Prior studies have shown that people of color (POC) in the United States are exposed to higher levels of pollution than non-Hispanic White people. We show that the city of Denver, Colorado, displays similar race- and ethnicity-based air pollution disparities by using a combination of high-resolution satellite data, air pollution modeling, historical demographic information, and areal apportionment techniques. TROPOMI NO2 columns and modeled PM2.5 concentrations from 2019 are higher in communities subject to redlining. We calculated and compared Spearman coefficients for pollutants and race at the census tract level for every city that underwent redlining to contextualize the disparities in Denver. We find that the location of polluting infrastructure leads to higher populations of POC living near point sources, including 40% higher Hispanic and Latino populations. This influences pollution distribution, with annual average PM2.5 surface concentrations of 6.5 mu g m(-3) in census tracts with 0-5% Hispanic and Latino populations and 7.5 mu g m(-3) in census tracts with 60-65% Hispanic and Latino populations. Traffic analysis and emission inventory data show that POC are more likely to live near busy highways. Unequal spatial distribution of pollution sources and POC have allowed for pollution disparities to persist despite attempts by the city to rectify them. Finally, we identify the core causes of the pollution disparities to provide direction for remediation.

<p>The likelihood for successful emission control and mitigation efforts of trace gases having adverse environmental effects can be enhanced by using a multi-faceted framework for quantifying and understanding emissions. While bottom-up activity-based inventories provide a quantification of various source sectors, appropriately designed atmosphere-based (top-down) approaches are able to independently evaluate the inventory and further refine temporal changes and spatial distributions.  Differences between bottom-up and top-down estimates are oftentimes observed and represent prime opportunities for increasing understanding and refining estimates of emissions.  Here we will present results derived from atmospheric observations made in the remote global atmosphere as well as from our North American measurement network.  The remote global observations enabled the identification of an apparent violation of the Montreal Protocol.  After our atmospheric measurements identified this unexpected issue, fairly quick resolution appears to have been achieved, in part due to the additional understanding of likely underlying causes provided by industry experts. Our North American measurement network also allows for trace-gas emission estimates on national and state scales.  Results from these efforts will be discussed, with an emphasis on describing how the interaction between inventory-derived and atmosphere-based information has led to an improved understanding of emission magnitudes along with identifying areas needing additional study.</p>

Urban air pollution is quite complex and exhibits significant spatial variability within communities. Traditional centralized monitoring captures temporal variability as well as the long-term trends of air pollution very well, but mapping spatial variability of air pollution in communities at high resolution would require large number of air quality monitors distributed across the community. Mobile monitoring complements stationary monitoring approaches by measuring pollution levels on accessible road networks in urban communities. This paper presents the application of an integrated mobile measurement and data analysis approach to study community-level air pollution patterns, separate the regional background and local contributions, and identify high pollution zones for black carbon (BC), ultrafine particles (UFP), and fine particulate matter (PM2.5). This study was conducted during different periods from 2017 to 2019 in three California cities (Richmond, Stockton, and Commerce) with diverse community and source characteristics. The study found that traffic was the dominant primary source of air pollution in both urban and suburban settings. Urban areas adjacent to large area sources, such as ports and railyards had increased pollutant enhancements due to either direct or indirect emissions, while suburban areas containing unpaved roads were observed to have large PM2.5 enhancement due to the resuspended dust. The analysis disaggregated the contribution of regional and local sources to local air pollution and found that regional background sources contributed up to 75% of the PM2.5 concentrations, while local sources contributed more than half of BC and UFP. The study suggests that 15-30 repeated measurements may be sufficient to map the general air pollution patterns within the community, while some extreme high pollution zones can be identified with fewer repeats (5-10). These techniques can be used for initial screening of air pollution variability within the community, and help identify priority areas for conducting follow-up long-term air quality measurements. The techniques also informs the relative importance of regional and local actions to reduce community pollutant levels.

