Assessment of emissions of greenhouse gases and air pollutants in Indonesia and impacts of national policy for elimination of kerosene use in cooking

Assessment of biomass open burning emissions in Indonesia and potential climate forcing impact

Development of 1 ×1 km gridded emission inventory for air quality assessment and mitigation strategies from open biomass burning in Karnataka, India

The activity of exploration and production in oil and gas industry is significant greenhouse gas (GHG) emission source. PT. XYZ is one of upstream oil and gas industry in Indonesia and it have large crude oil and gas potential with it reserves that not manage yet. Therefore, GHG emission potential from the activity of exploration and production in PT. XYZ is very large. This study is done for estimate GHG emission reduction potential in PT. XYZ from various activities. Emission inventory is the first step to estimate GHG released to atmosphere. Method of estimation use the method developed by American Petroleum Institute (API). This study considers three types of mitigation measures options, including technical options (scenario 1), behavior option (scenario 2), and policy option (scenario 3). Based on emission inventory, flare and oil storage tank are primary source of GHG emissions in PT. XYZ. Scenario 1 prefers control of GHG emissions in flare and storage tank as primary emission source. While others scenario prefers to control GHG emission from transportation sector. Scenario 1 has potential to reduce emissions by 48.3 %. While scenario 2, and 3 in sequences have potential to reduce emissions by 0.15%, and 0.52%. Emissions flare and oil storage tank can be reduced through the installation of flaring gas recovery unit and vapor recovery unit. Both are effective and efficient in reducing GHG emissions in PT. XYZ. In addition, all mitigation measures of transportation sector provide benefits even though the amount of GHG that can be reduced is not significant.

Biomass open burning emissions emit large amounts of air pollutant into the atmosphere, which has significant contribution to atmospheric chemistry pollution and also climate change. Southeast Asia currently has vast areas committed to agriculture. The agricultural areas in Southeast Asia contribute a large number of emissions from biomass open burning. Biomass open burning in Southeast Asia also has a big impact such as haze problem because of vegetation slash and burn as an impact of land use change. Remote sensing is used in this research to calculate burned area and emissions of the Southeast Asia area. The aim of this research is to get emissions inventory from biomass open burning in Southeast Asia. The burning of peat land in Indonesia also emits large of emissions, therefore this case has taken as a specific topic in this research. MODIS burned area and land cover data product is used to detect burned area and also the fuel load in Southeast Asia due to emissions calculation. As a result of this research, on 2001-2007, there are several countries in Southeast Asia which play a big role in emits atmospheric chemistry. The resulting inventory map shows that Myanmar contributes almost 50% of the total burned area in Southeast Asia during January to April, mainly caused by the open burning of agricultural (savanna). Burned area in Thailand largely has happen during November and December. Approximately 80% of the total burned are was occurred in Indonesia during May to October. From this study result, spatial and temporal information, the source of emission from biomass open burning can be detected. The emission of carbon dioxide with the consideration of calculation peat soil burning is increased about 85% compared to the emission of biomass open burning without the consideration of calculation peat soil burning. The significant influence of emissions of biomass open burning to the aerosol concentration and air quality in Southeast Asia could be seen in this study. The correlation coefficient of biomass open burning emissions for CO2, CO, and CH4 is about 0.6. Further expectation, NGO activist, government or scientist can elaborate to prevent the impact of emission from biomass open burning.

Background:Residential combustion (RC) and electricity generating unit (EGU) emissions adversely impact air quality and human health by increasing ambient concentrations of fine particulate matter (PM2.5) and ozone (O3). Studies to date have not isolated contributing emissions by state of origin (source-state), which is necessary for policy makers to determine efficient strategies to decrease health impacts.Objectives:In this study, we aimed to estimate health impacts (premature mortalities) attributable to PM2.5 and O3 from RC and EGU emissions by precursor species, source sector, and source-state in the continental United States for 2005.Methods:We used the Community Multiscale Air Quality model employing the decoupled direct method to quantify changes in air quality and epidemiological evidence to determine concentration–response functions to calculate associated health impacts.Results:We estimated 21,000 premature mortalities per year from EGU emissions, driven by sulfur dioxide emissions forming PM2.5. More than half of EGU health impacts are attributable to emissions from eight states with significant coal combustion and large downwind populations. We estimate 10,000 premature mortalities per year from RC emissions, driven by primary PM2.5 emissions. States with large populations and significant residential wood combustion dominate RC health impacts. Annual mortality risk per thousand tons of precursor emissions (health damage functions) varied significantly across source-states for both source sectors and all precursor pollutants.Conclusions:Our findings reinforce the importance of pollutant-specific, location-specific, and source-specific models of health impacts in design of health-risk minimizing emissions control policies.Citation:Penn SL, Arunachalam S, Woody M, Heiger-Bernays W, Tripodis Y, Levy JI. 2017. Estimating state-specific contributions to PM2.5- and O3-related health burden from residential combustion and electricity generating unit emissions in the United States. Environ Health Perspect 125:324–332; http://dx.doi.org/10.1289/EHP550

