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The Kathmandu Valley in Nepal experiences poor air quality, especially in the dry winter season. In this study, we investigated the concentration, chemical composition, and sources of fine and coarse particulate matter (PM

The Kathmandu Valley in Nepal suffers from unhealthy air quality, with mean pre-monsoon submicron particulate matter concentration (PM1) of 40 μg m−3 and daily peaks over 75 μg m−3. A high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) measured ambient non-refractory submicron PM (NR-PM1) in a Kathmandu suburb in April 2015. The mean NR-PM1 composition was 15.8 μg m−3 (39.7%) organic aerosol (OA), 10.5 μg m−3 (25.0%) BC, 8.4 μg m−3 (21.1%) SO42−, 2.96 μg m−3 (7.4%) NH4+, 1.22 μg m−3 (3.1%) NO3−, and 0.92 μg m−3 (2.3%) Cl−. NR-PM1 exhibited a diurnal pattern with concentration maxima at 08:00 local standard time. Afternoon winds and an elevated planetary boundary layer then mitigated NR-PM1. Positive matrix factorization (PMF) of OA mass spectral data identified four primary source components: hydrocarbon-like OA (HOA, 15%), biomass burning OA (BBOA, 15%), trash burning OA (TBOA, 11%), a local sulfur-containing OA (sLOA, 7%), and three oxidized OA (OOA, 50%) factors. sLOA contains the ion C3HSO+, associated with emissions from coal used in brick kilns. Secondary aerosols account for 50% of all OA mass within the valley. Gas-phase carbon monoxide (CO), carbon dioxide (CO2), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), methane (CH4), and black and brown carbon (BC, BrC) measurements also characterized pollution in the valley. Composition, concentration, and source analysis from AMS-PMF and filter-based chemical mass balance measurements agree well (OC slope = 1.05, R2 = 0.47). This work identifies and quantifies significant sources of PM1 in the Kathmandu Valley and provides insight into the impact of these sources on overall air quality throughout South Asia.

The lockdown due to COVID-19 created a rare opportunity to examine the nonlinear responses of secondary aerosols, which are formed through atmospheric oxidation of gaseous precursors, to intensive precursor emission reductions. Based on unique observational data sets from six supersites in eastern China during 2019-2021, we found that the lockdown caused considerable decreases (32-61%) in different secondary aerosol components in the study region because of similar-degree precursor reductions. However, due to insufficient combustion-related volatile organic compound (VOC) reduction, odd oxygen (Ox = O3 + NO2) concentration, an indicator of the extent of photochemical processing, showed little change and did not promote more decreases in secondary aerosols. We also found that the Chinese provinces and international cities that experienced reduced Ox during the lockdown usually gained a greater simultaneous PM2.5 decrease than other provinces and cities with an increased Ox. Therefore, we argue that strict VOC control in winter, which has been largely ignored so far, is critical in future policies to mitigate winter haze more efficiently by reducing Ox simultaneously.

The North China Plain (NCP) is a region that experiences serious aerosol pollution. A number of studies have focused on aerosol pollution in urban areas in the NCP region; however, research on characterizing aerosols in rural NCP areas is comparatively limited. In this study, we deployed a TD-HR-AMS (thermodenuder high-resolution aerosol mass spectrometer) system at a rural site in the NCP region in summer 2013 to characterize the chemical compositions and volatility of submicron aerosols (PM1). The average PM1 mass concentration was 51.2 ± 48.0 µg m−3 and organic aerosol (OA) contributed most (35.4%) to PM1. Positive matrix factorization (PMF) analysis of OA measurements identified four OA factors, including hydrocarbon-like OA (HOA, accounting for 18.4%), biomass burning OA (BBOA, 29.4%), less-oxidized oxygenated OA (LO-OOA, 30.8%) and more-oxidized oxygenated OA (MO-OOA, 21.4%). The volatility sequence of the OA factors was HOA > BBOA > LO-OOA > MO-OOA, consistent with their oxygen-to-carbon (O:C) ratios. Additionally, the mean concentration of organonitrates (ON) was 1.48–3.39 µg m−3, contributing 8.1%–19% of OA based on cross validation of two estimation methods with the high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) measurement. Correlation analysis shows that ON were more correlated with BBOA and black carbon emitted from biomass burning but poorly correlated with LO-OOA. Also, volatility analysis for ON further confirmed that particulate ON formation might be closely associated with primary emissions in rural NCP areas.

