Vegetation-fire feedback reduces projected area burned under climate change

Climate influences vegetation directly and through climate-mediated disturbance processes, such as wildfire. Temperature and area burned are positively associated, conditional on availability of vegetation to burn. Fire is a self-limiting process that is influenced by productivity. Yet, many fire projections assume sufficient vegetation to support fire, with substantial implications for carbon (C) dynamics and emissions. We simulated forest dynamics under projected climate and wildfire for the Sierra Nevada, accounting for climate effects on fuel flammability (static) and climate and prior fire effects on fuel availability and flammability (dynamic). We show that compared to climate effects on flammability alone, accounting for the interaction of prior fires and climate on fuel availability and flammability moderates the projected increase in area burned by 14.3%. This reduces predicted increases in area-weighted median cumulative emissions by 38.3 Tg carbon dioxide (CO2) and 0.6 Tg particulate matter (PM1), or 12.9% and 11.5%, respectively. Our results demonstrate that after correcting for potential over-estimates of the effects of climate-driven increases in area burned, California is likely to continue facing significant wildfire and air quality challenges with on-going climate change.</p

Wildfire burn severity and emissions inventory: an example implementation over California

Wildfire severity is a key indicator of both direct ecosystem impacts and indirect emissions impacts that affect air quality, climate, and public health far beyond the spatial footprint of the flames. Comprehensive, accurate inventories of severity and emissions are essential for assessing these impacts and setting appropriate fire management and health care preparedness strategies, as is the ability to project emissions for future wildfires. The frequency of large wildfires and the magnitude of their impacts have increased in recent decades, fueling concerns about decreased air quality. To improve the availability of accurate fire severity and emissions estimates, we developed the wildfire burn severity and emissions inventory (WBSE). WBSE is a retrospective spatial burn severity and emissions inventory at 30 m resolution for event-based assessment and 500 m resolution for daily emissions calculation. We applied the WBSE framework to calculate burn severity and emissions for historically observed large wildfires (&gt;404 hectares (ha)) that burned during 1984&ndash;2020 in the state of California, U.S., a substantially more extended period than existing inventories. We assigned the day of burning and daily emissions for each fire during 2002&ndash;2020. The framework described here can also be applied to estimate severity for smaller wildfires and can also be used to estimate emissions for fires simulated in California for future climate and land-use scenarios. The WBSE framework implemented in R and Google Earth Engine can provide quick estimates once a desired fire perimeter is available. The framework developed here could also easily be applied to other regions with user-modified vegetation, fuel data, and emission factors. &nbsp;</p

Greenhouse gas and air pollutant emissions from power barges (powerships)

Power barges or powerships that operate on natural gas (NG) are an increasingly appealing easy-to-use solution to electricity deficits in Africa, Asia, the Middle East, and the Caribbean. Global generating capacity has increased from 0.1 to 2.6 GW, and 4.4 GW is under construction. South Africa has licensed three powerships to provide 1.2 GW generating capacity with foreign liquefied NG (LNG) over 20 years. To understand the importance of this source, we estimate lifecycle emissions of GHGs and air pollutants for South Africa and extend this to the global fleet. Annual lifecycle GHG emissions for 1.2 GW generating capacity total 2.6–3.8 Tg carbon dioxide equivalents (CO2e) using 100 year global warming potentials (GWPs). This increases to 4.0–7.1 Tg CO_{2} e using 20 year GWPs, due to the potency of fugitive methane (CH4). Adoption of air pollutant emission control technology will need to be enforced to achieve compliance with national standards for fine particles (PM) and nitrogen oxides (NO_{x}). A global fleet of 7.0 GW generating capacity reliant on domestic NG could emit 12 Tg CO_{2}, 2.2–8.6 Tg CH_{4}, 4.3 Gg NO_{x}, and 2.6 Gg PM. Additional NOx and SO2 emissions would result from imported LNG, as LNG tankers burn dirty fuel oil, though SO_{2} emissions may be curtailed with recent stricter limits on the fuel sulfur content. These powerships could have important regional impacts, but emission estimates are uncertain. Characteristic emission factors, detailed operating conditions, and NG composition data are urgently needed to address uncertainties in emissions for air quality and climate modelling of this emergent source