Greenhouse gas (GHG) emission inventories, which currently inform abatement policy discussions, are developed mostly from national scale data. Nevertheless, although the policy debate tends to take place in global and national arenas, action to abate GHG emissions is inherently within the provenance of local institutions and communities. The purpose of this paper is to examine how much information is lost by not estimating GHG emissions data at scales finer than the whole US. Such information may be critical in bridging global and local policy. Differences in the composition of GHG emission sources based on GHG emission inventories at three nested spatial scales (national, state, local) for four study sites (in Kansas, North Carolina, Ohio and Pennsylvania) are analysed, drawing upon initial results of a large collaborative study known as the ‘Association of American Geographers‐Global Change in Local Places (GCLP)’ project. The concept of spatial sovereignty of emissions is developed to test the cross‐scale reliability of emission inventories. For the test year 1990, close agreement is found in the by‐gas composition of GHG emissions among national, state and local inventories. Spatial sovereignty in this case is maintained. However close agreement is not found in the by‐source composition of GHG emissions among national, state and local inventories. Spatial sovereignty in this case is not maintained. Regular compilation of state and local emissions source inventories may be necessary to track important spatial and temporal deviations from national trends.

Implementing city-level carbon accounting: A comparison between Madrid and London

Togo, in west Africa, is vulnerable to the impacts of climate change, but has made a negligible contribution to causing it. Togo ratified the Paris Agreement in 2017, committing to submit Nationally Determined Contributions (NDCs) that outline Togo's climate change mitigation commitment. Togo's capital, Lomé, as well as other areas of Togo have ambient air pollutant levels exceeding World Health Organisation guidelines for human health protection, and 91 % of Togolese households cook using solid biomass, elevating household air pollution exposure. In Togo's updated NDC, submitted in 2021, Togo acknowledges the importance and opportunity of achieving international climate change mitigation targets in ways that improve air quality and achieve health benefits for Togo's citizens. The aim of this work is to evaluate priority mitigation measures in an integrated assessment of air pollutant, Short-Lived Climate Pollutant (SLCP) and Greenhouse Gas (GHG) emissions to identify their effectiveness in simultaneously reducing air pollution and Togo's contribution to climate change. The mitigation assessment quantifies emissions for Togo and Grand Lomé from all major source sectors for historical years between 2010 and 2018, for a baseline projection to 2030 and for mitigation scenarios evaluating ten mitigation measures. The assessment estimates that Togo emitted ~21 million tonnes of GHG emissions in 2018, predominantly from the energy and Agriculture, Forestry and Other Land Use sectors. GHG emissions are projected to increase 42 % to 30 million tonnes in 2030 without implementation of mitigation policies and measures. The implementation of the ten identified priority mitigation measures could reduce GHG emissions by ~20 % in 2030 compared to the baseline, while SLCPs and air pollutants were estimated to be reduced more, with a more than 75 % reduction in black carbon emissions in 2030. This work therefore provides a clear pathway by which Togo can reduce its already small contribution to climate change while simultaneously achieving local benefits for air quality and human health in Togo and Grand Lomé.

Assessment of emissions from residential combustion in Southeast Asia and implications for climate forcing potential

Kerosene has been an important household fuel since the mid-19th century. In developed countries its use has greatly declined because of electrification. However, in developing countries, kerosene use for cooking and lighting remains widespread. This review focuses on household kerosene uses, mainly in developing countries, their associated emissions, and their hazards. Kerosene is often advocated as a cleaner alternative to solid fuels, biomass and coal, for cooking, and kerosene lamps are frequently used when electricity is unavailable. Globally, an estimated 500 million households still use fuels, particularly kerosene, for lighting. However, there are few studies, study designs and quality are varied, and results are inconsistent. Well-documented kerosene hazards are poisonings, fires, and explosions. Less investigated are exposures to and risks from kerosene's combustion products. Some kerosene-using devices emit substantial amounts of fine particulates, carbon monoxide (CO), nitric oxides (NOx), and sulfur dioxide (SO2). Studies of kerosene used for cooking or lighting provide some evidence that emissions may impair lung function and increase infectious illness (including tuberculosis), asthma, and cancer risks. However, there are few study designs, quality is varied, and results are inconsistent. Considering the widespread use in the developing world of kerosene, the scarcity of adequate epidemiologic investigations, the potential for harm, and the implications for national energy policies, researchers are strongly encouraged to consider collecting data on household kerosene uses in studies of health in developing countries. Given the potential risks of kerosene, policymakers may consider alternatives to kerosene subsidies, such as shifting support to cleaner technologies for lighting and cooking.