The oil and natural gas sector is the second largest source of methane (CH4) emissions in the U.S. (28% in 2018), and several studies have suggested that real-world emissions from this sector may be higher than previously reported estimates. This study was designed to measure methane emissions from non-associated (i.e., produced without crude oil extraction) natural gas (NG) well pads in California, by applying a novel mobile measurement system combined with a source characterization model. This study surveyed 86 non-associated NG well pads (66 active and 20 idle well pads) in northern California during a two-week field campaign in 2018. The mean emission rate from active non-associated NG well pads was estimated to be 9.5 (95% CI: 6.1–14.6) kg CH4/d. By extrapolating the survey results to the entire state, the annual methane emissions from all active non-associated NG well pads were 3.2 (95% CI: 2.0–5.1) Gg CH4/y, which represents roughly 5% of CH4 emissions from the oil and natural gas production sector in California. The methane emission rates exhibited a fat-tail distribution, with roughly 15% of the active well pads responsible for >85% of the total measured emissions. This result suggests that controlling a small number of large emitters can significantly reduce methane emissions from this sub-sector. Methane emissions were also detected from over 60% of the idle well pads, with a similar fat-tail distribution but much smaller magnitudes than the active well pads. Quick screening tools to identify and fix these unexpected fugitive leaks can offer useful real-world emission reductions. The mobile measurement system was also able to detect emissions from more well pads when compared to the use of an optical gas imaging camera, which suggests that mobile measurement techniques can be an effective screening tool to support leak detection and repair (LDAR) programs.

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NOx emissions. Second, the response of O3 to decreased NOx emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheri...

Soils are a source of atmospheric nitrogen oxides (NOx), especially in regions with significant cropland where nitrogen (N) fertilizers are used to enhance crop yields. The magnitude of soil NOx emissions, however, varies substantially by region, depending on the local land use pattern and management activities. We estimated soil NOx emissions in California based on the DeNitrification-DeComposition (DNDC) biogeochemical model, linked to a detailed spatial-temporal differentiated California-specific database. The DNDC-generated surface fluxes were used in the Community Multiscale Air Quality (CMAQ) model to evaluate impacts of soil NOx emissions on formation of ambient particulate (PM2.5) nitrate in the San Joaquin Valley (SJV) where cropland is the dominant land use. The DNDC-generated soil NOx emissions contribute approximately 1.1% of total anthropogenic NOx emissions in California, at an emission rate of roughly 24 t day(-1) (as NO2) statewide and 9 t day(-1) in the SJV. Cropland is the dominant source of soil NOx emissions in California, contributing nearly 60% of statewide soil NOx emissions, driven principally by fertilizer use. The PM2.5 nitrate concentrations simulated by CMAQ using the DNDC-generated soil NOx emissions are compatible with those observed in the SJV, suggesting that soil NOx emissions have limited impacts on PM2.5 nitrate formation in the atmosphere. Our emission and air quality modeling results are further supported by long-term ambient NOx-to-carbon monoxide (CO) and satellite NO2 data analyses in the SJV, which showed diurnal, monthly, and annual trends consistent with characteristics of NOx sources dominated by traffic combustion in both urban and agricultural regions.

California methane (CH4) emissions are quantified for three years from two tower networks and one aircraft campaign. We used backward trajectory simulations and a mesoscale Bayesian inverse model, initialized by three inventories, to achieve the emission quantification. Results show total statewide CH4 emissions of 2.05 ± 0.26 (at 95% confidence) Tg/yr, which is 1.14 to 1.47 times greater than the anthropogenic emission estimates by California Air Resource Board (CARB). Some of differences could be biogenic emissions, superemitter point sources, and other episodic emissions which may not be completely included in the CARB inventory. San Joaquin Valley (SJV) has the largest CH4 emissions (0.94 ± 0.18 Tg/yr), followed by the South Coast Air Basin, the Sacramento Valley, and the San Francisco Bay Area at 0.39 ± 0.18, 0.21 ± 0.04, and 0.16 ± 0.05 Tg/yr, respectively. The dairy and oil/gas production sources in the SJV contribute 0.44 ± 0.36 and 0.22 ± 0.23 Tg CH4/yr, respectively. This study has important policy implications for regulatory programs, as it provides a thorough multiyear evaluation of the emissions inventory using independent atmospheric measurements and investigates the utility of a complementary multiplatform approach in understanding the spatial and temporal patterns of CH4 emissions in the state and identifies opportunities for the expansion and applications of the monitoring network.

