| 1. |
- Kumar, Anikender, et al.
(författare)
-
Effects of low-carbon energy adoption on airborne particulate matter concentrations with feedbacks to future climate over California
- 2020
-
Ingår i: Journal of Geophysical Research: Atmospheres. - 2169-8996 .- 2169-897X. ; 125:16
-
Tidskriftsartikel (refereegranskat)abstract
- California plans to reduce emissions of long‐lived greenhouse gases (GHGs) through adoption of new energy systems that will also lower concentrations of short‐lived absorbing soot contained in airborne particulate matter (PM). Here we examine the direct and indirect effects of reduced PM concentrations under a low‐carbon energy (GHG‐Step) scenario on radiative forcing in California. Simulations were carried out using the source‐oriented WRF/Chem (SOWC) model with 12 km spatial resolution for the year 2054. The avoided aerosol emissions due to technology advances in the GHG‐step scenario reduce ground level PM concentrations by ~8.85% over land compared to the Business as Usual (BAU) scenario, but changes to meteorological parameters are more modest. Top of atmospheric forcing predicted by the SOWC model increased by 0.15 W m‐2, surface temperature warmed by 0.001 K, and planetary boundary layer height (PBLH) increased by 2.20 cm in the GHG‐Step scenario compared to the BAU scenario. PM climate feedbacks are small because the significant changes in ground level PM concentrations associated with the GHG‐Step scenario are limited to the first few hundred meters of the atmosphere, with little change for the majority of the vertical column above that level. As an order‐of‐magnitude comparison, the long‐term effects of global reductions in GHG emissions (RCP8.5 – RCP4.5) lowered average surface temperature over the California study domain by approximately 0.76 K. The effects of long‐lived climate pollutants such as CO2 are much stronger than the effects of short‐lived climate pollutants such as PM soot over California in the year 2054.
|
|
| 2. |
- Ramea, Kalai, et al.
(författare)
-
Integration of behavioral effects from vehicle choice models into long-term energy systems optimization models
- 2018
-
Ingår i: Energy Economics. - : Elsevier BV. - 0140-9883 .- 1873-6181. ; 74, s. 663-676
-
Tidskriftsartikel (refereegranskat)abstract
- Long-term energy systems models have been used extensively in energy planning and climate policy analysis. However, specifically in energy systems optimization models, heterogeneity of consumer preferences for competing energy technologies (e.g., vehicles), has not been adequately represented, leading to behaviorally unrealistic modeling results. This can lead to policy analysis results that are viewed by stakeholders as clearly deficient. This paper shows how heterogeneous consumer behavioral effects can be introduced into these models in the form of perceived disutility costs, to more realistically capture consumer choice in making technology purchase decisions. We developed a novel methodology that incorporates the theory of a classic consumer choice model into a commonly used long-term energy systems modeling framework using a case study of light-duty vehicles. A diverse set of consumer segments (thirty-six) is created to represent observable, identifiable differences in factors such as annual driving distances and attitude towards risks of new technology. Non-monetary or “disutility” costs associated with these factors are introduced to capture the differences in preferences across consumer segments for various technologies. We also create clones within each consumer segment to capture randomly distributed unobservable differences in preferences. We provide and review results for a specific example that includes external factors such as recharging/refueling station availability, battery size of electric vehicles, recharging time and perceived technology risks. Although the example is for light-duty vehicles in the US using a specific modeling system, this approach can be implemented more broadly to model the adoption of consumer technologies in other sectors or regions in similar energy systems modeling frameworks.
|
|
| 3. |
|
|
| 4. |
- Zapata, Christina, et al.
