The Georgia Basin-Puget Sound Airshed Characterization Report 2014: chapter 13


13. Air Quality and Climate Change

Brian Lamb, Serena Chung, Rodrigo Gonzales, Jeremy Avise (Washington State University),Janya Kelly, David Plummer, Paul Makar and Bill Taylor (Environment Canada)

The impacts of climate change during the 21st Century are likely to be pervasive; air quality will not be an exception. The air quality scenarios outlined in previous chapters consist of projections based solely on proposed emission controls or the implementation of air quality management actions. These projections assumed that other factors such as meteorology were held constant in order to isolate the effect of future emissions on ambient concentrations. A more realistic picture of future air quality, however, would be obtained by taking into account a host of other environmental changes that are expected to occur with a changing climate. While the popular and perhaps simplistic view of global warming may be limited to thinking about higher temperatures, this chapter takes a broader view of the many climate related global environmental changes that are projected to occur over the course of the 21st Century, and their potential effects on air quality. This perspective on climate change is referred to as global change.

13.1 Global Change

Global change encompasses myriad effects of climate warming, changes in anthropogenic pollutant emissions, and changes in land use/ land cover due to climate effects, urbanization, and land management decisions. Each of these aspects of global change has the potential to change air pollution levels on local to regional scales. In the Pacific Northwest, the intersection of local climate change, urbanization, land use/ land cover change, and long range transport of Asian air pollutants in the future, provides a complex set of conditions for air quality management. In this chapter, the effects of these changes are briefly reviewed and recent results based upon dynamic downscaling of climate simulations and global chemical transport modelling are presented. The objective is to demonstrate the types and extent of impact related to global change and air quality.

Climate change, in the absence of other global change features, can have effects upon ozone and PM levels in a variety of ways. These include the effects of warmer temperatures on chemical reaction rates, enhanced atmospheric moisture which can reduce ozone levels, but possibly increased PMmass, changes in wet deposition rates associated with changes in precipitation and increases in biogenic emissions due to warmer temperatures and enhanced biochemical processes. Climate change is expected to increase the occurrence of wildfires which can also have important air pollution implications on a regional basis. 

During the past decade, the U.S. EPA has sponsored a number of research programs designed to assess the impact of global change upon future air quality. Within these separate research projects, there are a variety of methods, models, and global scenarios addressed. Weaver et al. (2009) provided a synthesis of many of these projects and found that in general there is a climate penalty associated with ozone such that warmer future conditions leads to higher ozone levels (with constant emissions) such that greater reductions in VOC and/or NOx emissions will be required to maintain acceptable ozone levels compared to current climate conditions. For PM, the effects of climate are more complex and current results do not provide a clear indication of the overall effect of climate change on PM under future conditions (Jacob and Winner, 2009). 

In Canada, researchers at Environment Canada have successfully coupled the chemical transport model, AURAMS (A Unified Regional Air Quality Modelling System) with the Canadian Regional Climate Model (CRCM 4.2) to model the effects of climate change on concentrations of ozone, PM2.5 and its precursors over North America. The results of these modelling efforts are discussed later in this chapter.

13.2 Global and Regional Climate Change Models and Scenarios

Since concentrations of greenhouse gases are a major factor in the earth’s energy budget, one of the great uncertainties in climate change modelling is related to estimating future greenhouse gas emissions. In the 21st Century, humanity could embark on any one of several possible economic, political, social, and technological pathways, each leading to a diverse suite of activities that produce greenhouse gases. Since the future cannot be known with any degree of certainty, approaches to modelling climate change must rely on generating plausible emission scenarios based on varying sets of assumptions about the future.

The Intergovernmental Panel on Climate Change (IPCC) was established by the United Nations and the World Meteorological Organization as a scientific body to review and assess scientific and socio-economic information on the risks of climate change. The IPCChas published an updated assessment every five years or so since 1990 with the latest (Fourth Assessment Report) being published in 2007. In preparation for the Third Assessment Report in 2001, a committee of the IPCC prepared a Special Report on Emissions Scenarios (SRES) to guide the conduct of climate change studies (Nakicenovic et al., 2000). The SRES scenarios provide estimates of future greenhouse gas emissions based on varying assumptions about population growth, economic development, technology and changes in land use. There are 40 different SRESscenarios which are grouped into four broad scenario families named A1, A2, B1 and B2. Each scenario family is depicted by a century-long projection of global greenhouse gas emissions, as shown in Figure 13.1.

The following is a brief description of the four scenario families:

  • The A1 scenario family describes a future world of very rapid economic growth, global population that peaks in mid-century and declines thereafter and the rapid introduction of new and more efficient technologies. The A1 family has three sub-level scenarios that describe alternate directions of technological change in the energy system: the fossil intensive (A1FI), non-fossil energy sources (A1T ) and a balance across all sources (A1B).
  • The A2 scenario family describes a very heterogeneous world where the underlying theme is self-reliance and preservation of local identities. Fertility patterns and economic development is primarily regionally oriented. Global population is expected to continuously increase slowly, while technological change is more fragmented and slower than in other scenarios.
  • The B1 scenario family describes the same global population peak occurring in mid-century and declines thereafter, but with rapid changes in economic structures toward a service and information economy with reduction in material intensity and the introduction of clean and resource-efficient technologies. The emphasis is on global solutions to economic, social, and environmental sustainability, including improved equity, but without additional climate initiatives.
  • B2 scenario family describes a world with emphasis on local solutions to economic, social and environmental sustainability. Global population is expected to continuously increase at a rate lower than the A2 scenario. It is a world with intermediate levels of economic development and less rapid, although more diverse technological change than in the B1 and A1 scenarios. This scenario is oriented toward environmental protection and social equity on local and regional levels.

 

Figure 13.1 Four SRES scenarios depicting different projections of greenhouse gas emissions for the 21st century. (Adapted from IPCC, 2000.)

Figure 13.1 Four SRES scenarios depicting different projections of greenhouse gas emissions for the 21st century. (Adapted from IPCC, 2000.) (See long description below)

Note: Total global annual CO2 emissions from all sources (energy, industry, and land-use change) from 1990 to 2100 (in gigatonnes of carbon (GtC/yr)) for the families and six scenario groups. The 40 SRES scenarios are presented by the four families (A1, A2, B1, and B2) and six scenario groups: the fossil-intensive A1FI (comprising the high-coal and high-oil-and gas scenarios), the predominantly non-fossil fuel A1T , the balanced A1B in Figure 13.1a; A2 (slow technological change) in Figure 13.1b; B1 (rapid changes in economic structure and resource-efficient technologies) in Figure 13.1c, and B2 (less rapid but diverse technological change) in Figure 13.1d. Each coloured emission band shows the range of scenarios within each group. For each of the six scenario groups an illustrative scenario is provided, including the four illustrative marker scenarios (A1, A2, B1, B2, solid lines) and two illustrative scenarios for A1FI and A1T (dashed lines) (from IPCC, 2000).

Description of Figure 13.1

Figure 13.1 is composed of four panels each with a plot of total global annual CO2 emissions from all sources (energy, industry, and land-use change) in gigatonnes of carbon per year (GtC/yr) as a function of year from 1990 to 2100. Each panel presents one of the four broad SRES scenario families. In Panel A there is the A1 scenario family including the fossil-fuel intensive A1FI (comprising the high-coal and high-oil-and gas scenarios), the predominantly non-fossil fuel A1T , and the balanced A1B; In Panel B there is the A2 scenario family  (slow technological change);  In Panel C there is the B1 scenario family (rapid changes in economic structure and resource-efficient technologies); and In Panel D there is the B2 scenario family (less rapid but diverse technological change). Plotted in each panel is a coloured emission band which shows the range of scenarios within each group. Six illustrative scenarios are provided, including the four illustrative marker scenarios (A1, A2, B1, B2, solid lines) and two illustrative scenarios for A1FI and A1T (dashed lines).

In Panel A the A1FIscenario shows CO2emissions increasing rapidly from 1990 levels of approximately 8 GtC/yr to approximately 25 GtC/yr in 2050 (range 22-27 GtC/yr) and then leveling slowly by 2080 at approximately 29 GtC/yr (range in coloured emission band is 27-35 GtC/yr). The A1B scenario shows CO2 emissions increasing slowly from 1990 levels to approximately 17 GtC/yr in 2050 (range in coloured emission band is 13-25 GtC/yr) and then declining slightly by 2100 to approximately 15 GtC/yr (range in coloured emission band is 15-19 GtC/yr).  The A1T scenario shows CO2 emissions increasing slowly from 1990 levels to approximately 12 GtC/yr in 2040 (range 10-12 in coloured emission band is GtC/yr) and then declining by 2100 to approximately 5 GtC/yr (range in coloured emission band is 5-10 GtC/yr).

In Panel B the A2 scenario shows CO2 emissions increasing quite steadily from 1990 levels of approximately 8 GtC/yr to approximately 29 GtC/yr in 2100. At the low emission end of the range of scenarios within emissions remain steady from 1990 to 2030 and then rise to approximately 22 GtC/yr in 2100. At the high emission end of the range of scenarios emissions in 2100 are approximately 35 GtC/yr.

In Panel C the B1 scenario shows CO2 emissions increasing slightly from 1990 levels of approximately 8 GtC/yr to approximately 12 GtC/yr in 2040 (range in coloured emission band is 9-18 GtC/yr) and then declining by 2100 to approximately 5 GtC/yr (range in coloured emission band is 2-11 GtC/yr).

In Panel D the B2 scenario shows CO2 emissions increasing quite steadily from 1990 levels of approximately 8 GtC/yr to approximately 12 GtC/yr in 2100. This is close to the low emission end of the range of scenarios. At the high emission end of the range of scenarios emissions in 2100 are approximately 22 GtC/yr.

 

In preparation for the IPCC Fifth Assessment Report, a new set of scenarios called Representative Concentration Pathways (RCP) was developed for the climate modelling community (Moss et al., 2008). The primary goal of the RCPs is to provide, in a timely manner, the most up to date scenarios possible to be used to produce new climate model simulations (van Vuuren et al., 2008). The RCPs are four independent pathways developed by four individual modelling groups and are named according to their 2100 radiative forcing level as reported by the individual modelling teams. Unlike the SRESscenarios, the trajectories of the RCP scenarios are not associated with unique socioeconomic or emission scenarios and instead can result from different combinations of economic, technological, demographic, policy and instructional futures. The research community identified a specific emission scenario (including data on land use and land cover) from the peer-reviewed literature as a plausible pathway towards reaching each target radiative forcing trajectory (Moss et al., 2010). Figure 13.2 illustrates how the selected RCPs (2.6, 4.5, 6.0 and 8.5) represent the literature in terms of radiative forcing (Figure 13.2a) and energy and industry CO2 emissions (Figure 13.2b). The selected set of RCPs spans the range of radiative forcing scenarios in the published literature at September 2007 (Moss et al., 2010). For energy and industry CO2 emissions, RCP8.5 represents the 90th percentile of the reference emissions range, while RCP2.6 represents pathways below the 10thpercentile of mitigation scenarios.

 

Figure 13.2 Four RCP scenarios depicting different projections of greenhouse gas emissions for the 21st century. (Adapted from IPCC, 2000)

Figure 13.2 Four RCP scenarios depicting different projections of greenhouse gas emissions for the 21st century. (Adapted from IPCC, 2000) (See long description below)

Notes:

a) Changes in radiative forcing relative to pre-industrial conditions. Bold coloured lines show the four RCPs; thin lines show individual scenarios from approximately 30 candidate RCP scenarios that provide information on all key factors affecting radiative forcing from van Vuuren et al. (2008) and the larger set analysed by IPCC Working Group III during development of the Fourth Assessment Report (Fisher et al., 2007).
b) Energy and industry CO2 emissions for the RCPcandidates. The range of emissions in the post-SRES literature is presented for the maximum and minimum (thick dashed curve) and 10th to 90th percentile (shaded area). Blue shaded area corresponds to mitigation scenarios; grey shaded area corresponds to reference scenarios; pink area represents the overlap between reference and mitigation scenarios.

Description of Figure 13.2

Figure 13.2 is composed of two panels.  In Panel A changes in radiative forcing relative to pre-industrial conditions are shown as a function of year from 2000 to 2100. Bold coloured lines show the four selected RCPs; thin lines show individual scenarios from approximately 30 candidate RCP scenarios that provide information on all key factors affecting radiative forcing from van Vuuren et al. (2008) and the larger set analysed by IPCCWorking Group III during development of the Fourth Assessment Report (Fisher et al., 2007). The four selected RCPs are MESSAGE 8.5, AIM 6.0, GCAM 4.5, and IMAGE 2.6.  MESSAGE 8.5 represents the most extreme change in radiative forcing, rising steadily from a change of approximately 2 W/m2 in 2000 to a change of approximately 8.5 W/m2 in 2100. AIM 6.0 shows a more moderate change in radiative forcing, rising steadily from a change of approximately 2 W/m2 in 2000 to a change of approximately 6 W/m2 in 2100.  GCAM 4.5 rises steadily to a change of approximately 4 W/m2 in 2060 and then levels off from 2070 onwards around 4.5 W/m2.  IMAGE 2.6 shows the most modest increase in radiative forcing for 2100 relative to pre-industrial condition.  It rises to a change of just above 3 W/m2 in 2040 and then falls steadily to a change of approximately 2.6 W/m2 by 2100. The individual scenarios from the approximately 30 candidate RCPscenarios all fall within the range defined by MESSAGE 8.5 and IMAGE 2.6.

Panel B shows energy and industry CO2 emissions relative to pre-industrial conditions (in Gt) for the RCP candidates as a function of year from 2000 to 2100. The range of emissions in the post-SRES literature is presented for the maximum and minimum (thick dashed curve) and 10th to 90th percentile (shaded area). A blue shaded area corresponds to mitigation scenarios, a grey shaded area corresponds to reference scenarios, and a pink area represents the overlap between reference and mitigation scenarios.  The maximum line starts at approximately 35 Gt in 2000 and goes above the plot maximum of 120 Gt in 2050.  The minimum line starts at just above 20 Gt in 2000 and declines to approximately -15 Gt in 2100.  The 90th percentile line runs from approximately 25 Gt in 2000 to just over 100 Gt in 2100.  The 10th percentile line runs from approximately 25 Gt in 2000 to just above 0 Gt in 2100.  The blue shaded area (mitigation scenarios) extends from the 10th percentile line up to a line that rises slowly from approximately 25 Gt in 2000 to just over 30 Gt in 2040 and then falls to approximately 20 Gt in 2100.  The pink shaded area (overlap between reference and mitigation scenarios) extends from the upper edge of the blue shaded area to a line that rises slowly from approximately 25 Gt in 2000 to just over 40 Gt in 2045 then falls to approximately 30 Gt in 2100.  The grey shaded area (reference scenarios) extends from the upper edge of the pink shaded area to a line that rises from approximately 25 Gt in 2000 to approximately 110 Gt in 2100.  The bold grey line representing MESSAGE 8.5 rises steadily from approximately 25 Gt in 2000 to approximately 90 Gt in 2065 and then shows some signs of leveling off, reaching approximately 100 Gt by 2100.  The bold blue line representing AIM 6.0 rises slowly from approximately 25 Gt in 2000 to approximately 30 Gt in 2035 and then rises more rapidly to approximately 60 Gt in 2080. After 2080 it declines to approximately 45 Gt by 2100. The bold red line representing GCAM 4.5 rises slowly from approximately 25 Gt in 2000 to approximately 40 Gt in 2030 and remains at that level until 2050, after which time it falls to 15 Gt by 2080 and remains at that level through 2100.  The bold green line representing IMAGE 2.6 rises from approximately 25 Gt in 2000 to approximately 30 Gt in 2020 and then falls to -5 Gt by 2100. MESSAGE 8.5 and AIM 6.0 fall within the grey shaded area, GCAM 4.5 starts in the pink shaded area, but falls into the blue shaded area by 2065, and IMAGE 2.6 starts in the blue area but falls below it by 2040.

 

13.3 Washington State University Climate/Air Quality Simulations using CMAQ

Brian Lamb, Serena Chung, Rodrigo Gonzales, Jeremy Avise

Simulating the future global climate is achieved through the application of Global Circulation Models (GCMs) which are mathematical representations of various physical processes in the ocean, land and atmosphere driven by different greenhouse gas scenarios. A number of research centers around the world are actively developing GCMs, and these models provide the basis for the various climate change studies reviewed in the IPCCassessments. For example, the current version of the Canadian model is the Fourth Generation Canadian Coupled Global Climate Model (CanCM4). The Max Planck Institute in Hamburg Germany has developed ECHAM5, and in the United States, the Parallel Climate Model (PCM) has been developed through a multi-agency effort involving the National Center for Atmospheric Research and the Department of Energy. These are but three examples of the dozens of GCMs that are actively under development.

Because the resolution of GCMs is low (horizontal grid scale on the order of hundreds of kilometres), regional scale climate change studies must rely on downscaling of global model results into a form that can be applied at a finer level of detail. Although statistical approaches to downscaling are often used, dynamical downscaling methods will be discussed in this chapter. Dynamical downscaling generally involves nesting a higher resolution regional climate model (RCM) or a mesoscale meteorological model within a GCM over a limited geographical area. The higher resolution model is driven by boundary conditions supplied by the coarser GCM. Similar to GCMs, the development of RCMs takes place at many scientific institutes around the world. In Canada the current regional climate model is the Regional Climate Model (CRCM) version 4.2, while HadRM is a regional climate model developed by the Hadley Centre in the United Kingdom. Mesoscale meteorological models like the ones described in Chapter 10: Regional Air Quality Modelling may also be nested within a larger scale GCM.

13.3.1 Meteorological and Chemical Downscaling

The general approach used in the various EPA-supported projects involve use of GCM output to provide initial and boundary conditions for mesoscale meteorological models such as  the Weather Research Forecast (WRF) model. Similarly, output from global chemical transport models (CTMs), either GEOS-Chem or MOZART, are used to provide initial and boundary conditions for regional air quality models such as the Community Multi-scale Air Quality (CMAQ) model.

Meteorological Downscaling

GCM output is available from a number of modelling groups and for a wide range of IPCC global scenarios, while similar consistent chemical model output can be obtained for the global CTMs. A variety of configurations of global models and IPCCSRESfuture year emissions scenarios (illustrated in Figure 13.1) are represented in the EPA projects.

For example, Washington State University, together with the University of Washington, the National Center for Atmospheric Research, and the U.S. Forest Service, initially employed the NCAR/DOE Parallel Climate Model (PCM) to drive the MM5 mesoscale model using 36 km grid cells in a domain that covered the continental U.S. and used MOZART chemical output to drive CMAQ for the same domain. The A2 business as usual future year scenario was selected. Note that none of those modelling results are presented in this chapter. More recently, this group has moved to using the ECHAM5 GCM output for the A1B scenario to drive the WRF meteorological model. In this latter case, the CMAQ model was applied at a partial hemispheric scale to remove the need for MOZART boundary conditions and to make the treatment of long range transport from Asia more consistent with CMAQ for the continental U.S. The domains used for the WRF downscaling are shown in Figure 13.3

 

Figure 13.3 Downscaling domains used for WRF regional simulations including 108 km, 36 km, and 12 km grid scale domains. A separate 15 km domain used for some model runs driven with the HadRM is also shown.

