Air quality monitoring remains a challenge in areas lacking or having sparse federal monitoring infrastructure, posing significant barriers to public health research. This study demonstrates the usage of low-cost sensors in addressing gaps in air quality monitoring, source attribution, and health risk assessment in a Brownsville, TX neighborhood impacted by emissions from a barite and celestite mineral processing unit. PM2.5 concentrations were measured using PurpleAir sensors deployed across three residential locations, with the site nearest to the processing unit recording a 24-h averaged PM2.5 concentration of 25.12 μg/m3—approximately 2.79 times higher than the nearest Texas Commission of Environmental Quality (TCEQ) CAMS (Continuous Ambient Monitoring Station) site. Indoor air quality was also evaluated in two of the residential units to characterize the influence of outdoor pollution on indoor microenvironment. The local wind data was used to conduct source attribution, and the results suggested that the mineral processing entity located south of the neighborhood was the likely source of particulate pollution in this middle-income neighborhood. A health risk assessment for PM2.5 exposure was conducted, and the results indicate a hazard quotient level below unity, suggesting low-risk non-carcinogenic effects on the community. This study underscores the pivotal role of low-cost sensors in generating localized air quality data, and their potential to support ameliorative evidence-based interventions.

Formaldehyde (HCHO) plays significant roles in atmospheric chemistry and human health, but limited surface data hinders our understanding of its sources and variability. This study compiles ambient HCHO data from U.S. air monitoring sites over the past 36 years. Trend analysis shows that HCHO concentrations have declined modestly in urban areas; however, widespread downward trends are absent across most regions, despite substantial reductions in NO x emissions over recent decades. This persistence is explained by strong exponential dependence of HCHO on temperature, with temperature alone accounting for approximately 50% of HCHO variability. The observed temperature dependence closely resembles that of precursor biogenic volatile organic compound emissions rather than chemical rate constants. In addition, wildfire smoke enhances HCHO concentrations by 53% on average. We further employed ensemble and deep machine learning models to predict HCHO using routinely measured variables, with the eXtreme Gradient Boosting (XGBoost) model achieving the best performance. Combining XGBoost with explainable machine learning reveals that temperature is the dominant predictor, followed by particulate matter, with NO x as a relevant contributor. These models capture average HCHO variation at regional scales, which enables estimation of HCHO concentration in areas lacking monitoring data and prediction of its future trends under climate warming scenarios.

In recent years the area of wildland fires has increased in the US and many regions have experienced extremely poor air quality due to smoke. We combine data for PM2.5 (particulate matter with diameter <2.5 μm) with a satellite product to identify smoke-influenced days and associated PM2.5 for 2019-2024 from air quality monitors covering 85% of the US population. Averaged across the US, smoke is present on 14.2% of all days and increases the daily mean PM2.5 concentration on these days by 6.9 μg m-3, with a maximum of 687 μg m-3. For each region, we estimate the contribution of smoke PM2.5 to emergency department visits (EDV) for asthma. While rural regions in the western US have the highest contributions of smoke to the PM2.5 concentrations, larger metropolitan areas have a greater number of EDV from smoke due to greater populations. We next consider the impacts of smoke on compliance with the US annual standard for PM2.5 (9.0 μg m-3). Using data for 2022-2024, out of 807 of monitors studied 174 would not meet the standard, but in the absence of smoke, only 57 of these would not meet the standard. While observed annual PM2.5 has shown no significant change over the past 6 years, we find a significant decline in PM2.5 when the smoke contributions are excluded.

The 18th International Congress on Combustion Byproducts and Human Health Effects (PIC2024) was held in Durham, North Carolina on May 20th-22nd, 2024. The overall goal of this conference, typically organized biannually, is to bring together scholars and researchers from diverse fields including chemistry, toxicology, engineering, epidemiology, and occupational and public health, and from various sectors (academia, government, and industry) to engage on new and emerging issues related to combustion processes, human exposure, and potential health risks. The theme of the 18th International Congress was "Fire Emissions & Community Impacts at the Wildland Urban Interface and Disaster Sites." Specific focus and emphasis was placed on new research concerning wildland fires, climate change, firefighter exposures, and data collected following the East Palestine train derailment in Ohio. Plenary speakers included Drs. Toddi Steelman (Duke University), Daniel Jaffe (University of Washington), Miriam Calkins (NIOSH), Mark Durno (U.S. EPA), and Linda S. Birnbaum (NIEHS, retired). This report summarizes the primary research highlighted during the conference, major discussion points raised, and areas recommended for future research.

