Mitigation potential of global ammonia emissions and related health impacts in the trade network

Ammonia (NH3) emissions, mainly from agricultural sources, generate substantial health damage due to the adverse effects on air quality. NH3 emission reduction strategies are still far from being effective. In particular, a growing trade network in this era of globalization offers untapped emission mitigation potential that has been overlooked. Here we show that about one-fourth of global agricultural NH3 emissions in 2012 are trade-related. Globally they induce 61 thousand PM2.5-related premature mortalities, with 25 thousand deaths associated with crop cultivation and 36 thousand deaths with livestock production. The trade-related health damage network is regionally integrated and can be characterized by three trading communities. Thus, effective cooperation within trade-dependent communities will achieve considerable NH3 emission reductions allowed by technological advancements and trade structure adjustments. Identification of regional communities from network analysis offers a new perspective on addressing NH3 emissions and is also applicable to agricultural greenhouse gas emissions mitigation.

Greenhouse Gas Emission Intensity Assessment for Power Plants in Peninsular Malaysia

The power sector has been playing a vital role in the industrialization, societal and economic development of a nation. In Malaysia, the total power generation for 2014 is 147,480GWh and eventually accounts for 54% of total carbon emissions for that year alone. A study was conducted to quantify the greenhouse gas emission from stationary combustion from several power plants in Peninsular Malaysia, followed by proposal for the emission reduction strategies. For the GHG emissions assessment, the Greenhouse Gas Protocol: A Corporate Accounting and Reporting Standard and Intergovernmental Panel on Climate Change (IPCC) methodologies was adopted. Based on this study, the highest GHG emission intensity were from coal power plants which ranged from 0.67 – 0.85 tCO2/ MWh. The GHG emission intensity for natural gas power plants ranged from 0.38 – 0.78 tCO2/ MWh. The overall GHG emission intensity for all power plants studied was estimated to be 0.54 tCO2/ MWh. The large variations in CO2 emissions per MWh of electricity generated in fossil fuel power plants were due to differences in generation efficiency, fuel selection, technology, and plant age. In supporting Malaysia’s conditional commitment of 45% GHG emissions intensity reduction target against the country’s GDP, the emission reduction strategies up to 2025 were assessed using three key scenarios namely Business-As-Usual (BAU), Planning (PLAN) and Ambitious (AMB). Based on the analysis, the projection indicates that the emissions intensity for the power sector is about 0.79 tCO2/ MWh, 0.49 tCO2/ MWh, and 0.44 tCO2/ MWh under the BAU, PLN AMB scenarios respectively. Finally, GHG emission reduction potentials were also outlined in this paper.

Research on the Pollutant Emission Reduction Strategy and Simulation of Paper-Making Enterprises under the Reward and Punishment Mechanism

Environmental pollution has become an important obstacle on the path of ecological civilization construction, and it is urgent to control environmental pollution. By establishing an evolutionary game model, this thesis focuses on analyzing how paper-making enterprises choose their own emission reduction strategies under the reward and punishment mechanism. It further analyzes how social welfare changes under the reward and punishment mechanism, and finally through simulation research, this thesis analyzes the evolutionary paths of paper-making enterprises’ pollution emission strategies under the reward and punishment mechanism. The results of the reward and punishment mechanism are as follows: under the static reward and punishment mechanism, the game system will repeatedly oscillate around a point. There is no stable equilibrium point at this time. However, under the dynamic reward and punishment mechanism, the game system will tend to a stable equilibrium point. The results of social welfare analysis show that high-intensity rewards will reduce the amount of pollution discharged by paper-making enterprises, thereby maximizing social welfare. On the contrary, when paper-making enterprises discharge a large amount of pollution, they will be subject to high-intensity penalties. When facing high-intensity punishments, paper-making enterprises will tend to not to discharge. So social welfare is also maximized. The simulation research results show that reasonable punishment strategies are more effective than reward ones. Based on this, the author proposes countermeasures, such as establishing a reasonable reward and punishment mechanism, reasonably determining the reward and punishment intensity for polluting enterprises. The emission reduction strategies of paper-making enterprises will be affected by the government’s reward and punishment mechanism. A deep study of its internal mechanism is not only of great significance for pollution control but also of great significance for the development of a green economy.

