flypig.co.uk

The 6th January is traditionally the day Christmas decorations are dismantled in the UK. In Finland it's the 13th January, partly because the Christmas lights are needed to counteract the shorter daylight hours and partly to avoid angering the Yulegoat. But I'm in the UK so this weekend Joanna and I took down our Christmas decorations.

In previous years we've always tried to get a Christmas tree with roots. Our success rate in keeping it alive until the next Christmas currently stands at zero percent.

This year I went out of my way to care for our Christmas tree, carefully keeping the soil in its pot moist with daily watering, avoiding bumps and bashes, not overburdening the branches with crazy decorative figurines.

It's definitely fared better than any of our previous trees and today I dug a hole in the back garden and planted it solidly.

Here are the three stages of its life I've so far been involved with, from left-to-right: sitting in our living room right after we introduced it; with decorations ready for Christmas; and now transplanted to our back garden.
 

I'm no gardener and I don't rate its chances highly, but I'd love it to survive. Not only would it be wonderful to have a Norwegian Spruce living in our garden, but it would also feel like a real achievement to have a multi-year Christmas tree. I'm also counting this as one of the ecological acts needed to fulfil my New Year's Resolutions.

I'll report back later in the year on how the tree is doing. It feels like its success is now very much down to weather, nature and its will to survive. Maybe that's not the right way to look at these things, but that's why I'm not a gardener.

For the last four years I've been offsetting my carbon emissions. In the long run I accept that offsetting isn't a sustainable way to address the climate crisis, but until my CO₂ output reaches zero I still think it's better to offset than to not. Apart from attempting to address the balance of my impact on the world it also offers two other benefits.

First there's the personal financial cost I incur from having to pony up a hundred quid or thereabouts each year. That's a good way to incentivize myself to reduce my carbon footprint in the future. Second there's the active process of interrogating my consumption: working through the calculations is a great way to focus the mind, confront the consequences of my personal decisions and think about what I could improve on in the future.

Last year it took until April for me to run the calculations and act on them. This year I've done much better. That's partly driven by my New Year's Resolution to make at least one ecological improvement per month during the year. Even though this isn't a new thing for me, when I made the resolution the intention was always to count this as one of the tasks. And so it is.

Here's the table that shows which carbon emissions came from which activities. I've included all previous years so that some trends can be captured. I should emphasise that this represents household emissions, so covers two people, both Joanna and me. For comparison average emissions for individuals in the UK is 5.40 tonnes (10.80 tonnes for two people).
 

Source	CO2, 2019 (t)	CO2, 2020 (t)	CO2, 2021 (t)	CO2, 2022 (t)	CO2, 2023 (t)
Electricity	0.50	0.40	0.59	1.14	1.66
Natural gas	1.18	1.26	1.66	0.81	-0.25
Flights	5.76	2.26	1.90	5.34	1.32
Car	1.45	0.39	0.39	1.01	1.00
Bus	0.00	0.01	0.02	0.01	0.31
National rail	0.08	0.01	0.02	0.00	0.70
International rail	0.02	0.01	0.00	0.04	0.01
Taxi	0.01	0.01	0.01	0.01	0.01
Food and drink	1.69	1.11	1.05	1.35	1.07
Pharmaceuticals	0.26	0.32	0.31	0.06	0.13
Clothing	0.03	0.06	0.06	0.12	0.23
Paper-based products	0.34	0.15	0.14	0.37	0.38
Computer usage	1.30	1.48	0.75	0.93	0.23
Electrical	0.12	0.29	0.19	0.03	0.01
Non-fuel car	0.00	0.10	0.00	0.12	0.92
Manufactured goods	0.50	0.03	0.03	0.05	0.11
Hotels, restaurants	0.51	0.16	0.15	0.10	1.21
Telecoms	0.15	0.05	0.04	0.03	0.05
Finance	0.24	0.24	0.22	0.04	0.02
Insurance	0.19	0.11	0.10	0.04	0.04
Education	0.05	0.00	0.04	0.01	0.00
Recreation	0.09	0.06	0.05	0.03	0.06
Total	14.47	8.50	7.73	11.65	9.25

The headline result is that our total carbon emissions have been reduced compared to last year. That's mostly driven by a large decrease in the number of flights, from twenty in 2022 to just four last year. Twenty flights is a large number, a consequence of living in Finland. This year I moved back to the UK in February. That meant some flights to tidy up my life in Finland, but I've not flown again since then. In 2024 I'm hoping to push that down to zero flights.

