Design of an energy vulnerability index - spatial and temporal analysis: case of study Colombia.

Climate change might affect energy production and therefore the energy security of a country or region. This situation may impact renewable energy sources such as hydro power, leading to consequences on energy transition strategies. This might be critical in sensitive regions to climate change, one of them being the Caribe and northern South America. Since there are numerous energy systems based on sensitive technologies worldwide, it is necessary to introduce techniques to analyze the effects of climate change on different possible energy transition paths. The goal of this study is to develop and assess a method to analyze one of the most critical effects faced by climate change for societies worldwide: the sensitivity of the energy systems to climate change. This is especially critical in developing countries, in locations where temperatures will strongly increase in the following years. To assess this effect, this study proposes a vulnerability index (VI) to evaluate the vulnerability of an on-grid electricity system to climate change at the national and regional scales. This index was assessed using a Monte-Carlo method for uncertainty. The case of Colombia, a country with a system based on hydropower (> 70%) is used to illustrate the method. VI is based on variables related to climate change, the energy matrix, and vulnerability. Results show that the regions with the larger vulnerability correspond to the more energy-demanding ones. The VI for these regions is greater than 50% of the maximum possible vulnerability; meanwhile, the vulnerability of the whole country was estimated as 43%.

Spatio-temporal analysis of PM2.5 and policies in Northwestern South America.

This paper analyzes the spatio-temporal variations, and exceedances of the PM2.5 concentrations in Northwestern South America at different scales to assess the implemented policies and identify the involved phenomena. Through reanalysis and ground-based data, we found that high PM2.5 levels in most cities of the region are caused by wildfires and local emissions, including the capital cities of Venezuela, Ecuador, Colombia, and Panamá. In-situ measurements suggest that the majority of the cities comply with the local but not with the WHO guidelines, indicating that local annual limits should be more restrictive. Two peaks in the daily variations of PM2.5 (related to vehicle emissions) and also a steeper decrease around noon (associated with an increase in wind speed and in the boundary layer height) were identified. The trend-analysis shows that Bogotá and Medellín have a decreasing PM2.5 annual-trend (between -0.8µgm-3 and -1.7µgm-3) that corresponds to effective policies. In contrast, Cali has a positive annual-trend (0.8µgm-3) most likely because of Short-Range Transport produced by a northerly-flow from a highly polluted neighboring city, which also affects Cali's PM2.5 diurnal cycle, or by local-dynamics. The exceedances show that the policies are working on an annual but not at a daily time-scale. These results serve as a first input for additional studies, with the aim of gaining a better understanding of the contaminant before adapting current policies or implementing new policies and measures that need to include a joint international, regional, and inter-city efforts regarding pollution transport.

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions.

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015-2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O3 and the total gaseous oxidant (OX = NO2 + O3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015-2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples' mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared to the same period in 2015-2019. However, PM2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO2/CO ratio). Some Chinese cities showed similar increases in PM2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O3 concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO2 anomalies were negative for 2020 compared to 2015-2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO2/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO2 decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO2 + O3) showed that primary NO2 emissions at urban locations were greater than the O3 production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO2 and O3 concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.

Effects of fuel change to electricity on PM2.5 local levels in the Bus Rapid Transit System of Bogota.

The TransMilenio (TM) is a transport system. Twenty-year-old TM is a fast, highly efficient, and self-sufficient mode of passenger transport. This work aims to evaluate the effects of changing current TM diesel buses by electricity-powered buses (battery, wire-based), on the PM2.5 concentrations at surface level. Emissions calculations considering combustions and resuspension of TM and Non-TM were performed. A CFD model was implemented to estimate current PM2.5 concentrations at the roadside level, and the CFD results were validated using the statistic parameters: MB, RMSE, r, and IOA. Results from the emission calculations indicate that TM buses (30-50%) are one of the main sources of primary PM2.5 in all the considered urban sites in this study. Non-exhaust emissions from most vehicle categories were also identified as an important source of primary PM2.5 (40% of total emissions). The CFD model reproduced closely the trends and levels of PM2.5 concentrations measured at the roadside level in all the locations. Replacing TM diesel vehicles with electric vehicles reduces PM2.5 concentrations between 10 and 30% according to the CFD results obtained. Higher reductions can be achieved if policies are adopted to control other types of vehicles and non-exhaust emissions since they have a contribution of about 60%. Finally, this study shows that the combined use of emission calculations and advanced near-road dispersion models are useful tools to study and manage air quality in large cities.

Implementation and evaluation of WRF simulation over a city with complex terrain using Alos-Palsar 0.4 s topography.

Air quality modeling requires an accurate representation of meteorology, and in cities with complex topography, the performance of meteorological modeling can be improved by using an alternative global digital elevation model (GDEM) such as Alos-Palsar 0.4 s instead of the default elevation data. Bogotá is a city with complex topography geographically located over the Andes Mountains at 2600 m.a.s.l. A reliable meteorological simulation model is critical for performing a suitable air quality modeling in any case of study. Previous researches have been developed using the standard Weather Research and Forecast (WRF) topography (GTOPO 30 s). These studies have been developed with different configurations for the representation of meteorology. The aim of this study is to evaluate Alos-Palsar 0.4 s topography with WRF, and two domain configurations with horizontal spatial resolutions up to 1000 m, to establish a reliable and accurate way to simulate the meteorology in the city of Bogotá. The evaluation quantitative parameters: IOA, r (Pearson), RMSE, MGE, and MB were calculated for the quantitative evaluation of temperature, relative humidity, wind speed, wind direction, and solar radiation. An additional evaluation using Taylor diagrams was performed. Spatial differences were identified in the same locations as well the differences between the elevation from Alos-Palsar 0.4 s and GTOPO30. The results and evaluation suggest that simulations based on Alos-Palsar 0.4 s topography lead to a significant improvement in the meteorology representation by WRF in a region with complex topography such as Bogotá, Colombia.