12 % due to the more substantial influence of El Niño-induced meteorological anomalies. Under such climate extreme, sub-regional PM2.5 concentration may occasionally exceed WHO air quality guideline levels despite the compliance of the long-term mean. The simulated PM2.5 IAV over continental East Asia is ~25 % of that derived from the MERRA-2 data, which highlights the influence of both emission and meteorology-driven variations and trends inherent in the latter. Although emission-driven variability is significant to PM2.5 IAV, in remote areas downwind of major source regions in East Asia, North America, and Western Europe, the MERRA-2 data revealed that meteorological variations contributed more to PM2.5 IAV than emission variations. Thus, when setting policies for complying with the WHO PM2.5-related air quality guideline levels, the highest annual PM2.5 associated with climate extremes should be considered instead of that based on average climate conditions.

Simulating the effect of urban sprawl on air quality and outdoor human thermal comfort in a cold city, Erzurum, Turkey

Research on climate-sensitive urban planning is important to improve the quality of city life. Cold climate cities should respect climatic characteristics to diversify outdoor uses and increase air quality to maximize the benefits of winter. This study is aimed to explore the impact of changing urban pattern on air pollution and outdoor human thermal comfort conditions (HTCCs) in a newly developed urban area in Şükrüpaşa neighbourhood, Erzurum, among the coldest cities in Turkey, with high PM10 and low HTCCs levels. Sensitivity of urban development pattern to climate conditions and its suitability to eliminate the winter disturbances caused by HTCCs and air pollution were investigated by producing maps for HTCCs and air pollution using morphological, meteorological and spatial data and ENVI-met model in winter period of 2017 and 2022. It was found that newly developed areas increase the unfavourable conditions in terms of air quality, temperature and HTCCs due to the reasons like improper land uses, urban sprawl, high urban density and ventilation problems. In high-elevated cold cities, spatial planning and design principles should strictly be followed by incorporating climate knowledge and without revising the spatial decisions.

Abrupt exacerbation in air quality over Europe after the outbreak of Russia-Ukraine war

Much attention has been paid to the world economy and social situations in response to the outbreak of war between Russia and Ukraine in the context of COVID-19. However, much less attention has been paid to the detrimental effect of war on the atmospheric environment. Here, we used an extended deweathered-detrended technique to quantitatively evaluate changes in ambient NO2, O3, and PM2.5 AQI levels arising from emission changes (due to pandemic-driven lockdowns and war-related activities) in European cities. Results show pandemic-induced lockdowns mitigated regional air pollution in Europe, but the war activities led to an average increase of approximately 9.78% in PM2.5 and 10.07% in NO2, along with an average decrease of about 7.93% in O3 levels in cities near the war zones. Moreover, the regional air pollution exacerbated by the war activities has offset the improvements in air quality observed during the COVID-19 pandemic. The potential mechanism analysis show that the increase in atmospheric pollutant emissions driven by the war activities led to the complexity of chemical reactions in the mixed atmospheric system, which posed a huge challenge to the alleviation of air pollution in the region. This study highlights the urgent need for a ceasefire from an environmental perspective.

Modeling the impacts of land use/land cover change on meteorology and air quality during 2000-2018 in the Yangtze River Delta region, China

