Science Inventory

IMPACTS OF CHANGES IN LAND USE AND LAND COVER ON U.S. AIR QUALITY: DEVELOPMENT AND APPLICATION OF AN INTEGRATED CLIMATE-VEGETATION-CHEMISTRY MODELING SYSTEM

Impact/Purpose:

This project will investigate the potential impacts of changing land use and land cover on ozone and particulate matter (PM) air quality in the United States from 2010 to 2050. It will develop an integrated modeling system and quantify the contributing effects from changes in land cover due to climate change and increasing CO2 fertilization as well as those from anthropogenic land-use change. These changes are expected to affect air quality through various aspects including changes in the natural emissions of ozone and PM precursors and changes in the deposition of ozone and PM as well as their precursors. Some preliminary work has shown that these changes in the coming decades could have potentially large impacts on atmospheric chemistry and air quality.

Description:

(a). We have developed an integrated climate-vegetation-chemistry modeling system that incorporates a global chemical transport model model (GEOS-Chem CTM), a general circulation model (GISS GCM), and a global dynamic vegetation model (the LPJ model). This modeling system significantly improves our capability in understanding and quantifying the potential impacts on atmospheric chemistry and air quality from vegetation change associated with changes in climate and anthropogenic land use.
 
(b). We have improved some physical and chemical processes in the modeling system. For example, we have implemented new aging mechanisms for the hydrophobic-to-hydrophilic conversion of carbonaceous aerosols in the GEOS-Chem model – instead of the highly parameterized, global uniform fixed conversion lifetime of 1 day, the new scheme accounts for the effects from local atmospheric environment (such as humidity, concentration of ozone and other species). The hydrophobic-to-hydrophilic conversion rate of carbonaceous aerosols based on the new scheme show significant spatial and seasonal variations (Huang et al., 2013). This improvement has important implications for model simulations of aerosol (particulate matter) air quality.
 
(c). We have carried out a suite of model evaluations of the modeling system using various observational data. For example, by comparing against multiple datasets for carbonaceous aerosols around the world, we have found that the updated aging scheme discussed above can significantly improve the model simulation results for carbonaceous aerosols over some regions. We have also evaluated the model simulated present-day leaf area index (LAI) with observational data from the AVHRR satellite product. The LPJ model can generally reproduce the patterns for spatial and seasonal variations in LAI, but for some areas there are obvious discrepancies compared to AVHRR data products, which appears largely attributed to the fact that the LPJ model only resolves plant function types (PFTs) but not specific vegetation species, as is the case for the current generation of global vegetation models.
 
(d). We have applied the modeling system developed in this project to a suite of research questions, including:
 
d1) How Kudzu invasion in the southeastern United States is affecting U.S. air quality?
Kudzu is a widespread invasive plant in the southeastern United States. As a nitrogen-fixing legume, kudzu’s spread has the potential to increase nitric oxide (NO) emissions from soils as a consequence of increasing nitrogen inputs and cycling in soils. Using the modeling system we have developed, we investigated the consequences of kudzu invasion for atmospheric chemistry and air quality in the southeastern United States. Our study (Hickman et al., 2010) shows that extensive kudzu invasion leads to a 28% increase in the soil NO emissions. As a consequence, the average daily maximum 8 h ozone during summer time (June-August) is calculated to increase by up to 1.5 ppb, while the number of high ozone events (i.e., days with maximum 8 h ozone exceeding 70 ppb) is calculated to increase by up to 7 days each summer in some areas compared to the control scenario with no kudzu invasion.
 
d2) How the changing climate is affecting the global vegetation coverage?
We have simulated the impacts of climate change (the changes in atmospheric CO2 abundance, temperature, precipitation and cloud fraction, etc.) on the global distribution and evolution of various natural vegetation types (i.e., plant function types or PFTs). The natural vegetation are classified into nine PFTs, including tropical broadleaved evergreen tree, tropical broadleaved raingreen tree, temperate needleleaved evergreen tree, temperate broadleaved evergreen tree, temperate broadleaved summergreen tree, boreal needleleaved evergreen tree, boreal summergreen tree, C3 perennial grass, and C4 perennial grass. We find general increases in the leaf area index (LAI) with climate change except in the subtropical regions. Globally, we calculated a 40% increase in spatial coverage of temperate broadleaf trees and a 20% decrease in boreal needleleaf evergreen trees (Wu et al., 2012). The most significant changes in vegetation cover are found over the northern mid-latitudes, where we simulated a 60% increase in temperate broadleaf tree cover accompanied by a 30% decrease in boreal needleleaf evergreen tree cover and a 15% decrease in boreal summergreen tree cover.
 