Figure 13.3 Downscaling domains used for WRF regional simulations including 108 km, 36 km, and 12 km grid scale domains. A separate 15 km domain used for some model runs driven with the HadRM is also shown. (See long description below)

Note: Shadings represent terrain height (m) for the corresponding WRF and HadRM domain

Description of Figure 13.3

Figure 13.3 is a map of North America overlaid with the downscaling domains used for WRF regional simulations.  Domain 1 is the entire map area which extends from the approximately the arctic circle to the equator and encompasses much of the Pacific and Atlantic Oceans.  As described in the text, the outermost WRF domain (Domain 2) covers nearly the entire North American continent (from SE Alaska and Hudson Bay in the north to the Yucatán Peninsula in the south) as well as much of the eastern Pacific Ocean and the western Atlantic Ocean. The 36 km model domain (HadRM) covers the western continental U.S. and part of Canada and Mexico. The innermost model domain (Domain 3) is centered on the Pacific Northwest that includes the states of Washington, Oregon, and Idaho. Also indicated on the map is shading representing terrain height (0-3000m) for the corresponding WRF and HadRM domain.

 

The outermost WRF domain (Domain 2) covers nearly the entire North American continent as well as much of the eastern Pacific Ocean and the western Atlantic Ocean. The use of this large domain ensures that synoptic weather systems approaching the U.S. are well represented by the time they reach the region. The 36 km model domain (HadRM) covers the continental U.S. and part of Canada and Mexico; this domain is the primary focus for the CMAQ simulations presented later in this chapter. The innermost model domain (Domain 3) is centered on the Pacific Northwest that includes the states of Washington, Oregon, and Idaho. For all domains, 31 vertical levels were used in the model with the highest resolution (~ 20 - 100 m) in the boundary layer. The model top was fixed at 50 mb. The climate downscaling, going from GCM to WRF, involves specifying boundary conditions from the GCM and using interior GCM data to nudge the outer domain WRF solution. The finer resolution inner domain WRF solutions are not nudged in this approach, but are driven by the coarser outer domain WRF simulation. This provides results at the 36 km and 12 km grid scales that are driven by large scale climatology from the GCM while at the same time are influenced by regional scale terrain and land cover effects.

Chemical Downscaling

For the chemical downscaling, a hemispheric domain was used with WRF and CMAQto account for the impact of Asian and other large scale impacts upon chemical boundary conditions for the continental U.S. This domain is shown in Figure 13.4 along with the projected change in 2 m surface temperature from current conditions to the 2050 decade based upon the ECHAM5-A1B simulation. 

 

Figure 13.4 50 year projection of summertime surface temperature change over the partial hemispheric domains for WRF & CMAQ simulations.

Figure 13.4 50 year projection of summertime surface temperature change over the partial hemispheric domains for WRF & CMAQ simulations. (See long description below)

Note: Accounts for U.S. chemical boundary conditions and the change in surface temperatures for summertime conditions for the warmest future and current summers from decadal periods of 2045-2054 and 1995-2004. (ECHAM5-A1B model/scenario combination).

Description of Figure 13.4

Figure 13.4 is a line map of North America, the Pacific, and eastern Asia colored by the 50 year projection of summertime surface temperature change (average of 2048 and 2045 minus average of 1996 and 1997).  Also drawn on the map is the hemispheric domain used with WRF and CMAQ to account for the impact of Asian and other large scale impacts upon chemical boundary conditions for the continental U.S. This domain spans an area bounded in the north by a line running between Vancouver Island and Haida Gwaii, passing north of Lake Winnipeg, and reaching the Gulf of St Lawrence.   It is bounded in the south by a line running from the southern tip of the Baja Peninsula, across Mexico to Cuba.  The area immediately offshore of the US Pacific and Atlantic coasts is also included in the domain. 

The 50 year projection of summertime surface temperature change is between 1 and 4°C over much of the map area.  Exceptions include regions in the Sea of Okhotsk, in the Bering Sea, in the northern Gulf of Alaska, and in the Great Lakes with changes of 6-8°C.  Other exceptions are India, the Pacific Northwest of North America, the northern Canadian Prairies, Newfoundland, and the equatorial Pacific which have changes on the order of 0 to -3°C.  The average for the hemispheric domain used with WRF and CMAQ is 1.34°C while the US-Domain average is 1.85°C.

There is a note that the figure accounts for U.S. chemical boundary conditions and the change in surface temperatures for summertime conditions for the warmest future and current summers from decadal periods of 2045-2054 and 1995-2004. (ECHAM5-A1B model/scenario combination).

 

13.3.2 Emissions Inventories

Global emissions of ozone precursor gases from anthropogenic, natural, and  biomass burning sources have been estimated for the period of 1990-2000 (applied to 1995-2004) using the Precursors of Ozone and their Effects in the Troposphere (POET) emission inventory project (GEIA-ACCENT, 2005). Anthropogenic emissions are based on national activity data, emission factors, and gridded maps for spatial distribution of the emissions within a country. Satellite derived fire maps are used for the spatial and temporal distribution of fire emissions. The global tabulation for Black and Organic Carbon was obtained from Bond et al. (2004), who used emission factors on the basis of fuel type and economic sectors alone. The Bond et al. (2004) inventory includes emissions from fossil fuels, biofuels, open biomass burning and burning of urban waste. The dependence on combustion practices is covered by considering combinations of fuel, combustion type, and emission controls and their prevalence on a regional basis.

Three emissions inventories, those from POET, Model of Emissions of gases and Aerosols from Nature (MEGAN), and Bond et al. (2004) were coupled for the year of 2000. Diurnal emissions patterns were developed and applied to the gridded emission inventories and processed using the SMOKE emissions processing tool. Biomass burning emissions were included in the hemispheric emissions from the POET and Bond et al. (2004) emission inventories. For the continental U.S., historical fire data for the 1995-2004 period were employed for both current and future simulations. In future work, a stochastic fire occurrence model will be used to specify future fires.

For biogenic emissions, the MEGAN biogenic emission model (Guenther et al., 2006; Chen et al., 2009) was used with current and future land use/ land cover changes at the global and U.S. scales. For cropland distributions, three datasets were combined:  the IMAGE 2100 global cropland extent dataset, the SAGE maximum cultivable land dataset, and the MODIS current cropland data. The IMAGE 2100 dataset was created from the output of a land cover model (LCM, Zuidema et al., 1994) which forms part of a sub-system of the IMAGE 2.0 model of global climate change (Alcamo, 1994). The SAGE cultivable dataset (Ramankutty et al., 2002) was created using a ~1992 global cropland dataset (Ramankutty and Foley, 1998) modified by characterizing limitations to crop growth based on both climatic and soil properties. The future global cropland extent distribution was generated by analyzing predicted changes in agriculture on a continent-by-continent basis (using the IMAGE data), and then applying these changes to the MODIS based cropland map (used for present day MEGAN simulations), using the SAGE maximum cultivable dataset as an upper limit to cropland extent. A future isoprene emission factor distribution map is shown in Figure 13.5.

For the 36-km CONUS current decade CMAQ simulations, US anthropogenic emissions were developed using the 2002 National Emission Inventory. The Emission Scenario Projection (ESP) methodology, version 1.0 (Loughlin et al., 2011), was applied to project future decade US anthropogenic emissions. A primary component of ESP 1.0 is the MARKet Allocation (MARKAL) energy system model (Loulou et al., 2004). MARKAL is an energy system optimization model that characterizes scenarios of the evolution of an energy system over time. In this context, the energy system extends from obtaining primary energy sources, through their transformation to useful forms, to the variety of technologies (e.g. classes of light-duty personal vehicles, heat pumps, or gas furnaces) that meet “end-use” energy demands (e.g. projected vehicle miles traveled, space heating).

 

Figure 13.5 Isoprene emission factor (EF) distribution for present (left) and future (right) biogenic isoprene emission scenarios.

Figure 13.5 Isoprene emission factor (EF) distribution for present (left) and future (right) biogenic isoprene emission scenarios. (See long description below)

Figure 13.5 Isoprene emission factor (EF) distribution for present (left) and future (right) biogenic isoprene emission scenarios. (See long description below)

Note: Red indicates lower EFs and green indicates higher EFs. Changes in spatial distribution reflect expansion of cropland (lower isoprene emissions) in the future.

Description of Figure 13.5

Figure 13.5 is composed of two panels.  Each is a map of the continental US colored with red or green to indicate isoprene emission factors.  Red indicates lower EFs and green indicates higher EFs. The left map shows the emission factor (EF) distribution for a present biogenic isoprene emission scenario.  In this scenario green (higher EF) covers the eastern US from Maine to Louisiana and extending north to Missouri, Kentucky and Ohio.   Also colored green is Wisconsin, Minnesota, and North Dakota. 

The left map shows the emission factor (EF) distribution for a future biogenic isoprene emission scenario.  In this scenario the green (higher EF) occurs over much the same area with the exception of some green areas now occurring around Colorado, Wyoming, and eastern California.  New areas of red include regions of the east coast and throughout southern Florida.
There is a note that changes in spatial distribution reflect expansion of cropland (lower isoprene emissions) in the future. 

 

13.3.3 Model Performance

For the meteorological downscaling, model evaluations of the WRF and HadRM simulations for the ECHAM5 A1B scenario case are shown in Figure 13.6 and Figure 13.7 for the Pacific Northwest. In Figure 13.6, similar but small biases on the order of -0.5 ~ 0.5ºC are identified along the coast of the Pacific Northwest for both WRF Domain 2 and Domain 3, while cold biases on the order of 1.5 ~ 2.0 ºC are noted in the interior. The annual mean biases of Tmax in the HadRM simulations range predominantly between -0.5 ~ 0.5ºC at HCN stations and are smaller in magnitude when compared to the WRF simulations. Figure 13.7 illustrates wet biases at almost every station for both WRF simulations. HadRM exhibits small model normalized biases (-50 ~ 50%) at stations along the borders of Oregon and Washington and over the northern part of Idaho. However, a few larger positive model normalized biases (≥ 100%) are identified over the northern part of Washington and southern parts of Oregon and Idaho in the HadRM simulations.

 

Figure 13.6 Model evaluation of temperature for the historical modelled period of 1970-2000. Annual mean model biases of Tmax (ºC) at Historical Climatology Network (HCN) stations for (a) WRF Domain 2, (b) WRF Domain 3, and (c) HadRM.

Figure 13.6 Model evaluation of temperature for the historical modelled period of 1970-2000. Annual mean model biases of Tmax (ºC) at Historical Climatology Network (HCN) stations for (a) WRF Domain 2, (b) WRF Domain 3, and (c) HadRM. (See long description below)

Note: based on ECHAM5-A1B model/scenario combination, evaluated using years 1970-2000

Description of Figure 13.6

Figure 13.6 is composed of three panels each of which shows a line map of Washington, Oregon, and Idaho marked with squares which are sized to indicate annual mean model biases of Tmax (°C) at Historical Climatology Network stations in these three states.  Panel A shows the biases for WRF Domain 2, panel B shows the biases for WRF Domain 3, and panel C shows the biases for HadRM.  There is a note that the figure is based on ECHAM5-A1B model/scenario combination, evaluated using years 1970-2000.

In Panel A (WRF Domain 2) biases on the order of -0.5 to 0.5°C occur along the east side of Puget Sound and at stations closer to the coast.  Larger negative biases of -1.0 to -2.0°C occur in eastern Washington, along the eastern Columbia River, and in southern Idaho.

In Panel B (WRF Domain 3) biases on the order of -0.5 to 0.5°C also occur along the east side of Puget Sound and at stations closer to the coast.  Again, larger negative biases of -1.0 to -2.0°C occur in eastern Washington, along the eastern Columbia River, and in southern Idaho.

In Panel C (HadRM) biases on the order of -0.5 to 0.5°C occur at most stations. Exceptions are larger negative biases from -1.5 to -2.5°C that occur in southeastern Idaho and just south of Astoria, Oregon.  Positve biases on the order of 1.0 to 1.5°C occur at the central Oregon/Idaho border and near Portland. 

 

Figure 13.7 Model evaluation of precipitation for the historical modelled period of 1970-2000. Annually averaged model biases of precipitation (mm) normalized by annual mean precipitation at each Historical Climatology Network (HCN) station for (a) WRF Domain 2, (b) WRF Domain 3, and (c) HadRM.

Figure 13.7 Model evaluation of precipitation for the historical modelled period of 1970-2000. Annually averaged model biases of precipitation (mm) normalized by annual mean precipitation at each Historical Climatology Network (HCN) station for (a) WRF Domain 2, (b) WRF Domain 3, and (c) HadRM. (See long description below)

Note: based on ECHAM5-A1B model/scenario combination, evaluated using years 1970-2000

Description of Figure 13.7

Figure 13.7 is composed of three panels each of which shows a line map of Washington, Oregon, and Idaho marked with squares which are sized to indicate annually averaged model biases of precipitation (mm) at Historical Climatology Network stations in these three states.  Panel A shows the biases for WRF Domain 2, panel B shows the biases for WRF Domain 3, and panel C shows the biases for HadRM.  There is a note that the figure is based on ECHAM5-A1B model/scenario combination, evaluated using years 1970-2000.

In Panel A (WRF Domain 2) biases on the order of 0.5 to 1.0 mm occur along the east side of Puget Sound and at stations closer to the coast.  Larger wet biases on the order of 1.5 to 3.0 mm occur for almost all of the stations in central and eastern Washington, eastern and southern Oregon, and in southern Idaho.

In Panel B (WRF Domain 3) wet biases are also observed for all stations although these are generally smaller in magnitude.  Biases on the order of 0 to 0.5 mm occur along the east side of Puget Sound and at stations closer to the coast.  Inland stations have biases on the order of 1.0 to 1.5 mm with the exception of some biases on the order of 2.5 to 3.0 mm in southeastern Idaho.

In Panel C (HadRM) biases along the borders of Oregon and Washington and over the northern part of Idaho are fairly evenly distributed over the range of -0.5 to 0.5 mm.  In southern Oregon and Idaho larger wet biases of 1.5 to 3.0 mm occur.  In northern Washington there are wet biases on the order of 1.0 to 1.5 mm.

 

The CMAQU.S. simulation was evaluated in comparison to the Aeromatic Information Retrieval System (AIRS) O3 and PM data base on a regional basis within the U.S. Because the model results represent a climatological realization, the evaluation is in terms of the frequency distribution of observed and simulated results. These are shown in Figure 13.8. The model evaluation results for ozone show reasonable agreement, although modelled values tend to be higher than observed. These results are generally consistent with the model performance reported in our previous work by Chen et al. (2009) and Avise et al. (2009).

 

Figure 13.8 Comparison of statistical distributions of observed and model results for ozone.

Figure 13.8 Comparison of statistical distributions of observed and model results for ozone. (See long description below)

Figure 13.8 Comparison of statistical distributions of observed and model results for ozone. (See long description below)

Figure 13.8 Comparison of statistical distributions of observed and model results for ozone. (See long description below)

Notes: Based upon climatological downscaling of ECHAM5 meteorology with WRF and CMAQ at 36 km grid resolution for the U.S. during summertime conditions (June-Aug) for five representative summers in the current decadal period 1995 - 2004. Observations were taken from the AQS national network of ozone monitors (bottom left panel) and results are shown by geographic region as indicated in the bottom right panel.

Description of Figure 13.8

Figure 13.8 is composed of three panels.  In the top left is a box plot of modelled and observed daily maximum 8 hour ozone for seven regions in the continental US.  The modelled results are based upon climatological downscaling of ECHAM5 meteorology with WRF and CMAQ at 36 km grid resolution for the U.S. during summertime conditions (June-Aug) for five representative summers in the current decadal period 1995 - 2004. Observations were taken from the AQS national network of ozone monitors (locations shown on a map in the bottom left panel) and results are shown by geographic region (indicated on a map in the bottom right panel).

The seven geographic regions follows indicated on the map in the bottom right panel are as follows.

  • Northwest region made up of Washington, Oregon, and Idaho;
  • Southwest region made up of California, Nevada, and Arizona;
  • Central region made up of Montana, Wyoming, Utah, Colorado, Kansas, Nebraska, South Dakota, and North Dakota;
  • South region made up of New Mexico, Texas, Oklahoma, Arkansas, and Louisiana;
  • Midwest region made up of Illinois, Indiana, Iowa, Michigan, Minnesota, Missouri, Ohio, Kentucky, and Wisconsin;
  • Southeast region made up of Florida, Mississippi, Alabama, Georgia, South Carolina, North Carolina, and Tennessee;
  • Northeast region made up of Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont, New Jersey, New York, Virginia, West Virginia, and Pennsylvania.

The data shown in the box plot for the modelled and observed daily maximum 8 hour ozone for the seven regions are as follows. 

Northwest region: Observed median of approximately 38 ppb, modelled median of approximately 41 ppb, observed interquartile range of approximately 30-50 ppb, modelled interquartile range of approximately 35-50 ppb, observed range of approximately 15-72 ppb, modelled range of approximately 25-75 ppb.

Southwest region: Observed median of approximately 55 ppb, modelled median of approximately 60 ppb, observed interquartile range of approximately 40-70 ppb, modelled interquartile range of approximately 50-72 ppb, observed range of approximately 5-102 ppb, modelled range of approximately 35-105 ppb.

Central region: Observed median of approximately 55 ppb, modelled median of approximately 55 ppb, observed interquartile range of approximately 45-62 ppb, modelled interquartile range of approximately 48-61 ppb, observed range of approximately 25-80 ppb, modelled range of approximately 35-80 ppb.

South region: Observed median of approximately 50 ppb, modelled median of approximately 58 ppb, observed interquartile range of approximately 35-60 ppb, modelled interquartile range of approximately 50-70 ppb, observed range of approximately 28-90 ppb, modelled range of approximately 30-110 ppb.

Midwest region: Observed median of approximately 50 ppb, modelled median of approximately 70 ppb, observed interquartile range of approximately 42-63 ppb, modelled interquartile range of approximately 58-83 ppb, observed range of approximately 25-92 ppb, modelled range of approximately 40-122 ppb.

Southeast region: Observed median of approximately 52 ppb, modelled median of approximately 65 ppb, observed interquartile range of approximately 42-68 ppb, modelled interquartile range of approximately 55-75 ppb, observed range of approximately 23-100 ppb, modelled range of approximately 30-105 ppb.

Northeast region: Observed median of approximately 50 ppb, modelled median of approximately 70 ppb, observed interquartile range of approximately 38-64 ppb, modelled interquartile range of approximately 58-70 ppb, observed range of approximately 18-105 ppb, modelled range of approximately 40-135 ppb.

 

13.3.4 Model Simulations of Global Change Effects upon Air Quality

With the downscaling modelling simulations, it is possible to examine future air quality in terms of both the cumulative effects of global change as well as the separate effects of climate, global emissions, local U.S. emissions, and land use/land cover changes. The current decade was defined as the period 1995 - 2004, while future projections were for the period 2045-2054. Separate model simulations were completed as listed in the following:

  • CD_Base: Current decade climate, land use and emissions
  • A1B_Base: all future conditions (except fires)
  • A1B_BC (Boundary Conditions): only future chemical boundary conditions
  • A1B_US (U.S. Emissions): only future U.S. anthropogenic emissions
  • A1B_Met: only future meteorology, all emissions based on current climate conditions
  • A1B_M (MEGAN): future meteorology & biogenic emissions, current land use
  • A1B_M_LU (MEGAN Land Use): future meteorology, biogenic emissions & land use

For the ECHAM5/A1B configuration, results for summertime ozone in terms of difference maps (future minus current) are shown in Figure 13.9. The difference maps correspond to the simulations listed above. The cumulative effects of all of these future changes are shown in the difference map in Figure 13.9. For each figure, an expanded view of the results for the Pacific Northwest area is shown in addition to the continental U.S. view. A summary of the overall impact upon ozone of these future changes is compiled in Table 13.1.

