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China has been placing a substantial focus on biogas for reducing energy consumption and carbon dioxide (CO2) emissions. The operation mode of biogas systems may make the CO2 reduction target over-optimistic. There is limited research to investigate the influential factors that may be causing the gap between the actual and theoretical CO2 reduction costs of biogas systems in China. In this research, by using field survey data of 209 biogas users and 489 non-biogas users from 19 villages in 2015, the gap between actual and theoretical unit CO2 reduction cost is quantified at approximately 156 USD/t CO2. By employing the Logarithmic Mean Divisia Index I (LMDI) model, it is found that both the cost effect (48%) and the reduction effect (52%) contribute to the unit CO2 reduction cost gap. Four influential factors–household labor, accessibility to the energy resource, acceptance of biogas technology, and subsidy–significantly narrow the gap between actual and theoretical CO2 reduction costs, while the levelized subsidy contributes to widening the gap. On average, biogas systems should be operated for at least four years and the substitution rate should be more than 67% in order to keep the gap between actual and theoretical CO2 reduction costs under 50%.

The TROPOspheric Monitoring Instrument (TROPOMI) is used to derive top-down NOX emissions for two large power plants and three megacities in North America. We first re-process the vertical column N...

Energy consumption from central heating has rapidly increased in the cities of the North China Plain (NCP). The increasing use of natural gas in the central heating supply system may have altered the spatial and temporal patterns of CO2 emissions from central heating, yet the quantitative impacts are poorly understood. Here we detect the spatio-temporal dynamics of CO2 emissions of central heating from 2012 to 2016 at the prefectural-city level in the NCP region, by using the satellite NPP-VIIRS nighttime light data and a panel regression model to estimate CO2 emissions on a 5 × 5 km2 grid. We find that despite a slight decrease (2%) in 2014 under the “Natural Gas Utilization Policy”, CO2 emissions continued to grow. Between 2012 and 2016, CO2 emissions from central heating in the NCP increased from 106 to 121 Tg, although CO2 emissions declined by 12% in Beijing due to the increasing contribution of natural gas boilers. The gridded CO2 emissions map shows that over 2012–2016 coal burning is the main driving force of CO2 emissions in both urban and non-urban regions, despite the increasing fraction of gas-based heating. Our results contribute to city-level policymaking on carbon reduction and climate change mitigation. The high-resolution gridded CO2 emissions can also be applied in physical models to facilitate carbon cycle studies.

There exist substantial differences in top-of-atmosphere direct radiative forcing of aerosols due to a region's economic production (RFp) and consumption (RFc), in the context of economic globalization, trade and globalizing air pollution. Yet an explicit systematic analysis of all socioeconomic and atmospheric factors determining the RF difference is lacking. Here, we evaluate five socioeconomic (population, per capita output, emission intensity) and atmospheric (chemical efficiency and radiative efficiency) factors that determine a region's RFp, RFc and their difference. We consider the RF of secondary inorganic aerosols, primary organic aerosols and black carbon by 10 regions worldwide in 2007. The population size varies by a factor of nine across the regions, and per capita output by 40 times from both production- and consumption-based perspectives. The cross-regional spread reaches a factor of 181 (species dependent) for production-based emission intensity and a factor of 96 for consumption-based intensity. From one region to another, production-based chemical efficiency changes within a factor of 5 and consumption-based efficiency within a factor of 3.5. Radiative efficiency varies slightly across the regions (within 2) from both production- and consumption-based perspectives. Although socioeconomic factors are often a greater driver for the difference between a source region's RFp and RFc, the atmospheric factors are also important for many source regions and species. Our results contribute to regional attribution of climate change and establishment of effective international collaborative mitigation strategies.

China experienced rapid urbanization and industrialization in recent years, which resulted in large increases of nitrogen dioxide (NO2), particularly in urban areas. We analyze the spatiotemporal variations of the vertical column densities (VCDs) of tropospheric NO2 with the level of urban development across China during the period 2005–2016. Nighttime light (NTL) data are applied as a proxy for urban development to investigate the relationship between NO2 pollution and urban development. Both NO2 column data and NTL data are observed by satellite measurements. The annual mean of NO2 VCDs is presented on a grid basis. The average annual variations of NO2 VCDs and NTL value are detected for all 341 prefectural cities. Two-thirds of the cities reached their peak NO2 pollution level around 2010–2012, and decreased afterward. About 10% of the western cities kept on increasing their NO2 levels until 2016. All cities are classified into four categories with respect to the average annual variations of NO2 /NTL in 2005–2010, and 2011–2016. Approximately 62% of the cities turned the average annual variations of NO2 /NTL from positive to negative. 19% of the cities are in the positive-positive category and 11% of the cities are in the negative-negative category. The remaining 8% of the cities changed their ratios from negative to positive. We summarize the national air pollution regulations, and our results show the effectiveness of the regulations for most eastern China cities. This work can help to design more efficient regional emission reduction policies with sustainable development.

