Methane concentrations were measured at major New York State (NYS) landfills in 2021 and 2022 using both aerial and ground-level monitoring from a mobile research lab (MRL) to determine facility emission rates. These emission rates were estimated by a mass balance method using Gauss's Theorem and a Gaussian Plume Dispersion (GPD) method. Three separate emission rates were calculated for each of the facilities when data was available, two of which were calculated using both the GPD and mass balance methods from the MRL data, and the third using the more rigorous aircraft data and mass balance method, which was used as the reference estimate. Both MRL GPD and mass balance methods come with considerable uncertainty, which is mainly driven by stability class and distance for the GPD and plume height for the mass balance. All but one of the GPD estimates fell within the uncertainty range of the aircraft estimates and estimated a CH4 emission rate range of 262-3896 kg h-1. The MRL mass balance estimates, however, proved to be quite different from the aircraft aside from one case with an estimated range of 463-6285 kg h-1. The poor agreement between the MRL mass balance and the aircraft reduces confidence in these estimates. The observations were also compared to the 2021 and 2022 self-reported EPA Greenhouse Gas Reporting Program (GHGRP) Inventory. The aircraft estimates were, on average, 2.2 & times; greater than the GHGRP while the MRL estimates were more variable in comparison with the inventory. This study provides information on these different estimation methods and will help improve and inform the GHG emissions inventory. Ground-level mobile monitoring was used to estimate landfill emission rates and compare with the GHGRP inventory. While there was high uncertainty, accurate emission rates were calculated during favorable conditions. Observations were mostly similar, albeit higher than the GHGRP inventory.

Abstract The Unified Forecast System (UFS) is a community‐based Earth modeling system designed to support operational forecasts at the National Oceanic and Atmospheric Administration (NOAA), while also facilitating the integration of research advances from the broader scientific community. The Configurable ATmospheric Chemistry (CATChem) library and modeling component is being developed to include comprehensive chemical and aerosol processes for representing atmospheric composition through a flexible, easy‐to‐modify, and well‐documented infrastructure. Here CATChem version 1.0 (v1.0) is linked to the UFS High Resolution 3 configuration to create the Unified Forecast System with Chemistry (UFS‐Chem) v1.0. The configurability of UFS‐Chem enables its use for both research and operational applications, reducing time and effort for transitions to operations and enhancing collaboration with the research community. As a first step toward this goal, the gas‐phase chemistry from the Atmosphere Model version 4.1 (AM4.1), developed at NOAA Geophysical Fluid Dynamics Laboratory (GFDL), is incorporated into CATChem and linked to the UFS as the first UFS‐Chem configuration for global air quality applications. The simulated atmospheric compositions are generally consistent with those in GFDL‐AM4.1 and agree well with surface observations, aircraft measurements, and satellite retrievals (with biases mostly within 30%), demonstrating atmospheric chemistry is reasonably well represented in the model. This work documents model uncertainties and biases in UFS‐Chem v1.0 to help prioritize further improvements in emissions and process‐level representations. The new global configuration is shown to be robust in representing atmospheric composition and chemical processes and serves as a foundation for future development.

Abstract. Nitrous oxide (N2O) is a potent greenhouse gas and ozone-depleting substance. Approximately 42 % of anthropogenic N2O emissions are thought to be emitted from urban areas. We tested three N2O analyzers for their suitability to measure N2O in urban areas from tower and mobile platforms. All three analyzers (Aerodyne SuperDUAL, Aeris MIRA Ultra, and LI-COR LI-7820) have sufficient precision for urban measurements but require different amounts of calibration and attention for best results. Using these analyzers, we observed tower-level enhancements at least 3 times larger than predicted from the best available inventory for the NYC region. Co-measurement of carbon monoxide (available on all but the LI-7820) were used to identify combustion-related enhancements of N2O. Mobile driving confirmed that traffic related emissions for NYC are captured by the inventory and that wastewater treatment is the most likely source for the missing N2O emissions.

Robust information on the spatial distribution of global carbon fluxes is required to project the future trajectory of carbon-climate feedback effects and atmospheric CO2 concentrations. Estimates of the latitudinal partitioning of carbon fluxes from top-down atmospheric CO2 inverse models currently diverge widely, because of methodological limitations or systematic biases in models or observations. We use airborne CO2 observations from the NASA Atmospheric Tomography Mission to evaluate and refine inverse model estimates from the Orbiting Carbon Observatory version 10 Model Intercomparison Project of total CO2 exchange for the two-year period of June 2016-May 2018. Applying emergent concentration-flux relationships as constraints reduces zonal total flux uncertainties by 46 to 56% relative to the full v10 MIP ensemble and by 17 to 28% relative to the subset excluding satellite observations over ocean. Subtracting independent estimates of fossil-fuel emissions and air-sea gas exchange results in residual land fluxes with a large northern extratropical sink, a small southern extratropical sink, and a small tropical source. The airborne-derived tropical land source disagrees with a large tropical land sink from process-based terrestrial models combined with estimates of land use emissions and river fluxes, representing an important challenge for our understanding of the global carbon cycle. The large implied northern extratropical sink can be explained either by underestimated land uptake by process models or a combination of process model bias and overestimated fossil fuel emissions.