Reduced flights was partly offset by increased train and bus travel, largely due to my weekly commute between Cambridge and London for work. I took the journey 88 times, giving me a massive total distance travelled of 19 638 km by national rail. Thankfully trains are also far more carbon efficient than planes, so while distance travelled only reduced by a factor of 1.5, carbon emissions reduced by a factor of 5.75.

One potentially confusing thing about the numbers is that natural gas usage is a negative figure. We switched from a gas boiler to a heat pump, with the result that our gas usage tumbled. But of course it wasn't negative! The negative value is due to our power company overestimating our gas usage as a result of our heating change. The overestimate was included in the figures for last year and this negative figure redresses that.

The following table gives more detail about the numbers used to perform the calculations. After pulling these together I then fed them into Carbon Footprint Ltd's carbon calculator as I have in previous years to generate the results.
 

Source	2019	2020	2021	2022	2023
Electricity	1 794 kWh	1 427 kWh	3 009 kWh	4 101 kWh	5 975 kWh
Natural gas	6 433 kWh	6 869 kWh	9 089 kWh	4 439 kWh	-1 362 kWh
Flights	36 580 km 20 flights	14 632 km 8 flights	25 542 km 14 flights	36 042 km 20 flights	7 233 km 4 flights
Car	11 910 km	2 000 km	3 219 km	8 458 km	8 369 km
Bus	1 930 km	40 km	168 km	133 km	3 080 km
National rail	5 630 km	400 km	676 km	0 km	19 638 km
International rail	64 km	1 368 km	513 km	8 684 km	2 322 km
Taxi	64 km	37 km	100 km	100 km	100 km
Tube	0 km	0 km	0 km	0 km	100 km

As in previous years I've used the UN Framework Convention on Climate Change to offset my carbon output. The money will go to pay for improved cooking stoves in Malawi, a scheme managed by Ripple Africa.
 
 

After months of procrastination, I've finally completed the analysis of my consumption and waste data. The post is on my blog.

Last year was my last spent living in Finland, during which time I weighed all of my rubbish, split into categories. But last year I also collected data not just on my outputs, but also on my inputs too. All of my household purchases I recorded and stored in a big CSV file. I managed to collect a full 12 months' worth of waste and consumption data, in the hope that I could analyse them, compare them, and maybe extract something useful from them. Something about the cycles in my life, or how to make myself less damaging to the environment.

It's now Sunday 4th June, nearly six months after I moved from Finland to the UK and finished collecting data, and high time I put pen to paper... fingers to keyboard... to write up the results. There's going to be quite a lot to look at here, so I've split it into three sections: my waste data output; my consumption data input; and how they relate to one another.

Waste Data Output

Let's start with my outputs. I collected data about my rubbish from 18th August 2019 through to 1st January 2023, nearly three and a half years. You can read all about the results from earlier years on my waste pages.

What of 2022? As with previous years there are peaks and troughs that go alongside my activities. There's a big spike around Christmas when Joanna visited and we had two whole people living in my flat (we don't see the same spike in 2021 because that year I spent Christmas with Joanna in the UK). There's a trough around August when Joanna and I went on holiday. Similar holiday troughs — at slightly different times of year — can be seen in 2020 and 2021.

 

It's hard to get an overall picture from this temporal view, so perhaps the overall averages for the different categories are more insightful. These are shown on the right hand side of the graph. It's also interesting to compare them against previous years. Here's the same information collated into a couple of graphs.

 

On the left hand side we can see the weight of waste output for each category. This is the average daily output for the stated year. As you can see, I worked quite hard to reduce my waste output year-on-year, cutting it by around half in 2020 and then by nearly a quarter again in 2021. That seems to have been my limit though: my 2022 level is just marginally higher than in 2021.

To understand what changed, it's helpful to look at the graphs in terms of proportions rather than absolute values. The right hand graph shows each of the outputs as a proportion of the total year's output. What we can see is that from 2019 to 2021 I greatly reduced my glass and metal output. Looking at both graphs, we can see that I also reduced my paper and compost output quite considerably, but not as an overall proportion.

In contrast, both the proportions and absolute values for 2021 and 2022 are very similar.