Understanding baseline O3 is important as it defines the fraction of O3 coming from global sources and not subject to local control. We report the occurrence and sources of high baseline ozone days, defined as a day where the daily maximum 8 h average (MDA8) exceeds 70 ppb, as observed at the Mount Bachelor Observatory (MBO, 2.8 km asl) in Central Oregon from 2004 to 2022. We used various indicators and enhancement ratios to categorize each high-O3 day: carbon monoxide (CO), aerosol scattering, the water vapor mixing ratio (WV), the aerosol scattering-to-CO ratio, backward trajectories, and the NOAA Hazard Mapping System Fire and Smoke maps. Using these, we identified four causes of high-O3 days at the MBO: Upper Troposphere/Lower Stratosphere intrusions (UTLS), Asian long-range transport (ALRT), a mixed UTLS/ALRT category, and events enhanced by wildfire emissions. Wildfire sources were further divided into two categories: smoke transported in the boundary layer to the MBO and smoke transported in the free troposphere from more distant fires. Over the 19-year period, 167 high-ozone days were identified, with an increasing fraction due to contributions from wildfire emissions and a decreasing fraction of ALRT events. We further evaluated trends in the O3 and CO data distributions by season. For O3, we found an overall increase in the mean and median values of 2.2 and 1.5 ppb, respectively, from the earliest part of the record (2004–2013) compared to the later part (2014–2022), but no significant linear trends in any season. For CO, we found a significant positive trend in the summer 95th percentiles, associated with increasing fires in the Western U.S., and a strong negative trend in the springtime values at all percentiles (1.6% yr−1 for 50th percentile). This decline was likely associated with decreasing emissions from East Asia. Overall, our findings are consistent with the positive trend in wildfires in the Western United States and the efforts in Asia to decrease emissions. This work demonstrates the changing influence of these two source categories on global background O3 and CO.

Gas stoves and cooking are significant sources of indoor pollution. Using a combination of regulatory and calibrated low-cost sensors (LCS) we measured NO, NO2, CO and CO2 emission rates (g hr(-1)) and emission factors (g J(-1)) from a natural-gas stove and oven. The emission rates for gaseous pollutants were significantly higher, by factors of 2.6-29, from the oven compared to the stove for every pollutant measured. To evaluate the indoor air concentrations, we used a calibrated low-cost sensor (TSI Inc, AirAssure) to examine indoor concentration of CO, CO2, NO2 and PM2.5 for one month in one U.S. home with a gas stove during normal activities, including cooking. Indoor concentrations of one or more pollutants exceeded the U.S. EPA's Air Quality Index (AQI) level of 100 (for CO, NO2, and PM2.5) or 2000 ppm (for CO2) for an average of 99 min per day. The AirAssure, with only the manufacturer's calibration, was an excellent indicator of times when indoor concentrations of CO, CO2, and NO2 exceeded these reference levels. Without in-situ calibration, the AirAssure underestimated in-home PM2.5 concentrations. After in-situ calibration, the AirAssure correctly identified 1-min periods when the AQI was >100 85% of the time (up from 46% of the time without calibration).

Tropospheric ozone (O3) is one of the major air pollutants in China. This paper examined the O3 concentration in 16 important Chinese cities including 7 megacities and developed a statistical model named Generalized Additive Model (GAM) as a function of different factors to estimate the maximum daily 8 h (MDA8) O3 during 2014–2016 and how the leading factors impacts O3. We found that: (1) Three seasonal patterns of O3 have been summarized in the spatial-temporal analysis and summer is the highest season in most of the cities. (2) GAM performs very well that it can capture 43–90

