scholarly journals ESP v1.0: methodology for exploring emission impacts of future scenarios in the United States

2011 ◽  
Vol 4 (2) ◽  
pp. 287-297 ◽  
Author(s):  
D. H. Loughlin ◽  
W. G. Benjey ◽  
C. G. Nolte
Keyword(s):  
United States ◽  
Growth Factors ◽  
Air Quality ◽  
Air Pollutants ◽  
Energy System ◽  
The United States ◽  
Air Pollutant ◽  
Population Projections ◽  
Pollutant Emissions ◽  
Modeling Framework

Abstract. This article presents a methodology for creating anthropogenic emission inventories that can be used to simulate future regional air quality. The Emission Scenario Projection (ESP) methodology focuses on energy production and use, the principal sources of many air pollutants. Emission growth factors for energy system categories are calculated using the MARKAL energy system model. Growth factors for non-energy sectors are based on economic and population projections. These factors are used to grow a 2005 emissions inventory through 2050. The approach is demonstrated for two emission scenarios for the United States. Scenario 1 extends current air regulations through 2050, while Scenario 2 adds a hypothetical CO2 mitigation policy. Although both scenarios show significant reductions in air pollutant emissions through time, these reductions are more pronounced in Scenario 2, where the CO2 policy results in the adoption of technologies with lower emissions of both CO2 and traditional air pollutants. The methodology is expected to play an important role within an integrated modeling framework that supports the US EPA's investigations of linkages among emission drivers, climate and air quality.

scholarly journals Modeling framework for exploring emission impacts of alternative future scenarios

2010 ◽  
Vol 3 (4) ◽  
pp. 2021-2050 ◽  
Author(s):  
D. H. Loughlin ◽  
W. G. Benjey ◽  
C. G. Nolte
Keyword(s):  
Growth Factors ◽  
Air Quality ◽  
Energy System ◽  
Air Pollutant ◽  
Population Projections ◽  
Pollutant Emissions ◽  
Emission Scenarios ◽  
Modeling Framework ◽  
Emission Growth ◽  
Carbon Dioxide Co2

Abstract. This article presents an approach for creating anthropogenic emission scenarios that can be used to simulate future regional air quality. The approach focuses on energy production and use since these are principal sources of air pollution. We use the MARKAL model to characterize alternative realizations of the US energy system through 2050. Emission growth factors are calculated for major energy system categories using MARKAL, while growth factors from non-energy sectors are based on economic and population projections. The SMOKE model uses these factors to grow a base-year 2002 inventory to future years through 2050. The approach is demonstrated for two emission scenarios: Scenario 1 extends current air regulations through 2050, while Scenario 2 applies a hypothetical policy that limits carbon dioxide (CO2) emissions from the energy system. Although both scenarios show significant reductions in air pollutant emissions through time, these reductions are more pronounced in Scenario 2, where the CO2 policy results in the adoption of technologies with lower emissions of both CO2 and traditional air pollutants. The methodology is expected to play an important role in investigations of linkages among emission drivers, climate and air quality by the U.S. EPA and others.

scholarly journals ESP v2.0: enhanced method for exploring emission impacts of future scenarios in the United States – addressing spatial allocation

2015 ◽  
Vol 8 (1) ◽  
pp. 263-300 ◽  
Author(s):  
L. Ran ◽  
D. H. Loughlin ◽  
D. Yang ◽  
Z. Adelman ◽  
B. H. Baek ◽  
...  
Keyword(s):  
Land Use ◽  
Growth Factors ◽  
Air Quality ◽  
Alternative Energy ◽  
Land Use Changes ◽  
The United States ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
County Level ◽  
Air Quality Model