Mercury (Hg) is a naturally occurring element in the Earth's crust. It can be harmful to human health when released in large quantities and/or converted to the neurotoxicant methyl mercury in aquatic ecosystems. This study analyzes global and regional trends in anthropogenic Hg releases to the atmosphere between 2010 and 2015, as well as the associated trends in modeled and measured Hg concentrations at sites around the world. In general, we find that global Hg emissions and concentrations have grown slightly in this period, as declines from the phase-out of commercial Hg use in the developed world have been more than matched by increases in Hg-related activities in the industrializing countries of the world. We estimate that global Hg emissions between 2010 and 2015 have grown at a rate of 1.8%/yr, from 2188 Mg (+44%/-20%, 80% C.I.) in 2010 to 2390 Mg (+42%/-19%, 80% C.I.) in 2015. Regionally, emissions declined over this period in the U.S. (−10%), OECD Europe (−5.8%), and Canada (−3.2%), while they increased in Central America (+5.4%), South Asia (+4.6%), and Eastern Africa (+4.0%). East Asia remained the largest emitting region at 1012 Mg in 2015, though growth there has slowed significantly in recent years. The production of Hg (+7.9%), caustic soda (+6.3%), and cement (+6.3%) showed the highest increases by source type, though artisanal and small-scale gold mining (ASGM) was the single largest source of emissions in 2015 (775 Mg). The commercial use of Hg in dental applications (−5.6%) and electrical equipment (−5.2%) continued to decline. These emission trends show a continuation of the regional and sectoral shifts that began in the 1970s, but with a resulting reversal in global trends, because the benefits from Hg phase-out in North America and Europe have been largely realized and industrial growth in developing countries has begun to dominate. The emission trends are in agreement with trends in modeled and measured concentrations, which show small declines in surface air total gaseous Hg concentrations in eastern North America and Western Europe between 2010 and 2015, but slight increases for much of the rest of the world, driven by the continued increases in emissions from Asia and from ASGM. Our results suggest that reductions of Hg in the North Atlantic region have been largely successful, and focus now needs to shift to Asia and to the continued practice of ASGM worldwide.

In this work, we investigate the NOx emissions inventory in Seoul, South Korea, using a regional ozone monitoring instrument (OMI) NO2 product derived from the standard NASA product. We first develop a regional OMI NO2 product by recalculating the air mass factors using a high-resolution (4 km × 4 km) WRF-Chem model simulation, which better captures the NO2 profile shapes in urban regions. We then apply a model-derived spatial averaging kernel to further downscale the retrieval and account for the subpixel variability. These two modifications yield OMI NO2 values in the regional product that are 1.37 times larger in the Seoul metropolitan region and >2 times larger near substantial point sources. These two modifications also yield an OMI NO2 product that is in better agreement with the Pandora NO2 spectrometer measurements acquired during the South Korea–United States Air Quality (KORUS-AQ) field campaign. NOx emissions are then derived for the Seoul metropolitan area during the KORUS-AQ field campaign using a top-down approach with the standard and regional NASA OMI NO2 products. We first apply the top-down approach to a model simulation to ensure that the method is appropriate: the WRF-Chem simulation utilizing the bottom-up emissions inventory yields a NOx emissions rate of 227±94 kt yr −1 , while the bottom-up inventory itself within a 40 km radius of Seoul yields a NOx emissions rate of 198 kt yr −1 . Using the top-down approach on the regional OMI NO2 product, we derive the NOx emissions rate from Seoul to be 484±201 kt yr −1 , and a 353±146 kt yr −1 NOx emissions rate using the standard NASA OMI NO2 product. This suggests an underestimate of 53 % and 36 % in the bottom-up inventory using the regional and standard NASA OMI NO2 products respectively. To supplement this finding, we compare the NO2 and NOy simulated by WRF-Chem to observations of the same quantity acquired by aircraft and find a model underestimate. When NOx emissions in the WRF-Chem model are increased by a factor of 2.13 in the Seoul metropolitan area, there is better agreement with KORUS-AQ aircraft observations and the recalculated OMI NO2 tropospheric columns. Finally, we show that by using a WRF-Chem simulation with an updated emissions inventory to recalculate the air mass factor (AMF), there are small differences ( ∼8 %) in OMI NO2 compared to using the original WRF-Chem simulation to derive the AMF. This suggests that changes in model resolution have a larger effect on the AMF calculation than modifications to the South Korean emissions inventory. Although the current work is focused on South Korea using OMI, the methodology developed in this work can be applied to other world regions using TROPOMI and future satellite datasets (e.g., GEMS and TEMPO) to produce high-quality region-specific top-down NOx emissions estimates.

To link short-term exposures of air pollutants to health outcomes, scientists must use high temporal and spatial resolution estimates of PM2.5 concentrations. In this work, we develop a daily PM2.5 product at 1 × 1 km2 spatial resolution across the eastern United States (east of 90° W) with the aid of 1 × 1 km2 MAIAC aerosol optical depth (AOD) data, 36 × 36 km2 WRF-Chem output, 1 × 1 km2 land-use type from the National Land Cover Database, and 0.125° × 0.125° ERA-Interim re-analysis meteorology. A gap-filling technique is applied to MAIAC AOD data to construct robust daily estimates of AOD when the satellite data are missing (e.g., areas obstructed by clouds or snow cover). The input data are incorporated into a multiple-linear regression model trained to surface observations of PM2.5 from the EPA Air Quality System (AQS) monitoring network. The model generates a high-fidelity estimate (r2 = 0.75 using a 10-fold random cross-validation) of daily PM2.5 throughout the eastern United States. Of the inputs to the statistical model, WRF-Chem output (r2 = 0.66) is the most important contributor to the skill of the model. MAIAC AOD is also a strong contributor (r2 = 0.52). Daily PM2.5 output from our statistical model can be easily integrated into county-level epidemiological studies. The novelty of this project is that we are able to simulate PM2.5 in a computationally efficient manner that is constrained to ground monitors, satellite data, and chemical transport model output at high spatial resolution (1 × 1 km2) without sacrificing the temporal resolution (daily) or spatial coverage (>2,000,000 km2).