Aerosol and Air Quality Research is taking an editorial stand with regards to outdated data analysis methods, specifically principal component analysis (PCA) and related techniques and enrichment factors (EF). In both cases, they have been replaced with more quantitative data analytical tools that provide much greater information on sources of variation in the data. Enrichment factors were first used in the 1960s when we basically did not have computers. It was a simple way of using double ratios to see if an element were substantially enriched over crustal abundances that had been reported by one of several authors. However, the information is quite crude since it simply says that the element is higher than typical crustal values and does not account for local variations in elemental abundances. When we now have the capabilities to look at correlations, statistical assessment of differences in means or medians, etc., we should provide appropriate quantitative estimates of significance of differences among samples. In the case of PCA and other eigenvector-based methods, it has been shown by Lawson and Hanson (1974) and Malinowski (2002) that an eigenvector analysis is an unweighted least-square fit to the data. Such fits are going to create problems with heteroskedastic data such as is commonly encountered in atmospheric measurements. Typically, the measurement uncertainties are proportional to the measured values rather than a fixed value for all of the measurements (homoscedastic data). Thus, unweighted least squares fits will not provide the best estimators of the parameters of interest. PCA also typically uses a default of subtracting the mean value from the data points and scales them by the variance such that it apportions the variance rather than the variation of the actual measured concentrations. Although methods like Target-Transformation Factor Analysis (TTFA) avoided subtracting the mean, it still suffers from the problem of improper (absence of) data point weights. In the 1970s when mainframe computing power was less than what we carry in our pockets as a telephone, it was necessary to use simplifying methods like eigenvector decompositions to be able to obtain results in a reasonable time. However, we have long since gained sufficient computing power in personal computers to be able to perform full, explicit least-squares fits with proper data weighting. Factor analysis tools like non-negative constrained alternating least square (Tauler et al., 1993, 1994), positive matrix factorization (Paatero and Tapper, 1993, 1994), and non-negative least squares (e.g., Lee and Seung, 1999; Camp, 2019) have been available for more than 25 years that allow proper weighting of individual data points. Software for these techniques are readily available for download: MCR-ALS (http://www.mcrals.info), PMF (https://www.epa.gov/air-research/positive-matrix-factorization-model-environmental-data-analyses; https://www.psi.ch/lac/sofi-sourcefinder), and NNLS (https://pages.nist.gov/pyMCR/; https://cran.r-project.org/package=NMF) While PCA has value as a preliminary screening tool (e.g., Roscoe et al., 1982) and as an exploratory tool, but it should not be used as a receptor model. For quantitative analyses that form the basis of conclusions in a paper, we strongly recommend more modern and statistically appropriate methods be used.

In this study we evaluate the recently upgraded aethalometer (AE33) and the newly released tricolor absorption photometer (TAP) with respect to their response to wildfire aerosol plumes during their deployment at the Mount Bachelor Observatory (MBO; 2763 m a.s.l.) in central Oregon, USA, during the summer of 2016. While both instruments use similar methodology (i.e., light extinction through an aerosol-laden filter), each has a unique set of correction schemes to address artifacts originating from filter loading, scattering from captured aerosol particles, and multiple scattering effects of the filter fibers. We also utilize a Single Particle Soot Photometer (SP2) to determine refractory black carbon (rBC) in these air masses. In addition to comparing the AE33 filter-loading correction methodology to previously published aethalometer correction schemes, we also compare the AE33 to the correction schemes used for the TAP and evaluate the degree to which the different correction factors influence the derived absorption Ångström exponents (AAE) and mass absorption cross sections (MACs). We find that while the different correction factors for either the AE33 or TAP do exert an influence on the derived MACs, AAEs exhibit the most sensitivity to the correction schemes. Our study finds that using the AE33 manufacturer's recommended settings results in aerosol light absorption coefficients that are 3.4 to 4 times greater than the aerosol light absorption coefficients reported by the TAP. We calculated a correction factor (Cf) of 4.35 for the AE33 by normalizing the AE33 to match the TAP. The uncorrected AE33 also gives equivalent black carbon (eBC) values that are approximately 2 times the rBC measured by the SP2 instrument. We also find that biomass burning aerosols result in significant MAC enhancements, particularly at lower wavelengths, which is attributable to brown carbon (BrC).