Table 13.1 Summary of current ozone and projected changes {future case current base case} for 98 th percentile daily maximum 8-hr ozone and average daily maximum 8-hr ozone.
Regions CD_ Base A1B_
Base
A1B_ US A1B_
BC
A1B_
Met
A1B_
M
A1B_
M_LU
Northwest
73 (43)
2 (1)
-2 (0)
2 (3)
-7 (-1)
1 (-1)
2 (-1)
Southwest
106 (62)
-4 (0)
-6 (-4)
3 (5)
-3 (0)
0 (0)
-3 (-1)
Central
80 (54)
5 (4)
-5 (-2)
3 (5)
6 (3)
7 (2)
8 (2)
South
107 (60)
3 (6)
-2 (-2)
1 (4)
1 (5)
5 (5)
4 (5)
Midwest
123 (72)
6 (4)
-5 (-3)
1 (2)
8 (6)
13 (6)
10 (6)
Southeast
103 (66)
-2 (1)
-10 (-5)
1 (2)
7 (6)
7 (5)
8 (5)
Northeast
135 (75)
4 (2)
-9 (-5)
1 (1)
7 (6)
16 (7)
15 (7)

Notes: Values listed are in the format XX(YY) where XX is the value for the 98th percent daily maximum ozone
and YY is the value for the average daily maximum 8-hr ozone.
CD_Base is the measured ambient ozone level for all sites in a given region.
Columns to the right of CD-Base are difference results {future case - base case} for future case model simulations as described in the text. Current base case is for period 1995-2004; future case is for period 2045-2054

 

Description of Table 13.1

Table 13.1 gives a summary of current ozone and projected changes for the US.

The first row of the table contains the headers “Regions”, “CD_Base”, “A1B_Base”, “A1B_US”, “A1B_BC”, “A1B_Met”, “A1B_M” and “A1B_M_LU”.  There is a note that CD_Base is the measured ambient ozone level for all sites in a given region. Columns to the right of CD-Base are difference results {future case - base case} for future case model simulations as described in the text. Current base case is for period 1995-2004; future case is for period 2045-2054 

The first column gives the regions.  These are as follows:

  • Northwest
  • Southwest
  • Central
  • South
  • Midwest
  • Southeast
  • Northeast

The remaining columns give the ozone values for each region in each scenario. The values are listed in the format XX(YY) where XX is the value for the 98th percent daily maximum ozone and YY is the value for the average daily maximum 8-hr ozone.  These are as follows:

  • Northwest: CD_Base: 73(43); A1B_Base: 2(1); A1B_US: -2(0); A1B_BC: 2(3); A1B_Met: -7(-1); A1B_M: 1(-1); A1B_M_LU: 2(-1)
  • Southwest CD_Base: 106(62); A1B_Base: -4(0); A1B_US: -6(4); A1B_BC: 3(5); A1B_Met: -3(0); A1B_M: 0(0); A1B_M_LU: -3(-1)
  • Central CD_Base: 80(54); A1B_Base: 5(4); A1B_US: -5(-2); A1B_BC: 3(5); A1B_Met: 6(3); A1B_M: 7(2); A1B_M_LU: 8(2)
  • South CD_Base: 107(60); A1B_Base: 3(6); A1B_US: -2(-2); A1B_BC: 1(4); A1B_Met: 1(5); A1B_M: 5(5); A1B_M_LU: 4(5)
  • Midwest 123(72); A1B_Base: 6(4); A1B_US: -5(-3); A1B_BC: 1(2); A1B_Met: 8(6); A1B_M: 13(6); A1B_M_LU: 10(6)
  • Southeast 103(66); A1B_Base: -2(1); A1B_US: -10(-5); A1B_BC: 1(2); A1B_Met: 7(6); A1B_M: 7(5); A1B_M_LU: 8(5)
  • Northeast 135(75); A1B_Base: 4(2); A1B_US: -9(-5); A1B_BC: 1(1); A1B_Met: 7(6); A1B_M: 16(7); A1B_M_LU: 15(7)

 

The table and maps show that overall for the A1B future case, the peak ozone (as represented by the 98th percentile by region) slightly increases in the west, but increases by more (up to 7 ppbv) in the central and eastern portion of the U.S. These changes are the result of the combined effects of increases in ozone due to increasing chemical boundary conditions offset by decreases in ozone due to decreasing U.S. emissions. Depending on the region the result is perturbed either up or down and varies by changes in climate, biogenic emissions, and land use. In the western U.S., climatic effects (meteorology plus biogenic emissions) produce a slight increase in peak ozone values while larger increases are modelled in other parts of the U.S. due to warmer temperatures and the associated effects on atmospheric reactions and biogenic emissions.  Land use effects associated with expanded croplands tend to slightly offset the increases associated with climate effects alone. 

It should be recognized that the results presented here are for one modelling configuration and one IPCC future scenario. As illustrated in the synthesis provided by Weaver et al. (2009), it is clear that different modelling systems and different scenarios can lead to quite different results.  Thus, there is a need to continue to build an ensemble of modelling results for future conditions to account for both uncertainty and diversity in modelling approaches, as well as the range of possible trajectories for global change.

 

Figure 13.9 Change in summertime daily maximum 8 hr ozone levels for the A1B cumulative effects minus the current decade base case (A1B_Base - CD_Base). The right side of the figure is a zoomed image of the Pacific Northwest.

Figure 13.9 Change in summertime daily maximum 8 hr ozone levels for the A1B cumulative effects minus the current decade base case (A1B_Base - CD_Base). The right side of the figure is a zoomed image of the Pacific Northwest.

Description of Figure 13.9

Figure 13.9 is composed of two panels. On the left is a line map of the continental US including southern Canada and northern Mexico and on the right is a line map of the Pacific Northwest including Washington, Oregon, Idaho, northern California and Nevada, western Montana, and southeastern British Columbia. Both maps are colored by the change in summertime daily maximum 8-hr ozone levels levels for the A1B cumulative effects minus the current decade base case.  The color scale ranges from -18 to 18 ppbv.

In the left panel (continental US) most areas have changes in summertime daily maximum 8-hr ozone levels in the 1-8 ppbv range. Exceptions occur at the southern tip of the Baja Peninsula and across central Mexico where changes are on the order of 12 to 18 ppbv. The area around New Orleans and smaller areas around New York City, Boston, and Los Angeles also have changes in the 12 to 18 ppbv range.  In general, the east coast from North Carolina to Nova Scotia has changes in the -1 to -6 ppbv range.  Also in this range are the coasts of Georgia and northern Florida, the northeastern corner of Alabama, the central border of North and South Carolina, central California, and the west coast from Los Angeles, to central Washington.

In the right panel most of the inland regions of the Pacific Northwest have changes in summertime daily maximum 8-hr ozone levels in the 1-8 ppbv range.  The east side of Puget Sound and the lower Fraser Valley also have changes in the 1-8 ppbv range.  The Olympic Peninsula and Vancouver Island have changes in the -1 to 1 ppbv range (no change).  The very southern tip of Puget Sound and all coastal areas from Wilapa Bay south have changes in the -1 to -6 ppbv range.

 

Figure 13.10 Change in summertime daily maximum 8 hr ozone levels for the A1B chemical boundary conditions case minus the current decade base case (A1B_BC - CD_Base). The right side of the figure is a zoomed image of the Pacific Northwest.

Figure 13.10 Change in summertime daily maximum 8 hr ozone levels for the A1B cumulative effects minus the current decade base case (A1B_Base - CD_Base). The right side of the figure is a zoomed image of the Pacific Northwest.

 

Description of Figure 13.10

Figure 13.10 is composed of two panels. On the left is a line map of the continental US including southern Canada and northern Mexico and on the right is a line map of the Pacific Northwest including Washington, Oregon, Idaho, northern California and Nevada, western Montana, and southeastern British Columbia. Both maps are colored by the change in summertime daily maximum 8-hr ozone levels for the A1B chemical boundary conditions case minus the current decade base case.  The color scale ranges from -18 to 18 ppbv.

In the left panel (continental US) almost all areas have changes in summertime daily maximum 8-hr ozone between 2 and 8 ppbv.  The northeastern US and Canada east of the Great Lakes have changes on the order of 1-2 ppbv.  The only notable exception is the southern tip of the Baja Peninsula and across central Mexico where changes are on the order of 12 to 18 ppbv.

In the right panel the entire Pacific Northwest has changes in summertime daily maximum 8-hr ozone levels in the 2-8 ppbv range. 

 

Figure 13.11 Change in summertime daily maximum 8 hr ozone levels for the A1B US emissions case minus the current decade base case (A1B_US - CD Base). The right side of the figure is a zoomed image of the Pacific Northwest.

Figure 13.11 Change in summertime daily maximum 8 hr ozone levels for the A1B US emissions case minus the current decade base case (A1B_US - CD Base). (See long description below)

Description of Figure 13.11

Figure 13.11 is composed of two panels. On the left is a line map of the continental US including southern Canada and northern Mexico and on the right is a line map of the Pacific Northwest including Washington, Oregon, Idaho, northern California and Nevada, western Montana, and southeastern British Columbia. Both maps are colored by the change in summertime daily maximum 8-hr ozone levels for the A1B US emissions case minus the current decade base case.  The color scale ranges from -18 to 18 ppbv.

In the left panel (continental US) most of the US has changes in summertime daily maximum 8-hr ozone between 2 and 8 ppbv between 0 and -6 ppbv.  Exceptions include the east coast north of Cape Hatteras, central North Carolina, eastern South Carolina, and northern Georgia which have changes on the order of -6 to -10 ppbv.  A small strip through central Florida and along the southwest coast of that state also has changes on the order of -6 to -10 ppv.  A section of California extending to the east and south of San Francisco has changes on the order of -6 to -8 ppbv. Areas with positive changes include the region around Los Angeles (changes of 2 to 6 ppbv) and the area around Puget Sound (described in more detail below).  Most of Mexico has no change in summertime daily maximum 8-hr ozone with the exception of th eastern shore of the Sea of Cortez and some of central Mexico which have changes of 1 to 4 ppbv. Most of Canada also has no change in summertime daily maximum 8-hr ozone with the exception of an area along the Alberta/Saskatchewan border and the Georgia Basin which have changes on the order of 1 to 4 ppbv.

In the right panel (showing the Pacific Northwest) most of southwestern British Columbia has no change in summertime daily maximum 8-hr ozone.  The exceptions are the lower Fraser Valley and the Strait of Georgia which have changes of 1 to 4 ppbv.   Northern Washington, Montana, and Idaho as well as the Pacific coast north of Portland also show no change in summertime daily maximum 8-hr ozone. The eastern side of Puget Sound has changes of 1 to 6 ppbv while the remainder of the US area has changes of -1 to -6 ppbv.

 

Figure 13.12 (a) Change in summertime daily maximum 8 hr ozone levels for the A1B meteorology + biogenic emissions minus current decade base case (A1B_M - CD_Base) and (b) for the A1B meteorology + biogenic emissions + land use cases minus the current decade base case (A1B_M_LU - CD_Base). The right side of the figure is a zoomed image of the Pacific Northwest.

a) A1B meteorology + biogenic emissions

Figure 13.12 (a1) Change in summertime daily maximum 8 hr ozone levels for the A1B meteorology + biogenic emissions minus current decade base case (A1B_M - CD_Base). (See long description below) Figure 13.12 (a2) is a zoomed image of the Pacific Northwest. (See long description below)

b) A1B meteorology + biogenic emissions + landuse minus current decade base case

Figure 13.12 (b1) Change in summertime daily maximum for the A1B meteorology + biogenic emissions + land use cases minus the current decade base case (A1B_M_LU - CD_Base). (See long description below) Figure 13.12 (b2) is a zoomed image of the Pacific Northwest. (See long description below)

Description of Figure 13.12

Figure 13.12 is divided into two parts.  The top section (section a) shows change in summertime daily maximum 8 hr ozone levels for the A1B meteorology + biogenic emissions minus current decade base case (A1B_M - CD_Base), and the bottom section (section b) shows change in summertime daily maximum 8 hr ozone levels for the A1B meteorology + biogenic emissions + land use cases minus the current decade base case (A1B_M_LU - CD_Base).  Each of the two sections is composed of two panels. On the left in each case is a line map of the continental US including southern Canada and northern Mexico and on the right is a line map of the Pacific Northwest including Washington, Oregon, Idaho, northern California and Nevada, western Montana, and southeastern British Columbia.  In both cases the maps are colored by the change in summertime daily maximum 8-hr ozone levels on a color scale ranging from -18 to 18 ppbv.

In the left panel (continental US) of the top section (A1B_M - CD_Base) it can be seen that the Pacific coast and offshore waters north of Los Angeles show changes in in summertime daily maximum 8-hr ozone on the order of -1 to -6 ppbv. Northeastern California, Arizona, Idaho and eastern Washington and Oregon have no change in ozone levels while most of the remainder of the US has changes on the order of 1 to 8 ppbv.  Some exceptions are around New York City, Boston, Detroit, Chicago, and New Orleans where changes are on the order of 8 to 18 ppbv.  Most of Mexico has changes on the order of 1 to 4 ppbv.  In southern Canada most areas see no change with the exception of southwestern British Columbia which has changes on the order of -1 to -4 ppbv and the areas around Lake Winnipeg and the Great Lakes which have changes on the order of 1-6 ppbv.

In the right panel (Pacific Northwest) of the top section the entire coastal region and most of southwestern Bristish Columbia have changes on the order of -1 to -4 ppbv.  The remainder of the area sees no change.

The expected changes in summertime daily maximum 8 hr ozone levels for the A1B_M_LU - CD_Base case (bottom section) is very similar to the expected changes for the A1B_M - CD_Base case (top section).  Minor differences include a slightly smaller area showing increases in southern California and some larger increases (8-18 ppbv) around Tampa and Miami.  In the Pacific Northwest the picture is also almost identical with just slightly larger decreases occurring over central and northern Vancouver Island (-2 to -4 ppbv versus -1 to -2 ppbv).

 

13.3.5 Impacts for Georgia Basin Air Quality

The results for the ECHAM5/A1B case presented above suggest that future ozone levels (2045-2054) in the Georgia Basin-Puget Sound airshed will increase slightly (up to 2ppb) due to the cumulative effects of climate change, global and local emission changes and land use change. In terms of air quality management policies, the results in Table 13.1 suggest that the positive effect of reductions in local U.S. emissions may be offset by higher chemical background concentrations due to long range transport (Figure 13.10). Although climate effects (meteorology alone) show a net decrease in peak ozone values (Table 13.1), a combination of warmer temperatures, increased biogenic emissions and change in land use produces a slight increase in 8 hour ozone in the range of 1-2 ppb in portions of the Georgia Basin/Puget Sound airshed (Table 13.1). These results indicate that climatic effects and long range transport must be taken into account for any future air quality management decisions related to ozone in the region.

13.4 Environment Canada Climate/Air Quality Simulations Using AURAMS

J. Kelly, D. Plummer, P.A. Makar (Environment Canada)

As noted previously, a key aspect of the results presented above is that they represent just one IPCCSRESscenario and modelling configuration. As Weaver et al.(2009) showed there can be considerable differences among global emission scenarios and different modelling configurations.

Kelly et al. (2011) simulated the effects of climate change on concentrations of ozone and PM2.5 over North America using A Unified Regional Air Quality Modelling System (AURAMS v.1.3.2, Gong et al., 2006, Makar et al., 2010a; Houyoux et al., 2000; CEP, 2003;  Côté et al., 1998) in conjunction with the Canadian Regional Climate Model (CRCM 4.2.3 Caya and Laprise, 1999; Laprise et al., 2003; Plummer et al., 2006; Sushama et al., 2010; Mladjic et al., 2011, Kain and Fritsch, 1990; Bechtold et al., 2001)

AURAMS is a regional air-quality modelling system, similar to CMAQ in terms of level of complexity, but with different methodologies for many of the scientific modules.  AURAMS comprises the smog precursor emissions processing system SMOKE (Houyoux et al., 2000, CEP, 2003), a meteorological driving module, and a Chemical Transport Model, the latter including processes for gas-phase chemistry (42 gaseous species), inorganic and organic particle chemistry (8 aerosol species each with a 12 bin size distribution, dry deposition of gases and aerosols, aqueous chemistry, aerosol microphysics (nucleation, condensation/evaporation, coagulation, cloud condensation nuclei activation) particle gravitational settling, and wet and dry particle deposition.  AURAMS species and diagnostics were output on hourly intervals for the simulations performed here.

The CRCM is a 45km resolution limited-area regional climate model used here to downscale the results of the Canadian Coupled General Circulation Model (CGCM v3.1), in order to provide the meteorological inputs required by AURAMS. Two regional climate simulations were carried out; a current climate (1997-2006) and a future climate (2041-2050). The future climate projection used in these simulations is the SRES A2 emissions scenario, which creates a climate similar to A1B through to 2050 and begins to diverge thereafter. Three air-quality simulations at 45km resolution were carried out for the months June, July and August, using this meteorological input. The scenarios included:

  • Current Climate Current Emissions (1997 - 2006 climate, with 2002 Canadian and U.S. and 1999 Mexican anthropogenic air pollution precursor emissions).
  • Future Climate / Current emissions (2041 - 2050 SRES A2 climate, with 2002/1999 anthropogenic air pollution precursor emissions);
  • Future Climate, Future Emissions (2041 - 2050 SRES A2 climate, with Representative Concentration Pathway (RCP) 6.0 emissions). 

The last of these scenarios makes use of the IPCC’s Representative Concentration Pathway 6.0 (RCP 6.0; Fujino et al., 2006, Hijioka et al., 2008). RCP6 is a moderate-range stabilization scenario with a moderate rate of increase in total radiative forcing to 2100 followed by stabilization. The RCP scenarios are a more recent development linked to the earlier A2, A1, etc., scenarios. They include a more detailed development of the smog-precursor links to green-house gas emitting activities and how changing these activities would also change anthropogenic smog precursor emissions. The RCP6 emissions scenario includes decadal changes for 108 emitting activities for NOx, VOCs, SO2, etc. The ratios of the RCP6 values for 2020 and 2050 were used to scale Environment Canada’s best available emissions projections for “business as usual” (only currently legislated controls) for the year 2020, to create 2050 values. These scaling factors were applied in the SMOKE emissions processing system, used to create all smog precursor emissions datasets used in the AURAMS-CRCM simulations. Biogenic emissions are calculated on-line within AURAMS (that is, the emissions are functions of temperature and photosynthetically active radiation, both of these parameters originating in the driving meteorology).  The biogenic emission factors used in AURAMS are taken from BEIS3.09 (Vukovich and Pierce, 2002), with a land-use database originating in satellite-derived vegetation fields.  The modelling makes the assumption that the vegetation in 2041-2050 will not have had sufficient time to change substantially from the current climate vegetation. 

AURAMS requires many more meteorological fields than are available in standard CRCM output, at a time resolution of 15 minutes, which necessitated repeating earlier CRCM simulations with enhanced output capabilities in the CRCM. For these simulations, the CGCM was used to update the CRCM boundary conditions every 6 hours, and the CRCM meteorology was output on a 15 minute time-step for input into AURAMS. Initial conditions for the CRCM simulations for each summer simulated were taken from a previous CRCM simulation from the years 1959 to 2100 (with two weeks of spin-up in May). Figure 13.13 shows the grid used for the CRCM simulations.

 

Figure 13.13 CRCM and (within dashed line) AURAMS-CRCM grids, CRCM topography field shown.