Improving air quality is an important driving force for China’s move toward clean energy. Since 2017, the “coal-to-gas” and “coal-to-electricity” strategies have been extensively implemented in northern China, aiming at reducing dispersed coal consumption and related air pollution by promoting the use of clean and low-carbon fuels. Our analyses show that on top of meteorological influences, the effective emission mitigation measures achieved an average decrease of fine particulate matter (PM2.5) concentrations of ∼14% in Beijing and surrounding areas (the “2+26” pilot cities) in winter 2017 compared to the same period of 2016, where the dispersed coal control measures contributed ∼60% of the total PM2.5 reductions. However, the localized air quality improvement was accompanied by a contemporaneous ∼15% upsurge of PM2.5 concentrations over large areas in southern China. We find that the pollution transfer that resulted from a shift in emissions was of a high likelihood caused by a natural gas shortage in the south due to the coal-to-gas transition in the north. The overall shortage of natural gas greatly jeopardized the air quality benefits of the coal-to-gas strategy in winter 2017 and reflects structural challenges and potential threats in China’s clean-energy transition. Our finding highlights the importance and necessity of synergy between environmental and energy policymaking to address the grand challenge of an actionable future to achieve the cobenefits of air quality, human health, and climate.

Understanding the spatio-temporal heterogeneous effects of socioeconomic and meteorological factors on CO

Observing the spatial heterogeneities of NO2 air pollution is an important first step in quantifying NOx emissions and exposures. This study investigates the capabilities of the Tropospheric Monito...

Understanding the spatio-temporal heterogeneous effects of socioeconomic and meteorological factors on CO2 emissions from combinations of different district heating systems with “Coal-to-Gas” transition can contribute to the development of future low-carbon energy systems that are efficient and effective. This work downscales city-level CO2 emissions to a 3 × 3 km2 gridded level in northern China during 2012 to 2018. By employing the Geographically and Temporally Weighted Regression (GTWR) model, nighttime light (NTL) data are adopted as a proxy of the level of urbanization, and the Temperature-Humidity-Wind (THW) Index is used as a proxy of meteorological factors in the downscaling model. The results show that, for more than 85% of the cities, urbanization significantly enhances the CO2 emissions of district heating systems, while the THW Index shows negative impacts on CO2 emissions. Significant spatial and temporal heterogeneity exists. The grids with the highest CO2 emissions from coal-fired boilers (grids with annual variation >0.59 Gg CO2/year) are mainly located in nonurban areas of the two megacities Beijing and Tianjin and also in the capital cities of each province. Urbanization has larger effects on the CO2 emissions of natural gas-fired boilers than of coal-fired boilers and combined heat and power (CHP). The average growth rate of CO2 emissions of gas-fired boilers in the urban areas of the study regions was approximately 4.7 times that of nonurban areas. The spatio-temporal heterogeneous impacts of urbanization on CO2 emissions should therefore be considered in future discussions of clean heating policies and climate response strategies.

Residential solid fuel combustion makes a major contribution to black carbon (BC) emissions in China. A new estimation of BC emissions from rural solid biomass and coal consumption has been derived from field survey data. The following new contributions are made: (1) emission factors are collected and reviewed; (2) household energy data are collected from field survey data and from the literature; (3) a new extrapolation method is developed to extend the field survey data to other locations; (4) the ownership and usage of two stove types are estimated and considered in the emission calculations; and (5) uncertainties associated with the estimation results are quantified. It is shown that rural households with higher income will consume less biomass but more coal. Agricultural acreage and temperature also significantly influence the amount of solid fuel consumed in rural areas. It is estimated that 640 ± 245 Gg BC/y were emitted to the atmosphere due to residential solid fuel consumption in rural China in 2014. Emissions of BC from straw, wood, and coal contributed 42 ± 13%, 36 ± 15%, and 22 ± 10% of the total, respectively. We show that effective BC mitigation (a reduction of 47%) could be obtained through widespread introduction of improved stoves in rural households.

There are more than 30,000 biomass- and fossil-fuel-burning power plants now operating worldwide, reflecting a tremendously diverse infrastructure, which ranges in capacity from less than a megawatt to more than a gigawatt. In 2010, 68.7% of electricity generated globally came from these power plants, compared with 64.2% in 1990. Although the electricity generated by this infrastructure is vital to economic activity worldwide, it also produces more CO2 and air pollutant emissions than infrastructure from any other industrial sector. Here, we assess fuel- and region-specific opportunities for reducing undesirable air pollutant emissions using a newly developed emission dataset at the level of individual generating units. For example, we find that retiring or installing emission control technologies on units representing 0.8% of the global coal-fired power plant capacity could reduce levels of PM2.5 emissions by 7.7–14.2%. In India and China, retiring coal-fired plants representing 1.8% and 0.8% of total capacity can reduce total PM2.5 emissions from coal-fired plants by 13.2% and 16.0%, respectively. Our results therefore suggest that policies targeting a relatively small number of ‘super-polluting’ units could substantially reduce pollutant emissions and thus the related impacts on both human health and global climate. After developing a unit-based air pollutants emission inventory of more than 30,000 fossil fuel power plants operating worldwide in 2010, the authors find that retiring or implementing controlling measures on coal-fired power plants, representing 0.8% of global capacity, could reduce PM2.5 emissions from coal-fired plants by up to 14.2%.

