Urban Surface Modifications as a Potential Ozone Air Quality Improvement Strategy in California
Phase One: Initial Mesoscale Modeling
Publication Number: CEC-500-2005-128
Publication Date: July 2005
PIER Program Area: Energy-Related Environmental Research
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Air quality management plans, such as state implementation plans (SIPs), directly or indirectly provide region-specific estimates of the reductions in precursor emissions needed to reach and/or maintain the carrying capacity of the atmosphere below a certain threshold, so as to meet the standards for criteria pollutants. For ozone, such estimates suggest that a significant level of emissions reduction may be needed in urbanized areas—especially in terms of NOX.
As emission control strategies become relatively more expensive, and therefore more difficult to implement when regions approach their attainment targets (both in time and level of control), it is desirable to explore additional strategies that can supplement those planned or already in place. It is hoped that such alternative strategies would also be cost effective, so that they could efficiently complement the mix of other emission controls. One of several such strategies that have been discussed and evaluated at least qualitatively (but perhaps inconsistently) is the so-called “urban heat island control” strategy or, more accurately, “urban surface modification.” The proposed strategies of increased surface albedo and vegetative cover will produce effects, both positive and negative, regardless of whether heat islands exist and/or their timing (i.e., the classical heat island peaks at night).
Increased surface albedo and vegetative cover have been shown in field measurements, experiments, and theoretical modeling work to produce significant, measurable, verifiable, and repeatable savings in energy used for summer cooling. The savings have been evaluated and quantified at both the regional (utility) and building scales.
However, in terms of meteorology and air quality, the potential impacts of large-scale surface modifications can presently be demonstrated only via numerical (e.g., mesoscale meteorological and photochemical) modeling. The potential air-quality impacts of these strategies have been evaluated sporadically by several research entities, with mixed results. All studies show positive and negative impacts, but differ in characterizing the dominant effect in each region—that is, whether these strategies represent an overall benefit or a liability.
Because of the nature of the proposed strategies, and the many issues involved in modeling and quantifying their potential impacts, the U.S. Environmental Protection Agency (EPA) and air pollution control districts have considered these proposed strategies only informally/qualitatively and have not yet considered them seriously in a regulatory framework. This is partly because of the lack of conclusive results from modeling studies and partly because the current regulatory framework does not easily allow for “unconventional” strategies to be readily included in the SIP process. Thus, new or updated modeling efforts are needed to further improve upon past studies, develop more reliable and credible results, and resolve some issues with earlier modeling work— as well as to assemble modeling systems that are more acceptable to and can be adopted by regulatory agencies in their planning and modeling processes.
The purpose of this study was to explore and evaluate the potential of surface modifications in improving ozone air quality in addition to their energy savings.
This study’s first objective was to ensure that, at least, no significant adverse air-quality impacts would result from increasing urban albedo and vegetative cover for the purpose of reducing electricity use. The study also sought to discern whether such strategies have potential additional benefits, such as improving air quality, to provide a basis for considering them separately on their own merit.
As with some other strategies, the modification of surface properties in urban areas can cause both net decreases and increases in ozone concentrations. The task, then, is to tailor strategies to regions of interest so that they produce overall beneficial impacts while minimizing negative impacts. The optimal mix of such strategies (to maximize the net ozone reductions) will differ among regions and will depend on factors such as local emissions, meteorology, and episodic conditions. Thus, ideally, the variability in all forcings should be considered, and specific modeling studies should be designed to quantify local potential impacts. For the first phase of this study, the photochemical episodes used were those of August 3 through 7, 1997, for Southern California (SCOS-97), and July 29 through August 4, 2000, for Central California (CCOS-2000).
The present study was designed as an initial step towards developing region-specific impact assessments for California. Future follow-up studies could then be undertaken to provide more in-depth analysis and modeling detail for region-specific implementation plans or scenarios. In this initial phase of the project (Phase 2 of this study is currently underway), the modeling was performed in a fashion compatible with work done at the California regulatory agencies for the episodes identified earlier. However, the study introduced several improvements to the modeling methodology as well as to input data to improve the simulation of specific surface modification strategies. A relatively more detailed surface characterization system was also implemented to override the default and relatively coarse characterization of urban areas in mesoscale models.