Abstract Molecular chlorine (Cl 2 ) is a key source of chlorine atoms (Cl∙) in the atmosphere, which can alter local oxidation chemistry and enhance both ozone (O 3 ) and particulate matter. While Cl 2 levels in some coastal cities can be substantial and are enhanced by particulate nitrate, the presence and impact of Cl 2 in US cities is poorly understood. In summer 2023, we measured gas phase Cl 2 mixing ratios (4 and 32.5 m above ground level, a.g.l) and fluxes (32.5 m a.g.l) in Mineola, New York. Cl 2 mixing ratios and fluxes consistently peaked during the afternoon, with averages (± standard deviation) of 24 ± 10 ppt and 170 ± 100 ppt·cm·s −1 , respectively, at 32.5 m from 12 to 4 p.m. local time. Strong correlations between Cl 2 emissions, solar radiation, hypochlorous acid, and O 3 suggest photochemical multiphase chemistry is a prominent source of Cl 2 to the region. Positive fluxes indicate emission of Cl 2 from the surface to the atmosphere and are consistent with sources exceeding the expected multiphase production rate of Cl 2 on aerosol surfaces. We hypothesize that rooftops, fences, roads and other urban surfaces act as reservoirs for chloride (Cl − ) from deteriorating building materials, industrial processes, and dry deposition of sea spray particles and chlorine‐containing gases, enabling heterogeneous formation of gas phase Cl 2 upon interaction with atmospheric pollutants such as O 3 . Deterioration of building materials may also enable surface chemistry that could impact urban chlorine chemistry, even in areas without strong coastal sea spray influence.

More than a quarter of anthropogenic global warming has been attributed to methane growth in the atmosphere. Landfills account for 17% of estimated methane emissions in the United States of America (USA), according to the Environmental Protection Agency (EPA), but studies show that many landfills emit more than reported. We developed a novel method to calculate monthly methane emissions from an active landfill using atmospheric methane mixing ratios observed from a single tower in New Jersey, USA. The tower method provides two and a half years of semicontinuous measurements and therefore observes more of the variability of methane emissions and lacks the sampling bias present in other methods. Time-specific comparison of tower-based methane emissions against those observed from summertime aircraft sampling and year-round mobile ground-based platforms showed good agreement. Estimated methane emissions for 2023 were five times greater than those reported to the EPA. We observed a strong seasonality in methane emissions, with a peak in the winter and a minimum in the summer. This seasonal cycle was driven by a strong negative dependence on air temperature and the change in atmospheric pressure. Our results highlight the importance of observations in nonideal weather conditions (such as declining pressure and near-freezing temperatures) when methane emissions are largest. We suggest that this methodology could be applied to other suitable landfills to improve estimates of methane emissions.

Abstract. Benchmark datasets for evaluating profile-based ecosystem flux methods across environmental gradients are currently lacking. This limits method evaluation, cross-site intercomparison, and the expansion of tower-based monitoring for gases not routinely measured by the eddy covariance (EC) method. Here, we present a benchmark dataset derived from 47 terrestrial towers in the National Ecological Observatory Network (NEON), integrating co-located EC, concentration profiles, tower geometry, and canopy structural metrics. We developed a dataset to evaluate the performance of three widely used gradient flux approaches – the modified Bowen ratio (MBR), aerodynamic (AE), and wind-profile (WP) methods – against co-located EC measurements of CO₂ and H₂O. We evaluate how canopy structure, sensor height configuration, and data filtering influence agreement with EC across ecosystems, with canopy heights ranging from 0.15 to 53 m. Performance varied strongly among approaches and measurement configurations. Across all ecosystems, 11% of height-pair combinations for CO₂ and 19% for H₂O achieved moderate-to-strong concordance with EC, with the MBR approach providing the most consistent performance. Reliable estimates most often occurred when both sampling heights were above the canopy (AA) or when one level was above the canopy and the other within sparse canopies (AW). Concordance declined as canopy complexity increased, highlighting persistent challenges in tall, complex forests. Since filtering substantially reduced data availability, we developed an ensemble framework that combined reliable estimates across the three GF approaches and height pairs. Ensemble GF fluxes reproduced seasonal diel dynamics measured by EC across ecosystems (R2 = 0.58–0.99), capturing both the seasonal magnitude and direction of net ecosystem exchange. Benchmark analyses show that the GF method can provide robust ecosystem-scale flux information when deployed under favorable structural and micrometeorological conditions. The released benchmark dataset provides a resource for testing new flux algorithms, optimizing sensor placement, benchmarking profile methods, and extending multi-gas tower observations to be more inclusive of gases that are difficult to measure with fast-response EC instrumentation, including CH₄, N₂O, volatile organic compounds, and reactive pollutants.