Abstract. The Emission Scenario Projection (ESP) method produces future-year air pollutant emissions for mesoscale air quality modeling applications. We present ESP v2.0, which expands upon ESP v1.0 by spatially allocating future-year emissions to account for projected population and land use changes. In ESP v2.0, US Census Division-level emission growth factors are developed using an energy system model. Regional factors for population-related emissions are spatially disaggregated to the county level using population growth and migration projections. The county-level growth factors are then applied to grow a base-year emission inventory to the future. Spatial surrogates are updated to account for future population and land use changes, and these surrogates are used to map projected county-level emissions to a modeling grid for use within an air quality model. We evaluate ESP v2.0 by comparing US 12 km emissions for 2005 with projections for 2050. We also evaluate the individual and combined effects of county-level disaggregation and of updating spatial surrogates. Results suggest that the common practice of modeling future emissions without considering spatial redistribution over-predicts emissions in the urban core and under-predicts emissions in suburban and exurban areas. In addition to improving multi-decadal emission projections, a strength of ESP v2.0 is that it can be applied to assess the emissions and air quality implications of alternative energy, population and land use scenarios.

scholarly journals ESP v2.0: enhanced method for exploring emission impacts of future scenarios in the United States – addressing spatial allocation

2015 ◽  
Vol 8 (6) ◽  
pp. 1775-1787 ◽  
Author(s):  
L. Ran ◽  
D. H. Loughlin ◽  
D. Yang ◽  
Z. Adelman ◽  
B. H. Baek ◽  
...  
Keyword(s):  
Land Use ◽  
Growth Factors ◽  
Air Quality ◽  
Alternative Energy ◽  
Land Use Changes ◽  
The United States ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
County Level ◽  
Air Quality Model

Abstract. The Emission Scenario Projection (ESP) method produces future-year air pollutant emissions for mesoscale air quality modeling applications. We present ESP v2.0, which expands upon ESP v1.0 by spatially allocating future-year non-power sector emissions to account for projected population and land use changes. In ESP v2.0, US Census division-level emission growth factors are developed using an energy system model. Regional factors for population-related emissions are spatially disaggregated to the county level using population growth and migration projections. The county-level growth factors are then applied to grow a base-year emission inventory to the future. Spatial surrogates are updated to account for future population and land use changes, and these surrogates are used to map projected county-level emissions to a modeling grid for use within an air quality model. We evaluate ESP v2.0 by comparing US 12 km emissions for 2005 with projections for 2050. We also evaluate the individual and combined effects of county-level disaggregation and of updating spatial surrogates. Results suggest that the common practice of modeling future emissions without considering spatial redistribution over-predicts emissions in the urban core and under-predicts emissions in suburban and exurban areas. In addition to improving multi-decadal emission projections, a strength of ESP v2.0 is that it can be applied to assess the emissions and air quality implications of alternative energy, population and land use scenarios.

scholarly journals Assessment of the effect of air pollution controls on trends in shortwave radiation over the United States from 1995 through 2010 from multiple observation networks

2014 ◽  
Vol 14 (3) ◽  
pp. 1701-1715 ◽  
Author(s):  
C.-M. Gan ◽  
J. Pleim ◽  
R. Mathur ◽  
C. Hogrefe ◽  
C. N. Long ◽  
...  
Keyword(s):  
United States ◽  
Cloud Cover ◽  
The United States ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Clear Sky ◽  
Western Us ◽  
The Us ◽  
Clean Air ◽  
Increasing Trends

