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ÀÌ ¿¬±¸¿¡¼­ ¿¬±¸ÀÚµéÀº 4°¡Áö ÀáÀçÀûÀÎ ±âÈÄ Á¤Ã¥µé-2°³ÀÇ ±âÈÄ ¼¼±Ý ½Ã³ª¸®¿À(CT1, CT2), ¼ö¼Û°ú ¿¡³ÊÁö ½Ã³ª¸®¿À(TE), ¹ÙÀÌ¿À¸Å½º ¿¡³ÊÁö ½Ã³ª¸®¿À(BE)-ÀÌ ¹Ì±¹ ³»ÀÇ ´ë±â Ç°Áú¿¡ ¹ÌÄ¡´Â ¿µÇâÀ» Æò°¡ÇÏ¿´´Ù. ´ë±â ¿À¿°¹°ÁúÀÇ ³óµµ¸¦ ½Ã¹Ä·¹À̼ÇÇϱâ À§ÇÏ¿© È­ÇÐ Àü´Þ ¸ðµ¨(Chemical transport model, CTM)À» »ç¿ëÇÏ¿´°í ÃÖ½ÅÀÇ ±âÈÄ ¸ð»ç ¸ðµ¨°ú °³¼±µÈ ¹èÃ⠸𵨸µµµ ÀÌ¿ëÇÏ¿´´Ù.

¿¬±¸ÆÀÀº ¹Ì±¹ Àü¿ªÀÇ Áö¿ª ¼öÁرîÁö ±âÈÄ º¯È­¸¦ Àü»ê ¸ð»çÇÏ°í ¹èÃ⠽󪸮¿ÀµéÀ» °³¹ßÇϱâ À§ÇÏ¿© EPA ÀÚ·á(EPA US 9-region national database, EPAUS9r)¿Í ¸¶Ä®(MARKet Allocation, MARKAL) ¿¡³ÊÁö ½Ã½ºÅÛ ¸ðµ¨À» ÀÌ¿ëÇÏ¿´´Ù. ¸¶Ä® ¿¡³ÊÁö ½Ã½ºÅÛ ¸ðµ¨Àº ÁÖ°Å, »ó¾÷, »ê¾÷, ¼ö¼Û ºÐ¾ßµéÀÇ Áö¿ªÀû ±â¹ÝÀÇ ¿¡³ÊÁö ¼­ºñ½ºµéÀÇ ¼ö¿ä¸¦ ¸¸Á·½ÃÅ°´Â ÃÖ¼Ò ºñ¿ëÀ» Á¦°øÇϱâ À§ÇØ ÀÌ¿ë°¡´ÉÇÑ ±â¼úµé·ÎºÎÅÍ ¼±ÅÃÇÑ´Ù. ¹Ì±¹ ³»ÀÇ ÀÌ»êȭź¼Ò Àú°¨ Àü·«µéÀÇ ¿µÇâÀ» Á¶»çÇϱâ À§ÇØ ¸¶Ä® ¸ðµ¨À» ÀÌ¿ëÇÑ ÃÖÃÊÀÇ »ç·Ê·Î ¿¬±¸ÆÀÀº ¾Ë°í ÀÖ´Ù.

¿¬±¸ÆÀÀº CMAQ(community multiscale air quality model) ¸ðµ¨À» ÀÌ¿ëÇÏ¿© ¼­·Î ´Ù¸¥ Á¤Ã¥µé·Î ÀÎÇÑ ¿À¿°¹°ÀÇ º¯È­°¡ ´ë±â Ç°Áú¿¡ ¹ÌÄ¡´Â ¿µÇâÀ» ºÐ¼®ÇÏ¿´´Ù. ¹Ì·¡ÀÇ ±â»ó Á¤º¸´Â GISS(Goddard Institute for Space Studies ModelE2) ¸ðµ¨·ÎºÎÅÍ WRF(Weather Research Forecasting) ¸ðµ¨À» ÀÌ¿ëÇÏ¿© Áö¿ª ±Ô¸ð±îÁö È®´ëÇÏ¿© ÀÌ¿ëÇÏ¿´´Ù. GISS ModelE2´Â 2006~2010³â°ú 2048~2052³âÀÇ Áö¿ª ±âÈÄ ¸ðµ¨ÀÇ Ãʱâ Á¶°Ç ¹× °æ°è Á¶°ÇÀ» Á¦°øÇÑ´Ù.

