Sensitivities of ozone and fine particulate matter formation to emissions under the impact of potential future climate change

A review of the technology and applications of methods for evaluating the transport of air pollutants

A variety of methods based on air quality models, including tracer methods, the brute-force method (BFM), decoupled direct method (DDM), high-order decoupled direct method (HDDM), response surface models (RSMs) and so on forth, have been widely used to study the transport of air pollutants. These methods have good applicability for the transport of air pollutants with simple formation mechanisms. However, differences in research conclusions on secondary pollutants with obvious nonlinear characteristics have been reported. For example, the tracer method is suitable for the study of simplified scenarios, while HDDM and RSMs are more suitable for the study for nonlinear pollutants. Multiple observation techniques, including conventional air pollutant observation, lidar observation, air sounding balloons, vehicle-mounted and ship-borne technology, aerial surveys, and remote sensing observations, have been utilized to investigate air pollutant transport characteristics with time resolution as high as 1 sec. In addition, based on a multi-regional input-output model combined with emission inventories, the transfer of air pollutant emissions can be evaluated and applied to study the air pollutant transport characteristics. Observational technologies have advantages in temporal resolution and accuracy, while modeling technologies are more flexible in spatial resolution and research plan setting. In order to accurately quantify the transport characteristics of pollutants, it is necessary to develop a research method for interactive verification of observation and simulation. Quantitative evaluation of the transport of air pollutants from different angles can provide a scientific basis for regional joint prevention and control.

Integrated Modeling of U.S. Agricultural Soil Emissions of Reactive Nitrogen and Associated Impacts on Air Pollution, Health, and Climate

Agricultural soils are leading sources of reactive nitrogen (Nr) species including nitrogen oxides (NO_x), ammonia (NH₃), and nitrous oxide (N₂O). The propensity of NO_x and NH₃ to generate ozone and fine particulate matter and associated impacts on health are highly variable, whereas the climate impacts of long-lived N₂O are independent of emission timing and location. However, these impacts have rarely been compared on a spatially resolved monetized basis. In this study, we update the nitrogen scheme in an agroecosystem model to simulate the Nr emissions from fertilized soils across the contiguous United States. We then apply a reduced-form air pollution health effect model to assess air quality impacts from NO_x and NH₃ and a social cost of N₂O to assess the climate impacts. Assuming an $8.2 million value of a statistical life and a $13,100/ton social cost of N₂O, the air quality impacts are a factor of ∼7 to 15 times as large as the climate impacts in heavily populated coastal regions, whereas the ratios are closer to 2.5 in sparsely populated regions. Our results show that air pollution, health, and climate should be considered jointly in future assessments of how farming practices affect Nr emissions.

Urban heat island (UHI) influence on secondary pollutant formation in a tropical humid environment

The combined action of urbanization (change in land use) and increase in vehicular emissions intensifies the urban heat island (UHI) effect in many cities in the developed countries. The urban warming (UHI) enhances heat-stress-related diseases and ozone (O₃) levels due to a photochemical reaction. Even though UHI intensity depends on wind speed, wind direction, and solar flux, the thermodynamic properties of surface materials can accelerate the temperature profiles at the local scale. This mechanism modifies the atmospheric boundary layer (ABL) structure and mixing height in urban regions. These changes further deteriorate the local air quality. In this work, an attempt has been made to understand the interrelationship between air pollution and UHI intensity at selected urban areas located at tropical environment. The characteristics of ambient temperature profiles associated with land use changes in the different microenvironments of Chennai city were simulated using the Envi-Met model. The simulated surface 24-hr average air temperatures (11 m above the ground) for urban background and commercial and residential sites were found to be 30.81 ± 2.06, 31.51 ± 1.87, and 31.33 ± 2.1ºC, respectively. The diurnal variation of UHI intensity was determined by comparing the daytime average air temperatures to the diurnal air temperature for different wind velocity conditions. From the model simulations, we found that wind speed of 0.2 to 5 m/sec aggravates the UHI intensity. Further, the diurnal variation of mixing height was also estimated at the study locations. The estimated lowest mixing height at the residential area was found to be 60 m in the middle of night. During the same period, highest ozone (O₃) concentrations were also recorded at the continuous ambient air quality monitoring station (CAAQMS) located at the residential area.

IMPLICATIONS

An attempt has made to study the diurnal variation of secondary pollution levels in different study regions. This paper focuses mainly on the UHI intensity variations with respect to percentage of land use pattern change in Chennai city, India. The study simulated the area-based land use pattern with local mixing height variations. The relationship between UHI intensity and mixing height provides variations on local air quality.