Abstract Sub–micron particulate matter (PM 1 ) in the New York (NY) metropolitan area impacts air quality and human health. We characterized refractory black carbon (BC) and non–refractory (NR) PM 1 in Mineola, NY during winter 2024 and NR‐PM 1 during summer 2023. This study investigated seasonal differences in PM 1 , drivers of wintertime PM 1 elevated events, and potential respiratory exposure based on measured PM properties. Organic aerosol (OA) dominates both winter (63%) and summer (86%) NR–PM 1 while BC comprised 6% of winter PM 1 . Primary OA dominates winter PM 1 (57%) with cooking organic aerosol (COA) contributing on average 29%, but up to 81%, of elevated PM 1 events. In summer, OA was impacted by wildfire smoke and biogenic sources and COA averaged only 9% of OA, but sporadically enhanced OA. In winter, COA drove several PM 1 events, during which coating thickness increased. Modeled deposition rates allowed us to explore potential impacts of aerosol size on the human respiratory tract. Simulated deposition indicated urban PM 1 primarily deposited to the sensitive alveolar region. BC–containing particles exacerbated this effect relative to cores in the same size range. Canadian wildfire events during summer 2023 enhanced total deposition to the lungs when weighted by mass, with relative deposition favoring the nose, throat, and associated head airways more than other summer periods. Our observations demonstrate that cooking is an important local source of PM 1 in urban regions throughout the year, and that BC and NR‐PM 1 from multiple sources potentially pose a threat to respiratory deposition and community health.

Accurately quantifying methane emissions from cities, and understanding the processes that drive these emissions, is important for reaching climate mitigation goals. Methane emissions from New York City metropolitan area (NYCMA), the most populous urban area of the United States, have consistently been underestimated by emission inventories compared to aircraft and satellite observations. In this study, we used continuous rooftop measurements of methane over six winter-to-spring transitions (January–May 2019–2024) to examine the variability of city-scale methane enhancements (ΔCH4) and estimate methane emissions from the NYCMA. We found large variability in the 10 d mean observed ΔCH4 (∼50–250 ppbv) and monthly afternoon methane emissions rates (10.1–30.4 kg s−1) within and between the years of our study period. A recently released high-resolution regional methane emission inventory developed for the NYCMA performed better than other global and national inventories against the rooftop observations but still underestimated methane emissions, especially in winter. The estimates of methane emissions correlated with those of carbon monoxide (CO) emissions, determined from coincident measurements, suggesting a common city-scale incomplete combustion source for both methane and CO. Our analysis of these continuous measurements also implies a consistent diurnal cycle in urban methane emissions from the NYCMA, which reveals a potential bias in traditional afternoon-only approaches in this domain. This work highlights the usefulness of a long term, multi-species approach to constrain urban greenhouse gas emissions and their sources.

Urban aerosol pollution is evolving rapidly with global change and poses significant risks to public health. Measurements and machine learning-enabled chemical analysis of aerosol from a suburb of New York City in 2023 reveal emerging sources and drivers in a modern megacity. Regional wildfire smoke averaged 25% of organic aerosol (OA) mass and drove variability via enhancements of biogenic OA formation within smoke plumes. This biogenic OA contributed 40% of aerosol mass. Urban heatwaves enhanced both biogenic and anthropogenic sources, with ~20% of OA mass exhibiting significant heatwave sensitivity. For the first time, volatile chemical product (VCP) compounds were directly observed, speciated, and characterized in urban aerosol. Contributions to total OA averaged 15%, double the contribution from traffic. Together, this work identifies wildfire smoke, biogenic emissions, heat, and emerging anthropogenic emissions as critical global change vulnerabilities for North American urban aerosol pollution that pose unique challenges for control strategies.