Burning of Traditional Biofuels and the Global Methane Budget

Understanding biomass burning is important for understanding atmospheric carbon budgets. The two main types of biomass burning are wildfires, and the burning of traditional biofuels. Both types of biomass burning produce methane, among other gases. Satellites in space help quantify area burned from wildfires. However, it is much more difficult to quantify the burning of traditional biofuels, such as animal waste, fuelwood, charcoal, crop material, and peat. Therefore, limited information is available regarding these process, and how they contribute to human caused climate change. Here, we have developed a global inventory of methane emissions from the burning of traditional biofuels over a 15 year time span. Using information from the UN Energy Statistics Database, a global upper estimate of annual methane emissions from this type of biomass burning was calculated for the years 2001-2015. The equation had three components: the final energy consumption of each of the considered sources, in each country, for each year; the relative smoldering or flaming of that material when burned; and the emission factor for methane gas specific to each material. Results show it is evident that on a global scale, methane emissions from the burning of traditional biofuels are increasing over this time span. In fact, the upper estimate calculated suggests a 17.5% increase in global methane emissions from 2001-2015 from this type of biomass burning. Charcoal production and consumption are leading these increases, specifically in tropical regions. By 2015, the estimate suggests 17.5 Tg of methane is being emitted from the burning of traditional biofuels. Thus, methane emissions from burning traditional biofuels are not negligible when evaluating the global methane budget. This information is crucial when assessing methane emissions from other sources such as microbial sources and fossil fuels

Aerosol microphysical impact on summertime convective precipitation in the Rocky Mountain region

We present an aerosol-cloud-precipitation modeling study of convective clouds using the Weather Research and Forecasting model fully coupled with Chemistry (WRF-Chem) version 3.1.1. Comparison of the model output with measurements from a research site in the Rocky Mountains in Colorado revealed that the fraction of organics in the model is underpredicted. This is most likely due to missing processes in the aerosol module in the model version used, such as new particle formation and growth of secondary organic aerosols. When boundary conditions and domain-wide initial conditions of aerosol loading are changed in the model (factors of 0.1, 0.2, and 10 of initial aerosol mass of SO4-2, NH4+, and NO3-), the domain-wide precipitation changes by about 5%. Analysis of the model results reveals that the Rocky Mountain region and Front Range environment is not conducive for convective invigoration to play a major role, in increasing precipitation, as seen in some other studies. When localized organic aerosol emission are increased to mimic new particle formation, the resulting increased aerosol loading leads to increases in domain-wide precipitation, opposite to what is seen in the model simulations with changed boundary and initial conditions

A fuel-based method for updating mobile source emissions during the COVID-19 pandemic

The COVID-19 pandemic and ensuing lockdown of many US States resulted in rapid changes to motor vehicle traffic and their associated emissions. This presents a challenge for air quality modelling and forecasting during this period, in that transportation emission inventories need to be updated in near real-time. Here, we update the previously developed fuel-based inventory of vehicle emissions (FIVE) to account for changes due to COVID-19 lockdowns. We first construct a 2020 business-as-usual (BAU) case inventory and adjust the emissions for a COVID-19 case using monthly fuel sales information. We evaluate cellular phone-based mobility data products (Google COVID-19 Community Mobility, Apple COVID-19 Mobility Trends) in comparison to embedded traffic monitoring sites in four US cities. We find that mobility datasets tend to overestimate traffic reductions in April 2020 (i.e. lockdown period), while fuel sales adjustments are more similar to changes observed by traffic monitors; for example, mobility-based methods for scaling emissions result in an approximately two-times greater estimate of on-road nitrogen oxide (NOx) reductions in April 2020 than we find using a fuel-based method. Overall, FIVE estimates a 20%&ndash;25% reduction in mobile source NOx emissions in April 2020 versus BAU, and a smaller 6%&ndash;7% drop by July. Reductions in April showed considerable spatial heterogeneity, ranging from 6% to 39% at the state level. Similar decreases are found for carbon monoxide (CO) and volatile organic compounds. Decreases to mobile source NOx emissions are expected to lower total US anthropogenic emissions by 9%&ndash;12% and 3%&ndash;4% in April and July, respectively, with larger relative impacts in urban areas. Changes to diurnal and day-of-week patterns of light- and heavy-duty vehicular traffic are evaluated and found to be relatively minor. Beyond the applicability to modelling air quality in 2020, this work also represents a methodology for quickly updating US transportation inventories and for calibrating mobility-based estimates of emissions. </div

Sensitivity of Mesoscale Modeling of Smoke Direct Radiative Effect to the Emission Inventory: a Case Study in Northern Sub-Saharan African Region

An ensemble approach is used to examine the sensitivity of smoke loading and smoke direct radiative effect in the atmosphere to uncertainties in smoke emission estimates. Seven different fire emission inventories are applied independently to WRF-Chem model (v3.5) with the same model configuration (excluding dust and other emission sources) over the northern sub-Saharan African (NSSA) biomass-burning region. Results for November and February 2010 are analyzed, respectively representing the start and end of the biomass burning season in the study region. For February 2010, estimates of total smoke emission vary by a factor of 12, but only differences by factors of 7 or less are found in the simulated regional (15degW-42degE, 13degS-17degN) and monthly averages of column PM(sub 2.5) loading, surface PM(sub 2.5) concentration, aerosol optical depth (AOD), smoke radiative forcing at the top-of-atmosphere and at the surface, and air temperature at 2 m and at 700 hPa. The smaller differences in these simulated variables may reflect the atmospheric diffusion and deposition effects to dampen the large difference in smoke emissions that are highly concentrated in areas much smaller than the regional domain of the study. Indeed, at the local scale, large differences (up to a factor of 33) persist in simulated smoke-related variables and radiative effects including semi-direct effect. Similar results are also found for November 2010, despite differences in meteorology and fire activity. Hence, biomass burning emission uncertainties have a large influence on the reliability of model simulations of atmospheric aerosol loading, transport, and radiative impacts, and this influence is largest at local and hourly-to-daily scales. Accurate quantification of smoke effects on regional climate and air quality requires further reduction of emission uncertainties, particularly for regions of high fire concentrations such as NSSA