None of this is a huge surprise to me: I worked really hard to reduce my glass, metal and paper waste. I cut glass bottles and metal cans out of my shop almost entirely, switching them to plastic bottles, cardboard cartons and cardboard containers instead. You can read more about my reasoning for doing this in an earlier post. I cut down my paper waste output by putting a sing reading 'Ei mainoksia kiitos!' on my door (simple things) and by restructuring my magazine and postal subscriptions.

The following table gives the values for each of the categories in full. This is my average daily waste output measured in grammes.
 

Year	2019	2020	2021	2022
General	45.16	28.33	28.26	29.28
Plastic	6.65	11.27	9.52	9.97
Compost	94.84	43.51	31.11	27.85
Returnables	8.70	5.99	6.36	5.33
Metal	6.86	0.32	0.16	0.49
Glass	77.24	13.29	1.81	0.95
Card	35.27	27.44	20.93	23.89
Paper	64.82	24.83	21.73	25.18
Total	339.53	154.98	119.88	122.93

These values are rather small and hard to handle, so it can help to understand what these numbers mean on an annual basis. The following table shows the same values given in kilograms and multiplied up by a factor of 365.25. These represent the amount of waste for each category that I generated over the period of a year measured in kilogrammes.
 

Year	2019	2020	2021	2022
General	16.50	10.35	10.32	10.70
Plastic	2.43	4.12	3.48	3.64
Compost	34.64	15.89	11.36	10.17
Returnables	3.18	2.19	2.32	1.95
Metal	2.50	0.12	0.06	0.18
Glass	28.21	4.85	0.66	0.35
Card	12.88	10.02	7.64	8.73
Paper	23.67	9.07	7.94	9.20
Total	124.01	56.61	43.78	44.90

Consumption Data Input

Now let's look at my 2022 consumption data. The following graph shows what I bought in terms of weight. The categories were chosen by going through each item and selecting one of the existing categories if it fit, or creating a new one otherwise. The software I used for doing this is in the repository on GitHub.

 

It's interesting that there's so much variation through the year. Often this is driven by specific categories. I bought especially large quantities of soft drink in March, April and November, probably because of the weather. There are a few periods where my purchasing dropped to zero, because I was travelling away from home. Otherwise the cycle seems to be largely based on a three-week shopping period.

This is actually contrary to what I would have expected. I had thought my shopping cycle was roughly weekly, with smaller more frequent shopping trips for essentials (such as bread). But the graph tells me that in practice my shopping increased every third week or so. If I'd known this I might have organised things more intentionally.

Weight and costs are different things of course. The following graph shows the same purchases in terms of their cost in Euros, rather than their weight in grams. Although you can still see the same three-week shopping cycle, things do shift quite substantially. Drinks and 'other food' are costly (the former is also heavy, but the latter not). During the winter months 'other non-food' becomes a significant cost for me. That's probably Christmas presents.

 

Let's summaries all the results in terms of annual daily averages for the year. The following graph shows the details for all of the data I collected: number of items, weight of items and cost of items.

 

From this we can see that I'm buying over a kilogram of 'stuff' per day. That's more than I would have expected. The cost of all this stuff is averaging out to €12.20 per day. That's the cost of consumables it takes to run a human. That doesn't include rent, bills, transport, furniture: it's essentially just groceries. Again, that's more than I was expecting.

At this point we're already in a position to compare some of these inputs against outputs. For example, my overall daily input weight of 1171 g per day is getting converted into an output weight of 122.93 g per day. There's a big difference between the two, so where's all that extra weight going? Well, mostly down the toilet and sink I'd imagine.

In the next section we'll break all this down further and do a more careful comparison between inputs and outputs.

Garbage In, Garbage Out

It's interesting to consider how much waste I produce and how much it's all costing me. But by collecting this data, what I really hoped to discover was some connection between the two. The majority of things I throw away are at some time prior to that something I've bought.

In order to understand this relationship better the first step needed is to recategorise my consumption data to match those of my waste data. Given I catalogued exactly what I bought on each occasion, the underlying consumption data I've collected is far more detailed than the waste data I collected, so it makes sense to map the consumption data onto the waste data rather than vice versa.

Here's the graph showing my consumption graphed across the year, measured by weight and split across the eight waste categories. You'll notice that the total weight matches exactly with the graph above showing the data more finely categorised. However the individual strata that make up the total are quite different.

 

We can also render the cost graph using the same categories. Again, the total cost matches that of our earlier cost graph, but the individual strata that make it up are quite different. This is as we might expect.