Figure 13.13 CRCM and (within dashed line) AURAMS-CRCM grids, CRCM topography field shown. (See long description below)

Description of Figure 13.13

Figure 13.13 is a conic projection map of North America extending from 15°N to the North Pole and including Greenland, Cuba, and the Chukchi Peninsula in Russia. A dashed rectangle indicating the AURAMS-CRCM grids is bounded by a line that runs from the Kotzebue Sound area of northwestern Alaska, across the Arctic Ocean, to the Atlantic Ocean off of Newfoundland at approximately 45°N and 45°W. It then runs south to the Caribbean between Cuba and Jamaica and west to the Pacific Ocean at approximately 28°N and 130°W. The CRCM topography field is also shown.  This reflects the true continental topography and extends from 0 to 3500 m above sea level.

 

The design of the AURAMS-CRCM simulations differs from the simulations presented earlier in this chapter in that the AURAMS model is run in its native mode, with the same fixed chemical boundary conditions for all simulations.  That is, meteorological downscaling was applied, but not chemical downscaling.  The simulations thus provide information on the potential changes due to climate change within the model domain, but not how the emissions outside of the model domain might influence the North American Air-Quality picture. 

13.4.1 Model Performance

In order to evaluate the model performance, observations carried out over North America for the current climate period (1997-2006) were collected from ozone and PM2.5 observation stations across the continent.  A completeness criteria of 70% on the number of years with observations and 75% for the months of June, July and August was used to sort the data (that is, a station would have to have data for 7 out of the 10 years, and each of those reporting years would have to have more than 75% of the available days with valid data, before being included in the evaluation database).  The data at each station were used to determine the station average daily maximum 8 hour ozone and the 24 hour average PM2.5.  Averages for the maximum, minimum, 4th highest maximum, various percentiles, Canada-Wide Standard (CWS) and U.S. National Ambient Air-Quality Standard (NAAQS) values were also calculated, and all of these metrics were compared to the model predictions over the same time period.  The resulting evaluative statistics are shown in Tables 13.2 and 13.3. The model has a 10 to 11 ppbv positive bias for most ozone statistics (that is, the model predictions are on average 10 ppbv higher than the observed values, slopes close to unity for most statistics, over-predicting for minimum ozone), and correlation coefficients (R) values ranging from 0.39 for NAAQS to 0.62 for the mean ozone. The ozone statistics (Table 13.2) are similar to those achieved for AURAMS simulations using its standard meteorological driver (the Canadian Weather Forecast model: Global Environmental Multiscale (GEM)). Simulations at 42, 15 and 2.5km grid spacing (Makar et al., 2010) suggest that much of the positive bias in these model simulations is the result of insufficient NOx titration, and would be eliminated with further downscaling to higher grid resolutions than those attempted here). The PM2.5 statistics (Table 13.3) are similar to those achieved by this version of AURAMS driven by GEM in terms of correlation coefficient, with the important exceptions of the mean bias (which is more negative than achieved with GEM), and the correlation coefficients for CWS and NAAQS.  The relatively high negative bias is likely due to two factors:  the cloud physics package for this version of the CRCM lacks a parameterization for the evaporation of falling rain, and the surface temperatures of the CRCM over the western mountains and the boreal forest regions of the continent have negative biases. The former process has been shown to be a significant source of particle sulphate (SO2 taken up by clouds is converted to sulphuric acid and is released as sulphate particles when rain evaporates en route to the ground).  The latter reduces the rate of biogenic emissions, hence reducing the rate of secondary organic aerosol formation from the oxidation these hydrocarbons released by vegetation.

Table 13.2 AURAMS-CRCM Performance Statistics for Current Climate: Ozone.
Metric R2 R Slope Intercept Mean Bias Root Mean Square Error Normalized Mean Bias Normalized Mean Error
Minimum
0.23
0.48
0.60
21.8
12.5
15.4
0.54
0.56
Maximum
0.37
0.61
0.98
12.2
10.2
22.9
0.12
0.19
Mean
0.38
0.62
0.88
17.6
11.2
16.5
0.22
0.27
4th Highest Maximum
0.37
0.61
0.96
14.2
11.4
21.2
0.15
0.22
Lowest 10th Percentile
0.34
0.58
0.75
19.5
11.1
14.9
0.33
0.36
Highest 10th Percentile
0.36
0.60
0.91
17.6
11.2
19.6
0.16
0.23
Highest 98th Percentile
0.36
0.60
1.00
11.9
11.9
23.5
0.14
0.21
Canada-Wide Standard
0.25
0.50
0.93
20.4
19.0
31.1
1.00
1.31
NAAQS
0.16
0.39
0.92
14.8
14.1
25.2
1.63
2.09
Std. Dev.
0.31
0.56
0.83
2.3
0.0035
4.23
0.00026
0.23

 

Description of Table 13.2

Table 13.2 gives the performance statistics for AURAMS-CRCM for ozone in the current climate.

The first row of the table contains the headers “Metric”, “R2”, “R”, “Slope”, “Intercept”, “Mean Bias”, “Root Mean Square Error”, “Normalized Mean Bias”, and “Normalized Mean Error”.  The first row lists the ozone metrics that were evaluated.  These are as follows:

  • Minimum
  • Maximum
  • Mean
  • 4th highest maximum
  • Lowest 10th percentile
  • Highest 10th percentile
  • Highest 98th percentile
  • Canada-Wide Standard
  • NAAQS
  • Standard Deviation

The remaining columns give the numerical value of each performance statistic given in the headers for each of the ozone metrics.

 

 Table 13.3 AURAMS-CRCM Performance Statistics for Current Climate: PM2.5.
Metric R2 R Slope Intercept Mean Bias Root Mean Square Error Normalized Mean Bias Normalized Mean Error
Minimum
0.47
0.68
0.39
-0.01
-2.4
2.8
-0.62
0.63
Maximum
0.27
0.52
0.34
7.13
-13.8
18.9
-0.43
0.46
Mean
0.55
0.74
0.57
-0.63
-6.3
7.2
-0.48
0.50
4th Highest Maximum
0.38
0.62
0.51
3.13
-7.5
10.9
-0.35
0.40
Lowest 10th Percentile
0.52
0.72
0.53
-0.22
-2.9
3.4
-0.50
0.52
Highest 10th Percentile
0.53
0.73
0.55
-0.67
-11.0
12.7
-0.48
0.51
Highest 98th Percentile
0.39
0.63
0.44
2.78
-14.5
17.6
-0.47
0.49
Canada-Wide Standard
0.04
0.20
0.09
0.21
-1.6
3.2
-0.81
0.90
NAAQS
0.02
0.13
0.04
0.09
-0.9
1.9
-0.87
0.94
Std. Dev.
0.42
0.65
0.46
0.48
-3.1
3.8
-0.47
0.50

 

Description of Table 13.3

Table 13.3 gives the performance statistics for AURAMS-CRCM for PM2.5 in the current climate.

The first row of the table contains the headers “Metric”, “R2”, “R”, “Slope”, “Intercept”, “Mean Bias”, “Root Mean Square Error”, “Normalized Mean Bias”, and “Normalized Mean Error”.  The first row lists the PM2.5 metrics that were evaluated.  These are as follows:

  • Minimum
  • Maximum
  • Mean
  • 4th highest maximum
  • Lowest 10th percentile
  • Highest 10th percentile
  • Highest 98th percentile
  • Canada-Wide Standard
  • NAAQS
  • Standard Deviation

The remaining columns give the numerical value of each performance statistic given in the headers for each of the PM2.5metrics.

 

13.4.2 Model Predictions: Meteorological Changes

Three examples of the expected changes in meteorology that drive the changes in air-quality are given below; lowest model layer temperatures, relative humidity and precipitation rates.  Ten year averages of the summer average and 98th percentile values for these fields are given in Figure 13.14, 13.15 and 13.16.

Figure 13.14 shows that the average summer temperature is expected to increase, with the extent of the increase varying greatly in space, with maximum values of around 2.2 C.  The largest increases occur in the centre of the continent.  North-western USA and south-western Canada have summer average temperature increases between 1.0 and 1.7 C near the Pacific, with temperature increases rising as high as 1.9 C with increasing distance inland. The second row of contour maps in Figure 13.14 shows the summer average 98th percentile temperature, and its (future - current) difference. The 98th percentile temperatures are the temperature extremes; the lower half of the figure thus shows the hottest days of the summer on the left, and the change in the temperatures of the hottest days on the right. The lower right figure is significant in that the change in temperatures for the hottest summer days have increased more than the average (compare upper and lower right panels of Figure 13.14, which have different temperature scales). The pattern of the increase in extreme temperatures is very spatially inhomogeneous, with the greatest increase in local extreme temperatures occurring in the Canadian provinces of Ontario and Quebec, followed by parts of the north east USA and northern Canada. For example the increase in the average mean temperature for Toronto is 1.7 to 1.9 C, while the corresponding increase in the average 98th percentile temperature is 2.6 to 3.0 C. This effect is not as pronounced in the Seattle to Vancouver corridor, for example, with average mean temperatures increasing between 1.2 and 1.7 C and average 98th percentile temperatures increasing 1.1 to 1.8 C. Northern British Columbia and the Yukon Territory of Canada are two of the few places with decreases in the 98th percentile temperatures - increases are the norm across the continent. The temperature maps thus show an increase in average temperature and an increase in the number of extreme heat conditions for most of the continent.

 

Figure 13.14 Ten year average Current Climate (1997-2006) lowest model layer mean summer temperature (a) and change in temperature [Future average - current average] (b). Ten year average summer 98th percentile lowest model layer temperature (c) and change in lowest model layer temperature (d).

Figure 13.14 Ten year average Current Climate (1997-2006) lowest model layer mean summer temperature (a) and change in temperature [Future average - current average] (b). Ten year average summer 98th percentile lowest model layer temperature (c) and change in lowest model layer temperature (d). (See long description below)

Description of Figure 13.14

Figure 13.14 is composed of four panels each containing a map of North America covering an area from the tip of the Baja Peninsula to the Arctic Ocean.  In each, the area contained by the AURAMS-CRCM grids (described in Figure 13.13) is colored by temperature in degrees Celsius.

In Panel A the ten year average Current Climate (1997-2006) lowest model layer mean summer temperature is shown. The temperature scale ranges from -5 to 34°C.  Temperatures are between -5°C and 6°C in the Arctic Ocean and Hudson Bay, as well as in much of Alaska, the Yukon Territory, and in northwestern British Columbia.  The remainder of Canada (including the Georgia Basin) has temperatures in the range of 6 to 14°C.  In the northwestern US temperatures range from 6 to 17°C, while in the southwest they range from 14 to 32°C.  The central and southeastern US also has temperatures in the range of 14 to 32°C with the temperature generally increasing from northwest to southeast.  The northeastern US has temperatures in the range of 14 to 21°C.

In Panel B the change in average summer temperature [Future average - current average] is shown.  The scale ranges from 0.1 to 2.4°C.  Northern Canada, the Maritimes, and the British Columbia coast have changes on the order of 0.1 to 1.5°C.  Central Canada, including southeastern BC and northern Ontario, has changes on the order of 1.5 to 2.1°C.  In the US temperature changes range from 1.5 to 2.4°C with the smallest changes at the coasts and the largest changes in the central areas, particularly in the northern Midwest states.

In Panel C the ten year average summer 98thpercentile lowest model layer temperature is shown.  The temperature scale ranges from 1 to 40°C.  Temperatures are between 1°C and 12°C in the Arctic Ocean and Hudson Bays well as much of Alaska, the Yukon Territory and northwestern British Columbia.  The remainder of Canada (including the Georgia Basin) has temperatures in the range of 12 to 23°C.  In the northwestern US temperatures range from 12 to 23°C while in the southwest they range from 23 to 34°C.  The central and southeastern US also has temperatures in the range of 23 to 38°C with the temperature generally increasing from northwest to southeast.  The northeastern US has temperatures in the range of 19 to 27°C.

In Panel D the change in 98th percentile summer temperature is shown.  The scale ranges from -0.5 to 3.3°C.  In this case northwestern British Columbia and the Yukon have the smallest changes, on the order of -0.5 to 1.5°C.  The remainder of Canada, including the eastern Arctic, has changes on the order of 1.5 to 2.2°C with isolated patches showing changes up to 3.3°C.  In the US the Midwest and northeastern states have changes on the order of 1.8 to 3.3°C while the remainder of the US has changes on the order of 1.1 to 2.6°C. As noted in the text, the pattern of increases in 98th percentile summer temperatures is very spatially inhomogeneous

 

Figure 13.15 shows the mean summer average and 98th percentile specific humidity in the current climate simulations and their change between future and current climates.  The specific humidity is a measure of the water content of the atmosphere and influences atmospheric chemistry through different mechanisms (e.g. setting the background level of the OH radical, influencing the equilibria of inorganic particle chemistry, etc.). Specific humidity increases in both the mean and the 98th percentile, with the latter increasing the most in the Mississippi basin, southern Florida, and the Red River basin.  Similar to temperature, specific humidity increases at the 98th percentile are in general higher than increases in the average, indicating an increase in the magnitude of extreme humidity events across the continent, in a spatially inhomogeneous pattern.

 

Figure 13.15 Ten year average Current Climate (1997-2006) lowest model layer mean summer specific humidity (a) and change in specific humidity [Future average - current average] (b). Ten year average summer 98thpercentile lowest model layer specific humidity (c) and change in lowest model layer specific humidity (d).

Figure 13.15 Ten year average Current Climate (1997-2006) lowest model layer mean summer specific humidity (a) and change in specific humidity [Future average - current average] (b). Ten year average summer 98th percentile lowest model layer specific humidity (c) and change in lowest model layer specific humidity (d). (See long description below)

Description of Figure 13.15

Figure 13.15 is composed of four panels each containing a map of North America covering an area from the tip of the Baja Peninsula to the Arctic Ocean.  In each, the area contained by the AURAMS-CRCM grids (described in Figure 13.13) is colored by specific humidity in units of 103 kg/kg.

In Panel A the ten year average Current Climate (1997-2006) lowest model layer mean summer specific humidity is shown. The humidity scale ranges from 2.9 to 23.3 x 103 kg/kg.  In British Columbia and most of the Canadian Territories the humidity is 2.9 to 7 x 103 kg/kg. The exception is the western end of the Northwest Territory where humidity is 7.0 to 9.1 x 103 kg/kg.  In the rest of Canada humidity is also 7.0 to 9.1 x 103 kg/kg, except for the very southern prairies and southern Ontario, where humidity is 9.1 to 11.1 x 103 kg/kg.  In the western US humidity is spatially inhomogeneous but ranges from 5.0 to 13.2 x 103 kg/kg.  In the Midwest and northeastern US humidity also ranges from 5.0 to 13.2 x 103 kg/kg with an increasing trend from north to south.  In the south central and southeastern US humidity ranges fdrom 15.2 to 23.4 x 103 kg/kg with the highest humidity in the areas around the Gulf of Mexico and Florida.

In Panel B the change in average specific humidity [Future average - current average] is shown. The scale ranges from -0.38 to 1.9 x 103 kg/kg.    Changes in Canada are generally in -0.14 to 0.79 x 103 kg/kg range with southern Manitoba and southern Ontario having changes in the 0.79 to 1.2 x 103 kg/kg range. In the US the changes are very inhomogeneous but are generally in the range of 0.79 to 1.8 x 103 kg/kg.  The largest increases are seen in Florida, Texas, and scattered throughout the southeastern states.

In Panel C the ten year average summer 98thpercentile lowest model layer specific humidity is shown. The humidity scale ranges from 4.2 to 25.8 x 103 kg/kg.  In British Columbia and most of the Canadian Territories the humidity is 4.2 to 10.7 x 103 kg/kg with the western end of the North West Territory having humidity in 10.7 to 12.8 x 103 kg/kg range.  In the rest of Canada humidity is in the range of 10.7 to 17.2 x 103 kg/kg.  In the western US humidity is spatially inhomogeneous but ranges from 4.2 to 17.2 x 103 kg/kg.  In the Midwest and northeastern US humidity also ranges from 15.0 to 21.5 x 103 kg/kg with an increasing trend from north to south.  In the south central and southeastern US humidity ranges fdrom 17.2 to 23.7 x 103 kg/kg with a small section in the 23.7 to 25.8 x 103 kg/kg range along the Texas Gulf Coast.

In Panel D the change in 98th percentile specific humidity [Future average - current average] is shown. The scale ranges from -0.86 to 3.1 x 103 kg/kg.    Changes throughout the continent are inhomogeneous, but in Canada they are generally in -0.07 to 1.9 x 103 kg/kg range with southern Manitoba and the Quebec/Ontario border having changes in the 1.9 to 2.3 x 103 kg/kg range. In the US the changes are generally in the range of 1.1 to 2.3 x 103 kg/kg.  The largest increases are seen in the Midwest and southern Florida from 2.3 to 3.1 x 103 kg/kg.

 

Figure 13.16 shows the mean summer average and 98th percentile height of the planetary boundary layer (PBL).  The PBL height defines the thickness of the relatively well-mixed, higher turbulence lowest layer of the atmosphere.  Smaller PBL heights are associated with poor air-quality, due to the trapping of emitted precursors over a thinner region than with larger PBL heights.  The figure shows that the average and 98th percentile PBL heights tend to increase, although significant decreases occur in some regions as well.  In the Vancouver to Seattle corridor, for example, there is a slight decrease in the average PBL height, and an increase in the 98th percentile PBL height.  Other regions, such as the U.S. eastern seaboard, see increases in the mean PBL height of up to 40 m and local increases in the 98th percentile PBL height in the 100’s of meters.  Colorado is shown as having a large decrease in the mean and 98th percentile PBL heights; decreases in the 98th percentile PBL heights occur over much of the mountain ranges of the Yukon Territory, British Columbia, and the interior mountain ranges of Washington and Oregon States. 

 

Figure 13.16 Ten year average Current Climate (1997-2006) lowest model layer mean summer boundary layer height (a) and change in boundary layer height [Future average - current average] (b). Ten year average summer 98thpercentile boundary layer height (c) and change in boundary layer height (d).

Figure 13.16 Ten year average Current Climate (1997-2006) lowest model layer mean summer boundary layer height (a) and change in boundary layer height [Future average - current average] (b). Ten year average summer 98th percentile boundary layer height (c) and change in boundary layer height (d). (See long description below)

Description of Figure 13.16

Figure 13.16 is composed of four panels each containing a map of North America covering an area from the tip of the Baja Peninsula to the Arctic Ocean.  In each the area contained by the AURAMS-CRCM grids (described in Figure 13.13) is colored by boundary layer height in meters.

In Panel A the ten year average Current Climate (1997-2006) lowest model layer mean summer boundary layer height is shown. The scale ranges from 149 to 1050 m.  Along the Pacific, Arctic, and Atlantic coasts, as well as over the Great Lakes boundary layer height ranges from 149 to 348 m.  For most of British Columbia, the Canadian Arctic, and the northern prairies, Ontario, and Quebec boundary layer height ranges from 248 to 448 m. Over the remainder of Canada it ranges from 448 to 647 m. For the northeastern, midwestern, and most of the southeastern US, boundary layer height also ranges from 448 to 647 m.  This is also the case for the northwestern US and California.  The area east of California extending to Nebraska, Kansas and Texas in the east and south to the Mexican border has boundary layer heights in the range of 647 to 1050 m. 