CT1°ú CT2 ½Ã³ª¸®¿À´Â ź¼Ò¼¼ÀÇ ÃÖ´ë¿Í ÃÖÀú¸¦ ´ëÇ¥Çϵµ·Ï ¼³Á¤µÇ¾ú´Ù. CT1Àº 2015³â ÀÌ»êȭź¼Ò 1Åæ´ç 20ºÒ¿¡¼­ 2050³â 1Åæ´ç 90ºÒÀÌ´Ù. CT2´Â 2020³â 50ºÒ¿¡¼­ 2050³â 1,400ºÒÀÌ´Ù. TE´Â ¼ö¼Û ºÐ¾ß¿¡¼­ 70%ÀÇ ¿Â½Ç°¡½º ¹èÃâ °¨¼Ò¿Í »õ·Î¿î õ¿¬°¡½º º¹ÇÕ ¹ßÀüÀÇ ¹èÃâ°ú ºñ½ÁÇÏ°Ô ÀÌ»êȭź¼Ò ¹èÃâ ¼Óµµ´Â 880 lb/MWh, ÀÌ»êȭȲÀº 0.0058 lb/MWh, Áú¼Ò»êÈ­¹°Àº 0.14 lb/MWh·Î °¡Á¤ÇÏ¿´´Ù. Àü·Â ºÐ¾ßÀÇ Ãß°¡ÀûÀÎ Á¦ÇÑÀº Àü±â ÀÚµ¿Â÷ÀÇ Áõ°¡¿¡ µû¶ó Àü·Â »ý»êÀ¸·ÎºÎÅÍ Áõ°¡µÈ ¹èÃâ·®À» °¨¼Ò½ÃÅ°±â À§ÇÔÀÌ´Ù. BE´Â ¸ðµç ÀÌ¿ë°¡´ÉÇÑ ¹ÙÀÌ¿À¸Å½º°¡ ¿¡³ÊÁö ºÐ¾ß¿¡¼­ »ç¿ëµÇ´Â °ÍÀ¸·Î °¡Á¤ÇÏ¿´´Ù.

ÁÖ¿ä ¿¬±¸ °á°ú´Â ´ÙÀ½°ú °°´Ù.
- CT1°ú BE Á¤Ã¥µéÀº 2050³â ±âÁØ ÄÉÀ̽º¿Í ºñ±³ÇÏ¿© PM2.5ÀÇ ³óµµ°¡ Áõ°¡ÇÏ¿© ´ë±â Ç°ÁúÀ» ¾ÇÈ­½Ãų ¼ö ÀÖ´Ù. CT2¿Í TE´Â ´ë±â Ç°ÁúÀ» Çâ»ó½Ãų °ÍÀÌ´Ù.
- »ó´ëÀûÀ¸·Î °ø°ÝÀûÀΠź¼Ò ¼¼±Ý Á¤Ã¥ÀÇ ½ÃÇàÀº ¹è¿¬ ŻȲ °øÁ¤°ú ź¼Ò Æ÷Áý ¹× ÀúÀå ±â¼úÀÇ È®´ë·Î ÀÎÇؼ­ PM2.5ÀÇ Çâ»óÀ» À̲ø ¼ö ÀÖ´Ù. ±×·¯³ª Áú¼Ò »êÈ­¹° ¹èÃâÀÇ Áõ°¡·Î ÀÎÇؼ­ ´ë±â Ç°ÁúÀÇ ÀúÇ϶ó´Â ¸ð¼øµÇ´Â °á°ú°¡ ¹ß»ýÇÑ´Ù.
- TE´Â ÀÚµ¿Â÷ÀÇ Áú¼Ò»êÈ­¹° ¹èÃâÀ» Àú°¨½ÃÄÑ ¿ÀÁ¸ ³óµµ¸¦ °¨¼Ò½ÃŲ´Ù. ÀÌ ½Ã³ª¸®¿À´Â ¹Ì±¹ ´ëºÎºÐÀÇ PM2.5µµ Àú°¨½ÃŲ´Ù. ±×·¯³ª ¿¬·áÀÇ Àüȯ°ú °ü·ÃµÈ PM2.5, OC, ECÀÇ Áõ°¡´Â ¹Ì±¹ ÁÖ¿ä µµ½Ãµé¿¡¼­ PM2.5¸¦ Áõ°¡½ÃŲ´Ù.
- ºñ·Ï TE ½Ã³ª¸®¿À°¡ À¯ÀÏÇÏ°Ô ½ÇÇöµÈ ¹èÃâ Àú°¨ Á¤Ã¥ÀÌÁö¸¸ ¸ðµ¨ÀÇ ÇÑ°è°¡ Á¸ÀçÇϸç ÀÌ·Î ÀÎÇؼ­ ¿¬·á ÀüȯÀÇ ¿µÇâÀÌ ´ë±â Ç°Áú¿¡ ¿µÇâÀ» ³¢Ä¡°Ô µÈ´Ù.
 