 

Assigning a waste category to each of my purchases turns out to be quite challenging. Consider a box of tea. Should this be categorised as card for the box the tea comes in, or compost for the tea-leaves that are thrown away after brewing? My solution was to give each item only a single category, but to pick the one that disproportionately affects the waste that's thrown away. This involved some judgement calls that weren't always as clear cut as I'd have liked.

The following graph shows the annual summary for the data stratified into waste categories.

 

Comparing this against the waste summary graphs from earlier, there's obviously a big discrepancy between the weight of inputs and the weight of outputs: there's a roughly ten fold difference. But as we discussed earlier, this isn't unexpected. The proportions don't match up either: general waste makes up a larger proportion of my consumption input than it does my waste output, while the reverse is true for paper.

There are multiple reasons why this might be the case. Miscategorisation is one, but just as likely is that the weight ratios of inputs versus outputs aren't directly comparable. For example, a carton of orange juice is much heavier than a box of doughnuts, but they'll both end up generating a similar mass of cardboard waste. Once again, this highlights how much of an inexact process this all is.

Nevertheless it would be interesting to see if we can track inputs and see how long it takes for them to become outputs. If we can find this, it would provide an idea of how long it takes items within a given category to move from bought to binned. To estimate this we take each of the categories and compare the mean squared error of the consumption and waste data summed over time. We calculate the errors for different offsets between the waste data and the consumption data and compare them. The offset represents how long it takes for something to end up in the bin after purchase.

By minimising the mean square error over the offest we can find the offset that gives the best fit between the two graphs.

Given the ten-fold discrepancy between input weights and output weights, we normalise the data by scaling it so that both inputs and outputs sum to the same value across the year. The following figure shows the errors for each of the categories at different offsets. What we're interested in is the minimum point for each of the lines.

 

As you can see, in many of the cases the graph drops down to a single local minimum and then goes up again. This is an ideal situation as it gives us a clear candidate for generating the smallest error.

The remaining graphs at the end of this post show the normalised consumption and waste graphs for each of the categories, with the optimal offset applied.

As we can see, there's quite a range, and in some cases (paper, glass) the data is dominated by a few large purchases. In other cases we see a far noisier-looking graph for consumption as compared to waste. This is an artefact of my shopping patterns: while I recorded purchases throughout the week, I tended to only take waste readings fortnightly.

The table below lists the offsets that result in the smallest average mean square error for each of the categories.
 

Category	Min mean square error	Offset (days)
general	8.700 × 10-6	1
plastic	1.075 × 10-5	4
compost	9.964 × 10-6	0
returnables	1.729 × 10-5	1
metal	1.137 × 10-4	0
glass	4.296 × 10-5	9
card	1.483 × 10-5	10
paper	1.672 × 10-5	15
all	9.008 × 10-6	4

The error values don't tell us much since they can't be compared across categories (the values depend on the normalisation scaling which are different for each category). The offsets are the more interesting values. These range between zero days for metal and compost, and fifteen days for paper.

Given the small quantity that went through my household across the year (a total of 180 g), the result for metal isn't so suprising. The result for compost is less clear: there was a relatively consistent flow of compost throughout the year, which could explain the lack of offset. We can see both of these situations in the detailed graphs for metal and compost at the end of this post.

At the other end of the spectrum, paper has a turnaround rate of fourteen days, while glass and card have turnarounds of nine and ten days respectively. The remaining cases are less than a week.

If these are correct, they're interesting results. And they don't seem implausible. However in practice the data is so noisy, and I had to make so many assumptions while processing it, that I wouldn't put much stock in these results.

For all of my inputs and outputs combined the expected turnaround is four days. That's not implausible either, but again, I wouldn't give it much credence. To get a more accurate result, I'd had to have matched inputs with outputs exactly. I collected enough data on my consumption habits for this, but not on my waste-generating habits. I'd have needed to record each of the items in my bins and matched them to the items I bought previously. It's not implausible to imagine I could have done this, but sadly I didn't realise that these were data I'd really need for this analysis.

Summary

What can we conclude from all of this? The most actionable point I get from this is that my efforts to reduce my waste output by cutting out glass and metal, and cutting down on newspapers and magazines, were successful. This is a lesson I take forward.

My three week shopping cycle is also something I could potentially benefit from knowing. I should be planning my menus and performing one main shop every three weeks, with smaller top-ups from the local market in between.