The land use/land cover (LULC) change in the fast-developing city clusters of China exhibits impacts on both the meteorology and air quality. However, this effect, especially in the Yangtze River Delta (YRD), has not been well quantified. In this study, the LULC data are extracted from Landsat satellite imageries for year 2000 and 2018 for the YRD region. The Weather Research and Forecasting with Chemistry (WRF/Chem) model is applied to investigate the impact of historical LULC change on regional meteorology and air pollution over the YRD region during the past two decades. Two simulation scenarios are performed with two sets of LULC data to represent the pre-urbanization (LULC of year 2000) and the most recent urban pattern (LULC of year 2018). Results indicate that rapid urbanization leads to an increase of monthly mean 2-m temperature by 0.4-2.1 °C but decrease of the 10-m wind speed by 0.5-1.3 m/s in urban areas; the maximum increase of daytime planetary boundary layer height (PBLH) in July and November is 289 and 132 m, respectively. Affected by favorable changes in the meteorological conditions due to LULC change, the PM_2.5 concentrations in most urban areas show a decreasing trend, especially during the nighttime in summer. On the contrary, surface ozone (O₃) concentration in urban areas has increased by 7.2-9.8 ppb in summer and 1.9-2.1 ppb in winter. Changes in O₃ concentration are inversely proportional to changes in NO_x and the spatial distribution of PM_2.5. Areas with higher O₃ concentration are consistent with areas of higher temperature and lower wind speed. Our findings reveal that LULC changes during the past years bring observable changes in air pollutant concentrations, which should not be neglected in the YRD region regarding air quality trends as well as policy evaluations under the warming threat.

Economic and Life Cycle Analysis of Passive and Active Monitoring of Ozone for Forest Protection

At forest sites, phytotoxic tropospheric ozone (O3) can be monitored with continuously operating, active monitors (AM) or passive, cumulative samplers (PM). For the first time, we present evidence that the sustainability of active monitoring is better than that of passive sensors, as the environmental, economic, and social costs are usually lower in the former than in the latter. By using data collected in the field, environmental, social, and economic costs were analyzed. The study considered monitoring sites at three distances from a control station in Italy (30, 400, and 750 km), two forest types (deciduous and Mediterranean evergreen), and three time windows (5, 10, and 20 years of monitoring). AM resulted in more convenience than PM, even after 5 years, in terms of O3 depletion, global warming, and photochemical O3 creation potential, suggesting that passive monitoring of ozone is not environmentally sustainable, especially for long time periods. AM led to savings ranging from a minimum of EUR 9650 in 5 years up to EUR 94,796 in 20 years in evergreen forests. The resulting social cost of PM was always higher than that of AM. The present evaluation will help in the decision process for the set-up of long-term forest monitoring sites dedicated to the protection of forests from O3.

Responses in PM2.5 and its chemical components to typical unfavorable meteorological events in the suburban area of Tianjin, China

Air pollution is the result of enormous emissions and unfavorable meteorological conditions. The role of meteorology, particularly extremely unfavorable meteorological events (EUMEs), in processing atmospheric PM_2.5 pollution has not been fully addressed. This work examined the variations of PM_2.5 mass and its chemical components associated with various meteorological parameters and three EUMEs based on meteorological observations and analysis combined with one-year long in situ measurement in 2018 in the suburban area of Tianjin, China. Analysis shows that the polluted days in 2018 were mostly related to the increase in sulfate, nitrate, and ammonium (SNA). Temperature between -2 to 13 °C is more favorable for the formation of SNA, while high temperature exceeding 28 °C is favorable for the formation of organic carbon and sulfate. Most of the ions and carbon components showed significant increase in concentrations when relative humidity exceeded 80%. The maximum decreasing rate of PM_2.5 concentrations due to increase in wind speed and planetary boundary height could be 15.35 μg m^-3 (m s^-1)^-1, and 34.37 μg m^-3 (100 m)^-1, respectively. EUMEs showed significant impacts on PM_2.5 components, in which PM_2.5 concentrations showed the most significant increase under temperature inversion (TI) events, and surface-based TI (SBTI) events usually have much stronger impacts on PM_2.5 concentrations than elevated TI (ELTI). Nitrate was found to be the most sensitive component to EUMEs, especially under multiple EUMEs. The synthetic effects of multiple EUMEs could result in an increase of nitrate by 35.53 μg m^-3 (523.3%). In addition, OC and sulfate are more sensitive to heat wave events. Our analysis provides improved understanding of the formation of PM_2.5 pollution with respect to meteorology, particularly EUMEs. Based on such information, more attention may be needed on the collaborative prediction of EUMEs and air pollution episodes.