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Georgia Tech study projects potential mixed impacts of climate change policies on air quality

Results of a study by a team from Georgia Tech and their colleagues at NASA Goddard Institute for Space Studies and Northeast States for Coordinated Air Use Management show that national CO2emissions reductions strategies will play an important role in impacting air quality over the US. The results also show that CO2 emission reduction policies can have mixed positive and negative impacts on air quality. A paper on the study is published in the ACS journal Environmental Science & Technology.

In the study, the researchers assessed the impact of four potential climate mitigation policies—two climate tax scenarios (CT1 and CT2); a combined transportation and energy scenario (TE); a biomass energy (BE) scenario; plus a reference case—on air quality in the US in 2050 using a chemical transport model (CTM) to simulate air pollutant concentrations and applying recent climate downscaling and emissions modeling advancements.
 
•They used the EPA US 9-region national database (EPAUS9r) with the MARKet Allocation (MARKAL) energy system model to develop emissions scenarios and spectral nudging to downscale global climate to the regional scale over the US. The MARKAL energy system model selects from available technologies to provide the least-cost path that satisfies specified demands in the residential, commercial, industrial and transportation sectors for regionally based energy services.

To the team¡¯s knowledge, this is the first study to use MARKAL to investigate the effect of CO2 reduction strategies on air quality in the US.

•They used CMAQ (community multiscale air quality model) to analyze the impact of emissions changes from the different policies on regional air quality in 2050 in the contiguous United States.

•Future meteorology was downscaled from the Goddard Institute for Space Studies (GISS) ModelE2 General Circulation Model (GCM) to the regional scale using the Weather Research Forecasting (WRF) model with spectral nudging. The GISS ModelE2 provides the initial and boundary conditions to a regional climate model for the years 2006−2010 and 2048−2052.

The CT1 and CT2 scenarios, applied economy-wide and in nominal dollars, are intended to represent an upper and lower end of carbon tax options. CT1 begins in 2015 at $20 per ton CO2 and reaches $90 per ton in 2050. The more aggressive CT2 begins in 2020 at $50 per ton and reaches $1,400 per ton in 2050.

TE assumes a 70% greenhouse gas reduction from transportation sectors and an additional electricity sector emission rate limit of 880 lb/MWh for CO2, 0.0058 lb/MWh for SO2 and 0.14 lb/MWh for NOx—similar to that of new combined cycle natural gas power plants. The purpose of the additional limit on the electricity sector is to mitigate increased emissions from electric generation due to increased use of electric vehicles.

BE assumes that all available biomass will be used in the energy sector.

Among their findings were:
•Policies CT1 and BE can lead to worse air quality in the form of increased PM2.5 concentrations compared to the 2050 reference case and the two policies that lead to improvements compared to the 2050 reference case (CT2 and TE).

•The implementation of relatively aggressive carbon taxes can lead to improvements in PM2.5 air quality compared to the 2050 reference case due to the increased incentives to install FGD (flue gas desulfurization) process technologies and CCS (carbon capture and storage) technologies. However, there is an air quality trade-off because NOx emissions increase in states not subject to the Clean Air Interstate Rule¡¯s NOx cap, and O3 increases as a result.

•TE leads to reduced emissions of mobile source NOx, thus reducing O3 levels. This scenario leads to reduced PM2.5 concentrations over most of the US. However, increased primary PM2.5, OC and EC emissions associated with fuel switching leads to increased annual ambient PM2.5 in many major US cities.
 
Although the TE scenario is only one realization of emissions, which is subject to the limitations of the models, the results stress the impact of fuel switching in the energy market on air quality and the differences in air quality responses at different spatial scales (i.e., regional vs urban).
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