Land surface models (LSMs) are limited in their ability to reproduce observed soil moisture partially due to uncertainties in model parameters. Here we conduct a variance-based sensitivity analysis to quantify the relative contribution of different model parameters and their interactions to the uncertainty in the surface and root-zone soil moisture in the Community Land Model 5.0 (CLM5). We focus on soil-texture-related parameters (porosity, saturated matric potential, saturated hydraulic conductivity, shape parameter of soil-water retention model) and organic matter fraction. A Gaussian process emulator is constructed based on CLM5 simulations and used to estimate soil moisture across the five-dimensional parameter space for sensitivity analysis. The procedure is demonstrated for four seasons across various U.S. sites of distinct soil and vegetation types. We find that the emulator captures well the CLM5 behavior across the parameter space for different soil textures and seasons. The uncertainties of surface and root-zone soil moisture are dominated by the uncertainties in porosity and shape parameter with negligible parametric interactions. However, relative importance of porosity versus shape parameter varies with soil textures (sites), depths (surface versus root zone), and seasons. At most of the sites, surface soil moisture uncertainty is attributed largely to shape parameter uncertainty, while porosity uncertainty is more important for the root-zone soil moisture uncertainty. All individual parameter and interaction effects demonstrate less variability across different soil textures and seasons for root zone than for surface soil moisture. These results provide scientific guidance to prioritize reducing the uncertainty of sensitive parameters for improving soil moisture modeling with CLM.

The Indo-Gangetic Plains (IGP) experience high levels of airborne particulate matter (PM), especially during the dry season. Contributing to PM are natural and anthropogenic emissions and the atmos...

Increasing air pollution in South Asia has serious consequences for air quality and human/ecosystem health within the region. South Asia, including India and Nepal, suffers from severe air pollution, including high concentrations of aerosols, as well as gaseous pollutants. One of the often-neglected sources contributing to the regional air pollution is garbage burning. It is mostly related to numerous yet small, open, uncontrolled fires burning diverse fuels, making it difficult to quantify activity and emissions. In this study, we attempted to quantify the total emissions due to garbage burning and its contribution to regional air quality, using new observational data, a new inventory, and a regional chemical transport model. We implemented the newly available emission factors (EFs) from a recent field campaign, Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE), which took place in April 2015. Using a chemical transport model-Weather Research and Forecasting model coupled with Chemistry version 3.5 (WRF-Chem)-and three emission scenarios, we assessed the impact of open garbage burning emissions on regional air quality. Our results show that garbage burning emissions could increase PM

Ship emissions contribute to air pollution, increasing the adverse health impacts on people living in coastal cities. We estimated the impacts caused by ship emissions, both on air quality and human health, in 2015 and future (2030) within the Pearl River Delta (PRD) region of China. In addition, we assessed the potential health benefits of implementing an Emission Control Area (ECA) in the region by predicting avoided premature mortality with and without an ECA. In 2015, ship emissions increased PM2.5 concentrations and O3 mixing ratios by 1.4 μg/m3 and 1.9 ppb, respectively, within the PRD region. This resulted in 466 and 346 excess premature acute deaths from PM2.5 and O3, respectively. Premature mortality from chronic exposures was even more significant, with 2,085 and 852 premature deaths from ship‐related PM2.5 and O3, respectively. In 2030, we projected the future ship emissions with and without an ECA, using two possible land scenarios. With an ECA, we predicted 76% reductions in SO2 and 13% reductions in NOx from the shipping sector. Assuming constant land emissions from 2015 in 2030 (2030 Constant scenario), we found that an ECA could avoid 811 PM2.5‐related and 108 O3‐related deaths from chronic exposures. Using 2030 Projected scenario for land emissions, we found that an ECA would avoid 1,194 PM2.5‐related and 160 O3‐related premature deaths in 2030. In both scenarios, implementing an ECA resulted in 30% fewer PM2.5‐related premature deaths and 10% fewer O3‐related premature deaths, illustrating the importance of reducing ship emissions., Key Points In 2015, ship emissions increased summer PM2.5 and O3 by 1.4 μg/m3 and 1.9 ppb, respectively, within the Pearl River Delta (PRD), ChinaShip emissions caused over 2,500 PM2.5‐related and 1,200 O3‐related premature deaths in the PRD region in 2015Implementing an Emission Control Area in the PRD region in 2030 could reduce mortality due to PM2.5 and O3 exposures by 30% and 10%, respectively