Methods for quantifying methane emissions using unmanned aerial vehicles: a review

Methane is an important greenhouse gas, emissions of which have vital consequences for global climate change. Understanding and quantifying the sources (and sinks) of atmospheric methane is integral for climate change mitigation and emission reduction strategies, such as those outlined in the 2015 UN Paris Agreement on Climate Change. There are ongoing international efforts to constrain the global methane budget, using a wide variety of measurement platforms across a range of spatial and temporal scales. The advancements in unmanned aerial vehicle (UAV) technology over the past decade have opened up a new avenue for methane emission quantification. UAVs can be uniquely equipped to monitor natural and anthropogenic emissions at local scales, displaying clear advantages in versatility and manoeuvrability relative to other platforms. Their use is not without challenge, however: further miniaturization of high-performance methane instrumentation is needed to fully use the benefits UAVs afford. Developments in the models used to simulate atmospheric transport and dispersion across small, local scales are also crucial to improved flux accuracy and precision. This paper aims to provide an overview of currently available UAV-based technologies and sampling methodologies which can be used to quantify methane emission fluxes at local scales. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'.

Study on Emission Reduction Strategies of Dual-Channel Supply Chain Considering Green Finance

As a weapon for economic development, green finance plays an important supporting and promoting role in the economic recovery and transformation of enterprises in the post-epidemic era. By constructing a dual-channel supply chain model, this paper considers two situations in which manufacturers participate in carbon trading and green finance loans, and uses Stackelberg game to study the impact of different situations on participants’ profits and emission reduction decisions. The results show that: under the carbon trading mechanism, the carbon emission reduction level of the manufacturer is inversely proportional to the relevant price, and the demand and profit of the two channels increase with the increase in emission reduction; when carbon trading and green financial loans are carried out at the same time, participants have lower profits, but with the increase in emission reductions, it is still a growing trend.

A comparison of bottom-up methods for estimating institutional building energy use to inform resource and emission reduction strategies

Bottom-up engineering models are an emerging approach for evaluating energy efficiency solutions at district or regional scales. More flexible than statistical models, bottom-up models allow planners to quantitatively evaluate energy efficiency and supply options, leading to more effective policies and energy demand solutions that better reflect our changing climate. This thesis compares two bottom-up methods for exploring resource and emission reduction strategies in the institutional sector: the Wireframe method and the Reference method. These methods are compared by predicting the annual consumption of post-secondary student residences in Southern Ontario and measuring the error of each, compared with the 2013 mandatory energy report data from the Ministry of Energy of Ontario. Both methods produced aggregate energy error ranges of 5% to 12% in a detailed analysis, suggesting that they are both effective for large-scale energy reduction studies.

A comparison of bottom-up methods for estimating institutional building energy use to inform resource and emission reduction strategies

Bottom-up engineering models are an emerging approach for evaluating energy efficiency solutions at district or regional scales. More flexible than statistical models, bottom-up models allow planners to quantitatively evaluate energy efficiency and supply options, leading to more effective policies and energy demand solutions that better reflect our changing climate. This thesis compares two bottom-up methods for exploring resource and emission reduction strategies in the institutional sector: the Wireframe method and the Reference method. These methods are compared by predicting the annual consumption of post-secondary student residences in Southern Ontario and measuring the error of each, compared with the 2013 mandatory energy report data from the Ministry of Energy of Ontario. Both methods produced aggregate energy error ranges of 5% to 12% in a detailed analysis, suggesting that they are both effective for large-scale energy reduction studies.