Methane is a powerful greenhouse gas and is targeted for emissions mitigation by the US state of California and other jurisdictions worldwide(1,2). Unique opportunities for mitigation are presented by point-source emitters-surface features or infrastructure components that are typically less than 10 metres in diameter and emit plumes of highly concentrated methane(3). However, data on point-source emissions are sparse and typically lack sufficient spatial and temporal resolution to guide their mitigation and to accurately assess their magnitude(4). Here we survey more than 272,000 infrastructure elements in California using an airborne imaging spectrometer that can rapidly map methane plumes(5-7). We conduct five campaigns over several months from 2016 to 2018, spanning the oil and gas, manure-management and waste-management sectors, resulting in the detection, geolocation and quantification of emissions from 564 strong methane point sources. Our remote sensing approach enables the rapid and repeated assessment of large areas at high spatial resolution for a poorly characterized population of methane emitters that often appear intermittently and stochastically. We estimate net methane point-source emissions in California to be 0.618 teragrams per year (95 per cent confidence interval 0.523-0.725), equivalent to 34-46 per cent of the state's methane inventory(8) for 2016. Methane 'super-emitter' activity occurs in every sector surveyed, with 10 per cent of point sources contributing roughly 60 per cent of point-source emissions-consistent with a study of the US Four Corners region that had a different sectoral mix(9). The largest methane emitters in California are a subset of landfills, which exhibit persistent anomalous activity. Methane point-source emissions in California are dominated by landfills (41 per cent), followed by dairies (26 per cent) and the oil and gas sector (26 per cent). Our data have enabled the identification of the 0.2 per cent of California's infrastructure that is responsible for these emissions. Sharing these data with collaborating infrastructure operators has led to the mitigation of anomalous methane-emission activity(10).

Rapid increase in atmospheric methane (CH4) mixing ratios over the past century is attributable to the intensification of human activities. Information on spatially explicit source contributions is needed to develop efficient and cost-effective CH4 emission reduction and mitigation strategies to addresses near-term climate change. This study collected long-term ambient CH4 measurements at Mount Wilson Observatory (MWO) in Los Angeles, California, to estimate the annual CH4 emissions from the portion of Los Angeles County that is within the South Coast Air Basin (SCLA). The measurement-based CH4 emission estimates for SCLA ranged from 3.95 to 4.89 million metric tons (MMT) carbon dioxide equivalent (CO2e) per year between 2012 and 2016. Source apportionment of CH4, CO, CO2, and volatile organic compounds (VOCs) measurements were used to evaluate source categories that contributed to ambient CH4 mixing ratio enhancements (ΔCH4) at SCLA between 2014 and 2016. Results suggested ΔCH4 contributions of 56-79% from natural gas sources, 7-31% from landfills, and 4-15% from transportation sources. The SCLA-specific CH4 emission estimate made using a research grade gridded CH4 emission inventory suggested contributions of 47% from natural gas sources and 50% from landfills. Subsequent airborne measurements determined that CH4 emissions from two major CH4 sources in SCLA were significantly smaller in magnitude than previously thought. This study highlights the importance of studying the variabilities of CH4 emissions across California for policy makers and stakeholders alike.

The Paris Agreement is an historic achievement. For the first time, effectively all nations have committed to limit their greenhouse gas emissions and take other actions to limit and adapt to climate change to hold “the increase in the global average temperature to well below 2°C above pre-industrial levels and pursu[e] efforts to limit the temperature increase to 1.5°C above pre-industrial levels.” But the Agreement and supporting climate policies must be strengthened substantially within the next five years to prevent catastrophic warming. Until now, no specific plan or policy roadmap has been proposed to provide a realistic and reasonable chance of limiting global temperatures to safe levels and preventing unmanageable climate change. This report provides such a plan—an outline of specific solutions that serve as the building blocks for a three-lever strategy to limit warming to under 2°C and thus avoid extreme and unmanageable climate changes.

Air quality improvement in Los Angeles, California is reviewed with an emphasis on aspects that may inform air quality policy formulation in developing cities. In the mid-twentieth century the air quality in Los Angeles was degraded to an extent comparable to the worst found in developing cities today; ozone exceeded 600 ppb and annual average particulate matter <10 μm reached ~150 mg∙m–3. Today's air quality is much better due to very effective emission controls; e.g., modern automobiles emit about 1% of the hydrocarbons and carbon monoxide emitted by vehicles of 50 years ago. An overview is given of the emission control efforts in Los Angeles and their impact on ambient concentrations of primary and secondary pollutants; the costs and health benefits of these controls are briefly summarized. Today's developing cities have new challenges that are discussed: the effects of regional pollution transport are much greater in countries with very high population densities; often very large current populations must be supplied with goods and services even while economic development and air quality concerns are addressed; and many of currently developing cities are located in or close to the tropics where photochemical processing of pollution is expected to be more rapid than at higher latitudes. The air quality issues of Beijing are briefly compared and contrasted with those of Los Angeles, and the opportunities for co-benefits for climate and air quality improvement are pointed out.