The influence of air quality model resolution on health impact assessment for fine particulate matter and its components

Health impact assessments for fine particulate matter (PM2.5) often rely on simulated concentrations generated from air quality models. However, at the global level, these models often run at coarse resolutions, resulting in underestimates of peak concentrations in populated areas. This study aims to quantitatively examine the influence of model resolution on the estimates of mortality attributable to PM2.5 and its species in the USA. We use GEOS-Chem, a global 3-D model of atmospheric composition, to simulate the 2008 annual average concentrations of PM2.5 and its six species over North America. The model was run at a fine resolution of 0.5 × 0.66° and a coarse resolution of 2 × 2.5°, and mortality was calculated using output at the two resolutions. Using the fine-modeled concentrations, we estimate that 142,000 PM2.5-related deaths occurred in the USA in 2008, and the coarse resolution produces a national mortality estimate that is 8 % lower than the fine-model estimate. Our spatial analysis of mortality shows that coarse resolutions tend to substantially underestimate mortality in large urban centers. We also re-grid the fine-modeled concentrations to several coarser resolutions and repeat mortality calculation at these resolutions. We found that model resolution tends to have the greatest influence on mortality estimates associated with primary species and the least impact on dust-related mortality. Our findings provide evidence of possible biases in quantitative PM2.5 health impact assessments in applications of global atmospheric models at coarse spatial resolutions.

Impacts of potential CO2-reduction policies on air quality in the United States

Impacts of emissions changes from four potential U.S. CO2 emission reduction policies on 2050 air quality are analyzed using the community multiscale air quality model (CMAQ). Future meteorology was downscaled from the Goddard Institute for Space Studies (GISS) ModelE General Circulation Model (GCM) to the regional scale using the Weather Research Forecasting (WRF) model. We use emissions growth factors from the EPAUS9r MARKAL model to project emissions inventories for two climate tax scenarios, a combined transportation and energy scenario, a biomass energy scenario and a reference case. Implementation of a relatively aggressive carbon tax leads to improved PM2.5 air quality compared to the reference case as incentives increase for facilities to install flue-gas desulfurization (FGD) and carbon capture and sequestration (CCS) technologies. However, less capital is available to install NOX reduction technologies, resulting in an O3 increase. A policy aimed at reducing CO2 from the transportation sector and electricity production sectors leads to reduced emissions of mobile source NOX, thus reducing O3. Over most of the U.S., this scenario leads to reduced PM2.5 concentrations. However, increased primary PM2.5 emissions associated with fuel switching in the residential and industrial sectors leads to increased organic matter (OM) and PM2.5 in some cities.

A Statistical Modeling Framework for Projecting Future Ambient Ozone and its Health Impact due to Climate Change

The adverse health effects of ambient ozone are well established. Given the high sensitivity of ambient ozone concentrations to meteorological conditions, the impacts of future climate change on ozone concentrations and its associated health effects are of concern. We describe a statistical modeling framework for projecting future ozone levels and its health impacts under a changing climate. This is motivated by the continual effort to evaluate projection uncertainties to inform public health risk assessment. The proposed approach was applied to the 20-county Atlanta metropolitan area using regional climate model (RCM) simulations from the North American Regional Climate Change Assessment Program. Future ozone levels and ozone-related excesses in asthma emergency department (ED) visits were examined for the period 2041-2070. The computationally efficient approach allowed us to consider 8 sets of climate model outputs based on different combinations of 4 RCMs and 4 general circulation models. Compared to the historical period of 1999-2004, we found consistent projections across climate models of an average 11.5% higher ozone levels (range: 4.8%, 16.2%), and an average 8.3% (range: -7% to 24%) higher number of ozone exceedance days. Assuming no change in the at-risk population, this corresponds to excess ozone-related ED visits ranging from 267 to 466 visits per year. Health impact projection uncertainty was driven predominantly by uncertainty in the health effect association and climate model variability. Calibrating climate simulations with historical observations reduced differences in projections across climate models.

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.

Development of risk-based air quality management strategies under impacts of climate change

Climate change is forecast to adversely affect air quality through perturbations in meteorological conditions, photochemical reactions, and precursor emissions. To protect the environment and human health from air pollution, there is an increasing recognition of the necessity of developing effective air quality management strategies under the impacts of climate change. This paper presents a framework for developing risk-based air quality management strategies that can help policy makers improve their decision-making processes in response to current and future climate change about 30-50 years from now. Development of air quality management strategies under the impacts of climate change is fundamentally a risk assessment and risk management process involving four steps: (1) assessment of the impacts of climate change and associated uncertainties; (2) determination of air quality targets; (3) selections of potential air quality management options; and (4) identification of preferred air quality management strategies that minimize control costs, maximize benefits, or limit the adverse effects of climate change on air quality when considering the scarcity of resources. The main challenge relates to the level of uncertainties associated with climate change forecasts and advancements in future control measures, since they will significantly affect the risk assessment results and development of effective air quality management plans. The concept presented in this paper can help decision makers make appropriate responses to climate change, since it provides an integrated approach for climate risk assessment and management when developing air quality management strategies.

IMPLICATIONS

Development of climate-responsive air quality management strategies is fundamentally a risk assessment and risk management process. The risk assessment process includes quantification of climate change impacts on air quality and associated uncertainties. Risk management for air quality under the impacts of climate change includes determination of air quality targets, selections of potential management options, and identification of effective air quality management strategies through decision-making models. The risk-based decision-making framework can also be applied to develop climate-responsive management strategies for the other environmental dimensions and assess costs and benefits of future environmental management policies.

