- Direct estimates of biomass burning NOx emissions and lifetimes using daily observations from TROPOMIXiaomeng Jin, Qindan Zhu, and Ronald C. CohenAtmospheric Chemistry and Physics 2021
Biomass burning emits an estimated 25 % of global annual nitrogen oxides (NOx), an important constituent that participates in the oxidative chemistry of the atmosphere. Estimates of NOx emission factors, representing the amount of NOx per mass burned, are primarily based on field or laboratory case studies, but the sporadic and transient nature of wildfires makes it challenging to verify whether these case studies represent the behavior of the global fires that occur on earth. Satellite remote sensing provides a unique view of the earth, allowing for the study of emissions and downwind evolution of NOx from a large number of fires. We describe direct estimates of NOx emissions and lifetimes for fires using an exponentially modified Gaussian analysis of daily TROPOspheric Monitoring Instrument (TROPOMI) retrievals of NO2 tropospheric columns. We update the a priori profile of NO2 with a fine-resolution (0.25∘) global model simulation from NASA’s GEOS Composition Forecasting System (GEOS-CF), which largely enhances NO2 columns over fire plumes. We derive representative NOx emission factors for six fuel types globally by linking TROPOMI-derived NOx emissions with observations of fire radiative power from Moderate Resolution Imaging Spectroradiometer (MODIS). Satellite-derived NOx emission factors are largely consistent with those derived from in situ measurements. We observe decreasing NOx lifetime with fire emissions, which we infer is due to the increase in both NOx abundance and hydroxyl radical production. Our findings suggest promise for applying space-based observations to track the emissions and chemical evolution of reactive nitrogen from wildfires.
- Short-term PM2.5 and cardiovascular admissions in NY State: assessing sensitivity to exposure model choiceMike Z., Vivian Do, Siliang Liu, Patrick Kinney, Arlene Fiore, Xiaomeng Jin, Nicholas DeFelice, Jianzhao Bi, Yang Liu, Tabassum Insaf, and Marianthi-Anna KioumourtzoglouEnvironmental Health Aug 2021
Air pollution health studies have been increasingly using prediction models for exposure assessment even in areas without monitoring stations. To date, most studies have assumed that a single exposure model is correct, but estimated effects may be sensitive to the choice of exposure model.
- Development of a Solar-Induced Fluorescence─Canopy Conductance Model and Its Application to Stomatal Reactive Nitrogen DepositionErin R., Bryan Place, Alexander Turner, Qindan Zhu, Xiaomeng Jin, and Ronald CohenACS Earth and Space Chemistry Nov 2021
The bidirectional exchange of gases between vegetation and the atmosphere is controlled by a variety of environmental factors and feedbacks that are entangled and difficult to quantify. As a result of this complexity, parameterizations of canopy conductance (Gc) in atmospheric models introduce large uncertainties and likely biases into representations of atmosphere–biosphere gas exchange. We present a novel representation of canopy conductance derived from measurements of solar-induced fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI). We show a strong linear correlation between GPP and Gc, calculated using the Penman–Monteith theory, across a variety of ecosystem types in the AmeriFlux network. We couple this Gc–GPP correlation to previous research showing a strong linear correlation between SIF and GPP and estimate Gc at a 500 m spatial resolution across the continental United States. We also combine our model with surface estimates of NO2 and PAN from WRF-Chem to estimate stomatal deposition fluxes of these gases. Our results suggest that satellite measurements of SIF can provide important constraints on model representations of stomatal activity and canopy gas exchange on regional and global scales.