In Panel B the change in average boundary layer height [Future average - current average] is shown.  The scale ranges from -133 to 87 m.  For much of the continent changes are in the range of -26 to -1 m. Increases of 21 to 65m occur in eastern Alberta and western Saskatchewan, southern Manitoba, northwestern Ontario, and just west of Great Slave Lake in the Northwest Territory.  Increases of 21 to 65m also occur to the south of Lake Michigan and throughout much of the southeastern US.  Increase of 45 to 87 m occur around along the coast of Georgia, South Carolina, and North Carolina, as well as in southern Florida, the Gulf coast of Louisiana and Mississippi and in southern Texas. A decrease of -45 to -111 m occurs over Colorado.

In Panel C the ten year average summer 98thpercentile boundary layer height is shown. The scale ranges from 93 to 1650 m.  Along the most of the Pacific and Arctic coasts boundary layer height ranges from 93 to 559 m.  In the central British Columbia coast it ranges from 559 to 715m.  For most of British Columbia, the Canadian Arctic, and the northern prairies, Ontario, and Quebec boundary layer height ranges from 559 to 870 m. Over the Maritimes it ranges from 870 to 1340 m. Over the remainder of Canada it ranges from 870 to 1030 m. In the northwestern US including California it ranges from 559 to 1030 m . Throughout most of the Midwest and northeast it ranges from 715 to 1030 m, with the exception of New England where it ranges from 870 to 1340 m.   The area east of California extending to Florida in the east and south to the Mexican border has boundary layer heights in the range of 1030 to 1650 m. 

In Panel D the change in 98th percentile boundary layer height is shown.  The scale ranges from -210 to 208 m.  Changes in 98th percentile boundary layer height are very inhomogeneous, but in general the western half of the continent sees decreases on the order of 0 to -84 m, with isolated patches seeing decreases up to -168 m. In the eastern Canadian Prairies and in the eastern and southeastern US increases on the order of 0 to 84 m occur, with isolated patches seeing increases of up to 168 m.

 

These results indicate that the effect of climate change on air-quality are likely to be highly variable;  in general, mean temperatures and humidity levels increase, and the magnitude of extreme events increases (the most hot and humid days become more hot and humid), but these changes are highly dependent on location.  The climate model alone is thus insufficient to predict possible air-quality outcomes; the analysis now turns to the differences predicted by the AURAMS model for the different scenarios.

13.4.3 Model Predictions: Air-Quality Changes

The AURAMS results are presented as average current concentration fields and the differences between the two future climate scenarios and the current climate scenario average concentrations.  The latter are plotted using the same colour scale, to allow a direct comparison between the future climate, with 2002/1999 anthropogenic precursor emissions, and the future climate, with the RCP 6.0 emissions. 

The ten year average mean summer daily maximum 8 hour ozone concentrations across North American are shown in Figure 13.17.  The AURAMS results are presented as sets of four images; the average concentration fields for the base case of {current climate, current emissions} (Figure 13.17a) are followed by differences; [{future climate, current emissions} - {current, current emissions}] (Figure 13.17b), and [{future climate, RCP 6 emissions} - {current climate, current emissions}] (Figure 13.17c), while the final image shows the [{future climate, current emissions}-{current climate, current emissions}] field with the same colour scale as the [{future climate, RCP 6 emissions}- {current climate, current emissions}], allowing a comparison of the magnitude of the changes resulting from the two future emissions scenarios.  The most significant features of the future scenarios are the difference in the expected sign and magnitude of the change in ozone concentrations.  Figure 13.17(b) shows that O­3 concentrations are largely expected to increase with climate change, with maximum increases on the order of 9 to 10 ppbv.  The largest increases occur in the region around Los Angeles, Chicago, Detroit and other urban regions in the U.S. This is consistent with findings of the IPCC5th assessment report (IPCC, 2013b) which concluded that in the absence of future emission reductions, the effect of locally higher surface temperatures in polluted regions would trigger regional feedbacks in chemistry and local emissions that will increase peak levels of ozone.  In contrast, Figure 13.17 (c) shows that the RCP 6 emissions under the SRES A2 climate result in very large decreases in O3 (sometimes greater than 35 ppbv), extending across the eastern U.S. Decreases of 5 to 15 ppbv occur much of the rest of Canada and the U.S. under the RCP 6 scenario, again consistent with IPCC (2013b) report findings.  Almost the entire domain in Figure 13.17 (c) experiences ozone decreases, the one exception being Greater Los Angeles, where decreases in NOx emissions in the downtown core have led to reduced ozone titration, hence significant increases in ozone in that location.  Comparison of Figure 13.17 (c) and Figure 13.17 (d) shows that the increases in ozone expected via climate change (Figure 13.17c) are much smaller in magnitude than the decreases in ozone that could be achieved via the significant precursor emissions reductions associated with the RCP 6 emissions scenario (Figure 13.17d). These results are also in agreement with those of the IPCC5th assessment report (IPCC, 2013a) which concluded that reductions in air pollutant emissions would have a significantly larger impact on future air quality than climate change alone. The Vancouver to Seattle area would see decreases of 2 to 12 ppbv, with further decreases up to 23 ppbv further inland.

 

Figure 13.17 (a) Ten year average {current climate, current emissions} lowest model layer mean summer daily maximum 8 hour average O3 (ppbv). (b) Change in O3 [{future climate, current emissions} - {current climate, current emissions}]. (c) Change in O3 [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (d) Change in O3 [{future climate, current emissions} - {current climate, current emissions}] (same as (b) but with the colour scale of (c) for comparison purposes).

Figure 13.17 (a) Ten year average {current climate, current emissions} lowest model layer mean summer daily maximum 8 hour average O3 (ppbv). (b) Change in O3 [{future climate, current emissions} - {current climate, current emissions}]. (c) Change in O3 [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (d) Change in O3 [{future climate, current emissions} - {current climate, current emissions}] (same as (b) but with the colour scale of (c) for comparison purposes). (See long description below)

Description of Figure 13.17

Figure 13.17 is composed of four panels each containing a map of North America covering an area from the US/Mexico border to the Arctic Ocean.  In each the area contained by the AURAMS-CRCM grids (described in Figure 13.13) is colored by ozone concentration in ppbv.

In Panel A the ten year average (current climate, current emissions) lowest model layer mean summer daily maximum 8 hour average ozone is shown. The scale ranges from 10 to 100 ppbv.  All of Canada except for a thin strip along the US border and reaching up into central Alberta has ozone concentrations of 20 to 30 ppbv.  Along the border and up into central Alberta concentrations ozone concentrations are 30 to 40 ppbv, except for a patch in south-central Alberta where concentrations are 40 to 50 ppbv. In the northwestern US ozone concentrations are 30 to 50 ppbv. In the southwest they range from 40 to 60 ppbv, except in southern California where they reach as high as 80 ppbv. In the central US ozone concentrations are 40 to 60 ppbv. In the east from Illinois to the Atlantic ozone concentrations are from 50 to 80 ppbv with small patches near Atlanta and Chicago in the 80 to 100 ppbv range.

In Panel B the change in ozone concentration [{future climate, current emissions} - {current climate, current emissions}] is shown. The scale ranges from -4 to 10 ppbv.  In this scenario most of Canada sees changes in the -2 to 0 ppbv range.  Southern British Columbia, the south and central prairies, and southern Ontario and Quebec see changes in the 0 to 2 ppbv range. Most of the western half of the US sees changes of -1 to 2 ppbv with the exception of the Los Angeles to San Diego corridor which has changes of 4 to 10 ppbv and the area around San Francisco which has changes of 4 to 6 ppbv. In the eastern half of the US changes are on the order of 2 to 4 ppbv except around Chicago and Detroit where changes as high as 10 ppbv occur.

In Panel C the change in O3 [{future climate, RCP 6 emissions} - {current climate, current emissions}] is shown. The scale ranges from -45 to 65 ppbv. In this scenario much of the eastern US, from Illinois to Florida to Massachusetts, sees ozone concentration decreases of -35 to -15 ppbv.  Most of the remainder of the US sees decreases of -15 to -5 ppbv with decreases of -5 to 0 ppbv along the Mexican border.  In Canada decreases of -15 to -5 ppbv are expected along the US border with decreases of -5 to 0 ppbv further north.

Panel D shows the same scenario as in Panel B, but with the same color scale as in Panel C (-45 to 65 ppbv). In this case almost all of the US, Southern British Columbia, the south and central prairies, and southern Ontario and Quebec see increases of 0 to 5 ppbv.  The exceptions are the areas around Los Angeles, Chicago, and Detroit which have increases of 15 to 25 ppbv.   The remainder of Canada sees changes of 0 to -5 ppbv.

 

The ten year average mean summer daily average PM2.5 concentrations across North America are shown in Figure 13.18.  The projected effect of climate change alone {future climate, current emissions} is shown in Figure 13.18b.  The PM2.5 mass increases by between 0.5 and 1.0 µg m-3 over much of the inland eastern United States, while lower magnitude increases (>0.2 µg m-3) occur over much of North America.  Large increases (> 1.0 µg m-3) are also seen over Hudson’s Bay and are driven by increases in natural sea-salt aerosol emissions, with the reduction of ice cover and increased winds in that region.  Climate change alone will thus cause particulate matter to increase in these regions, even if anthropogenic precursor emissions remain constant at their current values.  The {future climate, RCP 6 emissions} scenario (Figure 13.18c) has large reductions in PM2.5 over much of the eastern USA and the Ontario to Quebec corridor (reductions of up to 10 µg/m3 in some regions, and larger regional decreases of more than 3 µg/m3). Some very local areas see increases in PM2.5 with RCP 6, Chicago, Los Angeles, the north Okanagan in British Columbia being examples.  The change in PM2.5 is associated with climate change alone are relatively small (compare Figure 13.18c and Figure 13.18d).  The use of current anthropogenic emissions in a warmer future climate thus increases PM2.5 on a regional basis, while the implementation of the RCP 6 emissions would result in a decrease in PM2.5 over large regions, with increases in a small number of urban locations. These results are consistent with PM2.5 projections for the North American continent reported in the IPCC5th Assessment Report (IPCC, 2013b). It should be noted that changes in the frequency and magnitude of forest fires have not been included into the emissions database - these may have a considerable impact on the PM2.5 loading associated with climate change.

 

Figure 13.18 (a) Ten year average {current climate, current emissions} lowest model layer mean summer daily average PM2.5 (μg/m3). (b) Change in PM2.5 [{future climate, current emissions} - {current climate, current emissions}]. (c) Change in PM2.5[{future climate, RCP 6 emissions} - {current climate, current emissions}]. (d) Change in PM2.5 [{future climate, current emissions} - {current climate, current emissions}](same as (b) but with the colour scale of (c) for comparison purposes).

Figure 13.18 (a) Ten year average {current climate, current emissions} lowest model layer mean summer daily average PM2.5 (μg/m3). (b) Change in PM2.5 [{future climate, current emissions} - {current climate, current emissions}]. (c) Change in PM2.5 [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (d) Change in PM2.5 [{future climate, current emissions} - {current climate, current emissions}] (same as (b) but with the colour scale of (c) for comparison purposes). (See long description below)

Description of Figure 13.18

Figure 13.18 is composed of four panels each containing a map of North America covering an area from the US/Mexico border to the Arctic Ocean.  In each the area contained by the AURAMS-CRCM grids (described in Figure 13.13) is colored by PM2.5concentration in µg/m3.

In Panel A the ten year average (current climate, current emissions) lowest model layer mean summer daily average PM2.5concentration is shown. The scale ranges from 0 to 28 µg/m3. Over most of the continent PM2.5 concentration is in the 0 to 6 µg/m3 range.  Exceptions are the Los Angeles - San Diego corridor which has concentrations from 10 to 28 µg/m3 and the states east of Illinois (except Florida) which have concentrations of 6 to 18 µg/m3. In addition the Gulf of St Lawrence has concentrations of 6 to 10 µg/m3.

In Panel B the change in PM2.5 [{future climate, current emissions} - {current climate, current emissions}] is shown. The scale ranges from -1.0 to 1.8 µg/m3.  In this scenario much of the US east of Illinois has increases of 0.6 to 1.2 µg/m3. The area around Los Angeles also has increases of 0.6 to 1.2 µg/m3.  Large increases of >1.0 µg/m3 occur throughout most of the southern half of Hudson Bay.  Decreases of -0.2 to -0.8 µg/m3occur in the mouth of the Gulf of St Lawrence.  Most of the remainder of the continent sees lower magnitude increases of 0.2 to 0.6 µg/m3.

In Panel C the change in PM2.5 [{future climate, RCP 6 emissions} - {current climate, current emissions}] is shown. The scale ranges from -11 to 8 µg/m3.   Much of the continent sees modest changes of -1 to 2 µg/m3, however, the much of the eastern US coast and the area south of Lake Erie sees decreases ranging of  -3 to -7 µg/m3and decreases of up to -10 µg/m3 in some areas. Decreases of up to -10 µg/m3 are also seen around San Diego and Tampa.  Increases of up to 8 µg/m3 occur at Chicago, Los Angeles, the north Okanagan in British Columbia.

Panel D shows the same scenario as in Panel B, but with the same color scale as in Panel C (-11 to 8 µg/m3). In this case the entire continent is colored almost homogenously with changes from -1 to 2 µg/m3.

 

The differences in PM2.5 can be further analysed through examination of the individual chemical components of PM2.5 that are resolved by AURAMS, as is shown in Figure 13.19 .  Each row of images in Figure 13.19 shows a chemical component of PM2.5.  The left column of the figures corresponds to the effect of climate change alone [{future climate, current emissions} - {current climate, current emissions}] for each particle species, the middle column the equivalent difference for the combined effects of climate change and the  RCP 6 emissions [{future climate, future emissions} - {current climate, current emissions}], and the final column shows the same information as the first column, re-plotted with the middle column’s colour scale to allow a magnitude comparison as above.  Figure 13.19 shows that the decreases in PM2.5 associated with the RCP 6 scenario result from decreases in sulphate (Figure 13.19 b), ammonium (Figure 13.19 e) and nitrate (Figure 13.19 h), as well as minor decreases in primary elemental carbon (Figure 13.19 n) and primary organic carbon (Figure 13.19 q).  Secondary organic aerosol increases slightly (Figure 13.19k) but at a level insufficient to offset the decreases in concentration of the other species.  Figure 13.19 shows that the increases in PM2.5 in the {future climate, current emissions} scenario (left and right columns) result from increases in secondary organic aerosol mass (Figure 13.19 j, Figure 13.19 l).  Increases in secondary organic aerosol mass also occur in the {future climate, RCP 6 emissions} scenario (Figure 13.19 k), but are lower in magnitude than the other scenario.  Both future scenarios have the same biogenic emissions - these are a function of the temperature and, for isoprene, the photosynthetically active radiation levels.  Similarly, both models have the same future climate.  Consequently, the differences in secondary organic aerosol result from differences in the anthropogenic emissions between the two future scenarios.  The increase in PM2.5 in the {future climate, current emissions} scenario thus results from increases in secondary organic aerosol, while the decreases in the RCP 6 scenario result from decreases in both secondary inorganic and primary particle mass and from a relatively reduced influence of secondary organic aerosols on the total PM2.5 loading.  

 

Figure 13.19 (a - i) Chemical speciation of differences in 10 year average summer particle mass, Future - Current, for the two future scenarios. (a) PM2.5 SO4: [{future climate, current emissions} - {current climate, current emissions}]. (b) PM2.5 SO4: [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (c) PM2.5 SO4: [{future climate, current emissions} - {current climate, current emissions}] (same as (a) but with the colour scale of (b) for comparison purposes). (d,e,f): PM2.5 NH4, as in (a,b,c). (g,h,i): PM2.5 NO3, as in (a,b,c).

(a, b, c) PM2.5SO4

Figure 13.19 (a,b,c) Chemical speciation of differences in 10 year average summer particle mass, Future - Current, for the two future scenarios. (a)PM2.5 SO4: [{future climate, current emissions} - {current climate, current emissions}]. (b) PM2.5 SO4: [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (c) PM2.5 SO4: [{future climate, current emissions} - {current climate, current emissions}] (same as (a) but with the colour scale of (b) for comparison purposes). (See long description below)

(d, e, f) PM2.5NH4

Figure 13.19 (d,e,f) Chemical speciation of differences in 10 year average summer particle mass, Future - Current, for the two future scenarios. (a) PM2.5 SO4: [{future climate, current emissions} - {current climate, current emissions}]. (b) PM2.5 SO4: [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (c) PM2.5 SO4: [{future climate, current emissions} - {current climate, current emissions}] (same as (a) but with the colour scale of (b) for comparison purposes). (d,e,f): PM2.5 NH4, as in (a,b,c). (g,h,i): PM2.5 NO3, as in (a,b,c). (See long description below)

(g ,h, i) PM2.5 NO3

Figure 13.19 (g,h,i) Chemical speciation of differences in 10 year average summer particle mass, Future - Current, for the two future scenarios. (a) PM2.5 SO4: [{future climate, current emissions} - {current climate, current emissions}]. (b) PM2.5 SO4: [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (c) PM2.5 SO4: [{future climate, current emissions} - {current climate, current emissions}] (same as (a) but with the colour scale of (b) for comparison purposes). (d,e,f): PM2.5 NH4, as in (a,b,c). (g,h,i): PM2.5 NO3, as in (a,b,c). (See long description below)

Description of Figure 13.19 (a - i)

Figure 13.19 is composed of six rows each containing three panels. In each panel is a map of North America covering an area from the US/Mexico border to the Arctic Ocean.  In each map the area contained by the AURAMS-CRCM grid (described in Figure 13.13) is colored by PM2.5 concentration in µg/m3.  In each row of maps a different chemical component of PM2.5 is shown.  The first map shows differences in 10 year average summer particle mass from that component for the [{future climate, current emissions} - {current climate, current emissions}] scenario, the second represents differences for the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario, and the third is the same scenario as the first, but plotted with the color scale of the second.

The first row of maps shows changes in sulfate PM2.5.  In the first map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.4 to 0.6 µg/m3.  Most of the continent sees changes on the order of -0.1 to 0.1 µg/m3.  The area between Mississippi, Alabama, Georgia, and the Great Lakes has changes on the order of 0.1 to 0.3 µg/m3 as does the east coast of the US between Massachusetts and Delaware and the central part of Florida.  In the second map the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario is shown. The scale is from -6.0 to 1.0 µg/m3.  In this scenario most of the continent sees changes of -0.5 to 0.5 µg/m3.   However, the US east of line between Lake Superior and Texas see decreases from -0.5 to -4.0 with some small isolated areas around Pittsburgh seeing decreases up to -6.0 µg/m3.    The largest decreases occur between Ohio and the Chesapeake Bay. In the third map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown again, this time on the color scale used for the second map. In this case the entire continent is nearly homogenously colored and is in the -0.5 to 0.5 µg/m3 range.

The second row of maps shows changes in ammonium PM2.5.  In the first map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.12 to 0.20 µg/m3.  Most of the continent sees changes on the order of -0.02 to 0.02 µg/m3.  Some exceptions include the area between Mississippi, Alabama, Georgia, and the Great Lakes which is inhomogeneous, but has large areas with changes of 0.02 to 0.10 µg/m3.  Coastal New Jersey and the area around New York City also have changes of 0.02 to 0.10 µg/m3. Significant decreases, on the order of -0.04 to -0.12 occur just south of Cape Hatteras, in northeastern Texas, in central Colorado, in southwestern California, and in southern Alberta. In the second map the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario is shown. The scale is from -2.4 to 1.0 µg/m3.  In this scenario most of the continent sees changes of -0.2 to 0.2 µg/m3.   However, the area between Mississippi, Alabama, Georgia, and the Great Lakes has changes on the order of -1.2 to -1.4 µg/m3, with local changes of up to -2.4 µg/m3 near Pittsburgh and Philidelphia. Decreases of up to -2.4 µg/m3 also occur very locally around San Diego. In the third map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown again, this time on the color scale used for the second map. In this case the entire continent is nearly homogenously colored and is in the -0.6 to 0.2 µg/m3 range.