In this study, we estimate the cost of PM2.5 and O3 pollution in China and explore how it differs by province. For the analysis, we extend the China Regional Energy Model—a computable general equilibrium model of the Chinese economy—to explicitly represent the pollution-health linkage within a larger economic system. Our results show that health damage from air pollution in China is substantially large. For each year between 2010 and 2030, China’s welfare loss from excess pollution is estimated to be 3.2–5.1% of the baseline level when welfare is measured as the sum of consumption and leisure. The PM2.5 share of the costs was > 13 times as large as the O3 share, and premature deaths from chronic exposure to PM2.5 were the single most important health endpoint, accounting for ≤ 56% of the total costs. Cross-regional heterogeneity is substantial, and populous and wealthy Eastern China is subject to particularly large health damage. When the size of provincial economies is controlled for, however, the dominance of the eastern region is less obvious and several inland provinces (e.g., Henan, Shanxi, and Chongqing) also suffer high pollution-health costs, due to low air quality and fast productivity growth. Finally, broader economic loss from inefficient resource allocation and its cumulative effects, which is often neglected in static analysis, accounts for > 29% of the total costs. Overlooking this cost component will, in particular, lead to substantial underestimation for China’s central and western regions, whose economies are growing fast.

Biomass burning (BB) is a major source of air pollution from local to global scale, having variable effects on air quality, human health, and climate system. Therefore, the source identification and characterization of BB-derived aerosols and tracer gases in the ambient environment is crucial. This review provides recent updates on the applicability of levoglucosan as a BB tracer in different environmental matrices such as aerosols, marine, snow and ice-cores etc. Among several tracer of BB emissions, levoglucosan has recently received widespread attention due to its unique origin solely from the pyrolysis of cellulose and hemicellulose, making it as a robust marker for characterization and quantification of BB throughout the world. This review first summarizes the established and emerging analytical methods, and their advantages and disadvantages for measurement of levoglucosan. Second, we discuss the formation mechanism, lifetime and its stability in different environmental conditions. In addition, we also try to deliberate on the application of ratios of levoglucosan with different organic components such as mannosan (M) and organic carbon (OC) for better identification of emission sources. Spatial distributions of levoglucosan in different locations (e.g., urban, rural, forest, marine, poles and higher altitude) are discussed scrupulously and meticulously on a global scale. We also reviewed the distributions of levoglucosan in snow, ice core and sediments to understand its applicability to construct paleofire records. Finally, we propose some key recommendations for future work in different ambient environmental conditions by utilizing the ratios of levoglucosan with other compounds (not limited only to M and OC) and the use of levoglucosan to reconstruct the paleo-historical records of fire-activity.

China's lockdown to control COVID-19 brought significant declines in air pollutant emissions, but haze was still a serious problem in North China Plain (NCP) during late-January to mid-February of 2020. We seek the potential causes for the poor air quality in NCP combining satellite data, ground measurements and model analyses. Efforts to constrain COVID-19 result in a drop-off of primary gaseous pollutants, e.g., −42.4% for surface nitrogen dioxide (NO2) and −38.9% for tropospheric NO2 column, but fine particulate matter (PM25) still remains high and ozone (O3) even increases sharply (+84.1%). Stagnant weather during COVID-19 outbreak, e.g., persistent low wind speed, frequent temperature inversion and wind convergence, are the major drivers for the poor air quality in NCP. The surface PM2.5 levels vary between −12.9∼+15.1% in NCP driven by the varying climate conditions between the years 2000 and 2020. Besides, the persistent PM2.5 pollution might be maintained by the still intensive industrial and residential emissions (primary PM2.5), and increased atmospheric oxidants (+26.1% for ozone and +29.4% for hydroxyl radical) in response to the NO2 decline (secondary PM2.5). Further understanding the nonlinear response between atmospheric secondary aerosols and NOx emissions is meaningful to cope with the emerging air pollution problems in China., Graphical abstract Image 1, Highlights • Both satellite data and ground measurements confirm improved NO2 air quality. • PM2.5 varies between −12.9∼+15.1% driven by climate conditions. • High PM2.5 is maintained by intensive primary emission and increased oxidants.