Emission inventory development for air pollutants, by compiling records from individual emission sources, takes many years and involves extensive multi-national effort. A complementary method to estimate air pollution emissions is in the use of satellite remote sensing. In this study, NO2 observations from the Ozone Monitoring Instrument are combined with re-analysis meteorology to estimate urban nitrogen oxide (NO X ) emissions for 80 global cities between 2005 and 2019. The global average downward trend in satellite-derived urban NOX emissions was 3.1%–4.0% yr−1 between 2009 and 2018 while inventories show a 0%–2.2% yr−1 drop over the same timeframe. This difference is primarily driven by discrepancies between satellite-derived urban NO X emissions and inventories in Africa, China, India, Latin America, and the Middle East. In North America, Europe, Korea, Japan, and Australasia, NOX emissions dropped similarly as reported in the inventories. In Europe, Korea, and Japan only, the temporal trends match the inventories well, but the satellite estimate is consistently larger over time. While many of the discrepancies between satellite-based and inventory emissions estimates represent real differences, some of the discrepancies might be related to the assumptions made to compare the satellite-based estimates with inventory estimates, such as the spatial disaggregation of emissions inventories. Our work identifies that the three largest uncertainties in the satellite estimate are the tropospheric column measurements, wind speed and direction, and spatial definition of each city.

We estimate that a cumulative total of 1540 (1060–2800) Gg (gigagrams, 109 grams or thousand tonnes) of mercury (Hg) have been released by human activities up to 2010, 73% of which was released after 1850. Of this liberated Hg, 470 Gg were emitted directly into the atmosphere, and 74% of the air emissions were elemental Hg. Cumulatively, about 1070 Gg were released to land and water bodies. Though annual releases of Hg have been relatively stable since 1880 at 8 ± 2 Gg, except for wartime, the distributions of those releases among source types, world regions, and environmental media have changed dramatically. Production of Hg accounts for 27% of cumulative Hg releases to the environment, followed by silver production (24%) and chemicals manufacturing (12%). North America (30%), Europe (27%), and Asia (16%) have experienced the largest releases. Biogeochemical modeling shows a 3.2-fold increase in the atmospheric burden relative to 1850 and a contemporary atmospheric reservoir of 4.57 Gg, both of which agr...

The MIX inventory is developed for the years 2008 and 2010 to support the Model Inter-Comparison Study for Asia (MICS-Asia) and the Task Force on Hemispheric Transport of Air Pollution (TF HTAP) by a mosaic of up-to-date regional emission inventories. Emissions are estimated for all major anthropogenic sources in 29 countries and regions in Asia. We conducted detailed comparisons of different regional emission inventories and incorporated the best available ones for each region into the mosaic inventory at a uniform spatial and temporal resolution. Emissions are aggregated to five anthropogenic sectors: power, industry, residential, transportation, and agriculture. We estimate the total Asian emissions of 10 species in 2010 as follows: 51.3 Tg SO2, 52.1 Tg NOx, 336.6 Tg CO, 67.0 Tg NMVOC (non-methane volatile organic compounds), 28.8 Tg NH3, 31.7 Tg PM10, 22.7 Tg PM2.5, 3.5 Tg BC, 8.3 Tg OC, and 17.3 Pg CO2. Emissions from China and India dominate the emissions of Asia for most of the species. We also estimated Asian emissions in 2006 using the same methodology of MIX. The relative change rates of Asian emissions for the period of 2006–2010 are estimated as follows: −8.1 % for SO2, +19.2 % for NOx, +3.9 % for CO, +15.5 % for NMVOC, +1.7 % for NH3, −3.4 % for PM10, −1.6 % for PM2.5, +5.5 % for BC, +1.8 % for OC, and +19.9 % for CO2. Model-ready speciated NMVOC emissions for SAPRC-99 and CB05 mechanisms were developed following a profile-assignment approach. Monthly gridded emissions at a spatial resolution of 0.25° × 0.25° are developed and can be accessed from http://www.meicmodel.org/dataset-mix.

The TROPOspheric Monitoring Instrument (TROPOMI) is used to derive top-down NO

Fossil-fuel CO

China’s rapid urbanization and industrialization have affected the spatiotemporal patterns of nitrogen dioxide (NO2) pollution, which has led to greater environmental pressures. In order to mitigate the environmental pressures caused by NO2 pollution, it is of vital importance to investigate the influencing factors. We first obtained data for NO2 pollution at the city level using satellite observation techniques and analyzed its spatial distribution. Next, we introduced a theoretical framework, an extended stochastic impacts by regression on population, affluence, and technology (STIRPAT) model, to quantify the relationship between NO2 pollution and its contributing natural and socio-economic factors. The results are as follows. Cities with high NO2 pollution are mainly concentrated in the North China Plain. On the contrary, southwestern cities are characterized by low NO2 pollution. In addition, we find that population, per capita gross domestic product, the share of the secondary industry, ambient air pressures, total nighttime light data, and urban road area have a positive impact on NO2 pollution. In contrast, increases in the normalized difference vegetation index (NDVI), relative humidity, temperature, and wind speed may reduce NO2 pollution. These empirical results should help the government to effectively and efficiently implement further emission reductions and energy saving policies in Chinese cities in a bid to mitigate the environmental pressures.