The third row of maps shows changes in nitrate PM2.5.  In the first map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.4 to 0.6 µg/m3.  Most of the continent sees changes on the order of -0.01 to 0.01 µg/m3.  Exceptions are the area around New York City, Southern Ontario, the eastern Midwest States, southwestern California, and small areas around Denver, New Orleans, and scattered sporadically throughout the inland eastern US which have changes on the order of -0.1 to -0.4 µg/m3.  In the second map the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario is shown. The scale is from -6.4 to 4.0 µg/m3.  In this scenario most of the continent sees changes of -0.5 to 0.5 µg/m3.   However, the area around Ohio and Indiana, coastal New Jersey, and eastern Puget Sound have changes on the order of -2.0 to -3.5 µg/m3. The immediate area around San Diego and Cleveland have decreases of greater than -4.0 µg/m3. The very local area around Los Angeles has increases of 1.5 to 4.0 µg/m3. In the third map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown again, this time on the color scale used for the second map. In this case the entire continent is nearly homogenously colored and is in the -0.5 to 0.5 µg/m3 range.

The fourth row of maps shows changes in secondary organic aerosol PM2.5.  In the first map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.1 to 1.4 µg/m3.  Most of Canada and the western US sees changes on the order of 0 to 0.2 µg/m3.  Exceptions are the interior of northern California and southern Oregon, most of Ontario and Manitoba, northeastern Saskatchewan, and some smaller patches in the north-central US which have changes on the order of 0.2 to 0.5 µg/m3.  The US east of a line between Lake Superior and Texas has changes on the order of 0.2 to 0.7 µg/m3with the magnitude of the change increasing from west to east, but declining again right along the coast.  A corridor through North Carolina and Tennesee has changes on the order of 0.9 to 1.4 µg/m3.  In the second map the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.6 to 0.7 µg/m3.  In this scenario northern Canada, the area west of Saskatchewan, and Quebec see changes on the order of -0.2 to 0.1 µg/m3.  The southern US west of Texas also sees changes on the order of -0.2 to 0.1 µg/m3.  Most of Ontario, Manitoba, and northeastern Saskatchewan see changes of 0.1 to 0.3 µg/m3.  The US north of 40°N also sees changes of 0.1 to 0.3 µg/m3.  Changes’ of 0.2 to 0.5 µg/m3 occur in the inland regions of the eastern US.In the third map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown again, this time on the color scale used for the second map. In this case the US east of a line between Lake Superior and Texas, and excluding Florida and New England, sees increases of 0.3 to 0.7 µg/m3 and appears dark red in color. The interior of northern California and southern Oregon also appears dark red and sees changes on the order of 0.2 to 0.6 µg/m3.  Most of Ontario, Manitoba, and northeastern Saskatchewan see changes of 0.2 to 0.5 µg/m3.

The fifth row of maps shows changes in elemental carbon PM2.5.  In the first map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.03 to 0.08 µg/m3.  Almost all of the continent is colored in only two shades and has changes on the order of -0.01 to 0.01 µg/m3.  The exception is the area immediately around Los Angeles, which has changes on the order of 0.04 to 0.07 µg/m3. In the second map the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.45 to 0.15 µg/m3.  In this scenario most of the continent sees changes of -0.05 to 0.05 µg/m3.   However, the areas immediately surrounding Calgary, Edmonton, Toronto, Montreal, Seattle, Los Angeles, San Diego, Houston, Chicago, Minneapolis, Detroit, Philadelphia, New York City, Atlanta, St Louis, and Indianapolis see changes of -0.4 to -0.2 µg/m3. In the third map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown again, this time on the color scale used for the second map. In this case the entire continent is nearly homogenously colored and is in the -0.05 to 0.05 µg/m3range.

The sixth row of maps shows changes in primary organic aerosol PM2.5.  In the first map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.08 to 0.18 µg/m3.  Almost all of the continent is colored in only two shades and has changes on the order of -0.02 to 0.02 µg/m3.  There are some patches south of the Great Lakes as far south as Tennesee which have changes of 0.02 to 0.06 µg/m3.  The area immediately around Los Angeles has changes of 0.08 to 0.18 µg/m3.  In the second map the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario is shown. The scale is from -1.0 to 1.4 µg/m3.  In this scenario most of the continent sees changes of -0.02 to 0.02 µg/m3.   However, the areas immediately surrounding Chicago and Los Angeles see changes of 0.4 to 1.0 µg/m3. In the third map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown again, this time on the color scale used for the second map. In this case the entire continent is nearly homogenously colored and is in the -0.2 to 0.2 µg/m3 range.

 

Figure 13.19 (continued) (j,k,l): PM2.5 Secondary Organic Aerosol, as in (a,b,c). (m,n,o): PM2.5 Elemental Carbon, as in (a,b,c). (p,q,r): PM2.5 Primary Organic Aerosol (PC), as in (a,b,c).

(j, k, l) PM2.5 SOA

Figure 13.19 (continued) (j,k,l): PM2.5> Secondary Organic Aerosol, as in (a,b,c). (m,n,o): PM2.5 Elemental Carbon, as in (a,b,c). (p,q,r): PM2.5 Primary Organic Aerosol (PC), as in (a,b,c). (See long description below)

(m, n, o) PM2.5 EC

Figure 13.19 (continued) (j,k,l): PM2.5 Secondary Organic Aerosol, as in (a,b,c). (m,n,o): PM2.5 Elemental Carbon, as in (a,b,c). (p,q,r): PM2.5 Primary Organic Aerosol (PC), as in (a,b,c). (See long description below)

(p, q, r) PM2.5 PC

Figure 13.19 (continued) (j,k,l): PM2.5 Secondary Organic Aerosol, as in (a,b,c). (m,n,o): PM2.5 Elemental Carbon, as in (a,b,c). (p,q,r): PM2.5 Primary Organic Aerosol (PC), as in (a,b,c). (See long description below)

Figure 13.19 (continued)

Figure 13.19 is composed of six rows each containing three panels. In each panel is a map of North America covering an area from the US/Mexico border to the Arctic Ocean.  In each map the area contained by the AURAMS-CRCM grid (described in Figure 13.13) is colored by PM2.5 concentration in µg/m3.  In each row of maps a different chemical component of PM2.5 is shown.  The first map shows differences in 10 year average summer particle mass from that component for the [{future climate, current emissions} - {current climate, current emissions}] scenario, the second represents differences for the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario, and the third is the same scenario as the first, but plotted with the color scale of the second.

The first row of maps shows changes in sulfate PM2.5.  In the first map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.4 to 0.6 µg/m3.  Most of the continent sees changes on the order of -0.1 to 0.1 µg/m3.  The area between Mississippi, Alabama, Georgia, and the Great Lakes has changes on the order of 0.1 to 0.3 µg/m3 as does the east coast of the US between Massachusetts and Delaware and the central part of Florida.  In the second map the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario is shown. The scale is from -6.0 to 1.0 µg/m3.  In this scenario most of the continent sees changes of -0.5 to 0.5 µg/m3.   However, the US east of line between Lake Superior and Texas see decreases from -0.5 to -4.0 with some small isolated areas around Pittsburgh seeing decreases up to -6.0 µg/m3.    The largest decreases occur between Ohio and the Chesapeake Bay. In the third map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown again, this time on the color scale used for the second map. In this case the entire continent is nearly homogenously colored and is in the -0.5 to 0.5 µg/m3 range.

The second row of maps shows changes in ammonium PM2.5.  In the first map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.12 to 0.20 µg/m3.  Most of the continent sees changes on the order of -0.02 to 0.02 µg/m3.  Some exceptions include the area between Mississippi, Alabama, Georgia, and the Great Lakes which is inhomogeneous, but has large areas with changes of 0.02 to 0.10 µg/m3.  Coastal New Jersey and the area around New York City also have changes of 0.02 to 0.10 µg/m3. Significant decreases, on the order of -0.04 to -0.12 occur just south of Cape Hatteras, in northeastern Texas, in central Colorado, in southwestern California, and in southern Alberta. In the second map the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario is shown. The scale is from -2.4 to 1.0 µg/m3.  In this scenario most of the continent sees changes of -0.2 to 0.2 µg/m3.   However, the area between Mississippi, Alabama, Georgia, and the Great Lakes has changes on the order of -1.2 to -1.4 µg/m3, with local changes of up to -2.4 µg/m3 near Pittsburgh and Philidelphia. Decreases of up to -2.4 µg/m3 also occur very locally around San Diego. In the third map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown again, this time on the color scale used for the second map. In this case the entire continent is nearly homogenously colored and is in the -0.6 to 0.2 µg/m3 range.

The third row of maps shows changes in nitrate PM2.5.  In the first map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.4 to 0.6 µg/m3.  Most of the continent sees changes on the order of -0.01 to 0.01 µg/m3.  Exceptions are the area around New York City, Southern Ontario, the eastern Midwest States, southwestern California, and small areas around Denver, New Orleans, and scattered sporadically throughout the inland eastern US which have changes on the order of -0.1 to -0.4 µg/m3.  In the second map the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario is shown. The scale is from -6.4 to 4.0 µg/m3.  In this scenario most of the continent sees changes of -0.5 to 0.5 µg/m3.   However, the area around Ohio and Indiana, coastal New Jersey, and eastern Puget Sound have changes on the order of -2.0 to -3.5 µg/m3. The immediate area around San Diego and Cleveland have decreases of greater than -4.0 µg/m3. The very local area around Los Angeles has increases of 1.5 to 4.0 µg/m3. In the third map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown again, this time on the color scale used for the second map. In this case the entire continent is nearly homogenously colored and is in the -0.5 to 0.5 µg/m3 range.

The fourth row of maps shows changes in secondary organic aerosol PM2.5.  In the first map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.1 to 1.4 µg/m3.  Most of Canada and the western US sees changes on the order of 0 to 0.2 µg/m3.  Exceptions are the interior of northern California and southern Oregon, most of Ontario and Manitoba, northeastern Saskatchewan, and some smaller patches in the north-central US which have changes on the order of 0.2 to 0.5 µg/m3.  The US east of a line between Lake Superior and Texas has changes on the order of 0.2 to 0.7 µg/m3with the magnitude of the change increasing from west to east, but declining again right along the coast.  A corridor through North Carolina and Tennesee has changes on the order of 0.9 to 1.4 µg/m3.  In the second map the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.6 to 0.7 µg/m3.  In this scenario northern Canada, the area west of Saskatchewan, and Quebec see changes on the order of -0.2 to 0.1 µg/m3.  The southern US west of Texas also sees changes on the order of -0.2 to 0.1 µg/m3.  Most of Ontario, Manitoba, and northeastern Saskatchewan see changes of 0.1 to 0.3 µg/m3.  The US north of 40°N also sees changes of 0.1 to 0.3 µg/m3.  Changes' of 0.2 to 0.5 µg/m3 occur in the inland regions of the eastern US.In the third map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown again, this time on the color scale used for the second map. In this case the US east of a line between Lake Superior and Texas, and excluding Florida and New England, sees increases of 0.3 to 0.7 µg/m3 and appears dark red in color. The interior of northern California and southern Oregon also appears dark red and sees changes on the order of 0.2 to 0.6 µg/m3.  Most of Ontario, Manitoba, and northeastern Saskatchewan see changes of 0.2 to 0.5 µg/m3.

The fifth row of maps shows changes in elemental carbon PM2.5.  In the first map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.03 to 0.08 µg/m3.  Almost all of the continent is colored in only two shades and has changes on the order of -0.01 to 0.01 µg/m3.  The exception is the area immediately around Los Angeles, which has changes on the order of 0.04 to 0.07 µg/m3. In the second map the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.45 to 0.15 µg/m3.  In this scenario most of the continent sees changes of -0.05 to 0.05 µg/m3.   However, the areas immediately surrounding Calgary, Edmonton, Toronto, Montreal, Seattle, Los Angeles, San Diego, Houston, Chicago, Minneapolis, Detroit, Philadelphia, New York City, Atlanta, St Louis, and Indianapolis see changes of -0.4 to -0.2 µg/m3. In the third map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown again, this time on the color scale used for the second map. In this case the entire continent is nearly homogenously colored and is in the -0.05 to 0.05 µg/m3range.

The sixth row of maps shows changes in primary organic aerosol PM2.5.  In the first map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown. The scale is from -0.08 to 0.18 µg/m3.  Almost all of the continent is colored in only two shades and has changes on the order of -0.02 to 0.02 µg/m3.  There are some patches south of the Great Lakes as far south as Tennesee which have changes of 0.02 to 0.06 µg/m3.  The area immediately around Los Angeles has changes of 0.08 to 0.18 µg/m3.  In the second map the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario is shown. The scale is from -1.0 to 1.4 µg/m3.  In this scenario most of the continent sees changes of -0.02 to 0.02 µg/m3.   However, the areas immediately surrounding Chicago and Los Angeles see changes of 0.4 to 1.0 µg/m3. In the third map the [{future climate, current emissions} - {current climate, current emissions}] scenario is shown again, this time on the color scale used for the second map. In this case the entire continent is nearly homogenously colored and is in the -0.2 to 0.2 µg/m3 range.

 

The climate-and-AQ changes to the overall reactivity of the atmosphere may be estimated by comparing the model 24 hour average OH radical concentrations in the lowest model layer, as is shown in Figure 13.20.  The OH radical will be affected by local meteorological (incoming solar radiation, cloudiness, water content of the atmosphere) and chemical factors, hence Figure 13.20 (a) is very spatially inhomogeneous.  Figure 13.20 (b) shows that the {future climate, current emissions} OH decreases over much of the domain, while increasing in the cities and over the prairie regions of Canada and the U.S.  The {future climate, RCP 6 emissions} scenario (Figure 13.20c) shows a relatively more substantial decrease in OH concentrations over much of the U.S. and Canada (compare Figure 13.20 (c) and Figure 13.20 (d)).  The latter decreases are sometimes a significant fraction of the OH present at specific locations.  For regions where biogenic hydrocarbons are important for near-surface atmospheric chemistry, the increases in biogenic emissions under future climate conditions will suppress OH and this effect will become larger for future climate with the reduced NOx emissions specified for the RCP 6 future emissions.  We note however that the OH changes analyzed here are for the lowest model layer and will emphasize the effects of changes in the emissions of short-lived species.  The RCP 6 (Figure 13.20 (c)) atmosphere has become less reactive, less oxidizing, than the 2002/1999 emissions atmosphere.  This may account for some of the other changes noted above, such as the reduction in secondary organic aerosol differences going from {future climate, current emissions} to {future climate, RCP 6 emissions}.

 

Figure 13.20 (a) Ten year average {current climate, current emissions} lowest model layer mean summer daily average OH (ppbv). (b) Change in OH [{future climate, current emissions} - {current climate, current emissions}]. (c) Change in OH [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (d) Change in OH [{future climate, current emissions} - {current climate, current emissions}] (same as (b) but with the colour scale of (c) for comparison purposes).

Figure 13.20 (a) Ten year average {current climate, current emissions} lowest model layer mean summer daily average OH (ppbv). (b) Change in OH [{future climate, current emissions} - {current climate, current emissions}]. (c) Change in OH [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (d) Change in OH [{future climate, current emissions} - {current climate, current emissions}] (same as (b) but with the colour scale of (c) for comparison purposes). (See long description below)

Description of Figure 13.20

Figure 13.20 is composed of four panels each containing a map of North America covering an area from the US/Mexico border to the Arctic Ocean.  In each the area contained by the AURAMS-CRCM grids (described in Figure 13.13) is colored by OH concentration in ppbv x 104.

In Panel A the ten year average (current climate, current emissions) lowest model layer mean summer daily average OH concentration is shown. The scale ranges from 0 to 3 ppbv x 104. Most of Canada has OH concentrations in the 0 to 0.6 ppbv x 104 range.  In the Lower Fraser Valley, through the southeastern half of Alberta, in southern Saskatchewan and Manitoba, and in Southern Ontario concentrations are in the 0.6 to 1.6 ppbv x 104 range.  In the US the OH concentration distribution is very inhomogeneous.  The lowest concentrations (0.2 to 0.8 ppbv x 104) are concentrated in the northwest and southeast while the highest concentrations (1.6 to 2.8 ppbv x 104) occur in the south central region. However, concentrations are extremely variable in all areas.

In Panel B the change in OH concentration [{future climate, current emissions} - {current climate, current emissions}] is shown. The scale ranges from -1.2 to 2.8 ppbv x 104. Again the distribution of changes is very inhomogeneous, however much of Canada has OH concentration changes in the -0.4 to 0.4 ppbv x 104 range. The southeastern half of Alberta, and the very southern tip of Ontario have changes on the order of 0.4 to 1.4 ppbv x 104. In the western US changes are generally on the order of -0.2 to 0.6 ppbv x 104, with the exception of Los Angeles which sees changes of 1.2 to 2.8 ppbv x 104. In the south central US changes are generally on the order of -0.8 to 0.2 ppbv x 104 with higher positive changes of up to 2.8 ppbv x 104 immediately over cities and slightly higher changes positive changes of 0.2 to 0.8 ppbv x 104 in the plains regions.  In the eastern US changes are generally on the order of -0.8 to 0.2 ppbv x 104 again with larger positive changes over the cities.

In Panel C the change in OH concentration [{future climate, RCP 6 emissions} - {current climate, current emissions}] is shown. The scale ranges from -1.3 to 1.2 ppbv x 104.   In this scenario most of Canada has changes in the -0.2 to 0.2 ppbv x 104 range, except for in the Lower Fraser Valley, through the southeastern half of Alberta, in southern Saskatchewan and Manitoba, and in Southern Ontario where changes in the -0.8 to -0.2 ppbv x 104 range are seen. In the US changes are very spatially inhomogeneous, but generally fall between -0.6 and 0.2 ppbv x 104, with small isolated patches with changes of -1.2 to -0.6 ppbv x 104.   The major exceptions are Los Angeles, San Francisco, Albuquerque, and Detroit which have changes on the order of 0.2 to 1.0 ppbv x 104.    
Panel D shows the same scenario as in Panel B, but with the same color scale as in Panel C. In this case the entire continent is colored almost homogenously with changes from -0.2 to 0.4 ppbv x 104.

 

The chemical analysis outlined above shows that changes to air quality due to climate change alone, with anthropogenic emissions remaining constant at 2002 levels, would be negative - with relatively small increases in PM2.5. The analysis also shows that a much more significant impact on air-quality would occur with the enactment of RCP 6 emissions reductions:  O3 and PM2.5 levels would decrease over much of North America, and the overall reactivity of the atmosphere would decrease.  The RCP6 scenario thus demonstrates that the negative effects of climate change on air-quality may be offset or even reversed, with reductions in emissions compared to current conditions.

13.4.4 Model Predictions: The Effects of Climate Change on Air-Quality-Induced Human Health

The Air-Quality Health Index (AQHI) is a three pollutant health metric designed by Health Canada in conjunction with Environment Canada, to convey the effects of air pollution on acute human health outcomes to the general public (Environment Canada, 2013).  The AQHI is a function of three chemical species (O3, PM2.5 and NO2), which are related via the formula:

Concentrations of NO2 and O3 are in units of ppbv, and the concentration of PM2.5 is in mg/m<;sup>3<;/sup> formula

Description of formula

In the above formula, the concentrations of NO2 and O3 are in units of ppbv, and the concentration of PM2.5 is in mg/m3.