The Arctic–Boreal Zone is rapidly warming, impacting its large soil carbon stocks. Here we use a new compilation of terrestrial ecosystem CO2 fluxes, geospatial datasets and random forest models to show that although the Arctic–Boreal Zone was overall an increasing terrestrial CO2 sink from 2001 to 2020 (mean ± standard deviation in net ecosystem exchange, −548 ± 140 Tg C yr−1; trend, −14 Tg C yr−1; P < 0.001), more than 30

The subtropics are influenced by stratosphere-troposphere exchange processes through the subtropical jet streams and tropopause folding events, which are commonly identified by the opposing gradients of ozone (O3) and carbon monoxide (CO) and thus their ratio. Here, we used airborne observations of CO and O3, as well as the global three-dimensional ECHAM5/MESSy Atmospheric Chemistry (EMAC) model, to investigate whether there is another important mechanism that conditions the subtropics. We show that high O3–CO ratios extend deeply into the troposphere in the subtropics, which is evident in both in situ observations and model results. Tropospheric photochemistry leads to similar O3–CO ratios as those for stratospheric air diluted into the troposphere. In the upper tropical troposphere, frequent deep convective events produce lightning that leads to high concentrations of nitrogen oxides (NOx≡NO+NO2), which drive O3 production and which further catalyze the recycling of hydroxyl (OH) radicals, which reduces CO. These lightning-affected air masses can be transported from the tropics into the subtropics via the Hadley circulation. We have excluded NO production through lightning in a sensitivity run of the EMAC model and see an annual relative reduction of the O3–CO ratio of up to almost 50 % in the tropics and up to 40 % in the northern subtropics, with even larger seasonal variability and major effects on the vertical profiles of O3 and CO. We therefore show that photochemistry is an additional key factor alongside stratosphere-troposphere mixing in determining O3-rich and CO-poor air masses in the troposphere.

The Arctic-Boreal Zone (ABZ) is rapidly warming, impacting its large soil carbon stocks. We use a new compilation of terrestrial ecosystem CO2 fluxes, geospatial datasets and random forest models to show that although the ABZ was an increasing terrestrial CO2 sink from 2001 to 2020 (mean ± standard deviation in net ecosystem exchange: -548 ± 140 Tg C yr-1; trend: -14 Tg C yr-1, p<0.001), more than 30% of the region was a net CO2 source. Tundra regions may have already started to function on average as CO2 sources, demonstrating a critical shift in carbon dynamics. After factoring in fire emissions, the increasing ABZ sink was no longer statistically significant (budget: -319 ± 140 Tg C yr-1; trend: -9 Tg C yr-1), with the permafrost region becoming CO2 neutral (budget: -24 ± 123 Tg C yr-1; trend: -3 Tg C yr-1), underscoring the importance of fire in this region.### Competing Interest StatementThe authors have declared no competing interest.

Landscapes are often assumed to be homogeneous when interpreting eddy covariance fluxes, which can lead to biases when gap-filling and scaling up observations to determine regional carbon budgets. Tundra ecosystems are heterogeneous at multiple scales. Plant functional types, soil moisture, thaw depth, and microtopography, for example, vary across the landscape and influence net ecosystem exchange (NEE) of carbon dioxide (CO2) and methane (CH4) fluxes. With warming temperatures, Arctic ecosystems are changing from a net sink to a net source of carbon to the atmosphere in some locations, but the Arctic's carbon balance remains highly uncertain. In this study we report results from growing season NEE and CH4 fluxes from an eddy covariance tower in the Yukon–Kuskokwim Delta in Alaska. We used footprint models and Bayesian Markov chain Monte Carlo (MCMC) methods to unmix eddy covariance observations into constituent land-cover fluxes based on high-resolution land-cover maps of the region. We compared three types of footprint models and used two land-cover maps with varying complexity to determine the effects of these choices on derived ecosystem fluxes. We used artificially created gaps of withheld observations to compare gap-filling performance using our derived land-cover-specific fluxes and traditional gap-filling methods that assume homogeneous landscapes. We also compared resulting regional carbon budgets when scaling up observations using heterogeneous and homogeneous approaches. Traditional gap-filling methods performed worse at predicting artificially withheld gaps in NEE than those that accounted for heterogeneous landscapes, while there were only slight differences between footprint models and land-cover maps. We identified and quantified hot spots of carbon fluxes in the landscape (e.g., late growing season emissions from wetlands and small ponds). We resolved distinct seasonality in tundra growing season NEE fluxes. Scaling while assuming a homogeneous landscape overestimated the growing season CO2 sink by a factor of 2 and underestimated CH4 emissions by a factor of 2 when compared to scaling with any method that accounts for landscape heterogeneity. We show how Bayesian MCMC, analytical footprint models, and high-resolution land-cover maps can be leveraged to derive detailed land-cover carbon fluxes from eddy covariance time series. These results demonstrate the importance of landscape heterogeneity when scaling carbon emissions across the Arctic.