d3) How the climate-driven vegetation changes affect atmospheric chemistry and air quality?
The changes in vegetation coverage and LAI could have significant effects on atmospheric chemistry and air quality by perturbing the biogenic emissions and also dry deposition of various atmospheric species. We have examined the changes in atmospheric composition, oxidizing capacity and air quality associated with 2000-2100 vegetation change driven by climate change and changes in atmospheric CO2 concentration. Our results indicate that climate and CO2 induced vegetation change between 2100 and 2000 would lead to substantial increases in ozone dry deposition associated with changes in the composition of temperate and boreal forests where conifer forests are replaced by those dominated by broadleaf tree types, as well as a CO2-driven increase in vegetation density. Climate-driven vegetation changes over the period 2000-2100 lead to general increases in biogenic isoprene emissions, globally by 10% in 2050 and 25% in 2100. General increases in monoterpene emissions are also calculated, although significant decreases are simulated over some northern mid-latitude regions where the needleleaf trees are being replaced by broadleaf trees. As a consequence, summer afternoon surface ozone concentrations are calculated to decrease by up to 10 ppb over large areas of the northern mid-latitudes. The climate-driven vegetation change would decrease the atmospheric oxidizing capacity (OH levels) by 2% and 4% by 2050 and 2100, respectively. Increases in biogenic VOC emissions also lead to higher concentrations of secondary organic aerosols (SOA), which increase globally by 10% in 2050 and 20% in 2100. Summertime surface concentrations of secondary organic aerosols are calculated to increase by up to 1 μg m-3 for large areas in Eurasia over the period of 2000-2100. The decreases in SOA concentrations over relatively small areas are associated with the decreases in biogenic monoterpene emissions (Wu et al., 2012).
 
d4) How the changes in anthropogenic land use affect air quality?
Similarly to the research question on impacts from natural vegetation change driven by climate change (as discussed above), we have investigated how the changes in anthropogenic land use would affect the atmospheric chemistry and air quality. We have implemented the 2000-2100 changes in anthropogenic land-use in our model system following the IPCC A1B scenario. Over the period 2000–2050, the agricultural land use is projected to decrease over some regions, including East Asia but increases over some others such as eastern United States, South Asia, and Central Africa, which is largely driven by changes in population, economic developments, energy supply and demand (e.g., energy crops). We find that Isoprene emissions generally decrease with increasing agricultural land use since crops are of the lowest isoprene emission rates among all the plant function types.
 
The decreases in isoprene emissions associated with anthropogenic land use change over east United States, South Asia and Central Africa more than compensate the increases in isoprene emissions associated with climate- and CO2-driven vegetation change. As a consequence, the global isoprene emissions for 2050 decrease by 5% compared to 2000. Associated with the 2000–2050 agricultural land use changes over South Asia and Central Africa, we find significant increases in surface ozone of up to 5 ppb in those regions, which appears driven by decreases in ozone deposition and isoprene emissions. In contrast, over east United States where there is relatively high NOx abundance, surface ozone decreases with decreasing isoprene emissions. The projected trends of agricultural land use for South Asia and Central Africa reverse after 2050; i.e., the total amount of land under cultivation decreases between 2050 and 2100, reflecting the projected human population maximum around 2050 (Nakicenovic and Swart, 2000). As a consequence, our model simulations over these regions show increasing isoprene emissions and decreasing surface ozone for the 2050–2100 period. Significant increases in agricultural land use are projected between 2050 and 2100 over the Amazon region where the isoprene would decrease leading to increasing surface ozone. Global total annual biogenic emissions are calculated to increase in 2100 compared to year 2000, with isoprene emissions up by 8% and mototerpenes up by 12%.
 
The changes in agricultural land use also have large effects on SOA. We find that when the agricultural land use change is accounted for, the global SOA burden in 2100 remains almost the same as 2000, in contrast to the large increase of 20% when only climate change and increasing CO2 abundance are considered. This implies that the projected expansion in agricultural land use between 2000 and 2100 lowers the global SOA burden by about 20%, which compensates for the effects of climate and CO2-driven changes in vegetation cover and composition. The model simulated changes in surface SOA concentrations due to changes in land use and land cover driven by the combined effects are shown. We find that the SOA increases by up to 1 μg m−3 by 2100 over the Eurasia region reflecting the changes in biogenic emissions of NMVOCs, in particular isoprene. Decreases in SOA concentrations, by up to 0.5 μg m−3 are calculated over the Amazon forest and eastern United States, which is driven by reduced biogenic isoprene and monoterpene emissions associated with increasing agricultural land use.
 
d5). Effects of CO2 inhibition on biogenic isoprene emission and implications for air quality.
The inhibition of biogenic isoprene emission by elevated atmospheric CO2 abundance as reported in the literature may significantly alter the sensitivity of air quality to global changes. However, this effect is not accounted for the standard version of GEOS-Chem we used in the climate-vegetation-chemistry modeling system. So we carried out further simulations under various combinations of 2000-to-2050 changes in climate, natural vegetation, and anthropogenic land use to examine the effect of the CO2 inhabitation on isoprene emissions and atmospheric composition (Tai et al., 2013). This part of the work is beyond what was proposed in the original proposal, but we have found the results from the “extra” work to be of relevance to the project. Our results indicate that the CO2 inhibition effect generally reduces the sensitivity of surface ozone to changes in climate and natural vegetation, resulting in smaller ozone and SOA increases in polluted regions than are projected by simulations without accounting this inhibition effect. Similar effects are found for the simulation results of secondary organic aerosols (Tai et al., 2013).
 
d6). Implications of land use/land cover change for wild fires
Changes in vegetation coverage (vegetation composition and density) could have significant implications for wild fires and the associated biomass burning emissions. Our simulations over the 2000-2050 period indicate significant increases in fire counts driven by changes in fire meteorology and vegetation composition (type) and density (expressed as leaf area index in the model) over most continental regions. This effect is also beyond the scope of researches planned in the original proposal, but given the important impacts of biomass burning emissions on atmospheric chemistry and air quality, we have found these results to be very interesting and may warrant some further investigation.

Record Details:

Record Type:PROJECT( ABSTRACT )
Start Date:07/01/2009
Completion Date:06/30/2012
Record ID: 250876