We investigated the impact of wildfires on maximum daily 8-hr average ozone concentrations (MDA8 O3) at four sites in Salt Lake City (SLC), Utah for May to September for 2006-2022. Smoke days, which were identified by a combination of overhead satellite smoke detection and surface PM2.5 data and accounted for approximately 9% of the total number of days, exhibited O3 levels 6.8 to 8.9 ppb higher than no-smoke days and were predominantly characterized by high daily maximum temperatures and low relative humidity. A Generalized Additive Model (GAM) was developed to quantify the impact of wildfire contributions to O3. The GAM, which provides smooth functions that make the interpretation of relationships more intuitive, employed 17 predictors and demonstrated reliable performance in various evaluation metrics. The mean of the residuals for all sites was approximately zero for the training and cross-validation data and 5.1 ppb for smoke days. We developed three approaches to estimate the contribution of smoke to O3 from the model residuals. These generate a minimum and maximum contribution for each smoke day. The average of the minimum and maximum wildfire contributions to O3 for the SLC sites was 5.1 and 8.5 ppb, respectively. Between 2006 and 2022, an increasing trend in the wildfire contributions to O3 was observed in SLC. Moreover, trends of the fourth-highest MDA8 O3 before and after removing the wildfire contributions to O3 at the SLC Hawthorne site in 2006-2022 were quite different. Whereas the unadjusted data do not meet the current O3 standard, after removing the contributions from wildfires the SLC region is close to achieving levels that are consistent with meeting the O3 standard. We also found that the wildfire contribution during smoke days was particularly high under conditions of high temperature, high PM2.5 concentration, and low cloud fraction.Implications: In this study, we quantified the impact of wildfires on maximum daily 8-hr average ozone concentrations (MDA8 O3) in Salt Lake City, Utah, using a Generalized Additive Model (GAM). The GAM results demonstrate the importance of wildfires as contributors to O3 air pollution. Our results suggest that states could use the GAM approach to assist in quantifying the wildfire contribution to MDA8 O3 under the U.S. EPA exceptional events rule. These findings also highlight the need for strategies to manage wildfires and their subsequent impacts on air quality in an era of climate warming.

We report the discovery of an extreme galaxy overdensity at z = 5.4 in the GOODS-S field using James Webb Space Telescope (JWST)/NIRCam imaging from JADES and JEMS alongside JWST/NIRCam wide-field slitless spectroscopy from FRESCO. We identified potential members of the overdensity using Hubble Space Telescope+JWST photometry spanning λ = 0.4–5.0 μ m. These data provide accurate and well-constrained photometric redshifts down to m ≈ 29–30 mag. We subsequently confirmed N = 81 galaxies at 5.2 < z < 5.5 using JWST slitless spectroscopy over λ = 3.9–5.0 μ m through a targeted line search for H α around the best-fit photometric redshift. We verified that N = 42 of these galaxies reside in the field, while N = 39 galaxies reside in a density around ∼10 times that of a random volume. Stellar populations for these galaxies were inferred from the photometry and used to construct the star-forming main sequence, where protocluster members appeared more massive and exhibited earlier star formation (and thus older stellar populations) when compared to their field galaxy counterparts. We estimate the total halo mass of this large-scale structure to be 12.6 ≲ log 10 M halo / M ⊙ ≲ 12.8 using an empirical stellar mass to halo mass relation, which is likely an underestimate as a result of incompleteness. Our discovery demonstrates the power of JWST at constraining dark matter halo assembly and galaxy formation at very early cosmic times.

IGRINS-2 is a high-resolution, near-infrared spectrograph developed by Korea Astronomy and Space Science Institute (KASI) for Gemini Observatory as a new facility instrument. It provides spectral resolving power of similar to 45,000 and a simultaneous wavelength coverage of 1.49-2.46 mu m. IGRINS-2 is an improved version of IGRINS (Immersion GRating INfrared Spectrometer) with minor optical and mechanical design changes, new detector controllers, and operating software to be fully integrated into Gemini operating systems. Since the project began in early 2020, project key milestones including assembly and pre-delivery performance verification were completed, and delivered to Gemini North in early September, 2023. After the successful post-delivery verification and telescope integration, the first light spectra were acquired in October 2023. We present design changes and upgrades made to IGRINS-2 from the original IGRINS, assembly and alignment procedures, and verification of the instrument requirements. We also report the preliminary results of the system performance tests.

Peroxyacetyl nitrate (PAN) is produced in the atmosphere by photochemical oxidation of non-methane volatile organic compounds in the presence of nitrogen oxides (NOx), and it can be transported over long distances at cold temperatures before decomposing thermally to release NOx in the remote troposphere. It is both a tracer and a precursor for transpacific ozone pollution transported from East Asia to North America. Here, we directly demonstrate this transport with PAN satellite observations from the infrared atmospheric sounding interferometer (IASI). We reprocess the IASI PAN retrievals by replacing the constant prior vertical profile with vertical shape factors from the GEOS-Chem model that capture the contrasting shapes observed from aircraft over South Korea (KORUS-AQ) and the North Pacific (ATom). The reprocessed IASI PAN observations show maximum transpacific transport of East Asian pollution in spring, with events over the Northeast Pacific offshore from the Western US associated in GEOS-Chem with elevated ozone in the lower free troposphere. However, these events increase surface ozone in the US by less than 1 ppbv because the East Asian pollution mainly remains offshore as it circulates the Pacific High.