The Adverse Impact of Air Pollution on China’s Economic Growth

This study empirically evaluates the impact of air pollution on China’s economic growth, based on a province-level sample for the period 2002–2017. Air pollution is measured by the concentration of fine particulate matter (PM2.5), and economic growth is measured by the annual growth rate of gross domestic product (GDP) per capita. A panel data fixed-effects regression model is built, and the instrumental variables estimation method is utilized for quantitative analyses. The study reports a significant negative impact of air pollution on the macroeconomic growth of China. According to our instrumental variables estimation, holding other factors constant, if the concentration of PM2.5 increases by 1%, then the GDP per capita growth rate will decline by 0.05818 percentage points. In addition, it is found that the adverse effect of atmospheric pollution is heterogeneous across different regions. The effect is stronger in the eastern region and in provinces with smaller state-owned enterprise shares, fewer governmental expenditures for public health services, and fewer medical resources. The study results reveal that air pollution poses a substantial threat to the sustainable economic growth of China. Taking actions to abate air pollution will generate great economic benefits, especially for those regions which are heavily damaged by pollution.

Evaluation of adverse effects of particulate matter on human life

Particulate matter (PM_2.5) has a severe impact on human health. The concentration of PM_2.5, related to air-quality changes, may be associated with perceptible effects on people's health. In this study, computer intelligence was used to assess the negative effects of PM_2.5. The input data, used for the evaluation, were grid definitions (shape-file), PM_2.5, air-quality data, incidence/prevalence rates, a population dataset, and the (Krewski) health-impact function. This paper presents a local (Pakistan) health-impact assessment of PM_2.5 in order to estimate the long-term effects on mortality. A rollback-to-a-standard scenario was based on the PM_2.5 concentration of 15 μg m^-3. Health benefits for a population of about 73 million people were calculated. The results showed that the estimated avoidable mortality, linked to ischemic heart disease and lung cancer, was 2,773 for every 100,000 people, which accounts for 2,024,290 preventable deaths of the total population. The total cost, related to the above mortality, was estimated to be US $ 1,000 million. Therefore, a policy for a PM_2.5-standard up to 15 μg m^-3 is suggested.

How changing climate may influence air pollution control strategies for 2030?

Air pollution is a global threat leading to large impacts on human health and ecosystems. In Europe, air quality remains poor in many areas, despite reductions in emissions and ambient concentrations. Air pollution and climate change are the biggest environmental concerns for Europeans, implying concerted and integrated actions to tackle them. The revised 2016 European National Emission Ceilings Directive (NECD) enforces Member States to implement strategies, based on emission reduction measures, aimed to comply with targets by 2030 and achieve European Union (EU) and World Health Organization air quality objectives for environment and health protection. Despite those strategies are designed for 2030, the influence of climate change on air quality is not accounted for. In this sense, the purpose of this paper is the evaluation of the climate change impact on future air quality, taking into consideration emission reduction measures. The WRF-CAMx air quality modelling system was applied over Europe for one year selected as representative of a short-term changing climate (around 2030), and compared to a base case year, to estimate to what extent the climate variables by themselves could positively or negatively influence air quality. Results indicate that meteorological conditions may be decisive for the air quality state in the future. Differences between future and present simulations pointed to a global decrease of ozone levels in the future; increases and decreases in particulate matter and nitrogen dioxide concentrations over different seasons and European regions. This work is intended to contribute to a better understanding of the influence of climate variables on air quality improvement strategies as an additional support to European environmental authorities in developing the National Air Pollution Control Programmes in the scope of NECD.