Finally, matching consumed inputs with waste outputs turned out to be more challenging than I was expecting, to the extent that it's not clear how much I really achieved from recording everything I purchased in quite such detail.

Nevertheless I feel it was a worthwhile experience: I definitely gained something intangible from the process that isn't reflected in the analysis of the data. I'll continue to estimate my CO₂ output and try to reduce the amount of waste I generate on a daily basis. This is the real win: I'm much more aware of what I buy and throw away, and for me, reducing this waste is a crucial aspect of limiting my negative impact on the wider environment.

 

It's reassuring to see how seriously global heating is being taken nowadays. There's been a notable shift from individuals being the sole drivers of change, to organisations and governments taking more of a lead. For my own part, I've been trying to keep track of my environmental impact for a number of years now, including offsetting my carbon footprint. Many will rightly say that it's more important to reduce carbon emissions than offset them, and I agree with that, but as long as it doesn't lead to complacency in achieving the former, I'm certain there's still value in doing the latter.

With that in mind, I've spent the last couple of weekends calculating my carbon footprint for 2022. The act of doing this has in itself been a useful exercise, helping highlight where I've been succeeding, and where I've been failing. But the final objective is to allow me to offset my carbon output, which as last year, I've done by contributing to the Ripple Africa initiative providing lower carbon cooking stoves in Malawi.

Here are the results for 2022, with comparison to earlier years and compiled once again using Carbon Footprint Ltd's carbon calculator. These results are for both Joanna and me, so I consider them to be outputs equivalent to a two-person household (even though we were actually living in different places throughout 2022).
 

Source	CO2 output 2019 (t)	CO2 output 2020 (t)	CO2 output 2021 (t)	CO2 output 2022 (t)
Electricity	0.50	0.40	0.59	1.14
Natural gas	1.18	1.26	1.66	0.81
Flights	5.76	2.26	1.90	5.34
Car	1.45	0.39	0.39	1.01
Bus	0.00	0.01	0.02	0.01
National rail	0.08	0.01	0.02	0.00
International rail	0.02	0.01	0.00	0.04
Taxi	0.01	0.01	0.01	0.01
Food and drink	1.69	1.11	1.05	1.35
Pharmaceuticals	0.26	0.32	0.31	0.06
Clothing	0.03	0.06	0.06	0.12
Paper-based products	0.34	0.15	0.14	0.37
Computer usage	1.30	1.48	0.75	0.93
Electrical	0.12	0.29	0.19	0.03
Non-fuel car	0.00	0.10	0.00	0.12
Manufactured goods	0.50	0.03	0.03	0.05
Hotels, restaurants	0.51	0.16	0.15	0.10
Telecoms	0.15	0.05	0.04	0.03
Finance	0.24	0.24	0.22	0.04
Insurance	0.19	0.11	0.10	0.04
Education	0.05	0.00	0.04	0.01
Recreation	0.09	0.06	0.05	0.03
Total	14.47	8.50	7.73	11.65

The first thing to note is that there's been abig increase compared to my carbon output in 2021 and 2022. The main contributor to this has been carbon emissions due to flying, and the factor with the biggest impact on this has been the pandemic. For all of the years shown here I was living in Tampere, Finland while Joanna was living in Cambridge, UK. Travelling between the two by train (and boat) takes a full four days, compared to a day's travel by plane (and car/train). During the pandemic our ability to travel was naturally curtailed. It's worth looking into the associated numbers here in more detail.
 

Source	Details for 2019	Details for 2020	Details for 2021	Details for 2022
Electricity	1 794 kWh	1 427 kWh	3 009 kWh	4 101 kWh
Natural gas	6 433 kWh	6 869 kWh	9 089 kWh	4 439 kWh
Flights	36 580 km (20 flights)	14 632 km (8 flights)	25 542 km (14 flights)	36 042 km (20 flights)
Car	11 910 km	2 000 km	3 219 km	8 458 km
Bus	1 930 km	40 km	168 km	133 km
National rail	5 630 km	400 km	676 km	0 km
International rail	64 km	1 368 km	513 km	8 684 km
Taxi	64 km	37 km	100 km	100 km

I moved back to the UK at the start of 2023 and now that Joanna and I are living together again, I'd expect our plane travel to reduce to just a handful of trips a year (our aim has to be zero).

