Correlations between fine particulate matter (PM2.5) and meteorological variables in the United States: Implications for the sensitivity of PM2.5 to climate change

We applied a multiple linear regression (MLR) model to study the correlations of total PM_2.5 and its components with meteorological variables using an 11-year (1998–2008) observational record over the contiguous US. The data were deseasonalized and detrended to focus on synoptic-scale correlations. We find that daily variation in meteorology as described by the MLR can explain up to 50% of PM_2.5 variability with temperature, relative humidity (RH), precipitation, and circulation all being important predictors. Temperature is positively correlated with sulfate, organic carbon (OC) and elemental carbon (EC) almost everywhere. The correlation of nitrate with temperature is negative in the Southeast but positive in California and the Great Plains. RH is positively correlated with sulfate and nitrate, but negatively with OC and EC. Precipitation is strongly negatively correlated with all PM_2.5 components. We find that PM_2.5 concentrations are on average 2.6 μg m^?3 higher on stagnant vs. non-stagnant days. Our observed correlations provide a test for chemical transport models used to simulate the sensitivity of PM_2.5 to climate change. They point to the importance of adequately representing the temperature dependence of agricultural, biogenic and wildfire emissions in these models.     

Hydrographic characterization of southeast Arabian Sea during the wane of southwest monsoon and spring intermonsoon

Seasonal variation of the hydrography along the southeast Arabian Sea is described using data collected onboard FORV Sagar Sampada in September–October 2003 (later phase of Southwest monsoon, SWM) and March–April 2004 (Spring inter monsoon, SIM). During the later phase of the SWM, upwelling was in the withdrawal phase and the frontal structure was clearer in the northern sections (13 and 15°N lat) indicating strong upwelling in the area. The driving force of upwelling is identified as the combination of alongshore wind stress and remote forcing with a latitudinal variability. Although a more prominent upwelling was found in the north, a maximum surface Chlorophyll-a was found in the south (10°N). During the SIM, the area was characterized by oligotrophic water with relatively high Sea Surface Temperature (>29°C) and low salinity (33.8 to 35.4). During March, the surface hydrography was found to be controlled mainly by the intrusion of low-saline waters from the south, while during September by the high saline water from the north. The presence of various water masses [Arabian Sea High Salinity Water (ASHSW), Persian Gulf Water (PGW), Red Sea Water (RSW)] and their seasonal variations in the region is discussed and their decreasing influence towards the south is noted during both periods of observation. During the SWM, the dynamic topography showed the equator-ward flow of the West India Coastal Current (WICC) at the surface and a pole-ward coastal under current at sub-thermocline depth. During the SIM, surface circulation revealed the WICC flowing pole-ward north of 13°N, but equator-ward flow in the south, with a clockwise circulation around the Lakshadweep High.     

WHIPPET: A novel tool for prioritizing invasive plant populations for regional eradication

Large geographic areas can have numerous incipient invasive plant populations that necessitate eradication. However, resources are often deficient to address every infestation. Within the United States, weed lists (either state-level or smaller unit) generally guide the prioritization of eradication of each listed species uniformly across the focus region. This strategy has several limitations that can compromise overall effectiveness, which include spending limited resources on 1) low impact populations, 2) difficult to access populations, or 3) missing high impact populations of low priority species. Therefore, we developed a novel science-based, transparent, analytical ranking tool to prioritize weed populations, instead of species, for eradication and tested it on a group of noxious weeds in California. For outreach purposes, we named the tool WHIPPET (Weed Heuristics: Invasive Population Prioritization for Eradication Tool). Using the Analytic Hierarchy Process that included expert opinion, we developed three major criteria, four sub-criteria, and four sub-sub-criteria, taking into account both species and population characteristics. Subject matter experts weighted and scored these criteria to assess the relative impact, potential spread, and feasibility of eradication (major criteria) for 100 total populations of 19 species. Species-wide population scores indicated that conspecific populations do not necessarily group together in the final ranked output. Thus, priority lists based solely on species-level characteristics are less effective compared to a blended prioritization based on both species attributes and individual population and site parameters. WHIPPET should facilitate a more efficacious decision-making process allocating limited resources to target invasive plant infestations with the greatest predicted impacts to the region under consideration.     

Overlooked biodiversity loss in tropical smallholder agriculture

Smallholder agriculture is the main driver of deforestation in the western Amazon, where terrestrial biodiversity reaches its global maximum. Understanding the biodiversity value of the resulting mosaics of cultivated and secondary forest is therefore crucial for conservation planning. However, Amazonian communities are organized across multiple forest types that support distinct species assemblages, and little is known about smallholder impacts across the range of forest types that are essential for sustaining biodiversity. We addressed this issue with a large-scale field inventory of birds (point counts) and trees (transects) in primary forest and smallholder agriculture in northern Peru across 3 forest types that are key for Amazonian biodiversity. For birds smallholder agriculture supported species richness comparable to primary forest within each forest type, but biotic homogenization across forest types resulted in substantial losses of biodiversity overall. These overall losses are invisible to studies that focus solely on upland (terra firma) forest. For trees biodiversity losses in upland forests dominated the signal across all habitats combined and homogenization across habitats did not exacerbate biodiversity loss. Proximity to forest strongly predicted the persistence of forest-associated bird and tree species in the smallholder mosaic, and because intact forest is ubiquitous in our study area, our results probably represent a best-case scenario for biodiversity in Amazonian agriculture. Land-use planning inside and outside protected areas should recognize that tropical smallholder agriculture has pervasive biodiversity impacts that are not apparent in typical studies that cover a single forest type. The full range of forest types must be surveyed to accurately assess biodiversity losses, and primary forests must be protected to prevent landscape-scale biodiversity loss.     