Monitoring, Mapping, and Modeling Spatial-Temporal Patterns of PM2.5 for Improved Understanding of Air Pollution Dynamics Using Portable Sensing Technologies

Fine particulate matter with an aerodynamic diameter of less than 2.5 µm (PM2.5) is highly variable in space and time. In this study, the dynamics of PM2.5 concentrations were mapped at high spatio-temporal resolutions using bicycle-based, mobile measures on a university campus. Significant diurnal and daily variations were revealed over the two-week survey, with the PM2.5 concentration peaking during the evening rush hours. A range of predictor variables that have been proven useful in estimating the pollution level was derived from Geographic Information System, high-resolution airborne images, and Light Detection and Ranging (LiDAR) datasets. Considering the complex interplay among landscape, wind, and air pollution, variables influencing the PM2.5 dynamics were quantified under a new wind wedge-based system that incorporates wind effects. Panel data analysis models identified eight natural and built environment variables as the most significant determinants of local-scale air quality (including four meteorological factors, distance to major roads, vegetation footprint, and building and vegetation height). The higher significance level of variables calculated using the wind wedge system as compared to the conventional circular buffer highlights the importance of incorporating the relative position of emission sources and receptors in modeling.

Estimation of monthly surface air temperatures from MODIS LST time series data: application to the deserts in the Sultanate of Oman

Air temperature records in remote deserts and inaccessible mountainous regions rely upon data acquired from the nearest meteorological stations, which could be at tens of kilometers apart. The present study provides a reliable approach to extract air temperatures for any distant region using thermal data of satellite images. The study postulates that if there is a strong correlation between land surface temperatures (LST) from satellite images and air temperature records from ground meteorological stations, hence, air temperatures (day/night) could be directly extrapolated from regression equations with high confidence results. Data utilized in this study were obtained from 12 meteorological stations settled and distributed upon different physiographic units of Oman. Satellite images were acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) LST product. Regression analysis of max and min air temperatures from weather stations was conducted versus day and night LST from MODIS Aqua LST (MYD11A2) images. Results showed that the regression coefficients for the selected locations are strong for the night/min (R² = 0.81-0.94) and day/max (R² = 0.72-0.92) correlations of the 12 stations. The root mean square errors (RMSE) of the statistical models are 0.97 and 1.98 for the night and day temperatures, respectively. Moreover, the association between each pair of the data is significant at the 99% level (p < 0.01). As MODIS data cover large geographic extents, it was possible to produce national diurnal and annual air temperature maps of accurate records with considering the variation of the physiographic setting.

Mechanism of Spatiotemporal Air Quality Response to Meteorological Parameters: A National-Scale Analysis in China

The air quality over China exhibits seasonal and regional variation, resulting from heterogeneity in industrialization, and is highly affected by variability in meteorological conditions. We performed the first national-scale exploration of the relationship between the Air Pollution Index (API) and multiple meteorological parameters in China, using partial correlation and hierarchical cluster analyses. Relative humidity, wind speed, and temperature were the dominant factors influencing air quality year-round, due to their significant effects on pollutant dispersion and/or transformation of pollutants. The response of the API to single or multiple meteorological factors varied among cities and seasons, and a regional clustering of response mechanisms was observed, particularly in winter. Clear north–south differentiation was detected in the mechanisms of API response to relative humidity and wind speed. These findings provide insight into the spatiotemporal variation in air quality sensitivity to meteorological conditions, which will be useful for implementing regional air pollution control strategies.

Exploration of the heterogeneous effect of climate change on ozone concentration in an urban environment

Ozone is a significant causative agent of mortality in cities. Urban environments are expressly vulnerable to global warming because of the extensive emission of air pollutants with urban heat island effect enhancing much rapidly the ozone concentration than in the less urbanized regions. This effect previously was not studied in local scale. It was hypothesized that climate change will cause heterogenic increase of ozone concentration in the different parts of the cities. To study this effect, the near-surface ozone concentration of 10 points of a Hungarian city was measured and modeled. At first step, the local correlations between solar radiation, air temperature, relative humidity and the near surface ozone concentrations at 3 m height were determined, specifying the local ozone-producing conditions. Then, based on the scenario of the Intergovernmental Panel on Climate Change 5th assessment report, the future seasonal near-surface ozone concentrations were modeled. Based on the model, it was determined that climate change will result in a heterogenic increase of near-surface ozone concentration.