Abstract. Long-term data sets of all-sky and clear-sky downwelling shortwave (SW) radiation, cloud cover fraction, and aerosol optical depth (AOD) were analyzed together with surface concentrations from several networks (e.g., Surface Radiation Budget Network (SURFRAD), Clean Air Status and Trend Network (CASTNET), Interagency Monitoring of Protection Visual Environments (IMPROVE) and Atmospheric Radiation Measurement (ARM)) in the United States (US). Seven states with varying climatology were selected to better understand the effects of aerosols and clouds on SW radiation. This analysis aims to assess the effects of reductions in anthropogenic aerosol burden resulting from substantial reductions in emissions of sulfur dioxide (SO2) and nitrogen oxides (NOx) over the past 16 yr across the US, based on trends in SW radiation. The SO2 and NOx emission data show decreasing trends from 1995 to 2010, which indirectly validates the effects of the Clean Air Act (CAA) in the US. Meanwhile, the total column AOD and surface total PM2.5 observations also show decreasing trends in the eastern US but slightly increasing trends in the western US. Moreover, measured surface concentrations of several other pollutants (i.e., SO2, SO4 and NOx) have similar behavior to AOD and total PM2.5. Analysis of the observed data shows strong increasing trends in all-sky downwelling SW radiation with decreasing trends in cloud cover. However, since observations of both all-sky direct and diffuse SW radiation show increasing trends, there may be other factors contributing to the radiation trends in addition to the decreasing trends in overall cloud cover. To investigate the role of direct radiative effects of aerosols, clear-sky downwelling radiation is analyzed so that cloud effects are eliminated. However, similar increasing trends in clear-sky total and diffuse SW radiation are observed. While significantly decreasing trends in AOD and surface PM2.5 concentrations along with increasing SW radiation (both all-sky and clear-sky) in the eastern US during 1995–2010 imply the occurrence of direct aerosol mediated "brightening", the increasing trends of both all-sky and clear-sky diffuse SW radiation contradicts this conclusion since diffuse radiation would be expected to decrease as aerosols direct effects decrease and cloud cover decreases. After investigating several confounding factors, the increasing trend in clear-sky diffuse SW may be due to more high-level cirrus from increasing air traffic over the US. The clear-sky radiation observations in the western US also show indications of "brightening" even though the AOD, PM2.5 and surface concentration do not vary drastically. This outcome was not unexpected because the CAA controls were mainly aimed at reducing air pollutant emissions in the eastern US and air pollutant levels in the western US were much lower at the onset. This suggests other factors affect the "brightening" especially in the western US.

scholarly journals Contiguous United States wildland fire emission estimates during 2003–2015

2018 ◽  
Author(s):  
Shawn P. Urbanski ◽  
Matt C. Reeves ◽  
Rachel Corley ◽  
Robin Silverstein ◽  
Wei Min Hao
Keyword(s):  
United States ◽  
Air Pollution ◽  
Air Quality ◽  
Emission Inventory ◽  
Ambient Air ◽  
The United States ◽  
Pollutant Emissions ◽  
Burned Area ◽  
Large Set ◽  
Fuel Loading

Abstract. Wildfires are a major source of air pollutants in the United States. Wildfire smoke can trigger severe pollution episodes with substantial impacts on public health. In addition to acute episodes, wildfires can have a marginal effect on air quality at significant distances from the source presenting significant challenges to air regulators’ efforts to meet National Ambient Air Quality Standards. Improved emission estimates are needed to quantify the contribution of wildfires to air pollution and thereby inform decision making activities related to the control and regulation of anthropogenic air pollution sources. To address the need of air regulators and land managers for improved wildfire emission estimates we developed the Missoula Fire Lab Emission Inventory (MFLEI), a retrospective, daily wildfire emission inventory for the contiguous United States (CONUS). MFLEI was produced using multiple datasets of fire activity and burned area, a newly developed wildland fuels map and an updated emission factor database. Daily burned area is based on a combination of Monitoring Trends in Burn Severity (MTBS) data, Moderate Resolution Imaging Spectroradiometer (MODIS) burned area and active fire detection products, incident fire perimeters, and a spatial wildfire occurrence database. The fuel type classification map is a merger of a national forest type map, produced by the USDA Forest Service (USFS) Forest Inventory and Analysis (FIA) program and the Geospatial Technology and Applications Center (GTAC), with a shrub and grassland vegetation map developed by the USFS Missoula Forestry Sciences Laboratory. Forest fuel loading is from a fuel classification developed from a large set (> 26 000 sites) of FIA surface fuel measurements. Herbaceous fuel loading is estimated using site specific parameters with normalized differenced vegetation index from MODIS. Shrub fuel loading is quantified by applying numerous allometric equations linking stand structure and composition to biomass and fuels, with the structure and composition data derived from geospatial data layers of the LANDFIRE Project. MFLEI provides estimates of CONUS daily wildfire burned area, fuel consumption, and pollutant emissions at a 250 m × 250 m resolution for 2003–2015. A spatially aggregated emission product (10 km × 10 km, 1 d) with uncertainty estimates is included to provide a representation of emission uncertainties at a spatial scale pertinent to air quality modelling. MFLEI will be updated, with recent years, as the MTBS burned area product becomes available. The data associated with this article can be found at https://doi.org/10.2737/RDS-2017-0039.