Spatiotemporal modeling of irregularly spaced aerosol optical depth data

Many advancements have been introduced to tackle spatial and temporal structures in data. When the spatial and/or temporal domains are relatively large, assumptions must be made to account for the sheer size of the data. The large data size, coupled with realities that come with observational data, make it difficult for all of these assumptions to be met. In particular, air quality data are very sparse across geographic space and time, due to a limited air pollution monitoring network. These “missing” values make it difficult to incorporate most dimension reduction techniques developed for high-dimensional spatiotemporal data. This article examines aerosol optical depth (AOD), an indirect measure of radiative forcing, and air quality. The spatiotemporal distribution of AOD can be influenced by both natural (e.g., meteorological conditions) and anthropogenic factors (e.g., emission from industries and transport). After accounting for natural factors influencing AOD, we examine the spatiotemporal relationship in the remaining human influenced portion of AOD. The presented data cover a portion of India surrounding New Delhi from 2000–2006. The proposed method is demonstrated showing how it can handle the large spatiotemporal structure containing so much missing data for both meteorologic conditions and AOD over time and space.     

Seasonal and spatial trends in the sources of fine particle organic carbon in Israel,Jordan, and Palestine

A study of carbonaceous particulate matter (PM) was conducted in the Middle East at sites in Israel, Jordan, and Palestine. The sources and seasonal variation of organic carbon, as well as the contribution to fine aerosol (PM_2.5) mass, were determined. Of the 11 sites studied, Nablus had the highest contribution of organic carbon (OC), 29%, and elemental carbon (EC), 19%, to total PM_2.5 mass. The lowest concentrations of PM_2.5 mass, OC, and EC were measured at southern desert sites, located in Aqaba, Eilat, and Rachma. The OC contribution to PM_2.5 mass at these sites ranged between 9.4% and 16%, with mean annual PM_2.5 mass concentrations ranging from 21 to 25 ug m^?3. These sites were also observed to have the highest OC to EC ratios (4.1–5.0), indicative of smaller contributions from primary combustion sources and/or a higher contribution of secondary organic aerosol. Biomass burning and vehicular emissions were found to be important sources of carbonaceous PM in this region at the non-southern desert sites, which together accounted for 30%–55% of the fine particle organic carbon at these sites. The fraction of measured OC unapportioned to primary sources (1.4 μgC m^?3 to 4.9 μgC m^?3; 30%–74%), which has been shown to be largely from secondary organic aerosol, is relatively constant at the sites examined in this study. This suggests that secondary organic aerosol is important in the Middle East during all seasons of the year.     

Enzymatic processing of municipal solid waste

The focus of this work was to investigate an enzymatic liquefaction of MSW organics, paper and cardboard. Liquefaction trials were conducted in different trial volumes: 50 g lab-scale trials and 50 kg vessel-tests and evaluated based on particle size and viscosity. The viscosity results showed that Celluclast 1.5 L had the singular significant effect on liquefaction of model MSW. No effect of α-amylase, protease and interaction in between and with cellulases on viscosity and particle size distribution was found in this study. Degradable material with a particle size above 1 mm after treatment was evaluated using SEM microscopy. These results showed that paper particles were the main obstacles needing additional treatment in order to become fully liquefied. In a pilot scale test treating authentic MSW; more than 90% of initial organic and paper dry matter (DM) was recovered as liquid slurry after sieving through a 5-mm sieve. These tests were performed at up to 35% DM, showing that this process can easily manage high DM loadings. MSW enzymatic liquefaction promotes the separation of organics and paper from solids, which facilitate the use of these degradable fractions, with minimal loss, capable to enter a biogas plant through existing pipes.     

Pollution influences on atmospheric composition and chemistry at high northern latitudes: Boreal and California forest fire emissions

We analyze detailed atmospheric gas/aerosol composition data acquired during the 2008 NASA ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) airborne campaign performed at high northern latitudes in spring (ARCTAS-A) and summer (ARCTAS-B) and in California in summer (ARCTAS-CARB). Biomass burning influences were widespread throughout the ARCTAS campaign. MODIS data from 2000 to 2009 indicated that 2008 had the second largest fire counts over Siberia and a more normal Canadian boreal forest fire season. Near surface arctic air in spring contained strong anthropogenic signatures indicated by high sulfate. In both spring and summer most of the pollution plumes transported to the Arctic region were from Europe and Asia and were present in the mid to upper troposphere and contained a mix of forest fire and urban influences. The gas/aerosol composition of the high latitude troposphere was strongly perturbed at all altitudes in both spring and summer. The reactive nitrogen budget was balanced with PAN as the dominant component. Mean ozone concentrations in the high latitude troposphere were only minimally perturbed (<5 ppb), although many individual pollution plumes sampled in the mid to upper troposphere, and mixed with urban influences, contained elevated ozone (ΔO₃/ΔCO = 0.11 ± 0.09 v/v). Emission and optical characteristics of boreal and California wild fires were quantified and found to be broadly comparable. Greenhouse gas emission estimates derived from ARCTAS-CARB data for the South Coast Air Basin of California show good agreement with state inventories for CO₂ and N₂O but indicate substantially larger emissions of CH₄. Simulations by multiple models of transport and chemistry were found to be broadly consistent with observations with a tendency towards under prediction at high latitudes.