Responses of PM2.5 and O3 concentrations to changes of meteorology and emissions in China

Tremendous efforts have been made to reduce the severe air pollution in China since 2013. However, the annual and peak fine particulate matter (PM_2.5) concentrations during severe events in winter did not always reduce as expected. This is partially due to the inter-annual variation of meteorology, which affects the emission, transport, transformation, and deposition processes of air pollutants. In this study, the responses of PM_2.5 and ozone (O₃) concentrations to changes in emission and meteorology from 2013 to 2015 were investigated based on ambient measurements and the Community Multi-Scale Air Quality (CMAQ) model simulations with anthropogenic emissions. It is found that emission reductions in 2014 and 2015 effectively reduced PM_2.5 concentrations by 23.9 and 43.5 μg/m³, respectively, but was partially counteracted by unfavorable meteorology. The negative effects from unfavorable meteorology were significant in extreme pollution events. For example, in December 2015, unfavorable meteorology caused a great increase (90 μg/m³) of PM_2.5 in Beijing. Reduction of primary PM and gaseous precursors led to 13.4 and 16.5 ppb increase of O₃-8 h daily concentrations in the summertime in 2014 and 2015 in comparison of 2013, which was likely caused by the increase of solar actinic flux due to PM reduction. In addition, reduction of nitrogen oxides (NOx) emissions in areas with negative NOx-O₃ sensitivity could lead to an increase of O₃ formation when the reduction of volatile organic compounds (VOCs) was not sufficient. This unintended enhanced O₃ formation could also lead to higher O₃ in downwind areas. This study emphasizes the role of meteorology in pollution control, validates the effectiveness of PM_2.5 control measures in China, and highlights the importance of appropriate joint reduction of NOx and VOCs to simultaneously decrease O₃ and PM_2.5 for higher air quality.

Comprehensively assessing the drivers of future air quality in California

In this study we analyze the impact of major drivers of future air quality, both separately and simultaneously, for the year 2035 in three major California air basins: the South Coast Air Basin (SoCAB), the San Francisco Bay Area (SFBA), and the San Joaquin Valley (SJV). A variety of scenarios are considered based on changes in climate-driven meteorological conditions and both biogenic and anthropogenic emissions. Anthropogenic emissions are based on (1) the California Air Resources Board (CARB) California Emissions Projection Analysis Model (CEPAM), (2) increases in electric sector emissions due to climate change, and (3) aggressive adoption of alternative energy technologies electrification of end-use technologies, and energy efficiency measures. Results indicate that climate-driven changes in meteorological conditions will significantly alter day-to-day variations in future ozone and PM_2.5 concentrations, likely increasing the frequency and severity of pollution periods in regions that already experience poor air quality and increasing health risks from pollutant exposure. Increases in biogenic and anthropogenic emissions due to climate change are important during the summer seasons, but have little effect on pollutant concentrations during the winter. Results also indicate that controlling anthropogenic emissions will play a critical role in mitigating climate-driven increases in both ozone and PM_2.5 concentrations in the most populated areas of California. In the absence of anthropogenic emissions controls, climate change will worsen ozone air quality throughout the state, increasing exceedances of ambient air quality standards. If planned reductions in anthropogenic emissions are implemented, ozone air quality throughout the less urban areas of the state may be improved in the year 2035, but regions such as the SoCAB and the east SFBA will likely continue to experience high ozone concentrations throughout the summer season. Climate change and anthropogenic emissions controls are both found to decrease wintertime PM_2.5 concentrations in the SJV, eliminating nearly all exceedances of PM_2.5 National Ambient Air Quality Standards (NAAQS) in the year 2035. However, reductions in anthropogenic emissions are unable to fully mitigate the impact of climate change on PM_2.5 concentrations in the SoCAB and east SFBA. Thus, while future air quality in the SJV is projected to be improved in the year 2035, air quality in the SoCAB and east SFBA will remain similar or marginally worsen compared to present day levels. Conversely, we find that aggressive adoption of alternative energy technologies including renewable resources, electrification of end-use technologies, and energy efficiency measures can offset the impacts of climate change. Overall, the two main drivers for air quality in 2035 are changes in meteorological conditions due to climate change and reductions in anthropogenic emissions.