The model-predicted AQHI values for each scenario were calculated on an hourly basis for Canadian cities and towns and major cities within the USA.   These values were used to construct box-and-whisker histograms for each of the selected cities (Figure 13.21).  Each city’s AQHI values for each scenario are represented by a set of three histograms; at left, in blue, {current climate, current emissions}, middle, in red, {future climate, current emissions}, and at right, in green, {future climate, RCP 6 emissions}. 

The general tendency of Figure 13.21is a worsening AQHI compared to current conditions (blue) for the {future climate, current emissions} scenario (red), and an improvement to AQHI when going to the {future climate, RCP 6 emission} scenario (green), for the metrics displayed.  Local differences may however be noted.  For Whitehorse, Yellowknife, (Figure 13.21 (a)), St. John’s (Figure 13.21 (b)), San Antonio, Dallas, Phoenix and Houston (Figure 13.21 (c)) both future climates improve (i.e. decrease) the 98thpercentile AQHI compared to the current climate.  However, for these cities, the RCP 6 scenario results in lower AQHI for all metrics displayed than the {future climate, current emissions} scenario.  Kamloops (Figure 13.21 (a)) has worse 98thpercentile and 2nd percentile AQHI when going from the {future climate, current emissions} to the {future climate, RCP 6 emissions} scenario, but the median, mean, and 75thpercentile values improve.  In general, however, the net effect of the RCP6 emissions changes is a positive one, with decreases in mean, median, and percentile AQHI values, while the {future climate, current emissions} result in increases in the mean, median, and/or extreme AQHI.  The climate-change-induced effect of air-quality changes on human health is thus of deterioration: increases in mortality can be expected due to worsening air pollution conditions, as a result of climate change, if anthropogenic emissions remain at their current levels.  Conversely, that effect would be substantially reduced and usually reversed if the RCP 6 emissions controls were enacted.

 

Figure 13.21 Air Quality Health Index box-and-whisker histograms for (a) western, (b) eastern Canadian towns and cities and (c) large American cities. Blue: {current climate, current emissions}. Red: {future climate, current emissions}. Green: {future climate, RCP 6 emissions}. Upper and lower whisker limits are 98th and 2nd percentiles, respectively, box limits are 75th and 25th percentile, median is solid horizontal bar, mean is * symbol.

(a)

Figure 13.21 Air Quality Health Index box-and-whisker histograms for western. Blue: {current climate, current emissions}. Red: {future climate, current emissions}. Green: {future climate, RCP 6 emissions}. Upper and lower whisker limits are 98th and 2nd percentiles, respectively, box limits are 75th and 25th percentile, median is solid horizontal bar, mean is * symbol. (See long description below)

(b)

Figure 13.21 Air Quality Health Index box-and-whisker histograms for eastern Canadian towns and cities Blue: {current climate, current emissions}. Red: {future climate, current emissions}. Green: {future climate, RCP 6 emissions}. Upper and lower whisker limits are 98th and 2nd percentiles, respectively, box limits are 75th and 25th percentile, median is solid horizontal bar, mean is * symbol. (See long description below)

(c)

Figure 13.21 Air Quality Health Index box-and-whisker histograms for large American cities. Blue: {current climate, current emissions}. Red: {future climate, current emissions}. Green: {future climate, RCP 6 emissions}. Upper and lower whisker limits are 98th and 2nd percentiles, respectively, box limits are 75th and 25th percentile, median is solid horizontal bar, mean is * symbol. (See long description below)

Description of Figure 13.21

Figure 13.21 has three panels all with box and whisker plots of Air Quality Health Index (AQHI). 

Panel A shows data for the western Canadian towns of Whitehorse, Victoria , Vancouver , Yellowknife, Kamloops, Calgary, Edmonton, Lethbridge, Saskatoon, Regina, and Winnipeg. The y-axis ranges from an AQHI of 0 to 5.  The data presented are as follows. 

Whitehorse (current climate and current emissions), median approximately 1.4, mean approximately 1.4, 25-75 percentile range approximately 1.3-1.5, 2-98 percentile range approximately 0.9-2. Whitehorse (future climate and current emissions), median approximately 1.35, mean approximately 1.35, 25-75 percentile range approximately 1.2-1.45, 2-98 percentile range approximately 0.8-1.9. Whitehorse (future climate and RCP 6 emissions), median approximately 1.35, mean approximately 1.35, 25-75 percentile range approximately 1.2-1.45, 2-98 percentile range approximately 0.7-1.9.

Victoria (current climate and current emissions), median approximately 1.5, mean approximately 1.5, 25-75 percentile range approximately 1.3-1.7, 2-98 percentile range approximately 0.8-3.1. Victoria (future climate and current emissions), median approximately 1.5, mean approximately 1.5, 25-75 percentile range approximately 1.3-1.7, 2-98 percentile range approximately 0.8-3.1. Victoria (future climate and RCP 6 emissions), median approximately 1.3, mean approximately 1.35, 25-75 percentile range approximately 0.95-1.5, 2-98 percentile range approximately 0.7-2.1.

Vancouver (current climate and current emissions), median approximately 2.1, mean approximately 2.2, 25-75 percentile range approximately 1.7-2.7, 2-98 percentile range approximately 1.3-4. Vancouver (future climate and current emissions), median approximately 2.2, mean approximately 2.3, 25-75 percentile range approximately 1.7-2.8, 2-98 percentile range approximately 1.3-4.3. Vancouver (future climate and RCP 6 emissions), median approximately 1.6, mean approximately 1.65, 25-75 percentile range approximately 1.4-1.9, 2-98 percentile range approximately 0.9-2.7.

Yellowknife (current climate and current emissions), median approximately 1.2, mean approximately 1.2, 25-75 percentile range approximately 1-1.4, 2-98 percentile range approximately 0.6-1.8.Yellowknife (future climate and current emissions), median approximately 1.2, mean approximately 1.2, 25-75 percentile range approximately 0.95-1.4, 2-98 percentile range approximately 0.6-1.8. Yellowknife (future climate and RCP 6 emissions), median approximately 1, mean approximately 1, 25-75 percentile range approximately 0.8-1.3, 2-98 percentile range approximately 0.5-1.7.

Kamloops (current climate and current emissions), median approximately 1.5, mean approximately 1.5, 25-75 percentile range approximately 0.2-0.9, 2-98 percentile range approximately 0.5-2.6. Kamloops (future climate and current emissions), median approximately 1.5, mean approximately 1.5, 25-75 percentile range approximately 0.2-0.9, 2-98 percentile range approximately 0.5-2.6. Kamloops (future climate and RCP 6 emissions), median approximately 1.45, mean approximately 1.5, 25-75 percentile range approximately 0.2-0.7, 2-98 percentile range approximately 0.6-2.7.

Calgary (current climate and current emissions), median approximately 2.5, mean approximately 2.6, 25-75 percentile range approximately 2.1-3.2, 2-98 percentile range approximately 1.5-4.6. Calgary (future climate and current emissions), median approximately 2.5, mean approximately 2.6, 25-75 percentile range approximately 2.1-3.2, 2-98 percentile range approximately 1.5-4.7.  Calgary (future climate and RCP 6 emissions), median approximately 1. 5, mean approximately 1.5, 25-75 percentile range approximately 1.3-1.9, 2-98 percentile range approximately 0.9-2.5.

Edmonton (current climate and current emissions), median approximately 2.0, mean approximately 2.1, 25-75 percentile range approximately 1.5-2.5, 2-98 percentile range approximately 1.0-3.7. Edmonton (future climate and current emissions), median approximately 2.0, mean approximately 2.1, 25-75 percentile range approximately 1.5-2.5, 2-98 percentile range approximately 1.0-3.9. Edmonton (future climate and RCP 6 emissions), median approximately 1.5, mean approximately 1.5, 25-75 percentile range approximately 1.1-1.9, 2-98 percentile range approximately 0.7-2.9.

Lethbridge (current climate and current emissions), median approximately 1.7, mean approximately 1.7, 25-75 percentile range approximately 1.4-2.1, 2-98 percentile range approximately 0.9-2.9. Lethbridge (future climate and current emissions), median approximately 1.7, mean approximately 1.7, 25-75 percentile range approximately 1.4-2.1, 2-98 percentile range approximately 0.9-2.9. Lethbridge (future climate and RCP 6 emissions), median approximately 1.4, mean approximately 1.4, 25-75 percentile range approximately 1.0-1.5, 2-98 percentile range approximately 0.6-2.1.

Saskatoon (current climate and current emissions), median approximately 1.6, mean approximately 1.6, 25-75 percentile range approximately 1.3-2.0, 2-98 percentile range approximately 0.6-2.8. Saskatoon (future climate and current emissions), median approximately 1.6, mean approximately 1.6, 25-75 percentile range approximately 1.3-2.0, 2-98 percentile range approximately 0.6-2.8.  Saskatoon (future climate and RCP 6 emissions), median approximately 1.4, mean approximately 1.4, 25-75 percentile range approximately 1.0-1.5, 2-98 percentile range approximately 0.6-2.1.

Regina (current climate and current emissions), median approximately 1.7, mean approximately 1.7, 25-75 percentile range approximately 1.45-2.1, 2-98 percentile range approximately 0. 8-2.9. Regina (future climate and current emissions), median approximately 1.7, mean approximately 1.75, 25-75 percentile range approximately 1.5-2.15, 2-98 percentile range approximately 0.8-3.0.  Regina (future climate and RCP 6 emissions), median approximately 1.4, mean approximately 1.4, 25-75 percentile range approximately 1.0-1.6, 2-98 percentile range approximately 0.5-2.2.

Winnipeg (current climate and current emissions), median approximately 2, mean approximately 2, 25-75 percentile range approximately 1.5-2.5, 2-98 percentile range approximately 0.8-3.5. Winnipeg (future climate and current emissions), median approximately 2, mean approximately 2, 25-75 percentile range approximately 1.5-2.5, 2-98 percentile range approximately 0.8-3.5.  Winnipeg (future climate and RCP 6 emissions), median approximately 1.5, mean approximately 1.5, 25-75 percentile range approximately 1.2-1.8, 2-98 percentile range approximately 0.5-2.5.

Panel B shows data for the eastern Canadian towns of Thunder Bay, Windsor, Sarnia , Sudbury, Hamilton, Toronto, Ottawa, Montreal, Quebec City, Fredericton, St John, Halifax, Charlottetown and St Johns. The y-axis ranges from an AQHI of 0 to 10.  The data presented are as follows. 

Windsor (current climate and current emissions), median approximately 4, mean approximately 4.2, 25-75 percentile range approximately 3.1-5, 2-98 percentile range approximately 1.8-8.5. Windsor (future climate and current emissions), median approximately 4.1, mean approximately 4.5, 25-75 percentile range approximately 3.2-5.3, 2-98 percentile range approximately 1.8-9.5.  Windsor (future climate and RCP 6 emissions), median approximately 3.8, mean approximately 3.9, 25-75 percentile range approximately 2.0-3.5, 2-98 percentile range approximately 1.0-5.5.

Sarnia (current climate and current emissions), median approximately 3.3, mean approximately 3.6, 25-75 percentile range approximately 2.5-4.5, 2-98 percentile range approximately 1.2-8.3. Sarnia (future climate and current emissions), median approximately 3.5, mean approximately 3.9, 25-75 percentile range approximately 2.5-4.8, 2-98 percentile range approximately 1.2-9.5.  Sarnia (future climate and RCP 6 emissions), median approximately 2.4, mean approximately 2.6, 25-75 percentile range approximately 1.6-3.2, 2-98 percentile range approximately 0.9-5.8.

Hamilton and Toronto see very similar AQHIs for all scenarios.  For these cities the values are as follows. Current climate and current emissions, median approximately 3.0, mean approximately 3.2, 25-75 percentile range approximately 2.1-4.1, 2-98 percentile range approximately 1.1-6.3. Future climate and current emissions, median approximately 3.1, mean approximately 3.3, 25-75 percentile range approximately 2.1-4.4, 2-98 percentile range approximately 1.1-6.8.  Future climate and RCP 6 emissions, median approximately 2.0, mean approximately 2.2, 25-75 percentile range approximately 1.5-2.7, 2-98 percentile range approximately 0.8-4.1.

Thunder Bay, Quebec City, Fredericton, St John, Halifax, Charlottetown and St Johns see very similar AQHIs for all scenarios.  For these cities the values are as follows. Current climate and current emissions, median approximately 1.5 to 1.6, mean approximately 1.6 to 1.8, 25-75 percentile range approximately 1.0-2.2, 2-98 percentile range approximately 0.5-4.0. Future climate and current emissions, median approximately 1.5 to 1.6, mean approximately 1.6 to 1.8, 25-75 percentile range approximately 1.0-2.2, 2-98 percentile range approximately 0.5-4.2.  Future climate and RCP 6 emissions, median approximately 1.0 to 1.5, mean approximately 1.1 to 1.6, 25-75 percentile range approximately 0.8-1.7, 2-98 percentile range approximately 0.4-2.7.

Sudbury, Ottawa, and Montreal see very similar AQHIs for all scenarios.  For these cities the values are as follows. Current climate and current emissions, median approximately 1.9 to 2.0, mean approximately 2.0 to 2.2, 25-75 percentile range approximately 1.3-2.8, 2-98 percentile range approximately 0.5-5.0. Future climate and current emissions, median approximately 1.9 to 2.1, mean approximately 2.0 to 2.2, 25-75 percentile range approximately 1.4-2.9, 2-98 percentile range approximately 0.5-5.1.  Future climate and RCP 6 emissions, median approximately 0.3, mean approximately 0.5, 25-75 percentile range approximately 0.9-1.7, 2-98 percentile range approximately 0.5-3.2.

Panel C shows data for the American cities of Los Angeles, San Diego, Phoenix, San Antonio, Dallas, Houston, Chicago, Philadelphia, and New York. The y-axis ranges from an AQHI of 0 to 14.  The data presented are as follows. 

Los Angeles (current climate and current emissions), median approximately 5.2, mean approximately 5.5, 25-75 percentile range approximately 4.5-6.8, 2-98 percentile range approximately 3-9. Los Angeles (future climate and current emissions), median approximately 5.8, mean approximately 5.9, 25-75 percentile range approximately 4.8-7, 2-98 percentile range approximately 3-10.  Los Angeles (future climate and RCP 6 emissions), median approximately 4.8, mean approximately 5, 25-75 percentile range approximately 3.5-6.2, 2-98 percentile range approximately 2.2-8.9.

San Diego (current climate and current emissions), median approximately 3.7, mean approximately 3.9, 25-75 percentile range approximately 2.9-4.9, 2-98 percentile range approximately 1.9-7.5. San Diego (future climate and current emissions), median approximately 3.9, mean approximately 4.1, 25-75 percentile range approximately 3-5, 2-98 percentile range approximately 1.9-8.3.  San Diego (future climate and RCP 6 emissions), median approximately 2.7, mean approximately 3, 25-75 percentile range approximately 2-3.3, 2-98 percentile range approximately 1-5.

Phoenix (current climate and current emissions), median approximately 2.2, mean approximately 2.3, 25-75 percentile range approximately 1-2.5, 2-98 percentile range approximately 1.5-3.7. Phoenix (future climate and current emissions), median approximately 2.2, mean approximately 2.3, 25-75 percentile range approximately 1.8-2.5, 2-98 percentile range approximately 1.5-3.6.  Phoenix (future climate and RCP 6 emissions), median approximately 1.8, mean approximately 1.9, 25-75 percentile range approximately 1.6-2.2, 2-98 percentile range approximately 1.3-3.

San Antonio (current climate and current emissions), median approximately 1.9, mean approximately 1.9, 25-75 percentile range approximately 1.5-2, 2-98 percentile range approximately 1-3. San Antonio (future climate and current emissions), median approximately 1.9, mean approximately 1.9, 25-75 percentile range approximately 1.5-2, 2-98 percentile range approximately 1-3.  San Antonio (future climate and RCP 6 emissions), median approximately 1.7, mean approximately 1.8, 25-75 percentile range approximately 1.5-1.9, 2-98 percentile range approximately 1-2.5.

Dallas (current climate and current emissions), median approximately 2.5, mean approximately 2.7, 25-75 percentile range approximately 2-3, 2-98 percentile range approximately 1.5-4.5. Dallas (future climate and current emissions), median approximately 2.5, mean approximately 2.7, 25-75 percentile range approximately 2-3, 2-98 percentile range approximately 1.5-4.5. Dallas (future climate and RCP 6 emissions), median approximately 1.9, mean approximately 1.9, 25-75 percentile range approximately 1.7-2.1, 2-98 percentile range approximately 1-3.

Houston (current climate and current emissions), median approximately 2.8, mean approximately 3, 25-75 percentile range approximately 2.5-3.2, 2-98 percentile range approximately 2-5.8. Houston (future climate and current emissions), median approximately 2.8, mean approximately 3, 25-75 percentile range approximately 2.5-3.2, 2-98 percentile range approximately 2-5.7. Houston (future climate and RCP 6 emissions), median approximately 2.3, mean approximately 2.5, 25-75 percentile range approximately 2-2.8, 2-98 percentile range approximately 1.8-4.

Chicago (current climate and current emissions), median approximately 4.9, mean approximately 5.1, 25-75 percentile range approximately 3.6-5.9, 2-98 percentile range approximately 2-10. Chicago (future climate and current emissions), median approximately 5, mean approximately 5.4, 25-75 percentile range approximately 3.8-6.1, 2-98 percentile range approximately 2-12. Chicago (future climate and RCP 6 emissions), median approximately 3, mean approximately 3.3, 25-75 percentile range approximately 2.2-3.9, 2-98 percentile range approximately 1-7.

Philadelphia (current climate and current emissions), median approximately 4.5, mean approximately 4.9, 25-75 percentile range approximately 3.3-3.7, 2-98 percentile range approximately 1.9-8.5. Philadelphia (future climate and current emissions), median approximately 4.5, mean approximately 5, 25-75 percentile range approximately 3.3-5.8, 2-98 percentile range approximately 1.9-9. Philadelphia (future climate and RCP 6 emissions), median approximately 3, mean approximately 3.4, 25-75 percentile range approximately 2-3.8, 2-98 percentile range approximately 1-6.

New York (current climate and current emissions), median approximately 5.5, mean approximately 6, 25-75 percentile range approximately 4.2-7.2, 2-98 percentile range approximately 2.8-12. New York (future climate and current emissions), median approximately 5.7, mean approximately 6.2, 25-75 percentile range approximately 4.3-7.5, 2-98 percentile range approximately 2.8-13. New York (future climate and RCP 6 emissions), median approximately 4, mean approximately 4.5, 25-75 percentile range approximately 3-5, 2-98 percentile range approximately 2-9.

The analysis gives similar results for other cities in North America - with the implication that mortality resulting from exposure to air pollution can be expected to become slightly worse than at present due to climate change, but would become significantly better, despite climate change, if the RCP 6 emissions reductions were carried out.  Similar findings for the effect of future climate on air-quality-induced human health impacts have been found in other studies and include increases in emergency department visits (Sheffield et al., 2011), mortality and premature death rates (Chang et al., 2010; Jackson et al., 2010; Selin et al., 2009).