Sensitivity of air pollution-induced premature mortality to precursor emissions under the influence of climate change

The relative contributions of PM(2.5) and ozone precursor emissions to air pollution-related premature mortality modulated by climate change are estimated for the U.S. using sensitivities of air pollutants to precursor emissions and health outcomes for 2001 and 2050. Result suggests that states with high emission rates and significant premature mortality increases induced by PM(2.5) will substantially benefit in the future from SO(2), anthropogenic NO(X) and NH(3) emissions reductions while states with premature mortality increases induced by O(3) will benefit mainly from anthropogenic NO(X) emissions reduction. Much of the increase in premature mortality expected from climate change-induced pollutant increases can be offset by targeting a specific precursor emission in most states based on the modeling approach followed here.

Potential impact of climate change on air pollution-related human health effects

The potential health impact of ambient ozone and PM2.5 concentrations modulated by climate change over the United States is investigated using combined atmospheric and health modeling. Regional air quality modeling for 2001 and 2050 was conducted using CMAQ Modeling System with meteorology from the GISS Global Climate Model, downscaled regionally using MM5,keeping boundary conditions of air pollutants, emission sources, population, activity levels, and pollution controls constant. BenMap was employed to estimate the air pollution health outcomes at the county, state, and national level for 2050 caused by the effect of meteorology on future ozone and PM2.5 concentrations. The changes in calculated annual mean PM2.5 concentrations show a relatively modest change with positive and negative responses (increasing PM2.5 levels across the northeastern U.S.) although average ozone levels slightly decrease across the northern sections of the U.S., and increase across the southern tier. Results suggest that climate change driven air quality-related health effects will be adversely affected in more then 2/3 of the continental U.S. Changes in health effects induced by PM2.5 dominate compared to those caused by ozone. PM2.5-induced premature mortality is about 15 times higher then that due to ozone. Nationally the analysis suggests approximately 4000 additional annual premature deaths due to climate change impacts on PM2.5 vs 300 due to climate change-induced ozone changes. However, the impacts vary spatially. Increased premature mortality due to elevated ozone concentrations will be offset by lower mortality from reductions in PM2.5 in 11 states. Uncertainties related to different emissions projections used to simulate future climate, and the uncertainties forecasting the meteorology, are large although there are potentially important unaddressed uncertainties (e.g., downscaling, speciation, interaction, exposure, and concentration-response function of the human health studies).

Effect of climate change between 1984 and 2007 on precipitation chemistry at a site in northeastern U.S.A

Climate change predictions for the northeastern US call for an increase in tropical storms and a decrease in extra tropical cyclones including continental storms. We ran 24-h back trajectories for each precipitation event that occurred at the Cary Institute of Ecosystem Studies in southeastern New York, U.S.A. from 1984 to 2007 and analyzed precipitation chemistry as well as air mass position 24 h prior to the onset of each precipitation event. The results showed an increase in marine precipitation and a slight but statistically insignificant decrease in continental precipitation during the 1984-2007 period. The chemistry of precipitation from the two directions was quite different marine storms were higher in Na4 and Cl- but lower in solutes associated with acid precipitation (H+, SO4(2-), NO3-, and NH4+). Annual mean concentrations of acid precipitation solutes declined for storms from both directions during the period. We used a simple mixing model based on the current rates of increase and decrease of marine and continental precipitation respectively to show that chemical changes in precipitation resulting from the shift in storm tracks are small compared to chemical changes due to emissions reductions.

Current and future linked responses of ozone and PM2.5 to emission controls

Responses of ozone and PM2.5 to emission changes are coupled because of interactions between their precursors. Here we show the interdependencies of ozone and PM2.5 responses to emission changes in 2001 and 2050, with the future case accounting for both currently planned emission controls and climate change. Current responses of ozone and PM2.5 to emissions are quantified and linked on a daily basis for five cities in the continental United States: Atlanta, Chicago, Houston, Los Angeles, and NewYork. Reductions in anthropogenic NO(x) emissions decrease 24-h average PM2.5 levels but may either increase or decrease daily maximum 8-h average ozone levels. Regional ozone maxima for all the cities are more sensitive to NO(x) reductions than at the city center, particularly in New York and Chicago. Planned controls of anthropogenic NO(x) emissions lead to more positive responses to NO(x) reductions in the future. Sensitivities of ozone and PM2.5 to anthropogenic VOC emissions are predicted to decrease between 2001 and 2050. Ammonium nitrate formation is predicted to be less ammonia-sensitive in 2050 than 2001 while the opposite is true for ammonium sulfate. Sensitivity of PM2.5 to SO2 and NO(x) emissions changes little between 2001 and 2050. Both ammonium sulfate and ammonium nitrate are predicted to decrease in sensitivity to SO2 and NO(x) emissions between 2001 and 2050. The complexities, linkages, and daily changes in the pollutant responses to emission changes suggest that strategies developed to meet specific air quality standards should consider other air quality impacts as well.