Understanding the different impacts of urbanization on sectorial carbon dioxide (CO2) emissions at different spatial scales is of great importance for the evaluation of energy transition policies and reduction of environmental inequality. However, how urbanization affects the CO2 emissions of central heating systems at high spatial resolution in China has not been fully studied before. Based on satellite-observed NPP-VIIRS nighttime light (NTL) data, we develop a 5 km × 5 km annual CO2 emission inventory for coal boilers, thermal power plants (TPPs), and natural gas boilers in China’s central heating systems for the period 2012–2017 by using the geographical and temporally weighted regression (GTWR) model. It is observed that nonurban areas generated 2–4 times the CO2 emissions of coal boilers in urban areas. The largest increments of CO2 emissions of gas boilers are observed in urban areas of the eastern (6.80 times) and central regions (2.86 times) in 2013–2014, due to the clean heating policy in the “2 + 26” cities in China. The effects of urbanization on CO2 emissions from natural gas boilers are approximately 2–3 times those of coal boilers, and the differences are largest in western cities with only minor differences in northeastern cities. Our results will aid in designing low-carbon development goals and provide micro-level information on central heating facilities in urbanized and less developed regions.

This study investigates the relationship between ground-level ozone variability and synoptic weather conditions in the Chicago area in the summertime over the period 1990–2014. It shows that the occurrence of dry tropical (DT) weather conditions is most likely to lead to high ozone concentrations. Both the 95th percentile of summertime daily maximum 8-hour-average ozone concentrations and the number of days > 70 ppb are shown to have a greater and more significant correlation with DT weather in recent years (2004–2014) than in the preceding period (1990–2003), indicating an increased dependence of ozone on DT weather. The DT weather is shown to be associated with increased geopotential height, warmer temperature, and slower eastward wind at 500 hPa and also with warmer temperature and increased northward wind near the surface. The results have implications for the likely effect of future climate change on ozone as a result of modified synoptic weather conditions. More frequent episodes of high ozone concentrations can be expected, leading to worsened effects on public health and the environment. It will also make it increasingly challenging for Chicago to attain the National Ambient Air Quality Standard for ozone, which has recently been tightened by the U.S. Environmental Protection Agency.

Air pollution related to traffic emissions pose an especially significant problem in cities; this is due to its adverse impact on human health and well-being. Previous studies which have aimed to quantify emissions from the transportation sector have been limited by either simulated or coarsely resolved traffic volume data. Emissions inventories form the basis of urban pollution models, therefore in this study, Global Positioning System (GPS) trajectory data from a taxi fleet of over 15,000 vehicles were analyzed with the aim of predicting air pollution emissions for Singapore. This novel approach enabled the quantification of instantaneous drive cycle parameters in high spatio-temporal resolution, which provided the basis for a microscopic emissions model. Carbon dioxide (CO2), nitrogen oxides (NOx), volatile organic compounds (VOCs) and particulate matter (PM) emissions were thus estimated. Highly localized areas of elevated emissions levels were identified, with a spatio-temporal precision not possible with previously used methods for estimating emissions. Relatively higher emissions areas were mainly concentrated in a few districts that were the Singapore Downtown Core area, to the north of the central urban region and to the east of it. Daily emissions quantified for the total motor vehicle population of Singapore were found to be comparable to another emissions dataset. Results demonstrated that high-resolution spatio-temporal vehicle traces detected using GPS in large taxi fleets could be used to infer highly localized areas of elevated acceleration and air pollution emissions in cities, and may become a complement to traditional emission estimates, especially in emerging cities and countries where reliable fine-grained urban air quality data is not easily available. This is the first study of its kind to investigate measured microscopic vehicle movement in tandem with microscopic emissions modeling for a substantial study domain. Keywords: Air quality; Transportation; Emissions; Microscopic emissions model; Microscopic vehicle movement

The Ozone Monitoring Instrument (OMI) has been estimating NO2 columns from space for over 10 years, and these have been used to estimate emissions and emission trends for point and area sources all over the world. In this study we evaluate the trends in NO2 columns over 54 cities in the USA and Canada to identify the long term trends due to air quality policies, the impact of the Great Recession, and the weekday-weekend effect. A multiple linear regression model is used to fit annual, seasonal and weekly factors for individual swath retrievals along with the impact of temperature, wind speed and pixel size. For most cities, the correlation coefficients of the model fit ranges from 0.47 to 0.76. There have been strong reductions in NO2 columns, with annual decreases of up to 7% per year in most cities. During the years of the Great Recession, NO2 columns were as much as 30% lower than they would have been had they followed the linear annual trend. The analysis yielded insights into the timing of the reductions, with some cities in the northwest and in the east experiencing reductions in 2008 already, and most areas back to where they would have been based on the uniform trend by 2011. The analysis also finds that reductions in columns during the weekend vary significantly from city to city, with a range in reductions of 10%–30% on Saturdays, and 20%–50% on Sundays.