Ambient particulate air pollution (PM2.5) is associated with the ratio of type 2 diabetes to obesity

We used county level data for T2D prevalence across the mainland USA and matched this to county level ambient PM2.5. Multiple linear regression was used to determine the relation between prevalence of T2D with PM2.5 after adjustment for confounding factors. PM2.5 explained 6.3% of the spatial variation in obesity, and 17.9% of the spatial variation in T2D. After correcting the T2D prevalence for obesity, race, poverty, education and temperature, PM2.5 still explained 8.3% of the residual variation in males (P < 0.0001) and 11.5% in females (P < 0.0001). The effect on obesity prevalence corrected for poverty, race education and temperature was much lower and hence the ratio of T2D to obesity prevalence was significantly associated with PM2.5 in males (R2 = 11.1%, P < 0.0001) and females (R2 = 16.8%, P < 0.0001). This association was repeated across non-African countries (R2 = 14.9%, P < 0.0001). High levels of PM2.5 probably contribute to increased T2D prevalence in the USA, but have a more minor effect on the obesity. Exposure to high environmental levels of PM2.5 (relative to the USA) may explain the disproportional risk of T2D in relation to obesity in Asian populations.

Influence of ambient temperature on the heterogeneity of ambient fine particle chemical composition and disease prevalence

In this study, we present the associations of fine particle nitrate, sulfate, and four organic carbon fractions with ambient temperature in urban and background monitoring sites in the United States for the 2011-2012 period. Nitrate concentrations increased for decreasing temperatures, while sulfate levels increased for temperatures higher than 14 °C. The profiles of organic carbon fractions for different temperatures were comparable to that observed for elemental carbon, a thermally stable and non-reactive component emitted from combustion-related sources. The trends for all parameters were comparable for the nine regions and independent to emission estimates of fine particles and their precursors. These patterns demonstrated that ambient temperature may manipulate fine particulate composition. These differences may be augmented by rising temperatures due to changing climate. Considering the causal associations between particulate pollution and pulmonary and cardiovascular diseases, changes in the composition of particulate pollution may imply adjustments on the human health impacts.

Public Health Costs of Primary PM2.5 and Inorganic PM2.5 Precursor Emissions in the United States

Current methods of estimating the public health effects of emissions are computationally too expensive or do not fully address complex atmospheric processes, frequently limiting their applications to policy research. Using a reduced-form model derived from tagged chemical transport model (CTM) simulations, we present PM2.5 mortality costs per tonne of inorganic air pollutants with the 36 km × 36 km spatial resolution of source location in the United States, providing the most comprehensive set of such estimates comparable to CTM-based estimates. Our estimates vary by 2 orders of magnitude. Emission-weighted seasonal averages were estimated at $88,000-130,000/t PM2.5 (inert primary), $14,000-24,000/t SO2, $3,800-14,000/t NOx, and $23,000-66,000/t NH3. The aggregate social costs for year 2005 emissions were estimated at $1.0 trillion dollars. Compared to other studies, our estimates have similar magnitudes and spatial distributions for primary PM2.5 but substantially different spatial patterns for precursor species where secondary chemistry is important. For example, differences of more than a factor of 10 were found in many areas of Texas, New Mexico, and New England states for NOx and of California, Texas, and Maine for NH3. Our method allows for updates as emissions inventories and CTMs improve, enhancing the potential to link policy research to up-to-date atmospheric science.

Projecting future air pollution-related mortality under a changing climate: progress, uncertainties and research needs

BACKGROUND

Climate change may affect mortality associated with air pollutants, especially for fine particulate matter (PM2.5) and ozone (O3). Projection studies of such kind involve complicated modelling approaches with uncertainties.