During the summer of 2012 and 2013, we measured carbon monoxide (CO), carbon dioxide (CO2), ozone (O3), nitrogen oxides (NOx), reactive nitrogen (NOy), peroxyacetyl nitrate (PAN), aerosol scattering (σsp) and absorption, elemental and organic carbon (EC and OC), and aerosol chemistry at the Mount Bachelor Observatory (2.8 km above sea level, Oregon, US). Here we analyze 23 of the individual plumes from regional wildfires to better understand production and loss of aerosols and gaseous species. We also developed a new method to calculate enhancement ratios and Modified Combustion Efficiency (MCE), which takes into account possible changes in background concentrations during transport. We compared this new method to existing methods for calculating enhancement ratios. The MCE values ranged from 0.79–0.98, ΔO3/ΔCO ranged from 0.01–0.07 ppbv ppbv−1, Δσsp/ΔCO ranged from 0.23–1.32 Mm−1 (at STP) ppbv−1, ΔNOy/ΔCO ranged from 2.89–12.82 pptv ppbv−1, and ΔPAN/ΔCO ranged from 1.46–6.25 pptv ppbv−1. A comparison of three different methods to calculate enhancement ratios (ER) showed that the methods generally resulted in similar Δσsp/ΔCO, ΔNOy/ΔCO, and ΔPAN/ΔCO; however, there was a significant bias between the methods when calculating ΔO3/ΔCO due to the small absolute enhancement of O3 in the plumes. The ΔO3/ΔCO ERs calculated using two common methods were biased low ( 20–30

Anthropogenic activities emit ~2000 Mg yr-1 of the toxic pollutant mercury (Hg) into the atmosphere, leading to long-range transport and deposition to remote ecosystems. Global anthropogenic emissions inventories report increases in Northern Hemispheric (NH) Hg emissions during the last three decades, in contradiction with the observed decline in atmospheric Hg concentrations at NH measurement stations. Many factors can obscure the link between anthropogenic emissions and atmospheric Hg concentrations, including trends in the re-emissions of previously released anthropogenic (“legacy”) Hg, atmospheric sink variability, and spatial heterogeneity of monitoring data. Here we assess the observed trends in gaseous elemental mercury (Hg0) in the NH and apply biogeochemical box modeling and chemical transport modeling to understand the trend drivers. Using linear mixed effects modeling of observational data from 51 stations, we find negative Hg0 trends in most NH regions, with an overall trend for 2005–2020 of ‑0.011 ± 0.006 ng m-3 yr-1 (±2 SD). In contrast to existing emission inventories, our modelling analysis suggests that NH anthropogenic emissions must have declined by at least 140 Mg yr-1 between the years 2005 and 2020 to be consistent with observed trends. Faster declines in 95th percentile Hg0 values than median values in Europe, North America, and East Asian measurement stations corroborate that the likely cause is a decline in nearby anthropogenic emissions rather than background legacy re-emissions. Our results are relevant for evaluating the effectiveness of the Minamata Convention on Mercury, demonstrating that existing emissions inventories are incompatible with the observed Hg0 declines.

In this study we investigate the use of ΔPM2.5/ΔCO and ΔNOy/ΔCO normalized enhancement ratios (NERs) in identifying wildfire (WF) smoke events in urban areas. Nine urban ambient monitoring sites with adequate CO, PM2.5, and/or NOy measurements were selected for this study. We investigated if WF events could be distinguished from general urban emissions by comparing NERs for wildfires with NERs calculated using yearly ambient data, which we call the ambient enhancement ratios (AERs). The PM2.5/CO and NOy/CO AERs represent typical urban concentrations and can provide insight into the dominant emission sources of the city. All 25 WF events were distinguished because they had ΔPM2.5/ΔCO NERs that were significantly greater than the PM2.5/CO AER for each site. The ΔPM2.5/ΔCO NERs for the WF events ranged from 0.057–0.228 µg m−3 ppbv−1. In contrast, we were only able to calculate useful ΔNOy/ΔCO NERs (correlations with R2 > 0.65) for 4 of 17 events (only 17 of 25 events had NOy data). For these 4 events, ΔNOy/ΔCO NERs ranged from 0.044–0.075 ppbv ppbv−1, not all of which were significantly different from the NOy/CO AERs at the site. We conclude that ΔPM2.5/ΔCO NERs are a very useful tool for identifying WF events, but that the high and variable NOy concentrations in urban areas present problems when trying to use ΔNOy/ΔCO NERs.