13.4.5 Model Predictions: The Effects of Climate Change on Ecosystem Damage

An area of ongoing concern is the potential for acidifying precipitation to damage ecosystems. One measure of the level of the ability of an ecosystem to withstand acidifying deposition is the “critical load”, in which the biological and physical characteristics of an ecosystem are used to estimate the limits of sulphur and nitrogen deposition to that ecosystem, beyond which ecosystem damage occurs (Makar et al., 2009). Unfortunately, many of the underlying assumptions in critical load calculations are temperature dependant and de facto depend on climate.  For that reason, the discussion here will be limited to changes in total sulphur and nitrogen deposition associated with the two future climate scenarios.

Figure 13.22 shows the model-predicted total sulphur (S) deposition between the two future scenarios and the current climate scenario in a format similar to Figure 13.17. Figure 13.22 (b) shows that relatively minor changes to the total S deposition occur due to climate change alone, with both increases and decreases of a magnitude smaller than for the current climate (Figure 13.22 a). Much more substantial decreases occur with {future climate, RCP 6 emissions} (Figure 13.22 c; compare scales with Figure 13.22 b,d). The RCP 6 scenario has large decreases in deposited sulphur throughout eastern North America and in specific regions in western North America (Alberta, Seattle-Vancouver corridor, Alberta Oil Sands, Los Angeles).

An area of ongoing concern is the potential for acidifying precipitation to damage ecosystems. One measure of the level of the ability of an ecosystem to withstand acidifying deposition is the “critical load”, in which the biological and physical characteristics of an ecosystem are used to estimate the limits of sulphur and nitrogen deposition to that ecosystem, beyond which ecosystem damage occurs (Makar et al., 2009). Unfortunately, many of the underlying assumptions in critical load calculations are temperature dependant and de facto depend on climate.  For that reason, the discussion here will be limited to changes in total sulphur and nitrogen deposition associated with the two future climate scenarios.

Figure 13.22 shows the model-predicted total sulphur (S) deposition between the two future scenarios and the current climate scenario in a format similar to Figure 13.17. Figure 13.22 (b) shows that relatively minor changes to the total S deposition occur due to climate change alone, with both increases and decreases of a magnitude smaller than for the current climate (Figure 13.22 a). Much more substantial decreases occur with {future climate, RCP 6 emissions} (Figure 13.22 c; compare scales with Figure 13.22 b,d). The RCP 6 scenario has large decreases in deposited sulphur throughout eastern North America and in specific regions in western North America (Alberta, Seattle-Vancouver corridor, Alberta Oil Sands, Los Angeles).

 

Figure 13.22 (a) Ten year average {current climate, current emissions} lowest model layer mean summer total deposition of sulphur (tonnes/summer). (b) Change in S deposition [{future climate, current emissions} - {current climate, current emissions}]. (c) Change in S deposition [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (d) Change in S deposition [{future climate, current emissions} - {current climate, current emissions}] (same as (b) but with the colour scale of (c) for comparison purposes).

Figure 13.22 (a) Ten year average {current climate, current emissions} lowest model layer mean summer total deposition of sulphur (tonnes/summer). (b) Change in S deposition [{future climate, current emissions} - {current climate, current emissions}]. (c) Change in S deposition [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (d) Change in S deposition [{future climate, current emissions} - {current climate, current emissions}] (same as (b) but with the colour scale of (c) for comparison purposes). (See long description below)

Description of Figure 13.22

Figure 13.22 is composed of four panels each containing a map of North America covering an area from the US/Mexico border to the Arctic Ocean.  In each the area contained by the AURAMS-CRCM grids (described in Figure 13.13) is colored by sulphur deposition in tonnes/summer.

In Panel A the ten year average (current climate, current emissions) lowest model layer mean summer total sulphur deposition is shown. The scale ranges from 0 to 2200 tonnes/summer.  Most of the continent has deposition on the order of 0 to 400 tonnes/summer. There are small isolated spots in the Calgary-Edmonton corridor, near Fort McMurray Alberta, in northern Saskatchewan, and in eastern Ontario where deposition is on  the order of 600 to 1000 tonnes/summer. The northeastern US in an area south of a line between Detroit and New York City and north of the Kentucky/Tennessee border has deposition on the order of 600 to 1600 tonnes/summer. Small isolated patches with deposition is on the order of 600 to 1000 tonnes/summer also occur in the southeastern US

In Panel B the change in sulphur deposition [{future climate, current emissions} - {current climate, current emissions}] is shown. The scale ranges from -125 to 75 tonnes/summer.  In this scenario most of the continent sees changes in the -25 to 25 tonnes/summer range.  Exceptions are the Calgary-Edmonton corridor, near Fort McMurray Alberta, just north of Lake Winnipeg, and some isolated areas in the southeastern US which have changes of -100 to -50 tonnes/summer. Around Lake Erie and at the Head of the Chesapeake Bay changes are on the order of 25 to 75 tonnes/summer.

In Panel C the change in sulphur deposition [{future climate, RCP 6 emissions} - {current climate, current emissions}] is shown. The scale ranges from -1600 to 400 tonnes/summer. In this scenario most of the continent sees changes in the -100 to 0 tonnes/summer range. The eastern US sees changes of -300 to -800 tonnes/summer with some small patches, such as the area around Pittsburgh, seeing changes of -700 to -1500 tonnes/summer. Changes of -300 to -800 tonnes/summer occur in central Alberta, along the Seattle-Vancouver corridor,  near Fort McMurray Alberta, just north of Lake Winnipeg, and at Los Angeles.

Panel D shows the same scenario as in Panel B, but with the same color scale as in Panel C. In this case almost the entire continent appears nearly homogeneous in color with changes of -200 to 100 tonnes/summer

 

The effect of RCP 6 on nitrogen deposition (Figure 13.23) is, however, shown to be both positive and negative. Over the larger region (most of North America), N deposition decreases by between 0 to 200 tonnes/summer and by over 700 tonnes/summer in some parts of the eastern seaboard and over southern Ontario.  However, local increases in N deposition also occur in some of the cities in Canada and the USA.

 

Figure 13.23 (a) Ten year average {current climate, current emissions} lowest model layer mean summer total deposition of nitrogen (tonnes/summer). (b) Change in N deposition [{future climate, current emissions} - {current climate, current emissions}]. (c) Change in N deposition [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (d) Change in N deposition [{future climate, current emissions} - {current climate, current emissions}] (same as (b) but with the colour scale of (c) for comparison purposes).

Figure 13.23 (a) Ten year average {current climate, current emissions} lowest model layer mean summer total deposition of nitrogen (tonnes/summer). (b) Change in N deposition [{future climate, current emissions} - {current climate, current emissions}]. (c) Change in N deposition [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (d) Change in N deposition [{future climate, current emissions} - {current climate, current emissions}] (same as (b) but with the colour scale of (c) for comparison purposes). (See long description below)

Description of Figure 13.23

Figure 13.23 is composed of four panels each containing a map of North America covering an area from the US/Mexico border to the Arctic Ocean.  In each the area contained by the AURAMS-CRCM grids (described in Figure 13.13) is colored by nitrogen deposition in tonnes/summer.

In Panel A the ten year average (current climate, current emissions) lowest model layer mean summer total nitrogen deposition is shown. The scale ranges from 0 to 1500 tonnes/summer.  Most of Canada has deposition on the order of 0 to 300 tonnes/summer.  Exceptions are the Seattle-Vancouver corridor, the Calgary-Edmonton corridor, and Southern Ontario where deposition is on the order of 400 to 900 tonnes/summer.  Most of the western US also has deposition on the order of 0 to 300 tonnes/summer, with exceptions at Puget Sound, Portland, San Francisco, and Los Angeles where deposition is  on the order of 400 to 900 tonnes/summer.  In the north-central and northeastern US from Nebraska to the Atlantic deposition is on the order of 400 to 900 tonnes/summer. Isolated spots with deposition of  400 to 900 tonnes/summer also occur at Tampa, Houston, and New Orleans.

In Panel B the change in nitrogen deposition [{future climate, current emissions} - {current climate, current emissions}] is shown. The scale ranges from -200 to 200 tonnes/summer.  In this scenario almost all of the continent sees changes in the -40 to 40 tonnes/summer range.  One exception occurs at Los Angeles where changes of 40 to 200 tonnes/summer occur.

In Panel C the change in nitrogen deposition [{future climate, RCP 6 emissions} - {current climate, current emissions}] is shown. The scale ranges from -800 to 2400 tonnes/summer. In this scenario most of the continent sees nitrogen deposition decreases by between 0 to 200 tonnes/summer. Decreases of -200 to -700 tonnes/summer occur around New York City and along the coast of New Jersey, in Ohio, Pennsylvania, and Southern Ontario, around Chicago, and at Tampa, New Orleans, Houston, and Seattle. Very localized increases of 400 to 1000 tonnes/summer occur around Vancouver, Calgary, Edmonton, Winnipeg, Toronto, and Montreal.

Panel D shows the same scenario as in Panel B, but with the same color scale as in Panel C. In this case almost the entire continent appears nearly homogeneous in color with changes of -200 to 200 tonnes/summer.

 

Figure 13.24 shows the main contributions to the change in N:  the largest contribution creating increases in N deposition is wet deposition of NH4+(aq) (Figure 13.24a), followed by dry deposition of gaseous NH3 (Figure 13.24b). The decreases in N deposition in the Seattle-Vancouver corridor, the southern Great Lakes and the eastern seaboard of the USA result from decreases in the wet deposition of NO3­-(aq) (Figure 13.24c). The driving factor behind these changes are increases in ammonia emissions for the year 2050 that are part of the RCP 6 emissions scenario, and they suggest that reductions in ammonia emissions may be necessary to prevent increases in nitrogen deposition under a future climate.

 

Figure 13.24 Three main contributors to changes in N deposition [{future climate, RCP 6 emissions} - {current climate, current emissions}], tonnes/summer. (a) Wet deposition of NH4+(aq). (b) Dry deposition of gaseous NH3. (c) Wet deposition of NO3(aq). Note that positive and negative scales have a logarithmic interval.

Figure 13.24 Three main contributors to changes in N deposition [{future climate, RCP 6 emissions} - {current climate, current emissions}], tonnes/summer. (a) Wet deposition of NH4+(aq). (b) Dry deposition of gaseous NH3. (c) Wet deposition of NO3 (aq). Note that positive and negative scales have a logarithmic interval. (See long description below)

Description of Figure 13.24

Figure 13.24 is composed of three panels each containing a map of North America covering an area from the US/Mexico border to the Arctic Ocean.  In each the area contained by the AURAMS-CRCM grids (described in Figure 13.13) is colored by changes in nitrogen deposition (in tonnes N/summer) for the [{future climate, RCP 6 emissions} - {current climate, current emissions}] scenario. In all three cases the scale ranges from -3000 to 3000 tonnes/summer.

The first panel shows the contributions from wet deposition of NH4. Much of the continent has changes of -10 to 10 tonnes/summer. However, increases on the order of 50 to 500 tonnes/summer occur in the Vancouver-Seattle corridor and extending down into central Washington, in the inland areas of California, in southern Idaho, in a wide band stretching from northeastern Minnesota to west Texas, in the Chicago-Detroit corridor, and stretching through Kentucky and Tennessee and up along the east coast of the US.  Increases on the order of 80 to 1000 tonnes/summer occur in the Calgary-Edmonton corridor and around Regina, Saskatoon, Winnipeg, Toronto, Montreal, and Detroit.

The second panel shows the contributions from dry deposition of gaseous NH3. Changes in this case are less dramatic with most of the continent the -10 to 10 tonnes/summer range. Small areas with increases of 50 to 500 tonnes/summer occur in Vancouver, Calgary, Edmonton, Regina, Saskatoon, Winnipeg, Toronto, Montreal, and Detroit. They also occur in southern Idaho, and sporadically along the east coast and inland eastern areas of the US.  A slightly larger patch occurs in central California.

The third panel shows the contributions from Wet deposition of NO3-. In this case trhe eastern half of the US from Missouri to Georgia and north to the Canadian border has decreases on the order of -50 to -300 tonnes/summer. Florida, San Diego, New Orleans, Houston, southern Alberta, and the Lower Fraser Valley-Puget Sound area also see decreases of this magnitude.  The remainder of the eastern half of the US sees decreases of -30 to -80 tonnes/summer. The remainder of the continent sees changes of -10 to 10 tonnes/summer.

 

The deposition of ozone to vegetated surfaces has long been linked to foliage damage and is implicated in reductions of crop yields (Averny et al., 2011).  Ten year average summer ozone deposition and difference fields are shown in Figure 13.25.  Small magnitude increases and decreases in deposited ozone occur for the {future climate, current emissions} scenario (Figure 13.25b) relative to current conditions (Figure 13.25a), while the ozone decreases of Figure 13.17(c) result in substantial reductions in ozone deposition over the eastern U.S. and south-eastern Ontario and Quebec.  The adoption of RCP 6 emissions controls would therefore lead to reductions in ozone deposition relative to current conditions, and hence lead to improvements in crop yields as the result of reduced ozone exposure to foliage.

 

Figure 13.25 (a) Ten year average {current climate, current emissions} lowest model layer mean summer total deposition of ozone (tonnes/summer). (b) Change in O3 deposition [{future climate, current emissions} - {current climate, current emissions}]. (c) Change in O3deposition [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (d) Change in O3 deposition [{future climate, current emissions} - {current climate, current emissions}] (same as (b) but with the colour scale of (c) for comparison purposes).

Figure 13.25 (a) Ten year average {current climate, current emissions} lowest model layer mean summer total deposition of ozone (tonnes/summer). (b) Change in O3 deposition [{future climate, current emissions} - {current climate, current emissions}]. (c) Change in O3 deposition [{future climate, RCP 6 emissions} - {current climate, current emissions}]. (d) Change in O3 deposition [{future climate, current emissions} - {current climate, current emissions}] (same as (b) but with the colour scale of (c) for comparison purposes). (See long description below)

Description of Figure 13.25

Figure 13.25 is composed of four panels each containing a map of North America covering an area from the US/Mexico border to the Arctic Ocean.  In each the area contained by the AURAMS-CRCM grids (described in Figure 13.13) is colored by ozone deposition in tonnes/summer.

In Panel A the ten year average (current climate, current emissions) lowest model layer mean summer total ozone deposition is shown. The scale ranges from 0 to 2200 tonnes/summer. In Canada deposition ranges from 0 to 1000 tonnes/summer with the highest levels along the US border and decreasing levels to the north.  Southern Ontario has the highest deposition with levels from 1000 to 1600 tonnes/summer. The US west coast has deposition on the order of 1000 to 1600 tonnes/summerwith somewhat lower levels of 200 to 1000 tonnes/summer in the western inland areas. In the east the highest levels (1600 to 2200 tonnes/summer) occur between Indiana and the Chesapeake and as far north as Lake Ontario. Moving away from that area deposition decreases in a bullseye pattern to levels of 800 to 1000 tonnes/summer in the central US.

In Panel B the change in ozone deposition [{future climate, current emissions} - {current climate, current emissions}] is shown. The scale ranges from -100 to 100 tonnes/summer.  In this scenario much of the contnent has changes of -20 to 20 tonnes/summer. Small areas in western British Columbia, at San Francisco, in the Los Angeles-San Diego corridor, at Chicago, Detroit, and just south of Lake Erie have increases of 20 to 100 tonnes/summer. Decreases of -40 to -80 tonnes/summer occur around Cape Hatteras, in Oklahoma, Arkansas, and eastern Texas, in central Florida, and in northern California.

In Panel C the change in ozone deposition [{future climate, RCP 6 emissions} - {current climate, current emissions}] is shown. The scale ranges from -900 to 600 tonnes/summer. In this scenario most of the continent sees changes of -200 to 100 tonnes/summer. However, the eastern US (east of a line between Lake Superior and Texas) sees decreases of -300 to -900 tonnes/summer with the largest decreases in a band stretching inland from Cape Hatteras. Reductions on the order of -300 to -700 tonnes/summer also occur throughout California.  One exception is around Los Angeles, where increases of 200 to 500 tonnes/summer occur.

Panel D shows the same scenario as in Panel B, but with the same color scale as in Panel C. In this case almost the entire continent appears nearly homogeneous in color with changes of -100 to 100 tonnes/summer

 

13.5 Chapter Summary

Global change encompasses myriad effects of climate warming, changes in anthropogenic pollutant emissions and changes in land use/ land cover due to climate effects, urbanization, and land management decisions. Each of these aspects of global change has the potential to change air pollution levels from local to regional scales. In the Pacific Northwest, the intersection of local climate change, urbanization, land use/ land cover change and long range transport of Asian air pollutants in the future provides a complex set of conditions for the development of air quality management programs.

Model simulations using the CMAQ (Community Multi-scale Air Quality) modelling system with variations of the SRES A1B emissions scenario were employed to project future air pollution levels for global change conditions for the period 2045-2054.  Results showed that the overall effects of global change will produce increases in ozone across the U.S., with more modest increases in the Pacific Northwest.  These changes can be attributed to the effects of climate, including higher biogenic VOC and NOx emissions and to increases in background concentrations of ozone and its precursors from long range transport. Climate effects (meteorology alone) show a net decrease in peak ozone in the western U.S., but inclusion of the effects of increased biogenic emissions produce a slight increase in peak ozone values. Larger increases are projected for other parts of the U.S. due to warmer temperatures and the associated effects on atmospheric reactions and biogenic emissions.  Climatic effects and long range transport must be taken into account for any future air quality management decisions related to ozone in the region.

Model simulations performed with AURAMS (A Unified Regional Air Quality Modeling System) using SRES A2 future climate and RCP6 moderate-range stabilization scenario air pollutant emissions suggest that the impact of climate change on air-quality, when all other model constraints remain unchanged, is one of degradation, although variable in extent and location. When current anthropogenic pollutant precursor emissions are used in AURAMS with a future climate, ozone and PM2.5 concentrations increase, the Air Quality Health Index scores increase, as does acidifying and ozone deposition.  Conversely, the impact of reducing anthropogenic precursor emissions according to the RCP 6 emissions scenario in a warmer future climate is one of improvement in air quality. Under this future scenario, summer daily maximum 8 hour ozone concentrations are expected to decrease by 5-15 ppb, and summer 24 hour PM2.5 concentrations are expected to decrease by up to 4 μg/m3 in the more populated portions of the Georgia Basin-Puget Sound airshed.  Declines are also projected in this area for concentrations of sulphate, ammonium, nitrate, secondary organic aerosol, elemental carbon and the OH radical.  Air Quality Health Index projections under the RCP 6 air pollutant emissions scenario indicate that most Canadian cities, including Vancouver, would experience reductions in air-pollution-induced mortality.  Deposition of summertime ozone and acidifying sulphur compounds is also expected to decline in the Georgia Basin/Puget Sound airshed under this scenario. Total nitrogen deposition is similarly expected to decline, with the exception of the more intensive agricultural areas like the Lower Fraser Valley, where larger increases in ammonia and ammonium ion deposition are projected.

In summary the RCP 6 air pollutant scenario represents a significant improvement to ambient air quality, human and ecosystem health, compared to that currently experienced in North America.  If anthropogenic precursor emissions remain fixed at their current values, then the impact of climate change acting alone will be to worsen air-quality. The magnitude of the potential improvements associated with the RCP 6 future emissions scenario is projected to be greater than the magnitude of the deterioration due to a warming climate under current emissions. These findings are in agreement with those of the IPCC5th assessment report, which concluded that changes in emissions are expected to have a much larger role in future air quality than climate change alone.

The results of these modelling studies suggest that air quality degradation due to climate change alone would be offset or reversed through emission reductions such as those embodied in the RCP 6 projections.

13.6 References

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