GHG (Greenhouse Gases) emission inventory and mitigation measures for public district heating plants in the Republic of Serbia

A differentiated urban metabolism methodology is developed to quantify inequality and inform social equity in urban infrastructure strategies aimed at mitigating local in-boundary PM2.5 and co-beneficially reducing transboundary greenhouse gas (GHG) emissions. The method differentiates community-wide local PM2.5 and transboundary GHG emission contributions by households of different income strata, alongside commercial and industrial activities. Applied in three Indian cities (Delhi, Coimbatore, and Rajkot) through development of new data sets, method yields key insights that across all three cities, top-20% highest-income households dominated motorized transportation, electricity, and construction activities, while poorest-20% homes dominated biomass and kerosene use, resulting in the top-20% households contributing more than three times GHGs as the bottom-20% homes. Further, after including commercial and industrial users, top-20% households contributed as much or more in-boundary PM2.5 emissions than all commercial OR all industrial emitters (e.g. Delhi’s top-20% homes contributed 21% of in-boundary PM2.5 similar to industries at 21%. These results enabled co-benefit analysis of various infrastructure transition strategies on the horizon, finding only three could yield both significant GHG and PM2.5 reductions (>2%-each): (a) Modest 10% efficiency improvements among top-20% households, industry and commercial sectors, requiring a focus on wealthiest homes; (b) Phasing out all biomass and kerosene use within cities (impacting poorest); (c) Replacing gas and diesel vehicles with renewable electric vehicles. The differentiated PM2.5 and GHG emissions data-informed social equity in the design of the three co-beneficial infrastructure transitions by: (a)-prioritizing free/subsidized clean cooking fuels to poorest homes; (b)-increasing electricity block rates and behavioral nudging for wealthiest homes; and, (c)-prioritizing electrification of mass transit and promoting electric two-wheelers ahead of providing subsidies for electric cars, where the free-rider phenomenon can occur, which benefits wealthiest homes. The methodology is broadly translatable to cities worldwide, while the policy insights are relevant to rapidly urbanizing Asia and Africa to advance clean, low-carbon urban infrastructure transitions.

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Open biomass burning (OBB) is a significant source of air pollutants and greenhouse gases that have contributed to air pollution episodes in China in recent years. An accurate emission inventory is critical for the precise control of OBB. Existing OBB emission datasets are commonly based on MODIS observations, and most only have a daily-scale temporal resolution. Daily OBB emissions, however, might not accurately represent diurnal variations, peak hours, or any open burning processes. The China Hourly Open Biomass Burning Emissions (CHOBE) dataset for mainland China from 2016 to 2020 was developed in this study using the spatiotemporal fusion of multiple active fires from MODIS, VIIRS S-NPP and Himawari-8 AHI detections. At a spatial resolution of 2 km, CHOBE provided gridded CO, NOx, SO2, NH3, VOCs, PM2.5, CO2, CH4 and N2O emissions from OBB. CHOBE will enhance insight into OBB spatiotemporal variability, improves air quality and climate modelling and forecasting, and aids in the formulation of precise OBB preventive and control measures.

Problem: Basing local climate action plans on greenhouse gas (GHG) emissions inventories has become standard practice for communities that want to address the problem of climate change. Communities use GHG emissions inventories to develop policy despite the fact that there has been little theoretical work on the implications of the assumptions embedded within them. Purpose: We identify elements and assumptions in emissions inventories that have important policy implications for climate action plan formulation, aiming to help planners make informed, defensible choices, and to refine future GHG emissions inventory protocols and climate action planning methods. Methods: We conducted a content analysis of 30 city climate action plans selected as a stratified random sample. We collected data on 70 different factors and used summary and trend statements, typologies, and descriptive statistics to link our findings to our research questions. Results and conclusions: Climate action plans obviously vary in many details, but most contain all of the core GHG emissions elements suggested in common protocols. We found GHG emissions inventories to be technically accurate but found their reduction targets to fall short of international targets. We also found exogenous change and uncertainty to be unaccounted for in emissions forecasts and reduction targets. The plans generally do a poor job of linking mitigation actions to reduction targets. Takeaway for practice: GHG emissions inventories supporting climate action planning are reasonably standardized, but documentation of data and assumptions should be improved and GHG reduction targets should be justified. The effect of future changes that are beyond the direct control of the community plan should be accounted for in GHG emissions forecasts and reduction targets. Rapid anticipated population growth should be acknowledged and taken into account, both in GHG emissions forecasts and in setting reduction targets. Effects of mitigation may be difficult to predict reliably, yet can be partly offset by effective monitoring that evaluates progress and changes course when necessary. Research support: None.