The prospect of global climate change will have wide scale impacts, such as ecological stress and human health hazards. One aspect of concern is future changes in air quality that will result from changes in both meteorological forcing and air pollutant emissions. In this study, the GU-WRF/Chem model is employed to simulate the impact of changing climate and emissions following the IPCC AR4 SRES A1B scenario. An average of 4 future years (2020, 2030, 2040, and 2050) is compared against an average of 2 current years (2001 and 2010). Under this scenario, by the Mid-21st century global air quality is projected to degrade with a global average increase of 2.5 ppb in the maximum 8-hr O 3 level and of 0.3 μg m −3 in 24-hr average PM 2.5 . However, PM 2.5 changes are more regional due to regional variations in primary aerosol emissions and emissions of gaseous precursor for secondary PM 2.5 . Increasing NO x emissions in this scenario combines with a wetter climate elevating levels of OH, HO 2 , H 2 O 2 , and the nitrate radical and increasing the atmosphere’s near surface oxidation state. This differs from findings under the RCP scenarios that experience declines in OH from reduced NO x emissions, stratospheric recovery of O 3 , and increases in CH 4 and VOCs. Increasing NO x and O 3 levels enhances the nitrogen and O 3 deposition, indicating potentially enhanced crop damage and ecosystem stress under this scenario. The enhanced global aerosol level results in enhancements in aerosol optical depth, cloud droplet number concentration, and cloud optical thickness. This leads to dimming at the Earth’s surface with a global average reduction in shortwave radiation of 1.2 W m −2 . This enhanced dimming leads to a more moderate warming trend and different trends in radiation than those found in NCAR’s CCSM simulation, which does not include the advanced chemistry and aerosol treatment of GU-WRF/Chem and cannot simulate the impacts of changing climate and emissions with the same level of detailed treatments. This study indicates that effective climate mitigation and emission control strategies are needed to prevent future health impact and ecosystem stress. Further, studies that are used to develop these strategies should use fully coupled models with sophisticated chemical and aerosol-interaction treatments that can provide a more realistic representation of the atmosphere.

The Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite has been providing global observations of the ozone layer and key atmospheric pollutant gases, such as nitrogen dioxide (NO2) and sulfur dioxide (SO2), since October 2004. The data products from the same instrument provide consistent spatial and temporal coverage and permit the study of anthropogenic and natural emissions on local-to-global scales. In this paper, we examine changes in SO2 and NO2 over some of the world's most polluted industrialized regions during the first decade of OMI observations. In terms of regional pollution changes, we see both upward and downward trends, sometimes in opposite directions for NO2 and SO2, for different study areas. The trends are, for the most part, associated with economic and/or technological changes in energy use, as well as regional regulatory policies. Over the eastern US, both NO2 and SO2 levels decreased dramatically from 2005 to 2015, by more than 40 and 80 %, respectively, as a result of both technological improvements and stricter regulations of emissions. OMI confirmed large reductions in SO2 over eastern Europe's largest coal-fired power plants after installation of flue gas desulfurization devices. The North China Plain has the world's most severe SO2 pollution, but a decreasing trend has been observed since 2011, with about a 50 % reduction in 2012–2015, due to an economic slowdown and government efforts to restrain emissions from the power and industrial sectors. In contrast, India's SO2 and NO2 levels from coal power plants and smelters are growing at a fast pace, increasing by more than 100 and 50 %, respectively, from 2005 to 2015. Several SO2 hot spots observed over the Persian Gulf are probably related to oil and gas operations and indicate a possible underestimation of emissions from these sources in bottom-up emission inventories. Overall, OMI observations have proved valuable in documenting rapid changes in air quality over different parts of the world during last decade. The baseline established during the first 11 years of OMI is indispensable for the interpretation of air quality measurements from current and future satellite atmospheric composition missions.

Nitrogen oxides (NOxNO+NO2) are produced during combustion processes and, thus may serve as a proxy for fossil fuel-based energy usage and committed greenhouse gases and other pollutants. We use high-resolution nitrogen dioxide (NO2) data from the Ozone Monitoring Instrument (OMI) to analyze changes in urban NO2 levels around the world from 2005 to 2014, finding complex heterogeneity in the changes. We discuss several potential factors that seem to determine these NOx changes. First, environmental regulations resulted in large decreases. The only large increases in the United States may be associated with three areas of intensive energy activity. Second, elevated NO2 levels were observed over many Asian, tropical, and subtropical cities that experienced rapid economic growth. Two of the largest increases occurred over recently expanded petrochemical complexes in Jamnagar (India) and Daesan (Korea). Third, pollution transport from China possibly influenced the Republic of Korea and Japan, diminishing the impact of local pollution controls. However, in China, there were large decreases over Beijing, Shanghai, and the Pearl River Delta, which were likely associated with local emission control efforts. Fourth, civil unrest and its effect on energy usage may have resulted in lower NO2 levels in Libya, Iraq, and Syria. Fifth, spatial heterogeneity within several megacities may reflect mixed efforts to cope with air quality degradation. We also show the potential of high-resolution data for identifying NOx emission sources in regions with a complex mix of sources. Intensive monitoring of the world's tropical subtropical megacities will remain a priority, as their populations and emissions of pollutants and greenhouse gases are expected to increase significantly.