- Evaluating Drought Responses of Surface Ozone Precursor Proxies: Variations With Land Cover Type, Precipitation, and TemperatureJacob G. Naimark, Arlene M. Fiore, Xiaomeng Jin, Yuxuan Wang, Elizabeth Klovenski, and Christian BraneonGeophysical Research Letters Nov 2021
Prior work suggests drought exacerbates US air quality by increasing surface ozone concentrations. We analyze 2005–2015 tropospheric column concentrations of two trace gases that serve as proxies for surface ozone precursors retrieved from the OMI/Aura satellite: Nitrogen dioxide (ΩNO2; NOx proxy) and formaldehyde (ΩHCHO; VOC proxy). We find 3.5% and 7.7% summer drought enhancements (classified by SPEI) for ΩNO2 and ΩHCHO, respectively, corroborating signals previously extracted from ground‐level observations. When we subset by land cover type, the strongest ΩHCHO drought enhancement (10%) occurs in the woody savannas of the Southeast US. By isolating the influences of precipitation and temperature, we infer that enhanced biogenic VOC emissions in this region increase ΩHCHO independently with both high temperature and low precipitation during drought. The strongest ΩNO2 drought enhancement (6.0%) occurs over Midwest US croplands and grasslands, which we infer to reflect the sensitivity of soil NOx emissions to temperature. Projected increases in drought severity and frequency for this century raise questions regarding possible impacts on air quality. Surface ozone, an air pollutant estimated to cause over 1 million annual premature deaths globally, forms when its precursor gases react in the sunlit atmosphere. These precursor gases depend on temperature and precipitation and thus can respond to drought. We analyze over a decade of satellite observations of two trace gases relevant to ozone formation and find that, on average, their concentrations increase during summer droughts in the Eastern US. While higher temperatures during droughts are usually associated with observed increases in trace gas concentrations, in the Southeast US we find increases associated with low precipitation independent of temperature. Satellite detection of these changes implies promise for application to other regions and more generally for improving mechanistic understanding of air quality responses to drought and other climate extremes. Satellite retrievals of tropospheric NO2 and HCHO show drought enhancements of 3.5% and 7.7%, respectively, during Eastern US summers Low precipitation and high temperatures both independently drive HCHO drought enhancement (10%) in Southeast US woody savannas High temperatures drive NO2 drought enhancement (6.0%) in Midwest US croplands and grasslands Satellite retrievals of tropospheric NO2 and HCHO show drought enhancements of 3.5% and 7.7%, respectively, during Eastern US summers Low precipitation and high temperatures both independently drive HCHO drought enhancement (10%) in Southeast US woody savannas High temperatures drive NO2 drought enhancement (6.0%) in Midwest US croplands and grasslands
- First Measurements of Ambient PM2.5 in Kinshasa, Democratic Republic of Congo and Brazzaville, Republic of Congo Using Field-calibrated Low-cost SensorsCeleste McFarlane, Paulson Kasereka Isevulambire, Raymond Sinsi Lumbuenamo, Arnold Murphy Elouma Ndinga, Ranil Dhammapala, Xiaomeng Jin, V Faye McNeill, Carl Malings, R Subramanian, and Daniel M WesterveltAerosol and Air Quality Research Nov 2021
Estimates of air pollution mortality in sub-Saharan Africa are limited by a lack of surface observations of fine particulate matter (PM2.5). Despite being large metropolises, Kinshasa, Democratic Republic of the Congo (DRC), and Brazzaville, Republic of the Congo (ROC), which possess populations of 14.3 million and 2.4 million, respectively, use no reference air pollution monitors at the time of writing. However, a few reference monitors have recently been deployed in other parts of sub-Saharan Africa, including a Met One Beta Attenuation Monitor (BAM-1020) at the U.S. Embassy in Kampala, Uganda, next to which a low-cost PM2.5 monitor, the PurpleAir, was collocated in August 2019. The raw PurpleAir data from September 2019 through February 2020 strongly correlated with the BAM-1020 measurements (R2 = 0.88) but also exhibited a mean absolute error (MAE) of approximately 14 µg m–3. Employing two calibration models, namely, multiple linear regression and random forests, decreased the MAE to 3.4 µg m–3 and increased R2 to 0.96. Given the similarity in climate and emissions, we applied the collocated field correction factors for Kampala to four PurpleAir units in Kinshasa and one in neighboring Brazzaville, which were deployed in April 2018. We estimated an average annual PM2.5 concentration of 43.5 µg m–3 in Kinshasa for 2019, which exceeds the World Health Organization (WHO)’s Interim Target 1 (10 µg m–3) by 4 times. Finally, the surface PM2.5 level and the aerosol optical depth were about 40% lower during the COVID-19 lockdown in 2020 than the corresponding period in 2019, which cannot be attributed solely to changes in meteorology or wildfire emission. Hence, our results highlight the need to implement clean air solutions in the Congo.