Lead poisoning is often seen as a problem of the past. While acute cases are now rare, there is no known safe level of lead for children and blood lead levels at and below 5 μg/dL are associated with neurological deficits. Previous work has established that risk factors for lead exposure include race/ethnicity, poverty, Medicaid enrollment, housing built before 1950, and age. Efficient blood lead screening is crucial in the greater Atlanta area as pockets of poverty and old housing put some children at particularly high risk for chronic exposure to low levels of lead. Here, 20 years of data on children’s blood lead levels in Georgia were used to create maps to assess the spatial distribution of blood lead screening and blood lead levels in the Atlanta area. ZIP code tabulation area (ZCTA)-level screening rates continue to be associated with relative poverty but not with housing age, a well-established risk factor for lead exposure. Building on previous research, a priority screening index based on poverty and housing age was also created to identify specific high-risk census tracts for screening within Atlanta ZCTAs. This index shows a total of 18 highest-priority census tracts in the greater Atlanta area. Together, these 18 tracts contain 2715 children under six years old, 1.7% of all children under six years old in the entire greater Atlanta area.

Research on temperature and respiratory hospitalizations is lacking in the southeastern U.S. where cold weather is relatively rare. This retrospective study examined the association between cold waves and pneumonia and influenza (PI) emergency department (ED) visits and hospitalizations in three metro-Atlanta hospitals.We used a case-crossover design, restricting data to the cooler seasons of 2009-2019, to determine whether cold waves influenced ED visits and hospitalizations. This analysis considered effects by race/ethnicity, age, sex, and severity of comorbidities. We used generalized additive models and distributed lag non-linear models to examine these relationships over a 21-day lag period.The odds of a PI ED visit approximately one week after a cold wave were increased by as much as 11%, and odds of an ED visit resulting in hospitalization increased by 8%. For ED visits on days with minimum temperatures20 °C, there was an increase of 10-15% in relative risk (RR) for short lags (0-2 days), and a slight decrease in RR (0-5%) one week later. For minimum temperatures0 °C, RR decreased at short lags (5-10%) before increasing (1-5%) one week later. Hospital admissions exhibited a similar, but muted, pattern.Unusually cold weather influenced PI ED visits and admissions in this population.

We present top-down constraints on global monthly N2O emissions for 2011 from a multi-inversion approach and an ensemble of surface observations. The inversions employ the GEOS-Chem adjoint and an array of aggregation strategies to test how well current observations can constrain the spatial distribution of global N2O emissions. The strategies include (1) a standard 4D-Var inversion at native model resolution (4° × 5°), (2) an inversion for six continental and three ocean regions, and (3) a fast 4D-Var inversion based on a novel dimension reduction technique employing randomized singular value decomposition (SVD). The optimized global flux ranges from 15.9 Tg N yr−1 (SVD-based inversion) to 17.5–17.7 Tg N yr−1 (continental-scale, standard 4D-Var inversions), with the former better capturing the extratropical N2O background measured during the HIAPER Pole-to-Pole Observations (HIPPO) airborne campaigns. We find that the tropics provide a greater contribution to the global N2O flux than is predicted by the prior bottom-up inventories, likely due to underestimated agricultural and oceanic emissions. We infer an overestimate of natural soil emissions in the extratropics and find that predicted emissions are seasonally biased in northern midlatitudes. Here, optimized fluxes exhibit a springtime peak consistent with the timing of spring fertilizer and manure application, soil thawing, and elevated soil moisture. Finally, the inversions reveal a major emission underestimate in the US Corn Belt in the bottom-up inventory used here. We extensively test the impact of initial conditions on the analysis and recommend formally optimizing the initial N2O distribution to avoid biasing the inferred fluxes. We find that the SVD-based approach provides a powerful framework for deriving emission information from N2O observations: by defining the optimal resolution of the solution based on the information content of the inversion, it provides spatial information that is lost when aggregating to political or geographic regions, while also providing more temporal information than a standard 4D-Var inversion.

About 78% of global greenhouse gas emissions between 1970 and 2010 were due to fossil fuel combustion, increasing the atmospheric mixing ratio of carbon dioxide to around 419 ppm by June 2021. During a similar period, between 1975 and 2017, 162 countries adopted renewable energy targets – official national commitments to increase the share of renewable energies. What induced the diffusion of these renewable energy targets? What are the patterns of their diffusion? We analyze data from 187 countries and assess four possible mechanisms of policy diffusion of renewable energy targets: learning, economic competition, emulation, and coercion. Using a qualitative comparative analysis, we find eight pathways to renewable energy target adoption. In the most common pathways, economic competition, emulation, and coercion played a significant role. Before there is a critical mass of countries to emulate, our analysis shows that early adopters followed the mechanisms of economic competition and coercion. Ultimately, we find that there is no one recipe for the diffusion of renewable energy targets, and we identify the specific countries associated with the different diffusion pathways.