Black carbon (BC) is a significant component of particulate matter (PM) that relates to air pollution, climate forcing, and further implications for public health. BC is predominantly released from the combustion of solid fuels. Combustion of low-quality fuels in rural China may induce severe respiratory and cardiopulmonary health outcomes for residents, which have however been inadequately assessed. One major reason for the limited understanding is the lack of a high-resolution inventory. An improved method of estimating the BC-associated public health burden is needed. This work quantified premature mortalities due to residential BC emissions in rural China. Domestic BC emissions at 1×1 km resolution were compiled based on previous field investigation, which were further configured for air quality simulation. A chemistry transport model, WRF–CMAQ v5.2, was employed for simulating BC concentrations. The consequent premature mortalities were quantified by a BC-specific concentration-response function (CRF) derived from an epidemiological study. Results show that residential combustion of solid fuel in rural China emitted 648.0 Gg (95%CI: 361.0–965.9) BC in 2014, after dispersion, accounting for 51.8% of annual mean ground-level BC concentration in China. Such impact was most severe in North and Northeast China, and the Sichuan Basin. The further investigation estimated 171,000 (95%CI: 69,000–387,000) premature mortalities that were attributable to exposure to rural residential BC. These findings reveal the major contribution of rural residential BC emissions to air pollution formation and public health impacts. Our findings are anticipated to provide useful information for enacting the next-stage environmental strategy for the residential sector in China.

Fossil-fuel CO2 emissions and their trends in eight U.S. megacities during 2006–2017 are inferred by combining satellite-derived NOX emissions with bottom-up city-specific NOX-to-CO2 emission ratios. A statistical model is fit to a collection NO2 plumes observed from the Ozone Monitoring Instrument (OMI), and is used to calculate top-down NOX emissions. Decreases in OMI-derived NOX emissions are observed across the eight cities from 2006 to 2017 (−17% in Miami to −58% in Los Angeles), and are generally consistent with long-term trends of bottom-up inventories (−25% in Miami to −49% in Los Angeles), but there are some interannual discrepancies. City-specific NOX-to-CO2 emission ratios, used to calculate inferred CO2, are estimated through annual bottom-up inventories of NOX and CO2 emissions disaggregated to 1 × 1 km2 resolution. Over the study period, NOX-to-CO2 emission ratios have decreased by ~40% nationwide (−24% to −51% for our studied cities), which is attributed to a faster reduction in NOX when compared to CO2 due to policy regulations and fuel type shifts. Combining top-down NOX emissions and bottom-up NOX-to-CO2 emission ratios, annual fossil-fuel CO2 emissions are derived. Inferred OMI-based top-down CO2 emissions trends vary between +7% in Dallas to −31% in Phoenix. For 2017, we report annual fossil-fuel CO2 emissions to be: Los Angeles 113 ± 49 Tg/yr; New York City 144 ± 62 Tg/yr; and Chicago 55 ± 24 Tg/yr. A study in the Los Angeles area, using independent methods, reported a 2013–2016 average CO2 emissions rate of 104 Tg/yr and 120 Tg/yr, which suggests that the CO2 emissions from our method are in good agreement with other studies' top-down estimates. We anticipate future remote sensing instruments – with better spatial and temporal resolution – will better constrain the NOX-to-CO2 ratio and reduce the uncertainty in our method.

A novel back-trajectory approach was adopted to determine the origins of black carbon (BC) and carbon monoxide (CO) transported to Beijing, Tianjin and Hebei. Results showed that the transport efficiency was controlled mainly by mid-latitude westerlies in winter, the South Asian monsoon in summer and prevailing westerly and northwesterly winds in spring and autumn. Hebei was identified as the most important source region of both BC (respectively accounting for 55% and 49%) and CO (39% and 38%) transported to Beijing and Tianjin. Inner Mongolia contributed more to the effective emission intensity (EEI) in winter than in summer for both BC and CO transported to Beijing and Tianjin. Shandong was responsible for higher EEI in summer than in winter. The six provinces making the greatest contributions to BC transported to Hebei were Shandong (19%), Shanxi (19%), Inner Mongolia (17%), Beijing (11%), Henan (11%), and Tianjin (10%), whereas those making the greatest contributions to CO transported to Hebei were Shandong (20%), Inner Mongolia (10%), Tianjin (9%), Henan (9%), Shanxi (9%), and Beijing (8%). In summary, Hebei, Inner Mongolia, Shandong, Tianjin and Shanxi were determined as the dominant source regions of not only BC but also CO transported to Beijing. Hebei, Shandong, Beijing, Inner Mongolia, Henan, Liaoning and Shanxi were relatively important source regions for Tianjin. Shandong, Shanxi, Inner Mongolia, Beijing, Henan, Tianjin, Liaoning, Jiangsu and Anhui were the main source regions for Hebei. Residential and industrial sectors were the dominant sectors for BC and CO transported to the receptors, respectively. These results are consistent with the results of previous studies. Finally, comparing the observed ΔBC/ΔCO ratio with the enhancement ratio of the EEI of BC with that of CO (ΔEEIBC/ΔEEICO) at Miyun site, we further confirmed that the EEI can be used to represent the amounts of BC and CO reaching receptors.