Sensitivity of Mesoscale Modeling of Smoke Direct Radiative Effect to the Emission Inventory: A Case Study in Northern Sub-Saharan African Region

An ensemble approach is used to examine the sensitivity of smoke loading and smoke direct radiative effect in the atmosphere to uncertainties in smoke emission estimates. Seven different fire emission inventories are applied independently to WRF-Chem model (v3.5) with the same model configuration (excluding dust and other emission sources) over the northern sub-Saharan African (NSSA) biomass-burning region. Results for November and February 2010 are analyzed, respectively representing the start and end of the biomass burning season in the study region. For February 2010, estimates of total smoke emission vary by a factor of 12, but only differences by factors of 7 or less are found in the simulated regional (15°W–42°E, 13°S–17°N) and monthly averages of column PM2.5 loading, surface PM2.5 concentration, aerosol optical depth (AOD), smoke radiative forcing at the top-of-atmosphere and at the surface, and air temperature at 2 m and at 700 hPa. The smaller differences in these simulated variables may reflect the atmospheric diffusion and deposition effects to dampen the large difference in smoke emissions that are highly concentrated in areas much smaller than the regional domain of the study. Indeed, at the local scale, large differences (up to a factor of 33) persist in simulated smoke-related variables and radiative effects including semi-direct effect. Similar results are also found for November 2010, despite differences in meteorology and fire activity. Hence, biomass burning emission uncertainties have a large influence on the reliability of model simulations of atmospheric aerosol loading, transport, and radiative impacts, and this influence is largest at local and hourly-to-daily scales. Accurate quantification of smoke effects on regional climate and air quality requires further reduction of emission uncertainties, particularly for regions of high fire concentrations such as NSSA

Rural-urban differences in cooking practices and exposures in Northern Ghana

Key differences between urban and rural populations can influence the adoption and impacts of new cooking technologies and fuels. We examine these differences among urban and rural households that are part of the REACCTING study in Northern Ghana. While urban and rural populations in the study area all use multiple stoves, the types of stoves and fuels differ, with urban participants more likely to use charcoal and LPG while rural households rely primarily on wood. Further, rural and urban households tend to use different stoves/fuels to cook the same dishes—for example, the staple porridge Tuo Zaafi (TZ) is primarily cooked over wood fires in rural areas and charcoal stoves in urban settings. This suggests that fuel availability and ability to purchase fuel may be a stronger predictor of fuel choice than cultural preferences alone. Ambient concentrations of air pollutants also differ in these two types of areas, with urban areas having pollutant hot spots to which residents can be exposed and rural areas having more homogeneous and lower pollutant concentrations. Further, exposures to carbon monoxide and particulate matter differ in magnitude and in timing between urban and rural study participants, suggesting different behaviors and sources of exposures. The results from this analysis highlight important disparities between urban and rural populations of a single region and imply that such a characterization is needed to successfully implement and assess the impacts of household energy interventions

Exposures to Carbon Monoxide in a Cookstove Intervention in Northern Ghana

Biomass burning for home energy use is a major environmental health concern. Improved cooking technologies could generate environmental health benefits, yet prior results regarding reduced personal exposure to air pollution are mixed. In this study, two improved stove types were distributed over four study groups in Northern Ghana. Participants wore real-time carbon monoxide (CO) monitors to measure the effect of the intervention on personal exposures. Relative to the control group (those using traditional stoves), there was a 30.3% reduction in CO exposures in the group given two Philips forced draft stoves (p = 0.08), 10.5% reduction in the group given two Gyapa stoves (locally made rocket stoves) (p = 0.62), and 10.2% reduction in the group given one of each (p = 0.61). Overall, CO exposure for participants was low given the prevalence of cooking over traditional three-stone fires, with 8.2% of daily samples exceeding WHO Tier-1 standards. We present quantification methods and performance of duplicate monitors. We analyzed the relationship between personal carbonaceous particulate matter less than 2.5 microns (PM2.5) and CO exposure for the dataset that included both measurements, finding a weak relationship likely due to the diversity of identified air pollution sources in the region and behavior variability.</p