Sulfur aerosols, mainly composed of sulfate and methanesulfonic acid (MSA), significantly affect the Earth’s radiation balance, biogeochemical cycles and ecosystems, especially in the polar regions with vulnerable environments. To better understand the relationship between anthropogenic activities and climate change, a comprehensive review is presented, covering sulfate and MSA concentrations and isotope composition from 18 sites in the Arctic, 22 sites in the Antarctic and 25 sites in the Tibetan Plateau. The spatio-temporal variability of sulfur aerosols and the potential factors controlling their concentrations are summarized, sulfur isotopes are used to identify the importance of anthropogenic vs. natural inputs, and ice cores are employed to reconstruct the paleo-evolution of atmospheric sulfates. Finally, this review discusses the need for future research on organosulfur aerosols, the mixing state of sulfur aerosols, their deposition fluxes and velocities, potential emissions by biomass burning, and the anticipated trends in sulfur aerosol concentrations in the Arctic, Antarctic, and Tibetan Plateau.

States have historically been the primary drivers of climate change policy in the US, particularly with regard to emissions from power plants. States have implemented policies designed either to directly curb greenhouse gas (GHG) emissions from power plants, or to encourage energy efficiency and renewable energy growth. With the federal government withdrawing from the global climate agreement, understanding which state-level policies have successfully mitigated power-plant emissions is urgent. Past research has assessed policy effectiveness using data for periods before the adoption of many policies. We assess 17 policies using the latest data on state-level power-sector CO2 emissions. We find that policies with mandatory compliance are reducing power-plant emissions, while voluntary policies are not. Electric decoupling, mandatory GHG registry/reporting and public benefit funds are associated with the largest reduction in emissions. Mandatory GHG registry/reporting and public benefit funds are also associated with a large reduction in emissions intensity. State policies play a key role in mitigation of power-sector emissions. Analysis of 17 policies in the US shows that mandatory compliance is reducing emissions, with the largest reductions related to greenhouse gas reporting and public benefit funds.

Research Partners: Emory University, Tsinghua University, and Massachusetts Institute of Technology. This research builds on the work of the MIT-Tsinghua China Energy and Climate Project. The China Energy and Climate Project (CECP) involves close collaboration and personnel exchange between the MIT Joint Program on the Science and Policy of Global Change and the Institute for Energy, Environment and Economy at Tsinghua University.

Anthropogenic air pollutant emissions have been increasing rapidly in China, leading to worsening air quality. Modelers use emissions inventories to represent the temporal and spatial distribution of these emissions needed to estimate their impacts on regional and global air quality. However, large uncertainties exist in emissions estimates. Thus, assessing differences in these inventories is essential for the better understanding of air pollution over China. We compare five different emissions inventories estimating emissions of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), and particulate matter with an aerodynamic diameter of 10 µm or less (PM10) from China. The emissions inventories analyzed in this paper include the Regional Emission inventory in ASia v2.1 (REAS), the Multi-resolution Emission Inventory for China (MEIC), the Emission Database for Global Atmospheric Research v4.2 (EDGAR), the inventory by Yu Zhao (ZHAO), and the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS). We focus on the period between 2000 and 2008, during which Chinese economic activities more than doubled. In addition to national totals, we also analyzed emissions from four source sectors (industry, transport, power, and residential) and within seven regions in China (East, North, Northeast, Central, Southwest, Northwest, and South) and found that large disagreements exist among the five inventories at disaggregated levels. These disagreements lead to differences of 67 µg m−3, 15 ppbv, and 470 ppbv for monthly mean PM10, O3, and CO, respectively, in modeled regional concentrations in China. We also find that all the inventory emissions estimates create a volatile organic compound (VOC)-limited environment and MEIC emissions lead to much lower O3 mixing ratio in East and Central China compared to the simulations using REAS and EDGAR estimates, due to their low VOC emissions. Our results illustrate that a better understanding of Chinese emissions at more disaggregated levels is essential for finding effective mitigation measures for reducing national and regional air pollution in China.