(författare)
-
Estimating criteria pollutant emissions using the California Regional Multisector Air Quality Emissions (CA-REMARQUE) model v1.0
- 2018
-
Ingår i: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 11, s. 1293-1320
-
Tidskriftsartikel (refereegranskat)abstract
- The California Regional Multisector Air Quality Emissions (CA-REMARQUE) model is developed to predict changes to criteria pollutant emissions inventories in California in response to sophisticated emissions control programs implemented to achieve deep greenhouse gas (GHG) emissions reductions. Two scenarios for the year 2050 act as the starting point for calculations: a business-as-usual (BAU) scenario and an 80 % GHG reduction (GHG-Step) scenario. Each of these scenarios was developed with an energy economic model to optimize costs across the entire California economy and so they include changes in activity, fuels, and technology across economic sectors. Separate algorithms are developed to estimate emissions of criteria pollutants (or their precursors) that are consistent with the future GHG scenarios for the following economic sectors: (i) on-road, (ii) rail and off-road, (iii) marine and aviation, (iv) residential and commercial, (v) electricity generation, and (vi) biorefineries. Properly accounting for new technologies involving electrification, biofuels, and hydrogen plays a central role in these calculations. Critically, criteria pollutant emissions do not decrease uniformly across all sectors of the economy. Emissions of certain criteria pollutants (or their precursors) increase in some sectors as part of the overall optimization within each of the scenarios. This produces nonuniform changes to criteria pollutant emissions in close proximity to heavily populated regions when viewed at 4 km spatial resolution with implications for exposure to air pollution for those populations. As a further complication, changing fuels and technology also modify the composition of reactive organic gas emissions and the size and composition of particulate matter emissions. This is most notably apparent through a comparison of emissions reductions for different size fractions of primary particulate matter. Primary PM2.5 emissions decrease by 4 % in the GHG-Step scenario vs. the BAU scenario while corresponding primary PM0.1 emissions decrease by 36 %. Ultrafine particles (PM0.1) are an emerging pollutant of concern expected to impact public health in future scenarios. The complexity of this situation illustrates the need for realistic treatment of criteria pollutant emissions inventories linked to GHG emissions policies designed for fully developed countries and states with strict existing environmental regulations.
|
|
| 5. |
- Zapata, Christina, et al.
(författare)
-
Low-carbon energy generates public health savings in California
- 2018
-
Ingår i: Atmospheric Chemistry and Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 18:7, s. 4817-4830
-
Tidskriftsartikel (refereegranskat)abstract
- California's goal to reduce greenhouse gas (GHG) emissions to a level that is 80 % below 1990 levels by the year 2050 will require adoption of low-carbon energy sources across all economic sectors. In addition to reducing GHG emissions, shifting to fuels with lower carbon intensity will change concentrations of short-lived conventional air pollutants, including airborne particles with a diameter of less than 2.5 µm (PM2.5) and ozone (O3). Here we evaluate how business-as-usual (BAU) air pollution and public health in California will be transformed in the year 2050 through the adoption of low-carbon technologies, expanded electrification, and modified activity patterns within a low-carbon energy scenario (GHG-Step). Both the BAU and GHG-Step statewide emission scenarios were constructed using the energy–economic optimization model, CA-TIMES, that calculates the multi-sector energy portfolio that meets projected energy supply and demand at the lowest cost, while also satisfying scenario-specific GHG emissions constraints. Corresponding criteria pollutant emissions for each scenario were then spatially allocated at 4 km resolution to support air quality analysis in different regions of the state. Meteorological inputs for the year 2054 were generated under a Representative Concentration Pathway (RCP) 8.5 future climate. Annual-average PM2.5 and O3 concentrations were predicted using the modified emissions and meteorology inputs with a regional chemical transport model. In the final phase of the analysis, mortality (total deaths) and mortality rate (deaths per 100 000) were calculated using established exposure-response relationships from air pollution epidemiology combined with simulated annual-average PM2.5 and O3 exposure. Net emissions reductions across all sectors are −36 % for PM0.1 mass, −3.6 % for PM2.5 mass, −10.6 % for PM2.5 elemental carbon, −13.3 % for PM2.5 organic carbon, −13.7 % for NOx, and −27.5 % for NH3. Predicted deaths associated with air pollution in 2050 dropped by 24–26 % in California (1537–2758 avoided deaths yr−1) in the climate-friendly 2050 GHG-Step scenario, which is equivalent to a 54–56 % reduction in the air pollution mortality rate (deaths per 100 000) relative to 2010 levels. These avoided deaths have an estimated value of USD 11.4–20.4 billion yr−1 based on the present-day value of a statistical life (VSL) equal to USD 7.6 million. The costs for reducing California GHG emissions 80 % below 1990 levels by the year 2050 depend strongly on numerous external factors such as the global price of oil. Best estimates suggest that meeting an intermediate target (40 % reduction in GHG emissions by the year 2030) using a non-optimized scenario would reduce personal income by USD 4.95 billion yr−1 (−0.15 %) and lower overall state gross domestic product by USD 16.1 billion yr−1 (−0.45 %). The public health benefits described here are comparable to these cost estimates, making a compelling argument for the adoption of low-carbon energy in California, with implications for other regions in the United States and across the world.
|
|