- Inferring Changes in Summertime Surface Ozone–NO x –VOC Chemistry over U.S. Urban Areas from Two Decades of Satellite and Ground-Based ObservationsXiaomeng Jin, Arlene Fiore, K. Folkert Boersma, Isabelle De Smedt, and Lukas ValinEnvironmental Science & Technology Nov 2020
Urban ozone (O3) formation can be limited by NO x , VOCs, or both, complicating the design of effective O3 abatement plans. A satellite-retrieved ratio of formaldehyde to NO2 (HCHO/NO2), developed from theory and modeling, has previously been used to indicate O3 formation chemistry. Here, we connect this space-based indicator to spatiotemporal variations in O3 recorded by on-the-ground monitors over major U.S. cities. High-O3 events vary nonlinearly with OMI HCHO and NO2, and the transition from VOC-limited to NO x -limited O3 formation regimes occurs at higher HCHO/NO2 value (3 to 4) than previously determined from models, with slight intercity variations. To extend satellite records back to 1996, we develop an approach to harmonize observations from GOME and SCIAMACHY that accounts for differences in spatial resolution and overpass time. Two-decade (1996–2016) multisatellite HCHO/NO2 captures the timing and location of the transition from VOC-limited to NO x -limited O3 production regimes in major U.S. cities, which aligns with the observed long-term changes in urban–rural gradient of O3 and the reversal of O3 weekend effect. Our findings suggest promise for applying space-based HCHO/NO2 to interpret local O3 chemistry, particularly with the new-generation satellite instruments that offer finer spatial and temporal resolution.
- Identifying coal-fired power plants for early retirementNada Maamoun, Ryan Kennedy, Xiaomeng Jin, and Johannes UrpelainenRenewable and Sustainable Energy Reviews Jul 2020
To ensure climate stability, the decarbonization of the global economy is necessary. Coal-fired power generation is both the most carbon-intensive form of electricity supply and associated with adverse health effects. Thus, retiring coal-fired power plants is essential for achieving the goals of the Paris agreement on climate change. Here we introduce a retirement index that ranks coal-fired power plants based on their age, carbon emissions, and potential for air pollution. We use data on 2143 operating coal-fired plants globally. Based on the index, the top plants identified for retirement are located in China, India and South Korea and account for a total capacity of 87 GW. These plants represent 1% of global coal fired plants yet account for 4.5% of global operating capacity. The results contrast with the commonly used approach that ranks plants based on age and thus prioritizes older plants in developed countries for early retirement rather than younger plants in developing countries. We run several sensitivity checks and results show that China and India remain consistently the top countries with most capacity in need of retirement.
- Environmental Justice in India: Incidence of Air Pollution from Coal-Fired Power PlantsJacob Kopas, Erin York, Xiaomeng Jin, S.P. Harish, Ryan Kennedy, Shiran Victoria Shen, and Johannes UrpelainenEcological Economics Jul 2020
Air pollution is a vexing problem for emerging countries that strike a delicate balance between environmental protection, health, and energy for growth. We examine these difficulties in a study of disparate levels of exposure to pollution from coal-fired power generation in India, a country with high levels of air pollution and large, marginalized populations. With data on coal plant locations, atmospheric conditions, and census demographics, we estimate exposure to coal plant emissions using models that predict emission transportation. We find that ethnic and poor populations are more likely to be exposed to coal pollution. However, this relationship is sometimes non-linear and follows an inverted u-shape similar to that of an Environmental Kuznets Curve. We theorize that this non-linear relationship is due to the exclusion of marginalized communities from both the negative and positive externalities of industrial development.