scholarly journals Analysis of the Main Anthropogenic Sources’ Contribution to Pollutant Emissions in the Lazio Region, Italy

2021 ◽  
Vol 11 (17) ◽  
pp. 7936
Author(s):  
Gabriele Battista ◽  
Emanuele de Lieto Vollaro ◽  
Roberto de Lieto Vollaro
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Air Pollutants ◽  
Global Climate ◽  
Atmospheric Stability ◽  
Air Pollutant ◽  
Urban Traffic ◽  
Pollutant Emissions ◽  
Anthropogenic Sources ◽  
Lazio Region

Most cities worldwide suffer from serious air-quality problems, which have received increasing attention in the past decade. The most probable reason for the air-quality problems is the urban population growth, combined with a change in land use due to increasing urban areas. The emission of air pollutants is caused by different anthropogenic processes which can be categorized into the sources of urban traffic, industry, and domestic heating. Dispersion and dilution of air pollutants are strongly influenced by meteorological conditions, especially by wind direction, wind speed, turbulence, and atmospheric stability. With an increasing number of people living in cities, there is the need to examine the correlation between air pollution, local climate, and the effects these changes have on global climate. New interdisciplinary research studies are needed to increase our understanding of the interactions among these aspects. The aim is to analyze the pollutant condition in Rome and the other provinces of the Lazio region with qualitative and quantitative analysis, in order to understand which are the main pollutant sources and what is the correlation of habits of the population on air pollutant emissions.

scholarly journals Perspectives for Mitigation of CO2 Emission due to Development of Electromobility in Several Countries

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4127 ◽  
Author(s):  
Karol Tucki ◽  
Olga Orynycz ◽  
Mateusz Mitoraj-Wojtanek
Keyword(s):  
United States ◽  
European Union ◽  
Power Plants ◽  
The United States ◽  
Primary Energy ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
The European Union ◽  
Growth Data ◽  
Electric Cars

The creep trend method is used for the analysis of the development of electric car production in three regions: The United States, the European Union and Japan. Based on vehicle registration and population growth data for each year the creep trend method using historical data for the years 2007–2017 is applied for forecasting development up to 2030. Moreover, the original method for calculating the primary energy factor (PEF) was applied to the analysis of power engineering systems in the regions investigated. The assessment of the effects of electromobility development on air quality has been performed, reduction values for pollutant and greenhouse gas emissions have been determined, which was the main objective of this manuscript. Mitigation of air pollutant emissions, i.e., carbon dioxide (CO2), carbon monoxide (CO) and nitrogen oxides (NOx) was estimated and compared to the eventual expected increase of emissions from power plants due to an increase of the demand for electricity. It can be concluded that electricity powered cars along with appropriate choices of energetic resources as well as electricity distribution management will play the important role to achieve the sustainable energy economy. Based on the emission reduction projections resulting from the projected increase in the number of electric cars, (corrected) emissions will be avoided in 2030 in the amount of over 14,908,000 thousand tonnes CO2 in European Union, 3,786,000 thousand tonnes CO2 in United States and 111,683 thousand tonnes CO2 in Japan.

scholarly journals Linking agricultural crop management and air quality models for regional to national-scale nitrogen assessments

2012 ◽  
Vol 9 (10) ◽  
pp. 4023-4035 ◽  
Author(s):  
E. J. Cooter ◽  
J. O. Bash ◽  
V. Benson ◽  
L. Ran
Keyword(s):  
United States ◽  
Air Quality ◽  
Ambient Air ◽  
The United States ◽  
Fertilizer Application ◽  
Nitrogen Fertilizers ◽  
System Level ◽  
Agricultural Crop ◽  
Modeling Framework ◽  
Continental Scale