Results to date (Phase 1 of study) suggest a host of meteorological changes in response to such surface modifications—most notably in relatively lower surface and air temperatures. These changes are the main effects of interest sought in this application, because decreased air temperatures help reduce cooling electricity use, emissions of ozone precursors (that are temperature dependent), and photochemical reaction rates in dominant mechanisms increasing tropospheric ozone, such as peroxyacetyl nitrate (PAN) chemistry. The spatial distribution of perturbations in meteorological fields (e.g., temperature, wind, and PBL depth) follows closely the geographical distribution of surface modifications. Where surface modifications are larger, the impacts on air temperature in the affected areas and immediately downwind of them are greater. For example, Figures ES-1 and ES-2 depict changes in 2-m air temperatures (relative to the base case) for Southern and Central California at 1300 on August 4 and at 1200 on July 31, respectively. The base-case wind vector field (at 10m) is superimposed on the temperature-change field in each domain.
Please see report for - Figure ES-1. Change in air temperature in Southern California as a result of increased urban albedo and vegetative cover (1300 on August 4).
Please see report for - Figure ES-2. Change in air temperature in Central California as a result of increased urban albedo and vegetative cover (1200 on July 31).
Overall, the simulations suggest that there is a large spatiotemporal variability in the impacts of meteorological perturbations on ozone concentrations. The sub-regional peaks in Central California (Sacramento, San Francisco Bay Area, Highway 99 corridor, Fresno, and Bakersfield) decrease as a result of implementing surface modification strategies. In Southern California, the domain peak can increase or decrease on August 5, depending on assumed surface modification scenarios but always decreases on August 6. In central California, 3-day averaged decreases in the regional peaks are in the range of 2 to 13 ppb, depending on the region, whereas in Southern California, the 2-day averaged reductions in the peak range from about 0.5 to 3 ppb.
The report provides additional metrics other than peak-related ones (e.g., area-averaged indices with respect to the 8-hour standard, 1-hour standard, 24-hour averages, daytime changes). In addition, some changes were converted into emission reduction “equivalents” to provide an alternate means of qualitatively evaluating the usefulness of the proposed strategies.
To achieve the levels of ozone changes detailed in the report, a significant surface modification effort is needed. Crude calculations suggest that, for the assumptions made in the study, about half of the modifiable built-up surface area (e.g., roofs, paved surfaces, driveways, parking lots) in each urbanized region need to be modified—for example, with application of high-albedo materials. In terms of vegetative cover increase, the calculations suggest that some 200,000 trees need to be added to the smaller urbanized regions in California (e.g., Bakersfield), and up to some 8 million trees need to be added in very large regions such as Southern California (which also includes the Los Angeles Basin, San Diego, and all surrounding areas).
Of course, implementation-specific simulations and calculations will have to be made in detailed follow-up studies to determine more accurately the level of modifications needed. Ultimately, there may be smaller or larger modification levels needed than suggested in this report. In particular, Phase 2 of this study will address these modeling issues in more detail with a new generation of modified and urbanized meteorological models and corresponding photochemical simulations.
For each region, the relative levels of benefits and adverse effects also depend on the level of surface modifications. Qualitatively speaking, there appears to be region-specific thresholds or ranges for such modifications beyond which further increases in surface modifications do not produce much additional net benefits and in some cases tend to produce net disbenefits. Because of such issues and the existence of competing non-linear effects, region-by-region and multi-episodic assessments and modeling may be needed to identify the optimal mix of surface modification strategies. And because the benefits and adverse effects also change from one location to another (or one level of surface modifications to another, etc.) region-by-region analysis and modeling are needed to evaluate the local usefulness and effectiveness of a range of scenarios and strategies before the appropriate policy action or recommendation can be developed.
Benefits to California
From a regulatory perspective, photochemical air-quality modeling is an important tool and a cornerstone component in the planning process that ultimately leads to implementing effective strategies for air-quality improvements. The Clean Air Act requires that non-attainment areas, especially those designated as serious or higher (for ozone), use a photochemical grid model to study the potential impacts of proposed control strategies and/or demonstrate attainment, using designated field-intensive periods or historical air-quality episodes, such as those with high observed ozone concentrations. To facilitate the usefulness of these results, the modeling episodes selected in this study were chosen to be compatible with those used by California regulatory agencies.
The ultimate goal of urban-surface modification strategies is to help lower ozone concentrations in California cities directly (by reducing the use of electricity for cooling) and indirectly (by affecting meteorology-dependent emission and photochemical-reaction rates). The anticipated effects from surface modifications such as increased albedo and vegetative cover arise because of the relatively lower surface temperatures (slower rates of warming) of the modified surfaces. These lower surface temperatures in turn cause changes in air temperatures, area-emission rates of ozone precursors (including biogenic emissions), electricity use for cooling and related emissions from power plants, and rates of photochemical production of ozone.