- Environmental Degradation and Public Opinion: The Case of Air Pollution in VietnamSung Eun Kim, S. P. Harish, Ryan Kennedy, Xiaomeng Jin, and Johannes UrpelainenThe Journal of Environment & Development Jul 2020
Air pollution is a pressing problem of public health for developing countries, but governments have few incentives to abate air pollution without public awareness of the issue. Focusing on the case of Vietnam, we examine the determinants of public awareness of air pollution. Using representative survey data for the entire country from 2017, we find that local exposure to air pollution increases public awareness and reduces satisfaction with governments but does not provoke opposition to coal-fired power generation. In contrast, education leads people to oppose coal-fired power plants. These results suggest that while local air pollution contributes to awareness and dissatisfaction with the government, support for effective policy measures depends on education levels.
- The COVID-19 lockdowns: a window into the Earth SystemNoah S. Diffenbaugh, Christopher B. Field, Eric A. Appel, Ines L. Azevedo, Dennis D. Baldocchi, Marshall Burke, Jennifer A. Burney, Philippe Ciais, Steven J. Davis, Arlene M. Fiore, Sarah M. Fletcher, Thomas W. Hertel, Daniel E. Horton, Solomon M. Hsiang, Robert B. Jackson, Xiaomeng Jin, Margaret Levi, David B. Lobell, Galen A. McKinley, Frances C. Moore, Anastasia Montgomery, Kari C. Nadeau, Diane E. Pataki, James T. Randerson, Markus Reichstein, Jordan L. Schnell, Sonia I. Seneviratne, Deepti Singh, Allison L. Steiner, and Gabrielle Wong-ParodiNature Reviews Earth & Environment Jul 2020
Restrictions to reduce human interaction have helped to avoid greater suffering and death from the COVID-19 pandemic, but have also created socioeconomic hardship. This disruption is unprecedented in the modern era of global observing networks, pervasive sensing and large-scale tracking of human mobility and behaviour, creating a unique test bed for understanding the Earth System. In this Perspective, we hypothesize the immediate and long-term Earth System responses to COVID-19 along two multidisciplinary cascades: energy, emissions, climate and air quality; and poverty, globalization, food and biodiversity. While short-term impacts are dominated by direct effects arising from reduced human activity, longer-lasting impacts are likely to result from cascading effects of the economic recession on global poverty, green investment and human behaviour. These impacts offer the opportunity for novel insight, particularly with the careful deployment of targeted data collection, coordinated model experiments and solution-oriented randomized controlled trials, during and after the pandemic. The COVID-19 pandemic has caused substantial global impact. This Perspective provides insight into the environmental effects of the pandemic, documenting how it offers an opportunity to better understand the Earth System.
