Substituting alternative materials and energy sources with forest biomass can cause significant environmental consequences, such as alteration in the released emissions which can be described by displacement factors (DFs). Until now, DFs of wood-based materials have included greenhouse gas (GHG) emissions and have been associated with lower fossil and process-based emissions than non-wood counterparts. In addition to GHGs, aerosols released in combustion processes, for example, alter radiative forcing in the atmosphere and consequently have an influence on climate. In this study, the objective was to quantify the changes in the most important aerosol emission components for cases when wood-based materials and energy were used to replace the production of high-density polyethylene (HDPE) plastic, common fossil-based construction materials (concrete, steel and brick), non-wood textile materials and energy produced by fossil fuels and peat. For this reason, we expanded the DF calculations to include aerosol emissions of total suspended particles (TSP), respirable particulate matter (PM10), fine particles (PM2.5), black carbon (BC), nitrogen oxides (NOx), sulphur dioxide (SO2) and non-methane volatile organic compounds (NMVOCs) based on the embodied energies of materials and energy sources. The DFs for cardboard implied a decrease in BC, SO2 and NMVOC emissions but an increase in the other emission components. DFs for sawn wood mainly indicated higher emissions of both particles and gaseous emissions compared to non-wood counterparts. DFs for wood-based textiles demonstrated increased particle emissions and reduced gaseous emissions. DFs for energy biomass mainly implied an increase in emissions, especially if biomass was combusted in small-scale appliances. Our main conclusion highlights the critical need to thoroughly assess how using forest biomass affects aerosol emissions. This improved understanding of the aerosol emissions of the forestry sector is crucial for a comprehensive evaluation of the climate and health implications associated with forest biomass use.

Aerosols affect Earth's climate both directly and indirectly, which is the largest uncertainty in the assessment of radiative forcings affecting anthropogenic climate change. The standard Aerosol Robotic Network (AERONET) aerosol products have been widely used for more than 30 years. Currently, there is strong community interest in the possibility of determining aerosol composition directly from remote sensing observations. This work presents the results of applying such a recently developed approach by Li et al. to extended datasets of the directional sky radiances and spectral aerosol optical depth (AOD) measured by AERONET for the retrievals of aerosol components. First, the validation of aerosol optical properties retrieved by this component approach with AERONET standard products shows good agreement. Then, spatiotemporal variations of the obtained aerosol component concentration are characterized globally, especially the absorbing aerosol species (black carbon, brown carbon, and iron oxides) and scattering aerosol species (organic carbon, quartz, and inorganic salts). Finally, we compared the black carbon (BC) and dust column concentration retrievals to the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), products in several regions of interest (Amazon zone, Desert, and Taklamakan Desert) for new insights on the quantitative assessment of MERRA-2 aerosol composition products (R = 0.60-0.85 for BC; R = 0.75-0.90 for dust). The new value-added and long-term aerosol composition product globally is available online (https://doi.org/10.6084/ m9.figshare.25415239.v1), which provides important measurements for the improvement and optimization of aerosol modeling to enhance estimation of the aerosol radiative forcing. SIGNIFICANCE STATEMENT: In the assessment of climate change, the uncertainty associated with aerosol radiative forcing is the largest one. The purpose of this study is to provide a new value-added and long-term aerosol composition (including absorbing and scattering aerosol species) inversion dataset derived from Aerosol Robotic Network (AERONET) measurements for characterizing their spatiotemporal variations at global scale. We find some new insights on the quantitative assessment of black carbon and dust column concentration products in the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Our results and aerosol composition inversion dataset will provide robust support for the overall improvement and optimization of aerosol modeling to better understand the aerosol radiative forcing.

Vehicle -emitted fine particulate matter (PM 2.5 ) has been associated with significant health outcomes and environmental risks. This study estimates the contribution of traffic -related exhaust emissions (TREE) to observed PM 2.5 using a novel factorization framework. Specifically, co -measured nitrogen oxides (NO x ) concentrations served as a marker of vehicle -tailpipe emissions and were integrated into the optimization of a Non -negative Matrix Factorization (NMF) analysis to guide the factor extraction. The novel TREE-NMF approach was applied to long-term (2012 - 2019) PM 2.5 observations from air quality monitoring (AQM) stations in two urban areas. The extracted TREE factor was evaluated against co -measured black carbon (BC) and PM 2.5 species to which the TREE-NMF optimization was blind. The contribution of the TREE factor to the observed PM 2.5 concentrations at an AQM station from the first location showed close agreement ( R 2 = 0 .79) with monitored BC data. In the second location, a comparison of the extracted TREE factor with measurements at a nearby Surface PARTiculate mAtter Network (SPARTAN) station revealed moderate correlations with PM 2.5 species commonly associated with fuel combustion, and a good linear regression fit with measured equivalent BC concentrations. The estimated concentrations of the TREE factor at the second location accounted for 7 - 11 % of the observed PM 2.5 in the AQM stations. Moreover, analysis of specific days known to be characterized by little traffic emissions suggested that approximately 60 - 78 % of the traffic -related PM 2.5 concentrations could be attributed to particulate traffic -exhaust emissions. The methodology applied in this study holds great potential in areas with limited monitoring of PM 2.5 speciation, in particular BC, and its results could be valuable for both future environmental health research, regional radiative forcing estimates, and promulgation of tailored regulations for traffic -related air pollution abatement.