While the micrometeorological and energy impacts of certain surface modification strategies can be demonstrated and evaluated in the field, the potential large-scale effects from such surface modifications are relatively unknown and can currently be assessed only via numerical modeling. Increased built-up surface albedo and vegetative cover, for example, have been shown to reduce cooling electricity use in summer in the United States, but their regional environmental impacts are more difficult to ascertain, because of uncertainties in meteorological and photochemical models and input data. Thus more up-to-date modeling is necessary if more accurate estimates of such impacts are sought.
This study consists of two phases, the first of which is summarized in this report. This first phase involved modification, update, improvement, and application of state-of-science mesoscale meteorological and photochemical models (MM5 and CAMx) and related emission models in evaluating the potential impacts of these strategies in California during two episodes. The findings suggest both positive and negative impacts depending on location, time, and level of modifications. Peak ozone concentrations in southern California can increase during certain times of the episode; whereas, in central California the peaks decrease considerably. In terms of area-averaged indices, all regions experience reductions in ozone levels. In the future, multi-episodic and seasonal evaluations may be needed.
In the second phase of the study, a new generation of mesoscale (urbanized) meteorological models will be used in further evaluating these positive and negative air-quality impacts to determine the dominant and overall effects.
Keywords: Mesoscale meteorological modeling, photochemical modeling, ozone air quality, surface modifications, MM5, CAMx, urban meteorology
Table of ContentsPreface ii
Executive Summary 1
1. Introduction and Background 6
1.2 Meteorology and Air Quality 9
3. Purpose of this Study 15
4. Approach 16
5. Mesoscale Models 18
5.2 Photochemical Model 19
5.3 Model Data 21
7. Additional Models Configurations 26
8. Episodes 30
8.2 July–August 2000 (Central California) 31
11. Improved Surface Characterization and Input 38
12. Base-case Development 41
12.2 Central California (CCOS-2000) Base Case 48
13.2 Model Performance for the CCOS-00 Domain and Episode 65
14.2 Discussion B: Increasing Vegetative Cover and Biogenic Hydrocarbon Emissions 82
14.3 Impacts on Biogenic Hydrocarbon Emissions 83
15.2 Central California 99
16.2 Emission Equivalents: South Coast Air Basin Example 116
17.2 Results Summary 119
17.3 Recap of Next/Future Steps and Research Needs 122
Appendix A: Brief Aspects of Meteorology and Photochemistry and Relevance to California A-1
Appendix B: Meteorological and Air Quality Stations and Monitors in
Southern and Central California B-1
Appendix C: Highlights of Selected Meteorological Models C-1
Appendix D: Highlights of Selected Photochemical Models D-1
Appendix E: Some Surface Characterization Data Sources E-1
List of Tables
Table 1 Impacts of urban areas on annual HDD and CDD 9
Table 2 T-O3 correlations for selected regions in the U.S 12
Table 3 Historical August 1997 emission inventories for the South Coast Air Basin 22
Table 4 Historical 2000 CCOS emission inventory for selected regions 22
Table 5 Vertical configuration of MM5 24
Table 6 MM5 and CAMx vertical levels correspondence 25
Table 7 Assumed EPA/ARB clean boundary conditions used in the study 29
Table 8 Observed peak ozone in the Southern California domain 31
Table 9 Observed peak ozone in the Central California domain 31
Table 10 Base-case values of LULC-related physical parameters (for summer) 40
Table 11 Air temperature bias (MRE) and error (MURE) averaged for three days 57
Table 12 Air temperature bias (MRE) and error (MURE) for each day 58
Table 13 Wind speed bias (MRE) and error (MURE) averaged for three days 58
Table 14 Wind speed bias (MRE) and error (MURE) for each day 59
Table 15 Wind speed gross error 59
Table 16 Nested grid model performance for entire domain (Southern California) 64
Table 17 Nested grid model performance for sub-domains (zones) 3, 4 and 5 64
Table 18 Standalone grid model performance for entire domain (Southern California) 64
Table 19 Standalone grid model performance for sub-domains (zones) 3, 4 and 5 64
Table 20 Bias (MRE) and gross error (MURE) for selected regions in the CCOS domain 66
Table 21 Observed peak concentrations in the CCOS domain 66
Table 22 MRE, MURE, and UA metrics compared to ARB model performance 67
Table 23 MRE, MURE, and UA metrics compared to model performance 68