Abstract. While nitrogen (N) is an essential element for life, human population growth and demands for energy, transportation and food can lead to excess nitrogen in the environment. A modeling framework is described and implemented to promote a more integrated, process-based and system-level approach to the estimation of ammonia (NH3) emissions which result from the application of inorganic nitrogen fertilizers to agricultural soils in the United States. The United States Department of Agriculture (USDA) Environmental Policy Integrated Climate (EPIC) model is used to simulate plant demand-driven fertilizer applications to commercial cropland throughout the continental US. This information is coupled with a process-based air quality model to produce continental-scale NH3 emission estimates. Regional cropland NH3 emissions are driven by the timing and amount of inorganic NH3 fertilizer applied, soil processes, local meteorology, and ambient air concentrations. Initial fertilizer application often occurs when crops are planted. A state-level evaluation of EPIC-simulated, cumulative planted area compares well with similar USDA reported estimates. EPIC-annual, inorganic fertilizer application amounts also agree well with reported spatial patterns produced by others, but domain-wide the EPIC values are biased about 6% low. Preliminary application of the integrated fertilizer application and air quality modeling system produces a modified geospatial pattern of seasonal NH3 emissions that improves current simulations of observed atmospheric particle nitrate concentrations. This modeling framework provides a more dynamic, flexible, and spatially and temporally resolved estimate of NH3 emissions than previous factor-based NH3 inventories, and will facilitate evaluation of alternative nitrogen and air quality policy and adaptation strategies associated with future climate and land use changes.

scholarly journals The potential effects of climate change on air quality across the conterminous US at 2030 under three Representative Concentration Pathways

2018 ◽  
Vol 18 (20) ◽  
pp. 15471-15489 ◽  
Author(s):  
Christopher G. Nolte ◽  
Tanya L. Spero ◽  
Jared H. Bowden ◽  
Megan S. Mallard ◽  
Patrick D. Dolwick
Keyword(s):  
Climate Change ◽  
Air Quality ◽  
Regional Climate ◽  
Regional Scale ◽  
The United States ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Good Representation ◽  
Representative Concentration Pathways ◽  
Concentration Changes

Abstract. The potential impacts of climate change on regional ozone (O3) and fine particulate (PM2.5) air quality in the United States (US) are investigated by linking global climate simulations with regional-scale meteorological and chemical transport models. Regional climate at 2000 and at 2030 under three Representative Concentration Pathways (RCPs) is simulated by using the Weather Research and Forecasting (WRF) model to downscale 11-year time slices from the Community Earth System Model (CESM). The downscaled meteorology is then used with the Community Multiscale Air Quality (CMAQ) model to simulate air quality during each of these 11-year periods. The analysis isolates the future air quality differences arising from climate-driven changes in meteorological parameters and specific natural emissions sources that are strongly influenced by meteorology. Other factors that will affect future air quality, such as anthropogenic air pollutant emissions and chemical boundary conditions, are unchanged across the simulations. The regional climate fields represent historical daily maximum and daily minimum temperatures well, with mean biases of less than 2 K for most regions of the US and most seasons of the year and good representation of variability. Precipitation in the central and eastern US is well simulated for the historical period, with seasonal and annual biases generally less than 25 %, with positive biases exceeding 25 % in the western US throughout the year and in part of the eastern US during summer. Maximum daily 8 h ozone (MDA8 O3) is projected to increase during summer and autumn in the central and eastern US. The increase in summer mean MDA8 O3 is largest under RCP8.5, exceeding 4 ppb in some locations, with smaller seasonal mean increases of up to 2 ppb simulated during autumn and changes during spring generally less than 1 ppb. Increases are magnified at the upper end of the O3 distribution, particularly where projected increases in temperature are greater. Annual average PM2.5 concentration changes range from −1.0 to 1.0 µg m−3. Organic PM2.5 concentrations increase during summer and autumn due to increased biogenic emissions. Aerosol nitrate decreases during winter, accompanied by lesser decreases in ammonium and sulfate, due to warmer temperatures causing increased partitioning to the gas phase. Among meteorological factors examined to account for modeled changes in pollution, temperature and isoprene emissions are found to have the largest changes and the greatest impact on O3 concentrations.

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