In this study, air pollutants were analyzed at a low-industry city on the Silk Road Economic Belt of Northwestern China from 2015 to 2018. The results show that SO2 and CO had a decreasing trend and NO2, O-3, PM2.5, and PM10 had an increasing trend during the study period. The primary characteristic pollutants were PM2.5 and PM10, which were higher than China's Grade II standard. SO2, NO2, CO, PM2.5, and PM10 concentrations showed similar seasonal variation patterns: the highest pollutant concentration was in winter and the lowest in summer. Those pollutants showed a similar diurnal pattern with two peaks, one at 7:00 to 9:00 and another at 21:00 to 22:00. However, O-3 concentration was highest in summer and lowest in winter, with a unimodal diurnal variation pattern. The annual average pollution concentrations in Tianshui in 2017 were substantially lower than the concentrations reported by most cities in China. By examining the meteorological conditions at a daily scale, we found that Tianshui was highly influenced by local emissions and a southwest wind. Potential source contributions and concentration weighted trajectory analyses indicated that the pollution from Gansu, Sichuan, Qinghai, and Shaanxi Province could affect the pollution concentration in Tianshui. The results provide directions for the government to take in formulating regional air pollution prevention and control measures and to improve air quality.

The Tibetan Plateau, referred as the last pure land on the earth, is frequently exposure to heavy air pollution during springtime. Here, we find South Asia biomass burning is crucial to cause the heavy springtime air pollution over the Tibetan Plateau, which explain the most (more than 60%) of aerosol components in the region, although its contribution to gaseous pollutants is not significant. South Asian biomass burning mainly affects primary PM2.5 components black carbon (65.3%) and organic carbon (79.5%) over the Tibetan Plateau, but has little influence (less than 5%) on second aerosol components (sulfate, nitrate, and ammonium). The transboundary transmissions of aerosols were regulated by a combination of large-scale westerly winds and regional mountain-valley winds in springtime. In addition to worsen air quality, aerosols from South Asian biomass burning lead to surface temperature decrease of 0.06 degrees C, and precipitation reduction of 3.9 mm over the Tibetan Plateau during springtime. These climate changes will threat the fragile ecosystem over the Tibetan Plateau, such as plant growth and flowering during springtime. Overall, our findings demonstrate a necessary and urgency to reduce biomass burning emissions over South Asia to protect the Tibetan Plateau environment.

To understand the characteristics of particulate matter (PM) and other air pollutants in Xinjiang, a region with one of the largest sand-shifting deserts in the world and significant natural dust emissions, the concentrations of six air pollutants monitored in 16 cities were analyzed for the period January 2013-June 2019. The annual mean PM2.5, PM10, SO2, NO2, CO, and O-3 concentrations ranged from 51.44 to 59.54 mu g m(-3), 128.43-155.28 mu g m(-3), 10.99-17.99 mu g m(-3), 26.27-31.71 mu g m(-3), 1.04-1.32 mg m(-3), and 55.27-65.26 mu g m(-3), respectively. The highest PM concentrations were recorded in cities surrounding the Taklimakan Desert during the spring season and caused by higher amounts of wind-blown dust from the desert. Coarse PM (PM10-2.5) was predominant, particularly during the spring and summer seasons. The highest PM2.5/PM10 ratio was recorded in most cities during the winter months, indicating the influence of anthropogenic emissions in winters. The annual mean PM2.5 (PM10) concentrations in the study area exceeded the annual mean guidelines recommended by the World Health Organization (WHO) by a factor of ca. similar to 5-6 (similar to 7-8). Very high ambient PM concentrations were recorded during March 19-22, 2019, that gradually influenced the air quality across four different cities, with daily mean PM2.5 (PM10) concentrations similar to 8-54 (similar to 26-115) times higher than the WHO guidelines for daily mean concentrations, and the daily mean coarse PM concentration reaching 4.4 mg m(-3). Such high PM2.5 and concentrations pose a significant risk to public health. These findings call for the formulation of various policies and action plans, including controlling the land degradation and desertification and reducing the concentrations of PM and other air pollutants in the region. (C) 2020 Elsevier Ltd. All rights reserved.

