This Tropospheric Ozone Assessment Report (TOAR) on the current state of knowledge of ozone metrics of relevance to vegetation (TOAR-Vegetation) reports on present-day global distribution of ozone at over 3300 vegetated sites and the long-term trends at nearly 1200 sites.TOAR-Vegetationfocusses on three metrics over vegetation-relevant time-periods across major world climatic zones: M12, the mean ozone during 08:00–19:59; AOT40, the accumulation of hourly mean ozone values over 40 ppb during daylight hours, and W126 with stronger weighting to higher hourly mean values, accumulated during 08:00–19:59.Although the density of measurement stations is highly variable across regions, in general, the highest ozone values (mean, 2010–14) are in mid-latitudes of the northern hemisphere, including southern USA, the Mediterranean basin, northern India, north, north-west and east China, the Republic of Korea and Japan. The lowest metric values reported are in Australia, New Zealand, southern parts of South America and some northern parts of Europe, Canada and the USA. Regional-scale assessments showed, for example, significantly higher AOT40 and W126 values in East Asia (EAS) than Europe (EUR) in wheat growing areas (p< 0.05), but not in rice growing areas. In NAM, the dominant trend during 1995–2014 was a significant decrease in ozone, whilst in EUR it was no change and in EAS it was a significant increase.TOAR-Vegetation provides recommendations to facilitate a more complete global assessment of ozone impacts on vegetation in the future, including: an increase in monitoring of ozone and collation of field evidence of the damaging effects on vegetation; an investigation of the effects on peri-urban agriculture and in mountain/upland areas; inclusion of additional pollutant, meteorological and inlet height data in the TOAR dataset; where not already in existence, establishing new region-specific thresholds for vegetation damage and an innovative integration of observations and modelling including stomatal uptake of the pollutant.

Elevated PM 2.5 concentrations frequently cause severe air pollution events in Delhi. Till recently, the effect of crop residue burning on the air quality in Delhi has not been fully quantified and the approaches to control the impact of fire emissions have not been effective. In this study, for the first time, we quantified the statewise contribution of post-monsoon crop residue burning in the northwestern states of India to surface PM 2.5 concentrations in Delhi using several sensitivity experiments with the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and FINNv1.5 fire emission inventory. Results were evaluated with ground-based observations in Delhi (21 stations), Punjab, and Haryana (14 stations). On average, ∼20% of PM 2.5 concentration in Delhi during the post-monsoon season (October−November) was found to be contributed by nonlocal fire emissions. However, on typical air pollution events, fire emissions contributed as high as 50−75% (80−120 μg/m 3 ) to PM 2.5 in Delhi, highlighting the importance of both external transport and local emissions to PM 2.5 pollution in Delhi.

Abstract. In this study we use a high-quality data set of in situ ozone measurements at a suburban site called Mohali in the state of Punjab to estimate ozone-related crop yield losses for wheat, rice, cotton and maize for Punjab and the neighbouring state Haryana for the years 2011–2013. We intercompare crop yield loss estimates according to different exposure metrics, such as AOT40 (accumulated ozone exposure over a threshold of 40) and M7 (mean 7-hour ozone mixing ratio from 09:00 to 15:59), for the two major crop growing seasons of kharif (June–October) and rabi (November–April) and establish a new crop-yield–exposure relationship for southern Asian wheat, maize and rice cultivars. These are a factor of 2 more sensitive to ozone-induced crop yield losses compared to their European and American counterparts. Relative yield losses based on the AOT40 metrics ranged from 27 to 41 % for wheat, 21 to 26 % for rice, 3 to 5 % for maize and 47 to 58 % for cotton. Crop production losses for wheat amounted to 20.8 ± 10.4 million t in the fiscal year of 2012–2013 and 10.3 ± 4.7 million t in the fiscal year of 2013–2014 for Punjab and Haryana taken together. Crop production losses for rice totalled 5.4 ± 1.2 million t in the fiscal year of 2012–2013 and 3.2 ± 0.8 million t in the year 2013–2014 for Punjab and Haryana taken together. The Indian National Food Security Ordinance entitles ~ 820 million of India's poor to purchase about 60 kg of rice or wheat per person annually at subsidized rates. The scheme requires 27.6 Mt of wheat and 33.6 Mt of rice per year. The mitigation of ozone-related crop production losses in Punjab and Haryana alone could provide > 50 % of the wheat and ~ 10 % of the rice required for the scheme. The total economic cost losses in Punjab and Haryana amounted to USD 6.5 ± 2.2 billion in the fiscal year of 2012–2013 and USD 3.7 ± 1.2 billion in the fiscal year of 2013–2014. This economic loss estimate represents a very conservative lower limit based on the minimum support price of the crop, which is lower than the actual production costs. The upper limit for ozone-related crop yield losses in all of India currently amounts to 3.5–20 % of India's GDP. The mitigation of high surface ozone would require relatively little investment in comparison to the economic losses incurred presently. Therefore, ozone mitigation can yield massive benefits in terms of ensuring food security and boosting the economy. The co-benefits of ozone mitigation also include a decrease in the ozone-related mortality and morbidity and a reduction of the ozone-induced warming in the lower troposphere.