- Using Satellites to Track Indicators of Global Air Pollution and Climate Change Impacts: Lessons Learned From a NASA‐Supported Science‐Stakeholder CollaborativeSusan C. Anenberg, Matilyn Bindl, Michael Brauer, Juan J. Castillo, Sandra Cavalieri, Bryan N. Duncan, Arlene M. Fiore, Richard Fuller, Daniel L. Goldberg, Daven K. Henze, Jeremy Hess, Tracey Holloway, Peter James, Xiaomeng Jin, Iyad Kheirbek, Patrick L. Kinney, Yang Liu, Arash Mohegh, Jonathan Patz, Marcia P. Jimenez, Ananya Roy, Daniel Tong, Katy Walker, Nick Watts, and J. Jason WestGeoHealth Jul 2020
The 2018 NASA Health and Air Quality Applied Science Team (HAQAST) “Indicators” Tiger Team collaboration between NASA‐supported scientists and civil society stakeholders aimed to develop satellite‐derived global air pollution and climate indicators. This Commentary shares our experience and lessons learned. Together, the team developed methods to track wildfires, dust storms, pollen counts, urban green space, nitrogen dioxide concentrations and asthma burdens, tropospheric ozone concentrations, and urban particulate matter mortality. Participatory knowledge production can lead to more actionable information but requires time, flexibility, and continuous engagement. Ground measurements are still needed for ground truthing, and sustained collaboration over time remains a challenge. Recent advances in satellite remote sensing enable observation‐based tracking of climate change and air pollution with relatively high spatial resolution globally. The 2018 NASA Health and Air Quality Applied Science Team (HAQAST) “Indicators” Tiger Team launched a collaboration between \textbackslashtextasciitilde20 NASA‐supported scientists and civil society stakeholders to develop satellite‐derived global air pollution and climate indicators. This Commentary demonstrates the range of air quality and climate change tracking uses for satellite data and shares our experience and lessons learned, which can inform future problem‐driven science‐stakeholder collaborative efforts. Together, the team developed methods to track wildfires, dust storms, pollen, urban green space, nitrogen dioxide concentrations and asthma burdens, tropospheric ozone concentrations, and urban fine particulate matter mortality. Lessons learned include that participatory knowledge production can lead to more actionable information for stakeholders but requires time and dedicated attention. Stakeholder engagement is valuable at each stage, from developing more nascent data sets to operationalizing mature data sets. Flexibility is critical, since stakeholder needs evolve and new synergies emerge when there are engagements across a wide range of stakeholders and teams. However, additional ground measurements are needed to ground truth satellite observations, and sustained collaboration between the researchers and stakeholders after extramural support ends remains a challenge. The NASA Health and Air Quality Applied Science Team “Indicators” Tiger Team developed satellite‐based air quality and climate indicators Participatory knowledge production can lead to more useful information for stakeholders but requires continuous engagement and flexibility Ground measurements are still needed, and sustained collaboration between the researchers and stakeholders over time remains a challenge
- Transboundary air pollution from coal-fired power generationXinming Du, Xiaomeng Jin, Noah Zucker, Ryan Kennedy, and Johannes UrpelainenJournal of Environmental Management Jul 2020
To what extent do the short-term negative externalities of fossil fuel use traverse national borders? Transnational negative externalities are thought to motivate international environmental cooperation, but we often lack detailed data on their occurrence. Using a Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT), we offer global estimates of the extent of transboundary air pollution from coal-fired power generation. In an advance of the existing literature, we attribute the air pollution experienced in different locales to specific coal-fired power plants, allowing us to evaluate the extent to which pollution from the coal industry is experienced across different jurisdictions. Our results indicate that the issue is most severe in South Asia and East Asia. When weighting by the population of “receiving” locations, India is found to be the largest emitter of transboundary air pollution, followed by China. Residents of Bangladesh are found to experience the most transboundary air pollution by a wide margin.