Background: Substantial increases in wildfire activity have been recorded in recent decades. Wildfires influence the chemical composition and concentration of particulate matter ≤2.5 μm in aerodynamic diameter (PM2.5). However, relatively few epidemiologic studies focus on the health impacts of wildfire smoke PM2.5 compared with the number of studies focusing on total PM2.5 exposure. Objectives: We estimated the associations between cardiorespiratory acute events and exposure to smoke PM2.5 in Colorado using a novel exposure model to separate smoke PM2.5 from background ambient PM2.5 levels. Methods: We obtained emergency department visits and hospitalizations for acute cardiorespiratory outcomes from Colorado for May–August 2011–2014, geocoded to a 4 km geographic grid. Combining ground measurements, chemical transport models, and remote sensing data, we estimated smoke PM2.5 and non-smoke PM2.5 on a 1 km spatial grid and aggregated to match the resolution of the health data. Time-stratified, case-crossover models were fit using conditional logistic regression to estimate associations between fire smoke PM2.5 and non-smoke PM2.5 for overall and age-stratified outcomes using 2-day averaging windows for cardiovascular disease and 3-day windows for respiratory disease. Results: Per 1 μg/m3 increase in fire smoke PM2.5, statistically significant associations were observed for asthma (OR = 1.081 (1.058, 1.105)) and combined respiratory disease (OR = 1.021 (1.012, 1.031)). No significant relationships were evident for cardiovascular diseases and smoke PM2.5. Associations with non-smoke PM2.5 were null for all outcomes. Positive age-specific associations related to smoke PM2.5 were observed for asthma and combined respiratory disease in children, and for asthma, bronchitis, COPD, and combined respiratory disease in adults. No significant associations were found in older adults. Discussion: This is the first multi-year, high-resolution epidemiologic study to incorporate statistical and chemical transport modeling methods to estimate PM2.5 exposure due to wildfires. Our results allow for a more precise assessment of the population health impact of wildfire-related PM2.5 exposure in a changing climate. Keywords: Particulate matter, Wildfire, Air quality, Epidemiology, Climate change, Respiratory, Cardiovascular

Although best management practices have been recommended by government agencies and non-profit organizations to reduce community gardeners' potential exposure to soil contaminants such as lead, some gardeners do not perform these practices. Understanding gardeners' beliefs and motivations is critical for effective promotion of safer gardening practices. This study, grounded in the Theory of Planned Behavior (TPB), employed five focus groups to investigate Atlanta community garden leaders' perspectives concerning three gardening practices: composting, hygiene behaviors, and mulching. These general practices are also considered safe gardening practices in that they can reduce exposure to toxicants in urban gardens. Qualitative analysis identified advantages and disadvantages; supporters and non-supporters; and barriers and facilitators that might influence gardeners' opinions regarding these behaviors. Gardeners expressed that more funding, volunteers, and training are needed to promote these behaviors. Gardeners noted that mulch and compost provided advantages such as improving soil quality, but a primary barrier was concern about contamination of source materials. Focus group participants did not directly associate composting and mulching with reduction of exposure to soil contaminants. Behavioral challenges related to hygiene included concerns about decreased exposure to salubrious bacteria, inadequate access to potable water, and limited availability of gloves and wipes. These study findings characterize factors that community garden stakeholders should consider when promoting safe gardening practices and interventions.

Community gardens offer numerous benefits, but there are also potential risks from exposure to chemical contaminants in the soil. Through the lens of the Theory of Planned Behavior, this mixed methods study examined community gardeners&rsquo, beliefs and intentions to conduct heavy metal soil testing. The qualitative component involved five focus groups of community garden leaders in Atlanta, Georgia. Qualitative analysis of the focus group data revealed that heavy metal soil contamination was not frequently identified as a common gardening hazard and several barriers limited soil testing in community gardens. The focus group results informed the development of a questionnaire that was administered to 500 community gardeners across the United States. Logistic regression analysis revealed that the soil testing intention was associated with attitude (aOR = 2.46, 95% CI: 1.34, 4.53), subjective norms (aOR = 3.39 95% CI: 2.07, 5.57), and perceived behavioral control (aOR = 1.81, 95% CI: 1.10, 2.99). Study findings have implications for interventions involving community garden risk mitigation, particularly gardens that engage children and vulnerable populations.

The Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) campaign took place in and around the Kathmandu Valley and in the Indo-Gangetic Plain (IGP) of southern Nepal during April 2015. The source characterization phase targeted numerous important but undersampled (and often inefficient) combustion sources that are widespread in the developing world such as cooking with a variety of stoves and solid fuels, brick kilns, open burning of municipal solid waste (a.k.a. trash or garbage burning), crop residue burning, generators, irrigation pumps, and motorcycles. NAMaSTE produced the first, or rare, measurements of aerosol optical properties, aerosol mass, and detailed trace gas chemistry for the emissions from many of the sources. This paper reports the trace gas and aerosol measurements obtained by Fourier transform infrared (FTIR) spectroscopy, whole-air sampling (WAS), and photoacoustic extinctiometers (PAX; 405 and 870 nm) based on field work with a moveable lab sampling authentic sources. The primary aerosol optical properties reported include emission factors (EFs) for scattering and absorption coefficients (EF Bscat, EF Babs, in m2 kg−1 fuel burned), single scattering albedos (SSAs), and absorption Ångström exponents (AAEs). From these data we estimate black and brown carbon (BC, BrC) emission factors (g kg−1 fuel burned). The trace gas measurements provide EFs (g kg−1) for CO2, CO, CH4, selected non-methane hydrocarbons up to C10, a large suite of oxygenated organic compounds, NH3, HCN, NOx, SO2, HCl, HF, etc. (up to ∼ 80 gases in all). The emissions varied significantly by source, and light absorption by both BrC and BC was important for many sources. The AAE for dung-fuel cooking fires (4.63 ± 0.68) was significantly higher than for wood-fuel cooking fires (3.01 ± 0.10). Dung-fuel cooking fires also emitted high levels of NH3 (3.00 ± 1.33 g kg−1), organic acids (7.66 ± 6.90 g kg−1), and HCN (2.01 ± 1.25 g kg−1), where the latter could contribute to satellite observations of high levels of HCN in the lower stratosphere above the Asian monsoon. HCN was also emitted in significant quantities by several non-biomass burning sources. BTEX compounds (benzene, toluene, ethylbenzene, xylenes) were major emissions from both dung- (∼ 4.5 g kg−1) and wood-fuel (∼ 1.5 g kg−1) cooking fires, and a simple method to estimate indoor exposure to the many measured important air toxics is described. Biogas emerged as the cleanest cooking technology of approximately a dozen stove–fuel combinations measured. Crop residue burning produced relatively high emissions of oxygenated organic compounds (∼ 12 g kg−1) and SO2 (2.54 ± 1.09 g kg−1). Two brick kilns co-firing different amounts of biomass with coal as the primary fuel produced contrasting results. A zigzag kiln burning mostly coal at high efficiency produced larger amounts of BC, HF, HCl, and NOx, with the halogenated emissions likely coming from the clay. The clamp kiln (with relatively more biomass fuel) produced much greater quantities of most individual organic gases, about twice as much BrC, and significantly more known and likely organic aerosol precursors. Both kilns were significant SO2 sources with their emission factors averaging 12.8 ± 0.2 g kg−1. Mixed-garbage burning produced significantly more BC (3.3 ± 3.88 g kg−1) and BTEX (∼ 4.5 g kg−1) emissions than in previous measurements. For all fossil fuel sources, diesel burned more efficiently than gasoline but produced larger NOx and aerosol emission factors. Among the least efficient sources sampled were gasoline-fueled motorcycles during start-up and idling for which the CO EF was on the order of ∼ 700 g kg−1 – or about 10 times that of a typical biomass fire. Minor motorcycle servicing led to minimal if any reduction in gaseous pollutants but reduced particulate emissions, as detailed in a companion paper (Jayarathne et al., 2016). A small gasoline-powered generator and an “insect repellent fire” were also among the sources with the highest emission factors for pollutants. These measurements begin to address the critical data gap for these important, undersampled sources, but due to their diversity and abundance, more work is needed.