My flat in Tampere was incredibly well insulated, but nevertheless still required heating and lighting. Now that I'm back in the UK and no longer renting a flat in Tampere, our overall heating requirements should reduce in 2023. It's also worth noting that our natural gas usage decreased in 2022, while our electricity usage increased. This will be due to the fact we installed a heat pump in February of 2022, so that our heating is now fully renewable rather than gas. For 2023 the balance should shift further.

Our car usage increased again back to something closer to pre-pandemic levels. This is due to Joanna travelling to work again (I had no access to a car in Finland). Our International Rail travel also increased due to two factors: partly because I'm now including all long-distance rail under the category, and partly because we travelled by Eurostar on a couple of occasions.

From the numbers it's clear Joanna and I travelled our longest distances by plane, but the numbers also highlight another important consideration. Each kilometre travelled by plane resulted in 148 g of CO₂ (this includes a radiative forcing factor of 1.891), compared to 119 g for car travel and 75 g for bus travel. But according to these numbers train travel generated only 5 g of CO₂ per kilometre. That's a huge differential.

Looking at the overall emissions compared to last year I was initially dispirited, but after more careful consideration I'm actually quite encouraged. Joanna and I reduced our carbon output considerably since 2019, which is a fairer point of comparison given the effects of the pandemic in 2020 and 2021. Our move from gas to heat-pump heating is shown positively in the numbers and will have an even bigger impact in 2023 when it covers the whole year. With me moving back to the UK we will be servicing only one household rather than two, and our reliance on flying will decrease, addressing the single largest contributor to our carbon footprint.

For comparison the average carbon footprint in the European Union is 6.8 tonnes, while world wide it's 4.79 tonnes. Split between Joanna and me, our individual footprints average out at 5.825 tonnes. That's clearly too high, but hopefully things are looking more promising for 2023.

In the meantime, I've once again used the UN Framework Convention on Climate Change to offset our emissions for 2022.
 
 

I've posted up my final waste data dump of 2022 to the waste page. This means I now have a full year's worth of data for 2022 and over three full years of data in total. That's the good news. The rather sad news is that an uptick in my waste output in the last two weeks has pushed my 2022 average to 122.93 g/day, which is slightly more than my 2021 average of 119.88 g/day. I really thought I would make it under. That's Christmas for you. Back in January last year I pledged to "keep my average waste down to below 200 g per day on average". I'm happy I achieved this, but secretly wanted to get my output lower than 2021 as well. Never mind! I'll be writing up a full analysis of my waste output as part of my annual environmental audit in the coming days.

My latest waste data is up on my waste page. I've manged to keep my waste down over the last three weeks, with a daily average of 68.64 g/day. That's pretty low for me, apparently due to lower general, plastic and card, although I'm not actually sure how I achieved that in practice. The result is that my daily average for 2022 is now 114.14 g/day, below my 2023 average of 119.88 g/day. Whether I'll be be able to keep it below over the next fortnight remains to be seen. Christmas, moving flat, Joanna staying (two people rather than one) are all going to add up, so I doubt it. But let's see.

My latest waste data dump is up on my waste page. Usually I do this every fortnight, but because I spent a week in the UK, and have been trying to be super-frugal since I got back, it's been a gap of a month this time. My time away skews the average to 72.34 g/day, which is very low (my average for 2022 so far is 117.18 g/day). But even after adjusting upwards to account for my time away, it's still only 96.45 g/day, which is a good outcome. This is the first time my 2022 average has dropped below my 2021 average, which is one of my goals for the year. Now I just need to try to keep this up over Christmas (which will be impossible, but I can at least try).

My latest waste data is on the waste page. Only a week between readings this time, but the values look okay this time. My daily average is 60.00 g/day, which is good, with everything down except for paper. It was an unusul week, so this will likely to a one-off. My overall average for 2022 is now 121.50 g/day, just slightly higher than my 2021 average of 119.88 g/day.

My latest waste data is up on the waste page. The numbers are surprisingly bad this time; I'm not exactly sure why. I had a bad cold, which resulted in lots more tissues getting thrown away. And I had to dump some newspapers that had been building up. But that doesn't explain the spike in plastic, compost and card. I'm a bit baffled, if I'm honest. Nevertheless, the result is that my average over the last fortnight was 211.08 g/day, well over my average for the year of 123.17 g/day. So I must try harder next fortnight.