- Assessing uncertainties of a geophysical approach to estimate surface fine particulate matter distributions from satellite-observed aerosol optical depthXiaomeng Jin, Arlene M Fiore, Gabriele Curci, Alexei Lyapustin, Kevin Civerolo, Michael Ku, Aaron van Donkelaar, and Randall V MartinAtmospheric Chemistry and Physics Jul 2019
Health impact analyses are increasingly tapping the broad spatial coverage of satellite aerosol optical depth (AOD) products to estimate human exposure to fine particulate matter (PM2.5). We use a forward geophysical approach to derive ground-level PM2.5 distributions from satellite AOD at 1 km2 resolution for 2011 over the northeastern US by applying relationships between surface PM2.5 and column AOD (calculated offline from speciated mass distributions) from a regional air quality model (CMAQ; 12×12 km2 horizontal resolution). Seasonal average satellite-derived PM2.5 reveals more spatial detail and best captures observed surface PM2.5 levels during summer. At the daily scale, however, satellite-derived PM2.5 is not only subject to measurement uncertainties from satellite instruments, but more importantly to uncertainties in the relationship between surface PM2.5 and column AOD. Using 11 ground-based AOD measurements within 10 km of surface PM2.5 monitors, we show that uncertainties in modeled PM2.5∕AOD can explain more than 70 % of the spatial and temporal variance in the total uncertainty in daily satellite-derived PM2.5 evaluated at PM2.5 monitors. This finding implies that a successful geophysical approach to deriving daily PM2.5 from satellite AOD requires model skill at capturing day-to-day variations in PM2.5∕AOD relationships. Overall, we estimate that uncertainties in the modeled PM2.5∕AOD lead to an error of 11 µg m−3 in daily satellite-derived PM2.5, and uncertainties in satellite AOD lead to an error of 8 µg m−3. Using multi-platform ground, airborne, and radiosonde measurements, we show that uncertainties of modeled PM2.5∕AOD are mainly driven by model uncertainties in aerosol column mass and speciation, while model representation of relative humidity and aerosol vertical profile shape contributes some systematic biases. The parameterization of aerosol optical properties, which determines the mass extinction efficiency, also contributes to random uncertainty, with the size distribution being the largest source of uncertainty and hygroscopicity of inorganic salt the second largest. Future efforts to reduce uncertainty in geophysical approaches to derive surface PM2.5 from satellite AOD would thus benefit from improving model representation of aerosol vertical distribution and aerosol optical properties, to narrow uncertainty in satellite-derived PM2.5.
- Comparison of multiple PM2.5 exposure products for estimating health benefits of emission controls over New York State, USAXiaomeng Jin, Arlene M Fiore, Kevin Civerolo, Jianzhao Bi, Yang Liu, Aaron van Donkelaar, Randall V Martin, Mohammad Al-Hamdan, Yuqiang Zhang, Tabassum Z Insaf, Marianthi-Anna Kioumourtzoglou, Mike Z He, and Patrick L KinneyEnvironmental Research Letters Jul 2019
Ambient exposure to fine particulate matter (PM2.5) is one of the top global health concerns. We estimate the PM2.5-related health benefits of emission reduction over New York State (NYS) from 2002 to 2012 using seven publicly available PM2.5 products that include information from ground-based observations, remote sensing and chemical transport models. While these PM2.5 products differ in spatial patterns, they show consistent decreases in PM2.5 by 28%–37% from 2002 to 2012. We evaluate these products using two sets of independent ground-based observations from the New York City Community Air Quality Survey (NYCCAS) Program for an urban area, and the Saint Regis Mohawk Tribe Air Quality Program for a remote area. Inclusion of satellite remote sensing improves the representativeness of surface PM2.5 in the remote area. Of the satellite-based products, only the statistical land use regression approach captures some of the spatial variability across New York City measured by NYCCAS. We estimate the PM2.5-related mortality burden by applying an integrated exposure-response function to the different PM2.5 products. The multi-product mean PM2.5-related mortality burden over NYS decreased by 5660 deaths (67%) from 8410 (95% confidence interval (CI): 4570–12 400) deaths in 2002 to 2750 (CI: 700–5790) deaths in 2012. We estimate a 28% uncertainty in the state-level PM2.5 mortality burden due to the choice of PM2.5 products, but such uncertainty is much smaller than the uncertainty (130%) associated with the exposure-response function.
- Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric modelsMinghui Diao, Tracey Holloway, Seohyun Choi, Susan M O’Neill, Mohammad Z Al-Hamdan, Aaron van Donkelaar, Randall V Martin, Xiaomeng Jin, Arlene M Fiore, Daven K Henze, Forrest Lacey, Patrick L Kinney, Frank Freedman, Narasimhan K Larkin, Yufei Zou, James T Kelly, and Ambarish VaidyanathanJournal of the Air & Waste Management Association Oct 2019
Fine particulate matter (PM2.5) is a well-established risk factor for public health. To support both health risk assessment and epidemiological studies, data are needed on spatial and temporal patterns of PM2.5 exposures. This review article surveys publicly available exposure datasets for surface PM2.5 mass concentrations over the contiguous U.S., summarizes their applications and limitations, and provides suggestions on future research needs. The complex landscape of satellite instruments, model capabilities, monitor networks, and data synthesis methods offers opportunities for research development, but would benefit from guidance for new users. Guidance is provided to access publicly available PM2.5 datasets, to explain and compare different approaches for dataset generation, and to identify sources of uncertainties associated with various types of datasets. Three main sources used to create PM2.5 exposure data are ground-based measurements (especially regulatory monitoring), satellite retrievals (especially aerosol optical depth, AOD), and atmospheric chemistry models. We find inconsistencies among several publicly available PM2.5 estimates, highlighting uncertainties in the exposure datasets that are often overlooked in health effects analyses. Major differences among PM2.5 estimates emerge from the choice of data (ground-based, satellite, and/or model), the spatiotemporal resolutions, and the algorithms used to fuse data sources.
- Evaluating a Space-Based Indicator of Surface Ozone-NO x-VOC Sensitivity Over Midlatitude Source Regions and Application to Decadal TrendsXiaomeng Jin, Arlene M Fiore, Lee T Murray, Lukas C Valin, Lok N Lamsal, Bryan Duncan, K Folkert Boersma, Isabelle De Smedt, Gonzalo González Abad, Kelly Chance, and Gail S TonnesenJournal of Geophysical Research: Atmospheres Oct 2017
Determining effective strategies for mitigating surface ozone (O3) pollution requires knowledge of the relative ambient concentrations of its precursors, NOx, and VOCs. The space-based tropospheric column ratio of formaldehyde to NO2 (FNR) has been used as an indicator to identify NOx-limited versus NOx-saturated O3 formation regimes. Quantitative use of this indicator ratio is subject to three major uncertainties: (1) the split between NOx-limited and NOx-saturated conditions may shift in space and time, (2) the ratio of the vertically integrated column may not represent the near-surface environment, and (3) satellite products contain errors. We use the GEOS-Chem global chemical transport model to evaluate the quantitative utility of FNR observed from the Ozone Monitoring Instrument over three northern midlatitude source regions. We find that FNR in the model surface layer is a robust predictor of the simulated near-surface O3 production regime. Extending this surface-based predictor to a column-based FNR requires accounting for differences in the HCHO and NO2 vertical profiles. We compare four combinations of two OMI HCHO and NO2 retrievals with modeled FNR. The spatial and temporal correlations between the modeled and satellite-derived FNR vary with the choice of NO2 product, while the mean offset depends on the choice of HCHO product. Space-based FNR indicates that the spring transition to NOx-limited regimes has shifted at least a month earlier over major cities (e.g., New York, London, and Seoul) between 2005 and 2015. This increase in NOx sensitivity implies that NOx emission controls will improve O3 air quality more now than it would have a decade ago.