As cities and states across the United States increasingly commit to building decarbonization, gas stoves are garnering public health attention because, in addition to contributing to greenhouse gas emissions, they may pose a respiratory health risk. Disadvantaged groups, as defined by demographic, socioeconomic, and residential factors, are often late adopters of new technology. To ensure that disadvantaged groups are not left behind from this transition, WE ACT for Environmental Justice, a New York City community-based environmental justice organization, implemented the first pilot of gas-to-electric stove transition in low-income housing. The goal of this mixed-methods study was to evaluate the effect of this intervention on indoor air quality and to characterize the distinct experiences of low-income residents. Twenty low-income households were recruited and randomized to an intervention (replacement of gas stove with induction stove) and a control arm. Between October 2021 and July 2022, three 168-hr long monitoring campaigns were conducted to assess indoor air quality (NO2, CO, and PM2.5) and stove use pre- and postintervention. The impact of cooking events on indoor air quality was further evaluated during controlled cooking tests carried out in both gas and induction homes. To identify key characteristics of the end-user experience throughout this intervention, participants were invited to join focus group discussions. Between baseline and endline, 168-hr average NO2 and CO concentrations decreased in both study arms, likely due to seasonality factors. Still, the induction arm showed a 56 % reduction (95 % CI: -61.9 %, -15.2 %) in mean daily NO2 concentration compared to the gas arm. During controlled cooking tests, the median background NO2 concentration (18 ppb) in gas homes rose to 197 ppb and negligibly changed in induction homes. During focus group discussions, participants unanimously reported being pleased with the transition and highlighted quality of life improvements resulting from the unexpected intervention's ability to address energy insecurity concerns. Taken together, our quantitative and qualitative results suggest that decarbonization energy transitions can improve health by reducing indoor NO2 but need to extend beyond single appliance swap-out to address health issues resulting from energy insecurity.

Recent studies have shown that methane emissions are underestimated by inventories in many US urban areas. This has important implications for climate change mitigation policy at the city, state, and national levels. Uncertainty in both the spatial distribution and sectoral allocation of urban emissions can limit the ability of policy makers to develop appropriately focused emission reduction strategies. Top-down emission estimates based on atmospheric greenhouse gas measurements can help to improve inventories and inform policy decisions. This study presents a new high-resolution (0.02 × 0.02°) methane emission inventory for New York City and its surrounding area, constructed using the latest activity data, emission factors, and spatial proxies. The new high-resolution inventory estimates of methane emissions for the New York-Newark urban area are 1.3 times larger than those for the gridded Environmental Protection Agency inventory. We used aircraft mole fraction measurements from nine research flights to optimize the high-resolution inventory emissions within a Bayesian inversion. These sectorally optimized emissions show that the high-resolution inventory still significantly underestimates methane emissions within the New York-Newark urban area, primarily because it underestimates emissions from thermogenic sources (by a factor of 2.3). This suggests that there remains a gap in our process-based understanding of urban methane emissions.

Global climate change is influencing the seasonal cycle amplitude of atmospheric CO2 (SCA), with the strongest increases at northern high latitudes (NHL; >45° N). In this Review, we explore the changes and underlying mechanisms influencing the NHL SCA, focusing on Arctic and boreal terrestrial ecosystems. Latitudinal gradients in the SCA are largely governed by seasonality in temperature and primary production, and their influence on ecosystem carbon dynamics. In the NHL, the SCA has increased by 50% since the 1960s, mostly due to enhanced seasonality in net carbon dioxide (CO2) exchange in NHL terrestrial ecosystems. Temperature most strongly influences this trend, owing to warming impacts on growing season length and plant productivity; CO2 fertilization effects have a secondary role. Eurasian boreal ecosystems exert the strongest influence on the SCA, and spring and summer are the most influential seasons. Enhanced ecosystem respiration during the non-growing season exhibits most uncertainty in the SCA response to global and landscape drivers. Observed changes in the seasonal amplitude are projected to continue. Key priorities include extending carbon flux and ecosystem observation networks, particularly in tundra ecosystems, and including drivers such as vegetation cover and permafrost in process models to better simulate seasonal dynamics of net CO2 exchange in the NHL. Changes in the seasonal cycle amplitude of atmospheric CO2 (SCA) reflect large-scale changes in the global carbon cycle. This Review summarizes the positive SCA trend in the northern high latitudes, where the signal is strongest, and explores the underlying mechanisms driving the trend and their relative importance.