We conducted simulations using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.5 to study air quality in East Asia at a spatial resolution of 20 km × 20 km. We find large discrepancies between two existing emissions inventories: the Regional Emission Inventory in ASia version 2 (REAS) and the Emissions Database for Global Atmospheric Research version 4.2 (EDGAR) at the provincial level in China, with maximum differences of up to 500 % for CO emissions, 190 % for NO, and 160 % for primary PM10. Such discrepancies in the magnitude and the spatial distribution of emissions for various species lead to a 40–70 % difference in surface PM10 concentrations, 16–20 % in surface O3 mixing ratios, and over 100 % in SO2 and NO2 mixing ratios in the polluted areas of China. WRF-Chem is sensitive to emissions, with the REAS-based simulation reproducing observed concentrations and mixing ratios better than the EDGAR-based simulation for July 2007. We conduct additional model simulations using REAS emissions for January, April, July, and October of 2007 and evaluate simulations with available ground-level observations. The model results illustrate clear regional variations in the seasonal cycle of surface PM10 and O3 over East Asia. The model meets the air quality model performance criteria for both PM10 (mean fractional bias, MFB ⩽ ±60 %) and O3 (MFB ⩽ ±15 %) at most of the observation sites, although the model underestimates PM10 over northeastern China in January. The model predicts the observed SO2 well at sites in Japan, while it tends to overestimate SO2 in China in July and October. The model underestimates observed NO2 in all 4 months. Our study highlights the importance of constraining emissions at the provincial level for regional air quality modeling over East Asia. Our results suggest that future work should focus on the improvement of provincial-level emissions especially estimating primary PM, SO2, and NOx.

This study assessed the sources, magnitudes, and chemical compositions of household air pollution (HAP) and personal exposure in traditional Tibetan households. We measured 24-h personal exposures to PM2.5 and kitchen area black carbon (BC) concentrations, using MicroPEMs and microAeths, respectively. Particulate polycyclic aromatic hydrocarbon (PAH) and inorganic element concentrations were quantified via post analyses of a subset of MicroPEM sample filters. Household surveys regarding participant demographics, cookstove usage, household fuel, cooking behaviors, and lifestyles were collected. The results reaffirm that burning firewood and yak dung, mainly for cooking, leads to high PM2.5 and BC exposures. The geometric mean concentration (95% confidence interval, CI) was 74.3 (53.6, 103) μg/m3 for PM2.5 and the arithmetic mean ± standard deviation (SD) concentration was 4.90 ± 5.01 μg/m3 for BC and 292 ± 364 ng/m3 for 15 identified PAHs, respectively. The arithmetic mean ± SD of mass concentrations of 24 detected elements ranged from 0.76 ± 0.91 ng/m3 (Co) to 1.31 ± 1.35 μg/m3 (Si). Our statistical analyses further illustrated that the high concentrations of PM2.5, BC, and most PAHs and metals, are significantly associated with nomadic village, poorer stove/chimney conditions and yak dung burning. The results from this study show that substantial HAP exposure is prevalent in Tibetan households and requires immediate actions to mitigate potential negative environmental health impacts. The observational data also revealed the possibility of other important sources (e.g. traffic and garbage burning) that have contributed to personal exposures. These findings improve our understanding of HAP exposure and potential health risks in Tibetan communities and will help inform strategies for reducing HAP in Tibetan households and beyond.

China has experienced rapid agricultural development over recent decades, accompanied by increased fertilizer consumption in croplands; yet, the trend and drivers of the associated nitrous oxide (N

China has experienced rapid agricultural development over recent decades, accompanied by increased fertilizer consumption in croplands; yet, the trend and drivers of the associated nitrous oxide (N2 O) emissions remain uncertain. The primary sources of this uncertainty are the coarse spatial variation of activity data and the incomplete model representation of N2 O emissions in response to agricultural management. Here, we provide new data-driven estimates of cropland-N2 O emissions across China in 1990-2014, compiled using a global cropland-N2 O flux observation dataset, nationwide survey-based reconstruction of N-fertilization and irrigation, and an updated nonlinear model. In addition, we have evaluated the drivers behind changing cropland-N2 O patterns using an index decomposition analysis approach. We find that China's annual cropland-N2 O emissions increased on average by 11.2GgN/year2 (p&nbsp

Air pollution has large impacts on the Hindu Kush Himalaya (HKH), affecting not just the health of people and ecosystems, but also climate, the cryosphere, monsoon patterns, water availability, agriculture, and incomes (established but incomplete). Although the available data are not comprehensive, they clearly show that the HKH receives significant amounts of air pollution from within and outside of the region, including the Indo-Gangetic Plain (IGP), a region where many rural areas are severely polluted. In addition, the HKH receives trans-boundary pollution from other parts of Asia. This chapter surveys the evidence on regional air pollution and considers options for reducing it, while underlining the need for regional collaboration in mitigation efforts. As described in Chap. 1, the HKH region is fragile and rapidly changing; while the outcome of the interplay of complex drivers is difficult to predict, it will have major consequences. That holds true for air pollution as well.