Abstract.A positive matrix factorization model (US EPA PMF version 5.0) was applied for the source apportionment of the dataset of 37 non-methane volatile organic compounds (NMVOCs) measured from 19 December 2012 to 30 January 2013 during the SusKat-ABC international air pollution measurement campaign using a proton-transfer-reaction time-of-flight mass spectrometer in the Kathmandu Valley. In all, eight source categories were identified with the PMF model using the new constrained model operation mode. Unresolved industrial emissions and traffic source factors were the major contributors to the total measured NMVOC mass loading (17.9 and 16.8 %, respectively) followed by mixed industrial emissions (14.0 %), while the remainder of the source was split approximately evenly between residential biofuel use and waste disposal (10.9 %), solvent evaporation (10.8 %), biomass co-fired brick kilns (10.4 %), biogenic emissions (10.0 %) and mixed daytime factor (9.2 %). Conditional probability function (CPF) analyses were performed to identify the physical locations associated with different sources. Source contributions to individual NMVOCs showed that biomass co-fired brick kilns significantly contribute to the elevated concentrations of several health relevant NMVOCs such as benzene. Despite the highly polluted conditions, biogenic emissions had the largest contribution (24.2 %) to the total daytime ozone production potential, even in winter, followed by solvent evaporation (20.2 %), traffic (15.0 %) and unresolved industrial emissions (14.3 %).Secondary organic aerosol (SOA) production had approximately equal contributions from biomass co-fired brick kilns (28.9 %) and traffic (28.2 %). Comparison of PMF results based on the in situ data versus REAS v2.1 and EDGAR v4.2 emission inventories showed that both the inventories underestimate the contribution of traffic and do not take the contribution of brick kilns into account. In addition, the REAS inventory overestimates the contribution of residential biofuel use and underestimates the contribution of solvent use and industrial sources in the Kathmandu Valley. The quantitative source apportionment of major NMVOC sources in the Kathmandu Valley based on this study will aid in improving hitherto largely un-validated bottom-up NMVOC emission inventories, enabling more focused mitigation measures and improved parameterizations in chemical transport models.

Angstrom exponent measurements of equivalent black carbon (BCeq) have recently been introduced as a novel tool to apportion the contribution of biomass burning sources to the BCeq mass. The BCeq is the mass of ideal BC with defined optical properties that, upon deposition on the aethalometer filter tape, would cause equal optical attenuation of light to the actual PM2.5 aerosol deposited. The BCeq mass hence is identical to the mass of the total light-absorbing carbon deposited on the filter tape. Here, we use simultaneously collected data from a seven-wavelength aethalometer and a high-sensitivity proton-transfer reaction mass spectrometer installed at a suburban site in Mohali (Punjab), India, to identify a number of biomass combustion plumes. The identified types of biomass combustion include paddy- and wheat-residue burning, leaf litter, and garbage burning. Traffic plumes were selected for comparison. We find that the combustion efficiency, rather than the fuel used, determines αabs, and consequently, the αabs can be ∼1 for flaming biomass combustion and >1 for older vehicles that operate with poorly optimized engines. Thus, the absorption angstrom exponent is not representative of the fuel used and, therefore, cannot be used as a generic tracer to constrain source contributions.

Accurate emission inventories serve as critical inputs for air quality and climate models but are poorly constrained over India. We present a new municipal open waste burning emission inventory from India (OWBEII), at a resolution of 0.1°× 0.1°. Out of the 216 (201−232) Tg y −1 of waste produced in the year 2015, 68 (45−105) Tg y −1 was burned in the open. To determine emissions from waste burning, emission factors of 59 non-methane volatile organic compounds (NMVOCs), CH 4 , CO 2 , CO, and NO x were measured from garbage fires in rural and urban sites in India. The NMVOC emissions from open waste burning of 1.4−2 Tg y −1 increase India's total anthropogenic NMVOC budget by 8−12%, while BC emissions (40−110 Ggy −1 ) increase the total anthropogenic BC emissions by 8−12%. Open waste burning in India emits 3−7 Tg y −1 of CO and 58−130 Tg y −1 of CO 2 . Emissions increase the total anthropogenic CO and CO 2 in the MIX-Asia inventory by 4−11% and 2−6%, respectively. Open waste burning may affect atmospheric OH reactivity and ozone formation rates downwind of urban centers through the emission of other highly reactive compounds such as acetaldehyde (20−320 Gg y −1 ), propene (50−170 Gg y −1 ), and ethene (50−190 Gg y −1 ) and is s source of carcinogenic benzene (30−280 Gg y −1 ).

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