Table 24 MRE, MURE, and UA metrics compared to ARB model performance for the CCOS domain and episode 69
Table 25 MRE, MURE, and UA metrics compared to model performance benchmarks (for the CCOS standalone grid) 69
Table 26 Assumed percentages of built-up surface types for USGS LULC 70
Table 27 Assumed levels of albedo increase per surface type 71
Table 28 Scenarios for albedo change at 200-m resolution 71
Table 29 Scenarios for vegetation cover increase (as % of 200-m cells) 72
Table 30 Base case and scenarios for soil moisture changes 72
Table 31 Total ROOF area to be modified (km2) 75
Table 32 Total PAVED-surface area (parking, roads, sidewalks) to be modified (km2) 76
Table 33 Number of buildings needed for modification 76
Table 34 Number of trees needed for modification 76
Table 35 Albedo of selected materials 82
Table 36 Changes in domain-wide unpaired peak (averaged over two days; 8/5 and 8/6) for the Southern California Domain 97
Table 37 Changes in region-averaged peaks (CCOS) 113
Table 38 Potential reduction in LADWP peak demand for three scenarios 115
List of Figures
Figure 1 Quantities of interest to this modeling study 16
Figure 2 Model simulation sequence 17
Figure 3 LULC processing step 17
Figure 4 Southern California modeling domain and nested grids 23
Figure 5 Central California modeling domain and nested grids 24
Figure 6a An example of vertical variation in nudging coefficients 28
Figure 6b Example scaling of vertical diffusivity in SCOS simulations 28
Figure 7 Model performance and signal/noise 35
Figure 8 Replication of the ARB SCOS-97 simulations with the CAMx 3.10 36
Figure 9 Replication of the ARB CCOS-00 simulations with the CAMx 3.10 37
Figure 10 Tiles of 200-m resolution USGS LULC for Central to Southern California 39
Figure 11 Simulated base-case wind and temperature fields for Southern California 41
Figure 12 Simulated ozone concentrations on August 5 and 6, Southern California. 46
Figure 13a Simulated base-case ozone concentrations for the Southern California domain at 1500 LST on August 5, 1997 47 Figure 13b Simulated base-case ozone concentrations for the Southern California domain at 1500 LST on August 6, 1997 47
Figure 14 Simulated base-case wind and temperature fields for Central California 48
Figure 15(a) Simulated 10-m streamlines at 1600 LST July 31 51
Figure 15(b) Simulated 10-m streamlines at 1600 LST August 1 51
Figure 16 Simulated base case ozone concentrations on July 31 and August 1, 2000 for Central California 52
Figure 17a Peak ozone concentrations at each grid cell on July 31 55
Figure 17b Peak ozone concentrations at each grid cell on August 1 55
Figure 18 SoCAB Model performance evaluation zones 57
Figure 19 Predicted vs. observed 2-m air temperature (K) 60
Figure 20 Air temperature σ/σο ratios 62
Figure 21 Air temperature E/σο ratios for 4 days 62
Figure 22 Air temperature E’/σο ratio for 4 days 63
Figure 23 Model performance evaluation sub-regions for the CCOS 65
Figure 24 Distributions of changes in surface albedo and soil moisture in the SCOS domain 73
Figure 25 Distributions of changes in surface albedo and soil moisture in the CCOS domain 74
Figure 26 Modification potential in Southern California 77
Figure 27 Modification potential in Central California 77
Figure 28 Example changes in soil moisture for Southern and Central California 78
Figure 29 Measured spectral reflectance of selected materials 80
Figure 30 Spectral reflectivity characteristics of selected roofing materials 81
Figure 31 Changes in 2-m air temperature and 10-m wind speed for four Southern California regions and for 5 surface-modification scenarios 85
Figure 32 Air temperature difference (from the base case) for scenario 22 88
Figure 33 Maximum hourly decreases in ozone concentration at each grid cell for several scenarios 93
Figure 34 RRF for four strategies (South Coast) for August 5 96
Figure 35 Changes in selected ozone indices for the Southern California domain 99
Figure 36 Changes in 2-m air temperature and 10-m wind speed for four Central California regions and for 3 surface-modification scenarios 101
Figure 37 Air temperature difference (from base case) for case 20 in the CCOS modeling domain 104
Figure 38 Differences in ozone concentrations (case 20 minus base case) for July 31 108
Figure 39 Maximum hourly decreases in ozone concentration at each grid cell for several scenarios 111
Figure 40 Changes in the 1-hr peak for case 10 and case 20 for four CCOS regions and three days 112
Figure 41 Daily peak load (LADWP) vs. daily maximum air temperature (1999-2004) in Los Angeles 115
Figure 42 Domain-peak ozone concentration (averaged over August 5 and 6) as a function of NOX and VOC emissions (%) for Southern California 117