The Surface PARTiculate mAtter Network (SPARTAN) is a long-term project that includes characterization of chemical and physical attributes of aerosols from filter samples collected worldwide. This paper discusses the ongoing efforts of SPARTAN to define and quantify major ions and trace metals found in fine particulate matter (PM_2.5). Our methods infer the spatial and temporal variability of PM_2.5 in a cost-effective manner. Gravimetrically weighed filters represent multi-day averages of PM_2.5, with a collocated nephelometer sampling air continuously. SPARTAN instruments are paired with AErosol RObotic NETwork (AERONET) sun photometers to better understand the relationship between ground-level PM_2.5 and columnar aerosol optical depth (AOD). We have examined the chemical composition of PM_2.5 at 12 globally dispersed, densely populated urban locations and a site at Mammoth Cave (US) National Park used as a background comparison. So far, each SPARTAN location has been active between the years 2013 and 2016 over periods of 2–26 months, with an average period of 12 months per site. These sites have collectively gathered over 10 years of quality aerosol data. The major PM_2.5 constituents across all sites (relative contribution ± SD) are ammoniated sulfate (20 % ± 11 %), crustal material (13.4 % ± 9.9 %), equivalent black carbon (11.9 % ± 8.4 %), ammonium nitrate (4.7 % ± 3.0 %), sea salt (2.3 % ± 1.6 %), trace element oxides (1.0 % ± 1.1 %), water (7.2 % ± 3.3 %) at 35 % RH, and residual matter (40 % ± 24 %). Analysis of filter samples reveals that several PM_2.5 chemical components varied by more than an order of magnitude between sites. Ammoniated sulfate ranges from 1.1 µg m⁻³ (Buenos Aires, Argentina) to 17 µg m⁻³ (Kanpur, India in the dry season). Ammonium nitrate ranged from 0.2 µg m⁻³ (Mammoth Cave, in summer) to 6.8 µg m⁻³ (Kanpur, dry season). Equivalent black carbon ranged from 0.7 µg m⁻³ (Mammoth Cave) to over 8 µg m⁻³ (Dhaka, Bangladesh and Kanpur, India). Comparison of SPARTAN vs. coincident measurements from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network at Mammoth Cave yielded a high degree of consistency for daily PM_2.5 (r² = 0.76, slope = 1.12), daily sulfate (r² = 0.86, slope = 1.03), and mean fractions of all major PM_2.5 components (within 6 %). Major ions generally agree well with previous studies at the same urban locations (e.g. sulfate fractions agree within 4 % for 8 out of 11 collocation comparisons). Enhanced anthropogenic dust fractions in large urban areas (e.g. Singapore, Kanpur, Hanoi, and Dhaka) are apparent from high Zn : Al ratios. The expected water contribution to aerosols is calculated via the hygroscopicity parameter κ_v for each filter. Mean aggregate values ranged from 0.15 (Ilorin) to 0.28 (Rehovot). The all-site parameter mean is 0.20 ± 0.04. Chemical composition and water retention in each filter measurement allows inference of hourly PM_2.5 at 35 % relative humidity by merging with nephelometer measurements. These hourly PM_2.5 estimates compare favourably with a beta attenuation monitor (MetOne) at the nearby US embassy in Beijing, with a coefficient of variation r² = 0.67 (n = 3167), compared to r² = 0.62 when κ_v was not considered. SPARTAN continues to provide an open-access database of PM_2.5 compositional filter information and hourly mass collected from a global federation of instruments.

Meeting future world energy needs while addressing climate change requires large-scale deployment of low or zero greenhouse gas (GHG) emission technologies such as wind energy. The widespread availability of wind power has fueled substantial interest in this renewable energy source as one of the needed technologies. For very large-scale utilization of this resource, there are however potential environmental impacts, and also problems arising from its inherent intermittency, in addition to the present need to lower unit costs. To explore some of these issues, we use a three-dimensional climate model to simulate the potential climate effects associated with installation of wind-powered generators over vast areas of land or coastal ocean. Using wind turbines to meet 10% or more of global energy demand in 2100, could cause surface warming exceeding 1 °C over land installations. In contrast, surface cooling exceeding 1 °C is computed over ocean installations, but the validity of simulating the impacts of wind turbines by simply increasing the ocean surface drag needs further study. Significant warming or cooling remote from both the land and ocean installations, and alterations of the global distributions of rainfall and clouds also occur. These results are influenced by the competing effects of increases in roughness and decreases in wind speed on near-surface turbulent heat fluxes, the differing nature of land and ocean surface friction, and the dimensions of the installations parallel and perpendicular to the prevailing winds. These results are also dependent on the accuracy of the model used, and the realism of the methods applied to simulate wind turbines. Additional theory and new field observations will be required for their ultimate validation. Intermittency of wind power on daily, monthly and longer time scales as computed in these simulations and inferred from meteorological observations, poses a demand for one or more options to ensure reliability, including backup generation capacity, very long distance power transmission lines, and onsite energy storage, each with specific economic and/or technological challenges.

Fires including peatland burning in Southeast Asia have become a major concern to the general public as well as governments in the region. This is because aerosols emitted from such fires can cause persistent haze events under certain weather conditions in downwind locations, degrading visibility and causing human health issues. In order to improve our understanding of the spatiotemporal coverage and influence of biomass burning aerosols in Southeast Asia, we have used surface visibility and particulate matter concentration observations, supplemented by decade-long (2003 to 2014) simulations using the Weather Research and Forecasting (WRF) model with a fire aerosol module, driven by high-resolution biomass burning emission inventories. We find that in the past decade, fire aerosols are responsible for nearly all events with very low visibility (< 7 km). Fire aerosols alone are also responsible for a substantial fraction of low-visibility events (visibility < 10 km) in the major metropolitan areas of Southeast Asia: up to 39 % in Bangkok, 36 % in Kuala Lumpur, and 34 % in Singapore. Biomass burning in mainland Southeast Asia accounts for the largest contribution to total fire-produced PM_2.5 in Bangkok (99 %), while biomass burning in Sumatra is a major contributor to fire-produced PM_2.5 in Kuala Lumpur (50 %) and Singapore (41 %). To examine the general situation across the region, we have further defined and derived a new integrated metric for 50 cities of the Association of Southeast Asian Nations (ASEAN): the haze exposure day (HED), which measures the annual exposure days of these cities to low visibility (< 10 km) caused by particulate matter pollution. It is shown that HEDs have increased steadily in the past decade across cities with both high and low populations. Fire events alone are found to be responsible for up to about half of the total HEDs. Our results suggest that in order to improve the overall air quality in Southeast Asia, mitigation policies targeting both biomass burning and fossil fuel burning sources need to be implemented.