OBJECTIVES

We conducted a systematic review of researches and methods for projecting future PM2.5-/O3-related mortality to identify the uncertainties and optimal approaches for handling uncertainty.

METHODS

A literature search was conducted in October 2013, using the electronic databases: PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 to September 2013.

DISCUSSION

Fifteen studies fulfilled the inclusion criteria. Most studies reported that an increase of climate change-induced PM2.5 and O3 may result in an increase in mortality. However, little research has been conducted in developing countries with high emissions and dense populations. Additionally, health effects induced by PM2.5 may dominate compared to those caused by O3, but projection studies of PM2.5-related mortality are fewer than those of O3-related mortality. There is a considerable variation in approaches of scenario-based projection researches, which makes it difficult to compare results. Multiple scenarios, models and downscaling methods have been used to reduce uncertainties. However, few studies have discussed what the main source of uncertainties is and which uncertainty could be most effectively reduced.

CONCLUSIONS

Projecting air pollution-related mortality requires a systematic consideration of assumptions and uncertainties, which will significantly aid policymakers in efforts to manage potential impacts of PM2.5 and O3 on mortality in the context of climate change.

Global air quality and climate

Emissions of air pollutants and their precursors determine regional air quality and can alter climate. Climate change can perturb the long-range transport, chemical processing, and local meteorology that influence air pollution. We review the implications of projected changes in methane (CH(4)), ozone precursors (O(3)), and aerosols for climate (expressed in terms of the radiative forcing metric or changes in global surface temperature) and hemispheric-to-continental scale air quality. Reducing the O(3) precursor CH(4) would slow near-term warming by decreasing both CH(4) and tropospheric O(3). Uncertainty remains as to the net climate forcing from anthropogenic nitrogen oxide (NO(x)) emissions, which increase tropospheric O(3) (warming) but also increase aerosols and decrease CH(4) (both cooling). Anthropogenic emissions of carbon monoxide (CO) and non-CH(4) volatile organic compounds (NMVOC) warm by increasing both O(3) and CH(4). Radiative impacts from secondary organic aerosols (SOA) are poorly understood. Black carbon emission controls, by reducing the absorption of sunlight in the atmosphere and on snow and ice, have the potential to slow near-term warming, but uncertainties in coincident emissions of reflective (cooling) aerosols and poorly constrained cloud indirect effects confound robust estimates of net climate impacts. Reducing sulfate and nitrate aerosols would improve air quality and lessen interference with the hydrologic cycle, but lead to warming. A holistic and balanced view is thus needed to assess how air pollution controls influence climate; a first step towards this goal involves estimating net climate impacts from individual emission sectors. Modeling and observational analyses suggest a warming climate degrades air quality (increasing surface O(3) and particulate matter) in many populated regions, including during pollution episodes. Prior Intergovernmental Panel on Climate Change (IPCC) scenarios (SRES) allowed unconstrained growth, whereas the Representative Concentration Pathway (RCP) scenarios assume uniformly an aggressive reduction, of air pollutant emissions. New estimates from the current generation of chemistry-climate models with RCP emissions thus project improved air quality over the next century relative to those using the IPCC SRES scenarios. These two sets of projections likely bracket possible futures. We find that uncertainty in emission-driven changes in air quality is generally greater than uncertainty in climate-driven changes. Confidence in air quality projections is limited by the reliability of anthropogenic emission trajectories and the uncertainties in regional climate responses, feedbacks with the terrestrial biosphere, and oxidation pathways affecting O(3) and SOA.

