Results

Qian et al. (2015) find that, when collectively considering all light-absorbing particles (black carbon, brown carbon, and organic carbon over snow or ice), induced changes in snow albedo generate changes in surface-radiative flux of 5–25 watts per square meter during the spring, with a maximum in April or May. Other studies have shown smaller-magnitude forcings (1–3 watts per square meter by Ménégoz et al. 2014; 1.5 watts per square meter by Flanner et al. 2007). However, Ménégoz et al. (2014) acknowledge that the coarse global model employed is not able to resolve adequately the extreme variation in wet deposition of BC with altitude and includes periods without snow cover. Flanner et al. (2007) find much higher magnitudes (10–20 watts per square meter) when averaging only over the snow-covered region of the Himalayas, a forcing one to four times greater than that exerted by carbon dioxide (CO2) alone.

Xu, Lamarque, and Sanderson (2018) use a global model with an approximately one-degree spatial resolution and scaling factors between two and four to bottom-up emissions inventories to reflect observations better. In addition to the altitude dependence of BC deposition described earlier, Xu et al. find that preindustrial to present-day increases in BC emissions reduce the annual average snow fraction over the Tibetan plateau by more than 6 percent (relatively) and reduce snow depth by approximately 19 percent. They also find that surface albedo decreases by more than 5 percent along the Himalayan mountain range and 1.4 percent over the entire Tibet region, providing positive local feedback to the enhanced local warming.

Kopacz et al. (2011), described above, calculate instantaneous radiative forcing (with and without the presence of BC particles in snow) of +3.78 to +15.6 watts per square meter at the five sites studied, with a minimum range in winter of approximately 3–11 watts per square meter across the sites and a maximum range in summer of approximately 7–16 watts per square meter. Their study does not account for the reduction in albedo due to dust or soil in the snow.

A framework for assessing the impacts of black carbon on glaciers is necessarily complex. Given the literature reviewed in this chapter, it is clear that a robust framework for exploring the role of BC and other air pollution in influencing snow melt and the subsequent hydrology in the HKHK region must be able to account for the tremendous variation in elevation, the transport of pollution, and the surface dynamics of snow melt and reflectance. The direct radiative forcing of aerosols is critical over highly reflective snow surfaces like the Himalayas, where a small concentration of absorbing aerosols in the atmosphere can lead to significant warming. The magnitude of this direct radiative forcing strongly depends on the columnar aerosol loading (aerosol optical depth). This section outlines the methodology used in this book to develop the BC scenarios. The methodology and results are detailed in Alvarado et al. (2018).

As detailed in Alvarado et al. (2018), the BC study models the impact of BC in the HKHK under both current and future climate conditions. Specifically, it uses the Weather Research and Forecasting model coupled with the Chemistry model (WRF-Chem) to understand the impacts of regional emissions and transport on the wet and dry deposition of BC in the HKHK region at high spatial resolution under both current conditions and future climate projections for 2040–50 (Grell et al. 2005).4 The BC study evaluates results using the WRF-Chem model for the same scenarios as the Goddard Institute for Space Studies (GISS) global climate model, which provides the driving boundary conditions for WRF-Chem and includes the RCP 4.5 (standard) and RCP 4.5 (mitigation) scenarios, but uses a 12-kilometer horizontal resolution grid that covers India and the HKHK region with 35 vertical layers (map 5.2) (map 5.2 is accessible in the Nontechnical Summary, appendix A, at https://openknowledge.worldbank.org/handle/10986/35600). The scenarios also include a sensitivity analysis of the three distinct phases of the El Niño–Southern Oscillation (ENSO) cycle.

The BC study employs tagged BC tracers from several source sectors and countries to assess their relative impact on BC deposition.5 Tagged tracers for BC were added to the WRF-Chem model code following the methods used by Kumar et al. (2015); these tracers track BC aerosol emissions from five sectors (diesel fuel, industry, solid fuel, open burning, and biomass burning) and six nations (Bangladesh, China, India, Myanmar, Nepal, and Pakistan), as well as BC from the initial and boundary conditions. Then 28-day (14-day spin-up, 14-day analysis) WRF-Chem simulations were run for each season (January, winter monsoon; April, monsoon transition; July, summer monsoon; and October, monsoon transition) for both current conditions (represented using the moderate ENSO year of 2013) and three future years between 2040 and 2050—a moderate ENSO year, a La Niña year, and an El Niño year. A more detailed treatment of this methodology is provided in appendix B.

Results estimate total BC deposition in South Asia as the sum of the fluxes of wet and dry deposition of BC. Map 5.3 shows total BC deposition for the 14-day analysis period of each month simulated for 2013. As expected, these values are generally highest near high-emission regions and lower over the HKHK region. Specifically, BC deposition is higher in the western Karakoram and Hindu Kush ranges near the Pakistan-China and India-China borders, respectively, and lower over the Himalayas in the east. The seasonal cycle of deposition peaks in January over India, the Arabian Sea, and the Bay of Bengal, but the seasonal peak in deposition over the HKHK region varies, with the southern regions peaking from January to April and the northern regions peaking from July to October.

BC is sourced extensively from outside the HKHK. Map 5.4 shows the division of this BC deposition between anthropogenic sources within the modeling domain, biomass burning (wildfires) within the modeling domain, and the boundary conditions (and thus BC from all sources outside the domain). Since the analysis period begins only after a two-week spin-up has occurred, the fraction of deposition coming from the initial conditions is negligible everywhere.