- Spatial and temporal variability of ozone sensitivity over China observed from the Ozone Monitoring InstrumentXiaomeng Jin, and Tracey HollowayJournal of Geophysical Research: Atmospheres Jul 2015
Surface ozone (O3) air pollution in populated regions has been attributed to emissions of nitrogen oxides (NO + NO2 = NOx) and reactive volatile organic compounds (VOCs). These constituents react with hydrogen oxide radicals (OH + HO2 = HOx) in the presence of sunlight and heat to produce O3. The question of whether to reduce NOx emissions, VOC emissions, or both is complicated by spatially and temporally heterogeneous ozone-NOx-VOC sensitivity. This study characterizes spatial and temporal variations in O3 sensitivity by analyzing the ratio of formaldehyde (HCHO, a marker of VOCs) to nitrogen dioxide (NO2), a metric known as the formaldehyde nitrogen ratio (FNR). Level 3 gridded retrievals from the Ozone Monitoring Instrument (OMI) aboard the NASA Aura satellite were used to calculate FNR, with our analysis focusing on China. Based on previous studies, we take FNR < 1.0 as indicating VOC-limited regimes, FNR > 2.0 as indicating NOx-limited regime, and FNR between 1.0 and 2.0 as indicating transitional regime (where either NOx reductions or VOC reductions would be expected to reduce O3). We find that the transitional regime is widespread over the North China Plain (NCP), the Yangtze River Delta, and the Pearl River Delta during the ozone season (defined as having near-surface air temperatures >20°C at the early afternoon OMI overpass time). Outside of these regions, the NOx-limited regime is dominant. Because HCHO and NO2 have distinct seasonal patterns, FNR also has a pronounced seasonality, consistent with the seasonal cycle of surface O3. Examining trends from 2005 to 2013 indicates rapid growth in NO2, especially over less-developed areas where O3 photochemistry is NOx limited. Over this time period, HCHO decreased in southern China, where VOC emissions are dominated by biogenic sources, but increased slightly over the NCP, where VOC emissions are dominated by anthropogenic sources. A linear regression approach suggests that most of China (70% of grid cells) will be characterized by a transitional regime during the O3 season by 2030. However, in megacities such as Guangzhou, Shanghai, and Beijing, NO2 has decreased such that the chemical regime has shifted from VOC limited in 2005 to transitional in 2013.
- Geostationary Satellite Observation of Precipitable Water Vapor Using an Empirical Orthogonal Function (EOF) based Reconstruction Technique over Eastern ChinaMan Wong, Xiaomeng Jin, Zhizhao Liu, Janet Nichol, Shirong Ye, Peng Jiang, and Pak ChanRemote Sensing Jul 2015
Water vapor, as one of the most important greenhouse gases, is crucial for both climate and atmospheric studies. Considering the high spatial and temporal variations of water vapor, a timely and accurate retrieval of precipitable water vapor (PWV) is urgently needed, but has long been constrained by data availability. Our study derived the vertically integrated precipitable water vapor over eastern China using Multi-functional Transport Satellite (MTSAT) data, which is in geostationary orbit with high temporal resolution. The missing pixels caused by cloud contamination were reconstructed using an Empirical Orthogonal Function (EOF) decomposition method over both spatial and temporal dimensions. GPS meteorology data were used to validate the retrieval and the reconstructed results. The diurnal variation of PWV over eastern China was analyzed using harmonic analysis, which indicates that the reconstructed PWV data can depict the diurnal cycle of PWV caused by evapotranspiration and local thermal circulation.
- Multi-sensors study of precipitable water vapour over mainland ChinaMan Sing Wong, Xiaomeng Jin, Zhizhao Liu, Janet Nichol, and P W ChanInternational Journal of Climatology Nov 2014
Water vapour, an important greenhouse gas in the atmosphere, is crucial for hydrological, atmospheric, and meteorological processes. This study first compared five precipitable water vapour (PWV) products from multi-sensors including radiosonde, AERosol RObotic NETwork (AERONET) sunphotometer, Global Positioning System (GPS) and MODerate resolution Imaging Spectroradiometer (MODIS), and then characterized the spatial and temporal trends of PWV in mainland China. Intercomparison results indicate good agreements among PWV products with correlation coefficients ranging from 0.775 to 0.937. As for spatial analysis, 13 years of MODIS MOD05 products were investigated and the spatial distribution of PWV is closely correlated with the topography, e.g. latitude and altitude, in mainland China. A monotonically increasing annual trend was detected in some radiosonde sites in China between 1976 and 1999, but a decreasing trend was observed between 2000 and 2012. Analysis of the differences in PWV between weekdays and weekends indicated a marked weekend effect, suggesting the influence of anthropogenic activities. Diurnal variations in PWV were also studied from 1999 to 2009 using GPS data. A pronounced diurnal cycle of PWV was observed in most of the sites during summer and spring seasons.