We examined PM2.5 and Hazard Mapping System smoke plume satellite data at similar to 600 United States (US) air monitoring stations to identify surface smoke on 14.0% of all May-September days for 2018-2023, with large influences in 2020 and 2021, due to California fires, and 2023, due to Canadian fires. Days with smoke have an average of 11 mu g m(-3) more PM2.5 and 8 ppb higher maximum daily 8 h average (MDA8) O-3 concentrations than nonsmoke days, and they also account for 94% of all days that exceed the daily PM2.5 health standard (35 mu g m(-3)) and 36% of all days that exceed the O-3 health standard (70 ppb). To estimate the smoke contributions to the O-3 MDA8, Generalized Additive Models (GAMs) were built for each site using the nonsmoke day data and up to 8 predictors. The mean and standard deviation of the residuals from the GAMs were 0 +/- 6.1 ppb for the nonsmoke day data and 4.3 +/- 7.9 ppb for the smoke day data, indicating a significant enhancement in the MDA8 O-3 on smoke days. We found positive residuals on 72% of the smoke days and for these days, we calculate an average smoke contribution to the O-3 MDA8 of 7.8 +/- 6.0 ppb. Over the 6 year period, the percentage of exceedance days due to smoke in the continental US was 25% of all exceedance days, and the highest was in 2023 (38%). In 2023, the Central US experienced an unusually high number of exceedance days, 1522, with 52% of these impacted by smoke, while the Eastern US had fewer exceedance days, 288, with 78% of these impacted by smoke. Our results demonstrate the importance of wildland fires as contributors to exceedances of the health-based national air quality standards for PM2.5 and O-3.

We looked at a Siberian biomass burning (BB) event on Spring 2015 that was observed at Mt. Bachelor Observatory (MBO; 2.8 km a.s.l) and by satellite instruments (MODIS and CALIPSO), and intercepted by the NOAA WP-3D research aircraft during the Shale Oil and Natural Gas Nexus (SONGNEX) campaign. The Siberian airmass split into two plumes in the eastern Pacific. One plume moved eastward and was sampled directly at MBO. The other moved northeast to Alaska and then down to the U.S. Midwest; this second plume was intercepted by the WP-3D aircraft. We find that the ΔO3/ΔCO enhancement ratio at MBO is higher than for the plume intercepted by the aircraft. This is due to the warmer plume observed at MBO which led to thermal decomposition of PAN to NOx. The colder plume observed by the aircraft allowed PAN to be locked up and therefore this led to less ozone production. This is supported by the reactive nitrogen (NOy) measurements from the aircraft, which show that 64

We report the first high-resolution, detailed abundances of 21 elements for giants in the Galactic bulge/bar within 1 degrees of the Galactic plane, where high extinction has rendered such studies challenging. Our high-signal-to-noise-ratio and high-resolution, near-infrared spectra of seven M giants in the inner bulge, located at (l, b) = (0 degrees, +1 degrees), are observed using the IGRINS spectrograph. We report the first multichemical study of the inner Galactic bulge by investigating, relative to a robust new solar neighborhood sample, the abundance trends of 21 elements, including the relatively difficult to study heavy elements. The elements studied are: F, Mg, Si, S, Ca, Na, Al, K, Sc, Ti, V, Cr, Mn, Co, Ni, Cu, Zn, Y, Ce, Nd, and Yb. We investigate bulge membership of all seven stars using distances and orbital simulations, and we find that the most metal-poor star may be a halo interloper. Our investigation also shows that the inner bulge as close as 1 degrees north of the Galactic Center displays a similarity to the inner disk sequence, following the high-[alpha/Fe] envelope of the solar vicinity metal-rich population, though no firm conclusions for a different enrichment history are evident from this sample. We find a small fraction of metal-poor stars ([Fe/H] > -0.5), but most of our stars are mainly of supersolar metallicity. Fluorine is found to be enhanced at high metallicity compared to the solar neighborhood, but confirmation with a larger sample is required. We will apply this approach to explore the populations of the nuclear stellar disk and the nuclear star cluster.