Observed suppression of ozone formation at extremely high temperatures due to chemical and biophysical feedbacks

Ground level ozone concentrations ([O(3)]) typically show a direct linear relationship with surface air temperature. Three decades of California measurements provide evidence of a statistically significant change in the ozone-temperature slope (Δm(O3-T)) under extremely high temperatures (> 312 K). This Δm(O3-T) leads to a plateau or decrease in [O(3)], reflecting the diminished role of nitrogen oxide sequestration by peroxyacetyl nitrates and reduced biogenic isoprene emissions at high temperatures. Despite inclusion of these processes in global and regional chemistry-climate models, a statistically significant change in Δm(O3-T) has not been noted in prior studies. Future climate projections suggest a more frequent and spatially widespread occurrence of this Δm(O3-T) response, confounding predictions of extreme ozone events based on the historically observed linear relationship.

Detailed chemical analysis of regional-scale air pollution in western Portugal using an adapted version of MCM v3.1

A version of the Master Chemical Mechanism (MCM) v3.1, refined on the basis of recent chamber evaluations, has been incorporated into a Photochemical Trajectory Model (PTM) and applied to the simulation of boundary layer photochemistry in the Portuguese west coast region. Comparison of modelled concentrations of ozone and a number of other species (NO(x) and selected hydrocarbons and organic oxygenates) was carried out, using data from three connected sites on two case study days when well-defined sea breeze conditions were established. The ozone concentrations obtained through the application of the PTM are a good approximation to the measured values, the average difference being ca. 15%, indicating that the model was acceptable for evaluation of the details of the chemical processing. The detailed chemistry is examined, allowing conclusions to be drawn concerning chemical interferences in the measurements of NO(2), and in relation to the sensitivity of ozone formation to changes in ambient temperature. Three important, and comparable, contributions to the temperature sensitivity are identified and quantified, namely (i) an effect of increasing biogenic emissions with temperature; (ii) an effect of increasing ambient water vapour concentration with temperature, and its influence on radical production; and (iii) an increase in VOC oxidation chain lengths resulting from the temperature-dependence of the kinetic parameters, particularly in relation to the stability of PAN and its higher analogues. The sensitivity of the simulations to the refinements implemented into MCM v3.1 are also presented and discussed.

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, air quality, and human health

Weather and climate play important roles in determining patterns of air quality over multiple scales in time and space, owing to the fact that emissions, transport, dilution, chemical transformation, and eventual deposition of air pollutants all can be influenced by meteorologic variables such as temperature, humidity, wind speed and direction, and mixing height. There is growing recognition that development of optimal control strategies for key pollutants like ozone and fine particles now requires assessment of potential future climate conditions and their influence on the attainment of air quality objectives. In addition, other air contaminants of relevance to human health, including smoke from wildfires and airborne pollens and molds, may be influenced by climate change. In this study, the focus is on the ways in which health-relevant measures of air quality, including ozone, particulate matter, and aeroallergens, may be affected by climate variability and change. The small but growing literature focusing on climate impacts on air quality, how these influences may play out in future decades, and the implications for human health is reviewed. Based on the observed and anticipated impacts, adaptation strategies and research needs are discussed.

Climate change and allergic disease

Climate change is potentially the largest global threat to human health ever encountered. The earth is warming, the warming is accelerating, and human actions are largely responsible. If current emissions and land use trends continue unchecked, the next generations will face more injury, disease, and death related to natural disasters and heat waves, higher rates of climate-related infections, and wide-spread malnutrition, as well as more allergic and air pollution-related morbidity and mortality. This review highlights links between global climate change and anticipated increases in prevalence and severity of asthma and related allergic disease mediated through worsening ambient air pollution and altered local and regional pollen production. The pattern of change will vary regionally depending on latitude, altitude, rainfall and storms, land-use patterns, urbanization, transportation, and energy production. The magnitude of climate change and related increases in allergic disease will be affected by how aggressively greenhouse gas mitigation strategies are pursued, but at best an average warming of 1 to 2 degrees C is certain this century. Thus, anticipation of a higher allergic disease burden will affect clinical practice as well as public health planning. A number of practical primary and secondary prevention strategies are suggested at the end of the review to assist in meeting this unprecedented public health challenge.