Characteristics of carbonaceous aerosol (CA) and its light absorption properties are limited in Karachi, which is one of the most polluted metropolitan cities in South Asia. This study presents a comprehensive measurement of seasonality of CA compositions and mass absorption cross- (MAC) of elemental carbon (EC) and water-soluble organic carbon (WSOC) in total suspended particles (TSP) collected from February 2015 to March 2017 in the southwest part of Karachi. The average TSP, organic carbon (OC), and EC concentrations were extremely high with values as 391.0 +/- 217.0, 37.2 +/- 28.0, and 8.53 +/- 6.97 mg/m(3), respectively. These components showed clear seasonal variations with high concentrations occurring during fall and winter followed by spring and summer. SO42-, NO3-, K+, and NH4+ showed similar variations with CA, implying the significant influence on atmospheric pollutants from anthropogenic activities. Relatively lower OC/EC ratio (4.20 +/- 2.50) compared with remote regions further indicates fossil fuel combustion as a primary source of CA. Meanwhile, sea salt and soil dust are important contribution sources for TSP. The average MAC of EC (632 nm) and WSOC (365 nm) were 6.56 +/- 2.70 and 0.97 +/- 0.37 m(2)/g, respectively. MACEC is comparable to that in urban areas but lower than that in remote regions, indicating the significant influence of local emissions. MACWSOC showed opposite distribution with EC, further suggesting that OC was significantly affected by local fossil fuel combustion. In addition, dust might be an important factor increasing MACWSOC particularly during spring and summer. (C) 2020 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.

Aerosol direct radiative forcing is strongly dependent on aerosol distributions and aerosol types. A detailed understanding of such information is still missing at the Alpine region, which currently undergoes amplified climate warming. Our goal was to study the vertical variability of aerosol types within and above the Vipava valley (45.87 degrees N, 13.90 degrees E, 125 m a.s.1.) to reveal the vertical impact of each particular aerosol type on this region, a representative complex terrain in the Alpine region which often suffers from air pollution in the wintertime. This investigation was performed using the entire dataset of a dual-wavelength polarization Raman lidar system, which covers 33 nights from September to December 2017. The lidar provides measurements from midnight to early morning (typically from 00:00 to 06:00 CET) to provide aerosol-type dependent properties, which include particle linear depolarization ratio, lidar ratio at 355 nm and the aerosol backscatter Angstrom exponent between 355 nm and 1064 nm. These aerosol properties were compared with similar studies, and the aerosol types were identified by the measured aerosol optical properties. Primary anthropogenic aerosols within the valley are mainly emitted from two sources: individual domestic heating systems, which mostly use biomass fuel, and traffic emissions. Natural aerosols, such as mineral dust and sea salt, are mostly transported over large distances. A mixture of two or more aerosol types was generally found. The aerosol characterization and statistical properties of vertical aerosol distributions were performed up to 3 km.

Total suspended particles (TSP) were collected in Lumbini from April 2013 to March 2016 to better understand the characteristics of carbonaceous aerosol (CA) concentrations, compositions and sources and their light absorption properties in rural region of severe polluted Indo-Gangetic Plain (IGP). Extremely high TSP (203.9 +/- 109.6 mu g m(-3)), organic carbon (OC 32.1 +/- 21.7 mu g m(-3)), elemental carbon (EC 6.44 +/- 3.17 mu g m(-3)) concentrations were observed in Lumbini particularly during winter and post-monsoon seasons, reflecting the combined influences of emission sources and weather conditions. SO42- (7.34 +/- 4.39 mu g m(-3)) and Ca2+ (5.46 +/- 5.20 mu g m(-3)) were the most dominant anion and cation in TSP. These components were comparable to those observed in urban areas in South and East Asia but significantly higher than those in remote regions over the Himalayas and Tibetan Plateau, suggesting severe air pollution in the study region. Various combustion activities including industry, vehicle emission, and biomass burning are the main reasons for high pollutant concentrations. The variation of OC/EC ratio further suggested that biomass such as agro-residue burning contributed a lot for CA, particularly during the non-monsoon season. The average mass absorption cross- of EC (MAC(EC)) and water-soluble organic carbon (MAC(WSOC)) were 7.58 +/- 3.39 and 1.52 +/- 0.41 m(2) g(-1), respectively, indicating that CA in Lumbini was mainly affected by local emissions. Increased biomass burning decreased MAC(EC); whereas, it could result in high MAC(WSOC) during the non-monsoon season. Furthermore, dust is one important factor causing higher MAC(WSOC) during the pre-monsoon season.

This study reports for the first time the content of trace elements and light-absorbing particles (LAPs) in snow samples collected from a Peruvian glacier (Huaytapallana). The sampling campaign was carried out monthly from November 2015 to March 2019. The trace elements content was quantified by inductively coupled plasma mass spectrometry, while LAPs were analyzed using the light absorption heating method. The chemical composition dataset was assessed by descriptive statistics and t-test for assessing dry season and wet season differences. In addition, enrichment factor (EF) and hierarchical cluster analysis (HCA) were employed to identify possible emission sources. The snow, ice, and aerosol radiative (SNICAR) model was used to measure the effect of LAPs on snow albedo and radiative forcing (RF). Based on analysis of EF and HCA, it was shown that Al, Ti, Si, Co, Ce, Sr, Mn, Mg, Ba and Na have mainly natural sources; K, Ca, Fe, Cu, Pb and As have a mixture of natural and anthropogenic sources, and Zn has anthropogenic source. SNICAR model results indicated that LAPs reduced the snow albedo by up 4.5 % in the dry season with RF values as high as 33 W/m(2). Therefore, we conclude that the presence of these particles substantially increases melt or sublimation rates of Peruvian glaciers.