In this work, we investigate the NOx emissions inventory in Seoul, South Korea, using a regional ozone monitoring instrument (OMI) NO2 product derived from the standard NASA product. We first develop a regional OMI NO2 product by recalculating the air mass factors using a high-resolution (4 km × 4 km) WRF-Chem model simulation, which better captures the NO2 profile shapes in urban regions. We then apply a model-derived spatial averaging kernel to further downscale the retrieval and account for the subpixel variability. These two modifications yield OMI NO2 values in the regional product that are 1.37 times larger in the Seoul metropolitan region and >2 times larger near substantial point sources. These two modifications also yield an OMI NO2 product that is in better agreement with the Pandora NO2 spectrometer measurements acquired during the South Korea–United States Air Quality (KORUS-AQ) field campaign. NOx emissions are then derived for the Seoul metropolitan area during the KORUS-AQ field campaign using a top-down approach with the standard and regional NASA OMI NO2 products. We first apply the top-down approach to a model simulation to ensure that the method is appropriate: the WRF-Chem simulation utilizing the bottom-up emissions inventory yields a NOx emissions rate of 227±94 kt yr−1, while the bottom-up inventory itself within a 40 km radius of Seoul yields a NOx emissions rate of 198 kt yr−1. Using the top-down approach on the regional OMI NO2 product, we derive the NOx emissions rate from Seoul to be 484±201 kt yr−1, and a 353±146 kt yr−1 NOx emissions rate using the standard NASA OMI NO2 product. This suggests an underestimate of 53 % and 36 % in the bottom-up inventory using the regional and standard NASA OMI NO2 products respectively. To supplement this finding, we compare the NO2 and NOy simulated by WRF-Chem to observations of the same quantity acquired by aircraft and find a model underestimate. When NOx emissions in the WRF-Chem model are increased by a factor of 2.13 in the Seoul metropolitan area, there is better agreement with KORUS-AQ aircraft observations and the recalculated OMI NO2 tropospheric columns. Finally, we show that by using a WRF-Chem simulation with an updated emissions inventory to recalculate the air mass factor (AMF), there are small differences (∼8 %) in OMI NO2 compared to using the original WRF-Chem simulation to derive the AMF. This suggests that changes in model resolution have a larger effect on the AMF calculation than modifications to the South Korean emissions inventory. Although the current work is focused on South Korea using OMI, the methodology developed in this work can be applied to other world regions using TROPOMI and future satellite datasets (e.g., GEMS and TEMPO) to produce high-quality region-specific top-down NOx emissions estimates.

Emissions from the transportation sector are rapidly changing worldwide; however, the interplay of such emission changes in the face of climate change are not as well understood. This two-part study examines the impact of projected emissions from the U.S. transportation sector (Part I) on ambient air quality in the face of climate change (Part II). In Part I of this study, we describe the methodology and results of a novel Technology Driver Model (see graphical abstract) that includes 1) transportation emission projections (including on-road vehicles, non-road engines, aircraft, rail, and ship) derived from a dynamic technology model that accounts for various technology and policy options under an IPCC emission scenario, and 2) the configuration/evaluation of a dynamically downscaled Weather Research and Forecasting/Community Multiscale Air Quality modeling system. By 2046-2050, the annual domain-average transportation emissions of carbon monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOCs), ammonia (NH3), and sulfur dioxide (SO2) are projected to decrease over the continental U.S. The decreases in gaseous emissions are mainly due to reduced emissions from on-road vehicles and non-road engines, which exhibit spatial and seasonal variations across the U.S. Although particulate matter (PM) emissions widely decrease, some areas in the U.S. experience relatively large increases due to increases in ship emissions. The on-road vehicle emissions dominate the emission changes for CO, NOx, VOC, and NH3, while emissions from both the on-road and non-road modes have strong contributions to PM and SO2 emission changes. The evaluation of the baseline 2005 WRF simulation indicates that annual biases are close to or within the acceptable criteria for meteorological performance in the literature, and there is an overall good agreement in the 2005 CMAQ simulations of chemical variables against both surface and satellite observations.

In Part II of this work we present the results of the downscaled offline Weather Research and Forecasting/Community Multiscale Air Quality (WRF/CMAQ) model, included in the “Technology Driver Model” (TDM) approach to future U.S. air quality projections (2046–2050) compared to a current-year period (2001–2005), and the interplay between future emission and climate changes. By 2046–2050, there are widespread decreases in future concentrations of carbon monoxide (CO), nitrogen oxides (NOx = NO + NO2), volatile organic compounds (VOCs), ammonia (NH3), sulfur dioxide (SO2), and particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM2.5) due mainly to decreasing on-road vehicle (ORV) emissions near urban centers as well as decreases in other transportation modes that include non-road engines (NRE). However, there are widespread increases in daily maximum 8-hr ozone (O3) across the U.S., which are due to enhanced greenhouse gases (GHG) including methane (CH4) and carbon dioxide (CO2) under the Intergovernmental Panel on Climate Change (IPCC) A1B scenario, and isolated areas of larger reduction in transportation emissions of NOx compared to that of VOCs over regions with VOC-limited O3 chemistry. Other notable future changes are reduced haze and improved visibility, increased primary organic to elemental carbon ratio, decreases in PM2.5 and its species, decreases and increases in dry deposition of SO2 and O3, respectively, and decreases in total nitrogen (TN) deposition. There is a tendency for transportation emission and CH4 changes to dominate the increases in O3, while climate change may either enhance or mitigate these increases in the west or east U.S., respectively. Climate change also decreases PM2.5 in the future. Other variable changes exhibit stronger susceptibility to either emission (e.g., CO, NOx, and TN deposition) or climate changes (e.g., VOC, NH3, SO2, and total sulfate deposition), which also have a strong dependence on season and specific U.S. regions.